From ca3aae7f75cd7c92a2bde4f80c088e864c1f038a Mon Sep 17 00:00:00 2001 From: Brian Joseph Petro Date: Wed, 18 Sep 2024 10:10:29 -0400 Subject: [PATCH] re-org dirs for next gen modules --- package-lock.json | 1028 ++---- .../MIT_LICENSE | 0 smart-chat-model-v1/README.md | 166 + .../adapters.js | 0 smart-chat-model-v1/adapters/anthropic.js | 158 + .../adapters/anthropic.test.js | 336 ++ smart-chat-model-v1/adapters/cohere.js | 95 + smart-chat-model-v1/adapters/cohere.test.js | 63 + .../adapters/gemini.js | 0 .../adapters/gemini.test.js | 0 smart-chat-model-v1/adapters/open_router.js | 39 + .../dist/smart_chat_model_web.js | 0 .../models.old.json | 0 .../models/anthropic.js | 0 .../models/cohere.js | 0 .../models/fetch.js | 0 .../models/google_gemini.js | 0 .../models/open_router.js | 0 .../models/openai.js | 0 .../package.json | 8 +- .../platforms.json | 46 +- smart-chat-model-v1/smart_chat_model.js | 466 +++ .../streamer.js | 6 +- .../utils/is_valid_tool_call.js | 0 .../utils/is_valid_tool_call.test.js | 0 .../web-build.js | 0 smart-chat-model-v2/README.md | 3 - smart-chat-model-v2/adapters/anthropic.js | 205 -- .../adapters/anthropic.test.js | 195 - smart-chat-model-v2/adapters/cohere.js | 196 - smart-chat-model-v2/adapters/cohere.test.js | 235 -- smart-chat-model-v2/adapters/open_router.js | 41 - smart-chat-model-v2/smart_chat_model.js | 125 - smart-chat-model/README.md | 165 +- .../adapters/_adapter.js | 0 .../adapters/_api.js | 0 .../adapters/_api.test.js | 0 smart-chat-model/adapters/anthropic.js | 335 +- smart-chat-model/adapters/anthropic.test.js | 469 +-- smart-chat-model/adapters/cohere.js | 277 +- smart-chat-model/adapters/cohere.test.js | 276 +- .../adapters/google.js | 0 .../adapters/google.test.js | 0 smart-chat-model/adapters/open_router.js | 70 +- .../adapters/open_router.test.js | 0 .../adapters/openai.js | 0 .../adapters/openai.test.js | 0 .../index.js | 0 .../package-lock.json | 0 smart-chat-model/package.json | 8 +- smart-chat-model/platforms.json | 46 +- .../schemas/anthropic_request.json | 0 .../schemas/anthropic_response.json | 0 .../schemas/cohere_request.json | 0 .../schemas/cohere_response.json | 0 .../schemas/google_request.json | 0 .../schemas/google_response.json | 0 .../schemas/open_router_request.json | 0 .../schemas/open_router_response.json | 0 .../schemas/openai_request.json | 0 .../schemas/openai_response.json | 0 smart-chat-model/smart_chat_model.js | 579 +-- smart-chat-model/streamer.js | 6 +- {smart-chats => smart-chats-v1}/MIT_LICENSE | 0 smart-chats-v1/README.md | 32 + {smart-chats => smart-chats-v1}/adapters.js | 0 .../adapters/canvas.js | 0 .../adapters/markdown.js | 0 .../package-lock.json | 177 +- .../package.json | 38 +- {smart-chats => smart-chats-v1}/smart_chat.js | 0 .../smart_chat_env.js | 0 .../smart_chat_md.js | 0 .../smart_chats.js | 0 .../smart_chats_ui.js | 0 {smart-chats => smart-chats-v1}/test/_env.js | 0 .../utils/add_content_to_message.js | 0 .../utils/add_content_to_message.test.js | 0 .../utils/canvas_to_chatml.js | 0 .../utils/canvas_to_chatml.test.js | 0 .../utils/chat_ml_to_markdown.js | 0 .../utils/chat_ml_to_markdown.test.js | 0 .../utils/chatml_to_canvas.js | 0 .../utils/chatml_to_canvas.test.js | 0 .../utils/markdown_to_chat_ml.js | 0 .../utils/markdown_to_chat_ml.test.js | 0 .../message_content_array_to_markdown.js | 0 smart-chats-v2/README.md | 5 - smart-chats/README.md | 35 +- .../adapters/_adapter.js | 0 .../adapters/openai_json.js | 0 .../components/_component.js | 0 .../components/message.js | 0 .../components/modal.js | 0 .../components/settings.js | 0 .../components/thread.js | 0 .../components/turn.js | 0 {smart-chats-v2 => smart-chats}/index.js | 0 smart-chats/package-lock.json | 177 +- smart-chats/package.json | 38 +- .../smart_threads.js | 0 smart-embed-model-v1/MIT_LICENSE | 20 + smart-embed-model-v1/README.md | 51 + smart-embed-model-v1/adapters.js | 11 + smart-embed-model-v1/adapters/_adapter.js | 9 + smart-embed-model-v1/adapters/iframe.js | 104 + smart-embed-model-v1/adapters/openai.js | 171 + smart-embed-model-v1/adapters/transformers.js | 78 + .../adapters/transformers_iframe.js | 18 + .../adapters/transformers_worker.js | 16 + smart-embed-model-v1/adapters/worker.js | 91 + smart-embed-model-v1/build/esbuild.js | 59 + .../build/transformers_iframe_script.js | 48 + .../build/transformers_worker_script.js | 64 + smart-embed-model-v1/cl100k_base.json | 1 + .../connectors/transformers_iframe.js | 1 + .../connectors/transformers_worker.js | 350 ++ smart-embed-model-v1/models.json | 115 + smart-embed-model-v1/package-lock.json | 3169 +++++++++++++++++ smart-embed-model-v1/package.json | 38 + smart-embed-model-v1/smart_embed_model.js | 142 + smart-embed-model-v1/test/_env.js | 33 + smart-embed-model-v1/test/openai.test.js | 64 + .../test/transformers.test.js | 34 + smart-entities/package.json | 2 +- smart-environment/package-lock.json | 19 +- smart-environment/package.json | 2 +- smart-templates/package-lock.json | 33 +- smart-templates/package.json | 2 +- 129 files changed, 7533 insertions(+), 3356 deletions(-) rename {smart-chat-model-v2 => smart-chat-model-v1}/MIT_LICENSE (100%) create mode 100644 smart-chat-model-v1/README.md rename {smart-chat-model => smart-chat-model-v1}/adapters.js (100%) create mode 100644 smart-chat-model-v1/adapters/anthropic.js create mode 100644 smart-chat-model-v1/adapters/anthropic.test.js create mode 100644 smart-chat-model-v1/adapters/cohere.js create mode 100644 smart-chat-model-v1/adapters/cohere.test.js rename {smart-chat-model => smart-chat-model-v1}/adapters/gemini.js (100%) rename {smart-chat-model => smart-chat-model-v1}/adapters/gemini.test.js (100%) create mode 100644 smart-chat-model-v1/adapters/open_router.js rename {smart-chat-model-v2 => smart-chat-model-v1}/dist/smart_chat_model_web.js (100%) rename {smart-chat-model => smart-chat-model-v1}/models.old.json (100%) rename {smart-chat-model => smart-chat-model-v1}/models/anthropic.js (100%) rename {smart-chat-model => smart-chat-model-v1}/models/cohere.js (100%) rename {smart-chat-model => smart-chat-model-v1}/models/fetch.js (100%) rename {smart-chat-model => smart-chat-model-v1}/models/google_gemini.js (100%) rename {smart-chat-model => smart-chat-model-v1}/models/open_router.js (100%) rename {smart-chat-model => smart-chat-model-v1}/models/openai.js (100%) rename {smart-chat-model-v2 => smart-chat-model-v1}/package.json (78%) rename {smart-chat-model-v2 => smart-chat-model-v1}/platforms.json (59%) create mode 100644 smart-chat-model-v1/smart_chat_model.js rename {smart-chat-model-v2 => smart-chat-model-v1}/streamer.js (98%) rename {smart-chat-model-v2 => smart-chat-model-v1}/utils/is_valid_tool_call.js (100%) rename {smart-chat-model-v2 => smart-chat-model-v1}/utils/is_valid_tool_call.test.js (100%) rename {smart-chat-model => smart-chat-model-v1}/web-build.js (100%) delete mode 100644 smart-chat-model-v2/README.md delete mode 100644 smart-chat-model-v2/adapters/anthropic.js delete mode 100644 smart-chat-model-v2/adapters/anthropic.test.js delete mode 100644 smart-chat-model-v2/adapters/cohere.js delete mode 100644 smart-chat-model-v2/adapters/cohere.test.js delete mode 100644 smart-chat-model-v2/adapters/open_router.js delete mode 100644 smart-chat-model-v2/smart_chat_model.js rename {smart-chat-model-v2 => smart-chat-model}/adapters/_adapter.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/_api.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/_api.test.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/google.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/google.test.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/open_router.test.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/openai.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/adapters/openai.test.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/index.js (100%) rename {smart-chat-model-v2 => smart-chat-model}/package-lock.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/anthropic_request.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/anthropic_response.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/cohere_request.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/cohere_response.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/google_request.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/google_response.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/open_router_request.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/open_router_response.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/openai_request.json (100%) rename {smart-chat-model-v2 => smart-chat-model}/schemas/openai_response.json (100%) rename {smart-chats => smart-chats-v1}/MIT_LICENSE (100%) create mode 100644 smart-chats-v1/README.md rename {smart-chats => smart-chats-v1}/adapters.js (100%) rename {smart-chats => smart-chats-v1}/adapters/canvas.js (100%) rename {smart-chats => smart-chats-v1}/adapters/markdown.js (100%) rename {smart-chats-v2 => smart-chats-v1}/package-lock.json (94%) rename {smart-chats-v2 => smart-chats-v1}/package.json (57%) rename {smart-chats => smart-chats-v1}/smart_chat.js (100%) rename {smart-chats => smart-chats-v1}/smart_chat_env.js (100%) rename {smart-chats => smart-chats-v1}/smart_chat_md.js (100%) rename {smart-chats => smart-chats-v1}/smart_chats.js (100%) rename {smart-chats => smart-chats-v1}/smart_chats_ui.js (100%) rename {smart-chats => smart-chats-v1}/test/_env.js (100%) rename {smart-chats => smart-chats-v1}/utils/add_content_to_message.js (100%) rename {smart-chats => smart-chats-v1}/utils/add_content_to_message.test.js (100%) rename {smart-chats => smart-chats-v1}/utils/canvas_to_chatml.js (100%) rename {smart-chats => smart-chats-v1}/utils/canvas_to_chatml.test.js (100%) rename {smart-chats => smart-chats-v1}/utils/chat_ml_to_markdown.js (100%) rename {smart-chats => smart-chats-v1}/utils/chat_ml_to_markdown.test.js (100%) rename {smart-chats => smart-chats-v1}/utils/chatml_to_canvas.js (100%) rename {smart-chats => smart-chats-v1}/utils/chatml_to_canvas.test.js (100%) rename {smart-chats => smart-chats-v1}/utils/markdown_to_chat_ml.js (100%) rename {smart-chats => smart-chats-v1}/utils/markdown_to_chat_ml.test.js (100%) rename {smart-chats => smart-chats-v1}/utils/message_content_array_to_markdown.js (100%) delete mode 100644 smart-chats-v2/README.md rename {smart-chats-v2 => smart-chats}/adapters/_adapter.js (100%) rename {smart-chats-v2 => smart-chats}/adapters/openai_json.js (100%) rename {smart-chats-v2 => smart-chats}/components/_component.js (100%) rename {smart-chats-v2 => smart-chats}/components/message.js (100%) rename {smart-chats-v2 => smart-chats}/components/modal.js (100%) rename {smart-chats-v2 => smart-chats}/components/settings.js (100%) rename {smart-chats-v2 => smart-chats}/components/thread.js (100%) rename {smart-chats-v2 => smart-chats}/components/turn.js (100%) rename {smart-chats-v2 => smart-chats}/index.js (100%) rename {smart-chats-v2 => smart-chats}/smart_threads.js (100%) create mode 100644 smart-embed-model-v1/MIT_LICENSE create mode 100644 smart-embed-model-v1/README.md create mode 100644 smart-embed-model-v1/adapters.js create mode 100644 smart-embed-model-v1/adapters/_adapter.js create mode 100644 smart-embed-model-v1/adapters/iframe.js create mode 100644 smart-embed-model-v1/adapters/openai.js create mode 100644 smart-embed-model-v1/adapters/transformers.js create mode 100644 smart-embed-model-v1/adapters/transformers_iframe.js create mode 100644 smart-embed-model-v1/adapters/transformers_worker.js create mode 100644 smart-embed-model-v1/adapters/worker.js create mode 100644 smart-embed-model-v1/build/esbuild.js create mode 100644 smart-embed-model-v1/build/transformers_iframe_script.js create mode 100644 smart-embed-model-v1/build/transformers_worker_script.js create mode 100644 smart-embed-model-v1/cl100k_base.json create mode 100644 smart-embed-model-v1/connectors/transformers_iframe.js create mode 100644 smart-embed-model-v1/connectors/transformers_worker.js create mode 100644 smart-embed-model-v1/models.json create mode 100644 smart-embed-model-v1/package-lock.json create mode 100644 smart-embed-model-v1/package.json create mode 100644 smart-embed-model-v1/smart_embed_model.js create mode 100644 smart-embed-model-v1/test/_env.js create mode 100644 smart-embed-model-v1/test/openai.test.js create mode 100644 smart-embed-model-v1/test/transformers.test.js diff --git a/package-lock.json b/package-lock.json index 89f471a8..30dee62d 100644 --- a/package-lock.json +++ b/package-lock.json @@ -23,17 +23,13 @@ }, "../smart-entities-actions": { "version": "2.0.0", + "extraneous": true, "license": "ISC", "dependencies": { - "smart-actions": "file:../smart-actions", - "smart-connect-core": "file:../smart-connect-core", - "smart-connect-notes-v1": "file:../smart-connect-notes-v1", - "smart-templates": "file:../jsbrains/smart-templates", - "smart-workflows": "file:../smart-workflows" + "smart-actions": "file:../smart-actions" }, "devDependencies": { - "ava": "^5.0.0", - "sinon": "^18.0.0" + "ava": "^5.0.0" } }, "node_modules/@babel/parser": { @@ -336,6 +332,22 @@ "node": ">=12" } }, + "node_modules/@esbuild/openbsd-arm64": { + "version": "0.23.1", + "resolved": "https://registry.npmjs.org/@esbuild/openbsd-arm64/-/openbsd-arm64-0.23.1.tgz", + "integrity": "sha512-3x37szhLexNA4bXhLrCC/LImN/YtWis6WXr1VESlfVtVeoFJBRINPJ3f0a/6LV8zpikqoUg4hyXw0sFBt5Cr+Q==", + "cpu": [ + "arm64" + ], + "dev": true, + "optional": true, + "os": [ + "openbsd" + ], + "engines": { + "node": ">=18" + } + }, "node_modules/@esbuild/openbsd-x64": { "version": "0.20.2", "resolved": "https://registry.npmjs.org/@esbuild/openbsd-x64/-/openbsd-x64-0.20.2.tgz", @@ -416,14 +428,6 @@ "node": ">=12" } }, - "node_modules/@huggingface/jinja": { - "version": "0.2.2", - "resolved": "https://registry.npmjs.org/@huggingface/jinja/-/jinja-0.2.2.tgz", - "integrity": "sha512-/KPde26khDUIPkTGU82jdtTW9UAuvUTumCAbFs/7giR0SxsvZC4hru51PBvpijH6BVkHcROcvZM/lpy5h1jRRA==", - "engines": { - "node": ">=18" - } - }, "node_modules/@jsdoc/salty": { "version": "0.2.8", "resolved": "https://registry.npmjs.org/@jsdoc/salty/-/salty-0.2.8.tgz", @@ -491,60 +495,6 @@ "node": ">= 8" } }, - "node_modules/@protobufjs/aspromise": { - "version": "1.1.2", - "resolved": "https://registry.npmjs.org/@protobufjs/aspromise/-/aspromise-1.1.2.tgz", - "integrity": "sha512-j+gKExEuLmKwvz3OgROXtrJ2UG2x8Ch2YZUxahh+s1F2HZ+wAceUNLkvy6zKCPVRkU++ZWQrdxsUeQXmcg4uoQ==" - }, - "node_modules/@protobufjs/base64": { - "version": "1.1.2", - "resolved": 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"@esbuild/win32-ia32": "0.23.1", + "@esbuild/win32-x64": "0.23.1" } }, "smart-entities": { @@ -5110,8 +4542,7 @@ "license": "MIT", "dependencies": { "smart-collections": "file:../smart-collections", - "smart-embed-model": "file:../smart-embed-model", - "smart-entities-actions": "file:../../smart-entities-actions" + "smart-embed-model": "file:../smart-embed-model-v1" }, "devDependencies": { "ava": "^6.0.1" @@ -5120,9 +4551,9 @@ "smart-entities-actions": { "extraneous": true }, - "smart-entities/node_modules/smart-entities-actions": { - "resolved": "../smart-entities-actions", - "link": true + "smart-http-request": { + "version": "1.0.0", + "license": "MIT" }, "smart-instruct-model": { "version": "1.0.3", @@ -5132,8 +4563,13 @@ "esbuild": "^0.20.2" } }, + "smart-model": { + "version": "1.0.0", + "license": "MIT" + }, "smart-ranker-model": { "version": "1.0.0", + "extraneous": true, "license": "MIT", "dependencies": { "@xenova/transformers": "latest" @@ -5142,6 +4578,16 @@ "ava": "^6.0.1", "dotenv": "^16.3.1" } + }, + "smart-sources": { + "version": "2.0.0", + "license": "MIT", + "dependencies": { + "smart-entities": "file:../smart-entities" + }, + "devDependencies": { + "ava": "^6.0.1" + } } } } diff --git a/smart-chat-model-v2/MIT_LICENSE b/smart-chat-model-v1/MIT_LICENSE similarity index 100% rename from smart-chat-model-v2/MIT_LICENSE rename to smart-chat-model-v1/MIT_LICENSE diff --git a/smart-chat-model-v1/README.md b/smart-chat-model-v1/README.md new file mode 100644 index 00000000..e4076c54 --- /dev/null +++ b/smart-chat-model-v1/README.md @@ -0,0 +1,166 @@ +# Smart Chat Model +Used to integrate OpenAI GPT-4, Antrhopic Claude, Google Gemini & Cohere Command-r in [Smart Connections](https://github.com/brianpetro/obsidian-smart-connections). + +Try the [demo](https://brianpetro.github.io/jsbrains/sample-web) or browse the [demo code here](https://github.com/brianpetro/jsbrains/tree/main/assets/sample-web.html). + +[![Smart Chat Model Demo](https://brianpetro.github.io/jsbrains/sample-web.gif)](https://brianpetro.github.io/jsbrains/sample-web) + +## SmartChatModel Usage Guide +```bash +npm install smart-chat-model +``` + +`SmartChatModel` is a comprehensive class designed to facilitate interactions with chat models, supporting features like streaming responses, handling tool calls, and customizing requests through adapters. It's built to be adaptable for various chat model configurations and platforms. +The SmartChatModel class provides a flexible and powerful way to interact with chat models, supporting advanced features like streaming, tool calls, and request customization. By following this guide, you should be able to integrate and use SmartChatModel effectively in your projects. + +### Initialization +To initialize a SmartChatModel instance, you need to provide the main environment object, a model key to select the configuration from chat_models.json, and optional user-defined options to override the default model configuration. + +```js +const { SmartChatModel } = require('./chat.js'); + +const mainEnv = {}; // Your main environment object + +const modelKey = 'your_model_key'; // Key from chat_models.json + +const options = {}; // Optional overrides + +const chatModel = new SmartChatModel(mainEnv, modelKey, options); +``` + +### Making Requests +To make a request to the chat model, use the complete method. This method allows for customization of the request through options and can handle both streaming and non-streaming responses. + +```js +const requestOptions = { + +  messages: [{ role: "user", content: "Hello" }], + +  temperature: 0.3, + +  max_tokens: 100, + +  stream: false, // Set to true for streaming responses + +}; + +chatModel.complete(requestOptions) + +  .then(response => { + +    console.log("Response:", response); + +  }) + +  .catch(error => { + +    console.error("Error:", error); + +  }); +``` + + +### Streaming Responses +If the chat model supports streaming and it's enabled in the configuration, you can set stream: true in the request options to receive streaming responses. The SmartChatModel will handle the streaming logic internally, including starting and stopping the stream as needed. + +### Handling Tool Calls +The SmartChatModel can automatically detect and handle tool calls within responses. It uses the configured adapters to interpret the tool call data and executes the corresponding tool handler if a valid tool call is detected. + +### Customization with Adapters +Adapters allow for customization of request and response handling. If your use case requires specific handling logic, you can create a custom adapter and specify it in the model configuration. The SmartChatModel will use this adapter for preparing requests, parsing responses, and handling tool calls. + +### Counting Tokens +The count_tokens and estimate_tokens methods are available for estimating the number of tokens in a given input. This can be useful for managing request sizes and understanding the complexity of inputs. + +```js +const input = "Hello, world!"; + +chatModel.count_tokens(input) + +  .then(tokenCount => { + +    console.log("Token count:", tokenCount); + +  }); +``` + +### Testing API Key +The test_api_key method allows you to verify if the provided API key is valid by making a test request to the chat model. + +```js +chatModel.test_api_key() + +  .then(isValid => { + +    console.log("API key valid:", isValid); + +  }); +``` + + + + +## Adapter Pattern for Platform Compatibility +The `SmartChatModel` class is designed to be extensible and compatible with various chat platforms. This is achieved through the use of the adapter pattern, which abstracts platform-specific logic into separate adapter classes. Each adapter implements a consistent interface that `SmartChatModel` can interact with, regardless of the underlying platform differences. + +### Purpose +The adapter pattern allows for the easy integration of new platforms by encapsulating the API-specific logic within adapters. This ensures that the core logic of `SmartChatModel` remains clean and focused, while still being able to support a wide range of platforms. + +### Key Adapter Methods +Adapters must implement the following methods to be compatible with SmartChatModel: + +##### Converting options into the platform-specific request format +- `prepare_request_body(opts)`: + +##### Extracting the message content from the platform's response. +- `get_message(resp_json)` +- `get_message_content(resp_json)` + +##### Methods for extracting and handling tool call information from the response. +- `get_tool_call(resp_json)` +- `get_tool_name(tool_call)` +- `get_tool_call_content(tool_call)` + +##### Handling streaming responses. +- `get_text_chunk_from_stream(event)` +- `is_end_of_stream(event)`:  + +##### Providing token counting for input validation or estimation. +- `async count_tokens(input)`  +- `estimate_tokens(input)` + +### Implementing a New Adapter +To add support for a new platform, follow these steps: +##### Create Adapter Class +1. Create a new file in the adapters directory for the platform, e.g., `new_platform.js`.  +2. Define a class `NewPlatformAdapter` that implements the required methods. + +```js +class NewPlatformAdapter { + prepare_request_body(opts) { /* Implementation */ } + get_message_content(json) { /* Implementation */ } + // Implement other required methods... +} + +exports.NewPlatformAdapter = NewPlatformAdapter; +``` +##### Integrate Adapter +1. Add the new adapter to `adapters.js` which exports all of the adapters. +2. Ensure `SmartChatModel` initializes it based on the `config.adapter`. + +### Using Adapters in SmartChatModel +`SmartChatModel` interacts with adapters by checking for the implementation of specific methods and calling them. This allows for flexible handling of different platform behaviors without modifying the core logic. + +For example, to prepare the request body: + +```js +req.body = JSON.stringify(this.adapter?.prepare_request_body ? this.adapter.prepare_request_body(body) : body); +``` + +And to handle streaming responses: + +```js +let text_chunk = this.adapter?.get_text_chunk_from_stream ? this.adapter.get_text_chunk_from_stream(event) : defaultTextChunkHandling(event); +``` + +This pattern ensures that `SmartChatModel` remains adaptable and can easily extend support to new platforms by adding corresponding adapters. \ No newline at end of file diff --git a/smart-chat-model/adapters.js b/smart-chat-model-v1/adapters.js similarity index 100% rename from smart-chat-model/adapters.js rename to smart-chat-model-v1/adapters.js diff --git a/smart-chat-model-v1/adapters/anthropic.js b/smart-chat-model-v1/adapters/anthropic.js new file mode 100644 index 00000000..a0b201e6 --- /dev/null +++ b/smart-chat-model-v1/adapters/anthropic.js @@ -0,0 +1,158 @@ +/** + * AnthropicAdapter class provides methods to adapt the chat model interactions specifically for the Anthropic model. + * It includes methods to prepare request bodies, count and estimate tokens, and handle tool calls and messages. + */ +class AnthropicAdapter { + /** + * Prepares the request body for the Anthropic API by converting ChatML format to a format compatible with Anthropic. + * @param {Object} opts - The options object containing messages and other parameters in ChatML format. + * @returns {Object} The request body formatted for the Anthropic API. + */ + prepare_request_body(opts) { return chatml_to_anthropic(opts); } + /** + * Counts the tokens in the input by estimating them, as the Anthropic model does not provide a direct method. + * @param {string|Object} input - The input text or object to count tokens in. + * @returns {Promise} The estimated number of tokens in the input. + */ + async count_tokens(input) { + // Currently, the Anthropic model does not provide a way to count tokens + return this.estimate_tokens(input); + } + /** + * Estimates the number of tokens in the input based on a rough average token size. + * @param {string|Object} input - The input text or object to estimate tokens in. + * @returns {number} The estimated number of tokens. + */ + estimate_tokens(input){ + if(typeof input === 'object') input = JSON.stringify(input); + // Note: The division by 6 is a rough estimate based on observed average token size. + return Math.ceil(input.length / 6); // Use Math.ceil for a more accurate count + } + /** + * Extracts the first tool call from the JSON response content. + * @param {Object} json - The JSON response from which to extract the tool call. + * @returns {Object|null} The first tool call found, or null if none exist. + */ + get_tool_call(json){ + return json.content.find(msg => msg.type === 'tool_use'); + } + /** + * Retrieves the input content of a tool call. + * @param {Object} tool_call - The tool call object from which to extract the input. + * @returns {Object} The input of the tool call. + */ + get_tool_call_content(tool_call){ + return tool_call.input; + } + /** + * Retrieves the name of the tool from a tool call object. + * @param {Object} tool_call - The tool call object from which to extract the name. + * @returns {string} The name of the tool. + */ + get_tool_name(tool_call){ + return tool_call.name; + } + /** + * Extracts the first message from the JSON response content. + * @param {Object} json - The JSON response from which to extract the message. + * @returns {Object|null} The first message found, or null if none exist. + */ + get_message(json){ return json.content?.[0]; } + /** + * Retrieves the content of the first message from the JSON response. + * @param {Object} json - The JSON response from which to extract the message content. + * @returns {string|null} The content of the first message, or null if no message is found. + */ + get_message_content(json) { return this.get_message(json)?.[this.get_message(json)?.type]; } +} +exports.AnthropicAdapter = AnthropicAdapter; +// https://docs.anthropic.com/claude/reference/messages_post +/** + * Convert a ChatML object to an Anthropic object + * @param {Object} opts - The ChatML object + * @description This function converts a ChatML object to an Anthropic object. It filters out system messages and adds a system message prior to the last user message. + * @returns {Object} - The Anthropic object + */ +function chatml_to_anthropic(opts) { + let tool_counter = 0; + const messages = opts.messages + .filter(msg => msg.role !== 'system') + .map(m => { + if(m.role === 'tool'){ + return { role: 'user', content: [ + { + type: 'tool_result', + tool_use_id: `tool-${tool_counter}`, + content: m.content + } + ]}; + } + if(m.role === 'assistant' && m.tool_calls){ + tool_counter++; + const out = { + role: m.role, + content: m.tool_calls.map(c => ({ + type: 'tool_use', + id: `tool-${tool_counter}`, + name: c.function.name, + input: (typeof c.function.arguments === 'string') ? JSON.parse(c.function.arguments) : c.function.arguments + })) + }; + if(m.content){ + if(typeof m.content === 'string') out.content.push({type: 'text', text: m.content}); + else m.content.forEach(c => out.content.push(c)); + } + return out; + } + if(typeof m.content === 'string') return { role: m.role, content: m.content }; + if(Array.isArray(m.content)){ + const content = m.content.map(c => { + if(c.type === 'text') return {type: 'text', text: c.text}; + if(c.type === 'image_url'){ + const image_url = c.image_url.url; + let media_type = image_url.split(":")[1].split(";")[0]; + if(media_type === 'image/jpg') media_type = 'image/jpeg'; + return {type: 'image', source: {type: 'base64', media_type: media_type, data: image_url.split(",")[1]}}; + } + }); + return { role: m.role, content }; + } + return m; + }) + ; + const { model, max_tokens, temperature, tools, tool_choice } = opts; + // DO: handled better (Smart Connections specific) + // get index of last system message + const last_system_idx = opts.messages.findLastIndex(msg => msg.role === 'system' && msg.content.includes('---BEGIN')); + if (last_system_idx > -1) { + const system_prompt = '\n' + opts.messages[last_system_idx].content + '\n\n'; + messages[messages.length - 1].content = system_prompt + messages[messages.length - 1].content; + } + const out = { + messages, + model, + max_tokens, + temperature, + } + if(tools){ + out.tools = tools.map(tool => ({ + name: tool.function.name, + description: tool.function.description, + input_schema: tool.function.parameters, + })); + if(tool_choice?.type === 'function'){ + // add "Use the ${tool.name} tool" to the last user message + const tool_prompt = `Use the "${tool_choice.function.name}" tool!`; + const last_user_idx = out.messages.findLastIndex(msg => msg.role === 'user'); + out.messages[last_user_idx].content += '\n' + tool_prompt; + out.system = `Required: use the "${tool_choice.function.name}" tool!`; + } + } + // DO: handled better (Smart Connections specific) + // if system message exists prior to last_system_idx AND does not include "---BEGIN" then add to body.system + const last_non_context_system_idx = opts.messages.findLastIndex(msg => msg.role === 'system' && !msg.content.includes('---BEGIN')); + if(last_non_context_system_idx > -1) out.system = opts.messages[last_non_context_system_idx].content; + return out; +} +exports.chatml_to_anthropic = chatml_to_anthropic; + diff --git a/smart-chat-model-v1/adapters/anthropic.test.js b/smart-chat-model-v1/adapters/anthropic.test.js new file mode 100644 index 00000000..dfef5834 --- /dev/null +++ b/smart-chat-model-v1/adapters/anthropic.test.js @@ -0,0 +1,336 @@ +const test = require('ava'); +const { chatml_to_anthropic } = require('./anthropic'); + +test('filters out system messages and formats correctly', t => { + const input = { + messages: [ + { role: 'user', content: 'Hello' }, + { role: 'assistant', content: 'Hi!' }, + { role: 'user', content: 'How are you?' } + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + const expected = { + messages: [ + { role: 'user', content: 'Hello' }, + { role: 'assistant', content: 'Hi!' }, + { role: 'user', content: 'How are you?' } + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + const result = chatml_to_anthropic(input); + t.deepEqual(result, expected); +}); + +test('adds system message context correctly', t => { + const input = { + messages: [ + { role: 'user', content: 'Hello' }, + { role: 'system', content: '---BEGIN NOTE---\nImportant info\n---END NOTE---' }, + { role: 'user', content: 'How are you?' } + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + const expectedContent = '\n---BEGIN NOTE---\nImportant info\n---END NOTE---\n\nHow are you?'; + const result = chatml_to_anthropic(input); + + t.is(result.messages[result.messages.length - 1].content, expectedContent); +}); + +const anthropic_lookup = { + "name": "lookup", + "description": "Semantic search", + "input_schema": { + "type": "object", + "properties": { + "hypotheticals": { + "type": "array", + "items": { "type": "string" } + } + }, + "required": ["hypotheticals"] + } +}; +const anthropic_create_note = { + "name": "create_note", + "description": "Create a note", + "input_schema": { + "type": "object", + "properties": { + "note": { + "type": "string" + } + }, + "required": ["note"] + } +}; +const openai_lookup = { + "type": "function", + "function": { + "name": "lookup", + "description": "Semantic search", + "parameters": { + "type": "object", + "properties": { + "hypotheticals": { + "type": "array", + "items": { "type": "string" } + } + }, + "required": ["hypotheticals"] + } + } +}; +const openai_create_note = { + "type": "function", + "function": { + "name": "create_note", + "description": "Create a note", + "parameters": { + "type": "object", + "properties": { + "note": { + "type": "string" + } + }, + "required": ["note"] + } + } +}; +test('should handle tool_choice forcing lookup', t => { + const input = { + messages: [ + { role: 'user', content: 'Hello' }, + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5, + tool_choice: { + type: "function", + function: { + name: "lookup", + } + }, + tools: [openai_lookup] + }; + const expected = { + messages: [ + { role: 'user', content: 'Hello\nUse the "lookup" tool!' }, + ], + model: 'test-model', + system: 'Required: use the "lookup" tool!', + max_tokens: 100, + temperature: 0.5, + tools: [anthropic_lookup] + }; + t.deepEqual(chatml_to_anthropic(input), expected); +}); +test('should handle tool_choice auto', t => { + const input = { + messages: [ + { role: 'user', content: 'Hello' }, + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5, + tool_choice: "auto", + tools: [openai_lookup, openai_create_note] + }; + const expected = { + messages: [ + { role: 'user', content: 'Hello' }, + ], + model: 'test-model', + // system: 'Required: use the "lookup" tool!', + max_tokens: 100, + temperature: 0.5, + tools: [anthropic_lookup, anthropic_create_note] + }; + t.deepEqual(chatml_to_anthropic(input), expected); +}); +test('should properly format tool role as tool result in user message', t => { + const input = { + messages: [ + { role: 'user', content: 'Hello' }, + { role: 'assistant', "tool_calls": [ + { + "id": "check_status", + "type": "function", + "function": { + "name": "check_status", + "arguments": "{\"status\":\"check\"}" + } + } + ]}, + { role: 'tool', content: '{"result": "ok"}' }, + { + role: 'assistant', + content: [ + { type: 'text', text: 'The result of the lookup tool was: OK; checking again' }, + ], + tool_calls: [ + { + id: 'check_status', + type: 'function', + function: { + name: 'check_status', + arguments: '{"status":"check2"}' + } + } + ] + }, + { role: 'tool', content: '{"result": "ok2"}' }, + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5, + }; + const expected = { + messages: [ + { role: 'user', content: 'Hello' }, + { role: 'assistant', content: [ + { type: 'tool_use', id: 'tool-1', name: 'check_status', input: {"status": "check"} } + ]}, + { role: 'user', content: [ + { + type: 'tool_result', + tool_use_id: 'tool-1', + content: '{"result": "ok"}' + } + ]}, + { role: 'assistant', content: [ + { type: 'tool_use', id: 'tool-2', name: 'check_status', input: {"status": "check2"} }, + { type: 'text', text: 'The result of the lookup tool was: OK; checking again' }, + ]}, + { role: 'user', content: [ + { + type: 'tool_result', + tool_use_id: 'tool-2', + content: '{"result": "ok2"}' + } + ]} + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5, + }; + t.deepEqual(chatml_to_anthropic(input), expected); +}); + +test('adds non-context system message correctly', t => { + const input = { + messages: [ + { role: 'user', content: 'Hello' }, + { role: 'system', content: 'Respond as if you are a helpful assistant' }, + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + const expected = { + messages: [ + { role: 'user', content: 'Hello' }, + ], + system: 'Respond as if you are a helpful assistant', + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + const result = chatml_to_anthropic(input); + t.deepEqual(result, expected); +}); + +test('handles message content as an array', t => { + const input = { + messages: [ + { + role: 'user', + content: [ + { + type: 'text', + text: "Hello" + } + ] + }, + { + role: 'assistant', + content: [ + { + type: 'text', + text: 'Hi!' + } + ] + }, + { + role: 'user', + content: [ + { + type: 'text', + text: 'How are you?' + } + ] + } + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + + const expected = { + messages: [ + { role: 'user', content: [{type: 'text', text: 'Hello'}] }, + { role: 'assistant', content: [{type: 'text', text: 'Hi!'}] }, + { role: 'user', content: [{type: 'text', text: 'How are you?'}] } + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + + + const result = chatml_to_anthropic(input); + t.deepEqual(result, expected); +}); + +test('should handle image_url', t => { + const input = { + messages: [ + { role: 'user', content: [ + {type: 'text', text: 'Transcribe this image' }, + {type: 'image_url', image_url: {url: 'data:image/jpg;base64,Base64 image'}} + ]} + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + const expected = { + messages: [ + { role: 'user', content: [ + {type: 'text', text: 'Transcribe this image'}, + {type: 'image', source: { + type: 'base64', + media_type: 'image/jpeg', + data: 'Base64 image' + }} + ]} + ], + model: 'test-model', + max_tokens: 100, + temperature: 0.5 + }; + t.deepEqual(chatml_to_anthropic(input), expected); +}) + diff --git a/smart-chat-model-v1/adapters/cohere.js b/smart-chat-model-v1/adapters/cohere.js new file mode 100644 index 00000000..c9f4ddfb --- /dev/null +++ b/smart-chat-model-v1/adapters/cohere.js @@ -0,0 +1,95 @@ +/** + * CohereAdapter class is designed to adapt the SmartChatModel's interaction with the Cohere API. + * It provides methods to prepare request bodies, handle streaming data, and extract message content from responses. + */ +class CohereAdapter { + /** + * Converts a ChatML object to a format suitable for a request to the Cohere API. + * @param {Object} chatml - The ChatML object containing the chat history and other parameters. + * @returns {Object} The request body formatted for the Cohere API. + */ + prepare_request_body(chatml) { return chatml_to_cohere(chatml); } + + /** + * Extracts the message content from a JSON response from the Cohere API. + * @param {Object} json - The JSON response object from which to extract the text content. + * @returns {string} The extracted text content from the response. + */ + get_message_content(json) { return json.text; } + + /** + * Processes streaming data received from the Cohere API and extracts text chunks. + * This method handles the accumulation of text data over multiple events and manages the state of the stream. + * @param {Object} event - The event object containing streaming data. + * @returns {string} The accumulated text chunk extracted from the stream. + */ + get_text_chunk_from_stream(event) { + if(!this.last_line_index) this.last_line_index = 0; + clearTimeout(this.last_line_timeout); + this.last_line_timeout = setTimeout(() => { + this.last_line_index = 0; + }, 10000); + const data = event.source.xhr.responseText; + // split by newline and get last + const lines = data.split('\n').slice(this.last_line_index); + this.last_line_index += lines.length; + const text_chunk = lines + .filter((line) => line.trim() !== '') + .map((line) => { + console.log(line); + const json = JSON.parse(line); + if(json.event_type === 'stream-end') { + console.log('stream-end'); + this.end_of_stream = true; + setTimeout(() => { + this.end_of_stream = false; + }, 3000); + return ''; + } + return json.text; + }) + .join(''); + console.log(text_chunk); + return text_chunk; + } + + /** + * Determines if the end of the stream has been reached based on the event data. + * @param {Object} event - The event object that may indicate the end of the stream. + * @returns {boolean} True if the end of the stream is indicated, false otherwise. + */ + is_end_of_stream(event) { return this.end_of_stream; } +} +exports.CohereAdapter = CohereAdapter; + +/** + * Converts a ChatML object into a format suitable for the Cohere API. + * This function prepares the data by structuring it according to the requirements of the Cohere API, + * including the model to use, the chat history excluding the last user message, and the last message separately. + * + * @param {Object} chatml - The ChatML object containing the model, messages, and other parameters like temperature. + * @returns {Object} The formatted object for the Cohere API request, containing the model, chat history, last message, and temperature. + */ +function chatml_to_cohere(chatml) { + const cohere = { + model: chatml.model, + // skip last user message + chat_history: chatml.messages + .slice(0, -1) + .map((message) => ({ + role: message.role, + message: parse_message_content_to_string(message), + })) + , + message: parse_message_content_to_string(chatml.messages[chatml.messages.length - 1]), + temperature: chatml.temperature, + // stream: chatml.stream // currently not supported + }; + return cohere; +} +exports.chatml_to_cohere = chatml_to_cohere; + +function parse_message_content_to_string(message) { + return Array.isArray(message.content) ? message.content.filter(c => c.type === 'text').map(c => c.text).join('\n') : message.content; +} + diff --git a/smart-chat-model-v1/adapters/cohere.test.js b/smart-chat-model-v1/adapters/cohere.test.js new file mode 100644 index 00000000..b3037dc3 --- /dev/null +++ b/smart-chat-model-v1/adapters/cohere.test.js @@ -0,0 +1,63 @@ +const test = require('ava'); +const { chatml_to_cohere } = require('./cohere'); + +test('reformats chatml to cohere format', (t) => { + const input = { + model: 'command-r', + messages: [ + { role: 'system', content: 'System message' }, + { role: 'user', content: 'User message' }, + { role: 'assistant', content: 'Assistant message' }, + { role: 'user', content: 'User message 2' } + ], + temperature: 0.5, + topK: 10, + topP: 0.8, + max_tokens: 100, + stopSequences: ['stop'], + n: 2 + }; + const expected = { + model: 'command-r', + chat_history: [ + { role: 'system', message: 'System message' }, + { role: 'user', message: 'User message' }, + { role: 'assistant', message: 'Assistant message' }, + ], + message: 'User message 2', + temperature: 0.5, + }; + + const cohere = chatml_to_cohere(input); + t.deepEqual(cohere, expected); +}); +test('handles message content as an array', (t) => { + const input = { + model: 'command-r', + messages: [ + { role: 'system', content: 'System message' }, + { role: 'user', content: [ { type: 'text', text: 'User message' } ]}, + { role: 'assistant', content: [ { type: 'text', text: 'Assistant message' } ]}, + { role: 'user', content: [ { type: 'text', text: 'User message 2' } ]} + ], + temperature: 0.5, + topK: 10, + topP: 0.8, + max_tokens: 100, + stopSequences: ['stop'], + n: 2 + }; + const expected = { + model: 'command-r', + chat_history: [ + { role: 'system', message: 'System message' }, + { role: 'user', message: 'User message' }, + { role: 'assistant', message: 'Assistant message' }, + ], + message: 'User message 2', + temperature: 0.5, + }; + + const cohere = chatml_to_cohere(input); + t.deepEqual(cohere, expected); +}); \ No newline at end of file diff --git a/smart-chat-model/adapters/gemini.js b/smart-chat-model-v1/adapters/gemini.js similarity index 100% rename from smart-chat-model/adapters/gemini.js rename to smart-chat-model-v1/adapters/gemini.js diff --git a/smart-chat-model/adapters/gemini.test.js b/smart-chat-model-v1/adapters/gemini.test.js similarity index 100% rename from smart-chat-model/adapters/gemini.test.js rename to smart-chat-model-v1/adapters/gemini.test.js diff --git a/smart-chat-model-v1/adapters/open_router.js b/smart-chat-model-v1/adapters/open_router.js new file mode 100644 index 00000000..96a2db1c --- /dev/null +++ b/smart-chat-model-v1/adapters/open_router.js @@ -0,0 +1,39 @@ +class OpenRouterAdapter { + constructor(model) { this.model = model; } + get_tool_call(json) { + // handles Gemini format + if(json.choices[0].message.tool_calls){ + return json.choices[0].message.tool_calls[0].function; + } + // handles mistral format + if(json.choices[0].message.content.includes("function")){ + const content = JSON.parse(json.choices[0].message.content); + if(!content.function) return null; + return content; + } + return null; + } + get_tool_name(tool_call) { + if(tool_call.function) return tool_call.function; // mistral format + if(tool_call.name) return tool_call.name; // gemini format + return null; + } + get_tool_call_content(tool_call) { + if(tool_call.parameters) return tool_call.parameters; // mistral format + // handle gemini format + if(tool_call.arguments){ + const args = JSON.parse(tool_call.arguments); + // prevent escape character issues + Object.entries(args).forEach(([key, value]) => { + args[key] = value.replace(/\\n/g, "\n") + .replace(/\\t/g, "\t") + .replace(/\\r/g, "\r") + .replace(/\\'/g, "'") + .replace(/\\"/g, '"') + }); + return args; + } + return null; + } +} +exports.OpenRouterAdapter = OpenRouterAdapter; \ No newline at end of file diff --git a/smart-chat-model-v2/dist/smart_chat_model_web.js b/smart-chat-model-v1/dist/smart_chat_model_web.js similarity index 100% rename from smart-chat-model-v2/dist/smart_chat_model_web.js rename to smart-chat-model-v1/dist/smart_chat_model_web.js diff --git a/smart-chat-model/models.old.json b/smart-chat-model-v1/models.old.json similarity index 100% rename from smart-chat-model/models.old.json rename to smart-chat-model-v1/models.old.json diff --git a/smart-chat-model/models/anthropic.js b/smart-chat-model-v1/models/anthropic.js similarity index 100% rename from smart-chat-model/models/anthropic.js rename to smart-chat-model-v1/models/anthropic.js diff --git a/smart-chat-model/models/cohere.js b/smart-chat-model-v1/models/cohere.js similarity index 100% rename from smart-chat-model/models/cohere.js rename to smart-chat-model-v1/models/cohere.js diff --git a/smart-chat-model/models/fetch.js b/smart-chat-model-v1/models/fetch.js similarity index 100% rename from smart-chat-model/models/fetch.js rename to smart-chat-model-v1/models/fetch.js diff --git a/smart-chat-model/models/google_gemini.js b/smart-chat-model-v1/models/google_gemini.js similarity index 100% rename from smart-chat-model/models/google_gemini.js rename to smart-chat-model-v1/models/google_gemini.js diff --git a/smart-chat-model/models/open_router.js b/smart-chat-model-v1/models/open_router.js similarity index 100% rename from smart-chat-model/models/open_router.js rename to smart-chat-model-v1/models/open_router.js diff --git a/smart-chat-model/models/openai.js b/smart-chat-model-v1/models/openai.js similarity index 100% rename from smart-chat-model/models/openai.js rename to smart-chat-model-v1/models/openai.js diff --git a/smart-chat-model-v2/package.json b/smart-chat-model-v1/package.json similarity index 78% rename from smart-chat-model-v2/package.json rename to smart-chat-model-v1/package.json index 0737c2b4..b4166635 100644 --- a/smart-chat-model-v2/package.json +++ b/smart-chat-model-v1/package.json @@ -1,11 +1,10 @@ { "name": "smart-chat-model", "author": "Brian Joseph Petro (🌴 Brian)", - "type": "module", "license": "MIT", "version": "1.0.5", "description": "no-nonsense adapter for Anthropic Claude, Google Gemini, Cohere & more with OpenAI style API interface.", - "main": "index.js", + "main": "smart_chat_model.js", "scripts": { "test": "npx ava" }, @@ -24,13 +23,8 @@ "url": "https://github.com/brianpetro/jsbrains/issues" }, "homepage": "https://jsbrains.org", - "dependencies": { - "smart-http-request": "../smart-http-request", - "smart-model": "../smart-model" - }, "devDependencies": { "ava": "^6.1.2", - "dotenv": "^16.4.5", "esbuild": "^0.20.2" } } diff --git a/smart-chat-model-v2/platforms.json b/smart-chat-model-v1/platforms.json similarity index 59% rename from smart-chat-model-v2/platforms.json rename to smart-chat-model-v1/platforms.json index 08f561ab..31b5e9fb 100644 --- a/smart-chat-model-v2/platforms.json +++ b/smart-chat-model-v1/platforms.json @@ -5,7 +5,7 @@ "endpoint": "https://api.openai.com/v1/chat/completions", "streaming": true, "actions": true, - "models_endpoint": "https://api.openai.com/v1/models", + "fetch_models": true, "default_model": "gpt-3.5-turbo", "signup_url": "https://platform.openai.com/api-keys" }, @@ -18,7 +18,7 @@ "streaming": true, "actions": true, "adapter": "Gemini", - "models_endpoint": "https://generativelanguage.googleapis.com/v1beta/models", + "fetch_models": true, "default_model": "gemini-1.5-pro", "signup_url": "https://ai.google.dev/" }, @@ -28,8 +28,8 @@ "endpoint": "https://openrouter.ai/api/v1/chat/completions", "streaming": true, "adapter": "OpenRouter", - "models_endpoint": "https://openrouter.ai/api/v1/models", - "default_model": "mistralai/mistral-7b-instruct:free", + "fetch_models": true, + "default_model": "meta-llama/llama-3.1-8b-instruct:free", "signup_url": "https://accounts.openrouter.ai/sign-up?redirect_url=https%3A%2F%2Fopenrouter.ai%2Fkeys" }, "cohere": { @@ -38,7 +38,7 @@ "endpoint": "https://api.cohere.ai/v1/chat", "streaming": false, "adapter": "Cohere", - "models_endpoint": "https://api.cohere.ai/v1/models", + "fetch_models": true, "default_model": "command-r", "signup_url": "https://dashboard.cohere.com/welcome/register?redirect_uri=%2Fapi-keys" }, @@ -54,41 +54,7 @@ }, "adapter": "Anthropic", "actions": true, - "models_endpoint": false, - "models": [ - { - "key": "claude-3-opus-20240229", - "model_name": "claude-3-opus-20240229", - "description": "Anthropic's Claude Opus", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - { - "key": "claude-3-5-sonnet-20240620", - "model_name": "claude-3.5-sonnet-20240620", - "description": "Anthropic's Claude Sonnet", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - { - "key": "claude-3-haiku-20240307", - "model_name": "claude-3-haiku-20240307", - "description": "Anthropic's Claude Haiku", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - { - "key": "claude-3-sonnet-20240229", - "model_name": "claude-3-sonnet-20240229", - "description": "Anthropic's Claude Sonnet", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - } - ], + "fetch_models": true, "default_model": "claude-3-sonnet-20240229", "signup_url": "https://console.anthropic.com/login?returnTo=%2Fsettings%2Fkeys" }, diff --git a/smart-chat-model-v1/smart_chat_model.js b/smart-chat-model-v1/smart_chat_model.js new file mode 100644 index 00000000..9422a3bc --- /dev/null +++ b/smart-chat-model-v1/smart_chat_model.js @@ -0,0 +1,466 @@ +// Copyright (c) Brian Joseph Petro + +// Permission is hereby granted, free of charge, to any person obtaining +// a copy of this software and associated documentation files (the +// "Software"), to deal in the Software without restriction, including +// without limitation the rights to use, copy, modify, merge, publish, +// distribute, sublicense, and/or sell copies of the Software, and to +// permit persons to whom the Software is furnished to do so, subject to +// the following conditions: + +// The above copyright notice and this permission notice shall be +// included in all copies or substantial portions of the Software. + +// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE +// LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION +// OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION +// WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + +const adapters = require('./adapters'); +const platforms = require('./platforms.json'); +const { is_valid_tool_call } = require('./utils/is_valid_tool_call'); +const { SmartStreamer } = require('./streamer'); +const fetch_models = require("./models/fetch"); +/** + * SmartChatModel class provides functionalities to handle chat interactions with various models and adapters. + * It supports streaming and non-streaming responses, tool calls, and customizations through options. + */ +class SmartChatModel { + /** + * Constructs an instance of SmartChatModel with specified environment, model key, and options. + * @param {Object} main - The main environment context, typically containing configurations and state. + * @param {string} platform_key - Key to select the specific model configuration from models.json. + * @param {Object} model_config - Optional parameters to override model configurations. + */ + constructor(main, platform_key, model_config={}) { + this.env = main; + this.main = this.env; // DEPRECATED + this.config = { + ...(platforms[platform_key] || {}), + ...model_config, // override default platform config + } + console.log(JSON.stringify(this.config)); + this.platform_key = platform_key; + this.active_stream = null; + this._request_adapter = null; + this.platforms = platforms; + if(this.config.adapter) this.adapter = new adapters[this.config.adapter](this); + if(this.adapter) console.log("has chat model adapter"); + } + static get models() { return platforms; } // DEPRECATED (confusing name) + // + static get platforms() { + return Object.keys(platforms).map(key => ({ + key, + ...platforms[key], + })); + } + get platform() { return platforms[this.platform_key]; } + get default_opts() { + return { + temperature: 0.3, + top_p: 1, + presence_penalty: 0, + frequency_penalty: 0, + n: 1, + model: this.model_name, + max_tokens: this.max_output_tokens, + }; + } + async request_middlewares(opts) { return opts; } + /** + * Completes the chat interaction by processing the provided options, making an API request, and handling the response. + * This method supports both streaming and non-streaming responses, and can handle tool calls if specified in the response. + * + * @param {Object} opts - The options for the chat completion which may include settings like temperature, max tokens, etc. + * @param {boolean} render - Flag to determine if the response should be rendered in the UI. + * @returns {Promise} - Returns the chat response content or handles tool outputs recursively. In case of errors, it may return an error message. + */ + async complete(opts = {}, render = true) { + const prepared_opts = await this.prepare_options(opts); + const request = this.create_request(prepared_opts); + + try { + if (prepared_opts.stream) { + return await this.handle_streaming_request(request, render); + } + return await this.handle_non_streaming_request(request, prepared_opts, render); + } catch (err) { + return this.handle_error(err, render); + } + } + + async prepare_options(opts) { + if (!this.base_model_config) { + this.base_model_config = await this.get_base_model_config(); + this.config = { + ...this.base_model_config, + ...this.config, + }; + } + + const prepared_opts = { + ...this.default_opts, + messages: (await this.current?.get_chat_ml())?.messages || [], + ...opts, + }; + + if (prepared_opts.stream !== false && this.config.streaming && !this.current?.tool_choice) { + prepared_opts.stream = true; + } else { + prepared_opts.stream = false; + } + + return this.request_middlewares(JSON.parse(JSON.stringify(prepared_opts))); + } + + create_request(opts) { + const req = { + headers: { + "Content-Type": "application/json", + Authorization: `Bearer ${this.api_key}` + }, + method: "POST", + }; + + if (this.config.headers) { + req.headers = { ...req.headers, ...this.config.headers }; + } + + if (this.config.api_key_header) { + if (this.config.api_key_header !== 'none') { + req.headers[this.config.api_key_header] = this.api_key; + } + delete req.headers.Authorization; + } + + const body = typeof this.env.actions?.prepare_request_body === 'function' + ? this.env.actions.prepare_request_body(opts) + : { ...opts }; + + req.body = JSON.stringify(typeof this.adapter?.prepare_request_body === 'function' + ? this.adapter.prepare_request_body(body) + : body); + + return req; + } + + async handle_streaming_request(request, render) { + return this.stream(request); + } + + async handle_non_streaming_request(request, opts, render) { + const resp_json = await this.request(request); + + if (resp_json.error) { + return this.handle_api_error(resp_json.error, render); + } + + // if is tool_call, handle tool_call and return + const tool_call = this.get_tool_call(resp_json); + if (tool_call) { + return this.handle_tool_call(tool_call, opts, render); + } + + const message_content = this.get_message_content(resp_json); + if (render) { + this.done_handler(message_content); + } + return message_content; + } + + handle_api_error(error, render) { + console.error(error); + if (render) { + if(typeof error?.message === 'string') this.done_handler("*API Error: " + error.message + "*"); + else this.done_handler("*API Error. See console logs for details.*"); + } + return "*API Error. See console logs for details.*"; + } + + async handle_tool_call(tool_call, opts, render) { + if (this.env.chats?.current?.tool_choice) { + this.env.chats.current.tool_choice = null; + } + + const tool_name = this.get_tool_name(tool_call); + const tool_call_content = this.get_tool_call_content(tool_call); + const tools = opts.tools || []; + const tool = tools.find((t) => t.function.name === tool_name); + const tool_handler = this.get_tool_handler(tool_name); + + if (!tool_handler || !is_valid_tool_call(tool, tool_call_content)) { + return this.handle_invalid_tool_call(tool_name, tool_call_content); + } + + await this.add_tool_call_to_chat(tool_name, tool_call_content); + const tool_output = await tool_handler(this.env, tool_call_content); + + if (tool_output) { + await this.current.add_tool_output(tool_name, tool_output); + this.current.tool_choice = 'none'; // prevent subsequent tool calls from preventing completion + return this.complete({}); // empty opts + } + } + + handle_invalid_tool_call(tool_name, tool_call_content) { + console.warn(`Tool ${tool_name} not found or invalid, returning tool_call_content`); + return tool_call_content; + } + + async add_tool_call_to_chat(tool_name, tool_call_content) { + if (typeof this.current?.add_message === 'function') { + await this.current.add_message({ + role: 'assistant', + tool_calls: [{ + function: { + name: tool_name, + arguments: JSON.stringify(tool_call_content), + } + }] + }); + } + } + + handle_error(err, render) { + console.error(err); + if (render) { + this.done_handler("*An error occurred. See console logs for details.*"); + } + return "*An error occurred. See console logs for details.*"; + } + + // HANDLE TOOLS + /** + * Retrieves the tool handler function based on the tool name from the environment's actions. + * This method can be overridden to use custom logic for handling tools. + * + * @param {string} tool_name - The name of the tool for which the handler is to be retrieved. + * @returns {Function} The handler function for the specified tool. + */ + get_tool_handler(tool_name) { return this.env.actions?.actions?.[tool_name]?.handler; } + + /** + * Extracts the tool call information from a JSON response. This method supports adapter-specific logic. + * If no adapter method is provided, it defaults to the expected OpenAI JSON format. + * + * @param {Object} json - The JSON response from which to extract the tool call. + * @returns {Object} The first tool call found in the response. + */ + get_tool_call(json) { + if(typeof this.adapter?.get_tool_call === 'function') return this.adapter.get_tool_call(json); + return json.choices?.[0].message.tool_calls?.[0]; // OpenAI format + } + + /** + * Determines the tool name from a tool call object. Supports adapter-specific implementations. + * Defaults to extracting the name directly from the tool call structure. + * + * @param {Object} tool_call - The tool call object from which to extract the tool name. + * @returns {string} The name of the tool. + */ + get_tool_name(tool_call) { + if(typeof this.adapter?.get_tool_name === 'function') return this.adapter.get_tool_name(tool_call); + return tool_call.function.name; + } + + /** + * Extracts the tool call content from a tool call object. Supports adapter-specific logic. + * Defaults to parsing the 'arguments' field of the tool call function as JSON. + * + * @param {Object} tool_call - The tool call object from which to extract the content. + * @returns {Object} The parsed arguments of the tool call. + */ + get_tool_call_content(tool_call) { + if(typeof this.adapter?.get_tool_call_content === 'function') return this.adapter.get_tool_call_content(tool_call); + return JSON.parse(tool_call.function.arguments); + } + + // HANDLE MESSAGES + /** + * Retrieves the message object from a JSON response. Supports adapter-specific implementations. + * Defaults to handling both OpenAI and Ollama formats by checking for message structures in 'choices'. + * + * @param {Object} json - The JSON response from which to extract the message. + * @returns {Object} The message object extracted from the response. + */ + get_message(json) { + if(typeof this.adapter?.get_message === 'function') return this.adapter.get_message(json); + return json.choices?.[0].message || json.message; // supports OpenAI and Ollama + } + + /** + * Extracts the content of a message from a JSON response. Supports adapter-specific implementations. + * This method relies on `get_message` to first retrieve the message object. + * + * @param {Object} json - The JSON response from which to extract the message content. + * @returns {string} The content of the message. + */ + get_message_content(json) { + if(typeof this.adapter?.get_message_content === 'function') return this.adapter.get_message_content(json); + return this.get_message(json).content; + } + + async request(req){ + req.url = this.endpoint; + req.throw = false; + // handle fallback to fetch (allows for overwriting in child classes) + const resp = this._request_adapter ? await this._request_adapter(req) : await fetch(this.endpoint, req); + const resp_json = await this.get_resp_json(resp); + return resp_json; + } + async get_resp_json(resp) { return (typeof resp.json === 'function') ? await resp.json() : await resp.json; } + get request_adapter(){ return this._request_adapter; } + + async stream(req) { + console.log("Streaming Request: "); + const full_text = await new Promise((resolve, reject) => { + try { + // console.log("stream", opts); + this.active_stream = new SmartStreamer(this.endpoint_streaming, req); + let curr_text = ""; + this.active_stream.addEventListener("message", (e) => { + if(this.is_end_of_stream(e)) { + this.stop_stream(); + return resolve(curr_text); + } + let text_chunk = this.get_text_chunk_from_stream(e); + if(!text_chunk) return; + curr_text += text_chunk; + this.chunk_handler(text_chunk); // call the chunk handler if it exists + }); + // unnecessary? + this.active_stream.addEventListener("readystatechange", (e) => { + if (e.readyState >= 2) console.log("ReadyState: " + e.readyState); + }); + this.active_stream.addEventListener("error", (e) => { + console.error(e); + this.done_handler("*API Error. See console logs for details.*"); + this.stop_stream(); + reject(e); + }); + this.active_stream.stream(); + } catch (err) { + console.error(err); + this.stop_stream(); + reject(err); + } + }); + this.done_handler(full_text); // handled in complete() + return full_text; + } + get_text_chunk_from_stream(event) { + if(typeof this.adapter?.get_text_chunk_from_stream === 'function') return this.adapter.get_text_chunk_from_stream(event); + let resp = null; + let text_chunk = ''; + // DO: is this try/catch still necessary? + try { + resp = JSON.parse(event.data); + text_chunk = resp.choices[0].delta.content; + } catch (err) { + console.log(err); + console.log(event.data); + if (event.data.indexOf('}{') > -1) event.data = event.data.replace(/}{/g, '},{'); + resp = JSON.parse(`[${event.data}]`); + resp.forEach((r) => { + if (r.choices) text_chunk += r.choices[0].delta.content; + }); + } + return text_chunk; + } + is_end_of_stream(event) { + if(typeof this.adapter?.is_end_of_stream === 'function') return this.adapter.is_end_of_stream(event); + return event.data === "[DONE]"; // use default OpenAI format + } + + stop_stream() { + if (this.active_stream) { + this.active_stream.end(); + this.active_stream = null; + } + } + done_handler(full_str) { + // Should handle: + // 1. Add message to current chat history + // 2. Update chat UI + if(typeof this.main.done_handler === 'function') this.main.done_handler(full_str); + } + chunk_handler(text_chunk) { + // Should handle: + // 1. Update chat UI + if(typeof this.main.chunk_handler === 'function') this.main.chunk_handler(text_chunk); + } + async count_tokens(input) { + if(typeof this.adapter?.count_tokens === 'function') return await this.adapter.count_tokens(input); + return this.estimate_tokens(input); + } + estimate_tokens(input) { + if(typeof this.adapter?.estimate_tokens === 'function') return this.adapter.estimate_tokens(input); + if(typeof input === 'object') input = JSON.stringify(input); + return input.length / 4; + } + async test_api_key() { + try{ + const request = { + messages: [ + { role: "user", content: "Hello" }, + ], + temperature: 0, + max_tokens: 100, + stream: false, + n: 1, + }; + if(this.config.fetch_models) { + request.model = this.config.default_model; + } + const resp = await this.complete(request, false); + if(!resp) return false; + return true; + }catch(err){ + console.error(err); + return false; + } + } + async get_models() { + if(!this.api_key){ + console.warn(`No API key found for ${this.platform_key}. Cannot retrieve models.`); + return []; + } + // const fx_name = this.plugin.settings.chat_model_platform_key; + if(this.platforms[this.platform_key]?.fetch_models && typeof fetch_models[this.platform_key] === "function"){ + const models = await fetch_models[this.platform_key](this.api_key, this._request_adapter); + if(models) { + // sort alphabetically by model name + models.sort((a, b) => a.model_name.localeCompare(b.model_name)); + return models; + }else console.error(`No models found for ${this.platform_key}`, models); + } + return []; + } + async get_base_model_config() { + const models = await this.get_models(); + return models.find((m) => m.key === this.model_name); + } + // getters + get api_key() { return this.config.api_key; } + get current() { return this.env.chats?.current; } + // use endpoint of combine protocol, hostname, port, and path + get endpoint() { + if(typeof this.adapter?.endpoint !== 'undefined') return this.adapter.endpoint.replace('MODEL_NAME', this.model_name); + return this.config.endpoint || this.config.protocol + "://" + this.config.hostname + (this.config.port ? ":" + this.config.port : "") + this.endpoint_path; + } + get endpoint_streaming() { + if(typeof this.adapter?.endpoint_streaming !== 'undefined') return this.adapter.endpoint_streaming.replace('MODEL_NAME', this.model_name); + return this.config.endpoint_streaming || this.endpoint; + } + get endpoint_path() { return this.config.path.startsWith('/') ? this.config.path : '/' + this.config.path; } + get max_input_tokens() { return this.config.max_input_tokens; } + get max_output_tokens() { return this.config.max_output_tokens; } + get model_name() { return this.config.model_name || this.config.default_model; } + get multimodal() { return typeof this.adapter?.multimodal !== 'undefined' ? this.adapter.multimodal : this.config.multimodal; } +} +exports.SmartChatModel = SmartChatModel; + diff --git a/smart-chat-model-v2/streamer.js b/smart-chat-model-v1/streamer.js similarity index 98% rename from smart-chat-model-v2/streamer.js rename to smart-chat-model-v1/streamer.js index aa8a3d6b..178b983e 100644 --- a/smart-chat-model-v2/streamer.js +++ b/smart-chat-model-v1/streamer.js @@ -1,4 +1,4 @@ -export class SmartStreamer { +class SmartStreamer { constructor(url, options = {}) { const { method = 'GET', @@ -176,4 +176,6 @@ export class SmartStreamer { if (this.xhr.readyState === XMLHttpRequest.DONE) this.#setReadyState(this.CLOSED); } -} \ No newline at end of file +} + +exports.SmartStreamer = SmartStreamer; diff --git a/smart-chat-model-v2/utils/is_valid_tool_call.js b/smart-chat-model-v1/utils/is_valid_tool_call.js similarity index 100% rename from smart-chat-model-v2/utils/is_valid_tool_call.js rename to smart-chat-model-v1/utils/is_valid_tool_call.js diff --git a/smart-chat-model-v2/utils/is_valid_tool_call.test.js b/smart-chat-model-v1/utils/is_valid_tool_call.test.js similarity index 100% rename from smart-chat-model-v2/utils/is_valid_tool_call.test.js rename to smart-chat-model-v1/utils/is_valid_tool_call.test.js diff --git a/smart-chat-model/web-build.js b/smart-chat-model-v1/web-build.js similarity index 100% rename from smart-chat-model/web-build.js rename to smart-chat-model-v1/web-build.js diff --git a/smart-chat-model-v2/README.md b/smart-chat-model-v2/README.md deleted file mode 100644 index 6b804da9..00000000 --- a/smart-chat-model-v2/README.md +++ /dev/null @@ -1,3 +0,0 @@ -# Smart Chat Model - -A universal chat model API client that supports a wide variety of providers, models, and features. \ No newline at end of file diff --git a/smart-chat-model-v2/adapters/anthropic.js b/smart-chat-model-v2/adapters/anthropic.js deleted file mode 100644 index a86fad85..00000000 --- a/smart-chat-model-v2/adapters/anthropic.js +++ /dev/null @@ -1,205 +0,0 @@ -import { SmartChatModelApiAdapter, SmartChatModelRequestAdapter, SmartChatModelResponseAdapter } from './_api.js'; - -export class SmartChatModelAnthropicAdapter extends SmartChatModelApiAdapter { - get res_adapter() { return SmartChatModelAnthropicResponseAdapter; } - get req_adapter() { return SmartChatModelAnthropicRequestAdapter; } - // Implement Anthropic-specific methods here - async get_models() { - return [ - { - "key": "claude-3-opus-20240229", - "model_name": "claude-3-opus-20240229", - "description": "Anthropic's Claude Opus", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - { - key: "claude-3-5-sonnet-20240620", - "model_name": "claude-3.5-sonnet-20240620", - "description": "Anthropic's Claude Sonnet", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - { - key: "claude-3-haiku-20240307", - "model_name": "claude-3-haiku-20240307", - "description": "Anthropic's Claude Haiku", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - { - key: "claude-3-sonnet-20240229", - "model_name": "claude-3-sonnet-20240229", - "description": "Anthropic's Claude Sonnet", - "max_input_tokens": 200000, - "max_output_tokens": 4000, - "multimodal": true - }, - ]; - } -} - -export class SmartChatModelAnthropicRequestAdapter extends SmartChatModelRequestAdapter { - - to_platform() { return this.to_anthropic(); } - - to_anthropic() { - this.anthropic_body = {}; - this.anthropic_body.model = this.model; - this.anthropic_body.messages = this._transform_messages_to_anthropic(); - this.anthropic_body.max_tokens = this.max_tokens; - this.anthropic_body.temperature = this.temperature; - this.anthropic_body.stream = this.stream; - if (this.tools) this.anthropic_body.tools = this._transform_tools_to_anthropic(); - if (this.tool_choice) { - if (this.tool_choice === 'auto') { - this.anthropic_body.tool_choice = { type: 'auto' }; - } else if (typeof this.tool_choice === 'object' && this.tool_choice.function) { - this.anthropic_body.tool_choice = { type: 'tool', name: this.tool_choice.function.name }; - } - } - - return { - url: this.adapter.endpoint, - method: 'POST', - headers: this.get_headers(), - body: JSON.stringify(this.anthropic_body) - }; - } - - _transform_messages_to_anthropic() { - let anthropic_messages = []; - - for (const message of this.messages) { - if (message.role === 'system') { - if(!this.anthropic_body.system) this.anthropic_body.system = ''; - else this.anthropic_body.system += '\n\n'; - this.anthropic_body.system += message.content; - } else { - anthropic_messages.push({ - role: this._get_anthropic_role(message.role), - content: this._get_anthropic_content(message.content) - }); - } - } - - - return anthropic_messages; - } - - _get_anthropic_role(role) { - const role_map = { - function: 'assistant' // Anthropic doesn't have a function role, so we'll treat it as assistant - }; - return role_map[role] || role; - } - - _get_anthropic_content(content) { - if (Array.isArray(content)) { - return content.map(item => { - if (item.type === 'text') return { type: 'text', text: item.text }; - if (item.type === 'image_url') { - return { - type: 'image', - source: { - type: 'base64', - media_type: item.image_url.url.split(';')[0].split(':')[1], - data: item.image_url.url.split(',')[1] - } - }; - } - return item; - }); - } - return content; - } - - _transform_tools_to_anthropic() { - if (!this.tools) return undefined; - return this.tools.map(tool => ({ - name: tool.function.name, - description: tool.function.description, - parameters: tool.function.parameters - })); - } -} - -export class SmartChatModelAnthropicResponseAdapter extends SmartChatModelResponseAdapter { - to_openai() { - return { - id: this._res.id, - object: 'chat.completion', - created: Date.now(), - choices: [ - { - index: 0, - message: this._transform_message_to_openai(), - finish_reason: this._get_openai_finish_reason(this._res.stop_reason) - } - ], - usage: this._transform_usage_to_openai() - }; - } - - _transform_message_to_openai() { - const message = { - role: 'assistant', - content: '', - tool_calls: [] - }; - - if (Array.isArray(this._res.content)) { - for (const content of this._res.content) { - if (content.type === 'text') { - message.content += (message.content ? '\n\n' : '') + content.text; - } else if (content.type === 'tool_use') { - message.tool_calls.push({ - id: content.tool_use.id, - type: 'function', - function: { - name: content.tool_use.name, - arguments: JSON.stringify(content.tool_use.input) - } - }); - } - } - } else { - message.content = this._res.content; - } - - if (message.tool_calls.length === 0) { - delete message.tool_calls; - } - - return message; - } - - _get_openai_finish_reason(stop_reason) { - const reason_map = { - 'end_turn': 'stop', - 'max_tokens': 'length', - 'tool_use': 'function_call' - }; - return reason_map[stop_reason] || stop_reason; - } - - _transform_usage_to_openai() { - if (!this._res.usage) { - return { - prompt_tokens: 0, - completion_tokens: 0, - total_tokens: 0 - }; - } - return { - prompt_tokens: this._res.usage.input_tokens || 0, - completion_tokens: this._res.usage.output_tokens || 0, - total_tokens: (this._res.usage.input_tokens || 0) + (this._res.usage.output_tokens || 0) - }; - } -} - - diff --git a/smart-chat-model-v2/adapters/anthropic.test.js b/smart-chat-model-v2/adapters/anthropic.test.js deleted file mode 100644 index d542d7e1..00000000 --- a/smart-chat-model-v2/adapters/anthropic.test.js +++ /dev/null @@ -1,195 +0,0 @@ -import test from 'ava'; -import dotenv from 'dotenv'; -import { SmartChatModel } from '../smart_chat_model.js'; -import { SmartChatModelAnthropicAdapter, SmartChatModelAnthropicRequestAdapter, SmartChatModelAnthropicResponseAdapter } from './anthropic.js'; -import platforms from '../platforms.json' assert { type: 'json' }; - -// Create an instance of SmartChatModel for Anthropic -const smart_chat_model_anthropic = new SmartChatModel({ - settings: { - platform_key: 'anthropic', - anthropic: { - api_key: 'test_api_key', - model_key: 'claude-2.1', - } - }, - adapters: { - anthropic: SmartChatModelAnthropicAdapter - } -}); - -test('SmartChatModelAnthropicRequestAdapter converts OpenAI request to Anthropic schema', t => { - const openai_request = { - model: 'claude-2.1', - messages: [ - { role: 'system', content: 'You are a helpful weather assistant.' }, - { role: 'user', content: 'Hello, how are you?' }, - { role: 'assistant', content: 'I\'m doing well, thank you for asking! How can I assist you today?' }, - { role: 'user', content: 'What\'s the weather like?' } - ], - max_tokens: 1000, - temperature: 0.7, - stream: false, - tools: [ - { - type: 'function', - function: { - name: 'weather_api', - description: 'Get weather information for a location', - parameters: { - type: 'object', - properties: { - location: { type: 'string' }, - date: { type: 'string' } - }, - required: ['location'] - } - } - } - ], - tool_choice: 'auto' - }; - - const request_adapter = new SmartChatModelAnthropicRequestAdapter(smart_chat_model_anthropic.adapter, openai_request); - const anthropic_request = request_adapter.to_anthropic(); - - t.is(anthropic_request.url, 'https://api.anthropic.com/v1/messages'); - t.is(anthropic_request.method, 'POST'); - t.deepEqual(anthropic_request.headers, { - ...platforms.anthropic.headers, - 'Content-Type': 'application/json', - 'x-api-key': 'test_api_key' - }); - - const body = JSON.parse(anthropic_request.body); - t.is(body.model, 'claude-2.1'); - t.is(body.max_tokens, 1000); - t.is(body.temperature, 0.7); - t.is(body.stream, false); - t.is(body.system, 'You are a helpful weather assistant.'); - t.deepEqual(body.messages, [ - { role: 'user', content: 'Hello, how are you?' }, - { role: 'assistant', content: 'I\'m doing well, thank you for asking! How can I assist you today?' }, - { role: 'user', content: 'What\'s the weather like?' } - ]); - t.deepEqual(body.tools, [ - { - name: 'weather_api', - description: 'Get weather information for a location', - parameters: openai_request.tools[0].function.parameters - } - ]); - t.deepEqual(body.tool_choice, { type: 'auto' }); -}); - -test('SmartChatModelAnthropicResponseAdapter converts Anthropic response to OpenAI schema', t => { - const anthropic_response = { - id: 'msg_1234567890', - type: 'message', - role: 'assistant', - content: [ - { - type: 'text', - text: 'To get the weather information, I\'ll need to use the weather API. Let me do that for you.' - }, - { - type: 'tool_use', - tool_use: { - id: 'call_1234567890', - name: 'weather_api', - input: { - location: 'New York', - date: '2023-03-01' - } - } - }, - { - type: 'text', - text: 'Here is the weather information for New York: It\'s currently sunny with a temperature of 72°F (22°C). The forecast predicts clear skies throughout the day with a high of 78°F (26°C) and a low of 65°F (18°C). It\'s a perfect day to spend some time outdoors!' - } - ], - model: 'claude-2.1', - stop_reason: 'end_turn', - stop_sequence: null, - usage: { - input_tokens: 20, - output_tokens: 25 - } - }; - - const response_adapter = new SmartChatModelAnthropicResponseAdapter(smart_chat_model_anthropic.adapter, anthropic_response); - const openai_response = response_adapter.to_openai(); - - t.is(openai_response.id, 'msg_1234567890'); - t.is(openai_response.object, 'chat.completion'); - t.truthy(openai_response.created); - t.deepEqual(openai_response.choices[0].message, { - role: 'assistant', - content: 'To get the weather information, I\'ll need to use the weather API. Let me do that for you.\n\nHere is the weather information for New York: It\'s currently sunny with a temperature of 72°F (22°C). The forecast predicts clear skies throughout the day with a high of 78°F (26°C) and a low of 65°F (18°C). It\'s a perfect day to spend some time outdoors!', - tool_calls: [ - { - id: 'call_1234567890', - type: 'function', - function: { - name: 'weather_api', - arguments: JSON.stringify({ - location: 'New York', - date: '2023-03-01' - }) - } - } - ] - }); - t.is(openai_response.choices[0].finish_reason, 'stop'); - t.deepEqual(openai_response.usage, { - prompt_tokens: 20, - completion_tokens: 25, - total_tokens: 45 - }); -}); - -dotenv.config({ path: '../.env' }); - -const ANTHROPIC_API_KEY = process.env.ANTHROPIC_API_KEY; - -test.serial('Live Anthropic Integration Test', async t => { - if (!ANTHROPIC_API_KEY) { - t.pass('Skipping live test: No Anthropic API key found in .env'); - return; - } - - const smart_chat_model = new SmartChatModel({ - settings: { - platform_key: 'anthropic', - anthropic: { - api_key: ANTHROPIC_API_KEY, - model_key: 'claude-2.1', - } - }, - adapters: { - anthropic: SmartChatModelAnthropicAdapter - } - }); - // fetch all models - const models = await smart_chat_model.get_models(); - console.log(JSON.stringify(models, null, 2)); - - const request = { - messages: [ - { role: 'user', content: 'What is the capital of Germany?' } - ], - max_tokens: 100, - temperature: 0.7 - }; - - try { - const response = await smart_chat_model.complete(request); - console.log(JSON.stringify(response, null, 2)); - t.truthy(response.choices[0].message.content); - t.is(response.choices[0].message.role, 'assistant'); - t.truthy(response.usage.total_tokens > 0); - } catch (error) { - console.log(error); - t.fail(`Live test failed: ${error.message}`); - } -}); diff --git a/smart-chat-model-v2/adapters/cohere.js b/smart-chat-model-v2/adapters/cohere.js deleted file mode 100644 index 48f9e6e3..00000000 --- a/smart-chat-model-v2/adapters/cohere.js +++ /dev/null @@ -1,196 +0,0 @@ -import { SmartChatModelApiAdapter, SmartChatModelRequestAdapter, SmartChatModelResponseAdapter } from './_api.js'; - -export class SmartChatModelCohereAdapter extends SmartChatModelApiAdapter { - get req_adapter() { return SmartChatModelCohereRequestAdapter; } - get res_adapter() { return SmartChatModelCohereResponseAdapter; } - - async count_tokens(input) { - const req = { - url: `${this.platform.endpoint}/tokenize`, - method: "POST", - headers: { - "Content-Type": "application/json", - "Authorization": `Bearer ${this.api_key}` - }, - body: JSON.stringify({ text: typeof input === 'string' ? input : JSON.stringify(input) }) - }; - const resp = await this.http_adapter.request(req); - return resp.json.tokens.length; - } - - get endpoint() { - return `${this.platform.endpoint}`; - } - - parse_model_data(model_data) { - return model_data.models - .filter(model => model.name.startsWith('command-')) - .map(model => ({ - model_name: model.name, - key: model.name, - max_input_tokens: model.context_length, - tokenizer_url: model.tokenizer_url, - finetuned: model.finetuned, - description: `Max input tokens: ${model.context_length}, Finetuned: ${model.finetuned}`, - raw: model - })) - .sort((a, b) => a.model_name.localeCompare(b.model_name)); - } -} - -export class SmartChatModelCohereRequestAdapter extends SmartChatModelRequestAdapter { - to_platform() { return this.to_cohere(); } - - to_cohere() { - const cohere_body = { - model: this.model, - message: this._get_latest_user_message(), - chat_history: this._transform_messages_to_cohere_chat_history(), - max_tokens: this.max_tokens, - temperature: this.temperature, - stream: this.stream, - ...(this.tools && { tools: this._transform_tools_to_cohere() }), - ...(this._req.tool_choice && { tool_choice: this._req.tool_choice }), - ...(this._req.preamble && { preamble: this._req.preamble }), - ...(this._req.conversation_id && { conversation_id: this._req.conversation_id }), - ...(this._req.connectors && { connectors: this._req.connectors }), - ...(this._req.documents && { documents: this._req.documents }), - }; - - if (this._req.response_format) { - cohere_body.response_format = { - type: this._req.response_format.type, - ...(this._req.response_format.schema && { schema: this._req.response_format.schema }) - }; - } - - return { - url: this.adapter.endpoint, - method: 'POST', - headers: this.get_headers(), - body: JSON.stringify(cohere_body) - }; - } - - _get_latest_user_message() { - // throw if image input - if (this.messages.some(msg => Array.isArray(msg.content) && msg.content.some(part => part.type === 'image_url'))) { - throw new Error("Cohere API does not support image input"); - } - const user_messages = this.messages.filter(msg => msg.role === 'user'); - return user_messages[user_messages.length - 1]?.content || ''; - } - - _transform_messages_to_cohere_chat_history() { - return this.messages.slice(0, -1).map(message => ({ - role: this._get_cohere_role(message.role), - message: this._get_cohere_content(message.content) - })); - } - - _get_cohere_role(role) { - const role_map = { - system: 'SYSTEM', - user: 'USER', - assistant: 'CHATBOT', - function: 'CHATBOT' - }; - return role_map[role] || role.toUpperCase(); - } - - _get_cohere_content(content) { - if (Array.isArray(content)) { - for (const part of content) { - if (part.type === 'image_url') { - throw new Error("Cohere API does not support image input"); - } - } - return content.map(part => { - if (part.type === 'text') return part.text; - return JSON.stringify(part); - }).join('\n'); - } - return content; - } - - _transform_tools_to_cohere() { - return this.tools.map(tool => ({ - name: tool.function.name, - description: tool.function.description, - parameters: tool.function.parameters - })); - } -} - -export class SmartChatModelCohereResponseAdapter extends SmartChatModelResponseAdapter { - to_openai() { - if (this._res.message) { - throw new Error(this._res.message); - } - - return { - id: this._res.generation_id || 'cohere_' + Date.now(), - object: 'chat.completion', - created: Date.now(), - model: this.adapter.model_key, - choices: [ - { - index: 0, - message: this._transform_message_to_openai(), - finish_reason: this._get_openai_finish_reason(this._res.finish_reason) - } - ], - usage: this._transform_usage_to_openai() - }; - } - - _transform_message_to_openai() { - const message = { - role: 'assistant', - content: this._res.text || '' - }; - - if (this._res.citations) { - message.citations = this._res.citations; - } - - if (this._res.documents) { - message.documents = this._res.documents; - } - - if (this._res.search_queries) { - message.search_queries = this._res.search_queries; - } - - if (this._res.search_results) { - message.search_results = this._res.search_results; - } - - return message; - } - - _get_openai_finish_reason(finish_reason) { - const reason_map = { - 'COMPLETE': 'stop', - 'MAX_TOKENS': 'length', - 'ERROR': 'error', - 'STOP_SEQUENCE': 'stop' - }; - return reason_map[finish_reason] || 'stop'; - } - - _transform_usage_to_openai() { - if (!this._res.meta || !this._res.meta.billed_units) { - return { - prompt_tokens: null, - completion_tokens: null, - total_tokens: null - }; - } - return { - prompt_tokens: this._res.meta.billed_units.input_tokens || null, - completion_tokens: this._res.meta.billed_units.output_tokens || null, - total_tokens: (this._res.meta.billed_units.input_tokens || 0) + (this._res.meta.billed_units.output_tokens || 0) - }; - } -} \ No newline at end of file diff --git a/smart-chat-model-v2/adapters/cohere.test.js b/smart-chat-model-v2/adapters/cohere.test.js deleted file mode 100644 index e7f0e7ff..00000000 --- a/smart-chat-model-v2/adapters/cohere.test.js +++ /dev/null @@ -1,235 +0,0 @@ -import test from 'ava'; -import dotenv from 'dotenv'; -import { SmartChatModel } from '../smart_chat_model.js'; -import { SmartChatModelCohereAdapter, SmartChatModelCohereRequestAdapter, SmartChatModelCohereResponseAdapter } from './cohere.js'; - -dotenv.config({ path: '../.env' }); - -const COHERE_API_KEY = process.env.COHERE_API_KEY; - -const smart_chat_model = new SmartChatModel({ - settings: { - platform_key: 'cohere', - cohere: { - api_key: 'test_api_key', - model_key: 'command', - } - }, - adapters: { - cohere: SmartChatModelCohereAdapter - } -}); - -test('SmartChatModelCohereRequestAdapter converts OpenAI request to Cohere schema', t => { - const openai_request = { - model: 'command', - messages: [ - { role: 'system', content: 'You are a helpful assistant.' }, - { role: 'user', content: 'Hello, how are you?' }, - { role: 'assistant', content: 'I\'m doing well, thank you for asking! How can I assist you today?' }, - { role: 'user', content: 'What\'s the weather like?' } - ], - max_tokens: 1000, - temperature: 0.7, - stream: false, - tools: [ - { - type: 'function', - function: { - name: 'get_weather', - description: 'Get weather information for a location', - parameters: { - type: 'object', - properties: { - location: { type: 'string' }, - unit: { type: 'string', enum: ['celsius', 'fahrenheit'] } - }, - required: ['location'] - } - } - } - ], - tool_choice: 'auto', - preamble: 'This is a preamble', - conversation_id: 'conv_123', - response_format: { type: 'json_object' } - }; - - const request_adapter = new SmartChatModelCohereRequestAdapter(smart_chat_model.adapter, openai_request); - const cohere_request = request_adapter.to_cohere(); - - t.is(cohere_request.method, 'POST'); - t.deepEqual(cohere_request.headers, { - 'Content-Type': 'application/json', - 'Authorization': 'Bearer test_api_key' - }); - - const body = JSON.parse(cohere_request.body); - t.is(body.model, 'command'); - t.is(body.max_tokens, 1000); - t.is(body.temperature, 0.7); - t.is(body.stream, false); - t.is(body.message, 'What\'s the weather like?'); - t.deepEqual(body.chat_history, [ - { role: 'SYSTEM', message: 'You are a helpful assistant.' }, - { role: 'USER', message: 'Hello, how are you?' }, - { role: 'CHATBOT', message: 'I\'m doing well, thank you for asking! How can I assist you today?' } - ]); - t.deepEqual(body.tools, [{ - name: 'get_weather', - description: 'Get weather information for a location', - parameters: openai_request.tools[0].function.parameters - }]); - t.is(body.tool_choice, 'auto'); - t.is(body.preamble, 'This is a preamble'); - t.is(body.conversation_id, 'conv_123'); - t.deepEqual(body.response_format, { type: 'json_object' }); -}); - -test('SmartChatModelCohereRequestAdapter throws error for image input', t => { - const openai_request = { - model: 'command', - messages: [ - { role: 'user', content: [ - { type: 'text', text: 'What\'s in this image?' }, - { type: 'image_url', image_url: { url: 'data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAA...' } } - ] } - ], - max_tokens: 500, - temperature: 0.8 - }; - - const request_adapter = new SmartChatModelCohereRequestAdapter(smart_chat_model.adapter, openai_request); - - const error = t.throws(() => { - request_adapter.to_platform(); - }, { instanceOf: Error }); - - t.is(error.message, "Cohere API does not support image input"); -}); - -test('SmartChatModelCohereResponseAdapter converts Cohere response to OpenAI schema', t => { - const cohere_response = { - text: 'The weather in New York is currently sunny with a temperature of 72°F (22°C).', - generation_id: 'gen_123456789', - finish_reason: 'COMPLETE', - citations: [ - { start: 0, end: 10, text: 'The weather', document_ids: ['doc1'] } - ], - documents: [ - { id: 'doc1', title: 'Weather Report', snippet: 'New York weather report', url: 'http://example.com', timestamp: '2023-06-01T12:00:00Z' } - ], - search_queries: [ - { text: 'New York weather', generation_id: 'gen_987654321' } - ], - search_results: [ - { connector: { id: 'web' }, document_ids: ['doc1'], search_query: { text: 'New York weather', generation_id: 'gen_987654321' } } - ], - meta: { - api_version: { version: '1.0' }, - billed_units: { input_tokens: 20, output_tokens: 15 }, - tokens: { input_tokens: 20, output_tokens: 15 } - } - }; - - const response_adapter = new SmartChatModelCohereResponseAdapter(smart_chat_model.adapter, cohere_response); - const openai_response = response_adapter.to_openai(); - - t.is(openai_response.id, 'gen_123456789'); - t.is(openai_response.object, 'chat.completion'); - t.truthy(openai_response.created); - t.deepEqual(openai_response.choices[0].message, { - role: 'assistant', - content: 'The weather in New York is currently sunny with a temperature of 72°F (22°C).', - citations: cohere_response.citations, - documents: cohere_response.documents, - search_queries: cohere_response.search_queries, - search_results: cohere_response.search_results - }); - t.is(openai_response.choices[0].finish_reason, 'stop'); - t.deepEqual(openai_response.usage, { - prompt_tokens: 20, - completion_tokens: 15, - total_tokens: 35 - }); -}); - -test.serial('Live Cohere Integration Test', async t => { - if (!COHERE_API_KEY) { - t.pass('Skipping live test: No Cohere API key found in .env'); - return; - } - - const smart_chat_model = new SmartChatModel({ - settings: { - platform_key: 'cohere', - cohere: { - api_key: COHERE_API_KEY, - model_key: 'command', - } - }, - adapters: { - cohere: SmartChatModelCohereAdapter - } - }); - - const request = { - messages: [ - { role: 'user', content: 'What is the capital of France?' } - ], - max_tokens: 100, - temperature: 0.7 - }; - - try { - const response = await smart_chat_model.complete(request); - console.log(JSON.stringify(response, null, 2)); - t.truthy(response.choices[0].message.content); - t.is(response.choices[0].message.role, 'assistant'); - t.truthy(response.usage.prompt_tokens > 0); - t.truthy(response.usage.completion_tokens > 0); - t.truthy(response.usage.total_tokens > 0); - } catch (error) { - console.error('Error details:', error); - t.fail(`Live test failed: ${error.message}`); - } -}); - -test.serial('Live Cohere get_models Integration Test', async t => { - if (!COHERE_API_KEY) { - t.pass('Skipping live test: No Cohere API key found in .env'); - return; - } - - const smart_chat_model = new SmartChatModel({ - settings: { - platform_key: 'cohere', - cohere: { - api_key: COHERE_API_KEY, - model_key: 'command', - } - }, - adapters: { - cohere: SmartChatModelCohereAdapter - } - }); - - try { - const models = await smart_chat_model.get_models(); - // console.log(JSON.stringify(models, null, 2)); - t.true(Array.isArray(models)); - t.true(models.length > 0); - t.true(models.every(model => - model.hasOwnProperty('model_name') && - model.hasOwnProperty('key') && - model.hasOwnProperty('max_input_tokens') && - model.hasOwnProperty('tokenizer_url') && - model.hasOwnProperty('finetuned') && - model.hasOwnProperty('description') && - model.hasOwnProperty('raw') - )); - } catch (error) { - console.error(error); - t.fail(`Live test failed: ${error.message}`); - } -}); \ No newline at end of file diff --git a/smart-chat-model-v2/adapters/open_router.js b/smart-chat-model-v2/adapters/open_router.js deleted file mode 100644 index faa72b23..00000000 --- a/smart-chat-model-v2/adapters/open_router.js +++ /dev/null @@ -1,41 +0,0 @@ -import { SmartChatModelApiAdapter, SmartChatModelRequestAdapter, SmartChatModelResponseAdapter } from './_api.js'; - -export class SmartChatModelOpenRouterAdapter extends SmartChatModelApiAdapter { - get req_adapter() { return SmartChatModelOpenRouterRequestAdapter; } - get res_adapter() { return SmartChatModelOpenRouterResponseAdapter; } - - async count_tokens(input) { - // OpenRouter doesn't provide a token counting endpoint, so we'll use a rough estimate - const text = typeof input === 'string' ? input : JSON.stringify(input); - return Math.ceil(text.length / 4); // Rough estimate: 1 token ≈ 4 characters - } - - get endpoint() { - return 'https://openrouter.ai/api/v1/chat/completions'; - } - - parse_model_data(model_data) { - if(model_data.data) { - model_data = model_data.data; - } - return model_data.map(model => ({ - model_name: model.id, - key: model.id, - max_input_tokens: model.context_length, - description: model.name, - actions: model.description.includes('tool use') || model.description.includes('function call'), - multimodal: model.architecture.modality === 'multimodal', - raw: model - })); - } -} - -export class SmartChatModelOpenRouterRequestAdapter extends SmartChatModelRequestAdapter { - to_platform() { return this.to_openai(); } - -} - -export class SmartChatModelOpenRouterResponseAdapter extends SmartChatModelResponseAdapter { - to_platform() { return this.to_openai(); } - get object() { return 'chat.completion'; } -} \ No newline at end of file diff --git a/smart-chat-model-v2/smart_chat_model.js b/smart-chat-model-v2/smart_chat_model.js deleted file mode 100644 index dd4d287a..00000000 --- a/smart-chat-model-v2/smart_chat_model.js +++ /dev/null @@ -1,125 +0,0 @@ -import { SmartHttpRequest } from "smart-http-request"; -import platforms from "./platforms.json" assert { type: "json" }; -import { SmartModel } from "smart-model"; -export class SmartChatModel extends SmartModel { - constructor(opts){ - super(opts); - this._adapters = {}; - this._http_adapter = null; - } - async complete(req){ return await this.adapter.complete(req); } - get_platforms_as_options(){ return Object.keys(platforms).map(key => ({ value: key })); } - async get_models(refresh=false){ return await this.adapter.get_models(refresh); } - async get_models_as_options(){ - const models = await this.adapter.get_models(); - return Object.values(models).map(model => ({ value: model.key })); - } - async stream(req, handlers={}){ return await this.adapter.stream(req, handlers); } - stop_stream() { this.adapter.stop_stream(); } - async test_api_key(){ return await this.adapter.test_api_key(); } - async count_tokens(input){ return await this.adapter.count_tokens(input); } - get adapters() { return this.opts.adapters; } - get adapter() { - if(!this._adapters[this.platform_key]){ - this._adapters[this.platform_key] = new this.adapters[this.platform_key](this); - } - return this._adapters[this.platform_key]; - } - get http_adapter() { - if(!this._http_adapter){ - if(this.opts.http_adapter) this._http_adapter = this.opts.http_adapter; - else this._http_adapter = new SmartHttpRequest(); - } - return this._http_adapter; - } - get model_key() { return this.platform_settings?.model_key; } - get platform() { return platforms[this.platform_key]; } - get platform_key() { return this.settings.platform_key; } - get platform_settings() { - if(!this.settings[this.platform_key]) this.settings[this.platform_key] = {}; - return this.settings[this.platform_key]; - } - get settings() { return this.opts.settings; } - get settings_config() { - const _settings_config = { - platform_key: { - name: 'Chat Model Platform', - type: "dropdown", - description: "Select a chat model platform to use with Smart Chat.", - options_callback: 'get_platforms_as_options', - is_scope: true, // trigger re-render of settings when changed - // callback: 'changed_chat_model_platform', - }, - "[CHAT_PLATFORM].model_key": { - name: 'Chat Model', - type: "dropdown", - description: "Select a chat model to use with Smart Chat.", - options_callback: 'get_models_as_options', - // callback: 'changed_chat_model', - conditional: (settings) => !local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].model_name": { - name: 'Model Name', - type: "text", - description: "Enter the model name for the chat model platform.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].api_key": { - name: 'API Key', - type: "password", - description: "Enter your API key for the chat model platform.", - callback: 'test_api_key', - is_scope: true, // trigger re-render of settings when changed (reload models dropdown) - }, - "[CHAT_PLATFORM].protocol": { - name: 'Protocol', - type: "text", - description: "Enter the protocol for the local chat model.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].hostname": { - name: 'Hostname', - type: "text", - description: "Enter the hostname for the local chat model.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].port": { - name: 'Port', - type: "number", - description: "Enter the port for the local chat model.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].path": { - name: 'Path', - type: "text", - description: "Enter the path for the local chat model.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].streaming": { - name: 'Streaming', - type: "toggle", - description: "Enable streaming for the local chat model.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - "[CHAT_PLATFORM].max_input_tokens": { - name: 'Max Input Tokens', - type: "number", - description: "Enter the maximum number of input tokens for the chat model.", - // callback: 'changed_chat_model', - conditional: (settings) => local_platforms.includes(settings.platform_key), - }, - ...(this.adapter.settings_config || {}), - } - return this.process_settings_config(_settings_config); - } - process_setting_key(key) { - return key.replace(/\[CHAT_PLATFORM\]/g, this.platform_key); - } -} -const local_platforms = ['custom_local', 'ollama', 'lm_studio']; \ No newline at end of file diff --git a/smart-chat-model/README.md b/smart-chat-model/README.md index e4076c54..6b804da9 100644 --- a/smart-chat-model/README.md +++ b/smart-chat-model/README.md @@ -1,166 +1,3 @@ # Smart Chat Model -Used to integrate OpenAI GPT-4, Antrhopic Claude, Google Gemini & Cohere Command-r in [Smart Connections](https://github.com/brianpetro/obsidian-smart-connections). -Try the [demo](https://brianpetro.github.io/jsbrains/sample-web) or browse the [demo code here](https://github.com/brianpetro/jsbrains/tree/main/assets/sample-web.html). - -[![Smart Chat Model Demo](https://brianpetro.github.io/jsbrains/sample-web.gif)](https://brianpetro.github.io/jsbrains/sample-web) - -## SmartChatModel Usage Guide -```bash -npm install smart-chat-model -``` - -`SmartChatModel` is a comprehensive class designed to facilitate interactions with chat models, supporting features like streaming responses, handling tool calls, and customizing requests through adapters. It's built to be adaptable for various chat model configurations and platforms. -The SmartChatModel class provides a flexible and powerful way to interact with chat models, supporting advanced features like streaming, tool calls, and request customization. By following this guide, you should be able to integrate and use SmartChatModel effectively in your projects. - -### Initialization -To initialize a SmartChatModel instance, you need to provide the main environment object, a model key to select the configuration from chat_models.json, and optional user-defined options to override the default model configuration. - -```js -const { SmartChatModel } = require('./chat.js'); - -const mainEnv = {}; // Your main environment object - -const modelKey = 'your_model_key'; // Key from chat_models.json - -const options = {}; // Optional overrides - -const chatModel = new SmartChatModel(mainEnv, modelKey, options); -``` - -### Making Requests -To make a request to the chat model, use the complete method. This method allows for customization of the request through options and can handle both streaming and non-streaming responses. - -```js -const requestOptions = { - -  messages: [{ role: "user", content: "Hello" }], - -  temperature: 0.3, - -  max_tokens: 100, - -  stream: false, // Set to true for streaming responses - -}; - -chatModel.complete(requestOptions) - -  .then(response => { - -    console.log("Response:", response); - -  }) - -  .catch(error => { - -    console.error("Error:", error); - -  }); -``` - - -### Streaming Responses -If the chat model supports streaming and it's enabled in the configuration, you can set stream: true in the request options to receive streaming responses. The SmartChatModel will handle the streaming logic internally, including starting and stopping the stream as needed. - -### Handling Tool Calls -The SmartChatModel can automatically detect and handle tool calls within responses. It uses the configured adapters to interpret the tool call data and executes the corresponding tool handler if a valid tool call is detected. - -### Customization with Adapters -Adapters allow for customization of request and response handling. If your use case requires specific handling logic, you can create a custom adapter and specify it in the model configuration. The SmartChatModel will use this adapter for preparing requests, parsing responses, and handling tool calls. - -### Counting Tokens -The count_tokens and estimate_tokens methods are available for estimating the number of tokens in a given input. This can be useful for managing request sizes and understanding the complexity of inputs. - -```js -const input = "Hello, world!"; - -chatModel.count_tokens(input) - -  .then(tokenCount => { - -    console.log("Token count:", tokenCount); - -  }); -``` - -### Testing API Key -The test_api_key method allows you to verify if the provided API key is valid by making a test request to the chat model. - -```js -chatModel.test_api_key() - -  .then(isValid => { - -    console.log("API key valid:", isValid); - -  }); -``` - - - - -## Adapter Pattern for Platform Compatibility -The `SmartChatModel` class is designed to be extensible and compatible with various chat platforms. This is achieved through the use of the adapter pattern, which abstracts platform-specific logic into separate adapter classes. Each adapter implements a consistent interface that `SmartChatModel` can interact with, regardless of the underlying platform differences. - -### Purpose -The adapter pattern allows for the easy integration of new platforms by encapsulating the API-specific logic within adapters. This ensures that the core logic of `SmartChatModel` remains clean and focused, while still being able to support a wide range of platforms. - -### Key Adapter Methods -Adapters must implement the following methods to be compatible with SmartChatModel: - -##### Converting options into the platform-specific request format -- `prepare_request_body(opts)`: - -##### Extracting the message content from the platform's response. -- `get_message(resp_json)` -- `get_message_content(resp_json)` - -##### Methods for extracting and handling tool call information from the response. -- `get_tool_call(resp_json)` -- `get_tool_name(tool_call)` -- `get_tool_call_content(tool_call)` - -##### Handling streaming responses. -- `get_text_chunk_from_stream(event)` -- `is_end_of_stream(event)`:  - -##### Providing token counting for input validation or estimation. -- `async count_tokens(input)`  -- `estimate_tokens(input)` - -### Implementing a New Adapter -To add support for a new platform, follow these steps: -##### Create Adapter Class -1. Create a new file in the adapters directory for the platform, e.g., `new_platform.js`.  -2. Define a class `NewPlatformAdapter` that implements the required methods. - -```js -class NewPlatformAdapter { - prepare_request_body(opts) { /* Implementation */ } - get_message_content(json) { /* Implementation */ } - // Implement other required methods... -} - -exports.NewPlatformAdapter = NewPlatformAdapter; -``` -##### Integrate Adapter -1. Add the new adapter to `adapters.js` which exports all of the adapters. -2. Ensure `SmartChatModel` initializes it based on the `config.adapter`. - -### Using Adapters in SmartChatModel -`SmartChatModel` interacts with adapters by checking for the implementation of specific methods and calling them. This allows for flexible handling of different platform behaviors without modifying the core logic. - -For example, to prepare the request body: - -```js -req.body = JSON.stringify(this.adapter?.prepare_request_body ? this.adapter.prepare_request_body(body) : body); -``` - -And to handle streaming responses: - -```js -let text_chunk = this.adapter?.get_text_chunk_from_stream ? this.adapter.get_text_chunk_from_stream(event) : defaultTextChunkHandling(event); -``` - -This pattern ensures that `SmartChatModel` remains adaptable and can easily extend support to new platforms by adding corresponding adapters. \ No newline at end of file +A universal chat model API client that supports a wide variety of providers, models, and features. \ No newline at end of file diff --git a/smart-chat-model-v2/adapters/_adapter.js b/smart-chat-model/adapters/_adapter.js similarity index 100% rename from smart-chat-model-v2/adapters/_adapter.js rename to smart-chat-model/adapters/_adapter.js diff --git a/smart-chat-model-v2/adapters/_api.js b/smart-chat-model/adapters/_api.js similarity index 100% rename from smart-chat-model-v2/adapters/_api.js rename to smart-chat-model/adapters/_api.js diff --git a/smart-chat-model-v2/adapters/_api.test.js b/smart-chat-model/adapters/_api.test.js similarity index 100% rename from smart-chat-model-v2/adapters/_api.test.js rename to smart-chat-model/adapters/_api.test.js diff --git a/smart-chat-model/adapters/anthropic.js b/smart-chat-model/adapters/anthropic.js index a0b201e6..a86fad85 100644 --- a/smart-chat-model/adapters/anthropic.js +++ b/smart-chat-model/adapters/anthropic.js @@ -1,158 +1,205 @@ -/** - * AnthropicAdapter class provides methods to adapt the chat model interactions specifically for the Anthropic model. - * It includes methods to prepare request bodies, count and estimate tokens, and handle tool calls and messages. - */ -class AnthropicAdapter { - /** - * Prepares the request body for the Anthropic API by converting ChatML format to a format compatible with Anthropic. - * @param {Object} opts - The options object containing messages and other parameters in ChatML format. - * @returns {Object} The request body formatted for the Anthropic API. - */ - prepare_request_body(opts) { return chatml_to_anthropic(opts); } - /** - * Counts the tokens in the input by estimating them, as the Anthropic model does not provide a direct method. - * @param {string|Object} input - The input text or object to count tokens in. - * @returns {Promise} The estimated number of tokens in the input. - */ - async count_tokens(input) { - // Currently, the Anthropic model does not provide a way to count tokens - return this.estimate_tokens(input); - } - /** - * Estimates the number of tokens in the input based on a rough average token size. - * @param {string|Object} input - The input text or object to estimate tokens in. - * @returns {number} The estimated number of tokens. - */ - estimate_tokens(input){ - if(typeof input === 'object') input = JSON.stringify(input); - // Note: The division by 6 is a rough estimate based on observed average token size. - return Math.ceil(input.length / 6); // Use Math.ceil for a more accurate count - } - /** - * Extracts the first tool call from the JSON response content. - * @param {Object} json - The JSON response from which to extract the tool call. - * @returns {Object|null} The first tool call found, or null if none exist. - */ - get_tool_call(json){ - return json.content.find(msg => msg.type === 'tool_use'); - } - /** - * Retrieves the input content of a tool call. - * @param {Object} tool_call - The tool call object from which to extract the input. - * @returns {Object} The input of the tool call. - */ - get_tool_call_content(tool_call){ - return tool_call.input; - } - /** - * Retrieves the name of the tool from a tool call object. - * @param {Object} tool_call - The tool call object from which to extract the name. - * @returns {string} The name of the tool. - */ - get_tool_name(tool_call){ - return tool_call.name; +import { SmartChatModelApiAdapter, SmartChatModelRequestAdapter, SmartChatModelResponseAdapter } from './_api.js'; + +export class SmartChatModelAnthropicAdapter extends SmartChatModelApiAdapter { + get res_adapter() { return SmartChatModelAnthropicResponseAdapter; } + get req_adapter() { return SmartChatModelAnthropicRequestAdapter; } + // Implement Anthropic-specific methods here + async get_models() { + return [ + { + "key": "claude-3-opus-20240229", + "model_name": "claude-3-opus-20240229", + "description": "Anthropic's Claude Opus", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + { + key: "claude-3-5-sonnet-20240620", + "model_name": "claude-3.5-sonnet-20240620", + "description": "Anthropic's Claude Sonnet", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + { + key: "claude-3-haiku-20240307", + "model_name": "claude-3-haiku-20240307", + "description": "Anthropic's Claude Haiku", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + { + key: "claude-3-sonnet-20240229", + "model_name": "claude-3-sonnet-20240229", + "description": "Anthropic's Claude Sonnet", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + ]; } - /** - * Extracts the first message from the JSON response content. - * @param {Object} json - The JSON response from which to extract the message. - * @returns {Object|null} The first message found, or null if none exist. - */ - get_message(json){ return json.content?.[0]; } - /** - * Retrieves the content of the first message from the JSON response. - * @param {Object} json - The JSON response from which to extract the message content. - * @returns {string|null} The content of the first message, or null if no message is found. - */ - get_message_content(json) { return this.get_message(json)?.[this.get_message(json)?.type]; } } -exports.AnthropicAdapter = AnthropicAdapter; -// https://docs.anthropic.com/claude/reference/messages_post -/** - * Convert a ChatML object to an Anthropic object - * @param {Object} opts - The ChatML object - * @description This function converts a ChatML object to an Anthropic object. It filters out system messages and adds a system message prior to the last user message. - * @returns {Object} - The Anthropic object - */ -function chatml_to_anthropic(opts) { - let tool_counter = 0; - const messages = opts.messages - .filter(msg => msg.role !== 'system') - .map(m => { - if(m.role === 'tool'){ - return { role: 'user', content: [ - { - type: 'tool_result', - tool_use_id: `tool-${tool_counter}`, - content: m.content - } - ]}; - } - if(m.role === 'assistant' && m.tool_calls){ - tool_counter++; - const out = { - role: m.role, - content: m.tool_calls.map(c => ({ - type: 'tool_use', - id: `tool-${tool_counter}`, - name: c.function.name, - input: (typeof c.function.arguments === 'string') ? JSON.parse(c.function.arguments) : c.function.arguments - })) - }; - if(m.content){ - if(typeof m.content === 'string') out.content.push({type: 'text', text: m.content}); - else m.content.forEach(c => out.content.push(c)); - } - return out; + +export class SmartChatModelAnthropicRequestAdapter extends SmartChatModelRequestAdapter { + + to_platform() { return this.to_anthropic(); } + + to_anthropic() { + this.anthropic_body = {}; + this.anthropic_body.model = this.model; + this.anthropic_body.messages = this._transform_messages_to_anthropic(); + this.anthropic_body.max_tokens = this.max_tokens; + this.anthropic_body.temperature = this.temperature; + this.anthropic_body.stream = this.stream; + if (this.tools) this.anthropic_body.tools = this._transform_tools_to_anthropic(); + if (this.tool_choice) { + if (this.tool_choice === 'auto') { + this.anthropic_body.tool_choice = { type: 'auto' }; + } else if (typeof this.tool_choice === 'object' && this.tool_choice.function) { + this.anthropic_body.tool_choice = { type: 'tool', name: this.tool_choice.function.name }; } - if(typeof m.content === 'string') return { role: m.role, content: m.content }; - if(Array.isArray(m.content)){ - const content = m.content.map(c => { - if(c.type === 'text') return {type: 'text', text: c.text}; - if(c.type === 'image_url'){ - const image_url = c.image_url.url; - let media_type = image_url.split(":")[1].split(";")[0]; - if(media_type === 'image/jpg') media_type = 'image/jpeg'; - return {type: 'image', source: {type: 'base64', media_type: media_type, data: image_url.split(",")[1]}}; - } + } + + return { + url: this.adapter.endpoint, + method: 'POST', + headers: this.get_headers(), + body: JSON.stringify(this.anthropic_body) + }; + } + + _transform_messages_to_anthropic() { + let anthropic_messages = []; + + for (const message of this.messages) { + if (message.role === 'system') { + if(!this.anthropic_body.system) this.anthropic_body.system = ''; + else this.anthropic_body.system += '\n\n'; + this.anthropic_body.system += message.content; + } else { + anthropic_messages.push({ + role: this._get_anthropic_role(message.role), + content: this._get_anthropic_content(message.content) }); - return { role: m.role, content }; } - return m; - }) - ; - const { model, max_tokens, temperature, tools, tool_choice } = opts; - // DO: handled better (Smart Connections specific) - // get index of last system message - const last_system_idx = opts.messages.findLastIndex(msg => msg.role === 'system' && msg.content.includes('---BEGIN')); - if (last_system_idx > -1) { - const system_prompt = '\n' + opts.messages[last_system_idx].content + '\n\n'; - messages[messages.length - 1].content = system_prompt + messages[messages.length - 1].content; + } + + + return anthropic_messages; } - const out = { - messages, - model, - max_tokens, - temperature, + + _get_anthropic_role(role) { + const role_map = { + function: 'assistant' // Anthropic doesn't have a function role, so we'll treat it as assistant + }; + return role_map[role] || role; + } + + _get_anthropic_content(content) { + if (Array.isArray(content)) { + return content.map(item => { + if (item.type === 'text') return { type: 'text', text: item.text }; + if (item.type === 'image_url') { + return { + type: 'image', + source: { + type: 'base64', + media_type: item.image_url.url.split(';')[0].split(':')[1], + data: item.image_url.url.split(',')[1] + } + }; + } + return item; + }); + } + return content; } - if(tools){ - out.tools = tools.map(tool => ({ + + _transform_tools_to_anthropic() { + if (!this.tools) return undefined; + return this.tools.map(tool => ({ name: tool.function.name, description: tool.function.description, - input_schema: tool.function.parameters, + parameters: tool.function.parameters })); - if(tool_choice?.type === 'function'){ - // add "Use the ${tool.name} tool" to the last user message - const tool_prompt = `Use the "${tool_choice.function.name}" tool!`; - const last_user_idx = out.messages.findLastIndex(msg => msg.role === 'user'); - out.messages[last_user_idx].content += '\n' + tool_prompt; - out.system = `Required: use the "${tool_choice.function.name}" tool!`; + } +} + +export class SmartChatModelAnthropicResponseAdapter extends SmartChatModelResponseAdapter { + to_openai() { + return { + id: this._res.id, + object: 'chat.completion', + created: Date.now(), + choices: [ + { + index: 0, + message: this._transform_message_to_openai(), + finish_reason: this._get_openai_finish_reason(this._res.stop_reason) + } + ], + usage: this._transform_usage_to_openai() + }; + } + + _transform_message_to_openai() { + const message = { + role: 'assistant', + content: '', + tool_calls: [] + }; + + if (Array.isArray(this._res.content)) { + for (const content of this._res.content) { + if (content.type === 'text') { + message.content += (message.content ? '\n\n' : '') + content.text; + } else if (content.type === 'tool_use') { + message.tool_calls.push({ + id: content.tool_use.id, + type: 'function', + function: { + name: content.tool_use.name, + arguments: JSON.stringify(content.tool_use.input) + } + }); + } + } + } else { + message.content = this._res.content; + } + + if (message.tool_calls.length === 0) { + delete message.tool_calls; + } + + return message; + } + + _get_openai_finish_reason(stop_reason) { + const reason_map = { + 'end_turn': 'stop', + 'max_tokens': 'length', + 'tool_use': 'function_call' + }; + return reason_map[stop_reason] || stop_reason; + } + + _transform_usage_to_openai() { + if (!this._res.usage) { + return { + prompt_tokens: 0, + completion_tokens: 0, + total_tokens: 0 + }; } + return { + prompt_tokens: this._res.usage.input_tokens || 0, + completion_tokens: this._res.usage.output_tokens || 0, + total_tokens: (this._res.usage.input_tokens || 0) + (this._res.usage.output_tokens || 0) + }; } - // DO: handled better (Smart Connections specific) - // if system message exists prior to last_system_idx AND does not include "---BEGIN" then add to body.system - const last_non_context_system_idx = opts.messages.findLastIndex(msg => msg.role === 'system' && !msg.content.includes('---BEGIN')); - if(last_non_context_system_idx > -1) out.system = opts.messages[last_non_context_system_idx].content; - return out; } -exports.chatml_to_anthropic = chatml_to_anthropic; + diff --git a/smart-chat-model/adapters/anthropic.test.js b/smart-chat-model/adapters/anthropic.test.js index dfef5834..d542d7e1 100644 --- a/smart-chat-model/adapters/anthropic.test.js +++ b/smart-chat-model/adapters/anthropic.test.js @@ -1,336 +1,195 @@ -const test = require('ava'); -const { chatml_to_anthropic } = require('./anthropic'); - -test('filters out system messages and formats correctly', t => { - const input = { - messages: [ - { role: 'user', content: 'Hello' }, - { role: 'assistant', content: 'Hi!' }, - { role: 'user', content: 'How are you?' } - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 - }; - - const expected = { - messages: [ - { role: 'user', content: 'Hello' }, - { role: 'assistant', content: 'Hi!' }, - { role: 'user', content: 'How are you?' } - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 - }; - - const result = chatml_to_anthropic(input); - t.deepEqual(result, expected); -}); - -test('adds system message context correctly', t => { - const input = { - messages: [ - { role: 'user', content: 'Hello' }, - { role: 'system', content: '---BEGIN NOTE---\nImportant info\n---END NOTE---' }, - { role: 'user', content: 'How are you?' } - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 - }; - - const expectedContent = '\n---BEGIN NOTE---\nImportant info\n---END NOTE---\n\nHow are you?'; - const result = chatml_to_anthropic(input); - - t.is(result.messages[result.messages.length - 1].content, expectedContent); -}); - -const anthropic_lookup = { - "name": "lookup", - "description": "Semantic search", - "input_schema": { - "type": "object", - "properties": { - "hypotheticals": { - "type": "array", - "items": { "type": "string" } - } - }, - "required": ["hypotheticals"] - } -}; -const anthropic_create_note = { - "name": "create_note", - "description": "Create a note", - "input_schema": { - "type": "object", - "properties": { - "note": { - "type": "string" - } - }, - "required": ["note"] - } -}; -const openai_lookup = { - "type": "function", - "function": { - "name": "lookup", - "description": "Semantic search", - "parameters": { - "type": "object", - "properties": { - "hypotheticals": { - "type": "array", - "items": { "type": "string" } - } - }, - "required": ["hypotheticals"] - } - } -}; -const openai_create_note = { - "type": "function", - "function": { - "name": "create_note", - "description": "Create a note", - "parameters": { - "type": "object", - "properties": { - "note": { - "type": "string" - } - }, - "required": ["note"] +import test from 'ava'; +import dotenv from 'dotenv'; +import { SmartChatModel } from '../smart_chat_model.js'; +import { SmartChatModelAnthropicAdapter, SmartChatModelAnthropicRequestAdapter, SmartChatModelAnthropicResponseAdapter } from './anthropic.js'; +import platforms from '../platforms.json' assert { type: 'json' }; + +// Create an instance of SmartChatModel for Anthropic +const smart_chat_model_anthropic = new SmartChatModel({ + settings: { + platform_key: 'anthropic', + anthropic: { + api_key: 'test_api_key', + model_key: 'claude-2.1', } + }, + adapters: { + anthropic: SmartChatModelAnthropicAdapter } -}; -test('should handle tool_choice forcing lookup', t => { - const input = { - messages: [ - { role: 'user', content: 'Hello' }, - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5, - tool_choice: { - type: "function", - function: { - name: "lookup", - } - }, - tools: [openai_lookup] - }; - const expected = { - messages: [ - { role: 'user', content: 'Hello\nUse the "lookup" tool!' }, - ], - model: 'test-model', - system: 'Required: use the "lookup" tool!', - max_tokens: 100, - temperature: 0.5, - tools: [anthropic_lookup] - }; - t.deepEqual(chatml_to_anthropic(input), expected); }); -test('should handle tool_choice auto', t => { - const input = { - messages: [ - { role: 'user', content: 'Hello' }, - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5, - tool_choice: "auto", - tools: [openai_lookup, openai_create_note] - }; - const expected = { + +test('SmartChatModelAnthropicRequestAdapter converts OpenAI request to Anthropic schema', t => { + const openai_request = { + model: 'claude-2.1', messages: [ - { role: 'user', content: 'Hello' }, + { role: 'system', content: 'You are a helpful weather assistant.' }, + { role: 'user', content: 'Hello, how are you?' }, + { role: 'assistant', content: 'I\'m doing well, thank you for asking! How can I assist you today?' }, + { role: 'user', content: 'What\'s the weather like?' } ], - model: 'test-model', - // system: 'Required: use the "lookup" tool!', - max_tokens: 100, - temperature: 0.5, - tools: [anthropic_lookup, anthropic_create_note] - }; - t.deepEqual(chatml_to_anthropic(input), expected); -}); -test('should properly format tool role as tool result in user message', t => { - const input = { - messages: [ - { role: 'user', content: 'Hello' }, - { role: 'assistant', "tool_calls": [ - { - "id": "check_status", - "type": "function", - "function": { - "name": "check_status", - "arguments": "{\"status\":\"check\"}" + max_tokens: 1000, + temperature: 0.7, + stream: false, + tools: [ + { + type: 'function', + function: { + name: 'weather_api', + description: 'Get weather information for a location', + parameters: { + type: 'object', + properties: { + location: { type: 'string' }, + date: { type: 'string' } + }, + required: ['location'] } } - ]}, - { role: 'tool', content: '{"result": "ok"}' }, - { - role: 'assistant', - content: [ - { type: 'text', text: 'The result of the lookup tool was: OK; checking again' }, - ], - tool_calls: [ - { - id: 'check_status', - type: 'function', - function: { - name: 'check_status', - arguments: '{"status":"check2"}' - } - } - ] - }, - { role: 'tool', content: '{"result": "ok2"}' }, - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5, - }; - const expected = { - messages: [ - { role: 'user', content: 'Hello' }, - { role: 'assistant', content: [ - { type: 'tool_use', id: 'tool-1', name: 'check_status', input: {"status": "check"} } - ]}, - { role: 'user', content: [ - { - type: 'tool_result', - tool_use_id: 'tool-1', - content: '{"result": "ok"}' - } - ]}, - { role: 'assistant', content: [ - { type: 'tool_use', id: 'tool-2', name: 'check_status', input: {"status": "check2"} }, - { type: 'text', text: 'The result of the lookup tool was: OK; checking again' }, - ]}, - { role: 'user', content: [ - { - type: 'tool_result', - tool_use_id: 'tool-2', - content: '{"result": "ok2"}' - } - ]} - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5, - }; - t.deepEqual(chatml_to_anthropic(input), expected); -}); - -test('adds non-context system message correctly', t => { - const input = { - messages: [ - { role: 'user', content: 'Hello' }, - { role: 'system', content: 'Respond as if you are a helpful assistant' }, - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 - }; - - const expected = { - messages: [ - { role: 'user', content: 'Hello' }, + } ], - system: 'Respond as if you are a helpful assistant', - model: 'test-model', - max_tokens: 100, - temperature: 0.5 + tool_choice: 'auto' }; - const result = chatml_to_anthropic(input); - t.deepEqual(result, expected); + const request_adapter = new SmartChatModelAnthropicRequestAdapter(smart_chat_model_anthropic.adapter, openai_request); + const anthropic_request = request_adapter.to_anthropic(); + + t.is(anthropic_request.url, 'https://api.anthropic.com/v1/messages'); + t.is(anthropic_request.method, 'POST'); + t.deepEqual(anthropic_request.headers, { + ...platforms.anthropic.headers, + 'Content-Type': 'application/json', + 'x-api-key': 'test_api_key' + }); + + const body = JSON.parse(anthropic_request.body); + t.is(body.model, 'claude-2.1'); + t.is(body.max_tokens, 1000); + t.is(body.temperature, 0.7); + t.is(body.stream, false); + t.is(body.system, 'You are a helpful weather assistant.'); + t.deepEqual(body.messages, [ + { role: 'user', content: 'Hello, how are you?' }, + { role: 'assistant', content: 'I\'m doing well, thank you for asking! How can I assist you today?' }, + { role: 'user', content: 'What\'s the weather like?' } + ]); + t.deepEqual(body.tools, [ + { + name: 'weather_api', + description: 'Get weather information for a location', + parameters: openai_request.tools[0].function.parameters + } + ]); + t.deepEqual(body.tool_choice, { type: 'auto' }); }); -test('handles message content as an array', t => { - const input = { - messages: [ +test('SmartChatModelAnthropicResponseAdapter converts Anthropic response to OpenAI schema', t => { + const anthropic_response = { + id: 'msg_1234567890', + type: 'message', + role: 'assistant', + content: [ { - role: 'user', - content: [ - { - type: 'text', - text: "Hello" - } - ] + type: 'text', + text: 'To get the weather information, I\'ll need to use the weather API. Let me do that for you.' }, { - role: 'assistant', - content: [ - { - type: 'text', - text: 'Hi!' + type: 'tool_use', + tool_use: { + id: 'call_1234567890', + name: 'weather_api', + input: { + location: 'New York', + date: '2023-03-01' } - ] + } }, { - role: 'user', - content: [ - { - type: 'text', - text: 'How are you?' - } - ] + type: 'text', + text: 'Here is the weather information for New York: It\'s currently sunny with a temperature of 72°F (22°C). The forecast predicts clear skies throughout the day with a high of 78°F (26°C) and a low of 65°F (18°C). It\'s a perfect day to spend some time outdoors!' } ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 + model: 'claude-2.1', + stop_reason: 'end_turn', + stop_sequence: null, + usage: { + input_tokens: 20, + output_tokens: 25 + } }; + const response_adapter = new SmartChatModelAnthropicResponseAdapter(smart_chat_model_anthropic.adapter, anthropic_response); + const openai_response = response_adapter.to_openai(); - const expected = { - messages: [ - { role: 'user', content: [{type: 'text', text: 'Hello'}] }, - { role: 'assistant', content: [{type: 'text', text: 'Hi!'}] }, - { role: 'user', content: [{type: 'text', text: 'How are you?'}] } - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 - }; + t.is(openai_response.id, 'msg_1234567890'); + t.is(openai_response.object, 'chat.completion'); + t.truthy(openai_response.created); + t.deepEqual(openai_response.choices[0].message, { + role: 'assistant', + content: 'To get the weather information, I\'ll need to use the weather API. Let me do that for you.\n\nHere is the weather information for New York: It\'s currently sunny with a temperature of 72°F (22°C). The forecast predicts clear skies throughout the day with a high of 78°F (26°C) and a low of 65°F (18°C). It\'s a perfect day to spend some time outdoors!', + tool_calls: [ + { + id: 'call_1234567890', + type: 'function', + function: { + name: 'weather_api', + arguments: JSON.stringify({ + location: 'New York', + date: '2023-03-01' + }) + } + } + ] + }); + t.is(openai_response.choices[0].finish_reason, 'stop'); + t.deepEqual(openai_response.usage, { + prompt_tokens: 20, + completion_tokens: 25, + total_tokens: 45 + }); +}); +dotenv.config({ path: '../.env' }); - const result = chatml_to_anthropic(input); - t.deepEqual(result, expected); -}); +const ANTHROPIC_API_KEY = process.env.ANTHROPIC_API_KEY; -test('should handle image_url', t => { - const input = { - messages: [ - { role: 'user', content: [ - {type: 'text', text: 'Transcribe this image' }, - {type: 'image_url', image_url: {url: 'data:image/jpg;base64,Base64 image'}} - ]} - ], - model: 'test-model', - max_tokens: 100, - temperature: 0.5 - }; - const expected = { +test.serial('Live Anthropic Integration Test', async t => { + if (!ANTHROPIC_API_KEY) { + t.pass('Skipping live test: No Anthropic API key found in .env'); + return; + } + + const smart_chat_model = new SmartChatModel({ + settings: { + platform_key: 'anthropic', + anthropic: { + api_key: ANTHROPIC_API_KEY, + model_key: 'claude-2.1', + } + }, + adapters: { + anthropic: SmartChatModelAnthropicAdapter + } + }); + // fetch all models + const models = await smart_chat_model.get_models(); + console.log(JSON.stringify(models, null, 2)); + + const request = { messages: [ - { role: 'user', content: [ - {type: 'text', text: 'Transcribe this image'}, - {type: 'image', source: { - type: 'base64', - media_type: 'image/jpeg', - data: 'Base64 image' - }} - ]} + { role: 'user', content: 'What is the capital of Germany?' } ], - model: 'test-model', max_tokens: 100, - temperature: 0.5 + temperature: 0.7 }; - t.deepEqual(chatml_to_anthropic(input), expected); -}) + try { + const response = await smart_chat_model.complete(request); + console.log(JSON.stringify(response, null, 2)); + t.truthy(response.choices[0].message.content); + t.is(response.choices[0].message.role, 'assistant'); + t.truthy(response.usage.total_tokens > 0); + } catch (error) { + console.log(error); + t.fail(`Live test failed: ${error.message}`); + } +}); diff --git a/smart-chat-model/adapters/cohere.js b/smart-chat-model/adapters/cohere.js index c9f4ddfb..48f9e6e3 100644 --- a/smart-chat-model/adapters/cohere.js +++ b/smart-chat-model/adapters/cohere.js @@ -1,95 +1,196 @@ -/** - * CohereAdapter class is designed to adapt the SmartChatModel's interaction with the Cohere API. - * It provides methods to prepare request bodies, handle streaming data, and extract message content from responses. - */ -class CohereAdapter { - /** - * Converts a ChatML object to a format suitable for a request to the Cohere API. - * @param {Object} chatml - The ChatML object containing the chat history and other parameters. - * @returns {Object} The request body formatted for the Cohere API. - */ - prepare_request_body(chatml) { return chatml_to_cohere(chatml); } - - /** - * Extracts the message content from a JSON response from the Cohere API. - * @param {Object} json - The JSON response object from which to extract the text content. - * @returns {string} The extracted text content from the response. - */ - get_message_content(json) { return json.text; } - - /** - * Processes streaming data received from the Cohere API and extracts text chunks. - * This method handles the accumulation of text data over multiple events and manages the state of the stream. - * @param {Object} event - The event object containing streaming data. - * @returns {string} The accumulated text chunk extracted from the stream. - */ - get_text_chunk_from_stream(event) { - if(!this.last_line_index) this.last_line_index = 0; - clearTimeout(this.last_line_timeout); - this.last_line_timeout = setTimeout(() => { - this.last_line_index = 0; - }, 10000); - const data = event.source.xhr.responseText; - // split by newline and get last - const lines = data.split('\n').slice(this.last_line_index); - this.last_line_index += lines.length; - const text_chunk = lines - .filter((line) => line.trim() !== '') - .map((line) => { - console.log(line); - const json = JSON.parse(line); - if(json.event_type === 'stream-end') { - console.log('stream-end'); - this.end_of_stream = true; - setTimeout(() => { - this.end_of_stream = false; - }, 3000); - return ''; - } - return json.text; - }) - .join(''); - console.log(text_chunk); - return text_chunk; +import { SmartChatModelApiAdapter, SmartChatModelRequestAdapter, SmartChatModelResponseAdapter } from './_api.js'; + +export class SmartChatModelCohereAdapter extends SmartChatModelApiAdapter { + get req_adapter() { return SmartChatModelCohereRequestAdapter; } + get res_adapter() { return SmartChatModelCohereResponseAdapter; } + + async count_tokens(input) { + const req = { + url: `${this.platform.endpoint}/tokenize`, + method: "POST", + headers: { + "Content-Type": "application/json", + "Authorization": `Bearer ${this.api_key}` + }, + body: JSON.stringify({ text: typeof input === 'string' ? input : JSON.stringify(input) }) + }; + const resp = await this.http_adapter.request(req); + return resp.json.tokens.length; + } + + get endpoint() { + return `${this.platform.endpoint}`; } - /** - * Determines if the end of the stream has been reached based on the event data. - * @param {Object} event - The event object that may indicate the end of the stream. - * @returns {boolean} True if the end of the stream is indicated, false otherwise. - */ - is_end_of_stream(event) { return this.end_of_stream; } + parse_model_data(model_data) { + return model_data.models + .filter(model => model.name.startsWith('command-')) + .map(model => ({ + model_name: model.name, + key: model.name, + max_input_tokens: model.context_length, + tokenizer_url: model.tokenizer_url, + finetuned: model.finetuned, + description: `Max input tokens: ${model.context_length}, Finetuned: ${model.finetuned}`, + raw: model + })) + .sort((a, b) => a.model_name.localeCompare(b.model_name)); + } } -exports.CohereAdapter = CohereAdapter; - -/** - * Converts a ChatML object into a format suitable for the Cohere API. - * This function prepares the data by structuring it according to the requirements of the Cohere API, - * including the model to use, the chat history excluding the last user message, and the last message separately. - * - * @param {Object} chatml - The ChatML object containing the model, messages, and other parameters like temperature. - * @returns {Object} The formatted object for the Cohere API request, containing the model, chat history, last message, and temperature. - */ -function chatml_to_cohere(chatml) { - const cohere = { - model: chatml.model, - // skip last user message - chat_history: chatml.messages - .slice(0, -1) - .map((message) => ({ - role: message.role, - message: parse_message_content_to_string(message), - })) - , - message: parse_message_content_to_string(chatml.messages[chatml.messages.length - 1]), - temperature: chatml.temperature, - // stream: chatml.stream // currently not supported + +export class SmartChatModelCohereRequestAdapter extends SmartChatModelRequestAdapter { + to_platform() { return this.to_cohere(); } + + to_cohere() { + const cohere_body = { + model: this.model, + message: this._get_latest_user_message(), + chat_history: this._transform_messages_to_cohere_chat_history(), + max_tokens: this.max_tokens, + temperature: this.temperature, + stream: this.stream, + ...(this.tools && { tools: this._transform_tools_to_cohere() }), + ...(this._req.tool_choice && { tool_choice: this._req.tool_choice }), + ...(this._req.preamble && { preamble: this._req.preamble }), + ...(this._req.conversation_id && { conversation_id: this._req.conversation_id }), + ...(this._req.connectors && { connectors: this._req.connectors }), + ...(this._req.documents && { documents: this._req.documents }), }; - return cohere; -} -exports.chatml_to_cohere = chatml_to_cohere; -function parse_message_content_to_string(message) { - return Array.isArray(message.content) ? message.content.filter(c => c.type === 'text').map(c => c.text).join('\n') : message.content; + if (this._req.response_format) { + cohere_body.response_format = { + type: this._req.response_format.type, + ...(this._req.response_format.schema && { schema: this._req.response_format.schema }) + }; + } + + return { + url: this.adapter.endpoint, + method: 'POST', + headers: this.get_headers(), + body: JSON.stringify(cohere_body) + }; + } + + _get_latest_user_message() { + // throw if image input + if (this.messages.some(msg => Array.isArray(msg.content) && msg.content.some(part => part.type === 'image_url'))) { + throw new Error("Cohere API does not support image input"); + } + const user_messages = this.messages.filter(msg => msg.role === 'user'); + return user_messages[user_messages.length - 1]?.content || ''; + } + + _transform_messages_to_cohere_chat_history() { + return this.messages.slice(0, -1).map(message => ({ + role: this._get_cohere_role(message.role), + message: this._get_cohere_content(message.content) + })); + } + + _get_cohere_role(role) { + const role_map = { + system: 'SYSTEM', + user: 'USER', + assistant: 'CHATBOT', + function: 'CHATBOT' + }; + return role_map[role] || role.toUpperCase(); + } + + _get_cohere_content(content) { + if (Array.isArray(content)) { + for (const part of content) { + if (part.type === 'image_url') { + throw new Error("Cohere API does not support image input"); + } + } + return content.map(part => { + if (part.type === 'text') return part.text; + return JSON.stringify(part); + }).join('\n'); + } + return content; + } + + _transform_tools_to_cohere() { + return this.tools.map(tool => ({ + name: tool.function.name, + description: tool.function.description, + parameters: tool.function.parameters + })); + } } +export class SmartChatModelCohereResponseAdapter extends SmartChatModelResponseAdapter { + to_openai() { + if (this._res.message) { + throw new Error(this._res.message); + } + + return { + id: this._res.generation_id || 'cohere_' + Date.now(), + object: 'chat.completion', + created: Date.now(), + model: this.adapter.model_key, + choices: [ + { + index: 0, + message: this._transform_message_to_openai(), + finish_reason: this._get_openai_finish_reason(this._res.finish_reason) + } + ], + usage: this._transform_usage_to_openai() + }; + } + + _transform_message_to_openai() { + const message = { + role: 'assistant', + content: this._res.text || '' + }; + + if (this._res.citations) { + message.citations = this._res.citations; + } + + if (this._res.documents) { + message.documents = this._res.documents; + } + + if (this._res.search_queries) { + message.search_queries = this._res.search_queries; + } + + if (this._res.search_results) { + message.search_results = this._res.search_results; + } + + return message; + } + + _get_openai_finish_reason(finish_reason) { + const reason_map = { + 'COMPLETE': 'stop', + 'MAX_TOKENS': 'length', + 'ERROR': 'error', + 'STOP_SEQUENCE': 'stop' + }; + return reason_map[finish_reason] || 'stop'; + } + + _transform_usage_to_openai() { + if (!this._res.meta || !this._res.meta.billed_units) { + return { + prompt_tokens: null, + completion_tokens: null, + total_tokens: null + }; + } + return { + prompt_tokens: this._res.meta.billed_units.input_tokens || null, + completion_tokens: this._res.meta.billed_units.output_tokens || null, + total_tokens: (this._res.meta.billed_units.input_tokens || 0) + (this._res.meta.billed_units.output_tokens || 0) + }; + } +} \ No newline at end of file diff --git a/smart-chat-model/adapters/cohere.test.js b/smart-chat-model/adapters/cohere.test.js index b3037dc3..e7f0e7ff 100644 --- a/smart-chat-model/adapters/cohere.test.js +++ b/smart-chat-model/adapters/cohere.test.js @@ -1,63 +1,235 @@ -const test = require('ava'); -const { chatml_to_cohere } = require('./cohere'); +import test from 'ava'; +import dotenv from 'dotenv'; +import { SmartChatModel } from '../smart_chat_model.js'; +import { SmartChatModelCohereAdapter, SmartChatModelCohereRequestAdapter, SmartChatModelCohereResponseAdapter } from './cohere.js'; -test('reformats chatml to cohere format', (t) => { - const input = { - model: 'command-r', +dotenv.config({ path: '../.env' }); + +const COHERE_API_KEY = process.env.COHERE_API_KEY; + +const smart_chat_model = new SmartChatModel({ + settings: { + platform_key: 'cohere', + cohere: { + api_key: 'test_api_key', + model_key: 'command', + } + }, + adapters: { + cohere: SmartChatModelCohereAdapter + } +}); + +test('SmartChatModelCohereRequestAdapter converts OpenAI request to Cohere schema', t => { + const openai_request = { + model: 'command', messages: [ - { role: 'system', content: 'System message' }, - { role: 'user', content: 'User message' }, - { role: 'assistant', content: 'Assistant message' }, - { role: 'user', content: 'User message 2' } - ], - temperature: 0.5, - topK: 10, - topP: 0.8, - max_tokens: 100, - stopSequences: ['stop'], - n: 2 + { role: 'system', content: 'You are a helpful assistant.' }, + { role: 'user', content: 'Hello, how are you?' }, + { role: 'assistant', content: 'I\'m doing well, thank you for asking! How can I assist you today?' }, + { role: 'user', content: 'What\'s the weather like?' } + ], + max_tokens: 1000, + temperature: 0.7, + stream: false, + tools: [ + { + type: 'function', + function: { + name: 'get_weather', + description: 'Get weather information for a location', + parameters: { + type: 'object', + properties: { + location: { type: 'string' }, + unit: { type: 'string', enum: ['celsius', 'fahrenheit'] } + }, + required: ['location'] + } + } + } + ], + tool_choice: 'auto', + preamble: 'This is a preamble', + conversation_id: 'conv_123', + response_format: { type: 'json_object' } }; - const expected = { - model: 'command-r', - chat_history: [ - { role: 'system', message: 'System message' }, - { role: 'user', message: 'User message' }, - { role: 'assistant', message: 'Assistant message' }, - ], - message: 'User message 2', - temperature: 0.5, + + const request_adapter = new SmartChatModelCohereRequestAdapter(smart_chat_model.adapter, openai_request); + const cohere_request = request_adapter.to_cohere(); + + t.is(cohere_request.method, 'POST'); + t.deepEqual(cohere_request.headers, { + 'Content-Type': 'application/json', + 'Authorization': 'Bearer test_api_key' + }); + + const body = JSON.parse(cohere_request.body); + t.is(body.model, 'command'); + t.is(body.max_tokens, 1000); + t.is(body.temperature, 0.7); + t.is(body.stream, false); + t.is(body.message, 'What\'s the weather like?'); + t.deepEqual(body.chat_history, [ + { role: 'SYSTEM', message: 'You are a helpful assistant.' }, + { role: 'USER', message: 'Hello, how are you?' }, + { role: 'CHATBOT', message: 'I\'m doing well, thank you for asking! How can I assist you today?' } + ]); + t.deepEqual(body.tools, [{ + name: 'get_weather', + description: 'Get weather information for a location', + parameters: openai_request.tools[0].function.parameters + }]); + t.is(body.tool_choice, 'auto'); + t.is(body.preamble, 'This is a preamble'); + t.is(body.conversation_id, 'conv_123'); + t.deepEqual(body.response_format, { type: 'json_object' }); +}); + +test('SmartChatModelCohereRequestAdapter throws error for image input', t => { + const openai_request = { + model: 'command', + messages: [ + { role: 'user', content: [ + { type: 'text', text: 'What\'s in this image?' }, + { type: 'image_url', image_url: { url: 'data:image/jpeg;base64,/9j/4AAQSkZJRgABAQEAYABgAAD/2wBDAA...' } } + ] } + ], + max_tokens: 500, + temperature: 0.8 }; - const cohere = chatml_to_cohere(input); - t.deepEqual(cohere, expected); + const request_adapter = new SmartChatModelCohereRequestAdapter(smart_chat_model.adapter, openai_request); + + const error = t.throws(() => { + request_adapter.to_platform(); + }, { instanceOf: Error }); + + t.is(error.message, "Cohere API does not support image input"); }); -test('handles message content as an array', (t) => { - const input = { - model: 'command-r', + +test('SmartChatModelCohereResponseAdapter converts Cohere response to OpenAI schema', t => { + const cohere_response = { + text: 'The weather in New York is currently sunny with a temperature of 72°F (22°C).', + generation_id: 'gen_123456789', + finish_reason: 'COMPLETE', + citations: [ + { start: 0, end: 10, text: 'The weather', document_ids: ['doc1'] } + ], + documents: [ + { id: 'doc1', title: 'Weather Report', snippet: 'New York weather report', url: 'http://example.com', timestamp: '2023-06-01T12:00:00Z' } + ], + search_queries: [ + { text: 'New York weather', generation_id: 'gen_987654321' } + ], + search_results: [ + { connector: { id: 'web' }, document_ids: ['doc1'], search_query: { text: 'New York weather', generation_id: 'gen_987654321' } } + ], + meta: { + api_version: { version: '1.0' }, + billed_units: { input_tokens: 20, output_tokens: 15 }, + tokens: { input_tokens: 20, output_tokens: 15 } + } + }; + + const response_adapter = new SmartChatModelCohereResponseAdapter(smart_chat_model.adapter, cohere_response); + const openai_response = response_adapter.to_openai(); + + t.is(openai_response.id, 'gen_123456789'); + t.is(openai_response.object, 'chat.completion'); + t.truthy(openai_response.created); + t.deepEqual(openai_response.choices[0].message, { + role: 'assistant', + content: 'The weather in New York is currently sunny with a temperature of 72°F (22°C).', + citations: cohere_response.citations, + documents: cohere_response.documents, + search_queries: cohere_response.search_queries, + search_results: cohere_response.search_results + }); + t.is(openai_response.choices[0].finish_reason, 'stop'); + t.deepEqual(openai_response.usage, { + prompt_tokens: 20, + completion_tokens: 15, + total_tokens: 35 + }); +}); + +test.serial('Live Cohere Integration Test', async t => { + if (!COHERE_API_KEY) { + t.pass('Skipping live test: No Cohere API key found in .env'); + return; + } + + const smart_chat_model = new SmartChatModel({ + settings: { + platform_key: 'cohere', + cohere: { + api_key: COHERE_API_KEY, + model_key: 'command', + } + }, + adapters: { + cohere: SmartChatModelCohereAdapter + } + }); + + const request = { messages: [ - { role: 'system', content: 'System message' }, - { role: 'user', content: [ { type: 'text', text: 'User message' } ]}, - { role: 'assistant', content: [ { type: 'text', text: 'Assistant message' } ]}, - { role: 'user', content: [ { type: 'text', text: 'User message 2' } ]} - ], - temperature: 0.5, - topK: 10, - topP: 0.8, + { role: 'user', content: 'What is the capital of France?' } + ], max_tokens: 100, - stopSequences: ['stop'], - n: 2 - }; - const expected = { - model: 'command-r', - chat_history: [ - { role: 'system', message: 'System message' }, - { role: 'user', message: 'User message' }, - { role: 'assistant', message: 'Assistant message' }, - ], - message: 'User message 2', - temperature: 0.5, + temperature: 0.7 }; - const cohere = chatml_to_cohere(input); - t.deepEqual(cohere, expected); + try { + const response = await smart_chat_model.complete(request); + console.log(JSON.stringify(response, null, 2)); + t.truthy(response.choices[0].message.content); + t.is(response.choices[0].message.role, 'assistant'); + t.truthy(response.usage.prompt_tokens > 0); + t.truthy(response.usage.completion_tokens > 0); + t.truthy(response.usage.total_tokens > 0); + } catch (error) { + console.error('Error details:', error); + t.fail(`Live test failed: ${error.message}`); + } +}); + +test.serial('Live Cohere get_models Integration Test', async t => { + if (!COHERE_API_KEY) { + t.pass('Skipping live test: No Cohere API key found in .env'); + return; + } + + const smart_chat_model = new SmartChatModel({ + settings: { + platform_key: 'cohere', + cohere: { + api_key: COHERE_API_KEY, + model_key: 'command', + } + }, + adapters: { + cohere: SmartChatModelCohereAdapter + } + }); + + try { + const models = await smart_chat_model.get_models(); + // console.log(JSON.stringify(models, null, 2)); + t.true(Array.isArray(models)); + t.true(models.length > 0); + t.true(models.every(model => + model.hasOwnProperty('model_name') && + model.hasOwnProperty('key') && + model.hasOwnProperty('max_input_tokens') && + model.hasOwnProperty('tokenizer_url') && + model.hasOwnProperty('finetuned') && + model.hasOwnProperty('description') && + model.hasOwnProperty('raw') + )); + } catch (error) { + console.error(error); + t.fail(`Live test failed: ${error.message}`); + } }); \ No newline at end of file diff --git a/smart-chat-model-v2/adapters/google.js b/smart-chat-model/adapters/google.js similarity index 100% rename from smart-chat-model-v2/adapters/google.js rename to smart-chat-model/adapters/google.js diff --git a/smart-chat-model-v2/adapters/google.test.js b/smart-chat-model/adapters/google.test.js similarity index 100% rename from smart-chat-model-v2/adapters/google.test.js rename to smart-chat-model/adapters/google.test.js diff --git a/smart-chat-model/adapters/open_router.js b/smart-chat-model/adapters/open_router.js index 96a2db1c..faa72b23 100644 --- a/smart-chat-model/adapters/open_router.js +++ b/smart-chat-model/adapters/open_router.js @@ -1,39 +1,41 @@ -class OpenRouterAdapter { - constructor(model) { this.model = model; } - get_tool_call(json) { - // handles Gemini format - if(json.choices[0].message.tool_calls){ - return json.choices[0].message.tool_calls[0].function; - } - // handles mistral format - if(json.choices[0].message.content.includes("function")){ - const content = JSON.parse(json.choices[0].message.content); - if(!content.function) return null; - return content; - } - return null; +import { SmartChatModelApiAdapter, SmartChatModelRequestAdapter, SmartChatModelResponseAdapter } from './_api.js'; + +export class SmartChatModelOpenRouterAdapter extends SmartChatModelApiAdapter { + get req_adapter() { return SmartChatModelOpenRouterRequestAdapter; } + get res_adapter() { return SmartChatModelOpenRouterResponseAdapter; } + + async count_tokens(input) { + // OpenRouter doesn't provide a token counting endpoint, so we'll use a rough estimate + const text = typeof input === 'string' ? input : JSON.stringify(input); + return Math.ceil(text.length / 4); // Rough estimate: 1 token ≈ 4 characters } - get_tool_name(tool_call) { - if(tool_call.function) return tool_call.function; // mistral format - if(tool_call.name) return tool_call.name; // gemini format - return null; + + get endpoint() { + return 'https://openrouter.ai/api/v1/chat/completions'; } - get_tool_call_content(tool_call) { - if(tool_call.parameters) return tool_call.parameters; // mistral format - // handle gemini format - if(tool_call.arguments){ - const args = JSON.parse(tool_call.arguments); - // prevent escape character issues - Object.entries(args).forEach(([key, value]) => { - args[key] = value.replace(/\\n/g, "\n") - .replace(/\\t/g, "\t") - .replace(/\\r/g, "\r") - .replace(/\\'/g, "'") - .replace(/\\"/g, '"') - }); - return args; + + parse_model_data(model_data) { + if(model_data.data) { + model_data = model_data.data; } - return null; + return model_data.map(model => ({ + model_name: model.id, + key: model.id, + max_input_tokens: model.context_length, + description: model.name, + actions: model.description.includes('tool use') || model.description.includes('function call'), + multimodal: model.architecture.modality === 'multimodal', + raw: model + })); } } -exports.OpenRouterAdapter = OpenRouterAdapter; \ No newline at end of file + +export class SmartChatModelOpenRouterRequestAdapter extends SmartChatModelRequestAdapter { + to_platform() { return this.to_openai(); } + +} + +export class SmartChatModelOpenRouterResponseAdapter extends SmartChatModelResponseAdapter { + to_platform() { return this.to_openai(); } + get object() { return 'chat.completion'; } +} \ No newline at end of file diff --git a/smart-chat-model-v2/adapters/open_router.test.js b/smart-chat-model/adapters/open_router.test.js similarity index 100% rename from smart-chat-model-v2/adapters/open_router.test.js rename to smart-chat-model/adapters/open_router.test.js diff --git a/smart-chat-model-v2/adapters/openai.js b/smart-chat-model/adapters/openai.js similarity index 100% rename from smart-chat-model-v2/adapters/openai.js rename to smart-chat-model/adapters/openai.js diff --git a/smart-chat-model-v2/adapters/openai.test.js b/smart-chat-model/adapters/openai.test.js similarity index 100% rename from smart-chat-model-v2/adapters/openai.test.js rename to smart-chat-model/adapters/openai.test.js diff --git a/smart-chat-model-v2/index.js b/smart-chat-model/index.js similarity index 100% rename from smart-chat-model-v2/index.js rename to smart-chat-model/index.js diff --git a/smart-chat-model-v2/package-lock.json b/smart-chat-model/package-lock.json similarity index 100% rename from smart-chat-model-v2/package-lock.json rename to smart-chat-model/package-lock.json diff --git a/smart-chat-model/package.json b/smart-chat-model/package.json index b4166635..0737c2b4 100644 --- a/smart-chat-model/package.json +++ b/smart-chat-model/package.json @@ -1,10 +1,11 @@ { "name": "smart-chat-model", "author": "Brian Joseph Petro (🌴 Brian)", + "type": "module", "license": "MIT", "version": "1.0.5", "description": "no-nonsense adapter for Anthropic Claude, Google Gemini, Cohere & more with OpenAI style API interface.", - "main": "smart_chat_model.js", + "main": "index.js", "scripts": { "test": "npx ava" }, @@ -23,8 +24,13 @@ "url": "https://github.com/brianpetro/jsbrains/issues" }, "homepage": "https://jsbrains.org", + "dependencies": { + "smart-http-request": "../smart-http-request", + "smart-model": "../smart-model" + }, "devDependencies": { "ava": "^6.1.2", + "dotenv": "^16.4.5", "esbuild": "^0.20.2" } } diff --git a/smart-chat-model/platforms.json b/smart-chat-model/platforms.json index 31b5e9fb..08f561ab 100644 --- a/smart-chat-model/platforms.json +++ b/smart-chat-model/platforms.json @@ -5,7 +5,7 @@ "endpoint": "https://api.openai.com/v1/chat/completions", "streaming": true, "actions": true, - "fetch_models": true, + "models_endpoint": "https://api.openai.com/v1/models", "default_model": "gpt-3.5-turbo", "signup_url": "https://platform.openai.com/api-keys" }, @@ -18,7 +18,7 @@ "streaming": true, "actions": true, "adapter": "Gemini", - "fetch_models": true, + "models_endpoint": "https://generativelanguage.googleapis.com/v1beta/models", "default_model": "gemini-1.5-pro", "signup_url": "https://ai.google.dev/" }, @@ -28,8 +28,8 @@ "endpoint": "https://openrouter.ai/api/v1/chat/completions", "streaming": true, "adapter": "OpenRouter", - "fetch_models": true, - "default_model": "meta-llama/llama-3.1-8b-instruct:free", + "models_endpoint": "https://openrouter.ai/api/v1/models", + "default_model": "mistralai/mistral-7b-instruct:free", "signup_url": "https://accounts.openrouter.ai/sign-up?redirect_url=https%3A%2F%2Fopenrouter.ai%2Fkeys" }, "cohere": { @@ -38,7 +38,7 @@ "endpoint": "https://api.cohere.ai/v1/chat", "streaming": false, "adapter": "Cohere", - "fetch_models": true, + "models_endpoint": "https://api.cohere.ai/v1/models", "default_model": "command-r", "signup_url": "https://dashboard.cohere.com/welcome/register?redirect_uri=%2Fapi-keys" }, @@ -54,7 +54,41 @@ }, "adapter": "Anthropic", "actions": true, - "fetch_models": true, + "models_endpoint": false, + "models": [ + { + "key": "claude-3-opus-20240229", + "model_name": "claude-3-opus-20240229", + "description": "Anthropic's Claude Opus", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + { + "key": "claude-3-5-sonnet-20240620", + "model_name": "claude-3.5-sonnet-20240620", + "description": "Anthropic's Claude Sonnet", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + { + "key": "claude-3-haiku-20240307", + "model_name": "claude-3-haiku-20240307", + "description": "Anthropic's Claude Haiku", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + }, + { + "key": "claude-3-sonnet-20240229", + "model_name": "claude-3-sonnet-20240229", + "description": "Anthropic's Claude Sonnet", + "max_input_tokens": 200000, + "max_output_tokens": 4000, + "multimodal": true + } + ], "default_model": "claude-3-sonnet-20240229", "signup_url": "https://console.anthropic.com/login?returnTo=%2Fsettings%2Fkeys" }, diff --git a/smart-chat-model-v2/schemas/anthropic_request.json b/smart-chat-model/schemas/anthropic_request.json similarity index 100% rename from smart-chat-model-v2/schemas/anthropic_request.json rename to smart-chat-model/schemas/anthropic_request.json diff --git a/smart-chat-model-v2/schemas/anthropic_response.json b/smart-chat-model/schemas/anthropic_response.json similarity index 100% rename from smart-chat-model-v2/schemas/anthropic_response.json rename to smart-chat-model/schemas/anthropic_response.json diff --git a/smart-chat-model-v2/schemas/cohere_request.json b/smart-chat-model/schemas/cohere_request.json similarity index 100% rename from smart-chat-model-v2/schemas/cohere_request.json rename to smart-chat-model/schemas/cohere_request.json diff --git a/smart-chat-model-v2/schemas/cohere_response.json b/smart-chat-model/schemas/cohere_response.json similarity index 100% rename from smart-chat-model-v2/schemas/cohere_response.json rename to smart-chat-model/schemas/cohere_response.json diff --git a/smart-chat-model-v2/schemas/google_request.json b/smart-chat-model/schemas/google_request.json similarity index 100% rename from smart-chat-model-v2/schemas/google_request.json rename to smart-chat-model/schemas/google_request.json diff --git a/smart-chat-model-v2/schemas/google_response.json b/smart-chat-model/schemas/google_response.json similarity index 100% rename from smart-chat-model-v2/schemas/google_response.json rename to smart-chat-model/schemas/google_response.json diff --git a/smart-chat-model-v2/schemas/open_router_request.json b/smart-chat-model/schemas/open_router_request.json similarity index 100% rename from smart-chat-model-v2/schemas/open_router_request.json rename to smart-chat-model/schemas/open_router_request.json diff --git a/smart-chat-model-v2/schemas/open_router_response.json b/smart-chat-model/schemas/open_router_response.json similarity index 100% rename from smart-chat-model-v2/schemas/open_router_response.json rename to smart-chat-model/schemas/open_router_response.json diff --git a/smart-chat-model-v2/schemas/openai_request.json b/smart-chat-model/schemas/openai_request.json similarity index 100% rename from smart-chat-model-v2/schemas/openai_request.json rename to smart-chat-model/schemas/openai_request.json diff --git a/smart-chat-model-v2/schemas/openai_response.json b/smart-chat-model/schemas/openai_response.json similarity index 100% rename from smart-chat-model-v2/schemas/openai_response.json rename to smart-chat-model/schemas/openai_response.json diff --git a/smart-chat-model/smart_chat_model.js b/smart-chat-model/smart_chat_model.js index 9422a3bc..dd4d287a 100644 --- a/smart-chat-model/smart_chat_model.js +++ b/smart-chat-model/smart_chat_model.js @@ -1,466 +1,125 @@ -// Copyright (c) Brian Joseph Petro - -// Permission is hereby granted, free of charge, to any person obtaining -// a copy of this software and associated documentation files (the -// "Software"), to deal in the Software without restriction, including -// without limitation the rights to use, copy, modify, merge, publish, -// distribute, sublicense, and/or sell copies of the Software, and to -// permit persons to whom the Software is furnished to do so, subject to -// the following conditions: - -// The above copyright notice and this permission notice shall be -// included in all copies or substantial portions of the Software. - -// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, -// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF -// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND -// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE -// LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION -// OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION -// WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. - -const adapters = require('./adapters'); -const platforms = require('./platforms.json'); -const { is_valid_tool_call } = require('./utils/is_valid_tool_call'); -const { SmartStreamer } = require('./streamer'); -const fetch_models = require("./models/fetch"); -/** - * SmartChatModel class provides functionalities to handle chat interactions with various models and adapters. - * It supports streaming and non-streaming responses, tool calls, and customizations through options. - */ -class SmartChatModel { - /** - * Constructs an instance of SmartChatModel with specified environment, model key, and options. - * @param {Object} main - The main environment context, typically containing configurations and state. - * @param {string} platform_key - Key to select the specific model configuration from models.json. - * @param {Object} model_config - Optional parameters to override model configurations. - */ - constructor(main, platform_key, model_config={}) { - this.env = main; - this.main = this.env; // DEPRECATED - this.config = { - ...(platforms[platform_key] || {}), - ...model_config, // override default platform config - } - console.log(JSON.stringify(this.config)); - this.platform_key = platform_key; - this.active_stream = null; - this._request_adapter = null; - this.platforms = platforms; - if(this.config.adapter) this.adapter = new adapters[this.config.adapter](this); - if(this.adapter) console.log("has chat model adapter"); - } - static get models() { return platforms; } // DEPRECATED (confusing name) - // - static get platforms() { - return Object.keys(platforms).map(key => ({ - key, - ...platforms[key], - })); - } +import { SmartHttpRequest } from "smart-http-request"; +import platforms from "./platforms.json" assert { type: "json" }; +import { SmartModel } from "smart-model"; +export class SmartChatModel extends SmartModel { + constructor(opts){ + super(opts); + this._adapters = {}; + this._http_adapter = null; + } + async complete(req){ return await this.adapter.complete(req); } + get_platforms_as_options(){ return Object.keys(platforms).map(key => ({ value: key })); } + async get_models(refresh=false){ return await this.adapter.get_models(refresh); } + async get_models_as_options(){ + const models = await this.adapter.get_models(); + return Object.values(models).map(model => ({ value: model.key })); + } + async stream(req, handlers={}){ return await this.adapter.stream(req, handlers); } + stop_stream() { this.adapter.stop_stream(); } + async test_api_key(){ return await this.adapter.test_api_key(); } + async count_tokens(input){ return await this.adapter.count_tokens(input); } + get adapters() { return this.opts.adapters; } + get adapter() { + if(!this._adapters[this.platform_key]){ + this._adapters[this.platform_key] = new this.adapters[this.platform_key](this); + } + return this._adapters[this.platform_key]; + } + get http_adapter() { + if(!this._http_adapter){ + if(this.opts.http_adapter) this._http_adapter = this.opts.http_adapter; + else this._http_adapter = new SmartHttpRequest(); + } + return this._http_adapter; + } + get model_key() { return this.platform_settings?.model_key; } get platform() { return platforms[this.platform_key]; } - get default_opts() { - return { - temperature: 0.3, - top_p: 1, - presence_penalty: 0, - frequency_penalty: 0, - n: 1, - model: this.model_name, - max_tokens: this.max_output_tokens, - }; - } - async request_middlewares(opts) { return opts; } - /** - * Completes the chat interaction by processing the provided options, making an API request, and handling the response. - * This method supports both streaming and non-streaming responses, and can handle tool calls if specified in the response. - * - * @param {Object} opts - The options for the chat completion which may include settings like temperature, max tokens, etc. - * @param {boolean} render - Flag to determine if the response should be rendered in the UI. - * @returns {Promise} - Returns the chat response content or handles tool outputs recursively. In case of errors, it may return an error message. - */ - async complete(opts = {}, render = true) { - const prepared_opts = await this.prepare_options(opts); - const request = this.create_request(prepared_opts); - - try { - if (prepared_opts.stream) { - return await this.handle_streaming_request(request, render); - } - return await this.handle_non_streaming_request(request, prepared_opts, render); - } catch (err) { - return this.handle_error(err, render); - } - } - - async prepare_options(opts) { - if (!this.base_model_config) { - this.base_model_config = await this.get_base_model_config(); - this.config = { - ...this.base_model_config, - ...this.config, - }; - } - - const prepared_opts = { - ...this.default_opts, - messages: (await this.current?.get_chat_ml())?.messages || [], - ...opts, - }; - - if (prepared_opts.stream !== false && this.config.streaming && !this.current?.tool_choice) { - prepared_opts.stream = true; - } else { - prepared_opts.stream = false; - } - - return this.request_middlewares(JSON.parse(JSON.stringify(prepared_opts))); - } - - create_request(opts) { - const req = { - headers: { - "Content-Type": "application/json", - Authorization: `Bearer ${this.api_key}` + get platform_key() { return this.settings.platform_key; } + get platform_settings() { + if(!this.settings[this.platform_key]) this.settings[this.platform_key] = {}; + return this.settings[this.platform_key]; + } + get settings() { return this.opts.settings; } + get settings_config() { + const _settings_config = { + platform_key: { + name: 'Chat Model Platform', + type: "dropdown", + description: "Select a chat model platform to use with Smart Chat.", + options_callback: 'get_platforms_as_options', + is_scope: true, // trigger re-render of settings when changed + // callback: 'changed_chat_model_platform', }, - method: "POST", - }; - - if (this.config.headers) { - req.headers = { ...req.headers, ...this.config.headers }; - } - - if (this.config.api_key_header) { - if (this.config.api_key_header !== 'none') { - req.headers[this.config.api_key_header] = this.api_key; - } - delete req.headers.Authorization; - } - - const body = typeof this.env.actions?.prepare_request_body === 'function' - ? this.env.actions.prepare_request_body(opts) - : { ...opts }; - - req.body = JSON.stringify(typeof this.adapter?.prepare_request_body === 'function' - ? this.adapter.prepare_request_body(body) - : body); - - return req; - } - - async handle_streaming_request(request, render) { - return this.stream(request); - } - - async handle_non_streaming_request(request, opts, render) { - const resp_json = await this.request(request); - - if (resp_json.error) { - return this.handle_api_error(resp_json.error, render); - } - - // if is tool_call, handle tool_call and return - const tool_call = this.get_tool_call(resp_json); - if (tool_call) { - return this.handle_tool_call(tool_call, opts, render); - } - - const message_content = this.get_message_content(resp_json); - if (render) { - this.done_handler(message_content); - } - return message_content; - } - - handle_api_error(error, render) { - console.error(error); - if (render) { - if(typeof error?.message === 'string') this.done_handler("*API Error: " + error.message + "*"); - else this.done_handler("*API Error. See console logs for details.*"); - } - return "*API Error. See console logs for details.*"; - } - - async handle_tool_call(tool_call, opts, render) { - if (this.env.chats?.current?.tool_choice) { - this.env.chats.current.tool_choice = null; - } - - const tool_name = this.get_tool_name(tool_call); - const tool_call_content = this.get_tool_call_content(tool_call); - const tools = opts.tools || []; - const tool = tools.find((t) => t.function.name === tool_name); - const tool_handler = this.get_tool_handler(tool_name); - - if (!tool_handler || !is_valid_tool_call(tool, tool_call_content)) { - return this.handle_invalid_tool_call(tool_name, tool_call_content); - } - - await this.add_tool_call_to_chat(tool_name, tool_call_content); - const tool_output = await tool_handler(this.env, tool_call_content); - - if (tool_output) { - await this.current.add_tool_output(tool_name, tool_output); - this.current.tool_choice = 'none'; // prevent subsequent tool calls from preventing completion - return this.complete({}); // empty opts - } - } - - handle_invalid_tool_call(tool_name, tool_call_content) { - console.warn(`Tool ${tool_name} not found or invalid, returning tool_call_content`); - return tool_call_content; - } - - async add_tool_call_to_chat(tool_name, tool_call_content) { - if (typeof this.current?.add_message === 'function') { - await this.current.add_message({ - role: 'assistant', - tool_calls: [{ - function: { - name: tool_name, - arguments: JSON.stringify(tool_call_content), - } - }] - }); - } - } - - handle_error(err, render) { - console.error(err); - if (render) { - this.done_handler("*An error occurred. See console logs for details.*"); - } - return "*An error occurred. See console logs for details.*"; - } - - // HANDLE TOOLS - /** - * Retrieves the tool handler function based on the tool name from the environment's actions. - * This method can be overridden to use custom logic for handling tools. - * - * @param {string} tool_name - The name of the tool for which the handler is to be retrieved. - * @returns {Function} The handler function for the specified tool. - */ - get_tool_handler(tool_name) { return this.env.actions?.actions?.[tool_name]?.handler; } - - /** - * Extracts the tool call information from a JSON response. This method supports adapter-specific logic. - * If no adapter method is provided, it defaults to the expected OpenAI JSON format. - * - * @param {Object} json - The JSON response from which to extract the tool call. - * @returns {Object} The first tool call found in the response. - */ - get_tool_call(json) { - if(typeof this.adapter?.get_tool_call === 'function') return this.adapter.get_tool_call(json); - return json.choices?.[0].message.tool_calls?.[0]; // OpenAI format - } - - /** - * Determines the tool name from a tool call object. Supports adapter-specific implementations. - * Defaults to extracting the name directly from the tool call structure. - * - * @param {Object} tool_call - The tool call object from which to extract the tool name. - * @returns {string} The name of the tool. - */ - get_tool_name(tool_call) { - if(typeof this.adapter?.get_tool_name === 'function') return this.adapter.get_tool_name(tool_call); - return tool_call.function.name; - } - - /** - * Extracts the tool call content from a tool call object. Supports adapter-specific logic. - * Defaults to parsing the 'arguments' field of the tool call function as JSON. - * - * @param {Object} tool_call - The tool call object from which to extract the content. - * @returns {Object} The parsed arguments of the tool call. - */ - get_tool_call_content(tool_call) { - if(typeof this.adapter?.get_tool_call_content === 'function') return this.adapter.get_tool_call_content(tool_call); - return JSON.parse(tool_call.function.arguments); - } - - // HANDLE MESSAGES - /** - * Retrieves the message object from a JSON response. Supports adapter-specific implementations. - * Defaults to handling both OpenAI and Ollama formats by checking for message structures in 'choices'. - * - * @param {Object} json - The JSON response from which to extract the message. - * @returns {Object} The message object extracted from the response. - */ - get_message(json) { - if(typeof this.adapter?.get_message === 'function') return this.adapter.get_message(json); - return json.choices?.[0].message || json.message; // supports OpenAI and Ollama - } - - /** - * Extracts the content of a message from a JSON response. Supports adapter-specific implementations. - * This method relies on `get_message` to first retrieve the message object. - * - * @param {Object} json - The JSON response from which to extract the message content. - * @returns {string} The content of the message. - */ - get_message_content(json) { - if(typeof this.adapter?.get_message_content === 'function') return this.adapter.get_message_content(json); - return this.get_message(json).content; - } - - async request(req){ - req.url = this.endpoint; - req.throw = false; - // handle fallback to fetch (allows for overwriting in child classes) - const resp = this._request_adapter ? await this._request_adapter(req) : await fetch(this.endpoint, req); - const resp_json = await this.get_resp_json(resp); - return resp_json; - } - async get_resp_json(resp) { return (typeof resp.json === 'function') ? await resp.json() : await resp.json; } - get request_adapter(){ return this._request_adapter; } - - async stream(req) { - console.log("Streaming Request: "); - const full_text = await new Promise((resolve, reject) => { - try { - // console.log("stream", opts); - this.active_stream = new SmartStreamer(this.endpoint_streaming, req); - let curr_text = ""; - this.active_stream.addEventListener("message", (e) => { - if(this.is_end_of_stream(e)) { - this.stop_stream(); - return resolve(curr_text); - } - let text_chunk = this.get_text_chunk_from_stream(e); - if(!text_chunk) return; - curr_text += text_chunk; - this.chunk_handler(text_chunk); // call the chunk handler if it exists - }); - // unnecessary? - this.active_stream.addEventListener("readystatechange", (e) => { - if (e.readyState >= 2) console.log("ReadyState: " + e.readyState); - }); - this.active_stream.addEventListener("error", (e) => { - console.error(e); - this.done_handler("*API Error. See console logs for details.*"); - this.stop_stream(); - reject(e); - }); - this.active_stream.stream(); - } catch (err) { - console.error(err); - this.stop_stream(); - reject(err); - } - }); - this.done_handler(full_text); // handled in complete() - return full_text; - } - get_text_chunk_from_stream(event) { - if(typeof this.adapter?.get_text_chunk_from_stream === 'function') return this.adapter.get_text_chunk_from_stream(event); - let resp = null; - let text_chunk = ''; - // DO: is this try/catch still necessary? - try { - resp = JSON.parse(event.data); - text_chunk = resp.choices[0].delta.content; - } catch (err) { - console.log(err); - console.log(event.data); - if (event.data.indexOf('}{') > -1) event.data = event.data.replace(/}{/g, '},{'); - resp = JSON.parse(`[${event.data}]`); - resp.forEach((r) => { - if (r.choices) text_chunk += r.choices[0].delta.content; - }); - } - return text_chunk; - } - is_end_of_stream(event) { - if(typeof this.adapter?.is_end_of_stream === 'function') return this.adapter.is_end_of_stream(event); - return event.data === "[DONE]"; // use default OpenAI format - } - - stop_stream() { - if (this.active_stream) { - this.active_stream.end(); - this.active_stream = null; - } - } - done_handler(full_str) { - // Should handle: - // 1. Add message to current chat history - // 2. Update chat UI - if(typeof this.main.done_handler === 'function') this.main.done_handler(full_str); - } - chunk_handler(text_chunk) { - // Should handle: - // 1. Update chat UI - if(typeof this.main.chunk_handler === 'function') this.main.chunk_handler(text_chunk); - } - async count_tokens(input) { - if(typeof this.adapter?.count_tokens === 'function') return await this.adapter.count_tokens(input); - return this.estimate_tokens(input); - } - estimate_tokens(input) { - if(typeof this.adapter?.estimate_tokens === 'function') return this.adapter.estimate_tokens(input); - if(typeof input === 'object') input = JSON.stringify(input); - return input.length / 4; - } - async test_api_key() { - try{ - const request = { - messages: [ - { role: "user", content: "Hello" }, - ], - temperature: 0, - max_tokens: 100, - stream: false, - n: 1, - }; - if(this.config.fetch_models) { - request.model = this.config.default_model; - } - const resp = await this.complete(request, false); - if(!resp) return false; - return true; - }catch(err){ - console.error(err); - return false; - } - } - async get_models() { - if(!this.api_key){ - console.warn(`No API key found for ${this.platform_key}. Cannot retrieve models.`); - return []; - } - // const fx_name = this.plugin.settings.chat_model_platform_key; - if(this.platforms[this.platform_key]?.fetch_models && typeof fetch_models[this.platform_key] === "function"){ - const models = await fetch_models[this.platform_key](this.api_key, this._request_adapter); - if(models) { - // sort alphabetically by model name - models.sort((a, b) => a.model_name.localeCompare(b.model_name)); - return models; - }else console.error(`No models found for ${this.platform_key}`, models); + "[CHAT_PLATFORM].model_key": { + name: 'Chat Model', + type: "dropdown", + description: "Select a chat model to use with Smart Chat.", + options_callback: 'get_models_as_options', + // callback: 'changed_chat_model', + conditional: (settings) => !local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].model_name": { + name: 'Model Name', + type: "text", + description: "Enter the model name for the chat model platform.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].api_key": { + name: 'API Key', + type: "password", + description: "Enter your API key for the chat model platform.", + callback: 'test_api_key', + is_scope: true, // trigger re-render of settings when changed (reload models dropdown) + }, + "[CHAT_PLATFORM].protocol": { + name: 'Protocol', + type: "text", + description: "Enter the protocol for the local chat model.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].hostname": { + name: 'Hostname', + type: "text", + description: "Enter the hostname for the local chat model.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].port": { + name: 'Port', + type: "number", + description: "Enter the port for the local chat model.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].path": { + name: 'Path', + type: "text", + description: "Enter the path for the local chat model.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].streaming": { + name: 'Streaming', + type: "toggle", + description: "Enable streaming for the local chat model.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + "[CHAT_PLATFORM].max_input_tokens": { + name: 'Max Input Tokens', + type: "number", + description: "Enter the maximum number of input tokens for the chat model.", + // callback: 'changed_chat_model', + conditional: (settings) => local_platforms.includes(settings.platform_key), + }, + ...(this.adapter.settings_config || {}), } - return []; - } - async get_base_model_config() { - const models = await this.get_models(); - return models.find((m) => m.key === this.model_name); - } - // getters - get api_key() { return this.config.api_key; } - get current() { return this.env.chats?.current; } - // use endpoint of combine protocol, hostname, port, and path - get endpoint() { - if(typeof this.adapter?.endpoint !== 'undefined') return this.adapter.endpoint.replace('MODEL_NAME', this.model_name); - return this.config.endpoint || this.config.protocol + "://" + this.config.hostname + (this.config.port ? ":" + this.config.port : "") + this.endpoint_path; + return this.process_settings_config(_settings_config); } - get endpoint_streaming() { - if(typeof this.adapter?.endpoint_streaming !== 'undefined') return this.adapter.endpoint_streaming.replace('MODEL_NAME', this.model_name); - return this.config.endpoint_streaming || this.endpoint; + process_setting_key(key) { + return key.replace(/\[CHAT_PLATFORM\]/g, this.platform_key); } - get endpoint_path() { return this.config.path.startsWith('/') ? this.config.path : '/' + this.config.path; } - get max_input_tokens() { return this.config.max_input_tokens; } - get max_output_tokens() { return this.config.max_output_tokens; } - get model_name() { return this.config.model_name || this.config.default_model; } - get multimodal() { return typeof this.adapter?.multimodal !== 'undefined' ? this.adapter.multimodal : this.config.multimodal; } } -exports.SmartChatModel = SmartChatModel; - +const local_platforms = ['custom_local', 'ollama', 'lm_studio']; \ No newline at end of file diff --git a/smart-chat-model/streamer.js b/smart-chat-model/streamer.js index 178b983e..aa8a3d6b 100644 --- a/smart-chat-model/streamer.js +++ b/smart-chat-model/streamer.js @@ -1,4 +1,4 @@ -class SmartStreamer { +export class SmartStreamer { constructor(url, options = {}) { const { method = 'GET', @@ -176,6 +176,4 @@ class SmartStreamer { if (this.xhr.readyState === XMLHttpRequest.DONE) this.#setReadyState(this.CLOSED); } -} - -exports.SmartStreamer = SmartStreamer; +} \ No newline at end of file diff --git a/smart-chats/MIT_LICENSE b/smart-chats-v1/MIT_LICENSE similarity index 100% rename from smart-chats/MIT_LICENSE rename to smart-chats-v1/MIT_LICENSE diff --git a/smart-chats-v1/README.md b/smart-chats-v1/README.md new file mode 100644 index 00000000..67b0e447 --- /dev/null +++ b/smart-chats-v1/README.md @@ -0,0 +1,32 @@ +# Smart Chats +Used to build [Smart Connections](https://github.com/brianpetro/obsidian-smart-connections). + +### Notes + +- `SmartEnv` is the orchestrator and loads mixin classes +- `SmartChats` is used to manage chat history +- `SmartChat` is a chat instance +- `SmartUI` is used to render the chat UI + +```mermaid +graph LR + SE[SmartEnv] + SR[Renderer] + SCs[Chats] + SC[Chat] + SM["Chat Model (OpenAI)"] + + SE -.-> SM + SE -.-> SR + SE -.-> SC + SE -.-> SCs + SCs -.->|has many| SC +``` + +### Minimal Dependencies + +One of the key advantages of `SmartChat` is its minimal dependency requirement. This makes it an ideal choice for developers looking to integrate chat functionalities without the overhead of managing numerous dependencies. By focusing on a lean architecture, `SmartChat` ensures that your application remains lightweight and easy to maintain. + +### Building Your Own App + +`SmartChat` is designed to be highly customizable, enabling developers to build their own applications that leverage its chat functionalities. diff --git a/smart-chats/adapters.js b/smart-chats-v1/adapters.js similarity index 100% rename from smart-chats/adapters.js rename to smart-chats-v1/adapters.js diff --git a/smart-chats/adapters/canvas.js b/smart-chats-v1/adapters/canvas.js similarity index 100% rename from smart-chats/adapters/canvas.js rename to smart-chats-v1/adapters/canvas.js diff --git a/smart-chats/adapters/markdown.js b/smart-chats-v1/adapters/markdown.js similarity index 100% rename from smart-chats/adapters/markdown.js rename to smart-chats-v1/adapters/markdown.js diff --git a/smart-chats-v2/package-lock.json b/smart-chats-v1/package-lock.json similarity index 94% rename from smart-chats-v2/package-lock.json rename to smart-chats-v1/package-lock.json index 1d1fb175..0c1322e3 100644 --- a/smart-chats-v2/package-lock.json +++ b/smart-chats-v1/package-lock.json @@ -1,28 +1,18 @@ { "name": "smart-chats", - "version": "2.0.0", + "version": "1.0.3", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "smart-chats", - "version": "2.0.0", - "license": "MIT", - "dependencies": { - "smart-sources": "file:../smart-sources" - }, - "devDependencies": { - "ava": "^6.0.1" - } - }, - "../smart-sources": { - "version": "2.0.0", + "version": "1.0.3", "license": "MIT", "dependencies": { - "smart-entities": "file:../smart-entities" + "smart-chat-model": "^1.0.0" }, "devDependencies": { - "ava": "^6.0.1" + "ava": "^6.1.2" } }, "node_modules/@mapbox/node-pre-gyp": { @@ -118,9 +108,9 @@ } }, "node_modules/@vercel/nft": { - "version": "0.26.5", - "resolved": "https://registry.npmjs.org/@vercel/nft/-/nft-0.26.5.tgz", - "integrity": "sha512-NHxohEqad6Ra/r4lGknO52uc/GrWILXAMs1BB4401GTqww0fw1bAqzpG1XHuDO+dprg4GvsD9ZLLSsdo78p9hQ==", + "version": "0.26.4", + "resolved": "https://registry.npmjs.org/@vercel/nft/-/nft-0.26.4.tgz", + "integrity": "sha512-j4jCOOXke2t8cHZCIxu1dzKLHLcFmYzC3yqAK6MfZznOL1QIJKd0xcFsXK3zcqzU7ScsE2zWkiMMNHGMHgp+FA==", "dev": true, "dependencies": { "@mapbox/node-pre-gyp": "^1.0.5", @@ -150,9 +140,9 @@ "dev": true }, "node_modules/acorn": { - 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"keywords": [ - "chats" - ], + "ava": { + "files": [ + "**/*.test.js" + ] + }, "repository": { "type": "git", "url": "brianpetro/jsbrains" }, + "keywords": [ + "AI", + "chat", + "models", + "universal", + "adapter" + ], "bugs": { "url": "https://github.com/brianpetro/jsbrains/issues" }, - "homepage": "https://jsbrains.org", - "devDependencies": { - "ava": "^6.0.1" - }, - "dependencies": { - "smart-sources": "file:../smart-sources" - }, - "ava": { - "files": [ - "test/**/*.test.js" - ] - } + "homepage": "https://jsbrains.org" } diff --git a/smart-chats/smart_chat.js b/smart-chats-v1/smart_chat.js similarity index 100% rename from smart-chats/smart_chat.js rename to smart-chats-v1/smart_chat.js diff --git a/smart-chats/smart_chat_env.js b/smart-chats-v1/smart_chat_env.js similarity index 100% rename from smart-chats/smart_chat_env.js rename to smart-chats-v1/smart_chat_env.js diff --git a/smart-chats/smart_chat_md.js b/smart-chats-v1/smart_chat_md.js similarity index 100% rename from smart-chats/smart_chat_md.js rename to smart-chats-v1/smart_chat_md.js diff --git a/smart-chats/smart_chats.js b/smart-chats-v1/smart_chats.js similarity index 100% rename from smart-chats/smart_chats.js rename to smart-chats-v1/smart_chats.js diff --git a/smart-chats/smart_chats_ui.js b/smart-chats-v1/smart_chats_ui.js similarity index 100% rename from smart-chats/smart_chats_ui.js rename to smart-chats-v1/smart_chats_ui.js diff --git a/smart-chats/test/_env.js b/smart-chats-v1/test/_env.js similarity index 100% rename from smart-chats/test/_env.js rename to smart-chats-v1/test/_env.js diff --git a/smart-chats/utils/add_content_to_message.js b/smart-chats-v1/utils/add_content_to_message.js similarity index 100% rename from smart-chats/utils/add_content_to_message.js rename to smart-chats-v1/utils/add_content_to_message.js diff --git a/smart-chats/utils/add_content_to_message.test.js b/smart-chats-v1/utils/add_content_to_message.test.js similarity index 100% rename from smart-chats/utils/add_content_to_message.test.js rename to smart-chats-v1/utils/add_content_to_message.test.js diff --git a/smart-chats/utils/canvas_to_chatml.js b/smart-chats-v1/utils/canvas_to_chatml.js similarity index 100% rename from smart-chats/utils/canvas_to_chatml.js rename to smart-chats-v1/utils/canvas_to_chatml.js diff --git a/smart-chats/utils/canvas_to_chatml.test.js b/smart-chats-v1/utils/canvas_to_chatml.test.js similarity index 100% rename from smart-chats/utils/canvas_to_chatml.test.js rename to smart-chats-v1/utils/canvas_to_chatml.test.js diff --git a/smart-chats/utils/chat_ml_to_markdown.js b/smart-chats-v1/utils/chat_ml_to_markdown.js similarity index 100% rename from smart-chats/utils/chat_ml_to_markdown.js rename to smart-chats-v1/utils/chat_ml_to_markdown.js diff --git a/smart-chats/utils/chat_ml_to_markdown.test.js b/smart-chats-v1/utils/chat_ml_to_markdown.test.js similarity index 100% rename from smart-chats/utils/chat_ml_to_markdown.test.js rename to smart-chats-v1/utils/chat_ml_to_markdown.test.js diff --git a/smart-chats/utils/chatml_to_canvas.js b/smart-chats-v1/utils/chatml_to_canvas.js similarity index 100% rename from smart-chats/utils/chatml_to_canvas.js rename to smart-chats-v1/utils/chatml_to_canvas.js diff --git a/smart-chats/utils/chatml_to_canvas.test.js b/smart-chats-v1/utils/chatml_to_canvas.test.js similarity index 100% rename from smart-chats/utils/chatml_to_canvas.test.js rename to smart-chats-v1/utils/chatml_to_canvas.test.js diff --git a/smart-chats/utils/markdown_to_chat_ml.js b/smart-chats-v1/utils/markdown_to_chat_ml.js similarity index 100% rename from smart-chats/utils/markdown_to_chat_ml.js rename to smart-chats-v1/utils/markdown_to_chat_ml.js diff --git a/smart-chats/utils/markdown_to_chat_ml.test.js b/smart-chats-v1/utils/markdown_to_chat_ml.test.js similarity index 100% rename from smart-chats/utils/markdown_to_chat_ml.test.js rename to smart-chats-v1/utils/markdown_to_chat_ml.test.js diff --git a/smart-chats/utils/message_content_array_to_markdown.js b/smart-chats-v1/utils/message_content_array_to_markdown.js similarity index 100% rename from smart-chats/utils/message_content_array_to_markdown.js rename to smart-chats-v1/utils/message_content_array_to_markdown.js diff --git a/smart-chats-v2/README.md b/smart-chats-v2/README.md deleted file mode 100644 index 40d81dbf..00000000 --- a/smart-chats-v2/README.md +++ /dev/null @@ -1,5 +0,0 @@ -# Smart Chat Collections (Smart Threads) - -## WHY -- Chat history management -- orchestrator between UI and Smart Chat Model diff --git a/smart-chats/README.md b/smart-chats/README.md index 67b0e447..40d81dbf 100644 --- a/smart-chats/README.md +++ b/smart-chats/README.md @@ -1,32 +1,5 @@ -# Smart Chats -Used to build [Smart Connections](https://github.com/brianpetro/obsidian-smart-connections). +# Smart Chat Collections (Smart Threads) -### Notes - -- `SmartEnv` is the orchestrator and loads mixin classes -- `SmartChats` is used to manage chat history -- `SmartChat` is a chat instance -- `SmartUI` is used to render the chat UI - -```mermaid -graph LR - SE[SmartEnv] - SR[Renderer] - SCs[Chats] - SC[Chat] - SM["Chat Model (OpenAI)"] - - SE -.-> SM - SE -.-> SR - SE -.-> SC - SE -.-> SCs - SCs -.->|has many| SC -``` - -### Minimal Dependencies - -One of the key advantages of `SmartChat` is its minimal dependency requirement. This makes it an ideal choice for developers looking to integrate chat functionalities without the overhead of managing numerous dependencies. By focusing on a lean architecture, `SmartChat` ensures that your application remains lightweight and easy to maintain. - -### Building Your Own App - -`SmartChat` is designed to be highly customizable, enabling developers to build their own applications that leverage its chat functionalities. +## WHY +- Chat history management +- orchestrator between UI and Smart Chat Model diff --git a/smart-chats-v2/adapters/_adapter.js b/smart-chats/adapters/_adapter.js similarity index 100% rename from smart-chats-v2/adapters/_adapter.js rename to smart-chats/adapters/_adapter.js diff --git a/smart-chats-v2/adapters/openai_json.js b/smart-chats/adapters/openai_json.js similarity index 100% rename from smart-chats-v2/adapters/openai_json.js rename to smart-chats/adapters/openai_json.js diff --git a/smart-chats-v2/components/_component.js b/smart-chats/components/_component.js similarity index 100% rename from smart-chats-v2/components/_component.js rename to smart-chats/components/_component.js diff --git a/smart-chats-v2/components/message.js b/smart-chats/components/message.js similarity index 100% rename from smart-chats-v2/components/message.js rename to smart-chats/components/message.js diff --git a/smart-chats-v2/components/modal.js b/smart-chats/components/modal.js similarity index 100% rename from smart-chats-v2/components/modal.js rename to smart-chats/components/modal.js diff --git a/smart-chats-v2/components/settings.js b/smart-chats/components/settings.js similarity index 100% rename from smart-chats-v2/components/settings.js rename to smart-chats/components/settings.js diff --git a/smart-chats-v2/components/thread.js b/smart-chats/components/thread.js similarity index 100% rename from smart-chats-v2/components/thread.js rename to smart-chats/components/thread.js diff --git a/smart-chats-v2/components/turn.js b/smart-chats/components/turn.js similarity index 100% rename from smart-chats-v2/components/turn.js rename to smart-chats/components/turn.js diff --git a/smart-chats-v2/index.js b/smart-chats/index.js similarity index 100% rename from smart-chats-v2/index.js rename to smart-chats/index.js diff --git a/smart-chats/package-lock.json b/smart-chats/package-lock.json index 0c1322e3..1d1fb175 100644 --- a/smart-chats/package-lock.json +++ b/smart-chats/package-lock.json @@ -1,18 +1,28 @@ { "name": "smart-chats", - "version": "1.0.3", + "version": "2.0.0", "lockfileVersion": 3, "requires": true, "packages": { "": { "name": "smart-chats", - "version": "1.0.3", + "version": "2.0.0", + "license": "MIT", + "dependencies": { + "smart-sources": "file:../smart-sources" + }, + "devDependencies": { + "ava": "^6.0.1" + } + }, + "../smart-sources": { + "version": "2.0.0", "license": "MIT", "dependencies": { - "smart-chat-model": "^1.0.0" + "smart-entities": "file:../smart-entities" }, "devDependencies": { - "ava": "^6.1.2" + "ava": "^6.0.1" } }, "node_modules/@mapbox/node-pre-gyp": { @@ -108,9 +118,9 @@ } }, "node_modules/@vercel/nft": { - "version": "0.26.4", - "resolved": "https://registry.npmjs.org/@vercel/nft/-/nft-0.26.4.tgz", - "integrity": "sha512-j4jCOOXke2t8cHZCIxu1dzKLHLcFmYzC3yqAK6MfZznOL1QIJKd0xcFsXK3zcqzU7ScsE2zWkiMMNHGMHgp+FA==", + "version": "0.26.5", + "resolved": "https://registry.npmjs.org/@vercel/nft/-/nft-0.26.5.tgz", + "integrity": "sha512-NHxohEqad6Ra/r4lGknO52uc/GrWILXAMs1BB4401GTqww0fw1bAqzpG1XHuDO+dprg4GvsD9ZLLSsdo78p9hQ==", "dev": true, "dependencies": { "@mapbox/node-pre-gyp": "^1.0.5", @@ -140,9 +150,9 @@ "dev": true }, "node_modules/acorn": { - 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"version": "7.6.0", - "resolved": "https://registry.npmjs.org/semver/-/semver-7.6.0.tgz", - "integrity": "sha512-EnwXhrlwXMk9gKu5/flx5sv/an57AkRplG3hTK68W7FRDN+k+OWBj65M7719OkA82XLBxrcX0KSHj+X5COhOVg==", + "version": "7.6.3", + "resolved": "https://registry.npmjs.org/semver/-/semver-7.6.3.tgz", + "integrity": "sha512-oVekP1cKtI+CTDvHWYFUcMtsK/00wmAEfyqKfNdARm8u1wNVhSgaX7A8d4UuIlUI5e84iEwOhs7ZPYRmzU9U6A==", "dev": true, - "dependencies": { - "lru-cache": "^6.0.0" - }, "bin": { "semver": "bin/semver.js" }, @@ -1765,10 +1763,9 @@ "url": "https://github.com/chalk/slice-ansi?sponsor=1" } }, - "node_modules/smart-chat-model": { - "version": "1.0.0", - "resolved": "https://registry.npmjs.org/smart-chat-model/-/smart-chat-model-1.0.0.tgz", - "integrity": "sha512-/ca8b0biN5GVT7ozBNZRpp+5IUBqSRUe4nu6w8jZXNWsH4CmAoatY1wZ6A4UfznnFq1oRxZnKfHbXBZX+e76Jg==" + "node_modules/smart-sources": { + "resolved": "../smart-sources", + "link": true }, "node_modules/sprintf-js": { "version": "1.0.3", @@ -1807,9 +1804,9 @@ } }, "node_modules/string-width": { - "version": "7.1.0", - "resolved": "https://registry.npmjs.org/string-width/-/string-width-7.1.0.tgz", - "integrity": "sha512-SEIJCWiX7Kg4c129n48aDRwLbFb2LJmXXFrWBG4NGaRtMQ3myKPKbwrD1BKqQn74oCoNMBVrfDEr5M9YxCsrkw==", + "version": "7.2.0", + "resolved": "https://registry.npmjs.org/string-width/-/string-width-7.2.0.tgz", + "integrity": "sha512-tsaTIkKW9b4N+AEj+SVA+WhJzV7/zMhcSu78mLKWSk7cXMOSHsBKFWUs0fWwq8QyK3MgJBQRX6Gbi4kYbdvGkQ==", "dev": true, "dependencies": { "emoji-regex": "^10.3.0", diff --git a/smart-chats/package.json b/smart-chats/package.json index 883c35b7..a4a90f61 100644 --- a/smart-chats/package.json +++ b/smart-chats/package.json @@ -2,33 +2,33 @@ "name": "smart-chats", "author": "Brian Joseph Petro (🌴 Brian)", "license": "MIT", - "version": "1.0.3", - "description": "no-nonsense storage and rendering for smart chats", - "main": "smart_chats.js", - "devDependencies": { - "ava": "^6.1.2" - }, + "version": "2.0.0", + "type": "module", + "description": "Easy to manage chats with AI.", + "main": "index.js", "scripts": { "test": "npx ava --verbose" }, - "ava": { - "files": [ - "**/*.test.js" - ] - }, + "keywords": [ + "chats" + ], "repository": { "type": "git", "url": "brianpetro/jsbrains" }, - "keywords": [ - "AI", - "chat", - "models", - "universal", - "adapter" - ], "bugs": { "url": "https://github.com/brianpetro/jsbrains/issues" }, - "homepage": "https://jsbrains.org" + "homepage": "https://jsbrains.org", + "devDependencies": { + "ava": "^6.0.1" + }, + "dependencies": { + "smart-sources": "file:../smart-sources" + }, + "ava": { + "files": [ + "test/**/*.test.js" + ] + } } diff --git a/smart-chats-v2/smart_threads.js b/smart-chats/smart_threads.js similarity index 100% rename from smart-chats-v2/smart_threads.js rename to smart-chats/smart_threads.js diff --git a/smart-embed-model-v1/MIT_LICENSE b/smart-embed-model-v1/MIT_LICENSE new file mode 100644 index 00000000..8c2ac962 --- /dev/null +++ b/smart-embed-model-v1/MIT_LICENSE @@ -0,0 +1,20 @@ +Copyright (c) Brian Joseph Petro + +Permission is hereby granted, free of charge, to any person obtaining +a copy of this software and associated documentation files (the +"Software"), to deal in the Software without restriction, including +without limitation the rights to use, copy, modify, merge, publish, +distribute, sublicense, and/or sell copies of the Software, and to +permit persons to whom the Software is furnished to do so, subject to +the following conditions: + +The above copyright notice and this permission notice shall be +included in all copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE +LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION +OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION +WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. \ No newline at end of file diff --git a/smart-embed-model-v1/README.md b/smart-embed-model-v1/README.md new file mode 100644 index 00000000..c9c1eeb0 --- /dev/null +++ b/smart-embed-model-v1/README.md @@ -0,0 +1,51 @@ +# SmartEmbedModel + +SmartEmbedModel is a versatile and convenient interface for utilizing various embedding models via API and locally. It provides a unified way to work with different embedding models, making it easy to switch between models or use multiple models in your projects. + +## Features + +- Support for multiple embedding models +- Easy-to-use API for embedding text +- Batch processing capabilities +- Token counting functionality +- Flexible configuration options +- Support for both local and API-based models + +## Configuration + +SmartEmbedModel can be configured with various options: + +- `embed_model_key`: The key of the embedding model to use (defined in `models.json`) +- `adapter`: The adapter to use for the chosen model +- `batch_size`: The number of inputs to process in a single batch +- `max_tokens`: The maximum number of tokens the model can handle +- `use_gpu`: Whether to use GPU acceleration (if available) +- `gpu_batch_size`: The batch size to use when GPU acceleration is enabled + +## Available Models + +The available models are defined in the `models.json` file. Some of the included models are: + +- TaylorAI/bge-micro-v2 +- andersonbcdefg/bge-small-4096 +- Xenova/jina-embeddings-v2-base-zh +- text-embedding-3-small +- text-embedding-3-large +- And more... + +## Adapters + +SmartEmbedModel uses adapters to interface with different embedding models. The available adapters are: + +- OpenAI +- Transformers +- TransformersIframe +- TransformersWorker + +## License + +This project is licensed under the MIT License - see the [LICENSE](MIT_LICENSE) file for details. + +## Author + +Brian Joseph Petro (🌴 Brian) \ No newline at end of file diff --git a/smart-embed-model-v1/adapters.js b/smart-embed-model-v1/adapters.js new file mode 100644 index 00000000..956ce45d --- /dev/null +++ b/smart-embed-model-v1/adapters.js @@ -0,0 +1,11 @@ +import { SmartEmbedAdapter } from "./adapters/_adapter.js"; +import { SmartEmbedOpenAIAdapter } from "./adapters/openai.js"; +import { SmartEmbedTransformersAdapter } from "./adapters/transformers.js"; +import { SmartEmbedTransformersIframeAdapter } from "./adapters/transformers_iframe.js"; + +export { + SmartEmbedAdapter as _default, + SmartEmbedOpenAIAdapter as openai, + SmartEmbedTransformersAdapter as transformers, + SmartEmbedTransformersIframeAdapter as transformers_iframe, +}; \ No newline at end of file diff --git a/smart-embed-model-v1/adapters/_adapter.js b/smart-embed-model-v1/adapters/_adapter.js new file mode 100644 index 00000000..1b9957e0 --- /dev/null +++ b/smart-embed-model-v1/adapters/_adapter.js @@ -0,0 +1,9 @@ +export class SmartEmbedAdapter { + constructor(smart_embed) { + this.smart_embed = smart_embed; + } + async load() { throw new Error("Not implemented"); } + async count_tokens(input) { throw new Error("Not implemented"); } + async embed(input) { throw new Error("Not implemented"); } + async embed_batch(input) { throw new Error("Not implemented"); } +} diff --git a/smart-embed-model-v1/adapters/iframe.js b/smart-embed-model-v1/adapters/iframe.js new file mode 100644 index 00000000..3492e666 --- /dev/null +++ b/smart-embed-model-v1/adapters/iframe.js @@ -0,0 +1,104 @@ +import { SmartEmbedAdapter } from "./_adapter.js"; + +export class SmartEmbedIframeAdapter extends SmartEmbedAdapter { + constructor(smart_embed) { + super(smart_embed); + this.iframe = null; + this.message_queue = {}; + this.message_id = 0; + this.connector = null; // override in subclass + this.origin = window.location.origin; + this.iframe_id = `smart_embed_iframe_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`; + } + + async load() { + // Create and append iframe + this.iframe = document.createElement('iframe'); + this.iframe.style.display = 'none'; + this.iframe.id = this.iframe_id; + document.body.appendChild(this.iframe); + + // Set up message listener + window.addEventListener('message', this._handle_message.bind(this)); + + // Load the iframe content + this.iframe.srcdoc = ` + + + + + + `; + + // Wait for iframe to load + await new Promise(resolve => this.iframe.onload = resolve); + + // Initialize the model in the iframe + await this._send_message('load', { + ...this.smart_embed.opts, + adapters: null, // cannot clone classes + }); + return new Promise(resolve => { + const check_model_loaded = () => { + if (this.smart_embed.model_loaded) { + resolve(); + } else { + setTimeout(check_model_loaded, 100); + } + }; + check_model_loaded(); + }); + } + + async _send_message(method, params) { + return new Promise((resolve, reject) => { + const id = this.message_id++; + this.message_queue[id] = { resolve, reject }; + this.iframe.contentWindow.postMessage({ method, params, id, iframe_id: this.iframe_id }, this.origin); + }); + } + + _handle_message(event) { + if (event.origin !== this.origin || event.data.iframe_id !== this.iframe_id) return; + + const { id, result, error } = event.data; + if (result?.model_loaded) { + console.log('model loaded'); + this.smart_embed.model_loaded = true; + } + if (this.message_queue[id]) { + if (error) { + this.message_queue[id].reject(new Error(error)); + } else { + this.message_queue[id].resolve(result); + } + delete this.message_queue[id]; + } + } + + async count_tokens(input) { + return this._send_message('count_tokens', { input }); + } + + async embed_batch(inputs) { + const filtered_inputs = inputs.filter(item => item.embed_input?.length > 0); + if (!filtered_inputs.length) return []; + const embed_inputs = filtered_inputs.map(item => ({ embed_input: item.embed_input })); + const result = await this._send_message('embed_batch', { inputs: embed_inputs }); + + return filtered_inputs.map((item, i) => { + item.vec = result[i].vec; + item.tokens = result[i].tokens; + return item; + }); + } +} \ No newline at end of file diff --git a/smart-embed-model-v1/adapters/openai.js b/smart-embed-model-v1/adapters/openai.js new file mode 100644 index 00000000..bc4902e4 --- /dev/null +++ b/smart-embed-model-v1/adapters/openai.js @@ -0,0 +1,171 @@ +import { SmartEmbedAdapter } from "./_adapter.js"; +import { Tiktoken } from 'js-tiktoken/lite'; +import cl100k_base from "../cl100k_base.json" assert { type: "json" }; + +export class SmartEmbedOpenAIAdapter extends SmartEmbedAdapter { + constructor(smart_embed) { + super(smart_embed); + this.model_key = smart_embed.opts.model_key || "text-embedding-ada-002"; + this.endpoint = "https://api.openai.com/v1/embeddings"; + this.max_tokens = 8191; // Default max tokens for OpenAI embeddings + this.dims = smart_embed.opts.dims || 1536; // Default dimensions for OpenAI embeddings + this.enc = null; + this.request_adapter = smart_embed.env.opts.request_adapter; + } + get api_key() { + return this.smart_embed.opts.api_key + || this.smart_embed.env.smart_connections_plugin?.settings?.api_key // temporary for backwards compatibility in SC OP + ; + } + + async load() { + this.enc = new Tiktoken(cl100k_base); + } + + async count_tokens(input) { + if (!this.enc) await this.load(); + return this.enc.encode(input).length; + } + + estimate_tokens(input) { + if (typeof input === 'object') input = JSON.stringify(input); + return Math.ceil(input.length / 3.7); + } + + async embed_batch(inputs) { + console.log(`Original inputs length: ${inputs.length}`); + inputs = inputs.filter(item => item.embed_input?.length > 0); + console.log(`Filtered inputs length: ${inputs.length}`); + if (inputs.length === 0) { + console.log("empty batch (or all items have empty embed_input)"); + return []; + } + const embed_inputs = await Promise.all(inputs.map(item => this.prepare_embed_input(item.embed_input))); + console.log(`Prepared embed_inputs length: ${embed_inputs.length}`); + const embeddings = await this.request_embedding(embed_inputs); + if (!embeddings) return console.error(inputs); + return inputs.map((item, i) => { + item.vec = embeddings[i].vec; + item.tokens = embeddings[i].tokens; + return item + }); + } + + async prepare_embed_input(embed_input) { + if (typeof embed_input !== 'string') { + throw new TypeError('embed_input must be a string'); + } + + if (embed_input.length === 0) { + console.log("Warning: prepare_embed_input received an empty string"); + return null; + } + + const tokens_ct = await this.count_tokens(embed_input); + if (tokens_ct <= this.max_tokens) { + return embed_input; + } + + const reduce_ratio = (tokens_ct - this.max_tokens) / tokens_ct; + const new_length = Math.floor(embed_input.length * (1 - reduce_ratio)); + + // Trim the input to the new length, ensuring we don't cut off in the middle of a word + let trimmed_input = embed_input.slice(0, new_length); + const last_space_index = trimmed_input.lastIndexOf(' '); + if (last_space_index > 0) { + trimmed_input = trimmed_input.slice(0, last_space_index); + } + + // Recursively call prepare_embed_input to ensure we're within token limit + const prepared_input = await this.prepare_embed_input(trimmed_input); + if (prepared_input === null) { + console.log("Warning: prepare_embed_input resulted in an empty string after trimming"); + return null; + } + return prepared_input; + } + + prepare_batch_input(items) { + return items.map(item => this.prepare_embed_input(item.embed_input)); + } + + prepare_request_body(embed_input) { + const body = { + model: this.model_key, + input: embed_input, + }; + if (this.model_key.startsWith("text-embedding-3")) { + body.dimensions = this.dims; + } + return body; + } + + prepare_request_headers() { + let headers = { + "Content-Type": "application/json", + "Authorization": `Bearer ${this.api_key}` + }; + if (this.smart_embed.opts.headers) { + headers = { ...headers, ...this.smart_embed.opts.headers }; + } + return headers; + } + + async request_embedding(embed_input) { + embed_input = embed_input.filter(input => input !== null && input.length > 0); + if (embed_input.length === 0) { + console.log("embed_input is empty after filtering null and empty strings"); + return null; + } + const request = { + url: this.endpoint, + method: "POST", + body: JSON.stringify(this.prepare_request_body(embed_input)), + headers: this.prepare_request_headers() + }; + const resp = await this.request(request); + return this.parse_response(resp); + } + + parse_response(resp) { + return resp.data.map(item => ({ + vec: item.embedding, + tokens: resp.usage.total_tokens + })); + } + + is_error(resp_json) { + return !resp_json.data || !resp_json.usage; + } + + async get_resp_json(resp) { + return (typeof resp.json === 'function') ? await resp.json() : await resp.json; + } + + async request(req, retries = 0) { + try { + req.throw = false; + const resp = this.request_adapter + ? await this.request_adapter({ url: this.endpoint, ...req }) + : await fetch(this.endpoint, req); + const resp_json = await this.get_resp_json(resp); + if (this.is_error(resp_json)) { + return await this.handle_request_err(resp_json, req, retries); + } + return resp_json; + } catch (error) { + return await this.handle_request_err(error, req, retries); + } + } + + async handle_request_err(error, req, retries) { + if (error.status === 429 && retries < 3) { + const backoff = Math.pow(retries + 1, 2); + console.log(`Retrying request (429) in ${backoff} seconds...`); + await new Promise(r => setTimeout(r, 1000 * backoff)); + return await this.request(req, retries + 1); + } + console.error(error); + return null; + } +} diff --git a/smart-embed-model-v1/adapters/transformers.js b/smart-embed-model-v1/adapters/transformers.js new file mode 100644 index 00000000..f7780e4a --- /dev/null +++ b/smart-embed-model-v1/adapters/transformers.js @@ -0,0 +1,78 @@ +import { SmartEmbedAdapter } from "./_adapter.js"; + +export class SmartEmbedTransformersAdapter extends SmartEmbedAdapter { + constructor(smart_embed) { + super(smart_embed); + this.model = null; + this.tokenizer = null; + } + get batch_size() { + if(this.use_gpu && this.smart_embed.opts.gpu_batch_size) return this.smart_embed.opts.gpu_batch_size; + return this.smart_embed.opts.batch_size || 1; + } + get max_tokens() { return this.smart_embed.opts.max_tokens || 512; } + get use_gpu() { return this.smart_embed.opts.use_gpu || false; } + + async load() { + const { pipeline, env, AutoTokenizer } = await import('@xenova/transformers'); + // const { pipeline, env, AutoTokenizer } = await import('https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.9'); + env.allowLocalModels = false; + const pipeline_opts = { + quantized: true, + }; + if (this.use_gpu) { + console.log("[Transformers] Using GPU"); + pipeline_opts.device = 'webgpu'; + pipeline_opts.dtype = 'fp32'; + } else { + console.log("[Transformers] Using CPU"); + env.backends.onnx.wasm.numThreads = 8; + } + this.model = await pipeline('feature-extraction', this.smart_embed.opts.model_key, pipeline_opts); + this.tokenizer = await AutoTokenizer.from_pretrained(this.smart_embed.opts.model_key); + } + + async count_tokens(input) { + if (!this.tokenizer) await this.load(); + const { input_ids } = await this.tokenizer(input); + return { tokens: input_ids.data.length }; + } + + async embed_batch(inputs) { + if (!this.model) await this.load(); + const filtered_inputs = inputs.filter(item => item.embed_input?.length > 0); + if (!filtered_inputs.length) return []; + + if (filtered_inputs.length > this.batch_size) { + throw new Error(`Input size (${filtered_inputs.length}) exceeds maximum batch size (${this.batch_size})`); + } + + const tokens = await Promise.all(filtered_inputs.map(item => this.count_tokens(item.embed_input))); + const embed_inputs = await Promise.all(filtered_inputs.map(async (item, i) => { + if (tokens[i].tokens < this.max_tokens) return item.embed_input; + let token_ct = tokens[i].tokens; + let truncated_input = item.embed_input; + while (token_ct > this.max_tokens) { + const pct = this.max_tokens / token_ct; + const max_chars = Math.floor(truncated_input.length * pct * 0.90); + truncated_input = truncated_input.substring(0, max_chars) + "..."; + token_ct = (await this.count_tokens(truncated_input)).tokens; + } + tokens[i].tokens = token_ct; + return truncated_input; + })); + + try { + const resp = await this.model(embed_inputs, { pooling: 'mean', normalize: true }); + + return filtered_inputs.map((item, i) => { + item.vec = Array.from(resp[i].data).map(val => Math.round(val * 1e8) / 1e8); + item.tokens = tokens[i].tokens; + return item; + }); + } catch (err) { + console.error("error_embedding_batch", err); + return Promise.all(filtered_inputs.map(item => this.embed(item.embed_input))); + } + } +} \ No newline at end of file diff --git a/smart-embed-model-v1/adapters/transformers_iframe.js b/smart-embed-model-v1/adapters/transformers_iframe.js new file mode 100644 index 00000000..3a081fd9 --- /dev/null +++ b/smart-embed-model-v1/adapters/transformers_iframe.js @@ -0,0 +1,18 @@ +import { SmartEmbedIframeAdapter } from "./iframe.js"; +import { transformers_connector } from "../connectors/transformers_iframe.js"; + +export class SmartEmbedTransformersIframeAdapter extends SmartEmbedIframeAdapter { + constructor(smart_embed) { + super(smart_embed); + this.connector = transformers_connector; + if(this.smart_embed.env.settings.legacy_transformers){ + this.connector = this.connector + .replace('@xenova/transformers', 'https://cdn.jsdelivr.net/npm/@xenova/transformers@2.17.2') + ; + this.smart_embed.opts.use_gpu = false; + } + else this.connector = this.connector + .replace('@xenova/transformers', 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.15') + ; + } +} \ No newline at end of file diff --git a/smart-embed-model-v1/adapters/transformers_worker.js b/smart-embed-model-v1/adapters/transformers_worker.js new file mode 100644 index 00000000..da824087 --- /dev/null +++ b/smart-embed-model-v1/adapters/transformers_worker.js @@ -0,0 +1,16 @@ +import { SmartEmbedWorkerAdapter } from "./worker.js"; +// import { transformers_connector } from "../connectors/transformers_worker.js"; + +export class SmartEmbedTransformersWorkerAdapter extends SmartEmbedWorkerAdapter { + constructor(smart_embed) { + super(smart_embed); + // Create worker using a relative path + let rel_path; + if (import.meta.url.includes('smart-embed-model')) { + rel_path = "../connectors/transformers_worker.js"; + } else { + rel_path = "../node_modules/smart-embed-model/connectors/transformers_worker.js"; + } + this.worker_url = new URL(rel_path, import.meta.url); + } +} diff --git a/smart-embed-model-v1/adapters/worker.js b/smart-embed-model-v1/adapters/worker.js new file mode 100644 index 00000000..6baabb0c --- /dev/null +++ b/smart-embed-model-v1/adapters/worker.js @@ -0,0 +1,91 @@ +import { SmartEmbedAdapter } from "./_adapter.js"; + +export class SmartEmbedWorkerAdapter extends SmartEmbedAdapter { + constructor(smart_embed) { + super(smart_embed); + this.worker = null; + this.message_queue = {}; + this.message_id = 0; + this.connector = null; // override in subclass + this.worker_id = `smart_embed_worker_${Date.now()}_${Math.random().toString(36).substr(2, 9)}`; + this.message_prefix = `msg_${Math.random().toString(36).substr(2, 9)}_`; + } + get main() { return this.smart_embed.env.main; } + + async load() { + console.log('loading worker adapter', this.smart_embed.opts); + + const global_key = `smart_embed_worker_${this.smart_embed.opts.embed_model_key}`; + + if (!this.main[global_key]) { + this.main[global_key] = new Worker(this.worker_url, { type: 'module' }); + console.log('new worker created', this.main[global_key]); + } + + this.worker = this.main[global_key]; + console.log('worker', this.worker); + console.log('worker_url', this.worker_url); + + // Set up message listener + this.worker.addEventListener('message', this._handle_message.bind(this)); + + // Initialize the model in the worker + await this._send_message('load', { ...this.smart_embed.opts, worker_id: this.worker_id }); + await new Promise(resolve => { + const check_model_loaded = () => { + console.log('check_model_loaded', this.smart_embed.model_loaded); + if (this.smart_embed.model_loaded) { + resolve(); + } else { + setTimeout(check_model_loaded, 100); + } + }; + check_model_loaded(); + }); + console.log('model loaded'); + } + + async _send_message(method, params) { + return new Promise((resolve, reject) => { + const id = `${this.message_prefix}${this.message_id++}`; + this.message_queue[id] = { resolve, reject }; + this.worker.postMessage({ method, params, id, worker_id: this.worker_id }); + }); + } + + _handle_message(event) { + const { id, result, error, worker_id } = event.data; + if (worker_id !== this.worker_id) return; + if (!id.startsWith(this.message_prefix)) return; + + if (result?.model_loaded) { + console.log('model loaded'); + this.smart_embed.model_loaded = true; + } + if (this.message_queue[id]) { + if (error) { + this.message_queue[id].reject(new Error(error)); + } else { + this.message_queue[id].resolve(result); + } + delete this.message_queue[id]; + } + } + + async count_tokens(input) { + return this._send_message('count_tokens', { input }); + } + + async embed_batch(inputs) { + const filtered_inputs = inputs.filter(item => item.embed_input?.length > 0); + if (!filtered_inputs.length) return []; + const embed_inputs = filtered_inputs.map(item => ({ embed_input: item.embed_input })); + const result = await this._send_message('embed_batch', { inputs: embed_inputs }); + + return filtered_inputs.map((item, i) => { + item.vec = result[i].vec; + item.tokens = result[i].tokens; + return item; + }); + } +} diff --git a/smart-embed-model-v1/build/esbuild.js b/smart-embed-model-v1/build/esbuild.js new file mode 100644 index 00000000..e474310a --- /dev/null +++ b/smart-embed-model-v1/build/esbuild.js @@ -0,0 +1,59 @@ +import * as esbuild from 'esbuild'; +import { readFileSync, writeFileSync } from 'fs'; +import { join, dirname } from 'path'; +import { fileURLToPath } from 'url'; + +const __dirname = dirname(fileURLToPath(import.meta.url)); + +async function build_transformers_iframe_connector() { + try { + const result = await esbuild.build({ + entryPoints: [join(__dirname, 'transformers_iframe_script.js')], + bundle: true, + format: 'esm', + target: 'es2020', + outfile: join(__dirname, '../connectors/transformers_iframe.js'), + write: false, + external: ['@xenova/transformers'], + }); + + const outputContent = result.outputFiles[0].text; + const wrappedContent = `export const transformers_connector = ${JSON.stringify(outputContent)};` + // .replace('@xenova/transformers', 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.13') + // escape ${} + // .replace(/\$\{([\w.]+)\}/g, '\\`+$1+\\`') + ; + + writeFileSync(join(__dirname, '../connectors/transformers_iframe.js'), wrappedContent); + console.log('Build completed successfully.'); + } catch (error) { + console.error('Build failed:', error); + } +} + +async function build_transformers_worker_connector() { + try { + const result = await esbuild.build({ + entryPoints: [join(__dirname, 'transformers_worker_script.js')], + bundle: true, + format: 'esm', + target: 'es2020', + outfile: join(__dirname, '../connectors/transformers_worker.js'), + write: false, + external: ['@xenova/transformers'], + }); + + const connector = result.outputFiles[0].text + .replace('@xenova/transformers', 'https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.13') + ; + writeFileSync(join(__dirname, '../connectors/transformers_worker.js'), connector); + console.log('Build worker completed successfully.'); + } catch (error) { + console.error('Build failed:', error); + } +} + +(async () => { + await build_transformers_iframe_connector(); + await build_transformers_worker_connector(); +})(); \ No newline at end of file diff --git a/smart-embed-model-v1/build/transformers_iframe_script.js b/smart-embed-model-v1/build/transformers_iframe_script.js new file mode 100644 index 00000000..08cd835d --- /dev/null +++ b/smart-embed-model-v1/build/transformers_iframe_script.js @@ -0,0 +1,48 @@ +import { SmartEmbedModel } from '../smart_embed_model.js'; +import { SmartEmbedTransformersAdapter } from '../adapters/transformers.js'; + +let model = null; +let smart_env = { + smart_embed_active_models: {}, + opts: { + modules: { + smart_embed_model: { + adapters: { + transformers: SmartEmbedTransformersAdapter + } + } + } + } +} + +async function processMessage(data) { + const { method, params, id, iframe_id } = data; + try { + let result; + switch (method) { + case 'init': + console.log('init'); + break; + case 'load': + console.log('load', params); + model = await SmartEmbedModel.load(smart_env, { adapter: 'transformers', model_key: params.model_key, ...params }); + result = { model_loaded: true }; + break; + case 'embed_batch': + if (!model) throw new Error('Model not loaded'); + result = await model.embed_batch(params.inputs); + break; + case 'count_tokens': + if (!model) throw new Error('Model not loaded'); + result = await model.count_tokens(params); + break; + default: + throw new Error(`Unknown method: ${method}`); + } + return { id, result, iframe_id }; + } catch (error) { + console.error('Error processing message:', error); + return { id, error: error.message, iframe_id }; + } +} +processMessage({ method: 'init' }); \ No newline at end of file diff --git a/smart-embed-model-v1/build/transformers_worker_script.js b/smart-embed-model-v1/build/transformers_worker_script.js new file mode 100644 index 00000000..f9b43950 --- /dev/null +++ b/smart-embed-model-v1/build/transformers_worker_script.js @@ -0,0 +1,64 @@ +import { SmartEmbedModel } from '../smart_embed_model.js'; +import { SmartEmbedTransformersAdapter } from '../adapters/transformers.js'; + +let model = null; +let smart_env = { + smart_embed_active_models: {}, + opts: { + modules: { + smart_embed_model: { + adapters: { + transformers: SmartEmbedTransformersAdapter + } + } + } + } +} +let processing_message = false; + +async function process_message(data) { + const { method, params, id, worker_id } = data; + try { + let result; + switch (method) { + case 'load': + console.log('load', params); + if(!model) { + model = await SmartEmbedModel.load(smart_env, { adapter: 'transformers', model_key: params.model_key, ...params }); + } + result = { model_loaded: true }; + break; + case 'embed_batch': + if (!model) throw new Error('Model not loaded'); + // wait until finished processing previous message + if (processing_message) while (processing_message) await new Promise(resolve => setTimeout(resolve, 100)); + processing_message = true; + result = await model.embed_batch(params.inputs); + processing_message = false; + break; + case 'count_tokens': + if (!model) throw new Error('Model not loaded'); + // wait until finished processing previous message + if (processing_message) while (processing_message) await new Promise(resolve => setTimeout(resolve, 100)); + processing_message = true; + result = await model.count_tokens(params); + processing_message = false; + break; + default: + throw new Error(`Unknown method: ${method}`); + } + return { id, result, worker_id }; + } catch (error) { + console.error('Error processing message:', error); + return { id, error: error.message, worker_id }; + } +} + +self.addEventListener('message', async (event) => { + const response = await process_message(event.data); + self.postMessage(response); +}); +console.log('worker loaded'); + +// Export process_message for testing purposes +self.process_message = process_message; \ No newline at end of file diff --git a/smart-embed-model-v1/cl100k_base.json b/smart-embed-model-v1/cl100k_base.json new file mode 100644 index 00000000..9b81734d --- /dev/null +++ b/smart-embed-model-v1/cl100k_base.json @@ -0,0 +1 @@ +{"pat_str":"('s|'S|'t|'T|'re|'rE|'Re|'RE|'ve|'vE|'Ve|'VE|'m|'M|'ll|'lL|'Ll|'LL|'d|'D)|[^\\r\\n\\p{L}\\p{N}]?\\p{L}+|\\p{N}{1,3}| ?[^\\s\\p{L}\\p{N}]+[\\r\\n]*|\\s*[\\r\\n]+|\\s+(?!\\S)|\\s+","special_tokens":{"<|endoftext|>":100257,"<|fim_prefix|>":100258,"<|fim_middle|>":100259,"<|fim_suffix|>":100260,"<|endofprompt|>":100276},"bpe_ranks":"! 0 IQ== Ig== Iw== JA== JQ== Jg== Jw== KA== KQ== Kg== Kw== LA== LQ== Lg== Lw== MA== MQ== Mg== Mw== NA== NQ== Ng== Nw== OA== OQ== Og== Ow== PA== PQ== Pg== Pw== QA== QQ== Qg== Qw== RA== RQ== 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models.json\nvar models_default = {\n \"TaylorAI/bge-micro-v2\": {\n model_key: \"TaylorAI/bge-micro-v2\",\n batch_size: 1,\n dims: 384,\n max_tokens: 512,\n name: \"BGE-micro-v2\",\n description: \"Local, 512 tokens, 384 dim\",\n adapter: \"transformers\"\n },\n \"andersonbcdefg/bge-small-4096\": {\n model_key: \"andersonbcdefg/bge-small-4096\",\n batch_size: 1,\n dims: 384,\n max_tokens: 4096,\n name: \"BGE-small-4K\",\n description: \"Local, 4,096 tokens, 384 dim\",\n adapter: \"transformers\"\n },\n \"Xenova/jina-embeddings-v2-base-zh\": {\n model_key: \"Xenova/jina-embeddings-v2-base-zh\",\n batch_size: 1,\n dims: 512,\n max_tokens: 8192,\n name: \"Jina-v2-base-zh-8K\",\n description: \"Local, 8,192 tokens, 512 dim, Chinese/English bilingual\",\n adapter: \"transformers\"\n },\n \"text-embedding-3-small\": {\n model_key: \"text-embedding-3-small\",\n batch_size: 50,\n dims: 1536,\n max_tokens: 8191,\n name: \"OpenAI Text-3 Small\",\n description: \"API, 8,191 tokens, 1,536 dim\",\n endpoint: \"https://api.openai.com/v1/embeddings\",\n adapter: \"openai\"\n },\n \"text-embedding-3-large\": {\n model_key: \"text-embedding-3-large\",\n batch_size: 50,\n dims: 3072,\n max_tokens: 8191,\n name: \"OpenAI Text-3 Large\",\n description: \"API, 8,191 tokens, 3,072 dim\",\n endpoint: \"https://api.openai.com/v1/embeddings\",\n adapter: \"openai\"\n },\n \"text-embedding-3-small-512\": {\n model_key: \"text-embedding-3-small\",\n batch_size: 50,\n dims: 512,\n max_tokens: 8191,\n name: \"OpenAI Text-3 Small - 512\",\n description: \"API, 8,191 tokens, 512 dim\",\n endpoint: \"https://api.openai.com/v1/embeddings\",\n adapter: \"openai\"\n },\n \"text-embedding-3-large-256\": {\n model_key: \"text-embedding-3-large\",\n batch_size: 50,\n dims: 256,\n max_tokens: 8191,\n name: \"OpenAI Text-3 Large - 256\",\n description: \"API, 8,191 tokens, 256 dim\",\n endpoint: \"https://api.openai.com/v1/embeddings\",\n adapter: \"openai\"\n },\n \"text-embedding-ada-002\": {\n model_key: \"text-embedding-ada-002\",\n batch_size: 50,\n dims: 1536,\n max_tokens: 8191,\n name: \"OpenAI Ada\",\n description: \"API, 8,191 tokens, 1,536 dim\",\n endpoint: \"https://api.openai.com/v1/embeddings\",\n adapter: \"openai\"\n },\n \"Xenova/jina-embeddings-v2-small-en\": {\n model_key: \"Xenova/jina-embeddings-v2-small-en\",\n batch_size: 1,\n dims: 512,\n max_tokens: 8192,\n name: \"Jina-v2-small-en\",\n description: \"Local, 8,192 tokens, 512 dim\",\n adapter: \"transformers\"\n },\n \"nomic-ai/nomic-embed-text-v1.5\": {\n model_key: \"nomic-ai/nomic-embed-text-v1.5\",\n batch_size: 1,\n dims: 256,\n max_tokens: 8192,\n name: \"Nomic-embed-text-v1.5\",\n description: \"Local, 8,192 tokens, 256 dim\",\n adapter: \"transformers\"\n },\n \"Xenova/bge-small-en-v1.5\": {\n model_key: \"Xenova/bge-small-en-v1.5\",\n batch_size: 1,\n dims: 384,\n max_tokens: 512,\n name: \"BGE-small\",\n description: \"Local, 512 tokens, 384 dim\",\n adapter: \"transformers\"\n },\n \"nomic-ai/nomic-embed-text-v1\": {\n model_key: \"nomic-ai/nomic-embed-text-v1\",\n batch_size: 1,\n dims: 768,\n max_tokens: 2048,\n name: \"Nomic-embed-text\",\n description: \"Local, 2,048 tokens, 768 dim\",\n adapter: \"transformers\"\n }\n};\n\n// smart_embed_model.js\nvar SmartEmbedModel = class _SmartEmbedModel {\n /**\n * Create a SmartEmbed instance.\n * @param {string} env - The environment to use.\n * @param {object} opts - Full model configuration object or at least a model_key and adapter\n */\n constructor(env, opts = {}) {\n this.env = env;\n this.opts = {\n ...models_default[opts.embed_model_key],\n ...opts\n };\n console.log(this.opts);\n if (!this.opts.adapter)\n return console.warn(\"SmartEmbedModel adapter not set\");\n if (!this.env.opts.smart_embed_adapters[this.opts.adapter])\n return console.warn(`SmartEmbedModel adapter ${this.opts.adapter} not found`);\n this.opts.use_gpu = !!navigator.gpu && this.opts.gpu_batch_size !== 0;\n if (this.opts.adapter === \"transformers\" && this.opts.use_gpu)\n this.opts.batch_size = this.opts.gpu_batch_size || 10;\n this.adapter = new this.env.opts.smart_embed_adapters[this.opts.adapter](this);\n }\n /**\n * Used to load a model with a given configuration.\n * @param {*} env \n * @param {*} opts \n */\n static async load(env, opts = {}) {\n try {\n const model2 = new _SmartEmbedModel(env, opts);\n await model2.adapter.load();\n env.smart_embed_active_models[opts.embed_model_key] = model2;\n return model2;\n } catch (error) {\n console.error(`Error loading model ${opts.model_key}:`, error);\n return null;\n }\n }\n /**\n * Count the number of tokens in the input string.\n * @param {string} input - The input string to process.\n * @returns {Promise} A promise that resolves with the number of tokens.\n */\n async count_tokens(input) {\n return this.adapter.count_tokens(input);\n }\n /**\n * Embed the input into a numerical array.\n * @param {string|Object} input - The input to embed. Can be a string or an object with an \"embed_input\" property.\n * @returns {Promise} A promise that resolves with an object containing the embedding vector at `vec` and the number of tokens at `tokens`.\n */\n async embed(input) {\n if (typeof input === \"string\")\n input = { embed_input: input };\n return (await this.embed_batch([input]))[0];\n }\n /**\n * Embed a batch of inputs into arrays of numerical arrays.\n * @param {Array} inputs - The array of inputs to embed. Each input can be a string or an object with an \"embed_input\" property.\n * @returns {Promise>} A promise that resolves with an array of objects containing `vec` and `tokens` properties.\n */\n async embed_batch(inputs) {\n return await this.adapter.embed_batch(inputs);\n }\n get batch_size() {\n return this.opts.batch_size || 1;\n }\n get max_tokens() {\n return this.opts.max_tokens || 512;\n }\n};\n\n// adapters/_adapter.js\nvar SmartEmbedAdapter = class {\n constructor(smart_embed) {\n this.smart_embed = smart_embed;\n }\n async load() {\n throw new Error(\"Not implemented\");\n }\n async count_tokens(input) {\n throw new Error(\"Not implemented\");\n }\n async embed(input) {\n throw new Error(\"Not implemented\");\n }\n async embed_batch(input) {\n throw new Error(\"Not implemented\");\n }\n};\n\n// adapters/transformers.js\nvar SmartEmbedTransformersAdapter = class extends SmartEmbedAdapter {\n constructor(smart_embed) {\n super(smart_embed);\n this.model = null;\n this.tokenizer = null;\n }\n get batch_size() {\n if (this.use_gpu && this.smart_embed.opts.gpu_batch_size)\n return this.smart_embed.opts.gpu_batch_size;\n return this.smart_embed.opts.batch_size || 1;\n }\n get max_tokens() {\n return this.smart_embed.opts.max_tokens || 512;\n }\n get use_gpu() {\n return this.smart_embed.opts.use_gpu || false;\n }\n async load() {\n const { pipeline, env, AutoTokenizer } = await import(\"@xenova/transformers\");\n env.allowLocalModels = false;\n const pipeline_opts = {\n quantized: true\n };\n if (this.use_gpu) {\n console.log(\"[Transformers] Using GPU\");\n pipeline_opts.device = \"webgpu\";\n pipeline_opts.dtype = \"fp32\";\n } else {\n console.log(\"[Transformers] Using CPU\");\n env.backends.onnx.wasm.numThreads = 8;\n }\n this.model = await pipeline(\"feature-extraction\", this.smart_embed.opts.model_key, pipeline_opts);\n this.tokenizer = await AutoTokenizer.from_pretrained(this.smart_embed.opts.model_key);\n }\n async count_tokens(input) {\n if (!this.tokenizer)\n await this.load();\n const { input_ids } = await this.tokenizer(input);\n return { tokens: input_ids.data.length };\n }\n async embed_batch(inputs) {\n if (!this.model)\n await this.load();\n const filtered_inputs = inputs.filter((item) => item.embed_input?.length > 0);\n if (!filtered_inputs.length)\n return [];\n if (filtered_inputs.length > this.batch_size) {\n throw new Error(`Input size (${filtered_inputs.length}) exceeds maximum batch size (${this.batch_size})`);\n }\n const tokens = await Promise.all(filtered_inputs.map((item) => this.count_tokens(item.embed_input)));\n const embed_inputs = await Promise.all(filtered_inputs.map(async (item, i) => {\n if (tokens[i].tokens < this.max_tokens)\n return item.embed_input;\n let token_ct = tokens[i].tokens;\n let truncated_input = item.embed_input;\n while (token_ct > this.max_tokens) {\n const pct = this.max_tokens / token_ct;\n const max_chars = Math.floor(truncated_input.length * pct * 0.9);\n truncated_input = truncated_input.substring(0, max_chars) + \"...\";\n token_ct = (await this.count_tokens(truncated_input)).tokens;\n }\n tokens[i].tokens = token_ct;\n return truncated_input;\n }));\n try {\n const resp = await this.model(embed_inputs, { pooling: \"mean\", normalize: true });\n return filtered_inputs.map((item, i) => {\n item.vec = Array.from(resp[i].data).map((val) => Math.round(val * 1e8) / 1e8);\n item.tokens = tokens[i].tokens;\n return item;\n });\n } catch (err) {\n console.error(\"error_embedding_batch\", err);\n return Promise.all(filtered_inputs.map((item) => this.embed(item.embed_input)));\n }\n }\n};\n\n// build/transformers_iframe_script.js\nvar model = null;\nvar smart_env = {\n smart_embed_active_models: {},\n opts: {\n smart_embed_adapters: {\n transformers: SmartEmbedTransformersAdapter\n }\n }\n};\nasync function processMessage(data) {\n const { method, params, id, iframe_id } = data;\n try {\n let result;\n switch (method) {\n case \"init\":\n console.log(\"init\");\n break;\n case \"load\":\n console.log(\"load\", params);\n model = await SmartEmbedModel.load(smart_env, { adapter: \"transformers\", model_key: params.model_key, ...params });\n result = { model_loaded: true };\n break;\n case \"embed_batch\":\n if (!model)\n throw new Error(\"Model not loaded\");\n result = await model.embed_batch(params.inputs);\n break;\n case \"count_tokens\":\n if (!model)\n throw new Error(\"Model not loaded\");\n result = await model.count_tokens(params);\n break;\n default:\n throw new Error(`Unknown method: ${method}`);\n }\n return { id, result, iframe_id };\n } catch (error) {\n console.error(\"Error processing message:\", error);\n return { id, error: error.message, iframe_id };\n }\n}\nprocessMessage({ method: \"init\" });\n"; \ No newline at end of file diff --git a/smart-embed-model-v1/connectors/transformers_worker.js b/smart-embed-model-v1/connectors/transformers_worker.js new file mode 100644 index 00000000..7b3c7d42 --- /dev/null +++ b/smart-embed-model-v1/connectors/transformers_worker.js @@ -0,0 +1,350 @@ +// models.json +var models_default = { + "TaylorAI/bge-micro-v2": { + model_key: "TaylorAI/bge-micro-v2", + batch_size: 1, + dims: 384, + max_tokens: 512, + name: "BGE-micro-v2", + description: "Local, 512 tokens, 384 dim", + adapter: "transformers" + }, + "andersonbcdefg/bge-small-4096": { + model_key: "andersonbcdefg/bge-small-4096", + batch_size: 1, + dims: 384, + max_tokens: 4096, + name: "BGE-small-4K", + description: "Local, 4,096 tokens, 384 dim", + adapter: "transformers" + }, + "Xenova/jina-embeddings-v2-base-zh": { + model_key: "Xenova/jina-embeddings-v2-base-zh", + batch_size: 1, + dims: 512, + max_tokens: 8192, + name: "Jina-v2-base-zh-8K", + description: "Local, 8,192 tokens, 512 dim, Chinese/English bilingual", + adapter: "transformers" + }, + "text-embedding-3-small": { + model_key: "text-embedding-3-small", + batch_size: 50, + dims: 1536, + max_tokens: 8191, + name: "OpenAI Text-3 Small", + description: "API, 8,191 tokens, 1,536 dim", + endpoint: "https://api.openai.com/v1/embeddings", + adapter: "openai" + }, + "text-embedding-3-large": { + model_key: "text-embedding-3-large", + batch_size: 50, + dims: 3072, + max_tokens: 8191, + name: "OpenAI Text-3 Large", + description: "API, 8,191 tokens, 3,072 dim", + endpoint: "https://api.openai.com/v1/embeddings", + adapter: "openai" + }, + "text-embedding-3-small-512": { + model_key: "text-embedding-3-small", + batch_size: 50, + dims: 512, + max_tokens: 8191, + name: "OpenAI Text-3 Small - 512", + description: "API, 8,191 tokens, 512 dim", + endpoint: "https://api.openai.com/v1/embeddings", + adapter: "openai" + }, + "text-embedding-3-large-256": { + model_key: "text-embedding-3-large", + batch_size: 50, + dims: 256, + max_tokens: 8191, + name: "OpenAI Text-3 Large - 256", + description: "API, 8,191 tokens, 256 dim", + endpoint: "https://api.openai.com/v1/embeddings", + adapter: "openai" + }, + "text-embedding-ada-002": { + model_key: "text-embedding-ada-002", + batch_size: 50, + dims: 1536, + max_tokens: 8191, + name: "OpenAI Ada", + description: "API, 8,191 tokens, 1,536 dim", + endpoint: "https://api.openai.com/v1/embeddings", + adapter: "openai" + }, + "Xenova/jina-embeddings-v2-small-en": { + model_key: "Xenova/jina-embeddings-v2-small-en", + batch_size: 1, + dims: 512, + max_tokens: 8192, + name: "Jina-v2-small-en", + description: "Local, 8,192 tokens, 512 dim", + adapter: "transformers" + }, + "nomic-ai/nomic-embed-text-v1.5": { + model_key: "nomic-ai/nomic-embed-text-v1.5", + batch_size: 1, + dims: 256, + max_tokens: 8192, + name: "Nomic-embed-text-v1.5", + description: "Local, 8,192 tokens, 256 dim", + adapter: "transformers" + }, + "Xenova/bge-small-en-v1.5": { + model_key: "Xenova/bge-small-en-v1.5", + batch_size: 1, + dims: 384, + max_tokens: 512, + name: "BGE-small", + description: "Local, 512 tokens, 384 dim", + adapter: "transformers" + }, + "nomic-ai/nomic-embed-text-v1": { + model_key: "nomic-ai/nomic-embed-text-v1", + batch_size: 1, + dims: 768, + max_tokens: 2048, + name: "Nomic-embed-text", + description: "Local, 2,048 tokens, 768 dim", + adapter: "transformers" + } +}; + +// smart_embed_model.js +var SmartEmbedModel = class _SmartEmbedModel { + /** + * Create a SmartEmbed instance. + * @param {string} env - The environment to use. + * @param {object} opts - Full model configuration object or at least a model_key and adapter + */ + constructor(env, opts = {}) { + this.env = env; + this.opts = { + ...models_default[opts.embed_model_key], + ...opts + }; + console.log(this.opts); + if (!this.opts.adapter) + return console.warn("SmartEmbedModel adapter not set"); + if (!this.env.opts.modules.smart_embed_model.adapters[this.opts.adapter]) + return console.warn(`SmartEmbedModel adapter ${this.opts.adapter} not found`); + this.opts.use_gpu = !!navigator.gpu && this.opts.gpu_batch_size !== 0; + if (this.opts.adapter === "transformers" && this.opts.use_gpu) + this.opts.batch_size = this.opts.gpu_batch_size || 10; + this.adapter = new this.env.opts.modules.smart_embed_model.adapters[this.opts.adapter](this); + } + /** + * Used to load a model with a given configuration. + * @param {*} env + * @param {*} opts + */ + static async load(env, opts = {}) { + try { + const model2 = new _SmartEmbedModel(env, opts); + await model2.adapter.load(); + env.smart_embed_active_models[opts.embed_model_key] = model2; + return model2; + } catch (error) { + console.error(`Error loading model ${opts.model_key}:`, error); + return null; + } + } + /** + * Count the number of tokens in the input string. + * @param {string} input - The input string to process. + * @returns {Promise} A promise that resolves with the number of tokens. + */ + async count_tokens(input) { + return this.adapter.count_tokens(input); + } + /** + * Embed the input into a numerical array. + * @param {string|Object} input - The input to embed. Can be a string or an object with an "embed_input" property. + * @returns {Promise} A promise that resolves with an object containing the embedding vector at `vec` and the number of tokens at `tokens`. + */ + async embed(input) { + if (typeof input === "string") + input = { embed_input: input }; + return (await this.embed_batch([input]))[0]; + } + /** + * Embed a batch of inputs into arrays of numerical arrays. + * @param {Array} inputs - The array of inputs to embed. Each input can be a string or an object with an "embed_input" property. + * @returns {Promise>} A promise that resolves with an array of objects containing `vec` and `tokens` properties. + */ + async embed_batch(inputs) { + return await this.adapter.embed_batch(inputs); + } + get batch_size() { + return this.opts.batch_size || 1; + } + get max_tokens() { + return this.opts.max_tokens || 512; + } +}; + +// adapters/_adapter.js +var SmartEmbedAdapter = class { + constructor(smart_embed) { + this.smart_embed = smart_embed; + } + async load() { + throw new Error("Not implemented"); + } + async count_tokens(input) { + throw new Error("Not implemented"); + } + async embed(input) { + throw new Error("Not implemented"); + } + async embed_batch(input) { + throw new Error("Not implemented"); + } +}; + +// adapters/transformers.js +var SmartEmbedTransformersAdapter = class extends SmartEmbedAdapter { + constructor(smart_embed) { + super(smart_embed); + this.model = null; + this.tokenizer = null; + } + get batch_size() { + if (this.use_gpu && this.smart_embed.opts.gpu_batch_size) + return this.smart_embed.opts.gpu_batch_size; + return this.smart_embed.opts.batch_size || 1; + } + get max_tokens() { + return this.smart_embed.opts.max_tokens || 512; + } + get use_gpu() { + return this.smart_embed.opts.use_gpu || false; + } + async load() { + const { pipeline, env, AutoTokenizer } = await import("https://cdn.jsdelivr.net/npm/@huggingface/transformers@3.0.0-alpha.13"); + env.allowLocalModels = false; + const pipeline_opts = { + quantized: true + }; + if (this.use_gpu) { + console.log("[Transformers] Using GPU"); + pipeline_opts.device = "webgpu"; + pipeline_opts.dtype = "fp32"; + } else { + console.log("[Transformers] Using CPU"); + env.backends.onnx.wasm.numThreads = 8; + } + this.model = await pipeline("feature-extraction", this.smart_embed.opts.model_key, pipeline_opts); + this.tokenizer = await AutoTokenizer.from_pretrained(this.smart_embed.opts.model_key); + } + async count_tokens(input) { + if (!this.tokenizer) + await this.load(); + const { input_ids } = await this.tokenizer(input); + return { tokens: input_ids.data.length }; + } + async embed_batch(inputs) { + if (!this.model) + await this.load(); + const filtered_inputs = inputs.filter((item) => item.embed_input?.length > 0); + if (!filtered_inputs.length) + return []; + if (filtered_inputs.length > this.batch_size) { + throw new Error(`Input size (${filtered_inputs.length}) exceeds maximum batch size (${this.batch_size})`); + } + const tokens = await Promise.all(filtered_inputs.map((item) => this.count_tokens(item.embed_input))); + const embed_inputs = await Promise.all(filtered_inputs.map(async (item, i) => { + if (tokens[i].tokens < this.max_tokens) + return item.embed_input; + let token_ct = tokens[i].tokens; + let truncated_input = item.embed_input; + while (token_ct > this.max_tokens) { + const pct = this.max_tokens / token_ct; + const max_chars = Math.floor(truncated_input.length * pct * 0.9); + truncated_input = truncated_input.substring(0, max_chars) + "..."; + token_ct = (await this.count_tokens(truncated_input)).tokens; + } + tokens[i].tokens = token_ct; + return truncated_input; + })); + try { + const resp = await this.model(embed_inputs, { pooling: "mean", normalize: true }); + return filtered_inputs.map((item, i) => { + item.vec = Array.from(resp[i].data).map((val) => Math.round(val * 1e8) / 1e8); + item.tokens = tokens[i].tokens; + return item; + }); + } catch (err) { + console.error("error_embedding_batch", err); + return Promise.all(filtered_inputs.map((item) => this.embed(item.embed_input))); + } + } +}; + +// build/transformers_worker_script.js +var model = null; +var smart_env = { + smart_embed_active_models: {}, + opts: { + modules: { + smart_embed_model: { + adapters: { + transformers: SmartEmbedTransformersAdapter + } + } + } + } +}; +var processing_message = false; +async function process_message(data) { + const { method, params, id, worker_id } = data; + try { + let result; + switch (method) { + case "load": + console.log("load", params); + if (!model) { + model = await SmartEmbedModel.load(smart_env, { adapter: "transformers", model_key: params.model_key, ...params }); + } + result = { model_loaded: true }; + break; + case "embed_batch": + if (!model) + throw new Error("Model not loaded"); + if (processing_message) + while (processing_message) + await new Promise((resolve) => setTimeout(resolve, 100)); + processing_message = true; + result = await model.embed_batch(params.inputs); + processing_message = false; + break; + case "count_tokens": + if (!model) + throw new Error("Model not loaded"); + if (processing_message) + while (processing_message) + await new Promise((resolve) => setTimeout(resolve, 100)); + processing_message = true; + result = await model.count_tokens(params); + processing_message = false; + break; + default: + throw new Error(`Unknown method: ${method}`); + } + return { id, result, worker_id }; + } catch (error) { + console.error("Error processing message:", error); + return { id, error: error.message, worker_id }; + } +} +self.addEventListener("message", async (event) => { + const response = await process_message(event.data); + self.postMessage(response); +}); +console.log("worker loaded"); +self.process_message = process_message; diff --git a/smart-embed-model-v1/models.json b/smart-embed-model-v1/models.json new file mode 100644 index 00000000..d1db9500 --- /dev/null +++ b/smart-embed-model-v1/models.json @@ -0,0 +1,115 @@ +{ + "TaylorAI/bge-micro-v2": { + "model_key": "TaylorAI/bge-micro-v2", + "batch_size": 1, + "dims": 384, + "max_tokens": 512, + "name": "BGE-micro-v2", + "description": "Local, 512 tokens, 384 dim", + "adapter": "transformers" + }, + "andersonbcdefg/bge-small-4096": { + "model_key": "andersonbcdefg/bge-small-4096", + "batch_size": 1, + "dims": 384, + "max_tokens": 4096, + "name": "BGE-small-4K", + "description": "Local, 4,096 tokens, 384 dim", + "adapter": "transformers" + }, + "Xenova/jina-embeddings-v2-base-zh": { + "model_key": "Xenova/jina-embeddings-v2-base-zh", + "batch_size": 1, + "dims": 512, + "max_tokens": 8192, + "name": "Jina-v2-base-zh-8K", + "description": "Local, 8,192 tokens, 512 dim, Chinese/English bilingual", + "adapter": "transformers" + }, + "text-embedding-3-small": { + "model_key": "text-embedding-3-small", + "batch_size": 50, + "dims": 1536, + "max_tokens": 8191, + "name": "OpenAI Text-3 Small", + "description": "API, 8,191 tokens, 1,536 dim", + "endpoint": "https://api.openai.com/v1/embeddings", + "adapter": "openai" + }, + "text-embedding-3-large": { + "model_key": "text-embedding-3-large", + "batch_size": 50, + "dims": 3072, + "max_tokens": 8191, + "name": "OpenAI Text-3 Large", + "description": "API, 8,191 tokens, 3,072 dim", + "endpoint": "https://api.openai.com/v1/embeddings", + "adapter": "openai" + }, + "text-embedding-3-small-512": { + "model_key": "text-embedding-3-small", + "batch_size": 50, + "dims": 512, + "max_tokens": 8191, + "name": "OpenAI Text-3 Small - 512", + "description": "API, 8,191 tokens, 512 dim", + "endpoint": "https://api.openai.com/v1/embeddings", + "adapter": "openai" + }, + "text-embedding-3-large-256": { + "model_key": "text-embedding-3-large", + "batch_size": 50, + "dims": 256, + "max_tokens": 8191, + "name": "OpenAI Text-3 Large - 256", + "description": "API, 8,191 tokens, 256 dim", + "endpoint": "https://api.openai.com/v1/embeddings", + "adapter": "openai" + }, + "text-embedding-ada-002": { + "model_key": "text-embedding-ada-002", + "batch_size": 50, + "dims": 1536, + "max_tokens": 8191, + "name": "OpenAI Ada", + "description": "API, 8,191 tokens, 1,536 dim", + "endpoint": "https://api.openai.com/v1/embeddings", + "adapter": "openai" + }, + "Xenova/jina-embeddings-v2-small-en": { + "model_key": "Xenova/jina-embeddings-v2-small-en", + "batch_size": 1, + "dims": 512, + "max_tokens": 8192, + "name": "Jina-v2-small-en", + "description": "Local, 8,192 tokens, 512 dim", + "adapter": "transformers" + }, + "nomic-ai/nomic-embed-text-v1.5": { + "model_key": "nomic-ai/nomic-embed-text-v1.5", + "batch_size": 1, + "dims": 256, + "max_tokens": 8192, + "name": "Nomic-embed-text-v1.5", + "description": "Local, 8,192 tokens, 256 dim", + "adapter": "transformers" + }, + "Xenova/bge-small-en-v1.5": { + "model_key": "Xenova/bge-small-en-v1.5", + "batch_size": 1, + "dims": 384, + "max_tokens": 512, + "name": "BGE-small", + "description": "Local, 512 tokens, 384 dim", + "adapter": "transformers" + }, + "nomic-ai/nomic-embed-text-v1": { + "model_key": "nomic-ai/nomic-embed-text-v1", + "batch_size": 1, + "dims": 768, + "max_tokens": 2048, + "name": "Nomic-embed-text", + "description": "Local, 2,048 tokens, 768 dim", + "adapter": "transformers" + } +} \ No newline at end of file diff --git a/smart-embed-model-v1/package-lock.json b/smart-embed-model-v1/package-lock.json new file mode 100644 index 00000000..2c3365b4 --- /dev/null +++ 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"brianpetro/jsbrains" + }, + "bugs": { + "url": "https://github.com/brianpetro/jsbrains/issues" + }, + "homepage": "https://jsbrains.org", + "devDependencies": { + "ava": "^6.0.1", + "dotenv": "^16.3.1", + "esbuild": "^0.23.1", + "jsdom": "^24.1.0" + }, + "dependencies": { + "js-tiktoken": "^1.0.11", + "smart-model": "../smart-model" + } +} diff --git a/smart-embed-model-v1/smart_embed_model.js b/smart-embed-model-v1/smart_embed_model.js new file mode 100644 index 00000000..f7106607 --- /dev/null +++ b/smart-embed-model-v1/smart_embed_model.js @@ -0,0 +1,142 @@ +// Copyright (c) Brian Joseph Petro + +// Permission is hereby granted, free of charge, to any person obtaining +// a copy of this software and associated documentation files (the +// "Software"), to deal in the Software without restriction, including +// without limitation the rights to use, copy, modify, merge, publish, +// distribute, sublicense, and/or sell copies of the Software, and to +// permit persons to whom the Software is furnished to do so, subject to +// the following conditions: + +// The above copyright notice and this permission notice shall be +// included in all copies or substantial portions of the Software. + +// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, +// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF +// MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND +// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE +// LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION +// OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION +// WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. + +import { SmartModel } from "smart-model"; +import embed_models from './models.json' with { type: 'json' }; +// import embed_models from './models.json' assert { type: 'json' }; +export class SmartEmbedModel extends SmartModel { + /** + * Create a SmartEmbed instance. + * @param {string} env - The environment to use. + * @param {object} opts - Full model configuration object or at least a model_key and adapter + */ + constructor(env, opts={}) { + super(opts); + if(this.opts.model_key === "None") return console.log(`Smart Embed Model: No active embedding model for ${this.collection_key}, skipping embedding`); + this.env = env; + this.opts = { + ...( + this.env.opts.modules.smart_embed_model?.class // if is module object (not class, has class key) + ? { ...this.env.opts.modules.smart_embed_model, class: null } + : {} + ), + ...embed_models[opts.model_key], + ...opts, + }; + if(!this.opts.adapter) return console.warn('SmartEmbedModel adapter not set'); + if(!this.opts.adapters[this.opts.adapter]) return console.warn(`SmartEmbedModel adapter ${this.opts.adapter} not found`); + // prepare opts for GPU (likely better handled in future) + this.opts.use_gpu = !!navigator.gpu && this.opts.gpu_batch_size !== 0; + if(this.opts.adapter === 'transformers' && this.opts.use_gpu) this.opts.batch_size = this.opts.gpu_batch_size || 10; + // init adapter + this.adapter = new this.env.opts.modules.smart_embed_model.adapters[this.opts.adapter](this); + } + async load() { + this.loading = true; + await this.adapter.load(); + this.loading = false; + this.loaded = true; + } + /** + * Count the number of tokens in the input string. + * @param {string} input - The input string to process. + * @returns {Promise} A promise that resolves with the number of tokens. + */ + async count_tokens(input) { + return this.adapter.count_tokens(input); + } + + /** + * Embed the input into a numerical array. + * @param {string|Object} input - The input to embed. Can be a string or an object with an "embed_input" property. + * @returns {Promise} A promise that resolves with an object containing the embedding vector at `vec` and the number of tokens at `tokens`. + */ + async embed(input) { + if(typeof input === 'string') input = {embed_input: input}; + return (await this.embed_batch([input]))[0]; + } + + /** + * Embed a batch of inputs into arrays of numerical arrays. + * @param {Array} inputs - The array of inputs to embed. Each input can be a string or an object with an "embed_input" property. + * @returns {Promise>} A promise that resolves with an array of objects containing `vec` and `tokens` properties. + */ + async embed_batch(inputs) { + return await this.adapter.embed_batch(inputs); + } + + get batch_size() { return this.opts.batch_size || 1; } + get max_tokens() { return this.opts.max_tokens || 512; } + get dims() { return this.opts.dims; } + + // TODO: replace static opts with dynamic reference to canonical settings via opts.settings (like smart-chat-model-v2) + get settings() { return this.opts.settings; } // ref to canonical settings + + get settings_config() { return this.process_settings_config(settings_config, 'embed_model'); } + process_setting_key(key) { + return key.replace(/\[EMBED_MODEL\]/g, this.opts.model_key); + } + get_embedding_model_options() { + return Object.entries(embed_models).map(([key, model]) => ({ value: key, name: key })); + } + get_block_embedding_model_options() { + const options = this.get_embedding_model_options(); + options.unshift({ value: 'None', name: 'None' }); + return options; + } + +} + +export const settings_config = { + model_key: { + name: 'Embedding Model', + type: "dropdown", + description: "Select an embedding model.", + options_callback: 'embed_model.get_embedding_model_options', + callback: 'embed_model_changed', + default: 'TaylorAI/bge-micro-v2', + // required: true + }, + "[EMBED_MODEL].min_chars": { + name: 'Minimum Embedding Length', + type: "number", + description: "Minimum length of note to embed.", + placeholder: "Enter number ex. 300", + // callback: 'refresh_embeddings', + // required: true, + }, + "[EMBED_MODEL].api_key": { + name: 'OpenAI API Key for embeddings', + type: "password", + description: "Required for OpenAI embedding models", + placeholder: "Enter OpenAI API Key", + // callback: 'test_api_key_openai_embeddings', + callback: 'restart', // TODO: should be replaced with better unload/reload of smart_embed + conditional: (settings) => !settings.smart_sources.embed_model?.model_key?.includes('/') || !settings.smart_blocks.embed_model?.model_key?.includes('/') + }, + "[EMBED_MODEL].gpu_batch_size": { + name: 'GPU Batch Size', + type: "number", + description: "Number of embeddings to process per batch on GPU. Use 0 to disable GPU.", + placeholder: "Enter number ex. 10", + callback: 'restart', + }, +}; \ No newline at end of file diff --git a/smart-embed-model-v1/test/_env.js b/smart-embed-model-v1/test/_env.js new file mode 100644 index 00000000..691820a6 --- /dev/null +++ b/smart-embed-model-v1/test/_env.js @@ -0,0 +1,33 @@ +import { SmartEnv } from '../../smart-environment/smart_env.js'; +import { SmartEmbedModel } from '../smart_embed_model.js'; +import { SmartEmbedTransformersAdapter } from '../adapters/transformers.js'; +const __dirname = new URL('.', import.meta.url).pathname; + +class TestMain { + load_settings() { return {}; } + save_settings() {} + get settings() { return {}; } + get smart_env_config() { + return { + env_path: __dirname, + env_data_dir: 'test', + modules: { + smart_embed_model: { + class: SmartEmbedModel, + adapters: { + transformers: SmartEmbedTransformersAdapter, + }, + }, + }, + }; + } +} +export async function load_test_env(t) { + const main = new TestMain(); + const env = new SmartEnv(main, main.smart_env_config); + // await env.init(); + await env.opts.modules.smart_embed_model.class.load(env, { + model_key: 'TaylorAI/bge-micro-v2', + }); + t.context.env = env; +} \ No newline at end of file diff --git a/smart-embed-model-v1/test/openai.test.js b/smart-embed-model-v1/test/openai.test.js new file mode 100644 index 00000000..89e1b22b --- /dev/null +++ b/smart-embed-model-v1/test/openai.test.js @@ -0,0 +1,64 @@ +import test from 'ava'; +import { load_test_env } from './_env.js'; +import { SmartEmbedOpenAIAdapter } from '../adapters/openai.js'; + +test.before(async t => { + await load_test_env(t); +}); + +test('init', t => { + t.true(t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter instanceof SmartEmbedOpenAIAdapter); +}); + +test('count_tokens', async t => { + const adapter = t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter; + const result = await adapter.count_tokens('Hello, world!'); + t.is(result, 4); // OpenAI tokenizer might count differently +}); + +test('embed', async t => { + const adapter = t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter; + const embedding = await adapter.embed('Hello, world!'); + t.is(embedding.vec.length, 1536); +}); + +test('embed_batch', async t => { + const adapter = t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter; + adapter.smart_embed.opts.batch_size = 2; + const entity_1 = { embed_input: 'Hello, world!' }; + const entity_2 = { embed_input: 'Hello, universe!' }; + const embeddings = await adapter.embed_batch([entity_1, entity_2]); + t.is(embeddings.length, 2); + t.is(entity_1.vec?.length, 1536); + t.is(entity_2.vec?.length, 1536); +}); + +test('api_key_validation', async t => { + const adapter = t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter; + const is_valid = await adapter.validate_api_key(); + t.true(is_valid); +}); + +test('prepare_embed_input handles long inputs', async t => { + const adapter = t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter; + const long_input = 'a'.repeat(100000); // A very long input that exceeds the token limit + const prepared_input = await adapter.prepare_embed_input(long_input); + const tokens = await adapter.count_tokens(prepared_input); + t.true(tokens <= adapter.max_tokens); +}); + +test('embed_batch handles long inputs', async t => { + const adapter = t.context.env.smart_embed_active_models['text-embedding-ada-002'].adapter; + const long_input = 'a'.repeat(100000); + const short_input = 'Hello, world!'; + const inputs = [ + { embed_input: long_input }, + { embed_input: short_input } + ]; + const embeddings = await adapter.embed_batch(inputs); + t.is(embeddings.length, 2); + t.is(embeddings[0].vec.length, 1536); + t.is(embeddings[1].vec.length, 1536); + t.true(embeddings[0].tokens <= adapter.max_tokens); + t.true(embeddings[1].tokens <= adapter.max_tokens); +}); \ No newline at end of file diff --git a/smart-embed-model-v1/test/transformers.test.js b/smart-embed-model-v1/test/transformers.test.js new file mode 100644 index 00000000..bc318eb9 --- /dev/null +++ b/smart-embed-model-v1/test/transformers.test.js @@ -0,0 +1,34 @@ +import test from 'ava'; +import { load_test_env } from './_env.js'; +import { SmartEmbedTransformersAdapter } from '../adapters/transformers.js'; + +test.before(async t => { + await load_test_env(t); +}); + +test('init', t => { + t.true(t.context.env.smart_embed_active_models['TaylorAI/bge-micro-v2'].adapter instanceof SmartEmbedTransformersAdapter); +}); + +test('count_tokens', async t => { + const adapter = t.context.env.smart_embed_active_models['TaylorAI/bge-micro-v2'].adapter; + const result = await adapter.count_tokens('Hello, world!'); + t.is(result.tokens, 6); +}); + +test('embed', async t => { + const adapter = t.context.env.smart_embed_active_models['TaylorAI/bge-micro-v2'].adapter; + const embedding = await adapter.embed('Hello, world!'); + t.is(embedding.vec.length, 384); +}); + +test('embed_batch', async t => { + const adapter = t.context.env.smart_embed_active_models['TaylorAI/bge-micro-v2'].adapter; + adapter.smart_embed.opts.batch_size = 2; + const entity_1 = { embed_input: 'Hello, world!' }; + const entity_2 = { embed_input: 'Hello, universe!' }; + const embeddings = await adapter.embed_batch([entity_1, entity_2]); + t.is(embeddings.length, 2); + t.is(entity_1.vec?.length, 384); + t.is(entity_2.vec?.length, 384); +}); \ No newline at end of file diff --git a/smart-entities/package.json b/smart-entities/package.json index 45c2920a..d8ec7c01 100644 --- a/smart-entities/package.json +++ b/smart-entities/package.json @@ -25,7 +25,7 @@ }, "dependencies": { "smart-collections": "file:../smart-collections", - "smart-embed-model": "file:../smart-embed-model" + "smart-embed-model": "file:../smart-embed-model-v1" }, "ava": { "files": [ diff --git a/smart-environment/package-lock.json b/smart-environment/package-lock.json index 5643df85..2e614155 100644 --- a/smart-environment/package-lock.json +++ b/smart-environment/package-lock.json @@ -10,7 +10,7 @@ "license": "MIT", "dependencies": { "smart-change": "../smart-change", - "smart-embed-model": "../smart-embed-model", + "smart-embed-model": "../smart-embed-model-v1", "smart-file-system": "../smart-fs", "smart-sources": "../smart-sources", "smart-view": "../smart-view" @@ -24,6 +24,21 @@ } }, "../smart-embed-model": { + "version": "1.0.7", + "extraneous": true, + "license": "MIT", + "dependencies": { + "js-tiktoken": "^1.0.11", + "smart-model": "../smart-model" + }, + "devDependencies": { + "ava": "^6.0.1", + "dotenv": "^16.3.1", + "esbuild": "^0.23.1", + "jsdom": "^24.1.0" + } + }, + "../smart-embed-model-v1": { "version": "1.0.7", "license": "MIT", "dependencies": { @@ -65,7 +80,7 @@ "link": true }, "node_modules/smart-embed-model": { - "resolved": "../smart-embed-model", + "resolved": "../smart-embed-model-v1", "link": true }, "node_modules/smart-file-system": { diff --git a/smart-environment/package.json b/smart-environment/package.json index 285b8f32..2a720e46 100644 --- a/smart-environment/package.json +++ b/smart-environment/package.json @@ -19,7 +19,7 @@ "homepage": "https://jsbrains.org", "dependencies": { "smart-change": "../smart-change", - "smart-embed-model": "../smart-embed-model", + "smart-embed-model": "../smart-embed-model-v1", "smart-file-system": "../smart-fs", "smart-sources": "../smart-sources", "smart-view": "../smart-view" diff --git a/smart-templates/package-lock.json b/smart-templates/package-lock.json index 9f5ff895..3facfa59 100644 --- a/smart-templates/package-lock.json +++ b/smart-templates/package-lock.json @@ -9,7 +9,8 @@ "version": "1.0.2", "license": "MIT", "dependencies": { - "smart-chat-model": "file:../smart-chat-model" + "smart-chat-model": "file:../smart-chat-model-v1", + "smart-sources": "file:../smart-sources" }, "devDependencies": { "ava": "^6.1.3", @@ -17,6 +18,20 @@ } }, "../smart-chat-model": { + "version": "1.0.5", + "extraneous": true, + "license": "MIT", + "dependencies": { + "smart-http-request": "../smart-http-request", + "smart-model": "../smart-model" + }, + "devDependencies": { + "ava": "^6.1.2", + "dotenv": "^16.4.5", + "esbuild": "^0.20.2" + } + }, + "../smart-chat-model-v1": { "version": "1.0.5", "license": "MIT", "devDependencies": { @@ -24,6 +39,16 @@ "esbuild": "^0.20.2" } }, + "../smart-sources": { + "version": "2.0.0", + "license": "MIT", + "dependencies": { + "smart-entities": "file:../smart-entities" + }, + "devDependencies": { + "ava": "^6.0.1" + } + }, "node_modules/@mapbox/node-pre-gyp": { "version": "1.0.11", "resolved": "https://registry.npmjs.org/@mapbox/node-pre-gyp/-/node-pre-gyp-1.0.11.tgz", @@ -1781,7 +1806,11 @@ } }, "node_modules/smart-chat-model": { - "resolved": "../smart-chat-model", + "resolved": "../smart-chat-model-v1", + "link": true + }, + "node_modules/smart-sources": { + "resolved": "../smart-sources", "link": true }, "node_modules/sprintf-js": { diff --git a/smart-templates/package.json b/smart-templates/package.json index 8bd1c5cf..693c53ce 100644 --- a/smart-templates/package.json +++ b/smart-templates/package.json @@ -19,7 +19,7 @@ }, "homepage": "https://jsbrains.org", "dependencies": { - "smart-chat-model": "file:../smart-chat-model", + "smart-chat-model": "file:../smart-chat-model-v1", "smart-sources": "file:../smart-sources" }, "devDependencies": {