Add README.md files for the plugins.

.github/workflows/ci_plugins.yaml

@@ -30,7 +30,10 @@ jobs:
           for file in "${changed_files[@]}"; do
             if [[ "$file" =~ ^plugins/ && ! "$file" =~ ^plugins/template/ ]]; then
               plugin_name=$(echo "$file" | cut -d '/' -f 2)
-              plugin_set[$plugin_name]=1
+              # Check if the plugin has a pyproject.toml file
+              if [[ -f "plugins/$plugin_name/pyproject.toml" ]]; then
+                plugin_set[$plugin_name]=1
+              fi
             fi
           done
           plugins=("${!plugin_set[@]}")

CHANGELOG.md

@@ -37,6 +37,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Fix the issue where MongoDB did not create the output table.
 - Fix the bug in the CI where plugins are skipping tests.
 - Updated CONTRIBUTING.md
+- Add README.md files for the plugins.
 
 #### New Features & Functionality
 

plugins/README.md

@@ -0,0 +1,5 @@
+# Superduper plugins
+
+Superduper plugins are a collection of plugins that provide additional functionality to the Superduper framework.
+
+These plugins are designed to be easily integrated into the Superduper framework, and provide additional functionality to the Superduper framework.

plugins/anthropic/README.md

@@ -0,0 +1,41 @@
+<!-- Auto-generated content start -->
+# superduper_anthropic
+
+Superduper allows users to work with anthropic API models. The key integration is the integration of high-quality API-hosted LLM services.
+
+## Installation
+
+```bash
+pip install superduper_anthropic
+```
+
+## API
+
+
+- [Code](https://github.com/superduper-io/superduper/tree/main/plugins/anthropic)
+- [API-docs](/docs/api/plugins/superduper_anthropic)
+
+| Class | Description |
+|---|---|
+| `superduper_anthropic.model.Anthropic` | Anthropic predictor. |
+| `superduper_anthropic.model.AnthropicCompletions` | Cohere completions (chat) predictor. |
+
+
+## Examples
+
+### AnthropicCompletions
+
+```python
+from superduper_anthropic.model import AnthropicCompletions
+
+model = AnthropicCompletions(
+    identifier="claude-2.1",
+    predict_kwargs={"max_tokens": 64},
+)
+model.predict_batches(["Hello, world!"])
+```
+
+
+<!-- Auto-generated content end -->
+
+<!-- Add your additional content below -->

plugins/anthropic/pyproject.toml

@@ -5,6 +5,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "superduper_anthropic"
 readme = "README.md"
+description = "Superduper allows users to work with anthropic API models. The key integration is the integration of high-quality API-hosted LLM services."
 license = {file = "LICENSE"}
 maintainers = [{name = "superduper.io, Inc.", email = "opensource@superduper.io"}]
 keywords = [

plugins/anthropic/superduper_anthropic/model.py

@@ -36,6 +36,17 @@ class AnthropicCompletions(Anthropic):
     """Cohere completions (chat) predictor.
 
     :param prompt: The prompt to use to seed the response.
+
+    Example:
+    -------
+    >>> from superduper_anthropic.model import AnthropicCompletions
+    >>>
+    >>> model = AnthropicCompletions(
+    >>>     identifier="claude-2.1",
+    >>>     predict_kwargs={"max_tokens": 64},
+    >>> )
+    >>> model.predict_batches(["Hello, world!"])
+
     """
 
     prompt: str = ''

plugins/cohere/README.md

@@ -0,0 +1,46 @@
+<!-- Auto-generated content start -->
+# superduper_cohere
+
+Superduper allows users to work with cohere API models.
+
+## Installation
+
+```bash
+pip install superduper_cohere
+```
+
+## API
+
+
+- [Code](https://github.com/superduper-io/superduper/tree/main/plugins/cohere)
+- [API-docs](/docs/api/plugins/superduper_cohere)
+
+| Class | Description |
+|---|---|
+| `superduper_cohere.model.Cohere` | Cohere predictor. |
+| `superduper_cohere.model.CohereEmbed` | Cohere embedding predictor. |
+| `superduper_cohere.model.CohereGenerate` | Cohere realistic text generator (chat predictor). |
+
+
+## Examples
+
+### CohereEmbed
+
+```python
+from superduper_cohere.model import CohereEmbed
+model = CohereEmbed(identifier='embed-english-v2.0', batch_size=1)
+model..predict('Hello world')
+```
+
+### CohereGenerate
+
+```python
+from superduper_cohere.model import CohereGenerate
+model = CohereGenerate(identifier='base-light', prompt='Hello, {context}')
+model.predict('', context=['world!'])
+```
+
+
+<!-- Auto-generated content end -->
+
+<!-- Add your additional content below -->

plugins/cohere/pyproject.toml

@@ -5,6 +5,7 @@ build-backend = "setuptools.build_meta"
 [project]
 name = "superduper_cohere"
 readme = "README.md"
+description = "Superduper allows users to work with cohere API models."
 license = {file = "LICENSE"}
 maintainers = [{name = "superduper.io, Inc.", email = "opensource@superduper.io"}]
 keywords = [

plugins/cohere/superduper_cohere/model.py

@@ -34,6 +34,13 @@ class CohereEmbed(Cohere):
 
     :param shape: The shape as ``tuple`` of the embedding.
     :param batch_size: The batch size to use for the predictor.
+
+    Example:
+    -------
+    >>> from superduper_cohere.model import CohereEmbed
+    >>> model = CohereEmbed(identifier='embed-english-v2.0', batch_size=1)
+    >>> model..predict('Hello world')
+
     """
 
     shapes: t.ClassVar[t.Dict] = {'embed-english-v2.0': (4096,)}
@@ -94,6 +101,13 @@ class CohereGenerate(Cohere):
 
     :param takes_context: Whether the model takes context into account.
     :param prompt: The prompt to use to seed the response.
+
+    Example:
+    -------
+    >>> from superduper_cohere.model import CohereGenerate
+    >>> model = CohereGenerate(identifier='base-light', prompt='Hello, {context}')
+    >>> model.predict('', context=['world!'])
+
     """
 
     signature: str = '*args,**kwargs'