[WIP] feat: #1550 Azure, Bard, Claude, ChatGLM, Qwen, Spark

app/api/openai/[...path]/route.ts

@@ -1,14 +1,14 @@
-import { type OpenAIListModelResponse } from "@/app/client/platforms/openai";
+import { type OpenAI } from "@/app/client/openai/types";
 import { getServerSideConfig } from "@/app/config/server";
 import { OpenaiPath } from "@/app/constant";
 import { prettyObject } from "@/app/utils/format";
 import { NextRequest, NextResponse } from "next/server";
 import { auth } from "../../auth";
 import { requestOpenai } from "../../common";
 
-const ALLOWD_PATH = new Set(Object.values(OpenaiPath));
+const ALLOWD_PATH = new Set(Object.values(OpenaiPath) as string[]);
 
-function getModels(remoteModelRes: OpenAIListModelResponse) {
+function getModels(remoteModelRes: OpenAI.ListModelResponse) {
   const config = getServerSideConfig();
 
   if (config.disableGPT4) {
@@ -56,8 +56,8 @@ async function handle(
     const response = await requestOpenai(req);
 
     // list models
-    if (subpath === OpenaiPath.ListModelPath && response.status === 200) {
-      const resJson = (await response.json()) as OpenAIListModelResponse;
+    if (subpath === OpenaiPath.ListModel && response.status === 200) {
+      const resJson = await response.json();
       const availableModels = getModels(resJson);
       return NextResponse.json(availableModels, {
         status: response.status,

app/client/anthropic/config.ts

@@ -0,0 +1,29 @@
+export const AnthropicConfig = {
+  model: {
+    model: "claude-instant-1",
+    summarizeModel: "claude-instant-1",
+
+    max_tokens_to_sample: 8192,
+    temperature: 0.5,
+    top_p: 0.7,
+    top_k: 5,
+  },
+  provider: {
+    name: "Anthropic" as const,
+    endpoint: "https://api.anthropic.com",
+    apiKey: "",
+    customModels: "",
+    version: "2023-06-01",
+
+    models: [
+      {
+        name: "claude-instant-1",
+        available: true,
+      },
+      {
+        name: "claude-2",
+        available: true,
+      },
+    ],
+  },
+};

app/client/anthropic/index.ts

@@ -0,0 +1,233 @@
+import { ModelConfig, ProviderConfig } from "@/app/store";
+import { createLogger } from "@/app/utils/log";
+import { getAuthKey } from "../common/auth";
+import { API_PREFIX, AnthropicPath, ApiPath } from "@/app/constant";
+import { getApiPath } from "@/app/utils/path";
+import { trimEnd } from "@/app/utils/string";
+import { Anthropic } from "./types";
+import { ChatOptions, LLMModel, LLMUsage, RequestMessage } from "../types";
+import { omit } from "@/app/utils/object";
+import {
+  EventStreamContentType,
+  fetchEventSource,
+} from "@fortaine/fetch-event-source";
+import { prettyObject } from "@/app/utils/format";
+import Locale from "@/app/locales";
+import { AnthropicConfig } from "./config";
+
+export function createAnthropicClient(
+  providerConfigs: ProviderConfig,
+  modelConfig: ModelConfig,
+) {
+  const anthropicConfig = { ...providerConfigs.anthropic };
+  const logger = createLogger("[Anthropic]");
+  const anthropicModelConfig = { ...modelConfig.anthropic };
+
+  return {
+    headers() {
+      return {
+        "Content-Type": "application/json",
+        "x-api-key": getAuthKey(anthropicConfig.apiKey),
+        "anthropic-version": anthropicConfig.version,
+      };
+    },
+
+    path(path: AnthropicPath): string {
+      let baseUrl: string = anthropicConfig.endpoint;
+
+      // if endpoint is empty, use default endpoint
+      if (baseUrl.trim().length === 0) {
+        baseUrl = getApiPath(ApiPath.Anthropic);
+      }
+
+      if (!baseUrl.startsWith("http") && !baseUrl.startsWith(API_PREFIX)) {
+        baseUrl = "https://" + baseUrl;
+      }
+
+      baseUrl = trimEnd(baseUrl, "/");
+
+      return `${baseUrl}/${path}`;
+    },
+
+    extractMessage(res: Anthropic.ChatResponse) {
+      return res.completion;
+    },
+
+    beforeRequest(options: ChatOptions, stream = false) {
+      const ClaudeMapper: Record<RequestMessage["role"], string> = {
+        assistant: "Assistant",
+        user: "Human",
+        system: "Human",
+      };
+
+      const prompt = options.messages
+        .map((v) => ({
+          role: ClaudeMapper[v.role] ?? "Human",
+          content: v.content,
+        }))
+        .map((v) => `\n\n${v.role}: ${v.content}`)
+        .join("");
+
+      if (options.shouldSummarize) {
+        anthropicModelConfig.model = anthropicModelConfig.summarizeModel;
+      }
+
+      const requestBody: Anthropic.ChatRequest = {
+        prompt,
+        stream,
+        ...omit(anthropicModelConfig, "summarizeModel"),
+      };
+
+      const path = this.path(AnthropicPath.Chat);
+
+      logger.log("path = ", path, requestBody);
+
+      const controller = new AbortController();
+      options.onController?.(controller);
+
+      const payload = {
+        method: "POST",
+        body: JSON.stringify(requestBody),
+        signal: controller.signal,
+        headers: this.headers(),
+        mode: "no-cors" as RequestMode,
+      };
+
+      return {
+        path,
+        payload,
+        controller,
+      };
+    },
+
+    async chat(options: ChatOptions) {
+      try {
+        const { path, payload, controller } = this.beforeRequest(
+          options,
+          false,
+        );
+
+        controller.signal.onabort = () => options.onFinish("");
+
+        const res = await fetch(path, payload);
+        const resJson = await res.json();
+
+        const message = this.extractMessage(resJson);
+        options.onFinish(message);
+      } catch (e) {
+        logger.error("failed to chat", e);
+        options.onError?.(e as Error);
+      }
+    },
+
+    async chatStream(options: ChatOptions) {
+      try {
+        const { path, payload, controller } = this.beforeRequest(options, true);
+
+        const context = {
+          text: "",
+          finished: false,
+        };
+
+        const finish = () => {
+          if (!context.finished) {
+            options.onFinish(context.text);
+            context.finished = true;
+          }
+        };
+
+        controller.signal.onabort = finish;
+
+        logger.log(payload);
+
+        fetchEventSource(path, {
+          ...payload,
+          async onopen(res) {
+            const contentType = res.headers.get("content-type");
+            logger.log("response content type: ", contentType);
+
+            if (contentType?.startsWith("text/plain")) {
+              context.text = await res.clone().text();
+              return finish();
+            }
+
+            if (
+              !res.ok ||
+              !res.headers
+                .get("content-type")
+                ?.startsWith(EventStreamContentType) ||
+              res.status !== 200
+            ) {
+              const responseTexts = [context.text];
+              let extraInfo = await res.clone().text();
+              try {
+                const resJson = await res.clone().json();
+                extraInfo = prettyObject(resJson);
+              } catch {}
+
+              if (res.status === 401) {
+                responseTexts.push(Locale.Error.Unauthorized);
+              }
+
+              if (extraInfo) {
+                responseTexts.push(extraInfo);
+              }
+
+              context.text = responseTexts.join("\n\n");
+
+              return finish();
+            }
+          },
+          onmessage(msg) {
+            if (msg.data === "[DONE]" || context.finished) {
+              return finish();
+            }
+            const chunk = msg.data;
+            try {
+              const chunkJson = JSON.parse(
+                chunk,
+              ) as Anthropic.ChatStreamResponse;
+              const delta = chunkJson.completion;
+              if (delta) {
+                context.text += delta;
+                options.onUpdate?.(context.text, delta);
+              }
+            } catch (e) {
+              logger.error("[Request] parse error", chunk, msg);
+            }
+          },
+          onclose() {
+            finish();
+          },
+          onerror(e) {
+            options.onError?.(e);
+          },
+          openWhenHidden: true,
+        });
+      } catch (e) {
+        logger.error("failed to chat", e);
+        options.onError?.(e as Error);
+      }
+    },
+
+    async usage() {
+      return {
+        used: 0,
+        total: 0,
+      } as LLMUsage;
+    },
+
+    async models(): Promise<LLMModel[]> {
+      const customModels = anthropicConfig.customModels
+        .split(",")
+        .map((v) => v.trim())
+        .filter((v) => !!v)
+        .map((v) => ({
+          name: v,
+          available: true,
+        }));
+
+      return [...AnthropicConfig.provider.models.slice(), ...customModels];
+    },
+  };
+}

app/client/anthropic/types.ts

@@ -0,0 +1,24 @@
+export namespace Anthropic {
+  export interface ChatRequest {
+    model: string; // The model that will complete your prompt.
+    prompt: string; // The prompt that you want Claude to complete.
+    max_tokens_to_sample: number; // The maximum number of tokens to generate before stopping.
+    stop_sequences?: string[]; // Sequences that will cause the model to stop generating completion text.
+    temperature?: number; // Amount of randomness injected into the response.
+    top_p?: number; // Use nucleus sampling.
+    top_k?: number; // Only sample from the top K options for each subsequent token.
+    metadata?: object; // An object describing metadata about the request.
+    stream?: boolean; // Whether to incrementally stream the response using server-sent events.
+  }
+
+  export interface ChatResponse {
+    completion: string;
+    stop_reason: "stop_sequence" | "max_tokens";
+    model: string;
+  }
+
+  export type ChatStreamResponse = ChatResponse & {
+    stop?: string;
+    log_id: string;
+  };
+}