diff --git a/.github/workflows/build-rs-capi.yml b/.github/workflows/build-rs-capi.yml index 7083e0c..2bb12cd 100644 --- a/.github/workflows/build-rs-capi.yml +++ b/.github/workflows/build-rs-capi.yml @@ -40,7 +40,6 @@ jobs: override: true - name: Install dependencies - if: matrix.target == 'aarch64-unknown-linux-gnu' run: | sudo apt-get update sudo apt-get install -y gcc-aarch64-linux-gnu g++-aarch64-linux-gnu pkg-config libssl-dev gcc-multilib crossbuild-essential-arm64 musl-tools diff --git a/README.md b/README.md index 68b8e94..6de0c16 100644 --- a/README.md +++ b/README.md @@ -20,7 +20,7 @@ ## 快速开始 ``` -docker run xxxx -p 3000:3000 ghcr.io/xxxx/rs-capi:latest +docker run --rm -p 7070:3000 ghcr.io/xxxx/rs-capi:latest ``` docker-compose diff --git a/rs-capi/Dockerfile b/rs-capi/Dockerfile index 44ca215..6e2b4f4 100644 --- a/rs-capi/Dockerfile +++ b/rs-capi/Dockerfile @@ -16,9 +16,9 @@ RUN cargo build --bin rs-capi --release FROM ubuntu:22.04 -# RUN apt-get update && apt-get install -y --no-install-recommends \ -# ca-certificates \ -# && rm -rf /var/lib/apt/lists/* +RUN apt-get update && apt-get install -y --no-install-recommends \ + ca-certificates \ + && rm -rf /var/lib/apt/lists/* COPY --from=builder /workspace/target/release/rs-capi /workspace/rs-capi diff --git a/rs-capi/main.py b/rs-capi/main.py deleted file mode 100644 index 30ccc01..0000000 --- a/rs-capi/main.py +++ /dev/null @@ -1,822 +0,0 @@ -import json - -from fastapi import FastAPI, Request, Response, HTTPException -from fastapi.responses import StreamingResponse -from fastapi.middleware.cors import CORSMiddleware -from pydantic import BaseModel -from typing import List, Optional, Dict, Any -import uuid -import httpx -import os -from dotenv import load_dotenv -import time -import re - -# 加载环境变量 -load_dotenv() - -app = FastAPI() - -# 添加CORS中间件 -app.add_middleware( - CORSMiddleware, - allow_origins=["*"], - allow_credentials=True, - allow_methods=["*"], - allow_headers=["*"], -) - - -# 定义请求模型 -class Message(BaseModel): - role: str - content: str - - -class ChatRequest(BaseModel): - model: str - messages: List[Message] - stream: bool = False - - -def string_to_hex(text: str, model_name: str) -> bytes: - """将文本转换为特定格式的十六进制数据""" - # 将输入文本转换为UTF-8字节 - text_bytes = text.encode('utf-8') - text_length = len(text_bytes) - - # 固定常量 - FIXED_HEADER = 2 - SEPARATOR = 1 - FIXED_SUFFIX_LENGTH = 0xA3 + len(model_name) - - # 计算第一个长度字段 - if text_length < 128: - text_length_field1 = format(text_length, '02x') - text_length_field_size1 = 1 - else: - low_byte1 = (text_length & 0x7F) | 0x80 - high_byte1 = (text_length >> 7) & 0xFF - text_length_field1 = format(low_byte1, '02x') + format(high_byte1, '02x') - text_length_field_size1 = 2 - - # 计算基础长度字段 - base_length = text_length + 0x2A - if base_length < 128: - text_length_field = format(base_length, '02x') - text_length_field_size = 1 - else: - low_byte = (base_length & 0x7F) | 0x80 - high_byte = (base_length >> 7) & 0xFF - text_length_field = format(low_byte, '02x') + format(high_byte, '02x') - text_length_field_size = 2 - - # 计算总消息长度 - message_total_length = (FIXED_HEADER + text_length_field_size + SEPARATOR + - text_length_field_size1 + text_length + FIXED_SUFFIX_LENGTH) - - # 构造十六进制字符串 - model_name_bytes = model_name.encode('utf-8') - model_name_length_hex = format(len(model_name_bytes), '02X') - model_name_hex = model_name_bytes.hex().upper() - - hex_string = ( - f"{message_total_length:010x}" - "12" - f"{text_length_field}" - "0A" - f"{text_length_field1}" - f"{text_bytes.hex()}" - "10016A2432343163636435662D393162612D343131382D393239612D3936626330313631626432612" - "2002A132F643A2F6964656150726F2F656475626F73733A1E0A" - f"{model_name_length_hex}" - f"{model_name_hex}" - "22004A" - "2461383761396133342D323164642D343863372D623434662D616636633365636536663765" - "680070007A2436393337376535612D386332642D343835342D623564392D653062623232336163303061" - "800101B00100C00100E00100E80100" - ).upper() - - return bytes.fromhex(hex_string) - - -def chunk_to_utf8_string(chunk: bytes) -> str: - """将二进制chunk转换为UTF-8字符串""" - if not chunk or len(chunk) < 2: - return '' - - if chunk[0] in [0x01, 0x02] or (chunk[0] == 0x60 and chunk[1] == 0x0C): - return '' - - # 记录原始chunk的十六进制（调试用） - print(f"chunk length: {len(chunk)}") - # print(f"chunk hex: {chunk.hex()}") - - try: - # 去掉0x0A之前的所有字节 - try: - chunk = chunk[chunk.index(0x0A) + 1:] - except ValueError: - pass - - filtered_chunk = bytearray() - i = 0 - while i < len(chunk): - # 检查是否有连续的0x00 - if i + 4 <= len(chunk) and all(chunk[j] == 0x00 for j in range(i, i + 4)): - i += 4 - while i < len(chunk) and chunk[i] <= 0x0F: - i += 1 - continue - - if chunk[i] == 0x0C: - i += 1 - while i < len(chunk) and chunk[i] == 0x0A: - i += 1 - else: - filtered_chunk.append(chunk[i]) - i += 1 - - # 过滤掉特定字节 - filtered_chunk = bytes(b for b in filtered_chunk - if b != 0x00 and b != 0x0C) - - if not filtered_chunk: - return '' - - result = filtered_chunk.decode('utf-8', errors='ignore').strip() - # print(f"decoded result: {result}") # 调试输出 - return result - - except Exception as e: - print(f"Error in chunk_to_utf8_string: {str(e)}") - return '' - - -async def process_stream(chunks, ): - """处理流式响应""" - response_id = f"chatcmpl-{str(uuid.uuid4())}" - - # 先将所有chunks读取到列表中 - # chunks = [] - # async for chunk in response.aiter_raw(): - # chunks.append(chunk) - - # 然后处理保存的chunks - for chunk in chunks: - text = chunk_to_utf8_string(chunk) - if text: - # 清理文本 - text = text.strip() - if "<|END_USER|>" in text: - text = text.split("<|END_USER|>")[-1].strip() - if text and text[0].isalpha(): - text = text[1:].strip() - text = re.sub(r"[\x00-\x1F\x7F]", "", text) - - if text: # 确保清理后的文本不为空 - data_body = { - "id": response_id, - "object": "chat.completion.chunk", - "created": int(time.time()), - "choices": [{ - "index": 0, - "delta": { - "content": text - } - }] - } - yield f"data: {json.dumps(data_body, ensure_ascii=False)}\n\n" - # yield "data: {\n" - # yield f' "id": "{response_id}",\n' - # yield ' "object": "chat.completion.chunk",\n' - # yield f' "created": {int(time.time())},\n' - # yield ' "choices": [{\n' - # yield ' "index": 0,\n' - # yield ' "delta": {\n' - # yield f' "content": "{text}"\n' - # yield " }\n" - # yield " }]\n" - # yield "}\n\n" - - yield "data: [DONE]\n\n" - - -@app.post("/v1/chat/completions") -async def chat_completions(request: Request, chat_request: ChatRequest): - # 验证o1模型不支持流式输出 - if chat_request.model.startswith('o1-') and chat_request.stream: - raise HTTPException( - status_code=400, - detail="Model not supported stream" - ) - - # 获取并处理认证令牌 - auth_header = request.headers.get('authorization', '') - if not auth_header.startswith('Bearer '): - raise HTTPException( - status_code=401, - detail="Invalid authorization header" - ) - - auth_token = auth_header.replace('Bearer ', '') - if not auth_token: - raise HTTPException( - status_code=401, - detail="Missing authorization token" - ) - - # 处理多个密钥 - keys = [key.strip() for key in auth_token.split(',')] - if keys: - auth_token = keys[0] # 使用第一个密钥 - - if '%3A%3A' in auth_token: - auth_token = auth_token.split('%3A%3A')[1] - - # 格式化消息 - formatted_messages = "\n".join( - f"{msg.role}:{msg.content}" for msg in chat_request.messages - ) - - # 生成请求数据 - hex_data = string_to_hex(formatted_messages, chat_request.model) - - # 准备请求头 - headers = { - 'Content-Type': 'application/connect+proto', - 'Authorization': f'Bearer {auth_token}', - 'Connect-Accept-Encoding': 'gzip,br', - 'Connect-Protocol-Version': '1', - 'User-Agent': 'connect-es/1.4.0', - 'X-Amzn-Trace-Id': f'Root={str(uuid.uuid4())}', - 'X-Cursor-Checksum': 'zo6Qjequ9b9734d1f13c3438ba25ea31ac93d9287248b9d30434934e9fcbfa6b3b22029e/7e4af391f67188693b722eff0090e8e6608bca8fa320ef20a0ccb5d7d62dfdef', - 'X-Cursor-Client-Version': '0.42.3', - 'X-Cursor-Timezone': 'Asia/Shanghai', - 'X-Ghost-Mode': 'false', - 'X-Request-Id': str(uuid.uuid4()), - 'Host': 'api2.cursor.sh' - } - - async with httpx.AsyncClient(timeout=httpx.Timeout(300.0)) as client: - try: - # 使用 stream=True 参数 - # 打印 headers 和 二进制 data - print(f"headers: {headers}") - print(hex_data) - async with client.stream( - 'POST', - 'https://api2.cursor.sh/aiserver.v1.AiService/StreamChat', - headers=headers, - content=hex_data, - timeout=None - ) as response: - if chat_request.stream: - chunks = [] - async for chunk in response.aiter_raw(): - chunks.append(chunk) - return StreamingResponse( - process_stream(chunks), - media_type="text/event-stream" - ) - else: - # 非流式响应处理 - text = '' - async for chunk in response.aiter_raw(): - # print('chunk:', chunk.hex()) - print('chunk length:', len(chunk)) - - res = chunk_to_utf8_string(chunk) - # print('res:', res) - if res: - text += res - - # 清理响应文本 - import re - text = re.sub(r'^.*<\|END_USER\|>', '', text, flags=re.DOTALL) - text = re.sub(r'^\n[a-zA-Z]?', '', text).strip() - text = re.sub(r'[\x00-\x1F\x7F]', '', text) - - return { - "id": f"chatcmpl-{str(uuid.uuid4())}", - "object": "chat.completion", - "created": int(time.time()), - "model": chat_request.model, - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": text - }, - "finish_reason": "stop" - }], - "usage": { - "prompt_tokens": 0, - "completion_tokens": 0, - "total_tokens": 0 - } - } - - except Exception as e: - print(f"Error: {str(e)}") - raise HTTPException( - status_code=500, - detail="Internal server error" - ) - - -@app.post("/models") -async def models(): - return { - "object": "list", - "data": [ - { - "id": "claude-3-5-sonnet-20241022", - "object": "model", - "created": 1713744000, - "owned_by": "anthropic" - }, - { - "id": "claude-3-opus", - "object": "model", - "created": 1709251200, - "owned_by": "anthropic" - }, - { - "id": "claude-3.5-haiku", - "object": "model", - "created": 1711929600, - "owned_by": "anthropic" - }, - { - "id": "claude-3.5-sonnet", - "object": "model", - "created": 1711929600, - "owned_by": "anthropic" - }, - { - "id": "cursor-small", - "object": "model", - "created": 1712534400, - "owned_by": "cursor" - }, - { - "id": "gpt-3.5-turbo", - "object": "model", - "created": 1677649200, - "owned_by": "openai" - }, - { - "id": "gpt-4", - "object": "model", - "created": 1687392000, - "owned_by": "openai" - }, - { - "id": "gpt-4-turbo-2024-04-09", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "gpt-4o", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "gpt-4o-mini", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "o1-mini", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "o1-preview", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - } - ] - } - -if __name__ == "__main__": - import uvicorn - port = int(os.getenv("PORT", "3001")) - uvicorn.run("main:app", host="0.0.0.0", port=port, reload=True, timeout_keep_alive=30) -import json - -from fastapi import FastAPI, Request, Response, HTTPException -from fastapi.responses import StreamingResponse -from fastapi.middleware.cors import CORSMiddleware -from pydantic import BaseModel -from typing import List, Optional, Dict, Any -import uuid -import httpx -import os -from dotenv import load_dotenv -import time -import re - -# 加载环境变量 -load_dotenv() - -app = FastAPI() - -# 添加CORS中间件 -app.add_middleware( - CORSMiddleware, - allow_origins=["*"], - allow_credentials=True, - allow_methods=["*"], - allow_headers=["*"], -) - - -# 定义请求模型 -class Message(BaseModel): - role: str - content: str - - -class ChatRequest(BaseModel): - model: str - messages: List[Message] - stream: bool = False - - -def string_to_hex(text: str, model_name: str) -> bytes: - """将文本转换为特定格式的十六进制数据""" - # 将输入文本转换为UTF-8字节 - text_bytes = text.encode('utf-8') - text_length = len(text_bytes) - - # 固定常量 - FIXED_HEADER = 2 - SEPARATOR = 1 - FIXED_SUFFIX_LENGTH = 0xA3 + len(model_name) - - # 计算第一个长度字段 - if text_length < 128: - text_length_field1 = format(text_length, '02x') - text_length_field_size1 = 1 - else: - low_byte1 = (text_length & 0x7F) | 0x80 - high_byte1 = (text_length >> 7) & 0xFF - text_length_field1 = format(low_byte1, '02x') + format(high_byte1, '02x') - text_length_field_size1 = 2 - - # 计算基础长度字段 - base_length = text_length + 0x2A - if base_length < 128: - text_length_field = format(base_length, '02x') - text_length_field_size = 1 - else: - low_byte = (base_length & 0x7F) | 0x80 - high_byte = (base_length >> 7) & 0xFF - text_length_field = format(low_byte, '02x') + format(high_byte, '02x') - text_length_field_size = 2 - - # 计算总消息长度 - message_total_length = (FIXED_HEADER + text_length_field_size + SEPARATOR + - text_length_field_size1 + text_length + FIXED_SUFFIX_LENGTH) - - # 构造十六进制字符串 - model_name_bytes = model_name.encode('utf-8') - model_name_length_hex = format(len(model_name_bytes), '02X') - model_name_hex = model_name_bytes.hex().upper() - - hex_string = ( - f"{message_total_length:010x}" - "12" - f"{text_length_field}" - "0A" - f"{text_length_field1}" - f"{text_bytes.hex()}" - "10016A2432343163636435662D393162612D343131382D393239612D3936626330313631626432612" - "2002A132F643A2F6964656150726F2F656475626F73733A1E0A" - f"{model_name_length_hex}" - f"{model_name_hex}" - "22004A" - "2461383761396133342D323164642D343863372D623434662D616636633365636536663765" - "680070007A2436393337376535612D386332642D343835342D623564392D653062623232336163303061" - "800101B00100C00100E00100E80100" - ).upper() - - return bytes.fromhex(hex_string) - - -def chunk_to_utf8_string(chunk: bytes) -> str: - """将二进制chunk转换为UTF-8字符串""" - if not chunk or len(chunk) < 2: - return '' - - if chunk[0] in [0x01, 0x02] or (chunk[0] == 0x60 and chunk[1] == 0x0C): - return '' - - # 记录原始chunk的十六进制（调试用） - print(f"chunk length: {len(chunk)}") - # print(f"chunk hex: {chunk.hex()}") - - try: - # 去掉0x0A之前的所有字节 - try: - chunk = chunk[chunk.index(0x0A) + 1:] - except ValueError: - pass - - filtered_chunk = bytearray() - i = 0 - while i < len(chunk): - # 检查是否有连续的0x00 - if i + 4 <= len(chunk) and all(chunk[j] == 0x00 for j in range(i, i + 4)): - i += 4 - while i < len(chunk) and chunk[i] <= 0x0F: - i += 1 - continue - - if chunk[i] == 0x0C: - i += 1 - while i < len(chunk) and chunk[i] == 0x0A: - i += 1 - else: - filtered_chunk.append(chunk[i]) - i += 1 - - # 过滤掉特定字节 - filtered_chunk = bytes(b for b in filtered_chunk - if b != 0x00 and b != 0x0C) - - if not filtered_chunk: - return '' - - result = filtered_chunk.decode('utf-8', errors='ignore').strip() - # print(f"decoded result: {result}") # 调试输出 - return result - - except Exception as e: - print(f"Error in chunk_to_utf8_string: {str(e)}") - return '' - - -async def process_stream(chunks, ): - """处理流式响应""" - response_id = f"chatcmpl-{str(uuid.uuid4())}" - - # 先将所有chunks读取到列表中 - # chunks = [] - # async for chunk in response.aiter_raw(): - # chunks.append(chunk) - - # 然后处理保存的chunks - for chunk in chunks: - text = chunk_to_utf8_string(chunk) - if text: - # 清理文本 - text = text.strip() - if "<|END_USER|>" in text: - text = text.split("<|END_USER|>")[-1].strip() - if text and text[0].isalpha(): - text = text[1:].strip() - text = re.sub(r"[\x00-\x1F\x7F]", "", text) - - if text: # 确保清理后的文本不为空 - data_body = { - "id": response_id, - "object": "chat.completion.chunk", - "created": int(time.time()), - "choices": [{ - "index": 0, - "delta": { - "content": text - } - }] - } - yield f"data: {json.dumps(data_body, ensure_ascii=False)}\n\n" - # yield "data: {\n" - # yield f' "id": "{response_id}",\n' - # yield ' "object": "chat.completion.chunk",\n' - # yield f' "created": {int(time.time())},\n' - # yield ' "choices": [{\n' - # yield ' "index": 0,\n' - # yield ' "delta": {\n' - # yield f' "content": "{text}"\n' - # yield " }\n" - # yield " }]\n" - # yield "}\n\n" - - yield "data: [DONE]\n\n" - - -@app.post("/v1/chat/completions") -async def chat_completions(request: Request, chat_request: ChatRequest): - # 验证o1模型不支持流式输出 - if chat_request.model.startswith('o1-') and chat_request.stream: - raise HTTPException( - status_code=400, - detail="Model not supported stream" - ) - - # 获取并处理认证令牌 - auth_header = request.headers.get('authorization', '') - if not auth_header.startswith('Bearer '): - raise HTTPException( - status_code=401, - detail="Invalid authorization header" - ) - - auth_token = auth_header.replace('Bearer ', '') - if not auth_token: - raise HTTPException( - status_code=401, - detail="Missing authorization token" - ) - - # 处理多个密钥 - keys = [key.strip() for key in auth_token.split(',')] - if keys: - auth_token = keys[0] # 使用第一个密钥 - - if '%3A%3A' in auth_token: - auth_token = auth_token.split('%3A%3A')[1] - - # 格式化消息 - formatted_messages = "\n".join( - f"{msg.role}:{msg.content}" for msg in chat_request.messages - ) - - # 生成请求数据 - hex_data = string_to_hex(formatted_messages, chat_request.model) - - # 准备请求头 - headers = { - 'Content-Type': 'application/connect+proto', - 'Authorization': f'Bearer {auth_token}', - 'Connect-Accept-Encoding': 'gzip,br', - 'Connect-Protocol-Version': '1', - 'User-Agent': 'connect-es/1.4.0', - 'X-Amzn-Trace-Id': f'Root={str(uuid.uuid4())}', - 'X-Cursor-Checksum': 'zo6Qjequ9b9734d1f13c3438ba25ea31ac93d9287248b9d30434934e9fcbfa6b3b22029e/7e4af391f67188693b722eff0090e8e6608bca8fa320ef20a0ccb5d7d62dfdef', - 'X-Cursor-Client-Version': '0.42.3', - 'X-Cursor-Timezone': 'Asia/Shanghai', - 'X-Ghost-Mode': 'false', - 'X-Request-Id': str(uuid.uuid4()), - 'Host': 'api2.cursor.sh' - } - - async with httpx.AsyncClient(timeout=httpx.Timeout(300.0)) as client: - try: - # 使用 stream=True 参数 - # 打印 headers 和 二进制 data - print(f"headers: {headers}") - print(hex_data) - async with client.stream( - 'POST', - 'https://api2.cursor.sh/aiserver.v1.AiService/StreamChat', - headers=headers, - content=hex_data, - timeout=None - ) as response: - if chat_request.stream: - chunks = [] - async for chunk in response.aiter_raw(): - chunks.append(chunk) - return StreamingResponse( - process_stream(chunks), - media_type="text/event-stream" - ) - else: - # 非流式响应处理 - text = '' - async for chunk in response.aiter_raw(): - # print('chunk:', chunk.hex()) - print('chunk length:', len(chunk)) - - res = chunk_to_utf8_string(chunk) - # print('res:', res) - if res: - text += res - - # 清理响应文本 - import re - text = re.sub(r'^.*<\|END_USER\|>', '', text, flags=re.DOTALL) - text = re.sub(r'^\n[a-zA-Z]?', '', text).strip() - text = re.sub(r'[\x00-\x1F\x7F]', '', text) - - return { - "id": f"chatcmpl-{str(uuid.uuid4())}", - "object": "chat.completion", - "created": int(time.time()), - "model": chat_request.model, - "choices": [{ - "index": 0, - "message": { - "role": "assistant", - "content": text - }, - "finish_reason": "stop" - }], - "usage": { - "prompt_tokens": 0, - "completion_tokens": 0, - "total_tokens": 0 - } - } - - except Exception as e: - print(f"Error: {str(e)}") - raise HTTPException( - status_code=500, - detail="Internal server error" - ) - - -@app.post("/models") -async def models(): - return { - "object": "list", - "data": [ - { - "id": "claude-3-5-sonnet-20241022", - "object": "model", - "created": 1713744000, - "owned_by": "anthropic" - }, - { - "id": "claude-3-opus", - "object": "model", - "created": 1709251200, - "owned_by": "anthropic" - }, - { - "id": "claude-3.5-haiku", - "object": "model", - "created": 1711929600, - "owned_by": "anthropic" - }, - { - "id": "claude-3.5-sonnet", - "object": "model", - "created": 1711929600, - "owned_by": "anthropic" - }, - { - "id": "cursor-small", - "object": "model", - "created": 1712534400, - "owned_by": "cursor" - }, - { - "id": "gpt-3.5-turbo", - "object": "model", - "created": 1677649200, - "owned_by": "openai" - }, - { - "id": "gpt-4", - "object": "model", - "created": 1687392000, - "owned_by": "openai" - }, - { - "id": "gpt-4-turbo-2024-04-09", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "gpt-4o", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "gpt-4o-mini", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "o1-mini", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - }, - { - "id": "o1-preview", - "object": "model", - "created": 1712620800, - "owned_by": "openai" - } - ] - } - -if __name__ == "__main__": - import uvicorn - port = int(os.getenv("PORT", "3001")) - uvicorn.run("main:app", host="0.0.0.0", port=port, reload=True, timeout_keep_alive=30) diff --git a/rs-capi/src/main.rs b/rs-capi/src/main.rs index 5051f41..e996dc7 100644 --- a/rs-capi/src/main.rs +++ b/rs-capi/src/main.rs @@ -7,6 +7,7 @@ use axum::{ routing::post, Json, Router, }; +use std::error::Error; use tower_http::trace::TraceLayer; use bytes::Bytes; @@ -262,7 +263,16 @@ async fn chat_completions( let client = reqwest::Client::builder() .timeout(Duration::from_secs(300)) .build() - .map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?; + .map_err(|e| { + tracing::error!("创建HTTP客户端失败: {:?}", e); + tracing::error!(error = %e, "错误详情"); + + if let Some(source) = e.source() { + tracing::error!(source = %source, "错误源"); + } + + StatusCode::INTERNAL_SERVER_ERROR + })?; let response = client .post("https://api2.cursor.sh/aiserver.v1.AiService/StreamChat") @@ -270,7 +280,32 @@ async fn chat_completions( .body(hex_data) .send() .await - .map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?; + .map_err(|e| { + tracing::error!("请求失败: {:?}", e); + tracing::error!(error = %e, "错误详情"); + + // 如果是超时错误 + if e.is_timeout() { + tracing::error!("请求超时"); + } + + // 如果是连接错误 + if e.is_connect() { + tracing::error!("连接失败"); + } + + // 如果有请求信息 + if let Some(url) = e.url() { + tracing::error!(url = %url, "请求URL"); + } + + // 如果有状态码 + if let Some(status) = e.status() { + tracing::error!(status = %status, "HTTP状态码"); + } + + StatusCode::INTERNAL_SERVER_ERROR + })?; if chat_request.stream { let mut chunks = Vec::new(); @@ -347,7 +382,72 @@ async fn models() -> Json { "created": 1713744000, "owned_by": "anthropic" }, - // ... 其他模型 + { + "id": "claude-3-opus", + "object": "model", + "created": 1709251200, + "owned_by": "anthropic" + }, + { + "id": "claude-3.5-haiku", + "object": "model", + "created": 1711929600, + "owned_by": "anthropic" + }, + { + "id": "claude-3.5-sonnet", + "object": "model", + "created": 1711929600, + "owned_by": "anthropic" + }, + { + "id": "cursor-small", + "object": "model", + "created": 1712534400, + "owned_by": "cursor" + }, + { + "id": "gpt-3.5-turbo", + "object": "model", + "created": 1677649200, + "owned_by": "openai" + }, + { + "id": "gpt-4", + "object": "model", + "created": 1687392000, + "owned_by": "openai" + }, + { + "id": "gpt-4-turbo-2024-04-09", + "object": "model", + "created": 1712620800, + "owned_by": "openai" + }, + { + "id": "gpt-4o", + "object": "model", + "created": 1712620800, + "owned_by": "openai" + }, + { + "id": "gpt-4o-mini", + "object": "model", + "created": 1712620800, + "owned_by": "openai" + }, + { + "id": "o1-mini", + "object": "model", + "created": 1712620800, + "owned_by": "openai" + }, + { + "id": "o1-preview", + "object": "model", + "created": 1712620800, + "owned_by": "openai" + } ] })) }