mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
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497 lines
20 KiB
Python
497 lines
20 KiB
Python
# encoding:utf-8
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import json
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import time
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import requests
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from models.baidu.baidu_wenxin_session import BaiduWenxinSession
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from models.bot import Bot
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from models.session_manager import SessionManager
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from bridge.context import ContextType
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from bridge.reply import Reply, ReplyType
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from common import const
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from common.log import logger
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from config import conf
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# Optional OpenAI image support
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try:
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from models.openai.open_ai_image import OpenAIImage
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_openai_image_available = True
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except Exception as e:
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logger.warning(f"OpenAI image support not available: {e}")
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_openai_image_available = False
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OpenAIImage = object # Fallback to object
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user_session = dict()
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# OpenAI对话模型API (可用)
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class ClaudeAPIBot(Bot, OpenAIImage):
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def __init__(self):
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super().__init__()
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self.api_key = conf().get("claude_api_key")
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self.api_base = conf().get("claude_api_base") or "https://api.anthropic.com/v1"
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self.proxy = conf().get("proxy", None)
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self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or "text-davinci-003")
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def reply(self, query, context=None):
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# acquire reply content
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if context and context.type:
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if context.type == ContextType.TEXT:
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logger.info("[CLAUDE_API] query={}".format(query))
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session_id = context["session_id"]
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reply = None
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if query == "#清除记忆":
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self.sessions.clear_session(session_id)
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reply = Reply(ReplyType.INFO, "记忆已清除")
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elif query == "#清除所有":
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self.sessions.clear_all_session()
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reply = Reply(ReplyType.INFO, "所有人记忆已清除")
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else:
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session = self.sessions.session_query(query, session_id)
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result = self.reply_text(session)
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logger.info(result)
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total_tokens, completion_tokens, reply_content = (
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result["total_tokens"],
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result["completion_tokens"],
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result["content"],
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)
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logger.debug(
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"[CLAUDE_API] new_query={}, session_id={}, reply_cont={}, completion_tokens={}".format(str(session), session_id, reply_content, completion_tokens)
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)
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if total_tokens == 0:
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reply = Reply(ReplyType.ERROR, reply_content)
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else:
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self.sessions.session_reply(reply_content, session_id, total_tokens)
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reply = Reply(ReplyType.TEXT, reply_content)
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return reply
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elif context.type == ContextType.IMAGE_CREATE:
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ok, retstring = self.create_img(query, 0)
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reply = None
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if ok:
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reply = Reply(ReplyType.IMAGE_URL, retstring)
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else:
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reply = Reply(ReplyType.ERROR, retstring)
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return reply
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def reply_text(self, session: BaiduWenxinSession, retry_count=0, tools=None):
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try:
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actual_model = self._model_mapping(conf().get("model"))
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# Prepare headers
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headers = {
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"x-api-key": self.api_key,
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"anthropic-version": "2023-06-01",
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"content-type": "application/json"
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}
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# Extract system prompt if present and prepare Claude-compatible messages
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system_prompt = conf().get("character_desc", "")
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claude_messages = []
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for msg in session.messages:
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if msg.get("role") == "system":
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system_prompt = msg["content"]
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else:
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claude_messages.append(msg)
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# Prepare request data
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data = {
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"model": actual_model,
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"messages": claude_messages,
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"max_tokens": self._get_max_tokens(actual_model)
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}
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if system_prompt:
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data["system"] = system_prompt
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if tools:
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data["tools"] = tools
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# Make HTTP request
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proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
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response = requests.post(
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f"{self.api_base}/messages",
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headers=headers,
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json=data,
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proxies=proxies
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)
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if response.status_code != 200:
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raise Exception(f"API request failed: {response.status_code} - {response.text}")
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claude_response = response.json()
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# Handle response content and tool calls
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res_content = ""
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tool_calls = []
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content_blocks = claude_response.get("content", [])
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for block in content_blocks:
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if block.get("type") == "text":
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res_content += block.get("text", "")
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elif block.get("type") == "tool_use":
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tool_calls.append({
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"id": block.get("id", ""),
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"name": block.get("name", ""),
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"arguments": block.get("input", {})
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})
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res_content = res_content.strip().replace("<|endoftext|>", "")
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usage = claude_response.get("usage", {})
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total_tokens = usage.get("input_tokens", 0) + usage.get("output_tokens", 0)
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completion_tokens = usage.get("output_tokens", 0)
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logger.info("[CLAUDE_API] reply={}".format(res_content))
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if tool_calls:
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logger.info("[CLAUDE_API] tool_calls={}".format(tool_calls))
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result = {
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"total_tokens": total_tokens,
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"completion_tokens": completion_tokens,
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"content": res_content,
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}
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if tool_calls:
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result["tool_calls"] = tool_calls
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return result
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except Exception as e:
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need_retry = retry_count < 2
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result = {"total_tokens": 0, "completion_tokens": 0, "content": "我现在有点累了，等会再来吧"}
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# Handle different types of errors
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error_str = str(e).lower()
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if "rate" in error_str or "limit" in error_str:
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logger.warn("[CLAUDE_API] RateLimitError: {}".format(e))
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result["content"] = "提问太快啦，请休息一下再问我吧"
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if need_retry:
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time.sleep(20)
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elif "timeout" in error_str:
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logger.warn("[CLAUDE_API] Timeout: {}".format(e))
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result["content"] = "我没有收到你的消息"
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if need_retry:
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time.sleep(5)
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elif "connection" in error_str or "network" in error_str:
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logger.warn("[CLAUDE_API] APIConnectionError: {}".format(e))
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need_retry = False
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result["content"] = "我连接不到你的网络"
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else:
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logger.warn("[CLAUDE_API] Exception: {}".format(e))
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need_retry = False
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self.sessions.clear_session(session.session_id)
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if need_retry:
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logger.warn("[CLAUDE_API] 第{}次重试".format(retry_count + 1))
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return self.reply_text(session, retry_count + 1, tools)
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else:
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return result
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def _model_mapping(self, model) -> str:
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if model == "claude-3-opus":
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return const.CLAUDE_3_OPUS
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elif model == "claude-3-sonnet":
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return const.CLAUDE_3_SONNET
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elif model == "claude-3-haiku":
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return const.CLAUDE_3_HAIKU
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elif model == "claude-3.5-sonnet":
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return const.CLAUDE_35_SONNET
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return model
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def _get_max_tokens(self, model: str) -> int:
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"""
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Get max_tokens for the model.
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Reference from pi-mono:
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- Claude 3.5/3.7: 8192
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- Claude 3 Opus: 4096
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- Default: 8192
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"""
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if model and (model.startswith("claude-3-5") or model.startswith("claude-3-7")):
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return 8192
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elif model and model.startswith("claude-3") and "opus" in model:
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return 4096
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elif model and (model.startswith("claude-sonnet-4") or model.startswith("claude-opus-4")):
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return 64000
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return 8192
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def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
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"""
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Call Claude API with tool support for agent integration
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Args:
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messages: List of messages
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tools: List of tool definitions
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stream: Whether to use streaming
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**kwargs: Additional parameters
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Returns:
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Formatted response compatible with OpenAI format or generator for streaming
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"""
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actual_model = self._model_mapping(conf().get("model"))
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# Extract system prompt from messages if present
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system_prompt = kwargs.get("system", conf().get("character_desc", ""))
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claude_messages = []
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for msg in messages:
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if msg.get("role") == "system":
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system_prompt = msg["content"]
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else:
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claude_messages.append(msg)
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request_params = {
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"model": actual_model,
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"max_tokens": kwargs.get("max_tokens", self._get_max_tokens(actual_model)),
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"messages": claude_messages,
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"stream": stream
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}
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if system_prompt:
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request_params["system"] = system_prompt
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if tools:
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request_params["tools"] = tools
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try:
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if stream:
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return self._handle_stream_response(request_params)
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else:
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return self._handle_sync_response(request_params)
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except Exception as e:
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logger.error(f"Claude API call error: {e}")
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if stream:
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# Return error generator for stream
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def error_generator():
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yield {
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"error": True,
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"message": str(e),
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"status_code": 500
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}
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return error_generator()
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else:
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# Return error response for sync
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return {
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"error": True,
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"message": str(e),
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"status_code": 500
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}
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def _handle_sync_response(self, request_params):
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"""Handle synchronous Claude API response"""
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# Prepare headers
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headers = {
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"x-api-key": self.api_key,
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"anthropic-version": "2023-06-01",
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"content-type": "application/json"
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}
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# Make HTTP request
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proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
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response = requests.post(
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f"{self.api_base}/messages",
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headers=headers,
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json=request_params,
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proxies=proxies
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)
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if response.status_code != 200:
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raise Exception(f"API request failed: {response.status_code} - {response.text}")
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claude_response = response.json()
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# Extract content blocks
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text_content = ""
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tool_calls = []
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content_blocks = claude_response.get("content", [])
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for block in content_blocks:
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if block.get("type") == "text":
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text_content += block.get("text", "")
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elif block.get("type") == "tool_use":
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tool_calls.append({
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"id": block.get("id", ""),
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"type": "function",
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"function": {
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"name": block.get("name", ""),
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"arguments": json.dumps(block.get("input", {}))
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}
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})
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# Build message in OpenAI format
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message = {
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"role": "assistant",
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"content": text_content
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}
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if tool_calls:
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message["tool_calls"] = tool_calls
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# Format response to match OpenAI structure
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usage = claude_response.get("usage", {})
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formatted_response = {
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"id": claude_response.get("id", ""),
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"object": "chat.completion",
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"created": int(time.time()),
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"model": claude_response.get("model", request_params["model"]),
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"choices": [
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{
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"index": 0,
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"message": message,
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"finish_reason": claude_response.get("stop_reason", "stop")
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}
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],
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"usage": {
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"prompt_tokens": usage.get("input_tokens", 0),
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"completion_tokens": usage.get("output_tokens", 0),
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"total_tokens": usage.get("input_tokens", 0) + usage.get("output_tokens", 0)
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}
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}
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return formatted_response
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def _handle_stream_response(self, request_params):
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"""Handle streaming Claude API response using HTTP requests"""
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# Prepare headers
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headers = {
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"x-api-key": self.api_key,
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"anthropic-version": "2023-06-01",
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"content-type": "application/json"
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}
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# Add stream parameter
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request_params["stream"] = True
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# Track tool use state
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tool_uses_map = {} # {index: {id, name, input}}
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current_tool_use_index = -1
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stop_reason = None # Track stop reason from Claude
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try:
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# Make streaming HTTP request
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proxies = {"http": self.proxy, "https": self.proxy} if self.proxy else None
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response = requests.post(
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f"{self.api_base}/messages",
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headers=headers,
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json=request_params,
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proxies=proxies,
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stream=True
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)
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if response.status_code != 200:
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error_text = response.text
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try:
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error_data = json.loads(error_text)
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error_msg = error_data.get("error", {}).get("message", error_text)
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except:
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error_msg = error_text or "Unknown error"
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yield {
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"error": True,
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"status_code": response.status_code,
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"message": error_msg
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}
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return
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# Process streaming response
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for line in response.iter_lines():
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if line:
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line = line.decode('utf-8')
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if line.startswith('data: '):
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line = line[6:] # Remove 'data: ' prefix
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if line == '[DONE]':
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break
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try:
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event = json.loads(line)
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event_type = event.get("type")
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if event_type == "content_block_start":
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# New content block
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block = event.get("content_block", {})
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if block.get("type") == "tool_use":
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current_tool_use_index = event.get("index", 0)
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tool_uses_map[current_tool_use_index] = {
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"id": block.get("id", ""),
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"name": block.get("name", ""),
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"input": ""
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}
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elif event_type == "content_block_delta":
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delta = event.get("delta", {})
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delta_type = delta.get("type")
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if delta_type == "text_delta":
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# Text content
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content = delta.get("text", "")
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yield {
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"id": event.get("id", ""),
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"object": "chat.completion.chunk",
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"created": int(time.time()),
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"model": request_params["model"],
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"choices": [{
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"index": 0,
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"delta": {"content": content},
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"finish_reason": None
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}]
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}
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elif delta_type == "input_json_delta":
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# Tool input accumulation
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if current_tool_use_index >= 0:
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tool_uses_map[current_tool_use_index]["input"] += delta.get("partial_json", "")
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elif event_type == "message_delta":
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# Extract stop_reason from delta
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delta = event.get("delta", {})
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if "stop_reason" in delta:
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stop_reason = delta.get("stop_reason")
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logger.info(f"[Claude] Stream stop_reason: {stop_reason}")
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# Message complete - yield tool calls if any
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if tool_uses_map:
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for idx in sorted(tool_uses_map.keys()):
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tool_data = tool_uses_map[idx]
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yield {
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"id": event.get("id", ""),
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"object": "chat.completion.chunk",
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"created": int(time.time()),
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"model": request_params["model"],
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"choices": [{
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"index": 0,
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"delta": {
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"tool_calls": [{
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"index": idx,
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"id": tool_data["id"],
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"type": "function",
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"function": {
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"name": tool_data["name"],
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"arguments": tool_data["input"]
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}
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}]
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},
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"finish_reason": stop_reason
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}]
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}
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elif event_type == "message_stop":
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# Final event - log completion
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logger.debug(f"[Claude] Stream completed with stop_reason: {stop_reason}")
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except json.JSONDecodeError:
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continue
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except requests.RequestException as e:
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logger.error(f"Claude streaming request error: {e}")
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yield {
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"error": True,
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"message": f"Connection error: {str(e)}",
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"status_code": 0
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}
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except Exception as e:
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logger.error(f"Claude streaming error: {e}")
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yield {
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"error": True,
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"message": str(e),
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"status_code": 500
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}
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