mirror of
https://github.com/zhayujie/chatgpt-on-wechat.git
synced 2026-07-21 22:27:13 +08:00
feat: support skills creator and gemini models
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saboteur7
@@ -8,6 +8,7 @@ import openai.error
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import requests
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from common import const
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from bot.bot import Bot
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from bot.openai_compatible_bot import OpenAICompatibleBot
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from bot.chatgpt.chat_gpt_session import ChatGPTSession
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from bot.openai.open_ai_image import OpenAIImage
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from bot.session_manager import SessionManager
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@@ -19,7 +20,7 @@ from config import conf, load_config
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from bot.baidu.baidu_wenxin_session import BaiduWenxinSession
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# OpenAI对话模型API (可用)
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class ChatGPTBot(Bot, OpenAIImage):
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class ChatGPTBot(Bot, OpenAIImage, OpenAICompatibleBot):
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def __init__(self):
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super().__init__()
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# set the default api_key
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@@ -53,6 +54,18 @@ class ChatGPTBot(Bot, OpenAIImage):
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if conf_model in [const.O1, const.O1_MINI]: # o1系列模型不支持系统提示词，使用文心模型的session
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self.sessions = SessionManager(BaiduWenxinSession, model=conf().get("model") or const.O1_MINI)
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def get_api_config(self):
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"""Get API configuration for OpenAI-compatible base class"""
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return {
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'api_key': conf().get("open_ai_api_key"),
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'api_base': conf().get("open_ai_api_base"),
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'model': conf().get("model", "gpt-3.5-turbo"),
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'default_temperature': conf().get("temperature", 0.9),
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'default_top_p': conf().get("top_p", 1.0),
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'default_frequency_penalty': conf().get("frequency_penalty", 0.0),
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'default_presence_penalty': conf().get("presence_penalty", 0.0),
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}
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def reply(self, query, context=None):
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# acquire reply content
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if context.type == ContextType.TEXT:
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@@ -172,252 +185,6 @@ class ChatGPTBot(Bot, OpenAIImage):
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else:
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return result
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def call_with_tools(self, messages, tools=None, stream=False, **kwargs):
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"""
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Call OpenAI API with tool support for agent integration
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Args:
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messages: List of messages (may be in Claude format from agent)
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tools: List of tool definitions (may be in Claude format from agent)
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stream: Whether to use streaming
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**kwargs: Additional parameters (max_tokens, temperature, system, etc.)
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Returns:
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Formatted response in OpenAI format or generator for streaming
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"""
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try:
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# Convert messages from Claude format to OpenAI format
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messages = self._convert_messages_to_openai_format(messages)
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# Convert tools from Claude format to OpenAI format
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if tools:
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tools = self._convert_tools_to_openai_format(tools)
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# Handle system prompt (OpenAI uses system message, Claude uses separate parameter)
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system_prompt = kwargs.get('system')
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if system_prompt:
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# Add system message at the beginning if not already present
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if not messages or messages[0].get('role') != 'system':
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messages = [{"role": "system", "content": system_prompt}] + messages
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else:
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# Replace existing system message
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messages[0] = {"role": "system", "content": system_prompt}
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# Build request parameters
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request_params = {
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"model": kwargs.get("model", conf().get("model") or "gpt-3.5-turbo"),
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"messages": messages,
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"temperature": kwargs.get("temperature", conf().get("temperature", 0.9)),
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"top_p": kwargs.get("top_p", conf().get("top_p", 1)),
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"frequency_penalty": kwargs.get("frequency_penalty", conf().get("frequency_penalty", 0.0)),
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"presence_penalty": kwargs.get("presence_penalty", conf().get("presence_penalty", 0.0)),
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"stream": stream
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}
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# Add max_tokens if specified
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if kwargs.get("max_tokens"):
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request_params["max_tokens"] = kwargs["max_tokens"]
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# Add tools if provided
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if tools:
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request_params["tools"] = tools
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request_params["tool_choice"] = kwargs.get("tool_choice", "auto")
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# Handle model-specific parameters (o1, gpt-5 series don't support some params)
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model = request_params["model"]
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if model in [const.O1, const.O1_MINI, const.GPT_5, const.GPT_5_MINI, const.GPT_5_NANO]:
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remove_keys = ["temperature", "top_p", "frequency_penalty", "presence_penalty"]
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for key in remove_keys:
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request_params.pop(key, None)
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# Make API call
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# Note: Don't pass api_key explicitly to use global openai.api_key and openai.api_base
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# which are set in __init__
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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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error_msg = str(e)
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logger.error(f"[ChatGPT] call_with_tools error: {error_msg}")
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if stream:
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def error_generator():
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yield {
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"error": True,
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"message": error_msg,
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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 {
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"error": True,
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"message": error_msg,
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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 OpenAI API response"""
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try:
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# Explicitly set API configuration to ensure it's used
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# (global settings can be unreliable in some contexts)
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api_key = conf().get("open_ai_api_key")
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api_base = conf().get("open_ai_api_base")
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# Build kwargs with explicit API configuration
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kwargs = dict(request_params)
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if api_key:
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kwargs["api_key"] = api_key
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if api_base:
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kwargs["api_base"] = api_base
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response = openai.ChatCompletion.create(**kwargs)
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# Response is already in OpenAI format
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logger.info(f"[ChatGPT] call_with_tools reply, model={response.get('model')}, "
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f"total_tokens={response.get('usage', {}).get('total_tokens', 0)}")
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return response
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except Exception as e:
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logger.error(f"[ChatGPT] sync response error: {e}")
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raise
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def _handle_stream_response(self, request_params):
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"""Handle streaming OpenAI API response"""
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try:
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# Explicitly set API configuration to ensure it's used
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api_key = conf().get("open_ai_api_key")
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api_base = conf().get("open_ai_api_base")
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logger.debug(f"[ChatGPT] Starting stream with params: model={request_params.get('model')}, stream={request_params.get('stream')}")
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# Build kwargs with explicit API configuration
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kwargs = dict(request_params)
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if api_key:
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kwargs["api_key"] = api_key
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if api_base:
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kwargs["api_base"] = api_base
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stream = openai.ChatCompletion.create(**kwargs)
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# OpenAI stream is already in the correct format
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chunk_count = 0
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for chunk in stream:
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chunk_count += 1
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yield chunk
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logger.debug(f"[ChatGPT] Stream completed, yielded {chunk_count} chunks")
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except Exception as e:
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logger.error(f"[ChatGPT] stream response error: {e}", exc_info=True)
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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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def _convert_tools_to_openai_format(self, tools):
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"""
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Convert tools from Claude format to OpenAI format
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Claude format: {name, description, input_schema}
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OpenAI format: {type: "function", function: {name, description, parameters}}
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"""
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if not tools:
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return None
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openai_tools = []
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for tool in tools:
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# Check if already in OpenAI format
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if 'type' in tool and tool['type'] == 'function':
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openai_tools.append(tool)
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else:
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# Convert from Claude format
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openai_tools.append({
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"type": "function",
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"function": {
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"name": tool.get("name"),
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"description": tool.get("description"),
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"parameters": tool.get("input_schema", {})
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}
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})
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return openai_tools
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def _convert_messages_to_openai_format(self, messages):
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"""
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Convert messages from Claude format to OpenAI format
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Claude uses content blocks with types like 'tool_use', 'tool_result'
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OpenAI uses 'tool_calls' in assistant messages and 'tool' role for results
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"""
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if not messages:
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return []
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openai_messages = []
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for msg in messages:
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role = msg.get("role")
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content = msg.get("content")
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# Handle string content (already in correct format)
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if isinstance(content, str):
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openai_messages.append(msg)
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continue
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# Handle list content (Claude format with content blocks)
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if isinstance(content, list):
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# Check if this is a tool result message (user role with tool_result blocks)
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if role == "user" and any(block.get("type") == "tool_result" for block in content):
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# Convert each tool_result block to a separate tool message
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for block in content:
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if block.get("type") == "tool_result":
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openai_messages.append({
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"role": "tool",
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"tool_call_id": block.get("tool_use_id"),
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"content": block.get("content", "")
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})
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# Check if this is an assistant message with tool_use blocks
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elif role == "assistant":
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# Separate text content and tool_use blocks
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text_parts = []
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tool_calls = []
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for block in content:
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if block.get("type") == "text":
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text_parts.append(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 OpenAI format assistant message
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openai_msg = {
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"role": "assistant",
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"content": " ".join(text_parts) if text_parts else None
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}
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if tool_calls:
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openai_msg["tool_calls"] = tool_calls
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openai_messages.append(openai_msg)
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else:
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# Other list content, keep as is
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openai_messages.append(msg)
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else:
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# Other formats, keep as is
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openai_messages.append(msg)
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return openai_messages
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class AzureChatGPTBot(ChatGPTBot):
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def __init__(self):
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super().__init__()
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