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chore: the bot directory was changed to models
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278
models/openai_compatible_bot.py
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278
models/openai_compatible_bot.py
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# encoding:utf-8
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"""
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OpenAI-Compatible Bot Base Class
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Provides a common implementation for bots that are compatible with OpenAI's API format.
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This includes: OpenAI, LinkAI, Azure OpenAI, and many third-party providers.
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"""
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import json
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import openai
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from common.log import logger
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class OpenAICompatibleBot:
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"""
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Base class for OpenAI-compatible bots.
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Provides common tool calling implementation that can be inherited by:
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- ChatGPTBot
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- LinkAIBot
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- OpenAIBot
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- AzureChatGPTBot
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- Other OpenAI-compatible providers
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Subclasses only need to override get_api_config() to provide their specific API settings.
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"""
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def get_api_config(self):
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"""
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Get API configuration for this bot.
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Subclasses should override this to provide their specific config.
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Returns:
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dict: {
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'api_key': str,
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'api_base': str (optional),
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'model': str,
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'default_temperature': float,
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'default_top_p': float,
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'default_frequency_penalty': float,
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'default_presence_penalty': float,
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}
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"""
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raise NotImplementedError("Subclasses must implement get_api_config()")
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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-compatible API with tool support for agent integration
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This method handles:
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1. Format conversion (Claude format → OpenAI format)
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2. System prompt injection
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3. API calling with proper configuration
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4. Error handling
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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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# Get API configuration from subclass
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api_config = self.get_api_config()
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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", api_config.get('model', 'gpt-3.5-turbo')),
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"messages": messages,
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"temperature": kwargs.get("temperature", api_config.get('default_temperature', 0.9)),
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"top_p": kwargs.get("top_p", api_config.get('default_top_p', 1.0)),
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"frequency_penalty": kwargs.get("frequency_penalty", api_config.get('default_frequency_penalty', 0.0)),
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"presence_penalty": kwargs.get("presence_penalty", api_config.get('default_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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# Make API call with proper configuration
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api_key = api_config.get('api_key')
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api_base = api_config.get('api_base')
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if stream:
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return self._handle_stream_response(request_params, api_key, api_base)
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else:
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return self._handle_sync_response(request_params, api_key, api_base)
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except Exception as e:
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error_msg = str(e)
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logger.error(f"[{self.__class__.__name__}] 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, api_key, api_base):
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"""Handle synchronous OpenAI API response"""
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try:
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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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return response
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except Exception as e:
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logger.error(f"[{self.__class__.__name__}] sync response error: {e}")
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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_stream_response(self, request_params, api_key, api_base):
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"""Handle streaming OpenAI API response"""
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try:
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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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# Stream chunks to caller
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for chunk in stream:
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yield chunk
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except Exception as e:
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logger.error(f"[{self.__class__.__name__}] stream response 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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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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