Markov
5417980b76
- Implemented ReAct loop in agent.py - Added Anthropic provider using httpx (no SDK) - Created tools: read, write, edit, bash - Added session management with JSONL format - Included configuration system with env var support - Added CLI interface and example usage - Minimal dependencies: only httpx
61 lines
1.6 KiB
Python
61 lines
1.6 KiB
Python
"""
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Base provider class for AI providers
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"""
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from abc import ABC, abstractmethod
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from typing import List, Dict, Any, Optional
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from ..config import Config
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class BaseProvider(ABC):
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"""Base class for AI providers"""
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def __init__(self, config: Config):
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self.config = config
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@abstractmethod
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async def chat_completion(
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self,
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messages: List[Dict[str, Any]],
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tools: Optional[List[Dict[str, Any]]] = None,
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system_prompt: Optional[str] = None
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) -> Dict[str, Any]:
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"""
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Get chat completion from the provider
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Args:
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messages: List of messages in the conversation
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tools: Optional list of available tools
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system_prompt: Optional system prompt
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Returns:
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Dictionary containing response with 'content' and optional 'tool_calls'
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"""
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pass
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@abstractmethod
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def parse_tool_calls(self, response: Dict[str, Any]) -> List[Dict[str, Any]]:
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"""
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Parse tool calls from provider response
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Args:
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response: Provider response
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Returns:
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List of tool calls with 'id', 'name', and 'arguments'
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"""
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pass
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@abstractmethod
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def format_tool_result(self, tool_call_id: str, result: str) -> Dict[str, Any]:
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"""
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Format tool result for next request
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Args:
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tool_call_id: ID of the tool call
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result: Result of tool execution
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Returns:
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Formatted message for the provider
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"""
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pass |