98 lines
2.5 KiB
Python
98 lines
2.5 KiB
Python
"""ProviderAdapter - LLM Provider adapter base class
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Defines unified adapter interface that all Provider adapters must implement.
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"""
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from abc import ABC, abstractmethod
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from typing import Dict, List, Any, AsyncGenerator
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class ProviderAdapter(ABC):
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"""LLM Provider adapter base class
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All LLM API adapters must inherit from this class and implement its methods.
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Adapters are responsible for:
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1. Building requests in provider-specific format
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2. Parsing streaming and non-streaming responses
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3. Providing provider capability information
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Attributes:
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provider_type: Provider type identifier
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"""
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@property
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@abstractmethod
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def provider_type(self) -> str:
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"""Return provider type identifier
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Returns:
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str: Provider type, e.g., "openai", "anthropic"
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"""
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pass
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@abstractmethod
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def build_request(
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self,
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model: str,
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messages: List[Dict[str, Any]],
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tools: List[Dict[str, Any]] = None,
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**kwargs
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) -> tuple[Dict[str, Any], Dict[str, str]]:
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"""Build request body and headers
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Args:
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model: Model name
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messages: Message list
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tools: Tool definition list
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**kwargs: Other parameters (temperature, max_tokens, thinking_enabled, etc.)
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Returns:
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tuple: (body, headers) tuple
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"""
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pass
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@abstractmethod
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async def parse_stream_chunk(
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self,
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raw_chunk: str
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) -> AsyncGenerator[Any, None]:
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"""Parse streaming response chunk
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Args:
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raw_chunk: Raw SSE line or chunk data
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Yields:
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ParsedDelta object or other parsed results
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"""
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pass
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@abstractmethod
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def parse_response(
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self,
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data: Dict[str, Any]
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) -> Any:
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"""Parse non-streaming response
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Args:
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data: API response data
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Returns:
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LLMResponse object
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"""
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pass
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def supports_thinking(self) -> bool:
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"""Whether provider supports thinking/reasoning
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Returns:
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bool: True if provider supports thinking/reasoning content
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"""
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return False
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def supports_tools(self) -> bool:
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"""Whether provider supports tool/function calls
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Returns:
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bool: True if provider supports function calling
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"""
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return False
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