56 lines
1.5 KiB
Python
56 lines
1.5 KiB
Python
"""Abstract LLM adapter interface; model-agnostic for orchestrator and agents."""
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from abc import ABC, abstractmethod
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from typing import Any
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class LLMAdapter(ABC):
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"""
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Abstract adapter for LLM completion.
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Implementations should handle:
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- openai/ - OpenAI API (GPT-4, etc.)
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- anthropic/ - Anthropic API (Claude, etc.)
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- local/ - Local models (Ollama, etc.)
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"""
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@abstractmethod
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def complete(
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self,
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messages: list[dict[str, str]],
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**kwargs: Any,
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) -> str:
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"""
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Return completion text for the given messages.
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Args:
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messages: List of message dicts with 'role' and 'content' keys.
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**kwargs: Provider-specific options (e.g., temperature, max_tokens).
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Returns:
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The model's response text.
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"""
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...
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def complete_structured(
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self,
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messages: list[dict[str, str]],
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schema: dict[str, Any] | None = None,
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**kwargs: Any,
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) -> Any:
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"""
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Return structured (JSON) output.
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Default implementation returns None; subclasses may override to use
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provider-specific JSON modes (e.g., OpenAI's response_format).
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Args:
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messages: List of message dicts with 'role' and 'content' keys.
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schema: Optional JSON schema for response validation.
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**kwargs: Provider-specific options.
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Returns:
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Parsed JSON response or None if not supported/parsing fails.
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"""
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return None
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