bryan
95 lines
2.8 KiB
Python
95 lines
2.8 KiB
Python
"""Anthropic Claude LLM provider - backward compatible wrapper around LiteLLM."""
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import os
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from typing import Any
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from framework.llm.provider import LLMProvider, LLMResponse, Tool
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from framework.llm.litellm import LiteLLMProvider
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def _get_api_key_from_credential_manager() -> str | None:
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"""Get API key from CredentialManager or environment.
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Priority:
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1. CredentialManager (supports .env hot-reload)
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2. os.environ fallback
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"""
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try:
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from aden_tools.credentials import CredentialManager
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creds = CredentialManager()
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if creds.is_available("anthropic"):
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return creds.get("anthropic")
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except ImportError:
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pass
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return os.environ.get("ANTHROPIC_API_KEY")
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class AnthropicProvider(LLMProvider):
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"""
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Anthropic Claude LLM provider.
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This is a backward-compatible wrapper that internally uses LiteLLMProvider.
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Existing code using AnthropicProvider will continue to work unchanged,
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while benefiting from LiteLLM's unified interface and features.
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"""
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def __init__(
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self,
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api_key: str | None = None,
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model: str = "claude-haiku-4-5-20251001",
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):
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"""
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Initialize the Anthropic provider.
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Args:
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api_key: Anthropic API key. If not provided, uses CredentialManager
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or ANTHROPIC_API_KEY env var.
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model: Model to use (default: claude-haiku-4-5-20251001)
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"""
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# Delegate to LiteLLMProvider internally.
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self.api_key = api_key or _get_api_key_from_credential_manager()
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if not self.api_key:
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raise ValueError(
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"Anthropic API key required. Set ANTHROPIC_API_KEY env var or pass api_key."
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)
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self.model = model
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self._provider = LiteLLMProvider(
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model=model,
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api_key=self.api_key,
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)
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def complete(
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self,
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messages: list[dict[str, Any]],
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system: str = "",
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tools: list[Tool] | None = None,
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max_tokens: int = 1024,
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) -> LLMResponse:
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"""Generate a completion from Claude (via LiteLLM)."""
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return self._provider.complete(
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messages=messages,
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system=system,
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tools=tools,
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max_tokens=max_tokens,
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)
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def complete_with_tools(
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self,
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messages: list[dict[str, Any]],
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system: str,
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tools: list[Tool],
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tool_executor: callable,
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max_iterations: int = 10,
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) -> LLMResponse:
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"""Run a tool-use loop until Claude produces a final response (via LiteLLM)."""
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return self._provider.complete_with_tools(
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messages=messages,
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system=system,
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tools=tools,
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tool_executor=tool_executor,
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max_iterations=max_iterations,
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)
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