panda
76f98a7aeb
- Add LLM_PROVIDER env var (openai/anthropic) to switch cloud backend - Use ChatAnthropic for anthropic provider with custom base_url - Add CONTEXT_MAX_TOKENS, CONTEXT_KEEP_RECENT, SESSIONS_DIR, HISTORY_MAX_SNAPSHOTS to .env and .env.example - Add langchain-anthropic dependency to requirements.txt Note: E2E testing blocked — the configured MiniMax API key (sk-cp-...) returns 401 across all endpoints (Anthropic and OpenAI). The API key may be expired or lack text-generation model access.
40 lines
1.2 KiB
Python
40 lines
1.2 KiB
Python
"""大语言模型工厂：支持 OpenAI 兼容的云端 API、Anthropic 兼容 API 和本地 Ollama。"""
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import os
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from dotenv import load_dotenv
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load_dotenv()
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def get_llm():
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backend = os.getenv("LLM_BACKEND", "cloud")
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if backend == "local":
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from langchain_ollama import ChatOllama
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model = os.getenv("LOCAL_LLM_MODEL", "qwen2.5-coder:7b")
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return ChatOllama(model=model, temperature=0.1)
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provider = os.getenv("LLM_PROVIDER", "openai")
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if provider == "anthropic":
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from langchain_anthropic import ChatAnthropic
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return ChatAnthropic(
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model=os.getenv("LLM_MODEL", "claude-sonnet-4-6"),
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api_key=os.getenv("OPENAI_API_KEY"),
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base_url=os.getenv("OPENAI_BASE_URL", "https://api.anthropic.com"),
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temperature=0.1,
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)
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else:
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from langchain_openai import ChatOpenAI
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return ChatOpenAI(
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model=os.getenv("LLM_MODEL", "gpt-4o"),
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api_key=os.getenv("OPENAI_API_KEY"),
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base_url=os.getenv("OPENAI_BASE_URL", "https://api.openai.com/v1"),
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temperature=0.1,
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)
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def get_llm_for_correction():
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return get_llm()
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