diff --git a/backend/llm.py b/backend/llm.py index 5c78cc4..c5b98ac 100644 --- a/backend/llm.py +++ b/backend/llm.py @@ -1,6 +1,8 @@ """大语言模型工厂:支持 OpenAI 兼容的云端 API、Anthropic 兼容 API 和本地 Ollama。""" import os +from typing import Any + from dotenv import load_dotenv load_dotenv() @@ -16,14 +18,35 @@ def get_llm(): provider = os.getenv("LLM_PROVIDER", "openai") if provider == "anthropic": - from langchain_anthropic import ChatAnthropic + from anthropic import Anthropic - return ChatAnthropic( - model=os.getenv("LLM_MODEL", "claude-sonnet-4-6"), - api_key=os.getenv("OPENAI_API_KEY"), - base_url=os.getenv("OPENAI_BASE_URL", "https://api.anthropic.com"), - temperature=0.1, - ) + api_key = os.getenv("OPENAI_API_KEY", "") + base_url = os.getenv("OPENAI_BASE_URL", "https://api.minimaxi.com/anthropic") + model = os.getenv("LLM_MODEL", "minimax-2.7") + temperature = 0.1 + max_tokens = 4096 + + os.environ["NO_PROXY"] = "*" + + client = Anthropic(base_url=base_url, timeout=120) + + class MiniMaxLLM: + def invoke(self, prompt: str) -> Any: + resp = client.messages.create( + model=model, + max_tokens=max_tokens, + temperature=temperature, + messages=[{"role": "user", "content": [{"type": "text", "text": prompt}]}], + ) + for block in resp.content: + if block.type == "text": + return type("Response", (), {"content": block.text})() + return type("Response", (), {"content": ""})() + + def get_num_tokens(self, text: str) -> int: + return client.count_tokens(text) + + return MiniMaxLLM() else: from langchain_openai import ChatOpenAI @@ -36,4 +59,4 @@ def get_llm(): def get_llm_for_correction(): - return get_llm() + return get_llm() \ No newline at end of file