import json
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from config.logger import setup_logging
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import requests
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from core.providers.llm.base import LLMProviderBase
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from core.utils.util import check_model_key
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TAG = __name__
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logger = setup_logging()
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class LLMProvider(LLMProviderBase):
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def __init__(self, config):
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self.api_key = config["api_key"]
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self.base_url = config.get("base_url")
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self.detail = config.get("detail", False)
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self.variables = config.get("variables", {})
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model_key_msg = check_model_key("FastGPTLLM", self.api_key)
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if model_key_msg:
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logger.bind(tag=TAG).error(model_key_msg)
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def response(self, session_id, dialogue, **kwargs):
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# 取最后一条用户消息
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last_msg = next(m for m in reversed(dialogue) if m["role"] == "user")
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# 发起流式请求
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with requests.post(
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f"{self.base_url}/chat/completions",
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headers={"Authorization": f"Bearer {self.api_key}"},
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json={
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"stream": True,
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"chatId": session_id,
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"detail": self.detail,
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"variables": self.variables,
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"messages": [{"role": "user", "content": last_msg["content"]}],
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},
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stream=True,
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) as r:
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for line in r.iter_lines():
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if line:
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try:
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if line.startswith(b"data: "):
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if line[6:].decode("utf-8") == "[DONE]":
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break
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data = json.loads(line[6:])
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if "choices" in data and len(data["choices"]) > 0:
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delta = data["choices"][0].get("delta", {})
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if (
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delta
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and "content" in delta
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and delta["content"] is not None
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):
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content = delta["content"]
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if "<think>" in content:
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continue
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if "</think>" in content:
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continue
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yield content
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except json.JSONDecodeError as e:
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continue
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except Exception as e:
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continue
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def response_with_functions(self, session_id, dialogue, functions=None):
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logger.bind(tag=TAG).error(
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f"fastgpt暂未实现完整的工具调用（function call），建议使用其他意图识别"
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)
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