101/RAG/models.py

from langchain_core.language_models import BaseChatModel
from langchain_core.callbacks import CallbackManagerForLLMRun
from langchain_core.outputs import ChatResult, ChatGeneration
from langchain_core.messages import BaseMessage, AIMessage, HumanMessage, SystemMessage
from pydantic import Field
import subprocess
from typing import Any, List, Optional
from tenacity import retry, stop_after_attempt, wait_random_exponential
from config import system_prompt

class OllamaChatModel(BaseChatModel):
    model_name: str = Field(default="taide-local-3")

    @retry(stop=stop_after_attempt(3), wait=wait_random_exponential(min=1, max=60))
    def _generate(
            self,
            messages: List[BaseMessage],
            stop: Optional[List[str]] = None,
            run_manager: Optional[CallbackManagerForLLMRun] = None,
            **kwargs: Any,
    ) -> ChatResult:
        formatted_messages = []
        for msg in messages:
            if isinstance(msg, HumanMessage):
                formatted_messages.append({"role": "user", "content": msg.content})
            elif isinstance(msg, AIMessage):
                formatted_messages.append({"role": "assistant", "content": msg.content})
            elif isinstance(msg, SystemMessage):
                 formatted_messages.append({"role": "system", "content": msg.content})

        prompt = f"<s>[INST] {system_prompt}\n\n"
        for msg in formatted_messages:
            if msg['role'] == 'user':
                prompt += f"{msg['content']} [/INST]"
            elif msg['role'] == "assistant":
                prompt += f"{msg['content']} </s><s>[INST]"

        command = ["ollama", "run", self.model_name, prompt]
        try:
            result = subprocess.run(command, capture_output=True, text=True, timeout=60)  # 添加60秒超時
        except subprocess.TimeoutExpired:
            raise Exception("Ollama command timed out")

        if result.returncode != 0:
            raise Exception(f"Ollama command failed: {result.stderr}")
        
        content = result.stdout.strip()

        message = AIMessage(content=content)
        generation = ChatGeneration(message=message)
        return ChatResult(generations=[generation])
    
    @property
    def _llm_type(self) -> str:
        return "ollama-chat-model"