llm.py

import os
# from langchain_groq import ChatGroq
# from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
from langchain_openai import ChatOpenAI
from dotenv import load_dotenv

load_dotenv()

def get_llm(provider: str = "groq"):
    if provider == "groq":
        # return ChatGroq(
        #     model="qwen/qwen3-32b",
        #     temperature=0
        # )
        
        # return ChatOpenAI(
        #     model="openai/gpt-4o-mini",
        #     api_key=os.getenv("OPENROUTER_API_KEY"),
        #     base_url="https://openrouter.ai/api/v1",
        #     temperature=0
        # )
        
        return ChatOpenAI(
            model="openai/gpt-4o-mini",
            base_url="https://openrouter.ai/api/v1",
            api_key=os.getenv("OPENROUTER_API_KEY"),
            default_headers={
                "HTTP-Referer": "http://localhost",
                "X-Title": "agent"
            },
            temperature=0,
            max_tokens=1024
        )

    # elif provider == "huggingface":
    #     return ChatHuggingFace(
    #         llm=HuggingFaceEndpoint(
    #             repo_id="TinyLlama/TinyLlama-1.1B-Chat-v1.0",
    #             task="text-generation",
    #             max_new_tokens=512,
    #             temperature=0,
    #             do_sample=False
    #         )
    #     )
    # else:
    #     raise ValueError("Invalid provider")


def bind_tools(llm, tools):
    return llm.bind_tools(tools)