modules/env.py

from crewai import LLM
import os
from dotenv import load_dotenv
from pathlib import Path
from langchain_openai import ChatOpenAI
from langchain_openrouter import ChatOpenRouter

env_path = Path(__file__).resolve().parents[1] / ".env"
# Load variables from .env file
load_dotenv(dotenv_path=env_path)

# Now you can access them
gemini_key = os.getenv("GEMINI_API_KEY")
tavily_key = os.getenv("TAVILY_API_KEY")
openrouter_key = os.getenv("OPENROUTER_API_KEY")
os.environ["ANTHROPIC_API_KEY"] = openrouter_key
# llm = LLM(model="gemini/gemini-2.5-flash", temperature=0, api_key=gemini_key)
# llm = LLM(
#     model="openrouter/openai/gpt-oss-20b:free",
#     api_key=openrouter_key,
#     base_url="https://openrouter.ai/api/v1",
# )
def llm():
    return LLM(
    model="openrouter/openai/gpt-oss-20b:free",
    api_key=openrouter_key,
    base_url="https://openrouter.ai/api/v1",
)
def llm_oss():
    return LLM(
    model="openrouter/openai/gpt-oss-20b:free",
    api_key=openrouter_key,
    base_url="https://openrouter.ai/api/v1",
)
def llm_oss_120b():
    return LLM(
    model="openai/gpt-oss-120b:nitro",
    api_key=openrouter_key,
    base_url="https://openrouter.ai/api/v1",
)


def llm_g():
    return LLM(
    model="openrouter/google/gemini-2.5-flash",
    temperature=0,
    api_key=openrouter_key,
    base_url="https://openrouter.ai/api/v1",
)

def llm_5m():
    return LLM(
        model="openrouter/openai/gpt-5-mini",
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
    )


def llm_4m():
    return LLM(
        model="openrouter/openai/gpt-4.1-mini",
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
    )





# def llm_5m():
#     return LLM(
#         model="gpt-5-mini-2025-08-07",
#     )


# def llm_4m():
#     return LLM(
#         model="gpt-4.1-mini-2025-04-14",
#     )


# def llm_5n():
#     return LLM(
#         model="gpt-5-nano-2025-08-07",
#     )

def llm_open_4m():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/openai/gpt-4.1-mini",
    )

def llm_5n():
    return LLM(
        model="openrouter/openai/gpt-5-nano",
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
    )

def llm_open_c3():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/anthropic/claude-3-haiku",
        # streaming=False,
    )

def llm_open_c35():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/anthropic/claude-3.5-haiku",
        # streaming=False,
    )
def llm_open_nova():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/amazon/nova-2-lite-v1",
        # streaming=False,
        # tools=[],
    )

def llm_open_hermes():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/nousresearch/hermes-3-llama-3.1-405b:free",
        # streaming=False,
)

def llm_open_grok():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/x-ai/grok-4.3",
        max_tokens=15000,
        # streaming=False,
    )

def llm_open_g25pro():  
        return LLM(
    api_key=openrouter_key,
    base_url="https://openrouter.ai/api/v1",
    model="openrouter/google/gemini-2.5-pro",
    # streaming=False,
    max_output_tokens=40000,
)

# Initialize Gemini model
def model():
    return ChatOpenAI(
    model="google/gemini-2.5-flash",
    temperature=0,
    api_key=openrouter_key,
    base_url="https://openrouter.ai/api/v1",
)

def llm_qwen():
    return LLM(
        api_key=openrouter_key,
        base_url="https://openrouter.ai/api/v1",
        model="openrouter/qwen/qwen3.6-plus:free",
        # streaming=False,
    )

def model_open_router():
    return ChatOpenRouter(
        model="x-ai/grok-4.1-fast",
        api_key=openrouter_key,
        temperature=0.2,
        max_retries=2,
    )

# # check llm
# response=llm_g.call("Hello, how are you?")
# print(response)