presenton/servers/fastapi/utils/llm_provider.py

131 lines
3.6 KiB
Python

import os
from fastapi import HTTPException
from openai import AsyncOpenAI
from google import genai
from enums.llm_provider import LLMProvider
from utils.get_env import (
get_custom_llm_api_key_env,
get_custom_llm_url_env,
get_custom_model_env,
get_google_api_key_env,
get_llm_provider_env,
get_ollama_model_env,
get_ollama_url_env,
get_openai_api_key_env,
)
def get_llm_provider():
try:
return LLMProvider(get_llm_provider_env())
except:
raise HTTPException(
status_code=500,
detail=f"Invalid LLM provider. Please select one of: openai, google, ollama, custom",
)
def get_ollama_url():
return get_ollama_url_env() or "http://localhost:11434"
def is_openai_selected():
return get_llm_provider() == LLMProvider.OPENAI
def is_google_selected():
return get_llm_provider() == LLMProvider.GOOGLE
def is_ollama_selected():
return get_llm_provider() == LLMProvider.OLLAMA
def is_custom_llm_selected():
return get_llm_provider() == LLMProvider.CUSTOM
def get_model_base_url():
selected_llm = get_llm_provider()
if selected_llm == LLMProvider.OPENAI:
return "https://api.openai.com/v1"
elif selected_llm == LLMProvider.GOOGLE:
return "https://generativelanguage.googleapis.com/v1beta/openai"
elif selected_llm == LLMProvider.OLLAMA:
return os.path.join(get_ollama_url(), "v1")
elif selected_llm == LLMProvider.CUSTOM:
return get_custom_llm_url_env()
else:
raise HTTPException(f"LLM provider {selected_llm} is not supported")
def get_llm_api_key():
selected_llm = get_llm_provider()
if selected_llm == LLMProvider.OPENAI:
return get_openai_api_key_env()
elif selected_llm == LLMProvider.GOOGLE:
return get_google_api_key_env()
elif selected_llm == LLMProvider.OLLAMA:
return "ollama"
elif selected_llm == LLMProvider.CUSTOM:
return get_custom_llm_api_key_env() or "none"
else:
raise HTTPException(f"LLM provider {selected_llm} is not supported")
def get_llm_client():
client = AsyncOpenAI(
base_url=get_model_base_url(),
api_key=get_llm_api_key(),
)
return client
def get_google_llm_client():
client = genai.Client(api_key=get_llm_api_key())
return client
def get_large_model():
selected_llm = get_llm_provider()
if selected_llm == LLMProvider.OPENAI:
return "gpt-4.1"
elif selected_llm == LLMProvider.GOOGLE:
return "gemini-2.0-flash"
elif selected_llm == LLMProvider.OLLAMA:
return get_ollama_model_env()
elif selected_llm == LLMProvider.CUSTOM:
return get_custom_model_env()
else:
raise ValueError(f"Invalid LLM model")
def get_small_model():
selected_llm = get_llm_provider()
if selected_llm == LLMProvider.OPENAI:
return "gpt-4.1-mini"
elif selected_llm == LLMProvider.GOOGLE:
return "gemini-2.0-flash"
elif selected_llm == LLMProvider.OLLAMA:
return get_ollama_model_env()
elif selected_llm == LLMProvider.CUSTOM:
return get_custom_model_env()
else:
raise ValueError(f"Invalid LLM model")
def get_nano_model():
selected_llm = get_llm_provider()
if selected_llm == LLMProvider.OPENAI:
return "gpt-4.1-nano"
elif selected_llm == LLMProvider.GOOGLE:
return "gemini-2.0-flash"
elif selected_llm == LLMProvider.OLLAMA:
return get_ollama_model_env()
elif selected_llm == LLMProvider.CUSTOM:
return get_custom_model_env()
else:
raise ValueError(f"Invalid LLM model")