presenton/servers/fastapi/utils/llm_provider.py
sudipnext d2e85a8ffa feat: implement Codex OAuth flow and integrate into application
- Added Codex authentication endpoints and logic for OAuth flow.
- Updated Docker configuration to expose port 1455 for Codex callback.
- Enhanced user configuration model to include Codex-related fields.
- Integrated Codex selection into the LLM provider UI.
- Implemented token management and refresh logic for Codex.
- Added utility functions for handling Codex OAuth tokens and state management.
2026-02-24 18:51:35 +05:45

72 lines
2 KiB
Python

from fastapi import HTTPException
from constants.llm import (
DEFAULT_ANTHROPIC_MODEL,
DEFAULT_GOOGLE_MODEL,
DEFAULT_OPENAI_MODEL,
)
from enums.llm_provider import LLMProvider
from utils.get_env import (
get_anthropic_model_env,
get_codex_model_env,
get_custom_model_env,
get_google_model_env,
get_llm_provider_env,
get_ollama_model_env,
get_openai_model_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, anthropic, ollama, custom, codex",
)
def is_openai_selected():
return get_llm_provider() == LLMProvider.OPENAI
def is_google_selected():
return get_llm_provider() == LLMProvider.GOOGLE
def is_anthropic_selected():
return get_llm_provider() == LLMProvider.ANTHROPIC
def is_ollama_selected():
return get_llm_provider() == LLMProvider.OLLAMA
def is_custom_llm_selected():
return get_llm_provider() == LLMProvider.CUSTOM
def is_codex_selected():
return get_llm_provider() == LLMProvider.CODEX
def get_model():
selected_llm = get_llm_provider()
if selected_llm == LLMProvider.OPENAI:
return get_openai_model_env() or DEFAULT_OPENAI_MODEL
elif selected_llm == LLMProvider.GOOGLE:
return get_google_model_env() or DEFAULT_GOOGLE_MODEL
elif selected_llm == LLMProvider.ANTHROPIC:
return get_anthropic_model_env() or DEFAULT_ANTHROPIC_MODEL
elif selected_llm == LLMProvider.OLLAMA:
return get_ollama_model_env()
elif selected_llm == LLMProvider.CUSTOM:
return get_custom_model_env()
elif selected_llm == LLMProvider.CODEX:
return get_codex_model_env()
else:
raise HTTPException(
status_code=500,
detail=f"Invalid LLM provider. Please select one of: openai, google, anthropic, ollama, custom, codex",
)