import time from fastapi import APIRouter, Depends, Request # Added Request from typing import List, Dict, Any from auth import get_api_key from model_loader import get_vertex_models, get_vertex_express_models, refresh_models_config_cache import config as app_config # Import config from credentials_manager import CredentialManager # To check its type router = APIRouter() @router.get("/v1/models") async def list_models(fastapi_request: Request, api_key: str = Depends(get_api_key)): await refresh_models_config_cache() OPENAI_DIRECT_SUFFIX = "-openai" EXPERIMENTAL_MARKER = "-exp-" PAY_PREFIX = "[PAY]" # Access credential_manager from app state credential_manager_instance: CredentialManager = fastapi_request.app.state.credential_manager has_sa_creds = credential_manager_instance.get_total_credentials() > 0 has_express_key = bool(app_config.VERTEX_EXPRESS_API_KEY_VAL) raw_vertex_models = await get_vertex_models() raw_express_models = await get_vertex_express_models() candidate_model_ids = set() raw_vertex_models_set = set(raw_vertex_models) # For checking origin during prefixing if has_express_key: candidate_model_ids.update(raw_express_models) # If *only* express key is available, only express models (and their variants) should be listed. # The current `vertex_model_ids` from remote config might contain non-express models. # The `get_vertex_express_models()` should be the source of truth for express-eligible base models. if not has_sa_creds: # Only list models that are explicitly in the express list. # Suffix generation will apply only to these if they are not gemini-2.0 all_model_ids = set(raw_express_models) else: # Both SA and Express are available, combine all known models all_model_ids = set(raw_vertex_models + raw_express_models) elif has_sa_creds: # Only SA creds available, use all vertex_models (which might include express-eligible ones) all_model_ids = set(raw_vertex_models) else: # No credentials available all_model_ids = set() # Create extended model list with variations (search, encrypt, auto etc.) # This logic might need to be more sophisticated based on actual supported features per base model. # For now, let's assume for each base model, we might have these variations. # A better approach would be if the remote config specified these variations. dynamic_models_data: List[Dict[str, Any]] = [] current_time = int(time.time()) # Add base models and their variations for original_model_id in sorted(list(all_model_ids)): current_display_prefix = "" # Only add PAY_PREFIX if the model is not already an EXPRESS model (which has its own prefix) # Apply PAY_PREFIX if SA creds are present, it's a model from raw_vertex_models, # it's not experimental, and not already an EXPRESS model. if has_sa_creds and \ original_model_id in raw_vertex_models_set and \ EXPERIMENTAL_MARKER not in original_model_id and \ not original_model_id.startswith("[EXPRESS]"): current_display_prefix = PAY_PREFIX base_display_id = f"{current_display_prefix}{original_model_id}" dynamic_models_data.append({ "id": base_display_id, "object": "model", "created": current_time, "owned_by": "google", "permission": [], "root": original_model_id, "parent": None }) # Conditionally add common variations (standard suffixes) if not original_model_id.startswith("gemini-2.0"): # Suffix rules based on original_model_id standard_suffixes = ["-search", "-encrypt", "-encrypt-full", "-auto"] for suffix in standard_suffixes: # Suffix is applied to the original model ID part suffixed_model_part = f"{original_model_id}{suffix}" # Then the whole thing is prefixed final_suffixed_display_id = f"{current_display_prefix}{suffixed_model_part}" # Check if this suffixed ID is already in all_model_ids (unlikely with prefix) or already added if final_suffixed_display_id not in all_model_ids and not any(m['id'] == final_suffixed_display_id for m in dynamic_models_data): dynamic_models_data.append({ "id": final_suffixed_display_id, "object": "model", "created": current_time, "owned_by": "google", "permission": [], "root": original_model_id, "parent": None }) # Apply special suffixes for models starting with "gemini-2.5-flash" if original_model_id.startswith("gemini-2.5-flash"): # Suffix rules based on original_model_id special_flash_suffixes = ["-nothinking", "-max"] for special_suffix in special_flash_suffixes: suffixed_model_part = f"{original_model_id}{special_suffix}" final_special_suffixed_display_id = f"{current_display_prefix}{suffixed_model_part}" if final_special_suffixed_display_id not in all_model_ids and not any(m['id'] == final_special_suffixed_display_id for m in dynamic_models_data): dynamic_models_data.append({ "id": final_special_suffixed_display_id, "object": "model", "created": current_time, "owned_by": "google", "permission": [], "root": original_model_id, "parent": None }) # Ensure uniqueness again after adding suffixes # Add OpenAI direct variations if SA creds are available if has_sa_creds: # OpenAI direct mode only works with SA credentials # `all_model_ids` contains the comprehensive list of base models that are eligible based on current credentials # We iterate through this to determine which ones get an -openai variation. # `raw_vertex_models` is used here to ensure we only add -openai suffix to models that are # fundamentally Vertex models, not just any model that might appear in `all_model_ids` (e.g. from Express list exclusively) # if express only key is provided. # We iterate through the base models from the main Vertex list. for base_model_id_for_openai in raw_vertex_models: # Iterate through original list of GAIA/Vertex base models display_model_id = "" if EXPERIMENTAL_MARKER in base_model_id_for_openai: display_model_id = f"{base_model_id_for_openai}{OPENAI_DIRECT_SUFFIX}" else: display_model_id = f"{PAY_PREFIX}{base_model_id_for_openai}{OPENAI_DIRECT_SUFFIX}" # Check if already added (e.g. if remote config somehow already listed it or added as a base model) if display_model_id and not any(m['id'] == display_model_id for m in dynamic_models_data): dynamic_models_data.append({ "id": display_model_id, "object": "model", "created": current_time, "owned_by": "google", "permission": [], "root": base_model_id_for_openai, "parent": None }) # final_models_data_map = {m["id"]: m for m in dynamic_models_data} # model_list = list(final_models_data_map.values()) # model_list.sort() return {"object": "list", "data": sorted(dynamic_models_data, key=lambda x: x['id'])}