Add tenant-aware provider config resolver across LLM facades

backend/services/llm_providers/main_text_generation.py

@@ -10,10 +10,10 @@ from typing import Optional, Dict, Any, List
 from datetime import datetime
 from loguru import logger
 from fastapi import HTTPException
-from ..onboarding.api_key_manager import APIKeyManager
 
 from .gemini_provider import gemini_text_response, gemini_structured_json_response
 from .huggingface_provider import huggingface_text_response, huggingface_structured_json_response
+from .tenant_provider_config import tenant_provider_config_resolver
 
 
 def llm_text_gen(
@@ -53,14 +53,17 @@ def llm_text_gen(
         frequency_penalty = 0.0
         presence_penalty = 0.0
         
-        # Check for GPT_PROVIDER environment variable
-        env_provider = os.getenv('GPT_PROVIDER', '').lower()
-        if env_provider in ['gemini', 'google']:
+        provider_cfg = tenant_provider_config_resolver.resolve(
+            modality="text",
+            user_id=user_id,
+        )
+        selected_provider = (provider_cfg.selected_providers or [None])[0]
+        if selected_provider in ["gemini", "google"]:
             gpt_provider = "google"
-            model = "gemini-2.0-flash-001"
-        elif env_provider in ['hf_response_api', 'huggingface', 'hf']:
+            model = provider_cfg.model_policy.get("default_model") or "gemini-2.0-flash-001"
+        elif selected_provider == "huggingface":
             gpt_provider = "huggingface"
-            model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
+            model = provider_cfg.model_policy.get("default_model") or "mistralai/Mistral-7B-Instruct-v0.3:groq"
         
         # Default blog characteristics
         blog_tone = "Professional"
@@ -70,38 +73,26 @@ def llm_text_gen(
         blog_output_format = "markdown"
         blog_length = 2000
         
-        # Check which providers have API keys available using APIKeyManager
-        api_key_manager = APIKeyManager()
         available_providers = []
-        if api_key_manager.get_api_key("gemini"):
-            available_providers.append("google")
-        if api_key_manager.get_api_key("hf_token"):
-            available_providers.append("huggingface")
-        
-        # If no environment variable set, auto-detect based on available keys
-        if not env_provider:
-            # Prefer Google Gemini if available, otherwise use Hugging Face
-            if "google" in available_providers:
-                gpt_provider = "google"
-                model = "gemini-2.0-flash-001"
-            elif "huggingface" in available_providers:
-                gpt_provider = "huggingface"
-                model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
+        for provider in ("google", "huggingface"):
+            if get_api_key(provider, user_id=user_id):
+                available_providers.append(provider)
+
+        if gpt_provider not in available_providers:
+            logger.warning(f"[llm_text_gen] Provider {gpt_provider} unavailable for user {user_id}, falling back.")
+            if available_providers:
+                gpt_provider = available_providers[0]
             else:
                 logger.error("[llm_text_gen] No API keys found for supported providers.")
-                raise RuntimeError("No LLM API keys configured. Configure GEMINI_API_KEY or HF_TOKEN to enable AI responses.")
-        else:
-            # Environment variable was set, validate it's supported
-            if gpt_provider not in available_providers:
-                logger.warning(f"[llm_text_gen] Provider {gpt_provider} not available, falling back to available providers")
-                if "google" in available_providers:
-                    gpt_provider = "google"
-                    model = "gemini-2.0-flash-001"
-                elif "huggingface" in available_providers:
-                    gpt_provider = "huggingface"
-                    model = "mistralai/Mistral-7B-Instruct-v0.3:groq"
-                else:
-                    raise RuntimeError("No supported providers available.")
+                raise RuntimeError("No LLM API keys configured for tenant or environment defaults.")
+
+        # Ensure downstream provider clients (currently env-based) receive resolved key
+        resolved_key = get_api_key(gpt_provider, user_id=user_id)
+        if gpt_provider == "google" and resolved_key:
+            os.environ["GEMINI_API_KEY"] = resolved_key
+            os.environ.setdefault("GOOGLE_API_KEY", resolved_key)
+        elif gpt_provider == "huggingface" and resolved_key:
+            os.environ["HF_TOKEN"] = resolved_key
 
         if gpt_provider == "huggingface" and preferred_hf_models:
             model = preferred_hf_models[0]
@@ -391,17 +382,16 @@ def check_gpt_provider(gpt_provider: str) -> bool:
     supported_providers = ["google", "huggingface"]
     return gpt_provider in supported_providers
 
-def get_api_key(gpt_provider: str) -> Optional[str]:
+def get_api_key(gpt_provider: str, user_id: Optional[str] = None) -> Optional[str]:
     """Get API key for the specified provider."""
     try:
-        api_key_manager = APIKeyManager()
         provider_mapping = {
             "google": "gemini",
-            "huggingface": "hf_token"
+            "huggingface": "huggingface"
         }
-        
         mapped_provider = provider_mapping.get(gpt_provider, gpt_provider)
-        return api_key_manager.get_api_key(mapped_provider)
+        key, _source = tenant_provider_config_resolver.resolve_provider_key(mapped_provider, user_id=user_id)
+        return key
     except Exception as e:
         logger.error(f"[get_api_key] Error getting API key for {gpt_provider}: {str(e)}")
         return None