feat: Implement LLM configuration validation in create and update routes

- Added `validate_llm_config` function to `llm_service.py` for validating LLM configurations via test API calls.
- Integrated validation in `create_llm_config` and `update_llm_config` routes in `llm_config_routes.py`, raising HTTP exceptions for invalid configurations.
- Enhanced error handling to provide detailed feedback on configuration issues.

surfsense_backend/app/routes/llm_config_routes.py

@@ -12,6 +12,7 @@ from app.db import (
     get_async_session,
 )
 from app.schemas import LLMConfigCreate, LLMConfigRead, LLMConfigUpdate
+from app.services.llm_service import validate_llm_config
 from app.users import current_active_user
 
 router = APIRouter()
@@ -98,6 +99,22 @@ async def create_llm_config(
         # Verify user has access to the search space
         await check_search_space_access(session, llm_config.search_space_id, user)
 
+        # Validate the LLM configuration by making a test API call
+        is_valid, error_message = await validate_llm_config(
+            provider=llm_config.provider.value,
+            model_name=llm_config.model_name,
+            api_key=llm_config.api_key,
+            api_base=llm_config.api_base,
+            custom_provider=llm_config.custom_provider,
+            litellm_params=llm_config.litellm_params,
+        )
+
+        if not is_valid:
+            raise HTTPException(
+                status_code=400,
+                detail=f"Invalid LLM configuration: {error_message}",
+            )
+
         db_llm_config = LLMConfig(**llm_config.model_dump())
         session.add(db_llm_config)
         await session.commit()
@@ -192,6 +209,39 @@ async def update_llm_config(
 
         update_data = llm_config_update.model_dump(exclude_unset=True)
 
+        # Apply updates to a temporary copy for validation
+        temp_config = {
+            "provider": update_data.get("provider", db_llm_config.provider).value
+            if "provider" in update_data
+            else db_llm_config.provider.value,
+            "model_name": update_data.get("model_name", db_llm_config.model_name),
+            "api_key": update_data.get("api_key", db_llm_config.api_key),
+            "api_base": update_data.get("api_base", db_llm_config.api_base),
+            "custom_provider": update_data.get(
+                "custom_provider", db_llm_config.custom_provider
+            ),
+            "litellm_params": update_data.get(
+                "litellm_params", db_llm_config.litellm_params
+            ),
+        }
+
+        # Validate the updated configuration
+        is_valid, error_message = await validate_llm_config(
+            provider=temp_config["provider"],
+            model_name=temp_config["model_name"],
+            api_key=temp_config["api_key"],
+            api_base=temp_config["api_base"],
+            custom_provider=temp_config["custom_provider"],
+            litellm_params=temp_config["litellm_params"],
+        )
+
+        if not is_valid:
+            raise HTTPException(
+                status_code=400,
+                detail=f"Invalid LLM configuration: {error_message}",
+            )
+
+        # Apply updates to the database object
         for key, value in update_data.items():
             setattr(db_llm_config, key, value)
 

surfsense_backend/app/services/llm_service.py

@@ -1,6 +1,7 @@
 import logging
 
 import litellm
+from langchain_core.messages import HumanMessage
 from langchain_litellm import ChatLiteLLM
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy.future import select
@@ -19,6 +20,93 @@ class LLMRole:
     STRATEGIC = "strategic"
 
 
+async def validate_llm_config(
+    provider: str,
+    model_name: str,
+    api_key: str,
+    api_base: str | None = None,
+    custom_provider: str | None = None,
+    litellm_params: dict | None = None,
+) -> tuple[bool, str]:
+    """
+    Validate an LLM configuration by attempting to make a test API call.
+
+    Args:
+        provider: LLM provider (e.g., 'OPENAI', 'ANTHROPIC')
+        model_name: Model identifier
+        api_key: API key for the provider
+        api_base: Optional custom API base URL
+        custom_provider: Optional custom provider string
+        litellm_params: Optional additional litellm parameters
+
+    Returns:
+        Tuple of (is_valid, error_message)
+        - is_valid: True if config works, False otherwise
+        - error_message: Empty string if valid, error description if invalid
+    """
+    try:
+        # Build the model string for litellm
+        if custom_provider:
+            model_string = f"{custom_provider}/{model_name}"
+        else:
+            # Map provider enum to litellm format
+            provider_map = {
+                "OPENAI": "openai",
+                "ANTHROPIC": "anthropic",
+                "GROQ": "groq",
+                "COHERE": "cohere",
+                "GOOGLE": "gemini",
+                "OLLAMA": "ollama",
+                "MISTRAL": "mistral",
+                "AZURE_OPENAI": "azure",
+                "OPENROUTER": "openrouter",
+                "COMETAPI": "cometapi",
+                # Chinese LLM providers (OpenAI-compatible)
+                "DEEPSEEK": "openai",
+                "ALIBABA_QWEN": "openai",
+                "MOONSHOT": "openai",
+                "ZHIPU": "openai",
+            }
+            provider_prefix = provider_map.get(provider, provider.lower())
+            model_string = f"{provider_prefix}/{model_name}"
+
+        # Create ChatLiteLLM instance
+        litellm_kwargs = {
+            "model": model_string,
+            "api_key": api_key,
+            "timeout": 30,  # Set a timeout for validation
+        }
+
+        # Add optional parameters
+        if api_base:
+            litellm_kwargs["api_base"] = api_base
+
+        # Add any additional litellm parameters
+        if litellm_params:
+            litellm_kwargs.update(litellm_params)
+
+        llm = ChatLiteLLM(**litellm_kwargs)
+
+        # Make a simple test call
+        test_message = HumanMessage(content="Hello")
+        response = await llm.ainvoke([test_message])
+
+        # If we got here without exception, the config is valid
+        if response and response.content:
+            logger.info(f"Successfully validated LLM config for model: {model_string}")
+            return True, ""
+        else:
+            logger.warning(
+                f"LLM config validation returned empty response for model: {model_string}"
+            )
+            return False, "LLM returned an empty response"
+
+    except Exception as e:
+        error_msg = f"Failed to validate LLM configuration: {e!s}"
+        logger.error(error_msg)
+        return False, error_msg
+
+
 async def get_user_llm_instance(
     session: AsyncSession, user_id: str, search_space_id: int, role: str
 ) -> ChatLiteLLM | None:

surfsense_backend/app/tasks/document_processors/file_processors.py

@@ -898,7 +898,7 @@ async def process_file_in_background(
                 # Suppress both Python warnings and logging warnings from pdfminer
                 pdfminer_logger = getLogger("pdfminer")
                 original_level = pdfminer_logger.level
-                
+
                 with warnings.catch_warnings():
                     warnings.filterwarnings(
                         "ignore", category=UserWarning, module="pdfminer"
@@ -907,16 +907,16 @@ async def process_file_in_background(
                         "ignore",
                         message=".*Cannot set gray non-stroke color.*",
                     )
-                    warnings.filterwarnings(
-                        "ignore", message=".*invalid float value.*"
-                    )
-                    
+                    warnings.filterwarnings("ignore", message=".*invalid float value.*")
+
                     # Temporarily suppress pdfminer logging warnings
                     pdfminer_logger.setLevel(ERROR)
-                    
+
                     try:
                         # Process the document
-                        result = await docling_service.process_document(file_path, filename)
+                        result = await docling_service.process_document(
+                            file_path, filename
+                        )
                     finally:
                         # Restore original logging level
                         pdfminer_logger.setLevel(original_level)

surfsense_backend/app/tasks/document_processors/url_crawler.py

@@ -73,7 +73,7 @@ async def add_crawled_url_document(
         )
 
         use_firecrawl = bool(config.FIRECRAWL_API_KEY)
-        
+
         if use_firecrawl:
             # Use Firecrawl SDK directly
             firecrawl_app = AsyncFirecrawlApp(api_key=config.FIRECRAWL_API_KEY)
@@ -84,40 +84,50 @@ async def add_crawled_url_document(
         await task_logger.log_task_progress(
             log_entry,
             f"Crawling URL content: {url}",
-            {"stage": "crawling", "crawler_type": "AsyncFirecrawlApp" if use_firecrawl else "AsyncChromiumLoader"},
+            {
+                "stage": "crawling",
+                "crawler_type": "AsyncFirecrawlApp"
+                if use_firecrawl
+                else "AsyncChromiumLoader",
+            },
         )
 
         if use_firecrawl:
             # Use async Firecrawl SDK with v1 API - properly awaited
             scrape_result = await firecrawl_app.scrape_url(
-                url=url,
-                formats=['markdown']
+                url=url, formats=["markdown"]
             )
-            
+
             # scrape_result is a Pydantic ScrapeResponse object
             # Access attributes directly
             if scrape_result and scrape_result.success:
                 # Extract markdown content
-                markdown_content = scrape_result.markdown or ''
-                
+                markdown_content = scrape_result.markdown or ""
+
                 # Extract metadata - this is a DICT
                 metadata = scrape_result.metadata if scrape_result.metadata else {}
-                
+
                 # Convert to LangChain Document format
-                url_crawled = [LangchainDocument(
-                    page_content=markdown_content,
-                    metadata={
-                        'source': url,
-                        'title': metadata.get('title', url),
-                        'description': metadata.get('description', ''),
-                        'language': metadata.get('language', ''),
-                        'sourceURL': metadata.get('sourceURL', url),
-                        **metadata  # Include all other metadata fields
-                    }
-                )]
+                url_crawled = [
+                    LangchainDocument(
+                        page_content=markdown_content,
+                        metadata={
+                            "source": url,
+                            "title": metadata.get("title", url),
+                            "description": metadata.get("description", ""),
+                            "language": metadata.get("language", ""),
+                            "sourceURL": metadata.get("sourceURL", url),
+                            **metadata,  # Include all other metadata fields
+                        },
+                    )
+                ]
                 content_in_markdown = url_crawled[0].page_content
             else:
-                error_msg = scrape_result.error if scrape_result and hasattr(scrape_result, 'error') else "Unknown error"
+                error_msg = (
+                    scrape_result.error
+                    if scrape_result and hasattr(scrape_result, "error")
+                    else "Unknown error"
+                )
                 raise ValueError(f"Firecrawl failed to scrape URL: {error_msg}")
         else:
             # Use AsyncChromiumLoader as fallback
@@ -249,7 +259,9 @@ async def add_crawled_url_document(
                 {"stage": "document_update", "chunks_count": len(chunks)},
             )
 
-            existing_document.title = url_crawled[0].metadata.get('title', url_crawled[0].metadata.get('source', url))
+            existing_document.title = url_crawled[0].metadata.get(
+                "title", url_crawled[0].metadata.get("source", url)
+            )
             existing_document.content = summary_content
             existing_document.content_hash = content_hash
             existing_document.embedding = summary_embedding
@@ -267,7 +279,9 @@ async def add_crawled_url_document(
 
             document = Document(
                 search_space_id=search_space_id,
-                title=url_crawled[0].metadata.get('title', url_crawled[0].metadata.get('source', url)),
+                title=url_crawled[0].metadata.get(
+                    "title", url_crawled[0].metadata.get("source", url)
+                ),
                 document_type=DocumentType.CRAWLED_URL,
                 document_metadata=url_crawled[0].metadata,
                 content=summary_content,

surfsense_web/app/dashboard/[search_space_id]/layout.tsx

@@ -49,10 +49,10 @@ export default function DashboardLayout({
 					title: "Upload Documents",
 					url: `/dashboard/${search_space_id}/documents/upload`,
 				},
-				{
-				  title: "Add Webpages",
-				  url: `/dashboard/${search_space_id}/documents/webpage`,
-				},
+				// {
+				//   title: "Add Webpages",
+				//   url: `/dashboard/${search_space_id}/documents/webpage`,
+				// },
 				{
 					title: "Add Youtube Videos",
 					url: `/dashboard/${search_space_id}/documents/youtube`,

surfsense_web/app/dashboard/[search_space_id]/researcher/[[...chat_id]]/page.tsx

@@ -5,7 +5,9 @@ import { useParams, useRouter } from "next/navigation";
 import { useEffect, useMemo } from "react";
 import ChatInterface from "@/components/chat/ChatInterface";
 import { useChatAPI, useChatState } from "@/hooks/use-chat";
+import { useDocumentTypes } from "@/hooks/use-document-types";
 import type { Document } from "@/hooks/use-documents";
+import { useSearchSourceConnectors } from "@/hooks/use-search-source-connectors";
 
 export default function ResearcherPage() {
 	const { search_space_id, chat_id } = useParams();
@@ -35,6 +37,19 @@ export default function ResearcherPage() {
 		search_space_id: search_space_id as string,
 	});
 
+	// Fetch all available sources (document types + live search connectors)
+	const { documentTypes } = useDocumentTypes(Number(search_space_id));
+	const { connectors: searchConnectors } = useSearchSourceConnectors(
+		false,
+		Number(search_space_id)
+	);
+
+	// Filter for non-indexable connectors (live search)
+	const liveSearchConnectors = useMemo(
+		() => searchConnectors.filter((connector) => !connector.is_indexable),
+		[searchConnectors]
+	);
+
 	// Memoize document IDs to prevent infinite re-renders
 	const documentIds = useMemo(() => {
 		return selectedDocuments.map((doc) => doc.id);
@@ -135,6 +150,27 @@ export default function ResearcherPage() {
 		}
 	}, [chatIdParam, search_space_id, setSelectedDocuments, setSelectedConnectors, setSearchMode]);
 
+	// Set all sources as default for new chats
+	useEffect(() => {
+		if (isNewChat && selectedConnectors.length === 0 && documentTypes.length > 0) {
+			// Combine all document types and live search connectors
+			const allSourceTypes = [
+				...documentTypes.map((dt) => dt.type),
+				...liveSearchConnectors.map((c) => c.connector_type),
+			];
+
+			if (allSourceTypes.length > 0) {
+				setSelectedConnectors(allSourceTypes);
+			}
+		}
+	}, [
+		isNewChat,
+		documentTypes,
+		liveSearchConnectors,
+		selectedConnectors.length,
+		setSelectedConnectors,
+	]);
+
 	const loadChatData = async (chatId: string) => {
 		try {
 			const chatData = await fetchChatDetails(chatId);

surfsense_web/components/chat/ChatInputGroup.tsx

@@ -115,18 +115,19 @@ const ConnectorSelector = React.memo(
 		const { search_space_id } = useParams();
 		const [isOpen, setIsOpen] = useState(false);
 
+		// Fetch immediately (not lazy) so the button can show the correct count
 		const { documentTypes, isLoading, isLoaded, fetchDocumentTypes } = useDocumentTypes(
 			Number(search_space_id),
-			true
+			false
 		);
 
-		// Fetch live search connectors (non-indexable)
+		// Fetch live search connectors immediately (non-indexable)
 		const {
 			connectors: searchConnectors,
 			isLoading: connectorsLoading,
 			isLoaded: connectorsLoaded,
 			fetchConnectors,
-		} = useSearchSourceConnectors(true, Number(search_space_id));
+		} = useSearchSourceConnectors(false, Number(search_space_id));
 
 		// Filter for non-indexable connectors (live search)
 		const liveSearchConnectors = React.useMemo(
@@ -134,18 +135,10 @@ const ConnectorSelector = React.memo(
 			[searchConnectors]
 		);
 
-		const handleOpenChange = useCallback(
-			(open: boolean) => {
-				setIsOpen(open);
-				if (open && !isLoaded) {
-					fetchDocumentTypes(Number(search_space_id));
-				}
-				if (open && !connectorsLoaded) {
-					fetchConnectors(Number(search_space_id));
-				}
-			},
-			[fetchDocumentTypes, isLoaded, fetchConnectors, connectorsLoaded, search_space_id]
-		);
+		const handleOpenChange = useCallback((open: boolean) => {
+			setIsOpen(open);
+			// Data is already loaded on mount, no need to fetch again
+		}, []);
 
 		const handleConnectorToggle = useCallback(
 			(connectorType: string) => {

surfsense_web/components/sidebar/app-sidebar.tsx

@@ -77,10 +77,10 @@ const defaultData = {
 					title: "Upload Documents",
 					url: "#",
 				},
-				{
-				  title: "Add Webpages",
-				  url: "#",
-				},
+				// {
+				//   title: "Add Webpages",
+				//   url: "#",
+				// },
 				{
 					title: "Manage Documents",
 					url: "#",

surfsense_web/hooks/use-github-stars.ts

@@ -47,6 +47,8 @@ export const useGithubStars = () => {
 		error,
 		compactFormat: Intl.NumberFormat("en-US", {
 			notation: "compact",
+			maximumFractionDigits: 1,
+			minimumFractionDigits: 1,
 		}).format(stars || 0),
 	};
 };