diff --git a/surfsense_backend/.env.example b/surfsense_backend/.env.example index c4facc84d..9aa4b0b34 100644 --- a/surfsense_backend/.env.example +++ b/surfsense_backend/.env.example @@ -9,6 +9,8 @@ CELERY_TASK_DEFAULT_QUEUE=surfsense # Redis for app-level features (heartbeats, podcast markers) # Defaults to CELERY_BROKER_URL when not set REDIS_APP_URL=redis://localhost:6379/0 +# Optional: TTL in seconds for connector indexing lock key +# CONNECTOR_INDEXING_LOCK_TTL_SECONDS=28800 #Electric(for migrations only) ELECTRIC_DB_USER=electric diff --git a/surfsense_backend/alembic/versions/96_add_shared_memories_table.py b/surfsense_backend/alembic/versions/96_add_shared_memories_table.py new file mode 100644 index 000000000..4455d4ead --- /dev/null +++ b/surfsense_backend/alembic/versions/96_add_shared_memories_table.py @@ -0,0 +1,77 @@ +"""Add shared_memories table (SUR-152).""" + +from collections.abc import Sequence + +from alembic import op +from app.config import config + +revision: str = "96" +down_revision: str | None = "95" +branch_labels: str | Sequence[str] | None = None +depends_on: str | Sequence[str] | None = None + +EMBEDDING_DIM = config.embedding_model_instance.dimension + + +def upgrade() -> None: + op.execute( + f""" + DO $$ + BEGIN + IF NOT EXISTS ( + SELECT FROM information_schema.tables + WHERE table_name = 'shared_memories' + ) THEN + CREATE TABLE shared_memories ( + id SERIAL PRIMARY KEY, + created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(), + updated_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(), + search_space_id INTEGER NOT NULL REFERENCES searchspaces(id) ON DELETE CASCADE, + created_by_id UUID NOT NULL REFERENCES "user"(id) ON DELETE CASCADE, + memory_text TEXT NOT NULL, + category memorycategory NOT NULL DEFAULT 'fact', + embedding vector({EMBEDDING_DIM}) + ); + END IF; + END$$; + """ + ) + op.execute( + """ + DO $$ + BEGIN + IF NOT EXISTS ( + SELECT 1 FROM pg_indexes + WHERE tablename = 'shared_memories' AND indexname = 'ix_shared_memories_search_space_id' + ) THEN + CREATE INDEX ix_shared_memories_search_space_id ON shared_memories(search_space_id); + END IF; + IF NOT EXISTS ( + SELECT 1 FROM pg_indexes + WHERE tablename = 'shared_memories' AND indexname = 'ix_shared_memories_updated_at' + ) THEN + CREATE INDEX ix_shared_memories_updated_at ON shared_memories(updated_at); + END IF; + IF NOT EXISTS ( + SELECT 1 FROM pg_indexes + WHERE tablename = 'shared_memories' AND indexname = 'ix_shared_memories_created_by_id' + ) THEN + CREATE INDEX ix_shared_memories_created_by_id ON shared_memories(created_by_id); + END IF; + END$$; + """ + ) + op.execute( + """ + CREATE INDEX IF NOT EXISTS shared_memories_vector_index + ON shared_memories USING hnsw (embedding public.vector_cosine_ops); + """ + ) + + +def downgrade() -> None: + op.execute("DROP INDEX IF EXISTS shared_memories_vector_index;") + op.execute("DROP INDEX IF EXISTS ix_shared_memories_created_by_id;") + op.execute("DROP INDEX IF EXISTS ix_shared_memories_updated_at;") + op.execute("DROP INDEX IF EXISTS ix_shared_memories_search_space_id;") + op.execute("DROP TABLE IF EXISTS shared_memories CASCADE;") diff --git a/surfsense_backend/alembic/versions/97_add_github_models_to_litellmprovider_enum.py b/surfsense_backend/alembic/versions/97_add_github_models_to_litellmprovider_enum.py new file mode 100644 index 000000000..a91cbd3c9 --- /dev/null +++ b/surfsense_backend/alembic/versions/97_add_github_models_to_litellmprovider_enum.py @@ -0,0 +1,23 @@ +"""Add GITHUB_MODELS to LiteLLMProvider enum + +Revision ID: 97 +Revises: 96 +""" + +from collections.abc import Sequence + +from alembic import op + +revision: str = "97" +down_revision: str | None = "96" +branch_labels: str | Sequence[str] | None = None +depends_on: str | Sequence[str] | None = None + + +def upgrade() -> None: + op.execute("COMMIT") + op.execute("ALTER TYPE litellmprovider ADD VALUE IF NOT EXISTS 'GITHUB_MODELS'") + + +def downgrade() -> None: + pass diff --git a/surfsense_backend/app/agents/new_chat/chat_deepagent.py b/surfsense_backend/app/agents/new_chat/chat_deepagent.py index 9da6ea3c2..d58a0fadb 100644 --- a/surfsense_backend/app/agents/new_chat/chat_deepagent.py +++ b/surfsense_backend/app/agents/new_chat/chat_deepagent.py @@ -22,6 +22,7 @@ from app.agents.new_chat.system_prompt import ( build_surfsense_system_prompt, ) from app.agents.new_chat.tools.registry import build_tools_async +from app.db import ChatVisibility from app.services.connector_service import ConnectorService # ============================================================================= @@ -126,6 +127,7 @@ async def create_surfsense_deep_agent( disabled_tools: list[str] | None = None, additional_tools: Sequence[BaseTool] | None = None, firecrawl_api_key: str | None = None, + thread_visibility: ChatVisibility | None = None, ): """ Create a SurfSense deep agent with configurable tools and prompts. @@ -228,14 +230,15 @@ async def create_surfsense_deep_agent( logging.warning(f"Failed to discover available connectors/document types: {e}") # Build dependencies dict for the tools registry + visibility = thread_visibility or ChatVisibility.PRIVATE dependencies = { "search_space_id": search_space_id, "db_session": db_session, "connector_service": connector_service, "firecrawl_api_key": firecrawl_api_key, - "user_id": user_id, # Required for memory tools - "thread_id": thread_id, # For podcast tool - # Dynamic connector/document type discovery for knowledge base tool + "user_id": user_id, + "thread_id": thread_id, + "thread_visibility": visibility, "available_connectors": available_connectors, "available_document_types": available_document_types, } @@ -255,10 +258,12 @@ async def create_surfsense_deep_agent( custom_system_instructions=agent_config.system_instructions, use_default_system_instructions=agent_config.use_default_system_instructions, citations_enabled=agent_config.citations_enabled, + thread_visibility=thread_visibility, ) else: - # Use default prompt (with citations enabled) - system_prompt = build_surfsense_system_prompt() + system_prompt = build_surfsense_system_prompt( + thread_visibility=thread_visibility, + ) # Create the deep agent with system prompt and checkpointer # Note: TodoListMiddleware (write_todos) is included by default in create_deep_agent diff --git a/surfsense_backend/app/agents/new_chat/llm_config.py b/surfsense_backend/app/agents/new_chat/llm_config.py index 8339e9eff..bf16b2fe9 100644 --- a/surfsense_backend/app/agents/new_chat/llm_config.py +++ b/surfsense_backend/app/agents/new_chat/llm_config.py @@ -45,6 +45,7 @@ PROVIDER_MAP = { "ALIBABA_QWEN": "openai", "MOONSHOT": "openai", "ZHIPU": "openai", + "GITHUB_MODELS": "github", "REPLICATE": "replicate", "PERPLEXITY": "perplexity", "ANYSCALE": "anyscale", diff --git a/surfsense_backend/app/agents/new_chat/system_prompt.py b/surfsense_backend/app/agents/new_chat/system_prompt.py index 01c762197..a3520dad6 100644 --- a/surfsense_backend/app/agents/new_chat/system_prompt.py +++ b/surfsense_backend/app/agents/new_chat/system_prompt.py @@ -12,6 +12,8 @@ The prompt is composed of three parts: from datetime import UTC, datetime +from app.db import ChatVisibility + # Default system instructions - can be overridden via NewLLMConfig.system_instructions SURFSENSE_SYSTEM_INSTRUCTIONS = """ @@ -22,7 +24,34 @@ Today's date (UTC): {resolved_today} """ -SURFSENSE_TOOLS_INSTRUCTIONS = """ +# Default system instructions for shared (team) threads: team context + message format for attribution +_SYSTEM_INSTRUCTIONS_SHARED = """ + +You are SurfSense, a reasoning and acting AI agent designed to answer questions in this team space using the team's shared knowledge base. + +In this team thread, each message is prefixed with **[DisplayName of the author]**. Use this to attribute and reference the author of anything in the discussion (who asked a question, made a suggestion, or contributed an idea) and to cite who said what in your answers. + +Today's date (UTC): {resolved_today} + + +""" + + +def _get_system_instructions( + thread_visibility: ChatVisibility | None = None, today: datetime | None = None +) -> str: + """Build system instructions based on thread visibility (private vs shared).""" + + resolved_today = (today or datetime.now(UTC)).astimezone(UTC).date().isoformat() + visibility = thread_visibility or ChatVisibility.PRIVATE + if visibility == ChatVisibility.SEARCH_SPACE: + return _SYSTEM_INSTRUCTIONS_SHARED.format(resolved_today=resolved_today) + else: + return SURFSENSE_SYSTEM_INSTRUCTIONS.format(resolved_today=resolved_today) + + +# Tools 0-6 (common to both private and shared prompts) +_TOOLS_INSTRUCTIONS_COMMON = """ You have access to the following tools: @@ -138,7 +167,11 @@ You have access to the following tools: * Prioritize showing: diagrams, charts, infographics, key illustrations, or images that help explain the content. * Don't show every image - just the most relevant 1-3 images that enhance understanding. -7. save_memory: Save facts, preferences, or context about the user for personalized responses. +""" + +# Private (user) memory: tools 7-8 + memory-specific examples +_TOOLS_INSTRUCTIONS_MEMORY_PRIVATE = """ +7. save_memory: Save facts, preferences, or context for personalized responses. - Use this when the user explicitly or implicitly shares information worth remembering. - Trigger scenarios: * User says "remember this", "keep this in mind", "note that", or similar @@ -178,6 +211,75 @@ You have access to the following tools: stating "Based on your memory..." - integrate the context seamlessly. +- User: "Remember that I prefer TypeScript over JavaScript" + - Call: `save_memory(content="User prefers TypeScript over JavaScript for development", category="preference")` + +- User: "I'm a data scientist working on ML pipelines" + - Call: `save_memory(content="User is a data scientist working on ML pipelines", category="fact")` + +- User: "Always give me code examples in Python" + - Call: `save_memory(content="User wants code examples to be written in Python", category="instruction")` + +- User: "What programming language should I use for this project?" + - First recall: `recall_memory(query="programming language preferences")` + - Then provide a personalized recommendation based on their preferences + +- User: "What do you know about me?" + - Call: `recall_memory(top_k=10)` + - Then summarize the stored memories + +""" + +# Shared (team) memory: tools 7-8 + team memory examples +_TOOLS_INSTRUCTIONS_MEMORY_SHARED = """ +7. save_memory: Save a fact, preference, or context to the team's shared memory for future reference. + - Use this when the user or a team member says "remember this", "keep this in mind", or similar in this shared chat. + - Use when the team agrees on something to remember (e.g., decisions, conventions). + - Someone shares a preference or fact that should be visible to the whole team. + - The saved information will be available in future shared conversations in this space. + - Args: + - content: The fact/preference/context to remember. Phrase it clearly, e.g. "API keys are stored in Vault", "The team prefers weekly demos on Fridays" + - category: Type of memory. One of: + * "preference": Team or workspace preferences + * "fact": Facts the team agreed on (e.g., processes, locations) + * "instruction": Standing instructions for the team + * "context": Current context (e.g., ongoing projects, goals) + - Returns: Confirmation of saved memory; returned context may include who added it (added_by). + - IMPORTANT: Only save information that would be genuinely useful for future team conversations in this space. + +8. recall_memory: Recall relevant team memories for this space to provide contextual responses. + - Use when you need team context to answer (e.g., "where do we store X?", "what did we decide about Y?"). + - Use when someone asks about something the team agreed to remember. + - Use when team preferences or conventions would improve the response. + - Args: + - query: Optional search query to find specific memories. If not provided, returns the most recent memories. + - category: Optional filter by category ("preference", "fact", "instruction", "context") + - top_k: Number of memories to retrieve (default: 5, max: 20) + - Returns: Relevant team memories and formatted context (may include added_by). Integrate naturally without saying "Based on team memory...". + + +- User: "Remember that API keys are stored in Vault" + - Call: `save_memory(content="API keys are stored in Vault", category="fact")` + +- User: "Let's remember that the team prefers weekly demos on Fridays" + - Call: `save_memory(content="The team prefers weekly demos on Fridays", category="preference")` + +- User: "What did we decide about the release date?" + - First recall: `recall_memory(query="release date decision")` + - Then answer based on the team memories + +- User: "Where do we document onboarding?" + - Call: `recall_memory(query="onboarding documentation")` + - Then answer using the recalled team context + +- User: "What have we agreed to remember about our deployment process?" + - Call: `recall_memory(query="deployment process", top_k=10)` + - Then summarize the relevant team memories + +""" + +# Examples shared by both private and shared prompts (knowledge base, docs, podcast, links, images, etc.) +_TOOLS_INSTRUCTIONS_EXAMPLES_COMMON = """ - User: "What time is the team meeting today?" - Call: `search_knowledge_base(query="team meeting time today")` (searches ALL sources - calendar, notes, Obsidian, etc.) - DO NOT limit to just calendar - the info might be in notes! @@ -209,23 +311,6 @@ You have access to the following tools: - User: "What's in my Obsidian vault about project ideas?" - Call: `search_knowledge_base(query="project ideas", connectors_to_search=["OBSIDIAN_CONNECTOR"])` -- User: "Remember that I prefer TypeScript over JavaScript" - - Call: `save_memory(content="User prefers TypeScript over JavaScript for development", category="preference")` - -- User: "I'm a data scientist working on ML pipelines" - - Call: `save_memory(content="User is a data scientist working on ML pipelines", category="fact")` - -- User: "Always give me code examples in Python" - - Call: `save_memory(content="User wants code examples to be written in Python", category="instruction")` - -- User: "What programming language should I use for this project?" - - First recall: `recall_memory(query="programming language preferences")` - - Then provide a personalized recommendation based on their preferences - -- User: "What do you know about me?" - - Call: `recall_memory(top_k=10)` - - Then summarize the stored memories - - User: "Give me a podcast about AI trends based on what we discussed" - First search for relevant content, then call: `generate_podcast(source_content="Based on our conversation and search results: [detailed summary of chat + search findings]", podcast_title="AI Trends Podcast")` @@ -315,6 +400,31 @@ You have access to the following tools: """ +# Reassemble so existing callers see no change (same full prompt) +SURFSENSE_TOOLS_INSTRUCTIONS = ( + _TOOLS_INSTRUCTIONS_COMMON + + _TOOLS_INSTRUCTIONS_MEMORY_PRIVATE + + _TOOLS_INSTRUCTIONS_EXAMPLES_COMMON +) + + +def _get_tools_instructions(thread_visibility: ChatVisibility | None = None) -> str: + """Build tools instructions based on thread visibility (private vs shared). + + For private chats: use user-focused memory wording and examples. + For shared chats: use team memory wording and examples. + """ + visibility = thread_visibility or ChatVisibility.PRIVATE + memory_block = ( + _TOOLS_INSTRUCTIONS_MEMORY_SHARED + if visibility == ChatVisibility.SEARCH_SPACE + else _TOOLS_INSTRUCTIONS_MEMORY_PRIVATE + ) + return ( + _TOOLS_INSTRUCTIONS_COMMON + memory_block + _TOOLS_INSTRUCTIONS_EXAMPLES_COMMON + ) + + SURFSENSE_CITATION_INSTRUCTIONS = """ CRITICAL CITATION REQUIREMENTS: @@ -413,6 +523,7 @@ Your goal is to provide helpful, informative answers in a clean, readable format def build_surfsense_system_prompt( today: datetime | None = None, + thread_visibility: ChatVisibility | None = None, ) -> str: """ Build the SurfSense system prompt with default settings. @@ -424,17 +535,17 @@ def build_surfsense_system_prompt( Args: today: Optional datetime for today's date (defaults to current UTC date) + thread_visibility: Optional; when provided, used for conditional prompt (e.g. private vs shared memory wording). Defaults to private behavior when None. Returns: Complete system prompt string """ - resolved_today = (today or datetime.now(UTC)).astimezone(UTC).date().isoformat() - return ( - SURFSENSE_SYSTEM_INSTRUCTIONS.format(resolved_today=resolved_today) - + SURFSENSE_TOOLS_INSTRUCTIONS - + SURFSENSE_CITATION_INSTRUCTIONS - ) + visibility = thread_visibility or ChatVisibility.PRIVATE + system_instructions = _get_system_instructions(visibility, today) + tools_instructions = _get_tools_instructions(visibility) + citation_instructions = SURFSENSE_CITATION_INSTRUCTIONS + return system_instructions + tools_instructions + citation_instructions def build_configurable_system_prompt( @@ -442,6 +553,7 @@ def build_configurable_system_prompt( use_default_system_instructions: bool = True, citations_enabled: bool = True, today: datetime | None = None, + thread_visibility: ChatVisibility | None = None, ) -> str: """ Build a configurable SurfSense system prompt based on NewLLMConfig settings. @@ -460,6 +572,7 @@ def build_configurable_system_prompt( citations_enabled: Whether to include citation instructions (True) or anti-citation instructions (False). today: Optional datetime for today's date (defaults to current UTC date) + thread_visibility: Optional; when provided, used for conditional prompt (e.g. private vs shared memory wording). Defaults to private behavior when None. Returns: Complete system prompt string @@ -473,16 +586,14 @@ def build_configurable_system_prompt( resolved_today=resolved_today ) elif use_default_system_instructions: - # Use default instructions - system_instructions = SURFSENSE_SYSTEM_INSTRUCTIONS.format( - resolved_today=resolved_today - ) + visibility = thread_visibility or ChatVisibility.PRIVATE + system_instructions = _get_system_instructions(visibility, today) else: # No system instructions (edge case) system_instructions = "" - # Tools instructions are always included - tools_instructions = SURFSENSE_TOOLS_INSTRUCTIONS + # Tools instructions: conditional on thread_visibility (private vs shared memory wording) + tools_instructions = _get_tools_instructions(thread_visibility) # Citation instructions based on toggle citation_instructions = ( diff --git a/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py b/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py index a11e4ac38..fefd80f04 100644 --- a/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py +++ b/surfsense_backend/app/agents/new_chat/tools/knowledge_base.py @@ -8,6 +8,7 @@ This module provides: - Tool factory for creating search_knowledge_base tools """ +import asyncio import json from datetime import datetime from typing import Any @@ -16,6 +17,7 @@ from langchain_core.tools import StructuredTool from pydantic import BaseModel, Field from sqlalchemy.ext.asyncio import AsyncSession +from app.db import async_session_maker from app.services.connector_service import ConnectorService # ============================================================================= @@ -333,7 +335,7 @@ async def search_knowledge_base_async( Returns: Formatted string with search results """ - all_documents = [] + all_documents: list[dict[str, Any]] = [] # Resolve date range (default last 2 years) from app.agents.new_chat.utils import resolve_date_range @@ -345,323 +347,131 @@ async def search_knowledge_base_async( connectors = _normalize_connectors(connectors_to_search, available_connectors) - for connector in connectors: + connector_specs: dict[str, tuple[str, bool, bool, dict[str, Any]]] = { + "YOUTUBE_VIDEO": ("search_youtube", True, True, {}), + "EXTENSION": ("search_extension", True, True, {}), + "CRAWLED_URL": ("search_crawled_urls", True, True, {}), + "FILE": ("search_files", True, True, {}), + "SLACK_CONNECTOR": ("search_slack", True, True, {}), + "TEAMS_CONNECTOR": ("search_teams", True, True, {}), + "NOTION_CONNECTOR": ("search_notion", True, True, {}), + "GITHUB_CONNECTOR": ("search_github", True, True, {}), + "LINEAR_CONNECTOR": ("search_linear", True, True, {}), + "TAVILY_API": ("search_tavily", False, True, {}), + "SEARXNG_API": ("search_searxng", False, True, {}), + "LINKUP_API": ("search_linkup", False, False, {"mode": "standard"}), + "BAIDU_SEARCH_API": ("search_baidu", False, True, {}), + "DISCORD_CONNECTOR": ("search_discord", True, True, {}), + "JIRA_CONNECTOR": ("search_jira", True, True, {}), + "GOOGLE_CALENDAR_CONNECTOR": ("search_google_calendar", True, True, {}), + "AIRTABLE_CONNECTOR": ("search_airtable", True, True, {}), + "GOOGLE_GMAIL_CONNECTOR": ("search_google_gmail", True, True, {}), + "GOOGLE_DRIVE_FILE": ("search_google_drive", True, True, {}), + "CONFLUENCE_CONNECTOR": ("search_confluence", True, True, {}), + "CLICKUP_CONNECTOR": ("search_clickup", True, True, {}), + "LUMA_CONNECTOR": ("search_luma", True, True, {}), + "ELASTICSEARCH_CONNECTOR": ("search_elasticsearch", True, True, {}), + "NOTE": ("search_notes", True, True, {}), + "BOOKSTACK_CONNECTOR": ("search_bookstack", True, True, {}), + "CIRCLEBACK": ("search_circleback", True, True, {}), + "OBSIDIAN_CONNECTOR": ("search_obsidian", True, True, {}), + # Composio connectors + "COMPOSIO_GOOGLE_DRIVE_CONNECTOR": ( + "search_composio_google_drive", + True, + True, + {}, + ), + "COMPOSIO_GMAIL_CONNECTOR": ("search_composio_gmail", True, True, {}), + "COMPOSIO_GOOGLE_CALENDAR_CONNECTOR": ( + "search_composio_google_calendar", + True, + True, + {}, + ), + } + + # Keep a conservative cap to avoid overloading DB/external services. + max_parallel_searches = 4 + semaphore = asyncio.Semaphore(max_parallel_searches) + + async def _search_one_connector(connector: str) -> list[dict[str, Any]]: + spec = connector_specs.get(connector) + if spec is None: + return [] + + method_name, includes_date_range, includes_top_k, extra_kwargs = spec + kwargs: dict[str, Any] = { + "user_query": query, + "search_space_id": search_space_id, + **extra_kwargs, + } + if includes_top_k: + kwargs["top_k"] = top_k + if includes_date_range: + kwargs["start_date"] = resolved_start_date + kwargs["end_date"] = resolved_end_date + try: - if connector == "YOUTUBE_VIDEO": - _, chunks = await connector_service.search_youtube( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, + # Use isolated session per connector. Shared AsyncSession cannot safely + # run concurrent DB operations. + async with semaphore, async_session_maker() as isolated_session: + isolated_connector_service = ConnectorService( + isolated_session, search_space_id ) - all_documents.extend(chunks) - - elif connector == "EXTENSION": - _, chunks = await connector_service.search_extension( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "CRAWLED_URL": - _, chunks = await connector_service.search_crawled_urls( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "FILE": - _, chunks = await connector_service.search_files( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "SLACK_CONNECTOR": - _, chunks = await connector_service.search_slack( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "TEAMS_CONNECTOR": - _, chunks = await connector_service.search_teams( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "NOTION_CONNECTOR": - _, chunks = await connector_service.search_notion( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "GITHUB_CONNECTOR": - _, chunks = await connector_service.search_github( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "LINEAR_CONNECTOR": - _, chunks = await connector_service.search_linear( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "TAVILY_API": - _, chunks = await connector_service.search_tavily( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - ) - all_documents.extend(chunks) - - elif connector == "SEARXNG_API": - _, chunks = await connector_service.search_searxng( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - ) - all_documents.extend(chunks) - - elif connector == "LINKUP_API": - # Keep behavior aligned with researcher: default "standard" - _, chunks = await connector_service.search_linkup( - user_query=query, - search_space_id=search_space_id, - mode="standard", - ) - all_documents.extend(chunks) - - elif connector == "BAIDU_SEARCH_API": - _, chunks = await connector_service.search_baidu( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - ) - all_documents.extend(chunks) - - elif connector == "DISCORD_CONNECTOR": - _, chunks = await connector_service.search_discord( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "JIRA_CONNECTOR": - _, chunks = await connector_service.search_jira( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "GOOGLE_CALENDAR_CONNECTOR": - _, chunks = await connector_service.search_google_calendar( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "AIRTABLE_CONNECTOR": - _, chunks = await connector_service.search_airtable( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "GOOGLE_GMAIL_CONNECTOR": - _, chunks = await connector_service.search_google_gmail( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "GOOGLE_DRIVE_FILE": - _, chunks = await connector_service.search_google_drive( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "CONFLUENCE_CONNECTOR": - _, chunks = await connector_service.search_confluence( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "CLICKUP_CONNECTOR": - _, chunks = await connector_service.search_clickup( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "LUMA_CONNECTOR": - _, chunks = await connector_service.search_luma( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "ELASTICSEARCH_CONNECTOR": - _, chunks = await connector_service.search_elasticsearch( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "NOTE": - _, chunks = await connector_service.search_notes( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "BOOKSTACK_CONNECTOR": - _, chunks = await connector_service.search_bookstack( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "CIRCLEBACK": - _, chunks = await connector_service.search_circleback( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "OBSIDIAN_CONNECTOR": - _, chunks = await connector_service.search_obsidian( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - # ========================================================= - # Composio Connectors - # ========================================================= - elif connector == "COMPOSIO_GOOGLE_DRIVE_CONNECTOR": - _, chunks = await connector_service.search_composio_google_drive( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "COMPOSIO_GMAIL_CONNECTOR": - _, chunks = await connector_service.search_composio_gmail( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - - elif connector == "COMPOSIO_GOOGLE_CALENDAR_CONNECTOR": - _, chunks = await connector_service.search_composio_google_calendar( - user_query=query, - search_space_id=search_space_id, - top_k=top_k, - start_date=resolved_start_date, - end_date=resolved_end_date, - ) - all_documents.extend(chunks) - + connector_method = getattr(isolated_connector_service, method_name) + _, chunks = await connector_method(**kwargs) + return chunks except Exception as e: print(f"Error searching connector {connector}: {e}") - continue + return [] - # Deduplicate by content hash + connector_results = await asyncio.gather( + *[_search_one_connector(connector) for connector in connectors] + ) + for chunks in connector_results: + all_documents.extend(chunks) + + # Deduplicate primarily by document ID. Only fall back to content hashing + # when a document has no ID. seen_doc_ids: set[Any] = set() - seen_hashes: set[int] = set() + seen_content_hashes: set[int] = set() deduplicated: list[dict[str, Any]] = [] + + def _content_fingerprint(document: dict[str, Any]) -> int | None: + chunks = document.get("chunks") + if isinstance(chunks, list): + chunk_texts = [] + for chunk in chunks: + if not isinstance(chunk, dict): + continue + chunk_content = (chunk.get("content") or "").strip() + if chunk_content: + chunk_texts.append(chunk_content) + if chunk_texts: + return hash("||".join(chunk_texts)) + + flat_content = (document.get("content") or "").strip() + if flat_content: + return hash(flat_content) + return None + for doc in all_documents: doc_id = (doc.get("document", {}) or {}).get("id") - content = (doc.get("content", "") or "").strip() - content_hash = hash(content) - if (doc_id and doc_id in seen_doc_ids) or content_hash in seen_hashes: + if doc_id is not None: + if doc_id in seen_doc_ids: + continue + seen_doc_ids.add(doc_id) + deduplicated.append(doc) continue - if doc_id: - seen_doc_ids.add(doc_id) - seen_hashes.add(content_hash) + content_hash = _content_fingerprint(doc) + if content_hash is not None: + if content_hash in seen_content_hashes: + continue + seen_content_hashes.add(content_hash) + deduplicated.append(doc) return format_documents_for_context(deduplicated) diff --git a/surfsense_backend/app/agents/new_chat/tools/podcast.py b/surfsense_backend/app/agents/new_chat/tools/podcast.py index e6412f4f2..8ac537f9a 100644 --- a/surfsense_backend/app/agents/new_chat/tools/podcast.py +++ b/surfsense_backend/app/agents/new_chat/tools/podcast.py @@ -11,21 +11,18 @@ Duplicate request prevention: - Returns a friendly message if a podcast is already being generated """ -import os from typing import Any import redis from langchain_core.tools import tool from sqlalchemy.ext.asyncio import AsyncSession +from app.config import config from app.db import Podcast, PodcastStatus # Redis connection for tracking active podcast tasks # Defaults to the Celery broker when REDIS_APP_URL is not set -REDIS_URL = os.getenv( - "REDIS_APP_URL", - os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0"), -) +REDIS_URL = config.REDIS_APP_URL _redis_client: redis.Redis | None = None diff --git a/surfsense_backend/app/agents/new_chat/tools/registry.py b/surfsense_backend/app/agents/new_chat/tools/registry.py index 2cf43c973..8092a6104 100644 --- a/surfsense_backend/app/agents/new_chat/tools/registry.py +++ b/surfsense_backend/app/agents/new_chat/tools/registry.py @@ -43,6 +43,8 @@ from typing import Any from langchain_core.tools import BaseTool +from app.db import ChatVisibility + from .display_image import create_display_image_tool from .generate_image import create_generate_image_tool from .knowledge_base import create_search_knowledge_base_tool @@ -51,6 +53,10 @@ from .mcp_tool import load_mcp_tools from .podcast import create_generate_podcast_tool from .scrape_webpage import create_scrape_webpage_tool from .search_surfsense_docs import create_search_surfsense_docs_tool +from .shared_memory import ( + create_recall_shared_memory_tool, + create_save_shared_memory_tool, +) from .user_memory import create_recall_memory_tool, create_save_memory_tool # ============================================================================= @@ -156,29 +162,42 @@ BUILTIN_TOOLS: list[ToolDefinition] = [ requires=["db_session"], ), # ========================================================================= - # USER MEMORY TOOLS - Claude-like memory feature + # USER MEMORY TOOLS - private or team store by thread_visibility # ========================================================================= - # Save memory tool - stores facts/preferences about the user ToolDefinition( name="save_memory", - description="Save facts, preferences, or context about the user for personalized responses", - factory=lambda deps: create_save_memory_tool( - user_id=deps["user_id"], - search_space_id=deps["search_space_id"], - db_session=deps["db_session"], + description="Save facts, preferences, or context for personalized or team responses", + factory=lambda deps: ( + create_save_shared_memory_tool( + search_space_id=deps["search_space_id"], + created_by_id=deps["user_id"], + db_session=deps["db_session"], + ) + if deps["thread_visibility"] == ChatVisibility.SEARCH_SPACE + else create_save_memory_tool( + user_id=deps["user_id"], + search_space_id=deps["search_space_id"], + db_session=deps["db_session"], + ) ), - requires=["user_id", "search_space_id", "db_session"], + requires=["user_id", "search_space_id", "db_session", "thread_visibility"], ), - # Recall memory tool - retrieves relevant user memories ToolDefinition( name="recall_memory", - description="Recall user memories for personalized and contextual responses", - factory=lambda deps: create_recall_memory_tool( - user_id=deps["user_id"], - search_space_id=deps["search_space_id"], - db_session=deps["db_session"], + description="Recall relevant memories (personal or team) for context", + factory=lambda deps: ( + create_recall_shared_memory_tool( + search_space_id=deps["search_space_id"], + db_session=deps["db_session"], + ) + if deps["thread_visibility"] == ChatVisibility.SEARCH_SPACE + else create_recall_memory_tool( + user_id=deps["user_id"], + search_space_id=deps["search_space_id"], + db_session=deps["db_session"], + ) ), - requires=["user_id", "search_space_id", "db_session"], + requires=["user_id", "search_space_id", "db_session", "thread_visibility"], ), # ========================================================================= # ADD YOUR CUSTOM TOOLS BELOW diff --git a/surfsense_backend/app/agents/new_chat/tools/shared_memory.py b/surfsense_backend/app/agents/new_chat/tools/shared_memory.py new file mode 100644 index 000000000..8cd4148ba --- /dev/null +++ b/surfsense_backend/app/agents/new_chat/tools/shared_memory.py @@ -0,0 +1,280 @@ +"""Shared (team) memory backend for search-space-scoped AI context.""" + +import logging +from typing import Any +from uuid import UUID + +from langchain_core.tools import tool +from sqlalchemy import select +from sqlalchemy.ext.asyncio import AsyncSession + +from app.config import config +from app.db import MemoryCategory, SharedMemory, User + +logger = logging.getLogger(__name__) + +DEFAULT_RECALL_TOP_K = 5 +MAX_MEMORIES_PER_SEARCH_SPACE = 250 + + +async def get_shared_memory_count( + db_session: AsyncSession, + search_space_id: int, +) -> int: + result = await db_session.execute( + select(SharedMemory).where(SharedMemory.search_space_id == search_space_id) + ) + return len(result.scalars().all()) + + +async def delete_oldest_shared_memory( + db_session: AsyncSession, + search_space_id: int, +) -> None: + result = await db_session.execute( + select(SharedMemory) + .where(SharedMemory.search_space_id == search_space_id) + .order_by(SharedMemory.updated_at.asc()) + .limit(1) + ) + oldest = result.scalars().first() + if oldest: + await db_session.delete(oldest) + await db_session.commit() + + +def _to_uuid(value: str | UUID) -> UUID: + if isinstance(value, UUID): + return value + return UUID(value) + + +async def save_shared_memory( + db_session: AsyncSession, + search_space_id: int, + created_by_id: str | UUID, + content: str, + category: str = "fact", +) -> dict[str, Any]: + category = category.lower() if category else "fact" + valid = ["preference", "fact", "instruction", "context"] + if category not in valid: + category = "fact" + try: + count = await get_shared_memory_count(db_session, search_space_id) + if count >= MAX_MEMORIES_PER_SEARCH_SPACE: + await delete_oldest_shared_memory(db_session, search_space_id) + embedding = config.embedding_model_instance.embed(content) + row = SharedMemory( + search_space_id=search_space_id, + created_by_id=_to_uuid(created_by_id), + memory_text=content, + category=MemoryCategory(category), + embedding=embedding, + ) + db_session.add(row) + await db_session.commit() + await db_session.refresh(row) + return { + "status": "saved", + "memory_id": row.id, + "memory_text": content, + "category": category, + "message": f"I'll remember: {content}", + } + except Exception as e: + logger.exception("Failed to save shared memory: %s", e) + await db_session.rollback() + return { + "status": "error", + "error": str(e), + "message": "Failed to save memory. Please try again.", + } + + +async def recall_shared_memory( + db_session: AsyncSession, + search_space_id: int, + query: str | None = None, + category: str | None = None, + top_k: int = DEFAULT_RECALL_TOP_K, +) -> dict[str, Any]: + top_k = min(max(top_k, 1), 20) + try: + valid_categories = ["preference", "fact", "instruction", "context"] + stmt = select(SharedMemory).where( + SharedMemory.search_space_id == search_space_id + ) + if category and category in valid_categories: + stmt = stmt.where(SharedMemory.category == MemoryCategory(category)) + if query: + query_embedding = config.embedding_model_instance.embed(query) + stmt = stmt.order_by( + SharedMemory.embedding.op("<=>")(query_embedding) + ).limit(top_k) + else: + stmt = stmt.order_by(SharedMemory.updated_at.desc()).limit(top_k) + result = await db_session.execute(stmt) + rows = result.scalars().all() + memory_list = [ + { + "id": m.id, + "memory_text": m.memory_text, + "category": m.category.value if m.category else "unknown", + "updated_at": m.updated_at.isoformat() if m.updated_at else None, + "created_by_id": str(m.created_by_id) if m.created_by_id else None, + } + for m in rows + ] + created_by_ids = list( + {m["created_by_id"] for m in memory_list if m["created_by_id"]} + ) + created_by_map: dict[str, str] = {} + if created_by_ids: + uuids = [UUID(uid) for uid in created_by_ids] + users_result = await db_session.execute( + select(User).where(User.id.in_(uuids)) + ) + for u in users_result.scalars().all(): + created_by_map[str(u.id)] = u.display_name or "A team member" + formatted_context = format_shared_memories_for_context( + memory_list, created_by_map + ) + return { + "status": "success", + "count": len(memory_list), + "memories": memory_list, + "formatted_context": formatted_context, + } + except Exception as e: + logger.exception("Failed to recall shared memory: %s", e) + await db_session.rollback() + return { + "status": "error", + "error": str(e), + "memories": [], + "formatted_context": "Failed to recall memories.", + } + + +def format_shared_memories_for_context( + memories: list[dict[str, Any]], + created_by_map: dict[str, str] | None = None, +) -> str: + if not memories: + return "No relevant team memories found." + created_by_map = created_by_map or {} + parts = [""] + for memory in memories: + category = memory.get("category", "unknown") + text = memory.get("memory_text", "") + updated = memory.get("updated_at", "") + created_by_id = memory.get("created_by_id") + added_by = ( + created_by_map.get(str(created_by_id), "A team member") + if created_by_id is not None + else "A team member" + ) + parts.append( + f" {text}" + ) + parts.append("") + return "\n".join(parts) + + +def create_save_shared_memory_tool( + search_space_id: int, + created_by_id: str | UUID, + db_session: AsyncSession, +): + """ + Factory function to create the save_memory tool for shared (team) chats. + + Args: + search_space_id: The search space ID + created_by_id: The user ID of the person adding the memory + db_session: Database session for executing queries + + Returns: + A configured tool function for saving team memories + """ + + @tool + async def save_memory( + content: str, + category: str = "fact", + ) -> dict[str, Any]: + """ + Save a fact, preference, or context to the team's shared memory for future reference. + + Use this tool when: + - User or a team member says "remember this", "keep this in mind", or similar in this shared chat + - The team agrees on something to remember (e.g., decisions, conventions, where things live) + - Someone shares a preference or fact that should be visible to the whole team + + The saved information will be available in future shared conversations in this space. + + Args: + content: The fact/preference/context to remember. + Phrase it clearly, e.g., "API keys are stored in Vault", + "The team prefers weekly demos on Fridays" + category: Type of memory. One of: + - "preference": Team or workspace preferences + - "fact": Facts the team agreed on (e.g., processes, locations) + - "instruction": Standing instructions for the team + - "context": Current context (e.g., ongoing projects, goals) + + Returns: + A dictionary with the save status and memory details + """ + return await save_shared_memory( + db_session, search_space_id, created_by_id, content, category + ) + + return save_memory + + +def create_recall_shared_memory_tool( + search_space_id: int, + db_session: AsyncSession, +): + """ + Factory function to create the recall_memory tool for shared (team) chats. + + Args: + search_space_id: The search space ID + db_session: Database session for executing queries + + Returns: + A configured tool function for recalling team memories + """ + + @tool + async def recall_memory( + query: str | None = None, + category: str | None = None, + top_k: int = DEFAULT_RECALL_TOP_K, + ) -> dict[str, Any]: + """ + Recall relevant team memories for this space to provide contextual responses. + + Use this tool when: + - You need team context to answer (e.g., "where do we store X?", "what did we decide about Y?") + - Someone asks about something the team agreed to remember + - Team preferences or conventions would improve the response + + Args: + query: Optional search query to find specific memories. + If not provided, returns the most recent memories. + category: Optional category filter. One of: + "preference", "fact", "instruction", "context" + top_k: Number of memories to retrieve (default: 5, max: 20) + + Returns: + A dictionary containing relevant memories and formatted context + """ + return await recall_shared_memory( + db_session, search_space_id, query, category, top_k + ) + + return recall_memory diff --git a/surfsense_backend/app/app.py b/surfsense_backend/app/app.py index 0f619097e..cdba7c7b7 100644 --- a/surfsense_backend/app/app.py +++ b/surfsense_backend/app/app.py @@ -1,7 +1,17 @@ +import logging +import time +from collections import defaultdict from contextlib import asynccontextmanager +from threading import Lock +import redis from fastapi import Depends, FastAPI, HTTPException, Request, status from fastapi.middleware.cors import CORSMiddleware +from fastapi.responses import JSONResponse +from slowapi import Limiter +from slowapi.errors import RateLimitExceeded +from slowapi.middleware import SlowAPIASGIMiddleware +from slowapi.util import get_remote_address from sqlalchemy.ext.asyncio import AsyncSession from uvicorn.middleware.proxy_headers import ProxyHeadersMiddleware @@ -17,6 +27,147 @@ from app.schemas import UserCreate, UserRead, UserUpdate from app.tasks.surfsense_docs_indexer import seed_surfsense_docs from app.users import SECRET, auth_backend, current_active_user, fastapi_users +rate_limit_logger = logging.getLogger("surfsense.rate_limit") + + +# ============================================================================ +# Rate Limiting Configuration (SlowAPI + Redis) +# ============================================================================ +# Uses the same Redis instance as Celery for zero additional infrastructure. +# Protects auth endpoints from brute force and user enumeration attacks. + +# SlowAPI limiter — provides default rate limits (60/min) for ALL routes +# via the ASGI middleware. This is the general safety net. +limiter = Limiter( + key_func=get_remote_address, + storage_uri=config.REDIS_APP_URL, + default_limits=["60/minute"], +) + + +def _rate_limit_exceeded_handler(request: Request, exc: RateLimitExceeded): + """Custom 429 handler that returns JSON matching our frontend error format.""" + retry_after = exc.detail.split("per")[-1].strip() if exc.detail else "60" + return JSONResponse( + status_code=429, + content={"detail": "RATE_LIMIT_EXCEEDED"}, + headers={"Retry-After": retry_after}, + ) + + +# ============================================================================ +# Auth-Specific Rate Limits (Redis-backed with in-memory fallback) +# ============================================================================ +# Stricter per-IP limits on auth endpoints to prevent: +# - Brute force password attacks +# - User enumeration via REGISTER_USER_ALREADY_EXISTS +# - Email spam via forgot-password +# +# Primary: Redis INCR+EXPIRE (shared across all workers). +# Fallback: In-memory sliding window (per-worker) when Redis is unavailable. +# Same Redis instance as SlowAPI / Celery. +_rate_limit_redis: redis.Redis | None = None + +# In-memory fallback rate limiter (per-worker, used only when Redis is down) +_memory_rate_limits: dict[str, list[float]] = defaultdict(list) +_memory_lock = Lock() + + +def _get_rate_limit_redis() -> redis.Redis: + """Get or create Redis client for auth rate limiting.""" + global _rate_limit_redis + if _rate_limit_redis is None: + _rate_limit_redis = redis.from_url(config.REDIS_APP_URL, decode_responses=True) + return _rate_limit_redis + + +def _check_rate_limit_memory( + client_ip: str, max_requests: int, window_seconds: int, scope: str +): + """ + In-memory fallback rate limiter using a sliding window. + Used only when Redis is unavailable. Per-worker only (not shared), + so effective limit = max_requests x num_workers. + """ + key = f"{scope}:{client_ip}" + now = time.monotonic() + + with _memory_lock: + # Evict timestamps outside the current window + _memory_rate_limits[key] = [ + t for t in _memory_rate_limits[key] if now - t < window_seconds + ] + + if len(_memory_rate_limits[key]) >= max_requests: + rate_limit_logger.warning( + f"Rate limit exceeded (in-memory fallback) on {scope} for IP {client_ip} " + f"({len(_memory_rate_limits[key])}/{max_requests} in {window_seconds}s)" + ) + raise HTTPException( + status_code=429, + detail="RATE_LIMIT_EXCEEDED", + ) + + _memory_rate_limits[key].append(now) + + +def _check_rate_limit( + request: Request, max_requests: int, window_seconds: int, scope: str +): + """ + Check per-IP rate limit using Redis. Raises 429 if exceeded. + Uses atomic INCR + EXPIRE to avoid race conditions. + Falls back to in-memory sliding window if Redis is unavailable. + """ + client_ip = get_remote_address(request) + key = f"surfsense:auth_rate_limit:{scope}:{client_ip}" + + try: + r = _get_rate_limit_redis() + + # Atomic: increment first, then set TTL if this is a new key + pipe = r.pipeline() + pipe.incr(key) + pipe.expire(key, window_seconds) + result = pipe.execute() + except (redis.exceptions.RedisError, OSError) as exc: + # Redis unavailable — fall back to in-memory rate limiting + rate_limit_logger.warning( + f"Redis unavailable for rate limiting ({scope}), " + f"falling back to in-memory limiter for {client_ip}: {exc}" + ) + _check_rate_limit_memory(client_ip, max_requests, window_seconds, scope) + return + + current_count = result[0] # INCR returns the new value + + if current_count > max_requests: + rate_limit_logger.warning( + f"Rate limit exceeded on {scope} for IP {client_ip} " + f"({current_count}/{max_requests} in {window_seconds}s)" + ) + raise HTTPException( + status_code=429, + detail="RATE_LIMIT_EXCEEDED", + ) + + +def rate_limit_login(request: Request): + """5 login attempts per minute per IP.""" + _check_rate_limit(request, max_requests=5, window_seconds=60, scope="login") + + +def rate_limit_register(request: Request): + """3 registration attempts per minute per IP.""" + _check_rate_limit(request, max_requests=3, window_seconds=60, scope="register") + + +def rate_limit_password_reset(request: Request): + """2 password reset attempts per minute per IP.""" + _check_rate_limit( + request, max_requests=2, window_seconds=60, scope="password_reset" + ) + @asynccontextmanager async def lifespan(app: FastAPI): @@ -45,6 +196,14 @@ def registration_allowed(): app = FastAPI(lifespan=lifespan) +# Register rate limiter and custom 429 handler +app.state.limiter = limiter +app.add_exception_handler(RateLimitExceeded, _rate_limit_exceeded_handler) + +# Add SlowAPI ASGI middleware for automatic rate limiting +# This applies default_limits to all routes and enables per-route overrides +app.add_middleware(SlowAPIASGIMiddleware) + # Add ProxyHeaders middleware FIRST to trust proxy headers (e.g., from Cloudflare) # This ensures FastAPI uses HTTPS in redirects when behind a proxy app.add_middleware(ProxyHeadersMiddleware, trusted_hosts="*") @@ -90,18 +249,25 @@ app.add_middleware( ) app.include_router( - fastapi_users.get_auth_router(auth_backend), prefix="/auth/jwt", tags=["auth"] + fastapi_users.get_auth_router(auth_backend), + prefix="/auth/jwt", + tags=["auth"], + dependencies=[Depends(rate_limit_login)], ) app.include_router( fastapi_users.get_register_router(UserRead, UserCreate), prefix="/auth", tags=["auth"], - dependencies=[Depends(registration_allowed)], # blocks registration when disabled + dependencies=[ + Depends(rate_limit_register), + Depends(registration_allowed), # blocks registration when disabled + ], ) app.include_router( fastapi_users.get_reset_password_router(), prefix="/auth", tags=["auth"], + dependencies=[Depends(rate_limit_password_reset)], ) app.include_router( fastapi_users.get_verify_router(UserRead), diff --git a/surfsense_backend/app/config/__init__.py b/surfsense_backend/app/config/__init__.py index e102c414d..68c65a818 100644 --- a/surfsense_backend/app/config/__init__.py +++ b/surfsense_backend/app/config/__init__.py @@ -213,6 +213,17 @@ class Config: # Database DATABASE_URL = os.getenv("DATABASE_URL") + # Celery / Redis + CELERY_BROKER_URL = os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0") + CELERY_RESULT_BACKEND = os.getenv( + "CELERY_RESULT_BACKEND", "redis://localhost:6379/0" + ) + CELERY_TASK_DEFAULT_QUEUE = os.getenv("CELERY_TASK_DEFAULT_QUEUE", "surfsense") + REDIS_APP_URL = os.getenv("REDIS_APP_URL", CELERY_BROKER_URL) + CONNECTOR_INDEXING_LOCK_TTL_SECONDS = int( + os.getenv("CONNECTOR_INDEXING_LOCK_TTL_SECONDS", str(8 * 60 * 60)) + ) + NEXT_FRONTEND_URL = os.getenv("NEXT_FRONTEND_URL") # Backend URL to override the http to https in the OAuth redirect URI BACKEND_URL = os.getenv("BACKEND_URL") diff --git a/surfsense_backend/app/connectors/notion_history.py b/surfsense_backend/app/connectors/notion_history.py index ff8478905..525b0b4c3 100644 --- a/surfsense_backend/app/connectors/notion_history.py +++ b/surfsense_backend/app/connectors/notion_history.py @@ -27,6 +27,12 @@ T = TypeVar("T") MAX_RETRIES = 5 BASE_RETRY_DELAY = 1.0 # seconds MAX_RETRY_DELAY = 60.0 # seconds (Notion's max request timeout) +MAX_RATE_LIMIT_WAIT_SECONDS = float( + getattr(config, "NOTION_MAX_RETRY_AFTER_SECONDS", 30.0) +) +MAX_TOTAL_RETRY_WAIT_SECONDS = float( + getattr(config, "NOTION_MAX_TOTAL_RETRY_WAIT_SECONDS", 120.0) +) # Type alias for retry callback function # Signature: async callback(retry_reason, attempt, max_attempts, wait_seconds) -> None @@ -292,6 +298,7 @@ class NotionHistoryConnector: """ last_exception: APIResponseError | None = None retry_delay = BASE_RETRY_DELAY + total_wait_time = 0.0 for attempt in range(MAX_RETRIES): try: @@ -325,6 +332,15 @@ class NotionHistoryConnector: wait_time = retry_delay else: wait_time = retry_delay + + # Avoid very long worker sleeps from external Retry-After values. + if wait_time > MAX_RATE_LIMIT_WAIT_SECONDS: + logger.warning( + f"Notion Retry-After ({wait_time}s) exceeds cap " + f"({MAX_RATE_LIMIT_WAIT_SECONDS}s). Clamping wait time." + ) + wait_time = MAX_RATE_LIMIT_WAIT_SECONDS + logger.warning( f"Notion API rate limited (429). " f"Waiting {wait_time}s. Attempt {attempt + 1}/{MAX_RETRIES}" @@ -348,6 +364,14 @@ class NotionHistoryConnector: # Notify about retry via callback (for user notifications) # Call before sleeping so user sees the message while we wait + if total_wait_time + wait_time > MAX_TOTAL_RETRY_WAIT_SECONDS: + logger.error( + "Notion API retry budget exceeded " + f"({total_wait_time + wait_time:.1f}s > " + f"{MAX_TOTAL_RETRY_WAIT_SECONDS:.1f}s). Failing fast." + ) + raise + if on_retry: try: await on_retry( @@ -362,6 +386,7 @@ class NotionHistoryConnector: # Wait before retrying await asyncio.sleep(wait_time) + total_wait_time += wait_time # Exponential backoff for next attempt retry_delay = min(retry_delay * 2, MAX_RETRY_DELAY) diff --git a/surfsense_backend/app/db.py b/surfsense_backend/app/db.py index 4f8648616..90c839980 100644 --- a/surfsense_backend/app/db.py +++ b/surfsense_backend/app/db.py @@ -211,6 +211,7 @@ class LiteLLMProvider(str, Enum): DATABRICKS = "DATABRICKS" COMETAPI = "COMETAPI" HUGGINGFACE = "HUGGINGFACE" + GITHUB_MODELS = "GITHUB_MODELS" CUSTOM = "CUSTOM" @@ -272,19 +273,19 @@ INCENTIVE_TASKS_CONFIG = { IncentiveTaskType.GITHUB_STAR: { "title": "Star our GitHub repository", "description": "Show your support by starring SurfSense on GitHub", - "pages_reward": 100, + "pages_reward": 30, "action_url": "https://github.com/MODSetter/SurfSense", }, IncentiveTaskType.REDDIT_FOLLOW: { "title": "Join our Subreddit", "description": "Join the SurfSense community on Reddit", - "pages_reward": 100, + "pages_reward": 30, "action_url": "https://www.reddit.com/r/SurfSense/", }, IncentiveTaskType.DISCORD_JOIN: { "title": "Join our Discord", "description": "Join the SurfSense community on Discord", - "pages_reward": 100, + "pages_reward": 40, "action_url": "https://discord.gg/ejRNvftDp9", }, # Future tasks can be configured here: @@ -801,9 +802,8 @@ class MemoryCategory(str, Enum): class UserMemory(BaseModel, TimestampMixin): """ - Stores facts, preferences, and context about users for personalized AI responses. - Similar to Claude's memory feature - enables the AI to remember user information - across conversations. + Private memory: facts, preferences, context per user per search space. + Used only for private chats (not shared/team chats). """ __tablename__ = "user_memories" @@ -847,6 +847,40 @@ class UserMemory(BaseModel, TimestampMixin): search_space = relationship("SearchSpace", back_populates="user_memories") +class SharedMemory(BaseModel, TimestampMixin): + __tablename__ = "shared_memories" + + search_space_id = Column( + Integer, + ForeignKey("searchspaces.id", ondelete="CASCADE"), + nullable=False, + index=True, + ) + created_by_id = Column( + UUID(as_uuid=True), + ForeignKey("user.id", ondelete="CASCADE"), + nullable=False, + index=True, + ) + memory_text = Column(Text, nullable=False) + category = Column( + SQLAlchemyEnum(MemoryCategory), + nullable=False, + default=MemoryCategory.fact, + ) + embedding = Column(Vector(config.embedding_model_instance.dimension)) + updated_at = Column( + TIMESTAMP(timezone=True), + nullable=False, + default=lambda: datetime.now(UTC), + onupdate=lambda: datetime.now(UTC), + index=True, + ) + + search_space = relationship("SearchSpace", back_populates="shared_memories") + created_by = relationship("User") + + class Document(BaseModel, TimestampMixin): __tablename__ = "documents" @@ -1215,6 +1249,12 @@ class SearchSpace(BaseModel, TimestampMixin): order_by="UserMemory.updated_at.desc()", cascade="all, delete-orphan", ) + shared_memories = relationship( + "SharedMemory", + back_populates="search_space", + order_by="SharedMemory.updated_at.desc()", + cascade="all, delete-orphan", + ) class SearchSourceConnector(BaseModel, TimestampMixin): @@ -1265,7 +1305,7 @@ class NewLLMConfig(BaseModel, TimestampMixin): - Configurable system instructions (defaults to SURFSENSE_SYSTEM_INSTRUCTIONS) - Citation toggle (enable/disable citation instructions) - Note: SURFSENSE_TOOLS_INSTRUCTIONS is always used and not configurable. + Note: Tools instructions are built by get_tools_instructions(thread_visibility) (personal vs shared memory). """ __tablename__ = "new_llm_configs" diff --git a/surfsense_backend/app/routes/documents_routes.py b/surfsense_backend/app/routes/documents_routes.py index 226d511cc..c8aeac0c9 100644 --- a/surfsense_backend/app/routes/documents_routes.py +++ b/surfsense_backend/app/routes/documents_routes.py @@ -19,6 +19,8 @@ from app.db import ( from app.schemas import ( DocumentRead, DocumentsCreate, + DocumentStatusBatchResponse, + DocumentStatusItemRead, DocumentStatusSchema, DocumentTitleRead, DocumentTitleSearchResponse, @@ -148,6 +150,7 @@ async def create_documents_file_upload( tuple[Document, str, str] ] = [] # (document, temp_path, filename) skipped_duplicates = 0 + duplicate_document_ids: list[int] = [] # ===== PHASE 1: Create pending documents for all files ===== # This makes ALL documents visible in the UI immediately with pending status @@ -182,6 +185,7 @@ async def create_documents_file_upload( # True duplicate — content already indexed, skip os.unlink(temp_path) skipped_duplicates += 1 + duplicate_document_ids.append(existing.id) continue # Existing document is stuck (failed/pending/processing) @@ -255,6 +259,7 @@ async def create_documents_file_upload( return { "message": "Files uploaded for processing", "document_ids": [doc.id for doc in created_documents], + "duplicate_document_ids": duplicate_document_ids, "total_files": len(files), "pending_files": len(files_to_process), "skipped_duplicates": skipped_duplicates, @@ -678,6 +683,74 @@ async def search_document_titles( ) from e +@router.get("/documents/status", response_model=DocumentStatusBatchResponse) +async def get_documents_status( + search_space_id: int, + document_ids: str, + session: AsyncSession = Depends(get_async_session), + user: User = Depends(current_active_user), +): + """ + Batch status endpoint for documents in a search space. + + Returns lightweight status info for the provided document IDs, intended for + polling async ETL progress in chat upload flows. + """ + try: + await check_permission( + session, + user, + search_space_id, + Permission.DOCUMENTS_READ.value, + "You don't have permission to read documents in this search space", + ) + + # Parse comma-separated IDs (e.g. "1,2,3") + parsed_ids = [] + for raw_id in document_ids.split(","): + value = raw_id.strip() + if not value: + continue + try: + parsed_ids.append(int(value)) + except ValueError: + raise HTTPException( + status_code=400, + detail=f"Invalid document id: {value}", + ) from None + + if not parsed_ids: + return DocumentStatusBatchResponse(items=[]) + + result = await session.execute( + select(Document).filter( + Document.search_space_id == search_space_id, + Document.id.in_(parsed_ids), + ) + ) + docs = result.scalars().all() + + items = [ + DocumentStatusItemRead( + id=doc.id, + title=doc.title, + document_type=doc.document_type, + status=DocumentStatusSchema( + state=(doc.status or {}).get("state", "ready"), + reason=(doc.status or {}).get("reason"), + ), + ) + for doc in docs + ] + return DocumentStatusBatchResponse(items=items) + except HTTPException: + raise + except Exception as e: + raise HTTPException( + status_code=500, detail=f"Failed to fetch document status: {e!s}" + ) from e + + @router.get("/documents/type-counts") async def get_document_type_counts( search_space_id: int | None = None, diff --git a/surfsense_backend/app/routes/new_chat_routes.py b/surfsense_backend/app/routes/new_chat_routes.py index 06e929997..ecb1c2a6f 100644 --- a/surfsense_backend/app/routes/new_chat_routes.py +++ b/surfsense_backend/app/routes/new_chat_routes.py @@ -8,16 +8,11 @@ These endpoints support the ThreadHistoryAdapter pattern from assistant-ui: - PUT /threads/{thread_id} - Update thread (rename, archive) - DELETE /threads/{thread_id} - Delete thread - POST /threads/{thread_id}/messages - Append message -- POST /attachments/process - Process attachments for chat context """ -import contextlib -import os -import tempfile -import uuid from datetime import UTC, datetime -from fastapi import APIRouter, Depends, File, HTTPException, Request, UploadFile +from fastapi import APIRouter, Depends, HTTPException, Request from fastapi.responses import StreamingResponse from sqlalchemy import func, or_ from sqlalchemy.exc import IntegrityError, OperationalError @@ -1045,12 +1040,13 @@ async def handle_new_chat( search_space_id=request.search_space_id, chat_id=request.chat_id, session=session, - user_id=str(user.id), # Pass user ID for memory tools and session state + user_id=str(user.id), llm_config_id=llm_config_id, - attachments=request.attachments, mentioned_document_ids=request.mentioned_document_ids, mentioned_surfsense_doc_ids=request.mentioned_surfsense_doc_ids, needs_history_bootstrap=thread.needs_history_bootstrap, + thread_visibility=thread.visibility, + current_user_display_name=user.display_name or "A team member", ), media_type="text/event-stream", headers={ @@ -1276,11 +1272,12 @@ async def regenerate_response( session=session, user_id=str(user.id), llm_config_id=llm_config_id, - attachments=request.attachments, mentioned_document_ids=request.mentioned_document_ids, mentioned_surfsense_doc_ids=request.mentioned_surfsense_doc_ids, checkpoint_id=target_checkpoint_id, needs_history_bootstrap=thread.needs_history_bootstrap, + thread_visibility=thread.visibility, + current_user_display_name=user.display_name or "A team member", ): yield chunk # If we get here, streaming completed successfully @@ -1329,185 +1326,3 @@ async def regenerate_response( status_code=500, detail=f"An unexpected error occurred during regeneration: {e!s}", ) from None - - -# ============================================================================= -# Attachment Processing Endpoint -# ============================================================================= - - -@router.post("/attachments/process") -async def process_attachment( - file: UploadFile = File(...), - session: AsyncSession = Depends(get_async_session), - user: User = Depends(current_active_user), -): - """ - Process an attachment file and extract its content as markdown. - - This endpoint uses the configured ETL service to parse files and return - the extracted content that can be used as context in chat messages. - - Supported file types depend on the configured ETL_SERVICE: - - Markdown/Text files: .md, .markdown, .txt (always supported) - - Audio files: .mp3, .mp4, .mpeg, .mpga, .m4a, .wav, .webm (if STT configured) - - Documents: .pdf, .docx, .doc, .pptx, .xlsx (depends on ETL service) - - Returns: - JSON with attachment id, name, type, and extracted content - """ - from app.config import config as app_config - - if not file.filename: - raise HTTPException(status_code=400, detail="No filename provided") - - filename = file.filename - attachment_id = str(uuid.uuid4()) - - try: - # Save file to a temporary location - file_ext = os.path.splitext(filename)[1].lower() - with tempfile.NamedTemporaryFile(delete=False, suffix=file_ext) as temp_file: - temp_path = temp_file.name - content = await file.read() - temp_file.write(content) - - extracted_content = "" - - # Process based on file type - if file_ext in (".md", ".markdown", ".txt"): - # For text/markdown files, read content directly - with open(temp_path, encoding="utf-8") as f: - extracted_content = f.read() - - elif file_ext in (".mp3", ".mp4", ".mpeg", ".mpga", ".m4a", ".wav", ".webm"): - # Audio files - transcribe if STT service is configured - if not app_config.STT_SERVICE: - raise HTTPException( - status_code=422, - detail="Audio transcription is not configured. Please set STT_SERVICE.", - ) - - stt_service_type = ( - "local" if app_config.STT_SERVICE.startswith("local/") else "external" - ) - - if stt_service_type == "local": - from app.services.stt_service import stt_service - - result = stt_service.transcribe_file(temp_path) - extracted_content = result.get("text", "") - else: - from litellm import atranscription - - with open(temp_path, "rb") as audio_file: - transcription_kwargs = { - "model": app_config.STT_SERVICE, - "file": audio_file, - "api_key": app_config.STT_SERVICE_API_KEY, - } - if app_config.STT_SERVICE_API_BASE: - transcription_kwargs["api_base"] = ( - app_config.STT_SERVICE_API_BASE - ) - - transcription_response = await atranscription( - **transcription_kwargs - ) - extracted_content = transcription_response.get("text", "") - - if extracted_content: - extracted_content = ( - f"# Transcription of {filename}\n\n{extracted_content}" - ) - - else: - # Document files - use configured ETL service - if app_config.ETL_SERVICE == "UNSTRUCTURED": - from langchain_unstructured import UnstructuredLoader - - from app.utils.document_converters import convert_document_to_markdown - - loader = UnstructuredLoader( - temp_path, - mode="elements", - post_processors=[], - languages=["eng"], - include_orig_elements=False, - include_metadata=False, - strategy="auto", - ) - docs = await loader.aload() - extracted_content = await convert_document_to_markdown(docs) - - elif app_config.ETL_SERVICE == "LLAMACLOUD": - from llama_cloud_services import LlamaParse - from llama_cloud_services.parse.utils import ResultType - - parser = LlamaParse( - api_key=app_config.LLAMA_CLOUD_API_KEY, - num_workers=1, - verbose=False, - language="en", - result_type=ResultType.MD, - ) - result = await parser.aparse(temp_path) - markdown_documents = await result.aget_markdown_documents( - split_by_page=False - ) - - if markdown_documents: - extracted_content = "\n\n".join( - doc.text for doc in markdown_documents - ) - - elif app_config.ETL_SERVICE == "DOCLING": - from app.services.docling_service import create_docling_service - - docling_service = create_docling_service() - result = await docling_service.process_document(temp_path, filename) - extracted_content = result.get("content", "") - - else: - raise HTTPException( - status_code=422, - detail=f"ETL service not configured or unsupported file type: {file_ext}", - ) - - # Clean up temp file - with contextlib.suppress(Exception): - os.unlink(temp_path) - - if not extracted_content: - raise HTTPException( - status_code=422, - detail=f"Could not extract content from file: {filename}", - ) - - # Determine attachment type (must be one of: "image", "document", "file") - # assistant-ui only supports these three types - if file_ext in (".png", ".jpg", ".jpeg", ".gif", ".webp"): - attachment_type = "image" - else: - # All other files (including audio, documents, text) are treated as "document" - attachment_type = "document" - - return { - "id": attachment_id, - "name": filename, - "type": attachment_type, - "content": extracted_content, - "contentLength": len(extracted_content), - } - - except HTTPException: - raise - except Exception as e: - # Clean up temp file on error - with contextlib.suppress(Exception): - os.unlink(temp_path) - - raise HTTPException( - status_code=500, - detail=f"Failed to process attachment: {e!s}", - ) from e diff --git a/surfsense_backend/app/routes/search_source_connectors_routes.py b/surfsense_backend/app/routes/search_source_connectors_routes.py index 747e02834..ba6877376 100644 --- a/surfsense_backend/app/routes/search_source_connectors_routes.py +++ b/surfsense_backend/app/routes/search_source_connectors_routes.py @@ -19,7 +19,7 @@ Non-OAuth connectors (BookStack, GitHub, etc.) are limited to one per search spa """ import logging -import os +from contextlib import suppress from datetime import UTC, datetime, timedelta from typing import Any @@ -32,6 +32,7 @@ from sqlalchemy.exc import IntegrityError from sqlalchemy.ext.asyncio import AsyncSession from sqlalchemy.future import select +from app.config import config from app.connectors.github_connector import GitHubConnector from app.db import ( Permission, @@ -70,6 +71,10 @@ from app.tasks.connector_indexers import ( index_slack_messages, ) from app.users import current_active_user +from app.utils.indexing_locks import ( + acquire_connector_indexing_lock, + release_connector_indexing_lock, +) from app.utils.periodic_scheduler import ( create_periodic_schedule, delete_periodic_schedule, @@ -91,11 +96,9 @@ def get_heartbeat_redis_client() -> redis.Redis: """Get or create Redis client for heartbeat tracking.""" global _heartbeat_redis_client if _heartbeat_redis_client is None: - redis_url = os.getenv( - "REDIS_APP_URL", - os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0"), + _heartbeat_redis_client = redis.from_url( + config.REDIS_APP_URL, decode_responses=True ) - _heartbeat_redis_client = redis.from_url(redis_url, decode_responses=True) return _heartbeat_redis_client @@ -1229,10 +1232,19 @@ async def _run_indexing_with_notifications( from celery.exceptions import SoftTimeLimitExceeded notification = None + connector_lock_acquired = False # Track indexed count for retry notifications and heartbeat current_indexed_count = 0 try: + connector_lock_acquired = acquire_connector_indexing_lock(connector_id) + if not connector_lock_acquired: + logger.info( + f"Skipping indexing for connector {connector_id} " + "(another worker already holds Redis connector lock)" + ) + return + # Get connector info for notification connector_result = await session.execute( select(SearchSourceConnector).where( @@ -1558,6 +1570,9 @@ async def _run_indexing_with_notifications( get_heartbeat_redis_client().delete(heartbeat_key) except Exception: pass # Ignore cleanup errors - key will expire anyway + if connector_lock_acquired: + with suppress(Exception): + release_connector_indexing_lock(connector_id) async def run_notion_indexing_with_new_session( diff --git a/surfsense_backend/app/schemas/__init__.py b/surfsense_backend/app/schemas/__init__.py index c6d66149f..b015cf715 100644 --- a/surfsense_backend/app/schemas/__init__.py +++ b/surfsense_backend/app/schemas/__init__.py @@ -11,6 +11,8 @@ from .documents import ( DocumentBase, DocumentRead, DocumentsCreate, + DocumentStatusBatchResponse, + DocumentStatusItemRead, DocumentStatusSchema, DocumentTitleRead, DocumentTitleSearchResponse, @@ -105,6 +107,8 @@ __all__ = [ # Document schemas "DocumentBase", "DocumentRead", + "DocumentStatusBatchResponse", + "DocumentStatusItemRead", "DocumentStatusSchema", "DocumentTitleRead", "DocumentTitleSearchResponse", diff --git a/surfsense_backend/app/schemas/documents.py b/surfsense_backend/app/schemas/documents.py index 4cedc7d93..2ca341921 100644 --- a/surfsense_backend/app/schemas/documents.py +++ b/surfsense_backend/app/schemas/documents.py @@ -99,3 +99,20 @@ class DocumentTitleSearchResponse(BaseModel): items: list[DocumentTitleRead] has_more: bool + + +class DocumentStatusItemRead(BaseModel): + """Lightweight document status payload for batch status polling.""" + + id: int + title: str + document_type: DocumentType + status: DocumentStatusSchema + + model_config = ConfigDict(from_attributes=True) + + +class DocumentStatusBatchResponse(BaseModel): + """Batch status response for a set of document IDs.""" + + items: list[DocumentStatusItemRead] diff --git a/surfsense_backend/app/schemas/new_chat.py b/surfsense_backend/app/schemas/new_chat.py index 84ba1b950..efa314979 100644 --- a/surfsense_backend/app/schemas/new_chat.py +++ b/surfsense_backend/app/schemas/new_chat.py @@ -159,15 +159,6 @@ class ChatMessage(BaseModel): content: str -class ChatAttachment(BaseModel): - """An attachment with its extracted content for chat context.""" - - id: str # Unique attachment ID - name: str # Original filename - type: str # Attachment type: document, image, audio - content: str # Extracted markdown content from the file - - class NewChatRequest(BaseModel): """Request schema for the deep agent chat endpoint.""" @@ -175,9 +166,6 @@ class NewChatRequest(BaseModel): user_query: str search_space_id: int messages: list[ChatMessage] | None = None # Optional chat history from frontend - attachments: list[ChatAttachment] | None = ( - None # Optional attachments with extracted content - ) mentioned_document_ids: list[int] | None = ( None # Optional document IDs mentioned with @ in the chat ) @@ -201,7 +189,6 @@ class RegenerateRequest(BaseModel): user_query: str | None = ( None # New user query (for edit). None = reload with same query ) - attachments: list[ChatAttachment] | None = None mentioned_document_ids: list[int] | None = None mentioned_surfsense_doc_ids: list[int] | None = None diff --git a/surfsense_backend/app/services/llm_router_service.py b/surfsense_backend/app/services/llm_router_service.py index 3a19f0b8e..58a75cf54 100644 --- a/surfsense_backend/app/services/llm_router_service.py +++ b/surfsense_backend/app/services/llm_router_service.py @@ -56,6 +56,7 @@ PROVIDER_MAP = { "ALIBABA_QWEN": "openai", "MOONSHOT": "openai", "ZHIPU": "openai", + "GITHUB_MODELS": "github", "HUGGINGFACE": "huggingface", "CUSTOM": "custom", } diff --git a/surfsense_backend/app/services/llm_service.py b/surfsense_backend/app/services/llm_service.py index 5af804fed..24bc4138b 100644 --- a/surfsense_backend/app/services/llm_service.py +++ b/surfsense_backend/app/services/llm_service.py @@ -119,6 +119,7 @@ async def validate_llm_config( "ALIBABA_QWEN": "openai", "MOONSHOT": "openai", "ZHIPU": "openai", # GLM needs special handling + "GITHUB_MODELS": "github", } provider_prefix = provider_map.get(provider, provider.lower()) model_string = f"{provider_prefix}/{model_name}" @@ -335,6 +336,7 @@ async def get_search_space_llm_instance( "ALIBABA_QWEN": "openai", "MOONSHOT": "openai", "ZHIPU": "openai", + "GITHUB_MODELS": "github", } provider_prefix = provider_map.get( llm_config.provider.value, llm_config.provider.value.lower() diff --git a/surfsense_backend/app/tasks/celery_tasks/document_tasks.py b/surfsense_backend/app/tasks/celery_tasks/document_tasks.py index 81c5dbba2..3e60b5819 100644 --- a/surfsense_backend/app/tasks/celery_tasks/document_tasks.py +++ b/surfsense_backend/app/tasks/celery_tasks/document_tasks.py @@ -36,11 +36,9 @@ def _get_doc_heartbeat_redis(): global _doc_heartbeat_redis if _doc_heartbeat_redis is None: - redis_url = os.getenv( - "REDIS_APP_URL", - os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0"), + _doc_heartbeat_redis = redis.from_url( + config.REDIS_APP_URL, decode_responses=True ) - _doc_heartbeat_redis = redis.from_url(redis_url, decode_responses=True) return _doc_heartbeat_redis diff --git a/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py b/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py index 14df83508..973e7e750 100644 --- a/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py +++ b/surfsense_backend/app/tasks/celery_tasks/podcast_tasks.py @@ -46,16 +46,10 @@ def get_celery_session_maker(): def _clear_generating_podcast(search_space_id: int) -> None: """Clear the generating podcast marker from Redis when task completes.""" - import os - import redis try: - redis_url = os.getenv( - "REDIS_APP_URL", - os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0"), - ) - client = redis.from_url(redis_url, decode_responses=True) + client = redis.from_url(config.REDIS_APP_URL, decode_responses=True) key = f"podcast:generating:{search_space_id}" client.delete(key) logger.info( diff --git a/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py b/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py index b33e25170..80d271aaa 100644 --- a/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py +++ b/surfsense_backend/app/tasks/celery_tasks/schedule_checker_task.py @@ -9,7 +9,8 @@ from sqlalchemy.pool import NullPool from app.celery_app import celery_app from app.config import config -from app.db import SearchSourceConnector, SearchSourceConnectorType +from app.db import Notification, SearchSourceConnector, SearchSourceConnectorType +from app.utils.indexing_locks import is_connector_indexing_locked logger = logging.getLogger(__name__) @@ -107,6 +108,32 @@ async def _check_and_trigger_schedules(): # Trigger indexing for each due connector for connector in due_connectors: + # Primary guard: Redis lock indicates a task is currently running. + if is_connector_indexing_locked(connector.id): + logger.info( + f"Skipping periodic indexing for connector {connector.id} " + "(Redis lock indicates indexing is already in progress)" + ) + continue + + # Skip scheduling if a sync for this connector is already in progress. + # This prevents duplicate tasks from piling up under slow/rate-limited providers. + in_progress_result = await session.execute( + select(Notification.id).where( + Notification.type == "connector_indexing", + Notification.notification_metadata["connector_id"].astext + == str(connector.id), + Notification.notification_metadata["status"].astext + == "in_progress", + ) + ) + if in_progress_result.first(): + logger.info( + f"Skipping periodic indexing for connector {connector.id} " + "(already has in-progress indexing notification)" + ) + continue + task = task_map.get(connector.connector_type) if task: logger.info( diff --git a/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py b/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py index f3bbddee0..c2c82dd2c 100644 --- a/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py +++ b/surfsense_backend/app/tasks/celery_tasks/stale_notification_cleanup_task.py @@ -25,7 +25,6 @@ Detection mechanism: import contextlib import json import logging -import os from datetime import UTC, datetime import redis @@ -52,11 +51,7 @@ def get_redis_client() -> redis.Redis: """Get or create Redis client for heartbeat checking.""" global _redis_client if _redis_client is None: - redis_url = os.getenv( - "REDIS_APP_URL", - os.getenv("CELERY_BROKER_URL", "redis://localhost:6379/0"), - ) - _redis_client = redis.from_url(redis_url, decode_responses=True) + _redis_client = redis.from_url(config.REDIS_APP_URL, decode_responses=True) return _redis_client diff --git a/surfsense_backend/app/tasks/chat/stream_new_chat.py b/surfsense_backend/app/tasks/chat/stream_new_chat.py index 685f77e39..31e67c7ff 100644 --- a/surfsense_backend/app/tasks/chat/stream_new_chat.py +++ b/surfsense_backend/app/tasks/chat/stream_new_chat.py @@ -26,9 +26,8 @@ from app.agents.new_chat.llm_config import ( load_agent_config, load_llm_config_from_yaml, ) -from app.db import Document, SurfsenseDocsDocument +from app.db import ChatVisibility, Document, SurfsenseDocsDocument from app.prompts import TITLE_GENERATION_PROMPT_TEMPLATE -from app.schemas.new_chat import ChatAttachment from app.services.chat_session_state_service import ( clear_ai_responding, set_ai_responding, @@ -38,23 +37,6 @@ from app.services.new_streaming_service import VercelStreamingService from app.utils.content_utils import bootstrap_history_from_db -def format_attachments_as_context(attachments: list[ChatAttachment]) -> str: - """Format attachments as context for the agent.""" - if not attachments: - return "" - - context_parts = [""] - for i, attachment in enumerate(attachments, 1): - context_parts.append( - f"" - ) - context_parts.append(f"") - context_parts.append("") - context_parts.append("") - - return "\n".join(context_parts) - - def format_mentioned_documents_as_context(documents: list[Document]) -> str: """ Format mentioned documents as context for the agent. @@ -203,11 +185,12 @@ async def stream_new_chat( session: AsyncSession, user_id: str | None = None, llm_config_id: int = -1, - attachments: list[ChatAttachment] | None = None, mentioned_document_ids: list[int] | None = None, mentioned_surfsense_doc_ids: list[int] | None = None, checkpoint_id: str | None = None, needs_history_bootstrap: bool = False, + thread_visibility: ChatVisibility | None = None, + current_user_display_name: str | None = None, ) -> AsyncGenerator[str, None]: """ Stream chat responses from the new SurfSense deep agent. @@ -222,7 +205,6 @@ async def stream_new_chat( session: The database session user_id: The current user's UUID string (for memory tools and session state) llm_config_id: The LLM configuration ID (default: -1 for first global config) - attachments: Optional attachments with extracted content needs_history_bootstrap: If True, load message history from DB (for cloned chats) mentioned_document_ids: Optional list of document IDs mentioned with @ in the chat mentioned_surfsense_doc_ids: Optional list of SurfSense doc IDs mentioned with @ in the chat @@ -295,17 +277,18 @@ async def stream_new_chat( # Get the PostgreSQL checkpointer for persistent conversation memory checkpointer = await get_checkpointer() - # Create the deep agent with checkpointer and configurable prompts + visibility = thread_visibility or ChatVisibility.PRIVATE agent = await create_surfsense_deep_agent( llm=llm, search_space_id=search_space_id, db_session=session, connector_service=connector_service, checkpointer=checkpointer, - user_id=user_id, # Pass user ID for memory tools - thread_id=chat_id, # Pass chat ID for podcast association - agent_config=agent_config, # Pass prompt configuration - firecrawl_api_key=firecrawl_api_key, # Pass Firecrawl API key if configured + user_id=user_id, + thread_id=chat_id, + agent_config=agent_config, + firecrawl_api_key=firecrawl_api_key, + thread_visibility=visibility, ) # Build input with message history @@ -313,7 +296,9 @@ async def stream_new_chat( # Bootstrap history for cloned chats (no LangGraph checkpoint exists yet) if needs_history_bootstrap: - langchain_messages = await bootstrap_history_from_db(session, chat_id) + langchain_messages = await bootstrap_history_from_db( + session, chat_id, thread_visibility=visibility + ) # Clear the flag so we don't bootstrap again on next message from app.db import NewChatThread @@ -355,13 +340,10 @@ async def stream_new_chat( ) mentioned_surfsense_docs = list(result.scalars().all()) - # Format the user query with context (attachments + mentioned documents + surfsense docs) + # Format the user query with context (mentioned documents + SurfSense docs) final_query = user_query context_parts = [] - if attachments: - context_parts.append(format_attachments_as_context(attachments)) - if mentioned_documents: context_parts.append( format_mentioned_documents_as_context(mentioned_documents) @@ -376,6 +358,9 @@ async def stream_new_chat( context = "\n\n".join(context_parts) final_query = f"{context}\n\n{user_query}" + if visibility == ChatVisibility.SEARCH_SPACE and current_user_display_name: + final_query = f"**[{current_user_display_name}]:** {final_query}" + # if messages: # # Convert frontend messages to LangChain format # for msg in messages: @@ -451,39 +436,20 @@ async def stream_new_chat( last_active_step_id = analyze_step_id # Determine step title and action verb based on context - if attachments and (mentioned_documents or mentioned_surfsense_docs): - last_active_step_title = "Analyzing your content" - action_verb = "Reading" - elif attachments: - last_active_step_title = "Reading your content" - action_verb = "Reading" - elif mentioned_documents or mentioned_surfsense_docs: + if mentioned_documents or mentioned_surfsense_docs: last_active_step_title = "Analyzing referenced content" action_verb = "Analyzing" else: last_active_step_title = "Understanding your request" action_verb = "Processing" - # Build the message with inline context about attachments/documents + # Build the message with inline context about referenced documents processing_parts = [] # Add the user query query_text = user_query[:80] + ("..." if len(user_query) > 80 else "") processing_parts.append(query_text) - # Add file attachment names inline - if attachments: - attachment_names = [] - for attachment in attachments: - name = attachment.name - if len(name) > 30: - name = name[:27] + "..." - attachment_names.append(name) - if len(attachment_names) == 1: - processing_parts.append(f"[{attachment_names[0]}]") - else: - processing_parts.append(f"[{len(attachment_names)} files]") - # Add mentioned document names inline if mentioned_documents: doc_names = [] diff --git a/surfsense_backend/app/tasks/connector_indexers/base.py b/surfsense_backend/app/tasks/connector_indexers/base.py index 6a1226230..139aed1d3 100644 --- a/surfsense_backend/app/tasks/connector_indexers/base.py +++ b/surfsense_backend/app/tasks/connector_indexers/base.py @@ -52,10 +52,22 @@ def safe_set_chunks(document: Document, chunks: list) -> None: # Instead of: document.chunks = chunks (DANGEROUS!) safe_set_chunks(document, chunks) # Always safe """ + from sqlalchemy.orm import object_session from sqlalchemy.orm.attributes import set_committed_value + # Keep relationship assignment lazy-load-safe. set_committed_value(document, "chunks", chunks) + # Ensure chunk rows are actually persisted. + # set_committed_value bypasses normal unit-of-work tracking, so we need to + # explicitly attach chunk objects to the current session. + session = object_session(document) + if session is not None: + if document.id is not None: + for chunk in chunks: + chunk.document_id = document.id + session.add_all(chunks) + def parse_date_flexible(date_str: str) -> datetime: """ diff --git a/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py b/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py index 1b13a2c37..cf6828268 100644 --- a/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py +++ b/surfsense_backend/app/tasks/connector_indexers/teams_indexer.py @@ -1,7 +1,10 @@ """ Microsoft Teams connector indexer. -Implements 2-phase document status updates for real-time UI feedback: +Implements batch indexing: groups up to TEAMS_BATCH_SIZE messages per channel +into a single document for efficient indexing and better conversational context. + +Uses 2-phase document status updates for real-time UI feedback: - Phase 1: Create all documents with 'pending' status (visible in UI immediately) - Phase 2: Process each document: pending → processing → ready/failed """ @@ -41,6 +44,72 @@ HeartbeatCallbackType = Callable[[int], Awaitable[None]] # Heartbeat interval in seconds - update notification every 30 seconds HEARTBEAT_INTERVAL_SECONDS = 30 +# Number of messages to combine into a single document for batch indexing. +# Grouping messages improves conversational context in embeddings/chunks and +# drastically reduces the number of documents, embedding calls, and DB overhead. +TEAMS_BATCH_SIZE = 100 + + +def _build_batch_document_string( + team_name: str, + team_id: str, + channel_name: str, + channel_id: str, + messages: list[dict], +) -> str: + """ + Combine multiple Teams messages into a single document string. + + Each message is formatted with its timestamp and author, and all messages + are concatenated into a conversation-style document. The chunker will + later split this into overlapping windows of ~8-10 consecutive messages, + preserving conversational context in each chunk's embedding. + + Args: + team_name: Name of the Microsoft Team + team_id: ID of the Microsoft Team + channel_name: Name of the channel + channel_id: ID of the channel + messages: List of formatted message dicts with 'user_name', 'created_datetime', 'content' + + Returns: + Formatted document string with metadata and conversation content + """ + first_msg_time = messages[0].get("created_datetime", "Unknown") + last_msg_time = messages[-1].get("created_datetime", "Unknown") + + metadata_lines = [ + f"TEAM_NAME: {team_name}", + f"TEAM_ID: {team_id}", + f"CHANNEL_NAME: {channel_name}", + f"CHANNEL_ID: {channel_id}", + f"MESSAGE_COUNT: {len(messages)}", + f"FIRST_MESSAGE_TIME: {first_msg_time}", + f"LAST_MESSAGE_TIME: {last_msg_time}", + ] + + conversation_lines = [] + for msg in messages: + author = msg.get("user_name", "Unknown User") + timestamp = msg.get("created_datetime", "Unknown Time") + content = msg.get("content", "") + conversation_lines.append(f"[{timestamp}] {author}: {content}") + + metadata_sections = [ + ("METADATA", metadata_lines), + ( + "CONTENT", + [ + "FORMAT: markdown", + "TEXT_START", + "\n".join(conversation_lines), + "TEXT_END", + ], + ), + ] + + return build_document_metadata_markdown(metadata_sections) + async def index_teams_messages( session: AsyncSession, @@ -55,6 +124,12 @@ async def index_teams_messages( """ Index Microsoft Teams messages from all accessible teams and channels. + Messages are grouped into batches of TEAMS_BATCH_SIZE per channel, + so each document contains up to 100 consecutive messages with full + conversational context. This reduces document count, embedding calls, + and DB overhead by ~100x while improving search quality through + context-aware chunk embeddings. + Implements 2-phase document status updates for real-time UI feedback: - Phase 1: Create all documents with 'pending' status (visible in UI immediately) - Phase 2: Process each document: pending → processing → ready/failed @@ -184,6 +259,7 @@ async def index_teams_messages( documents_skipped = 0 documents_failed = 0 duplicate_content_count = 0 + total_messages_collected = 0 skipped_channels = [] # Heartbeat tracking - update notification periodically to prevent appearing stuck @@ -199,21 +275,21 @@ async def index_teams_messages( start_datetime = None end_datetime = None if start_date_str: - # Parse as naive datetime and make it timezone-aware (UTC) start_datetime = datetime.strptime(start_date_str, "%Y-%m-%d").replace( tzinfo=UTC ) if end_date_str: - # Parse as naive datetime, set to end of day, and make it timezone-aware (UTC) end_datetime = datetime.strptime(end_date_str, "%Y-%m-%d").replace( hour=23, minute=59, second=59, tzinfo=UTC ) # ======================================================================= - # PHASE 1: Collect all messages and create pending documents - # This makes ALL documents visible in the UI immediately with pending status + # PHASE 1: Collect messages, group into batches, and create pending documents + # Messages are grouped into batches of TEAMS_BATCH_SIZE per channel. + # Each batch becomes a single document with full conversational context. + # All documents are visible in the UI immediately with pending status. # ======================================================================= - messages_to_process = [] # List of dicts with document and message data + batches_to_process = [] # List of dicts with document and batch data new_documents_created = False for team in teams: @@ -251,65 +327,72 @@ async def index_teams_messages( ) continue - # Process each message + # Format messages for batching + formatted_messages = [] for msg in messages: # Skip deleted messages or empty content if msg.get("deletedDateTime"): continue - # Extract message details - message_id = msg.get("id", "") - created_datetime = msg.get("createdDateTime", "") from_user = msg.get("from", {}) user_name = from_user.get("user", {}).get( "displayName", "Unknown User" ) - user_email = from_user.get("user", {}).get( - "userPrincipalName", "Unknown Email" - ) - # Extract message content body = msg.get("body", {}) - content_type = body.get("contentType", "text") msg_text = body.get("content", "") # Skip empty messages if not msg_text or msg_text.strip() == "": continue - # Format document metadata - metadata_sections = [ - ( - "METADATA", - [ - f"TEAM_NAME: {team_name}", - f"TEAM_ID: {team_id}", - f"CHANNEL_NAME: {channel_name}", - f"CHANNEL_ID: {channel_id}", - f"MESSAGE_TIMESTAMP: {created_datetime}", - f"MESSAGE_USER_NAME: {user_name}", - f"MESSAGE_USER_EMAIL: {user_email}", - f"CONTENT_TYPE: {content_type}", - ], - ), - ( - "CONTENT", - [ - f"FORMAT: {content_type}", - "TEXT_START", - msg_text, - "TEXT_END", - ], - ), - ] - - # Build the document string - combined_document_string = build_document_metadata_markdown( - metadata_sections + formatted_messages.append( + { + "message_id": msg.get("id", ""), + "created_datetime": msg.get("createdDateTime", ""), + "user_name": user_name, + "content": msg_text, + } ) - # Generate unique identifier hash for this Teams message - unique_identifier = f"{team_id}_{channel_id}_{message_id}" + if not formatted_messages: + logger.info( + "No valid messages found in channel %s of team %s after filtering.", + channel_name, + team_name, + ) + documents_skipped += 1 + continue + + total_messages_collected += len(formatted_messages) + + # ======================================================= + # Group messages into batches of TEAMS_BATCH_SIZE + # Each batch becomes a single document with conversation context + # ======================================================= + for batch_start in range( + 0, len(formatted_messages), TEAMS_BATCH_SIZE + ): + batch = formatted_messages[ + batch_start : batch_start + TEAMS_BATCH_SIZE + ] + + # Build combined document string from all messages in this batch + combined_document_string = _build_batch_document_string( + team_name=team_name, + team_id=team_id, + channel_name=channel_name, + channel_id=channel_id, + messages=batch, + ) + + # Generate unique identifier for this batch using + # team_id + channel_id + first message id + last message id + first_msg_id = batch[0].get("message_id", "") + last_msg_id = batch[-1].get("message_id", "") + unique_identifier = ( + f"{team_id}_{channel_id}_{first_msg_id}_{last_msg_id}" + ) unique_identifier_hash = generate_unique_identifier_hash( DocumentType.TEAMS_CONNECTOR, unique_identifier, @@ -331,7 +414,6 @@ async def index_teams_messages( if existing_document: # Document exists - check if content has changed if existing_document.content_hash == content_hash: - # Ensure status is ready (might have been stuck in processing/pending) if not DocumentStatus.is_state( existing_document.status, DocumentStatus.READY ): @@ -342,7 +424,7 @@ async def index_teams_messages( continue # Queue existing document for update (will be set to processing in Phase 2) - messages_to_process.append( + batches_to_process.append( { "document": existing_document, "is_new": False, @@ -352,14 +434,21 @@ async def index_teams_messages( "team_id": team_id, "channel_name": channel_name, "channel_id": channel_id, - "message_id": message_id, + "first_message_id": first_msg_id, + "last_message_id": last_msg_id, + "first_message_time": batch[0].get( + "created_datetime", "Unknown" + ), + "last_message_time": batch[-1].get( + "created_datetime", "Unknown" + ), + "message_count": len(batch), "start_date": start_date_str, "end_date": end_date_str, } ) continue - # Document doesn't exist by unique_identifier_hash # Check if a document with the same content_hash exists (from another connector) with session.no_autoflush: duplicate_by_content = ( @@ -370,9 +459,10 @@ async def index_teams_messages( if duplicate_by_content: logger.info( - "Teams message %s in channel %s already indexed by another connector " + "Teams batch (%s msgs) in %s/%s already indexed by another connector " "(existing document ID: %s, type: %s). Skipping.", - message_id, + len(batch), + team_name, channel_name, duplicate_by_content.id, duplicate_by_content.document_type, @@ -391,6 +481,9 @@ async def index_teams_messages( "team_id": team_id, "channel_name": channel_name, "channel_id": channel_id, + "first_message_id": first_msg_id, + "last_message_id": last_msg_id, + "message_count": len(batch), "connector_id": connector_id, }, content="Pending...", # Placeholder until processed @@ -406,7 +499,7 @@ async def index_teams_messages( session.add(document) new_documents_created = True - messages_to_process.append( + batches_to_process.append( { "document": document, "is_new": True, @@ -416,12 +509,30 @@ async def index_teams_messages( "team_id": team_id, "channel_name": channel_name, "channel_id": channel_id, - "message_id": message_id, + "first_message_id": first_msg_id, + "last_message_id": last_msg_id, + "first_message_time": batch[0].get( + "created_datetime", "Unknown" + ), + "last_message_time": batch[-1].get( + "created_datetime", "Unknown" + ), + "message_count": len(batch), "start_date": start_date_str, "end_date": end_date_str, } ) + logger.info( + "Phase 1: Collected %s messages from %s/%s, " + "grouped into %s batch(es)", + len(formatted_messages), + team_name, + channel_name, + (len(formatted_messages) + TEAMS_BATCH_SIZE - 1) + // TEAMS_BATCH_SIZE, + ) + except Exception as e: logger.error( "Error processing channel %s in team %s: %s", @@ -441,17 +552,20 @@ async def index_teams_messages( # Commit all pending documents - they all appear in UI now if new_documents_created: logger.info( - f"Phase 1: Committing {len([m for m in messages_to_process if m['is_new']])} pending documents" + "Phase 1: Committing %s pending batch documents " + "(%s total messages across all channels)", + len([b for b in batches_to_process if b["is_new"]]), + total_messages_collected, ) await session.commit() # ======================================================================= - # PHASE 2: Process each document one by one + # PHASE 2: Process each batch document one by one # Each document transitions: pending → processing → ready/failed # ======================================================================= - logger.info(f"Phase 2: Processing {len(messages_to_process)} documents") + logger.info("Phase 2: Processing %s batch documents", len(batches_to_process)) - for item in messages_to_process: + for item in batches_to_process: # Send heartbeat periodically if on_heartbeat_callback: current_time = time.time() @@ -481,6 +595,11 @@ async def index_teams_messages( "team_id": item["team_id"], "channel_name": item["channel_name"], "channel_id": item["channel_id"], + "first_message_id": item["first_message_id"], + "last_message_id": item["last_message_id"], + "first_message_time": item["first_message_time"], + "last_message_time": item["last_message_time"], + "message_count": item["message_count"], "start_date": item["start_date"], "end_date": item["end_date"], "indexed_at": datetime.now().strftime("%Y-%m-%d %H:%M:%S"), @@ -495,20 +614,25 @@ async def index_teams_messages( # Batch commit every 10 documents (for ready status updates) if documents_indexed % 10 == 0: logger.info( - "Committing batch: %s Teams messages processed so far", + "Committing batch: %s Teams batch documents processed so far", documents_indexed, ) await session.commit() except Exception as e: - logger.error(f"Error processing Teams message: {e!s}", exc_info=True) + logger.error( + "Error processing Teams batch document: %s", + str(e), + exc_info=True, + ) # Mark document as failed with reason (visible in UI) try: document.status = DocumentStatus.failed(str(e)) document.updated_at = get_current_timestamp() except Exception as status_error: logger.error( - f"Failed to update document status to failed: {status_error}" + "Failed to update document status to failed: %s", + str(status_error), ) documents_failed += 1 continue @@ -518,7 +642,9 @@ async def index_teams_messages( # Final commit for any remaining documents not yet committed in batches logger.info( - "Final commit: Total %s Teams messages processed", documents_indexed + "Final commit: Total %s Teams batch documents processed (from %s messages)", + documents_indexed, + total_messages_collected, ) try: await session.commit() @@ -530,8 +656,9 @@ async def index_teams_messages( or "uniqueviolationerror" in str(e).lower() ): logger.warning( - f"Duplicate content_hash detected during final commit. " - f"Rolling back and continuing. Error: {e!s}" + "Duplicate content_hash detected during final commit. " + "Rolling back and continuing. Error: %s", + str(e), ) await session.rollback() else: @@ -557,13 +684,16 @@ async def index_teams_messages( "documents_failed": documents_failed, "duplicate_content_count": duplicate_content_count, "skipped_channels_count": len(skipped_channels), + "total_messages_collected": total_messages_collected, + "batch_size": TEAMS_BATCH_SIZE, }, ) logger.info( - "Teams indexing completed: %s ready, %s skipped, %s failed " - "(%s duplicate content)", + "Teams indexing completed: %s batch docs ready (from %s messages), " + "%s skipped, %s failed (%s duplicate content)", documents_indexed, + total_messages_collected, documents_skipped, documents_failed, duplicate_content_count, diff --git a/surfsense_backend/app/tasks/document_processors/base.py b/surfsense_backend/app/tasks/document_processors/base.py index 2047ec63d..2edc48e91 100644 --- a/surfsense_backend/app/tasks/document_processors/base.py +++ b/surfsense_backend/app/tasks/document_processors/base.py @@ -38,10 +38,22 @@ def safe_set_chunks(document: Document, chunks: list) -> None: # Instead of: document.chunks = chunks (DANGEROUS!) safe_set_chunks(document, chunks) # Always safe """ + from sqlalchemy.orm import object_session from sqlalchemy.orm.attributes import set_committed_value + # Keep relationship assignment lazy-load-safe. set_committed_value(document, "chunks", chunks) + # Ensure chunk rows are actually persisted. + # set_committed_value bypasses normal unit-of-work tracking, so we need to + # explicitly attach chunk objects to the current session. + session = object_session(document) + if session is not None: + if document.id is not None: + for chunk in chunks: + chunk.document_id = document.id + session.add_all(chunks) + def get_current_timestamp() -> datetime: """ diff --git a/surfsense_backend/app/users.py b/surfsense_backend/app/users.py index ee07ba88f..7ec657781 100644 --- a/surfsense_backend/app/users.py +++ b/surfsense_backend/app/users.py @@ -47,6 +47,14 @@ if config.AUTH_TYPE == "GOOGLE": class UserManager(UUIDIDMixin, BaseUserManager[User, uuid.UUID]): + """ + Custom user manager extending fastapi-users BaseUserManager. + + Authentication returns a generic error for both non-existent accounts + and incorrect passwords to comply with OWASP WSTG-IDNT-04 and + prevent user enumeration attacks. + """ + reset_password_token_secret = SECRET verification_token_secret = SECRET diff --git a/surfsense_backend/app/utils/content_utils.py b/surfsense_backend/app/utils/content_utils.py index d2342b79e..5f2a4cd46 100644 --- a/surfsense_backend/app/utils/content_utils.py +++ b/surfsense_backend/app/utils/content_utils.py @@ -9,9 +9,17 @@ Message content in new_chat_messages can be stored in various formats: These utilities help extract and transform content for different use cases. """ +from __future__ import annotations + +from typing import TYPE_CHECKING + from langchain_core.messages import AIMessage, HumanMessage from sqlalchemy import select from sqlalchemy.ext.asyncio import AsyncSession +from sqlalchemy.orm import selectinload + +if TYPE_CHECKING: + from app.db import ChatVisibility def extract_text_content(content: str | dict | list) -> str: @@ -38,6 +46,7 @@ def extract_text_content(content: str | dict | list) -> str: async def bootstrap_history_from_db( session: AsyncSession, thread_id: int, + thread_visibility: ChatVisibility | None = None, ) -> list[HumanMessage | AIMessage]: """ Load message history from database and convert to LangChain format. @@ -45,20 +54,28 @@ async def bootstrap_history_from_db( Used for cloned chats where the LangGraph checkpointer has no state, but we have messages in the database that should be used as context. + When thread_visibility is SEARCH_SPACE, user messages are prefixed with + the author's display name so the LLM sees who said what. + Args: session: Database session thread_id: The chat thread ID + thread_visibility: When SEARCH_SPACE, user messages get author prefix Returns: List of LangChain messages (HumanMessage/AIMessage) """ - from app.db import NewChatMessage + from app.db import ChatVisibility, NewChatMessage - result = await session.execute( + is_shared = thread_visibility == ChatVisibility.SEARCH_SPACE + stmt = ( select(NewChatMessage) .filter(NewChatMessage.thread_id == thread_id) .order_by(NewChatMessage.created_at) ) + if is_shared: + stmt = stmt.options(selectinload(NewChatMessage.author)) + result = await session.execute(stmt) db_messages = result.scalars().all() langchain_messages: list[HumanMessage | AIMessage] = [] @@ -68,6 +85,11 @@ async def bootstrap_history_from_db( if not text_content: continue if msg.role == "user": + if is_shared: + author_name = ( + msg.author.display_name if msg.author else None + ) or "A team member" + text_content = f"**[{author_name}]:** {text_content}" langchain_messages.append(HumanMessage(content=text_content)) elif msg.role == "assistant": langchain_messages.append(AIMessage(content=text_content)) diff --git a/surfsense_backend/app/utils/indexing_locks.py b/surfsense_backend/app/utils/indexing_locks.py new file mode 100644 index 000000000..7790bcc11 --- /dev/null +++ b/surfsense_backend/app/utils/indexing_locks.py @@ -0,0 +1,46 @@ +"""Redis-based connector indexing locks to prevent duplicate sync tasks.""" + +import redis + +from app.config import config + +_redis_client: redis.Redis | None = None +LOCK_TTL_SECONDS = config.CONNECTOR_INDEXING_LOCK_TTL_SECONDS + + +def get_indexing_lock_redis_client() -> redis.Redis: + """Get or create Redis client for connector indexing locks.""" + global _redis_client + if _redis_client is None: + _redis_client = redis.from_url(config.REDIS_APP_URL, decode_responses=True) + return _redis_client + + +def _get_connector_lock_key(connector_id: int) -> str: + """Generate Redis key for a connector indexing lock.""" + return f"indexing:connector_lock:{connector_id}" + + +def acquire_connector_indexing_lock(connector_id: int) -> bool: + """Acquire lock for connector indexing. Returns True if acquired.""" + key = _get_connector_lock_key(connector_id) + return bool( + get_indexing_lock_redis_client().set( + key, + "1", + nx=True, + ex=LOCK_TTL_SECONDS, + ) + ) + + +def release_connector_indexing_lock(connector_id: int) -> None: + """Release lock for connector indexing.""" + key = _get_connector_lock_key(connector_id) + get_indexing_lock_redis_client().delete(key) + + +def is_connector_indexing_locked(connector_id: int) -> bool: + """Check if connector indexing lock exists.""" + key = _get_connector_lock_key(connector_id) + return bool(get_indexing_lock_redis_client().exists(key)) diff --git a/surfsense_backend/pyproject.toml b/surfsense_backend/pyproject.toml index 8e9a57786..99c888b14 100644 --- a/surfsense_backend/pyproject.toml +++ b/surfsense_backend/pyproject.toml @@ -1,6 +1,6 @@ [project] name = "surf-new-backend" -version = "0.0.12" +version = "0.0.13" description = "SurfSense Backend" requires-python = ">=3.12" dependencies = [ @@ -62,6 +62,7 @@ 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b/surfsense_browser_extension/package.json index bf926d09f..c01ec1514 100644 --- a/surfsense_browser_extension/package.json +++ b/surfsense_browser_extension/package.json @@ -1,7 +1,7 @@ { "name": "surfsense_browser_extension", "displayName": "Surfsense Browser Extension", - "version": "0.0.12", + "version": "0.0.13", "description": "Extension to collect Browsing History for SurfSense.", "author": "https://github.com/MODSetter", "engines": { diff --git a/surfsense_web/app/(home)/login/LocalLoginForm.tsx b/surfsense_web/app/(home)/login/LocalLoginForm.tsx index 21928708c..cb3ee73a1 100644 --- a/surfsense_web/app/(home)/login/LocalLoginForm.tsx +++ b/surfsense_web/app/(home)/login/LocalLoginForm.tsx @@ -9,7 +9,7 @@ import { useEffect, useState } from "react"; import { toast } from "sonner"; import { loginMutationAtom } from "@/atoms/auth/auth-mutation.atoms"; import { Spinner } from "@/components/ui/spinner"; -import { getAuthErrorDetails, isNetworkError, shouldRetry } from "@/lib/auth-errors"; +import { getAuthErrorDetails, isNetworkError } from "@/lib/auth-errors"; import { AUTH_TYPE } from "@/lib/env-config"; import { ValidationError } from "@/lib/error"; import { trackLoginAttempt, trackLoginFailure, trackLoginSuccess } from "@/lib/posthog/events"; @@ -65,10 +65,6 @@ export function LocalLoginForm() { if (err instanceof ValidationError) { trackLoginFailure("local", err.message); setError({ title: err.name, message: err.message }); - toast.error(err.name, { - description: err.message, - duration: 6000, - }); return; } @@ -92,22 +88,6 @@ export function LocalLoginForm() { title: errorDetails.title, message: errorDetails.description, }); - - // Show error toast with conditional retry action - const toastOptions: any = { - description: errorDetails.description, - duration: 6000, - }; - - // Add retry action if the error is retryable - if (shouldRetry(errorCode)) { - toastOptions.action = { - label: "Retry", - onClick: () => handleSubmit(e), - }; - } - - toast.error(errorDetails.title, toastOptions); } }; diff --git a/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentTypeIcon.tsx b/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentTypeIcon.tsx index 92ddb0057..dfd2c6d85 100644 --- a/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentTypeIcon.tsx +++ b/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentTypeIcon.tsx @@ -1,19 +1,51 @@ "use client"; import type React from "react"; -import { useRef, useState, useEffect } from "react"; -import { getConnectorIcon } from "@/contracts/enums/connectorIcons"; +import { useEffect, useRef, useState } from "react"; import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip"; +import { getConnectorIcon } from "@/contracts/enums/connectorIcons"; export function getDocumentTypeIcon(type: string, className?: string): React.ReactNode { return getConnectorIcon(type, className); } export function getDocumentTypeLabel(type: string): string { - return type - .split("_") - .map((word) => word.charAt(0) + word.slice(1).toLowerCase()) - .join(" "); + const labelMap: Record = { + EXTENSION: "Extension", + CRAWLED_URL: "Web Page", + FILE: "File", + SLACK_CONNECTOR: "Slack", + TEAMS_CONNECTOR: "Microsoft Teams", + NOTION_CONNECTOR: "Notion", + YOUTUBE_VIDEO: "YouTube Video", + GITHUB_CONNECTOR: "GitHub", + LINEAR_CONNECTOR: "Linear", + DISCORD_CONNECTOR: "Discord", + JIRA_CONNECTOR: "Jira", + CONFLUENCE_CONNECTOR: "Confluence", + CLICKUP_CONNECTOR: "ClickUp", + GOOGLE_CALENDAR_CONNECTOR: "Google Calendar", + GOOGLE_GMAIL_CONNECTOR: "Gmail", + GOOGLE_DRIVE_FILE: "Google Drive", + AIRTABLE_CONNECTOR: "Airtable", + LUMA_CONNECTOR: "Luma", + ELASTICSEARCH_CONNECTOR: "Elasticsearch", + BOOKSTACK_CONNECTOR: "BookStack", + CIRCLEBACK: "Circleback", + OBSIDIAN_CONNECTOR: "Obsidian", + SURFSENSE_DOCS: "SurfSense Docs", + NOTE: "Note", + COMPOSIO_GOOGLE_DRIVE_CONNECTOR: "Composio Google Drive", + COMPOSIO_GMAIL_CONNECTOR: "Composio Gmail", + COMPOSIO_GOOGLE_CALENDAR_CONNECTOR: "Composio Google Calendar", + }; + return ( + labelMap[type] || + type + .split("_") + .map((word) => word.charAt(0) + word.slice(1).toLowerCase()) + .join(" ") + ); } export function DocumentTypeChip({ type, className }: { type: string; className?: string }) { diff --git a/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentsTableShell.tsx b/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentsTableShell.tsx index a44295ec0..02c359be9 100644 --- a/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentsTableShell.tsx +++ b/surfsense_web/app/dashboard/[search_space_id]/documents/(manage)/components/DocumentsTableShell.tsx @@ -11,14 +11,13 @@ import { Clock, FileText, FileX, - Loader2, Network, Plus, User, } from "lucide-react"; import { motion } from "motion/react"; import { useTranslations } from "next-intl"; -import React, { useRef, useState, useEffect, useCallback } from "react"; +import React, { useCallback, useEffect, useRef, useState } from "react"; import { useDocumentUploadDialog } from "@/components/assistant-ui/document-upload-popup"; import { JsonMetadataViewer } from "@/components/json-metadata-viewer"; import { MarkdownViewer } from "@/components/markdown-viewer"; @@ -354,11 +353,11 @@ export function DocumentsTableShell({ - + {columnVisibility.document_type && ( - + )} @@ -396,11 +395,11 @@ export function DocumentsTableShell({ - + {columnVisibility.document_type && ( - + )} @@ -499,7 +498,7 @@ export function DocumentsTableShell({ /> - + {columnVisibility.document_type && ( - + - + - - - {isComposer && !isProcessing && } - - - {isProcessing ? ( - - - Processing... - - ) : ( - - )} - - - ); -}; - -const AttachmentRemove: FC = () => { - return ( - - - - - - ); -}; - -/** - * Image attachment with preview thumbnail (click to expand) - */ -const MessageImageAttachment: FC = () => { - const attachmentName = useAssistantState(({ attachment }) => attachment?.name || "Image"); - const src = useAttachmentSrc(); - - if (!src) return null; - - return ( - -
- {attachmentName} - {/* Hover overlay with filename */} -
-
- - {attachmentName} - -
-
-
- - ); -}; - -/** - * Document/file attachment as chip (similar to mentioned documents) - */ -const MessageDocumentAttachment: FC = () => { - const attachmentName = useAssistantState(({ attachment }) => attachment?.name || "Attachment"); - - return ( - - - - {attachmentName} - - - ); -}; - -/** - * Attachment component for user messages - * Shows image preview for images, chip for documents - */ -const MessageAttachmentChip: FC = () => { - const isImage = useAssistantState(({ attachment }) => attachment?.type === "image"); - - if (isImage) { - return ; - } - - return ; -}; - -export const UserMessageAttachments: FC = () => { - return ; -}; - -export const ComposerAttachments: FC = () => { - return ( -
- -
- ); -}; - -export const ComposerAddAttachment: FC = () => { - const chatAttachmentInputRef = useRef(null); - const { openDialog } = useDocumentUploadDialog(); - - const handleFileUpload = () => { - openDialog(); - }; - - const handleChatAttachment = () => { - chatAttachmentInputRef.current?.click(); - }; - - // Prevent event bubbling when file input is clicked - const handleFileInputClick = (e: React.MouseEvent) => { - e.stopPropagation(); - }; - - return ( - <> - - - - - - - - - - Add attachment to this chat - - - - Upload documents to Search Space - - - - - - - - ); -}; diff --git a/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx b/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx index b885f35da..11760bb30 100644 --- a/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx +++ b/surfsense_web/components/assistant-ui/connector-popup/connector-configs/views/indexing-configuration-view.tsx @@ -122,10 +122,12 @@ export const IndexingConfigurationView: FC = ({
{getConnectorTypeDisplay(connector?.connector_type || "")} Connected ! - {" "} - - {getConnectorDisplayName(connector?.name || "")} + {connector?.name?.includes(" - ") && ( + + {getConnectorDisplayName(connector.name)} + + )}

Configure when to start syncing your data diff --git a/surfsense_web/components/assistant-ui/inline-mention-editor.tsx b/surfsense_web/components/assistant-ui/inline-mention-editor.tsx index 437e5a7a5..b8194c91f 100644 --- a/surfsense_web/components/assistant-ui/inline-mention-editor.tsx +++ b/surfsense_web/components/assistant-ui/inline-mention-editor.tsx @@ -27,6 +27,12 @@ export interface InlineMentionEditorRef { getText: () => string; getMentionedDocuments: () => MentionedDocument[]; insertDocumentChip: (doc: Pick) => void; + setDocumentChipStatus: ( + docId: number, + docType: string | undefined, + statusLabel: string | null, + statusKind?: "pending" | "processing" | "ready" | "failed" + ) => void; } interface InlineMentionEditorProps { @@ -46,6 +52,7 @@ interface InlineMentionEditorProps { const CHIP_DATA_ATTR = "data-mention-chip"; const CHIP_ID_ATTR = "data-mention-id"; const CHIP_DOCTYPE_ATTR = "data-mention-doctype"; +const CHIP_STATUS_ATTR = "data-mention-status"; /** * Type guard to check if a node is a chip element @@ -182,6 +189,11 @@ export const InlineMentionEditor = forwardRef { + if (!editorRef.current) return; + + const chips = editorRef.current.querySelectorAll( + `span[${CHIP_DATA_ATTR}="true"]` + ); + for (const chip of chips) { + const chipId = getChipId(chip); + const chipType = getChipDocType(chip); + if (chipId !== docId) continue; + if ((docType ?? "UNKNOWN") !== chipType) continue; + + const statusEl = chip.querySelector(`span[${CHIP_STATUS_ATTR}="true"]`); + if (!statusEl) continue; + + if (!statusLabel) { + statusEl.textContent = ""; + statusEl.className = "text-[10px] font-semibold opacity-80 hidden"; + continue; + } + + const statusClass = + statusKind === "failed" + ? "text-destructive" + : statusKind === "processing" + ? "text-amber-700" + : statusKind === "ready" + ? "text-emerald-700" + : "text-amber-700"; + statusEl.textContent = statusLabel; + statusEl.className = `text-[10px] font-semibold opacity-80 ${statusClass}`; + } + }, + [] + ); + // Expose methods via ref useImperativeHandle(ref, () => ({ focus: () => editorRef.current?.focus(), @@ -339,6 +394,7 @@ export const InlineMentionEditor = forwardRef; header?: React.ReactNode; @@ -230,8 +246,13 @@ const Composer: FC = () => { const [mentionedDocuments, setMentionedDocuments] = useAtom(mentionedDocumentsAtom); const [showDocumentPopover, setShowDocumentPopover] = useState(false); const [mentionQuery, setMentionQuery] = useState(""); + const [uploadedMentionDocs, setUploadedMentionDocs] = useState< + Record + >({}); + const [isUploadingDocs, setIsUploadingDocs] = useState(false); const editorRef = useRef(null); const editorContainerRef = useRef(null); + const uploadInputRef = useRef(null); const documentPickerRef = useRef(null); const { search_space_id, chat_id } = useParams(); const setMentionedDocumentIds = useSetAtom(mentionedDocumentIdsAtom); @@ -357,9 +378,28 @@ const Composer: FC = () => { [showDocumentPopover] ); + const uploadedMentionedDocs = useMemo( + () => mentionedDocuments.filter((doc) => uploadedMentionDocs[doc.id]), + [mentionedDocuments, uploadedMentionDocs] + ); + + const blockingUploadedMentions = useMemo( + () => + uploadedMentionedDocs.filter((doc) => { + const state = uploadedMentionDocs[doc.id]?.state; + return state === "pending" || state === "processing" || state === "failed"; + }), + [uploadedMentionedDocs, uploadedMentionDocs] + ); + // Submit message (blocked during streaming, document picker open, or AI responding to another user) const handleSubmit = useCallback(() => { - if (isThreadRunning || isBlockedByOtherUser) { + if ( + isThreadRunning || + isBlockedByOtherUser || + isUploadingDocs || + blockingUploadedMentions.length > 0 + ) { return; } if (!showDocumentPopover) { @@ -375,6 +415,8 @@ const Composer: FC = () => { showDocumentPopover, isThreadRunning, isBlockedByOtherUser, + isUploadingDocs, + blockingUploadedMentions.length, composerRuntime, setMentionedDocuments, setMentionedDocumentIds, @@ -395,6 +437,11 @@ const Composer: FC = () => { }); return updated; }); + setUploadedMentionDocs((prev) => { + if (!(docId in prev)) return prev; + const { [docId]: _removed, ...rest } = prev; + return rest; + }); }, [setMentionedDocuments, setMentionedDocumentIds] ); @@ -433,6 +480,139 @@ const Composer: FC = () => { [mentionedDocuments, setMentionedDocuments, setMentionedDocumentIds] ); + const refreshUploadedDocStatuses = useCallback( + async (documentIds: number[]) => { + if (!search_space_id || documentIds.length === 0) return; + const statusResponse = await documentsApiService.getDocumentsStatus({ + queryParams: { + search_space_id: Number(search_space_id), + document_ids: documentIds, + }, + }); + + setUploadedMentionDocs((prev) => { + const next = { ...prev }; + for (const item of statusResponse.items) { + next[item.id] = { + id: item.id, + title: item.title, + document_type: item.document_type, + state: item.status.state, + reason: item.status.reason, + }; + } + return next; + }); + + handleDocumentsMention( + statusResponse.items.map((item) => ({ + id: item.id, + title: item.title, + document_type: item.document_type, + })) + ); + }, + [search_space_id, handleDocumentsMention] + ); + + const handleUploadClick = useCallback(() => { + uploadInputRef.current?.click(); + }, []); + + const handleUploadInputChange = useCallback( + async (event: React.ChangeEvent) => { + const files = Array.from(event.target.files ?? []); + event.target.value = ""; + if (files.length === 0 || !search_space_id) return; + + setIsUploadingDocs(true); + try { + const uploadResponse = await documentsApiService.uploadDocument({ + files, + search_space_id: Number(search_space_id), + }); + const uploadedIds = uploadResponse.document_ids ?? []; + const duplicateIds = uploadResponse.duplicate_document_ids ?? []; + const idsToMention = Array.from(new Set([...uploadedIds, ...duplicateIds])); + if (idsToMention.length === 0) { + toast.warning("No documents were created or matched from selected files."); + return; + } + + await refreshUploadedDocStatuses(idsToMention); + if (uploadedIds.length > 0 && duplicateIds.length > 0) { + toast.success( + `Uploaded ${uploadedIds.length} file${uploadedIds.length > 1 ? "s" : ""} and matched ${duplicateIds.length} existing file${duplicateIds.length > 1 ? "s" : ""}.` + ); + } else if (uploadedIds.length > 0) { + toast.success(`Uploaded ${uploadedIds.length} file${uploadedIds.length > 1 ? "s" : ""}`); + } else { + toast.success( + `Matched ${duplicateIds.length} existing file${duplicateIds.length > 1 ? "s" : ""} and added mention${duplicateIds.length > 1 ? "s" : ""}.` + ); + } + } catch (error) { + const message = error instanceof Error ? error.message : "Upload failed"; + toast.error(`Upload failed: ${message}`); + } finally { + setIsUploadingDocs(false); + } + }, + [search_space_id, refreshUploadedDocStatuses] + ); + + // Poll status for uploaded mentioned documents until all are ready or removed. + useEffect(() => { + const trackedIds = uploadedMentionedDocs.map((doc) => doc.id); + const needsPolling = trackedIds.some((id) => { + const state = uploadedMentionDocs[id]?.state; + return state === "pending" || state === "processing"; + }); + if (!needsPolling) return; + + const interval = setInterval(() => { + refreshUploadedDocStatuses(trackedIds).catch((error) => { + console.error("[Composer] Failed to refresh uploaded mention statuses:", error); + }); + }, 2500); + + return () => clearInterval(interval); + }, [uploadedMentionedDocs, uploadedMentionDocs, refreshUploadedDocStatuses]); + + // Push upload status directly onto mention chips (instead of separate status rows). + useEffect(() => { + for (const doc of uploadedMentionedDocs) { + const state = uploadedMentionDocs[doc.id]?.state ?? "pending"; + const statusLabel = + state === "ready" + ? null + : state === "failed" + ? "failed" + : state === "processing" + ? "indexing" + : "queued"; + editorRef.current?.setDocumentChipStatus(doc.id, doc.document_type, statusLabel, state); + } + }, [uploadedMentionedDocs, uploadedMentionDocs]); + + // Prune upload status entries that are no longer mentioned in the composer. + useEffect(() => { + const activeIds = new Set(mentionedDocuments.map((doc) => doc.id)); + setUploadedMentionDocs((prev) => { + let changed = false; + const next: Record = {}; + for (const [key, value] of Object.entries(prev)) { + const id = Number(key); + if (activeIds.has(id)) { + next[id] = value; + } else { + changed = true; + } + } + return changed ? next : prev; + }); + }, [mentionedDocuments]); + return ( { currentUserId={currentUser?.id ?? null} members={members ?? []} /> - - +

{/* Inline editor with @mention support */}
{ className="min-h-[24px]" />
+ {/* Document picker popover (portal to body for proper z-index stacking) */} {showDocumentPopover && @@ -483,33 +670,43 @@ const Composer: FC = () => { />, document.body )} - - + uploadedMentionDocs[doc.id]?.state === "failed" + )} + /> +
); }; interface ComposerActionProps { isBlockedByOtherUser?: boolean; + onUploadClick: () => void; + isUploadingDocs: boolean; + blockingUploadedMentionsCount: number; + hasFailedUploadedMentions: boolean; } -const ComposerAction: FC = ({ isBlockedByOtherUser = false }) => { - // Check if any attachments are still being processed (running AND progress < 100) - // When progress is 100, processing is done but waiting for send() - const hasProcessingAttachments = useAssistantState(({ composer }) => - composer.attachments?.some((att) => { - const status = att.status; - if (status?.type !== "running") return false; - const progress = (status as { type: "running"; progress?: number }).progress; - return progress === undefined || progress < 100; - }) - ); +const ComposerAction: FC = ({ + isBlockedByOtherUser = false, + onUploadClick, + isUploadingDocs, + blockingUploadedMentionsCount, + hasFailedUploadedMentions, +}) => { + const mentionedDocuments = useAtomValue(mentionedDocumentsAtom); - // Check if composer text is empty - const isComposerEmpty = useAssistantState(({ composer }) => { + // Check if composer text is empty (chips are represented in mentionedDocuments atom) + const isComposerTextEmpty = useAssistantState(({ composer }) => { const text = composer.text?.trim() || ""; return text.length === 0; }); + const isComposerEmpty = isComposerTextEmpty && mentionedDocuments.length === 0; // Check if a model is configured const { data: userConfigs } = useAtomValue(newLLMConfigsAtom); @@ -530,25 +727,47 @@ const ComposerAction: FC = ({ isBlockedByOtherUser = false }, [preferences, globalConfigs, userConfigs]); const isSendDisabled = - hasProcessingAttachments || isComposerEmpty || !hasModelConfigured || isBlockedByOtherUser; + isComposerEmpty || + !hasModelConfigured || + isBlockedByOtherUser || + isUploadingDocs || + blockingUploadedMentionsCount > 0; return (
- + + {isUploadingDocs ? ( + + ) : ( + + )} +
- {/* Show processing indicator when attachments are being processed */} - {hasProcessingAttachments && ( + {blockingUploadedMentionsCount > 0 && (
- - Processing... + {hasFailedUploadedMentions ? : } + + {hasFailedUploadedMentions + ? "Remove or retry failed uploads" + : "Waiting for uploaded files to finish indexing"} +
)} {/* Show warning when no model is configured */} - {!hasModelConfigured && !hasProcessingAttachments && ( + {!hasModelConfigured && blockingUploadedMentionsCount === 0 && (
Select a model @@ -561,13 +780,17 @@ const ComposerAction: FC = ({ isBlockedByOtherUser = false tooltip={ isBlockedByOtherUser ? "Wait for AI to finish responding" - : !hasModelConfigured - ? "Please select a model from the header to start chatting" - : hasProcessingAttachments - ? "Wait for attachments to process" - : isComposerEmpty - ? "Enter a message to send" - : "Send message" + : hasFailedUploadedMentions + ? "Remove or retry failed uploads before sending" + : blockingUploadedMentionsCount > 0 + ? "Waiting for uploaded files to finish indexing" + : isUploadingDocs + ? "Uploading documents..." + : !hasModelConfigured + ? "Please select a model from the header to start chatting" + : isComposerEmpty + ? "Enter a message to send" + : "Send message" } side="bottom" type="submit" diff --git a/surfsense_web/components/assistant-ui/user-message.tsx b/surfsense_web/components/assistant-ui/user-message.tsx index e70806d44..7ba5b9462 100644 --- a/surfsense_web/components/assistant-ui/user-message.tsx +++ b/surfsense_web/components/assistant-ui/user-message.tsx @@ -3,7 +3,6 @@ import { useAtomValue } from "jotai"; import { FileText, PencilIcon } from "lucide-react"; import { type FC, useState } from "react"; import { messageDocumentsMapAtom } from "@/atoms/chat/mentioned-documents.atom"; -import { UserMessageAttachments } from "@/components/assistant-ui/attachment"; import { TooltipIconButton } from "@/components/assistant-ui/tooltip-icon-button"; interface AuthorMetadata { @@ -48,9 +47,6 @@ export const UserMessage: FC = () => { const mentionedDocs = messageId ? messageDocumentsMap[messageId] : undefined; const metadata = useAssistantState(({ message }) => message?.metadata); const author = metadata?.custom?.author as AuthorMetadata | undefined; - const hasAttachments = useAssistantState( - ({ message }) => message?.attachments && message.attachments.length > 0 - ); return ( { >
- {/* Display attachments and mentioned documents */} - {(hasAttachments || (mentionedDocs && mentionedDocs.length > 0)) && ( + {/* Display mentioned documents */} + {mentionedDocs && mentionedDocs.length > 0 && (
- {/* Attachments (images show as thumbnails, documents as chips) */} - {/* Mentioned documents as chips */} {mentionedDocs?.map((doc) => ( ( export function HeroSection() { const containerRef = useRef(null); const parentRef = useRef(null); - const heroVariant = useFeatureFlagVariantKey("notebooklm_flag"); - const isNotebookLMVariant = heroVariant === "notebooklm"; + const heroVariant = useFeatureFlagVariantKey("notebooklm_superpowers_flag"); + const isNotebookLMVariant = heroVariant === "superpowers"; return (
- NotebookLM for Teams + NotebookLM with Superpowers
) : ( - <> - The AI Workspace{" "} -
-
- Built for Teams -
+
+
+ NotebookLM for Teams
- +
)} {/* // TODO:aCTUAL DESCRITION */}

- Connect any LLM to your internal knowledge sources and chat with it in real time alongside - your team. + Connect any AI to your documents and knowledge sources. +

+

+ Then chat with it in real-time, even alongside your team.

diff --git a/surfsense_web/components/homepage/integrations.tsx b/surfsense_web/components/homepage/integrations.tsx index 53aaf624a..662387de5 100644 --- a/surfsense_web/components/homepage/integrations.tsx +++ b/surfsense_web/components/homepage/integrations.tsx @@ -1,5 +1,7 @@ "use client"; -import React, { useEffect, useState } from "react"; + +import type React from "react"; +import Image from "next/image"; interface Integration { name: string; @@ -8,181 +10,210 @@ interface Integration { const INTEGRATIONS: Integration[] = [ // Search - { name: "Tavily", icon: "https://www.tavily.com/images/logo.svg" }, - { - name: "LinkUp", - icon: "https://framerusercontent.com/images/7zeIm6t3f1HaSltkw8upEvsD80.png?scale-down-to=512", - }, - { name: "Elasticsearch", icon: "https://cdn.simpleicons.org/elastic/00A9E5" }, + { name: "Tavily", icon: "/connectors/tavily.svg" }, + { name: "Elasticsearch", icon: "/connectors/elasticsearch.svg" }, + { name: "Baidu Search", icon: "/connectors/baidu-search.svg" }, + { name: "SearXNG", icon: "/connectors/searxng.svg" }, // Communication - { - name: "Slack", - icon: "https://upload.wikimedia.org/wikipedia/commons/d/d5/Slack_icon_2019.svg", - }, - { name: "Discord", icon: "https://cdn.simpleicons.org/discord/5865F2" }, - { name: "Gmail", icon: "https://cdn.simpleicons.org/gmail/EA4335" }, + { name: "Slack", icon: "/connectors/slack.svg" }, + { name: "Discord", icon: "/connectors/discord.svg" }, + { name: "Gmail", icon: "/connectors/google-gmail.svg" }, + { name: "Microsoft Teams", icon: "/connectors/microsoft-teams.svg" }, // Project Management - { name: "Linear", icon: "https://cdn.simpleicons.org/linear/5E6AD2" }, - { name: "Jira", icon: "https://cdn.simpleicons.org/jira/0052CC" }, - { name: "ClickUp", icon: "https://cdn.simpleicons.org/clickup/7B68EE" }, - { name: "Airtable", icon: "https://cdn.simpleicons.org/airtable/18BFFF" }, + { name: "Linear", icon: "/connectors/linear.svg" }, + { name: "Jira", icon: "/connectors/jira.svg" }, + { name: "ClickUp", icon: "/connectors/clickup.svg" }, + { name: "Airtable", icon: "/connectors/airtable.svg" }, // Documentation & Knowledge - { name: "Confluence", icon: "https://cdn.simpleicons.org/confluence/172B4D" }, - { name: "Notion", icon: "https://cdn.simpleicons.org/notion/000000/ffffff" }, - { name: "Web Pages", icon: "https://cdn.jsdelivr.net/npm/lucide-static@0.294.0/icons/globe.svg" }, + { name: "Confluence", icon: "/connectors/confluence.svg" }, + { name: "Notion", icon: "/connectors/notion.svg" }, + { name: "BookStack", icon: "/connectors/bookstack.svg" }, + { name: "Obsidian", icon: "/connectors/obsidian.svg" }, // Cloud Storage - { name: "Google Drive", icon: "https://cdn.simpleicons.org/googledrive/4285F4" }, - { name: "Dropbox", icon: "https://cdn.simpleicons.org/dropbox/0061FF" }, - { - name: "Amazon S3", - icon: "https://upload.wikimedia.org/wikipedia/commons/b/bc/Amazon-S3-Logo.svg", - }, + { name: "Google Drive", icon: "/connectors/google-drive.svg" }, // Development - { name: "GitHub", icon: "https://cdn.simpleicons.org/github/181717/ffffff" }, + { name: "GitHub", icon: "/connectors/github.svg" }, // Productivity - { name: "Google Calendar", icon: "https://cdn.simpleicons.org/googlecalendar/4285F4" }, - { name: "Luma", icon: "https://images.lumacdn.com/social-images/default-social-202407.png" }, + { name: "Google Calendar", icon: "/connectors/google-calendar.svg" }, + { name: "Luma", icon: "/connectors/luma.svg" }, // Media - { name: "YouTube", icon: "https://cdn.simpleicons.org/youtube/FF0000" }, + { name: "YouTube", icon: "/connectors/youtube.svg" }, + + // Search + { name: "Linkup", icon: "/connectors/linkup.svg" }, + + // Meetings + { name: "Circleback", icon: "/connectors/circleback.svg" }, + + // AI + { name: "MCP", icon: "/connectors/modelcontextprotocol.svg" }, ]; -function SemiCircleOrbit({ radius, centerX, centerY, count, iconSize, startIndex }: any) { +// 5 vertical columns — 23 icons spread across categories +const COLUMNS: number[][] = [ + [2, 5, 10, 0, 21, 11], + [1, 7, 20, 17], + [13, 6, 23, 4, 16], + [12, 8, 15, 18], + [3, 9, 14, 22, 19], +]; + +// Different scroll speeds per column for organic feel (seconds) +const SCROLL_DURATIONS = [26, 32, 22, 30, 28]; + +function IntegrationCard({ integration }: { integration: Integration }) { return ( - <> - {/* Semi-circle glow background */} -
-
+
+ {integration.name} +
+ ); +} + +function ScrollingColumn({ + cards, + scrollUp, + duration, + colIndex, + isEdge, + isEdgeAdjacent, +}: { + cards: number[]; + scrollUp: boolean; + duration: number; + colIndex: number; + isEdge: boolean; + isEdgeAdjacent: boolean; +}) { + // Edge columns get a heavy vertical mask; edge-adjacent columns get a lighter one to smooth the transition + const columnMask = isEdge + ? { + maskImage: + "linear-gradient(to bottom, transparent 0%, transparent 20%, black 40%, black 60%, transparent 80%, transparent 100%)", + WebkitMaskImage: + "linear-gradient(to bottom, transparent 0%, transparent 20%, black 40%, black 60%, transparent 80%, transparent 100%)", + } + : isEdgeAdjacent + ? { + maskImage: + "linear-gradient(to bottom, transparent 0%, transparent 10%, black 30%, black 70%, transparent 90%, transparent 100%)", + WebkitMaskImage: + "linear-gradient(to bottom, transparent 0%, transparent 10%, black 30%, black 70%, transparent 90%, transparent 100%)", + } + : {}; + + const cardSet = cards.map((integrationIndex, i) => ( + + )); + + return ( +
+ {/* Outer div has NO gap — each inner copy uses pb matching the gap so both halves are identical in height → seamless -50% loop */} +
+
+ {cardSet} +
+
+ {cardSet} +
- - {/* Orbit icons */} - {Array.from({ length: count }).map((_, index) => { - const actualIndex = startIndex + index; - // Skip if we've run out of integrations - if (actualIndex >= INTEGRATIONS.length) return null; - - const angle = (index / (count - 1)) * 180; - const x = radius * Math.cos((angle * Math.PI) / 180); - const y = radius * Math.sin((angle * Math.PI) / 180); - const integration = INTEGRATIONS[actualIndex]; - - // Tooltip positioning — above or below based on angle - const tooltipAbove = angle > 90; - - return ( -
- {integration.name} - - {/* Tooltip */} - -
- ); - })} - +
); } export default function ExternalIntegrations() { - const [size, setSize] = useState({ width: 0, height: 0 }); - - useEffect(() => { - const updateSize = () => setSize({ width: window.innerWidth, height: window.innerHeight }); - updateSize(); - window.addEventListener("resize", updateSize); - return () => window.removeEventListener("resize", updateSize); - }, []); - - const baseWidth = Math.min(size.width * 0.8, 700); - const centerX = baseWidth / 2; - const centerY = baseWidth * 0.5; - - const iconSize = - size.width < 480 - ? Math.max(24, baseWidth * 0.05) - : size.width < 768 - ? Math.max(28, baseWidth * 0.06) - : Math.max(32, baseWidth * 0.07); - return ( -
-
-

Integrations

-

- Integrate with your team's most important tools -

+
+ {/* Heading */} +
+

+ Integrate with your +
+ team's most important tools +

+
-
- - - + {/* Scrolling columns container — masked at edges so the page background shows through seamlessly */} +
+ {/* 5 scrolling columns */} +
+ {COLUMNS.map((column, colIndex) => ( + + ))}
diff --git a/surfsense_web/components/json-metadata-viewer.tsx b/surfsense_web/components/json-metadata-viewer.tsx index faab000ad..cc87a75c5 100644 --- a/surfsense_web/components/json-metadata-viewer.tsx +++ b/surfsense_web/components/json-metadata-viewer.tsx @@ -1,4 +1,4 @@ -import { FileJson, Loader2 } from "lucide-react"; +import { FileJson } from "lucide-react"; import React from "react"; import { defaultStyles, JsonView } from "react-json-view-lite"; import { Button } from "@/components/ui/button"; @@ -9,6 +9,7 @@ import { DialogTitle, DialogTrigger, } from "@/components/ui/dialog"; +import { Spinner } from "@/components/ui/spinner"; import "react-json-view-lite/dist/index.css"; interface JsonMetadataViewerProps { @@ -58,7 +59,7 @@ export function JsonMetadataViewer({
{loading ? (
- +
) : ( diff --git a/surfsense_web/components/layout/hooks/SidebarContext.tsx b/surfsense_web/components/layout/hooks/SidebarContext.tsx index 35f76929d..bfb5b5aeb 100644 --- a/surfsense_web/components/layout/hooks/SidebarContext.tsx +++ b/surfsense_web/components/layout/hooks/SidebarContext.tsx @@ -6,6 +6,7 @@ interface SidebarContextValue { isCollapsed: boolean; setIsCollapsed: (collapsed: boolean) => void; toggleCollapsed: () => void; + sidebarWidth: number; } const SidebarContext = createContext(null); diff --git a/surfsense_web/components/layout/hooks/useSidebarResize.ts b/surfsense_web/components/layout/hooks/useSidebarResize.ts new file mode 100644 index 000000000..887c86dce --- /dev/null +++ b/surfsense_web/components/layout/hooks/useSidebarResize.ts @@ -0,0 +1,101 @@ +"use client"; + +import { useCallback, useEffect, useRef, useState } from "react"; + +const SIDEBAR_WIDTH_COOKIE_NAME = "sidebar_width"; +const SIDEBAR_WIDTH_COOKIE_MAX_AGE = 60 * 60 * 24 * 365; // 1 year + +export const SIDEBAR_MIN_WIDTH = 240; +export const SIDEBAR_MAX_WIDTH = 480; + +interface UseSidebarResizeReturn { + sidebarWidth: number; + handleMouseDown: (e: React.MouseEvent) => void; + isDragging: boolean; +} + +export function useSidebarResize(defaultWidth = SIDEBAR_MIN_WIDTH): UseSidebarResizeReturn { + const [sidebarWidth, setSidebarWidth] = useState(defaultWidth); + const [isDragging, setIsDragging] = useState(false); + + const startXRef = useRef(0); + const startWidthRef = useRef(defaultWidth); + + // Initialize from cookie on mount + useEffect(() => { + try { + const match = document.cookie.match(/(?:^|; )sidebar_width=([^;]+)/); + if (match) { + const parsed = Number(match[1]); + if (!Number.isNaN(parsed) && parsed >= SIDEBAR_MIN_WIDTH && parsed <= SIDEBAR_MAX_WIDTH) { + setSidebarWidth(parsed); + } + } + } catch { + // Ignore cookie read errors + } + }, []); + + // Persist width to cookie + const persistWidth = useCallback((width: number) => { + try { + document.cookie = `${SIDEBAR_WIDTH_COOKIE_NAME}=${width}; path=/; max-age=${SIDEBAR_WIDTH_COOKIE_MAX_AGE}`; + } catch { + // Ignore cookie write errors + } + }, []); + + const handleMouseDown = useCallback( + (e: React.MouseEvent) => { + e.preventDefault(); + startXRef.current = e.clientX; + startWidthRef.current = sidebarWidth; + setIsDragging(true); + + document.body.style.cursor = "col-resize"; + document.body.style.userSelect = "none"; + }, + [sidebarWidth] + ); + + useEffect(() => { + if (!isDragging) return; + + const handleMouseMove = (e: MouseEvent) => { + const delta = e.clientX - startXRef.current; + const newWidth = Math.min( + SIDEBAR_MAX_WIDTH, + Math.max(SIDEBAR_MIN_WIDTH, startWidthRef.current + delta) + ); + setSidebarWidth(newWidth); + }; + + const handleMouseUp = () => { + setIsDragging(false); + document.body.style.cursor = ""; + document.body.style.userSelect = ""; + + // Persist the final width + setSidebarWidth((currentWidth) => { + persistWidth(currentWidth); + return currentWidth; + }); + }; + + document.addEventListener("mousemove", handleMouseMove); + document.addEventListener("mouseup", handleMouseUp); + + return () => { + document.removeEventListener("mousemove", handleMouseMove); + document.removeEventListener("mouseup", handleMouseUp); + document.body.style.cursor = ""; + document.body.style.userSelect = ""; + }; + }, [isDragging, persistWidth]); + + return { + sidebarWidth, + handleMouseDown, + isDragging, + }; +} diff --git a/surfsense_web/components/layout/providers/LayoutDataProvider.tsx b/surfsense_web/components/layout/providers/LayoutDataProvider.tsx index ead017a3e..ed96b84ca 100644 --- a/surfsense_web/components/layout/providers/LayoutDataProvider.tsx +++ b/surfsense_web/components/layout/providers/LayoutDataProvider.tsx @@ -25,16 +25,14 @@ import { Input } from "@/components/ui/input"; import { isPageLimitExceededMetadata } from "@/contracts/types/inbox.types"; import { useInbox } from "@/hooks/use-inbox"; import { searchSpacesApiService } from "@/lib/apis/search-spaces-api.service"; -import { deleteThread, fetchThreads, updateThread } from "@/lib/chat/thread-persistence"; import { logout } from "@/lib/auth-utils"; +import { deleteThread, fetchThreads, updateThread } from "@/lib/chat/thread-persistence"; import { cleanupElectric } from "@/lib/electric/client"; import { resetUser, trackLogout } from "@/lib/posthog/events"; import { cacheKeys } from "@/lib/query-client/cache-keys"; import type { ChatItem, NavItem, SearchSpace } from "../types/layout.types"; import { CreateSearchSpaceDialog } from "../ui/dialogs"; import { LayoutShell } from "../ui/shell"; -import { AllPrivateChatsSidebar } from "../ui/sidebar/AllPrivateChatsSidebar"; -import { AllSharedChatsSidebar } from "../ui/sidebar/AllSharedChatsSidebar"; interface LayoutDataProviderProps { searchSpaceId: string; @@ -390,7 +388,13 @@ export function LayoutDataProvider({ (item: NavItem) => { // Handle inbox specially - toggle sidebar instead of navigating if (item.url === "#inbox") { - setIsInboxSidebarOpen((prev) => !prev); + setIsInboxSidebarOpen((prev) => { + if (!prev) { + setIsAllSharedChatsSidebarOpen(false); + setIsAllPrivateChatsSidebarOpen(false); + } + return !prev; + }); return; } router.push(item.url); @@ -490,10 +494,14 @@ export function LayoutDataProvider({ const handleViewAllSharedChats = useCallback(() => { setIsAllSharedChatsSidebarOpen(true); + setIsAllPrivateChatsSidebarOpen(false); + setIsInboxSidebarOpen(false); }, []); const handleViewAllPrivateChats = useCallback(() => { setIsAllPrivateChatsSidebarOpen(true); + setIsAllSharedChatsSidebarOpen(false); + setIsInboxSidebarOpen(false); }, []); // Delete handlers @@ -614,6 +622,16 @@ export function LayoutDataProvider({ isDocked: isInboxDocked, onDockedChange: setIsInboxDocked, }} + allSharedChatsPanel={{ + open: isAllSharedChatsSidebarOpen, + onOpenChange: setIsAllSharedChatsSidebarOpen, + searchSpaceId, + }} + allPrivateChatsPanel={{ + open: isAllPrivateChatsSidebarOpen, + onOpenChange: setIsAllPrivateChatsSidebarOpen, + searchSpaceId, + }} > {children} @@ -796,20 +814,6 @@ export function LayoutDataProvider({ - {/* All Shared Chats Sidebar */} - - - {/* All Private Chats Sidebar */} - - {/* Create Search Space Dialog */} void; + searchSpaceId: string; + }; + allPrivateChatsPanel?: { + open: boolean; + onOpenChange: (open: boolean) => void; + searchSpaceId: string; + }; } export function LayoutShell({ @@ -112,15 +131,22 @@ export function LayoutShell({ className, inbox, isLoadingChats = false, + allSharedChatsPanel, + allPrivateChatsPanel, }: LayoutShellProps) { const isMobile = useIsMobile(); const [mobileMenuOpen, setMobileMenuOpen] = useState(false); const { isCollapsed, setIsCollapsed, toggleCollapsed } = useSidebarState(defaultCollapsed); + const { + sidebarWidth, + handleMouseDown: onResizeMouseDown, + isDragging: isResizing, + } = useSidebarResize(); // Memoize context value to prevent unnecessary re-renders const sidebarContextValue = useMemo( - () => ({ isCollapsed, setIsCollapsed, toggleCollapsed }), - [isCollapsed, setIsCollapsed, toggleCollapsed] + () => ({ isCollapsed, setIsCollapsed, toggleCollapsed, sidebarWidth }), + [isCollapsed, setIsCollapsed, toggleCollapsed, sidebarWidth] ); // Mobile layout @@ -236,6 +262,9 @@ export function LayoutShell({ setTheme={setTheme} className="hidden md:flex border-r shrink-0" isLoadingChats={isLoadingChats} + sidebarWidth={sidebarWidth} + onResizeMouseDown={onResizeMouseDown} + isResizing={isResizing} /> {/* Docked Inbox Sidebar - renders as flex sibling between sidebar and content */} @@ -275,6 +304,24 @@ export function LayoutShell({ onDockedChange={inbox.onDockedChange} /> )} + + {/* All Shared Chats - slide-out panel */} + {allSharedChatsPanel && ( + + )} + + {/* All Private Chats - slide-out panel */} + {allPrivateChatsPanel && ( + + )}
diff --git a/surfsense_web/components/layout/ui/sidebar/AllPrivateChatsSidebar.tsx b/surfsense_web/components/layout/ui/sidebar/AllPrivateChatsSidebar.tsx index 1d4f590bd..3dd77ea1d 100644 --- a/surfsense_web/components/layout/ui/sidebar/AllPrivateChatsSidebar.tsx +++ b/surfsense_web/components/layout/ui/sidebar/AllPrivateChatsSidebar.tsx @@ -12,11 +12,9 @@ import { User, X, } from "lucide-react"; -import { AnimatePresence, motion } from "motion/react"; import { useParams, useRouter } from "next/navigation"; import { useTranslations } from "next-intl"; import { useCallback, useEffect, useMemo, useState } from "react"; -import { createPortal } from "react-dom"; import { toast } from "sonner"; import { Button } from "@/components/ui/button"; import { @@ -40,6 +38,7 @@ import { updateThread, } from "@/lib/chat/thread-persistence"; import { cn } from "@/lib/utils"; +import { SidebarSlideOutPanel } from "./SidebarSlideOutPanel"; interface AllPrivateChatsSidebarProps { open: boolean; @@ -69,16 +68,11 @@ export function AllPrivateChatsSidebar({ const [archivingThreadId, setArchivingThreadId] = useState(null); const [searchQuery, setSearchQuery] = useState(""); const [showArchived, setShowArchived] = useState(false); - const [mounted, setMounted] = useState(false); const [openDropdownId, setOpenDropdownId] = useState(null); const debouncedSearchQuery = useDebouncedValue(searchQuery, 300); const isSearchMode = !!debouncedSearchQuery.trim(); - useEffect(() => { - setMounted(true); - }, []); - useEffect(() => { const handleEscape = (e: KeyboardEvent) => { if (e.key === "Escape" && open) { @@ -89,17 +83,6 @@ export function AllPrivateChatsSidebar({ return () => document.removeEventListener("keydown", handleEscape); }, [open, onOpenChange]); - useEffect(() => { - if (open) { - document.body.style.overflow = "hidden"; - } else { - document.body.style.overflow = ""; - } - return () => { - document.body.style.overflow = ""; - }; - }, [open]); - const { data: threadsData, error: threadsError, @@ -214,248 +197,221 @@ export function AllPrivateChatsSidebar({ const activeCount = activeChats.length; const archivedCount = archivedChats.length; - if (!mounted) return null; + return ( + +
+
+ +

{t("chats") || "Private Chats"}

+
- return createPortal( - - {open && ( - <> - onOpenChange(false)} - aria-hidden="true" +
+ + setSearchQuery(e.target.value)} + className="pl-9 pr-8 h-9" /> + {searchQuery && ( + + )} +
+
- -
-
- -

{t("chats") || "Private Chats"}

-
- -
- - setSearchQuery(e.target.value)} - className="pl-9 pr-8 h-9" - /> - {searchQuery && ( - - )} -
-
- - {!isSearchMode && ( - setShowArchived(value === "archived")} - className="shrink-0 mx-4" - > - - - - - Active - - {activeCount} - - - - - - - Archived - - {archivedCount} - - - - - - )} - -
- {isLoading ? ( -
- {[75, 90, 55, 80, 65, 85].map((titleWidth, i) => ( -
- - -
- ))} -
- ) : error ? ( -
- {t("error_loading_chats") || "Error loading chats"} -
- ) : threads.length > 0 ? ( -
- {threads.map((thread) => { - const isDeleting = deletingThreadId === thread.id; - const isArchiving = archivingThreadId === thread.id; - const isBusy = isDeleting || isArchiving; - const isActive = currentChatId === thread.id; - - return ( -
- {isMobile ? ( - - ) : ( - - - - - -

- {t("updated") || "Updated"}:{" "} - {format(new Date(thread.updatedAt), "MMM d, yyyy 'at' h:mm a")} -

- - - )} - - setOpenDropdownId(isOpen ? thread.id : null)} - > - - - - - handleToggleArchive(thread.id, thread.archived)} - disabled={isArchiving} - > - {thread.archived ? ( - <> - - {t("unarchive") || "Restore"} - - ) : ( - <> - - {t("archive") || "Archive"} - - )} - - - handleDeleteThread(thread.id)} - className="text-destructive focus:text-destructive" - > - - {t("delete") || "Delete"} - - - -
- ); - })} -
- ) : isSearchMode ? ( -
- -

- {t("no_chats_found") || "No chats found"} -

-

- {t("try_different_search") || "Try a different search term"} -

-
- ) : ( -
- -

- {showArchived - ? t("no_archived_chats") || "No archived chats" - : t("no_chats") || "No private chats"} -

- {!showArchived && ( -

- {t("start_new_chat_hint") || "Start a new chat from the chat page"} -

- )} -
- )} -
- - + {!isSearchMode && ( + setShowArchived(value === "archived")} + className="shrink-0 mx-4" + > + + + + + Active + + {activeCount} + + + + + + + Archived + + {archivedCount} + + + + + )} - , - document.body + +
+ {isLoading ? ( +
+ {[75, 90, 55, 80, 65, 85].map((titleWidth, i) => ( +
+ + +
+ ))} +
+ ) : error ? ( +
+ {t("error_loading_chats") || "Error loading chats"} +
+ ) : threads.length > 0 ? ( +
+ {threads.map((thread) => { + const isDeleting = deletingThreadId === thread.id; + const isArchiving = archivingThreadId === thread.id; + const isBusy = isDeleting || isArchiving; + const isActive = currentChatId === thread.id; + + return ( +
+ {isMobile ? ( + + ) : ( + + + + + +

+ {t("updated") || "Updated"}:{" "} + {format(new Date(thread.updatedAt), "MMM d, yyyy 'at' h:mm a")} +

+ + + )} + + setOpenDropdownId(isOpen ? thread.id : null)} + > + + + + + handleToggleArchive(thread.id, thread.archived)} + disabled={isArchiving} + > + {thread.archived ? ( + <> + + {t("unarchive") || "Restore"} + + ) : ( + <> + + {t("archive") || "Archive"} + + )} + + + handleDeleteThread(thread.id)} + className="text-destructive focus:text-destructive" + > + + {t("delete") || "Delete"} + + + +
+ ); + })} +
+ ) : isSearchMode ? ( +
+ +

+ {t("no_chats_found") || "No chats found"} +

+

+ {t("try_different_search") || "Try a different search term"} +

+
+ ) : ( +
+ +

+ {showArchived + ? t("no_archived_chats") || "No archived chats" + : t("no_chats") || "No private chats"} +

+ {!showArchived && ( +

+ {t("start_new_chat_hint") || "Start a new chat from the chat page"} +

+ )} +
+ )} +
+ ); } diff --git a/surfsense_web/components/layout/ui/sidebar/AllSharedChatsSidebar.tsx b/surfsense_web/components/layout/ui/sidebar/AllSharedChatsSidebar.tsx index db7ca73b2..fae9fb05e 100644 --- a/surfsense_web/components/layout/ui/sidebar/AllSharedChatsSidebar.tsx +++ b/surfsense_web/components/layout/ui/sidebar/AllSharedChatsSidebar.tsx @@ -12,11 +12,9 @@ import { Users, X, } from "lucide-react"; -import { AnimatePresence, motion } from "motion/react"; import { useParams, useRouter } from "next/navigation"; import { useTranslations } from "next-intl"; import { useCallback, useEffect, useMemo, useState } from "react"; -import { createPortal } from "react-dom"; import { toast } from "sonner"; import { Button } from "@/components/ui/button"; import { @@ -40,6 +38,7 @@ import { updateThread, } from "@/lib/chat/thread-persistence"; import { cn } from "@/lib/utils"; +import { SidebarSlideOutPanel } from "./SidebarSlideOutPanel"; interface AllSharedChatsSidebarProps { open: boolean; @@ -69,16 +68,11 @@ export function AllSharedChatsSidebar({ const [archivingThreadId, setArchivingThreadId] = useState(null); const [searchQuery, setSearchQuery] = useState(""); const [showArchived, setShowArchived] = useState(false); - const [mounted, setMounted] = useState(false); const [openDropdownId, setOpenDropdownId] = useState(null); const debouncedSearchQuery = useDebouncedValue(searchQuery, 300); const isSearchMode = !!debouncedSearchQuery.trim(); - useEffect(() => { - setMounted(true); - }, []); - useEffect(() => { const handleEscape = (e: KeyboardEvent) => { if (e.key === "Escape" && open) { @@ -89,17 +83,6 @@ export function AllSharedChatsSidebar({ return () => document.removeEventListener("keydown", handleEscape); }, [open, onOpenChange]); - useEffect(() => { - if (open) { - document.body.style.overflow = "hidden"; - } else { - document.body.style.overflow = ""; - } - return () => { - document.body.style.overflow = ""; - }; - }, [open]); - const { data: threadsData, error: threadsError, @@ -214,248 +197,221 @@ export function AllSharedChatsSidebar({ const activeCount = activeChats.length; const archivedCount = archivedChats.length; - if (!mounted) return null; + return ( + +
+
+ +

{t("shared_chats") || "Shared Chats"}

+
- return createPortal( - - {open && ( - <> - onOpenChange(false)} - aria-hidden="true" +
+ + setSearchQuery(e.target.value)} + className="pl-9 pr-8 h-9" /> + {searchQuery && ( + + )} +
+
- -
-
- -

{t("shared_chats") || "Shared Chats"}

-
- -
- - setSearchQuery(e.target.value)} - className="pl-9 pr-8 h-9" - /> - {searchQuery && ( - - )} -
-
- - {!isSearchMode && ( - setShowArchived(value === "archived")} - className="shrink-0 mx-4" - > - - - - - Active - - {activeCount} - - - - - - - Archived - - {archivedCount} - - - - - - )} - -
- {isLoading ? ( -
- {[75, 90, 55, 80, 65, 85].map((titleWidth, i) => ( -
- - -
- ))} -
- ) : error ? ( -
- {t("error_loading_chats") || "Error loading chats"} -
- ) : threads.length > 0 ? ( -
- {threads.map((thread) => { - const isDeleting = deletingThreadId === thread.id; - const isArchiving = archivingThreadId === thread.id; - const isBusy = isDeleting || isArchiving; - const isActive = currentChatId === thread.id; - - return ( -
- {isMobile ? ( - - ) : ( - - - - - -

- {t("updated") || "Updated"}:{" "} - {format(new Date(thread.updatedAt), "MMM d, yyyy 'at' h:mm a")} -

- - - )} - - setOpenDropdownId(isOpen ? thread.id : null)} - > - - - - - handleToggleArchive(thread.id, thread.archived)} - disabled={isArchiving} - > - {thread.archived ? ( - <> - - {t("unarchive") || "Restore"} - - ) : ( - <> - - {t("archive") || "Archive"} - - )} - - - handleDeleteThread(thread.id)} - className="text-destructive focus:text-destructive" - > - - {t("delete") || "Delete"} - - - -
- ); - })} -
- ) : isSearchMode ? ( -
- -

- {t("no_chats_found") || "No chats found"} -

-

- {t("try_different_search") || "Try a different search term"} -

-
- ) : ( -
- -

- {showArchived - ? t("no_archived_chats") || "No archived chats" - : t("no_shared_chats") || "No shared chats"} -

- {!showArchived && ( -

- Share a chat to collaborate with your team -

- )} -
- )} -
- - + {!isSearchMode && ( + setShowArchived(value === "archived")} + className="shrink-0 mx-4" + > + + + + + Active + + {activeCount} + + + + + + + Archived + + {archivedCount} + + + + + )} - , - document.body + +
+ {isLoading ? ( +
+ {[75, 90, 55, 80, 65, 85].map((titleWidth, i) => ( +
+ + +
+ ))} +
+ ) : error ? ( +
+ {t("error_loading_chats") || "Error loading chats"} +
+ ) : threads.length > 0 ? ( +
+ {threads.map((thread) => { + const isDeleting = deletingThreadId === thread.id; + const isArchiving = archivingThreadId === thread.id; + const isBusy = isDeleting || isArchiving; + const isActive = currentChatId === thread.id; + + return ( +
+ {isMobile ? ( + + ) : ( + + + + + +

+ {t("updated") || "Updated"}:{" "} + {format(new Date(thread.updatedAt), "MMM d, yyyy 'at' h:mm a")} +

+ + + )} + + setOpenDropdownId(isOpen ? thread.id : null)} + > + + + + + handleToggleArchive(thread.id, thread.archived)} + disabled={isArchiving} + > + {thread.archived ? ( + <> + + {t("unarchive") || "Restore"} + + ) : ( + <> + + {t("archive") || "Archive"} + + )} + + + handleDeleteThread(thread.id)} + className="text-destructive focus:text-destructive" + > + + {t("delete") || "Delete"} + + + +
+ ); + })} +
+ ) : isSearchMode ? ( +
+ +

+ {t("no_chats_found") || "No chats found"} +

+

+ {t("try_different_search") || "Try a different search term"} +

+
+ ) : ( +
+ +

+ {showArchived + ? t("no_archived_chats") || "No archived chats" + : t("no_shared_chats") || "No shared chats"} +

+ {!showArchived && ( +

+ Share a chat to collaborate with your team +

+ )} +
+ )} +
+ ); } diff --git a/surfsense_web/components/layout/ui/sidebar/InboxSidebar.tsx b/surfsense_web/components/layout/ui/sidebar/InboxSidebar.tsx index b6caed330..ce64adae9 100644 --- a/surfsense_web/components/layout/ui/sidebar/InboxSidebar.tsx +++ b/surfsense_web/components/layout/ui/sidebar/InboxSidebar.tsx @@ -19,7 +19,6 @@ import { Search, X, } from "lucide-react"; -import { AnimatePresence, motion } from "motion/react"; import { useParams, useRouter } from "next/navigation"; import { useTranslations } from "next-intl"; import { useCallback, useEffect, useMemo, useRef, useState } from "react"; @@ -53,17 +52,13 @@ import { isNewMentionMetadata, isPageLimitExceededMetadata, } from "@/contracts/types/inbox.types"; -import type { InboxItem } from "@/hooks/use-inbox"; import { useDebouncedValue } from "@/hooks/use-debounced-value"; +import type { InboxItem } from "@/hooks/use-inbox"; import { useMediaQuery } from "@/hooks/use-media-query"; import { notificationsApiService } from "@/lib/apis/notifications-api.service"; import { cacheKeys } from "@/lib/query-client/cache-keys"; import { cn } from "@/lib/utils"; -import { useSidebarContextSafe } from "../../hooks"; - -// Sidebar width constants -const SIDEBAR_COLLAPSED_WIDTH = 60; -const SIDEBAR_EXPANDED_WIDTH = 240; +import { SidebarSlideOutPanel } from "./SidebarSlideOutPanel"; /** * Get initials from name or email for avatar fallback @@ -561,13 +556,6 @@ export function InboxSidebar({ }; }; - // Get sidebar collapsed state from context (provided by LayoutShell) - const sidebarContext = useSidebarContextSafe(); - const isCollapsed = sidebarContext?.isCollapsed ?? false; - - // Calculate the left position for the inbox panel (relative to sidebar) - const sidebarWidth = isCollapsed ? SIDEBAR_COLLAPSED_WIDTH : SIDEBAR_EXPANDED_WIDTH; - if (!mounted) return null; // Shared content component for both docked and floating modes @@ -1126,49 +1114,8 @@ export function InboxSidebar({ // FLOATING MODE: Render with animation and click-away layer return ( - - {open && ( - <> - {/* Click-away layer - only covers the content area, not the sidebar */} - onOpenChange(false)} - aria-hidden="true" - /> - - {/* Clip container - positioned at sidebar edge with overflow hidden */} -
- - {inboxContent} - -
- - )} - + + {inboxContent} + ); } diff --git a/surfsense_web/components/layout/ui/sidebar/Sidebar.tsx b/surfsense_web/components/layout/ui/sidebar/Sidebar.tsx index 883fa5890..aee98a290 100644 --- a/surfsense_web/components/layout/ui/sidebar/Sidebar.tsx +++ b/surfsense_web/components/layout/ui/sidebar/Sidebar.tsx @@ -6,6 +6,7 @@ import { Button } from "@/components/ui/button"; import { Skeleton } from "@/components/ui/skeleton"; import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip"; import { cn } from "@/lib/utils"; +import { SIDEBAR_MIN_WIDTH } from "../../hooks/useSidebarResize"; import type { ChatItem, NavItem, PageUsage, SearchSpace, User } from "../../types/layout.types"; import { ChatListItem } from "./ChatListItem"; import { NavSection } from "./NavSection"; @@ -51,6 +52,9 @@ interface SidebarProps { className?: string; isLoadingChats?: boolean; disableTooltips?: boolean; + sidebarWidth?: number; + onResizeMouseDown?: (e: React.MouseEvent) => void; + isResizing?: boolean; } export function Sidebar({ @@ -80,17 +84,29 @@ export function Sidebar({ className, isLoadingChats = false, disableTooltips = false, + sidebarWidth = SIDEBAR_MIN_WIDTH, + onResizeMouseDown, + isResizing = false, }: SidebarProps) { const t = useTranslations("sidebar"); return (
+ {/* Resize handle on right border */} + {!isCollapsed && onResizeMouseDown && ( +
+ )} {/* Header - search space name or collapse button when collapsed */} {isCollapsed ? (
diff --git a/surfsense_web/components/layout/ui/sidebar/SidebarSlideOutPanel.tsx b/surfsense_web/components/layout/ui/sidebar/SidebarSlideOutPanel.tsx new file mode 100644 index 000000000..beb1c81c0 --- /dev/null +++ b/surfsense_web/components/layout/ui/sidebar/SidebarSlideOutPanel.tsx @@ -0,0 +1,82 @@ +"use client"; + +import { AnimatePresence, motion } from "motion/react"; +import { useMediaQuery } from "@/hooks/use-media-query"; +import { cn } from "@/lib/utils"; +import { useSidebarContextSafe } from "../../hooks"; + +const SIDEBAR_COLLAPSED_WIDTH = 60; + +interface SidebarSlideOutPanelProps { + open: boolean; + onOpenChange: (open: boolean) => void; + ariaLabel: string; + width?: number; + children: React.ReactNode; +} + +/** + * Reusable slide-out panel that appears from the right edge of the sidebar. + * Used by InboxSidebar (floating mode), AllSharedChatsSidebar, and AllPrivateChatsSidebar. + * + * Must be rendered inside a positioned container (the LayoutShell's relative flex container) + * and within the SidebarProvider context. + */ +export function SidebarSlideOutPanel({ + open, + onOpenChange, + ariaLabel, + width = 360, + children, +}: SidebarSlideOutPanelProps) { + const isMobile = !useMediaQuery("(min-width: 640px)"); + const sidebarContext = useSidebarContextSafe(); + const isCollapsed = sidebarContext?.isCollapsed ?? false; + const sidebarWidth = isCollapsed + ? SIDEBAR_COLLAPSED_WIDTH + : (sidebarContext?.sidebarWidth ?? 240); + + return ( + + {open && ( + <> + {/* Click-away layer - covers the full container including the sidebar */} + onOpenChange(false)} + aria-hidden="true" + /> + + {/* Clip container - positioned at sidebar edge with overflow hidden */} +
+ + {children} + +
+ + )} + + ); +} diff --git a/surfsense_web/components/layout/ui/sidebar/SidebarUserProfile.tsx b/surfsense_web/components/layout/ui/sidebar/SidebarUserProfile.tsx index 997482ed3..ea9b0189c 100644 --- a/surfsense_web/components/layout/ui/sidebar/SidebarUserProfile.tsx +++ b/surfsense_web/components/layout/ui/sidebar/SidebarUserProfile.tsx @@ -1,16 +1,6 @@ "use client"; -import { - Check, - ChevronUp, - Languages, - Laptop, - Loader2, - LogOut, - Moon, - Settings, - Sun, -} from "lucide-react"; +import { Check, ChevronUp, Languages, Laptop, LogOut, Moon, Settings, Sun } from "lucide-react"; import { useTranslations } from "next-intl"; import { useState } from "react"; import { @@ -25,6 +15,7 @@ import { DropdownMenuSubTrigger, DropdownMenuTrigger, } from "@/components/ui/dropdown-menu"; +import { Spinner } from "@/components/ui/spinner"; import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip"; import { useLocaleContext } from "@/contexts/LocaleContext"; import { cn } from "@/lib/utils"; @@ -266,7 +257,7 @@ export function SidebarUserProfile({ {isLoggingOut ? ( - + ) : ( )} @@ -388,7 +379,7 @@ export function SidebarUserProfile({ {isLoggingOut ? ( - + ) : ( )} diff --git a/surfsense_web/components/public-chat/public-chat-footer.tsx b/surfsense_web/components/public-chat/public-chat-footer.tsx index 2211f3142..79b317ddf 100644 --- a/surfsense_web/components/public-chat/public-chat-footer.tsx +++ b/surfsense_web/components/public-chat/public-chat-footer.tsx @@ -1,10 +1,11 @@ "use client"; -import { Copy, Loader2 } from "lucide-react"; +import { Copy } from "lucide-react"; import { useRouter, useSearchParams } from "next/navigation"; import { useCallback, useEffect, useRef, useState } from "react"; import { toast } from "sonner"; import { Button } from "@/components/ui/button"; +import { Spinner } from "@/components/ui/spinner"; import { publicChatApiService } from "@/lib/apis/public-chat-api.service"; import { getBearerToken } from "@/lib/auth-utils"; @@ -61,9 +62,14 @@ export function PublicChatFooter({ shareToken }: PublicChatFooterProps) { }; return ( -
-
diff --git a/surfsense_web/components/public-chat/public-chat-view.tsx b/surfsense_web/components/public-chat/public-chat-view.tsx index 08a450d06..a1e6008ff 100644 --- a/surfsense_web/components/public-chat/public-chat-view.tsx +++ b/surfsense_web/components/public-chat/public-chat-view.tsx @@ -1,12 +1,12 @@ "use client"; import { AssistantRuntimeProvider } from "@assistant-ui/react"; -import { Loader2 } from "lucide-react"; import { Navbar } from "@/components/homepage/navbar"; import { DisplayImageToolUI } from "@/components/tool-ui/display-image"; import { GeneratePodcastToolUI } from "@/components/tool-ui/generate-podcast"; import { LinkPreviewToolUI } from "@/components/tool-ui/link-preview"; import { ScrapeWebpageToolUI } from "@/components/tool-ui/scrape-webpage"; +import { Spinner } from "@/components/ui/spinner"; import { usePublicChat } from "@/hooks/use-public-chat"; import { usePublicChatRuntime } from "@/hooks/use-public-chat-runtime"; import { PublicChatFooter } from "./public-chat-footer"; @@ -26,7 +26,7 @@ export function PublicChatView({ shareToken }: PublicChatViewProps) {
- +
); diff --git a/surfsense_web/components/settings/image-model-manager.tsx b/surfsense_web/components/settings/image-model-manager.tsx index 1e1354718..80828f825 100644 --- a/surfsense_web/components/settings/image-model-manager.tsx +++ b/surfsense_web/components/settings/image-model-manager.tsx @@ -71,8 +71,8 @@ import { Skeleton } from "@/components/ui/skeleton"; import { Spinner } from "@/components/ui/spinner"; import { Tooltip, TooltipContent, TooltipProvider, TooltipTrigger } from "@/components/ui/tooltip"; import { - IMAGE_GEN_PROVIDERS, getImageGenModelsByProvider, + IMAGE_GEN_PROVIDERS, } from "@/contracts/enums/image-gen-providers"; import type { ImageGenerationConfig } from "@/contracts/types/new-llm-config.types"; import { cn } from "@/lib/utils"; diff --git a/surfsense_web/components/ui/checkbox.tsx b/surfsense_web/components/ui/checkbox.tsx index 2b59d1f47..789a6b68b 100644 --- a/surfsense_web/components/ui/checkbox.tsx +++ b/surfsense_web/components/ui/checkbox.tsx @@ -1,7 +1,7 @@ "use client"; import * as CheckboxPrimitive from "@radix-ui/react-checkbox"; -import { CheckIcon } from "lucide-react"; +import { CheckIcon, MinusIcon } from "lucide-react"; import type * as React from "react"; import { cn } from "@/lib/utils"; @@ -11,16 +11,17 @@ function Checkbox({ className, ...props }: React.ComponentProps - + + ); diff --git a/surfsense_web/contracts/enums/connectorIcons.tsx b/surfsense_web/contracts/enums/connectorIcons.tsx index 18a872d94..c9375a5ca 100644 --- a/surfsense_web/contracts/enums/connectorIcons.tsx +++ b/surfsense_web/contracts/enums/connectorIcons.tsx @@ -1,4 +1,4 @@ -import { IconLinkPlus, IconUsersGroup } from "@tabler/icons-react"; +import { IconUsersGroup } from "@tabler/icons-react"; import { BookOpen, File, @@ -15,11 +15,16 @@ import { EnumConnectorName } from "./connector"; export const getConnectorIcon = (connectorType: EnumConnectorName | string, className?: string) => { const iconProps = { className: className || "h-4 w-4" }; - const imgProps = { className: className || "h-5 w-5", width: 20, height: 20 }; + const imgProps = { + className: `${className || "h-5 w-5"} select-none pointer-events-none`, + width: 20, + height: 20, + draggable: false as const, + }; switch (connectorType) { case EnumConnectorName.LINKUP_API: - return ; + return Linkup; case EnumConnectorName.LINEAR_CONNECTOR: return Linear; case EnumConnectorName.GITHUB_CONNECTOR: @@ -63,7 +68,7 @@ export const getConnectorIcon = (connectorType: EnumConnectorName | string, clas case EnumConnectorName.YOUTUBE_CONNECTOR: return YouTube; case EnumConnectorName.CIRCLEBACK_CONNECTOR: - return ; + return Circleback; case EnumConnectorName.MCP_CONNECTOR: return MCP; case EnumConnectorName.OBSIDIAN_CONNECTOR: diff --git a/surfsense_web/contracts/enums/llm-models.ts b/surfsense_web/contracts/enums/llm-models.ts index 5ff15c3df..467522faa 100644 --- a/surfsense_web/contracts/enums/llm-models.ts +++ b/surfsense_web/contracts/enums/llm-models.ts @@ -1477,6 +1477,78 @@ export const LLM_MODELS: LLMModel[] = [ provider: "DATABRICKS", contextWindow: "128K", }, + + // GitHub Models + { + value: "openai/gpt-5", + label: "GitHub GPT-5", + provider: "GITHUB_MODELS", + }, + { + value: "openai/gpt-4.1", + label: "GitHub GPT-4.1", + provider: "GITHUB_MODELS", + contextWindow: "1048K", + }, + { + value: "openai/gpt-4o", + label: "GitHub GPT-4o", + provider: "GITHUB_MODELS", + contextWindow: "128K", + }, + { + value: "deepseek/DeepSeek-V3-0324", + label: "GitHub DeepSeek V3", + provider: "GITHUB_MODELS", + contextWindow: "64K", + }, + { + value: "xai/grok-3", + label: "GitHub Grok 3", + provider: "GITHUB_MODELS", + contextWindow: "131K", + }, + { + value: "openai/gpt-5-mini", + label: "GitHub GPT-5 Mini", + provider: "GITHUB_MODELS", + }, + { + value: "openai/gpt-4.1-mini", + label: "GitHub GPT-4.1 Mini", + provider: "GITHUB_MODELS", + contextWindow: "1048K", + }, + { + value: "meta/Llama-4-Scout-17B-16E-Instruct", + label: "GitHub Llama 4 Scout", + provider: "GITHUB_MODELS", + contextWindow: "512K", + }, + { + value: "openai/gpt-4.1-nano", + label: "GitHub GPT-4.1 Nano", + provider: "GITHUB_MODELS", + contextWindow: "1048K", + }, + { + value: "openai/gpt-4o-mini", + label: "GitHub GPT-4o Mini", + provider: "GITHUB_MODELS", + contextWindow: "128K", + }, + { + value: "openai/o4-mini", + label: "GitHub O4 Mini", + provider: "GITHUB_MODELS", + contextWindow: "200K", + }, + { + value: "deepseek/DeepSeek-R1", + label: "GitHub DeepSeek R1", + provider: "GITHUB_MODELS", + contextWindow: "64K", + }, ]; // Helper function to get models by provider diff --git a/surfsense_web/contracts/enums/llm-providers.ts b/surfsense_web/contracts/enums/llm-providers.ts index 40b7ee2df..7e6542c11 100644 --- a/surfsense_web/contracts/enums/llm-providers.ts +++ b/surfsense_web/contracts/enums/llm-providers.ts @@ -174,6 +174,13 @@ export const LLM_PROVIDERS: LLMProvider[] = [ example: "databricks/databricks-meta-llama-3-3-70b-instruct", description: "Databricks Model Serving", }, + { + value: "GITHUB_MODELS", + label: "GitHub Models", + example: "openai/gpt-5, meta/llama-3.1-405b-instruct", + description: "AI models from GitHub Marketplace", + apiBase: "https://models.github.ai/inference", + }, { value: "CUSTOM", label: "Custom Provider", diff --git a/surfsense_web/contracts/types/document.types.ts b/surfsense_web/contracts/types/document.types.ts index b7a2d2cf8..f96ecf85e 100644 --- a/surfsense_web/contracts/types/document.types.ts +++ b/surfsense_web/contracts/types/document.types.ts @@ -138,6 +138,37 @@ export const uploadDocumentRequest = z.object({ export const uploadDocumentResponse = z.object({ message: z.literal("Files uploaded for processing"), + document_ids: z.array(z.number()), + duplicate_document_ids: z.array(z.number()).optional(), + total_files: z.number().optional(), + pending_files: z.number().optional(), + skipped_duplicates: z.number().optional(), +}); + +/** + * Batch document status + */ +export const getDocumentsStatusRequest = z.object({ + queryParams: z.object({ + search_space_id: z.number(), + document_ids: z.array(z.number()).min(1), + }), +}); + +export const documentStatus = z.object({ + state: z.enum(["ready", "pending", "processing", "failed"]), + reason: z.string().nullable().optional(), +}); + +export const documentStatusItem = z.object({ + id: z.number(), + title: z.string(), + document_type: documentTypeEnum, + status: documentStatus, +}); + +export const getDocumentsStatusResponse = z.object({ + items: z.array(documentStatusItem), }); /** @@ -261,6 +292,10 @@ export type CreateDocumentRequest = z.infer; export type CreateDocumentResponse = z.infer; export type UploadDocumentRequest = z.infer; export type UploadDocumentResponse = z.infer; +export type GetDocumentsStatusRequest = z.infer; +export type GetDocumentsStatusResponse = z.infer; +export type DocumentStatus = z.infer; +export type DocumentStatusItem = z.infer; export type SearchDocumentsRequest = z.infer; export type SearchDocumentsResponse = z.infer; export type SearchDocumentTitlesRequest = z.infer; diff --git a/surfsense_web/contracts/types/incentive-tasks.types.ts b/surfsense_web/contracts/types/incentive-tasks.types.ts index 56a62fa06..c45121c29 100644 --- a/surfsense_web/contracts/types/incentive-tasks.types.ts +++ b/surfsense_web/contracts/types/incentive-tasks.types.ts @@ -3,7 +3,7 @@ import { z } from "zod"; /** * Incentive task type enum - matches backend IncentiveTaskType */ -export const incentiveTaskTypeEnum = z.enum(["GITHUB_STAR"]); +export const incentiveTaskTypeEnum = z.enum(["GITHUB_STAR", "REDDIT_FOLLOW", "DISCORD_JOIN"]); /** * Single incentive task info schema diff --git a/surfsense_web/contracts/types/new-llm-config.types.ts b/surfsense_web/contracts/types/new-llm-config.types.ts index 0885fa7f5..b01e2abdf 100644 --- a/surfsense_web/contracts/types/new-llm-config.types.ts +++ b/surfsense_web/contracts/types/new-llm-config.types.ts @@ -33,6 +33,7 @@ export const liteLLMProviderEnum = z.enum([ "DATABRICKS", "COMETAPI", "HUGGINGFACE", + "GITHUB_MODELS", "CUSTOM", ]); diff --git a/surfsense_web/lib/apis/documents-api.service.ts b/surfsense_web/lib/apis/documents-api.service.ts index 03d86a253..c9d649c68 100644 --- a/surfsense_web/lib/apis/documents-api.service.ts +++ b/surfsense_web/lib/apis/documents-api.service.ts @@ -8,6 +8,7 @@ import { type GetDocumentByChunkRequest, type GetDocumentRequest, type GetDocumentsRequest, + type GetDocumentsStatusRequest, type GetDocumentTypeCountsRequest, type GetSurfsenseDocsRequest, getDocumentByChunkRequest, @@ -16,6 +17,8 @@ import { getDocumentResponse, getDocumentsRequest, getDocumentsResponse, + getDocumentsStatusRequest, + getDocumentsStatusResponse, getDocumentTypeCountsRequest, getDocumentTypeCountsResponse, getSurfsenseDocsByChunkResponse, @@ -130,6 +133,30 @@ class DocumentsApiService { }); }; + /** + * Batch document status for async processing tracking + */ + getDocumentsStatus = async (request: GetDocumentsStatusRequest) => { + const parsedRequest = getDocumentsStatusRequest.safeParse(request); + + if (!parsedRequest.success) { + console.error("Invalid request:", parsedRequest.error); + const errorMessage = parsedRequest.error.issues.map((issue) => issue.message).join(", "); + throw new ValidationError(`Invalid request: ${errorMessage}`); + } + + const { search_space_id, document_ids } = parsedRequest.data.queryParams; + const params = new URLSearchParams({ + search_space_id: String(search_space_id), + document_ids: document_ids.join(","), + }); + + return baseApiService.get( + `/api/v1/documents/status?${params.toString()}`, + getDocumentsStatusResponse + ); + }; + /** * Search documents by title */ diff --git a/surfsense_web/lib/apis/image-gen-config-api.service.ts b/surfsense_web/lib/apis/image-gen-config-api.service.ts index 379edfa53..a9d444d21 100644 --- a/surfsense_web/lib/apis/image-gen-config-api.service.ts +++ b/surfsense_web/lib/apis/image-gen-config-api.service.ts @@ -2,12 +2,12 @@ import { type CreateImageGenConfigRequest, createImageGenConfigRequest, createImageGenConfigResponse, + deleteImageGenConfigResponse, + getGlobalImageGenConfigsResponse, + getImageGenConfigsResponse, type UpdateImageGenConfigRequest, updateImageGenConfigRequest, updateImageGenConfigResponse, - deleteImageGenConfigResponse, - getImageGenConfigsResponse, - getGlobalImageGenConfigsResponse, } from "@/contracts/types/new-llm-config.types"; import { ValidationError } from "../error"; import { baseApiService } from "./base-api.service"; diff --git a/surfsense_web/lib/auth-errors.ts b/surfsense_web/lib/auth-errors.ts index ce50c9c99..d1816cbdd 100644 --- a/surfsense_web/lib/auth-errors.ts +++ b/surfsense_web/lib/auth-errors.ts @@ -20,8 +20,8 @@ const AUTH_ERROR_MESSAGES: AuthErrorMapping = { description: "Your account may be suspended or restricted", }, "404": { - title: "Account not found", - description: "No account exists with this email address", + title: "Not found", + description: "The requested resource was not found", }, "409": { title: "Account conflict", @@ -31,6 +31,10 @@ const AUTH_ERROR_MESSAGES: AuthErrorMapping = { title: "Too many attempts", description: "Please wait before trying again", }, + RATE_LIMIT_EXCEEDED: { + title: "Too many attempts", + description: "You've made too many requests. Please wait a minute and try again.", + }, "500": { title: "Server error", description: "Something went wrong on our end. Please try again", @@ -42,8 +46,8 @@ const AUTH_ERROR_MESSAGES: AuthErrorMapping = { // FastAPI specific errors LOGIN_BAD_CREDENTIALS: { - title: "Invalid credentials", - description: "The email or password you entered is incorrect", + title: "Login failed", + description: "Invalid email or password. If you don't have an account, please sign up.", }, LOGIN_USER_NOT_VERIFIED: { title: "Account not verified", diff --git a/surfsense_web/lib/auth-utils.ts b/surfsense_web/lib/auth-utils.ts index 8c067a4b7..c2a0d58a5 100644 --- a/surfsense_web/lib/auth-utils.ts +++ b/surfsense_web/lib/auth-utils.ts @@ -10,28 +10,53 @@ const REFRESH_TOKEN_KEY = "surfsense_refresh_token"; let isRefreshing = false; let refreshPromise: Promise | null = null; +/** Path prefixes for routes that do not require auth (no current-user fetch, no redirect on 401) */ +const PUBLIC_ROUTE_PREFIXES = [ + "/login", + "/register", + "/auth", + "/docs", + "/public", + "/invite", + "/contact", + "/pricing", + "/privacy", + "/terms", + "/changelog", +]; + /** - * Saves the current path and redirects to login page - * Call this when a 401 response is received + * Returns true if the pathname is a public route where we should not run auth checks + * or redirect to login on 401. + */ +export function isPublicRoute(pathname: string): boolean { + if (pathname === "/" || pathname === "") return true; + return PUBLIC_ROUTE_PREFIXES.some((prefix) => pathname.startsWith(prefix)); +} + +/** + * Clears tokens and optionally redirects to login. + * Call this when a 401 response is received. + * Only redirects when the current route is protected; on public routes we just clear tokens. */ export function handleUnauthorized(): void { if (typeof window === "undefined") return; - // Save the current path (including search params and hash) for redirect after login - const currentPath = window.location.pathname + window.location.search + window.location.hash; + const pathname = window.location.pathname; - // Don't save auth-related paths - const excludedPaths = ["/auth", "/auth/callback", "/"]; - if (!excludedPaths.includes(window.location.pathname)) { - localStorage.setItem(REDIRECT_PATH_KEY, currentPath); - } - - // Clear both tokens + // Always clear tokens localStorage.removeItem(BEARER_TOKEN_KEY); localStorage.removeItem(REFRESH_TOKEN_KEY); - // Redirect to home page (which has login options) - window.location.href = "/login"; + // Only redirect on protected routes; stay on public pages (e.g. /docs) + if (!isPublicRoute(pathname)) { + const currentPath = pathname + window.location.search + window.location.hash; + const excludedPaths = ["/auth", "/auth/callback", "/"]; + if (!excludedPaths.includes(pathname)) { + localStorage.setItem(REDIRECT_PATH_KEY, currentPath); + } + window.location.href = "/login"; + } } /** @@ -179,7 +204,6 @@ export function getAuthHeaders(additionalHeaders?: Record): Reco /** * Attempts to refresh the access token using the stored refresh token. * Returns the new access token if successful, null otherwise. - * Exported for use by API services. */ export async function refreshAccessToken(): Promise { // If already refreshing, wait for that request to complete diff --git a/surfsense_web/lib/chat/attachment-adapter.ts b/surfsense_web/lib/chat/attachment-adapter.ts deleted file mode 100644 index f084af411..000000000 --- a/surfsense_web/lib/chat/attachment-adapter.ts +++ /dev/null @@ -1,324 +0,0 @@ -/** - * Attachment adapter for assistant-ui - * - * This adapter handles file uploads by: - * 1. Uploading the file to the backend /attachments/process endpoint - * 2. The backend extracts markdown content using the configured ETL service - * 3. The extracted content is stored in the attachment and sent with messages - */ - -import type { AttachmentAdapter, CompleteAttachment, PendingAttachment } from "@assistant-ui/react"; -import { getBearerToken } from "@/lib/auth-utils"; - -/** - * Supported file types for the attachment adapter - * - * - Text/Markdown: .md, .markdown, .txt - * - Audio (if STT configured): .mp3, .mp4, .mpeg, .mpga, .m4a, .wav, .webm - * - Documents (depends on ETL service): .pdf, .docx, .doc, .pptx, .xlsx, .html - * - Images: .jpg, .jpeg, .png, .gif, .webp - */ -const ACCEPTED_FILE_TYPES = [ - // Text/Markdown (always supported) - ".md", - ".markdown", - ".txt", - // Audio files - ".mp3", - ".mp4", - ".mpeg", - ".mpga", - ".m4a", - ".wav", - ".webm", - // Document files (depends on ETL service) - ".pdf", - ".docx", - ".doc", - ".pptx", - ".xlsx", - ".html", - // Image files - ".jpg", - ".jpeg", - ".png", - ".gif", - ".webp", -].join(","); - -/** - * Response from the attachment processing endpoint - */ -interface ProcessAttachmentResponse { - id: string; - name: string; - type: "document" | "image" | "file"; - content: string; - contentLength: number; -} - -/** - * Extended CompleteAttachment with our custom extractedContent field - * We store the extracted text in a custom field so we can access it in onNew - * For images, we also store the data URL so it can be displayed after persistence - */ -export interface ChatAttachment extends CompleteAttachment { - extractedContent: string; - imageDataUrl?: string; // Base64 data URL for images (persists across page reloads) -} - -/** - * Process a file through the backend ETL service - */ -async function processAttachment(file: File): Promise { - const token = getBearerToken(); - if (!token) { - throw new Error("Not authenticated"); - } - - const backendUrl = process.env.NEXT_PUBLIC_FASTAPI_BACKEND_URL || "http://localhost:8000"; - - const formData = new FormData(); - formData.append("file", file); - - const response = await fetch(`${backendUrl}/api/v1/attachments/process`, { - method: "POST", - headers: { - Authorization: `Bearer ${token}`, - }, - body: formData, - }); - - if (!response.ok) { - const errorText = await response.text(); - console.error("[processAttachment] Error response:", errorText); - let errorDetail = "Unknown error"; - try { - const errorJson = JSON.parse(errorText); - // FastAPI validation errors return detail as array - if (Array.isArray(errorJson.detail)) { - errorDetail = errorJson.detail - .map((err: { msg?: string; loc?: string[] }) => { - const field = err.loc?.join(".") || "unknown"; - return `${field}: ${err.msg || "validation error"}`; - }) - .join("; "); - } else if (typeof errorJson.detail === "string") { - errorDetail = errorJson.detail; - } else { - errorDetail = JSON.stringify(errorJson); - } - } catch { - errorDetail = errorText || `HTTP ${response.status}`; - } - throw new Error(errorDetail); - } - - return response.json(); -} - -// Store processed results for the send() method -const processedAttachments = new Map(); - -// Store image data URLs for attachments (so they persist after File objects are lost) -const imageDataUrls = new Map(); - -/** - * Convert a File to a data URL (base64) for images - */ -async function fileToDataUrl(file: File): Promise { - return new Promise((resolve, reject) => { - const reader = new FileReader(); - reader.onload = () => resolve(reader.result as string); - reader.onerror = reject; - reader.readAsDataURL(file); - }); -} - -/** - * Create the attachment adapter for assistant-ui - * - * This adapter: - * 1. Accepts file upload - * 2. Processes the file through the backend ETL service - * 3. Returns the attachment with extracted markdown content - * - * The content is stored in the attachment and will be sent with the message. - */ -export function createAttachmentAdapter(): AttachmentAdapter { - return { - accept: ACCEPTED_FILE_TYPES, - - /** - * Async generator that yields pending states while processing - * and returns a pending attachment when done. - * - * IMPORTANT: The generator should return status: { type: "running", progress: 100 } - * NOT status: { type: "complete" }. The "complete" status is set by send(). - * Returning "complete" from the generator will prevent send() from being called! - * - * This pattern allows the UI to show a loading indicator - * while the file is being processed by the backend. - * The send() method is called to finalize the attachment. - */ - async *add(input: File | { file: File }): AsyncGenerator { - // Handle both direct File and { file: File } patterns - const file = input instanceof File ? input : input.file; - - if (!file) { - console.error("[AttachmentAdapter] No file found in input:", input); - throw new Error("No file provided"); - } - - // Generate a unique ID for this attachment - const id = crypto.randomUUID(); - - // Determine attachment type from file - const attachmentType = file.type.startsWith("image/") ? "image" : "document"; - - // Yield initial pending state with "running" status (0% progress) - // This triggers the loading indicator in the UI - yield { - id, - type: attachmentType, - name: file.name, - file, - status: { type: "running", reason: "uploading", progress: 0 }, - } as PendingAttachment; - - try { - // For images, convert to data URL so we can display them after persistence - if (attachmentType === "image") { - const dataUrl = await fileToDataUrl(file); - imageDataUrls.set(id, dataUrl); - } - - // Process the file through the backend ETL service - const result = await processAttachment(file); - - // Verify we have the required fields - if (!result.content) { - console.error("[AttachmentAdapter] WARNING: No content received from backend!"); - } - - // Store the processed result for send() - processedAttachments.set(id, result); - - // Create the final pending attachment - // IMPORTANT: Use "running" status with progress: 100 to indicate processing is done - // but attachment is still pending. The "complete" status will be set by send(). - // Yield the final state to ensure it gets processed by the UI - yield { - id, - type: result.type, - name: result.name, - file, - status: { type: "running", reason: "uploading", progress: 100 }, - } as PendingAttachment; - } catch (error) { - console.error("[AttachmentAdapter] Failed to process attachment:", error); - throw error; - } - }, - - /** - * Called when user sends the message. - * Converts the pending attachment to a complete attachment. - */ - async send(pendingAttachment: PendingAttachment): Promise { - const result = processedAttachments.get(pendingAttachment.id); - const imageDataUrl = imageDataUrls.get(pendingAttachment.id); - - if (result) { - // Clean up stored result - processedAttachments.delete(pendingAttachment.id); - if (imageDataUrl) { - imageDataUrls.delete(pendingAttachment.id); - } - - return { - id: result.id, - type: result.type, - name: result.name, - contentType: "text/markdown", - status: { type: "complete" }, - content: [ - { - type: "text", - text: result.content, - }, - ], - extractedContent: result.content, - imageDataUrl, // Store data URL for images so they can be displayed after persistence - }; - } - - // Fallback if no processed result found - console.warn( - "[AttachmentAdapter] send() - No processed result found for attachment:", - pendingAttachment.id - ); - return { - id: pendingAttachment.id, - type: pendingAttachment.type, - name: pendingAttachment.name, - contentType: "text/plain", - status: { type: "complete" }, - content: [], - extractedContent: "", - imageDataUrl, // Still include data URL if available - }; - }, - - async remove() { - // No server-side cleanup needed since we don't persist attachments - }, - }; -} - -/** - * Extract attachment content for chat request - * - * This function extracts the content from attachments to be sent with the chat request. - * Only attachments that have been fully processed (have content) will be included. - */ -export function extractAttachmentContent( - attachments: Array -): Array<{ id: string; name: string; type: string; content: string }> { - return attachments - .filter((att): att is ChatAttachment => { - if (!att || typeof att !== "object") return false; - const a = att as Record; - // Check for our custom extractedContent field first - if (typeof a.extractedContent === "string" && a.extractedContent.length > 0) { - return true; - } - // Fallback: check if content array has text content - if (Array.isArray(a.content)) { - const textContent = (a.content as Array<{ type: string; text?: string }>).find( - (c) => c.type === "text" && typeof c.text === "string" && c.text.length > 0 - ); - return Boolean(textContent); - } - return false; - }) - .map((att) => { - // Get content from extractedContent or from content array - let content = ""; - if (typeof att.extractedContent === "string") { - content = att.extractedContent; - } else if (Array.isArray(att.content)) { - const textContent = (att.content as Array<{ type: string; text?: string }>).find( - (c) => c.type === "text" - ); - content = textContent?.text || ""; - } - - return { - id: att.id, - name: att.name, - type: att.type, - content, - }; - }); -} diff --git a/surfsense_web/lib/chat/message-utils.ts b/surfsense_web/lib/chat/message-utils.ts index 868ed28eb..81538731b 100644 --- a/surfsense_web/lib/chat/message-utils.ts +++ b/surfsense_web/lib/chat/message-utils.ts @@ -1,46 +1,9 @@ import type { ThreadMessageLike } from "@assistant-ui/react"; -import { z } from "zod"; import type { MessageRecord } from "./thread-persistence"; -/** - * Zod schema for persisted attachment info - */ -const PersistedAttachmentSchema = z.object({ - id: z.string(), - name: z.string(), - type: z.string(), - contentType: z.string().optional(), - imageDataUrl: z.string().optional(), - extractedContent: z.string().optional(), -}); - -const AttachmentsPartSchema = z.object({ - type: z.literal("attachments"), - items: z.array(PersistedAttachmentSchema), -}); - -type PersistedAttachment = z.infer; - -/** - * Extract persisted attachments from message content (type-safe with Zod) - */ -function extractPersistedAttachments(content: unknown): PersistedAttachment[] { - if (!Array.isArray(content)) return []; - - for (const part of content) { - const result = AttachmentsPartSchema.safeParse(part); - if (result.success) { - return result.data.items; - } - } - - return []; -} - /** * Convert backend message to assistant-ui ThreadMessageLike format * Filters out 'thinking-steps' part as it's handled separately via messageThinkingSteps - * Restores attachments for user messages from persisted data */ export function convertToThreadMessage(msg: MessageRecord): ThreadMessageLike { let content: ThreadMessageLike["content"]; @@ -52,7 +15,7 @@ export function convertToThreadMessage(msg: MessageRecord): ThreadMessageLike { const filteredContent = msg.content.filter((part: unknown) => { if (typeof part !== "object" || part === null || !("type" in part)) return true; const partType = (part as { type: string }).type; - // Filter out thinking-steps, mentioned-documents, and attachments + // Filter out metadata parts not directly renderable by assistant-ui return ( partType !== "thinking-steps" && partType !== "mentioned-documents" && @@ -67,25 +30,6 @@ export function convertToThreadMessage(msg: MessageRecord): ThreadMessageLike { content = [{ type: "text", text: String(msg.content) }]; } - // Restore attachments for user messages - let attachments: ThreadMessageLike["attachments"]; - if (msg.role === "user") { - const persistedAttachments = extractPersistedAttachments(msg.content); - if (persistedAttachments.length > 0) { - attachments = persistedAttachments.map((att) => ({ - id: att.id, - name: att.name, - type: att.type as "document" | "image" | "file", - contentType: att.contentType || "application/octet-stream", - status: { type: "complete" as const }, - content: [], - // Custom fields for our ChatAttachment interface - imageDataUrl: att.imageDataUrl, - extractedContent: att.extractedContent, - })); - } - } - // Build metadata.custom for author display in shared chats const metadata = msg.author_id ? { @@ -103,7 +47,6 @@ export function convertToThreadMessage(msg: MessageRecord): ThreadMessageLike { role: msg.role, content, createdAt: new Date(msg.created_at), - attachments, metadata, }; } diff --git a/surfsense_web/lib/connectors/utils.ts b/surfsense_web/lib/connectors/utils.ts index 0ca1c1ea9..27da40cc3 100644 --- a/surfsense_web/lib/connectors/utils.ts +++ b/surfsense_web/lib/connectors/utils.ts @@ -1,15 +1,18 @@ // Helper function to get connector type display name export const getConnectorTypeDisplay = (type: string): string => { const typeMap: Record = { + SERPER_API: "Serper API", TAVILY_API: "Tavily API", SEARXNG_API: "SearxNG", + LINKUP_API: "Linkup", + BAIDU_SEARCH_API: "Baidu Search", SLACK_CONNECTOR: "Slack", + TEAMS_CONNECTOR: "Microsoft Teams", NOTION_CONNECTOR: "Notion", GITHUB_CONNECTOR: "GitHub", LINEAR_CONNECTOR: "Linear", JIRA_CONNECTOR: "Jira", DISCORD_CONNECTOR: "Discord", - LINKUP_API: "Linkup", CONFLUENCE_CONNECTOR: "Confluence", BOOKSTACK_CONNECTOR: "BookStack", CLICKUP_CONNECTOR: "ClickUp", @@ -23,8 +26,10 @@ export const getConnectorTypeDisplay = (type: string): string => { LUMA_CONNECTOR: "Luma", ELASTICSEARCH_CONNECTOR: "Elasticsearch", WEBCRAWLER_CONNECTOR: "Web Pages", + YOUTUBE_CONNECTOR: "YouTube", CIRCLEBACK_CONNECTOR: "Circleback", OBSIDIAN_CONNECTOR: "Obsidian", + MCP_CONNECTOR: "MCP Server", }; return typeMap[type] || type; }; diff --git a/surfsense_web/package.json b/surfsense_web/package.json index ba5045001..038bdc47e 100644 --- a/surfsense_web/package.json +++ b/surfsense_web/package.json @@ -1,6 +1,6 @@ { "name": "surfsense_web", - "version": "0.0.12", + "version": "0.0.13", "private": true, "description": "SurfSense Frontend", "scripts": { diff --git a/surfsense_web/public/connectors/circleback.svg b/surfsense_web/public/connectors/circleback.svg new file mode 100644 index 000000000..76bdcddd8 --- /dev/null +++ b/surfsense_web/public/connectors/circleback.svg @@ -0,0 +1,19 @@ + + + + + + + + + diff --git a/surfsense_web/public/connectors/composio.svg b/surfsense_web/public/connectors/composio.svg deleted file mode 100644 index 7c06babeb..000000000 --- a/surfsense_web/public/connectors/composio.svg +++ /dev/null @@ -1,12 +0,0 @@ - - - - - - - - - - - - diff --git a/surfsense_web/public/connectors/linkup.svg b/surfsense_web/public/connectors/linkup.svg new file mode 100644 index 000000000..8b0ffb071 --- /dev/null +++ b/surfsense_web/public/connectors/linkup.svg @@ -0,0 +1,50 @@ + + + + + + + + + + + + + + +