refactor: remove search_surfsense_docs tool and related references

- Deleted the `search_surfsense_docs` tool and its associated files, streamlining the agent's toolset.
- Updated various components and prompts to remove references to the now-removed tool, ensuring consistency across the codebase.
- Adjusted documentation to direct users to the SurfSense documentation link for product-related queries instead.

surfsense_backend/alembic/versions/146_drop_surfsense_docs_tables.py

@@ -0,0 +1,129 @@
+"""Drop Surfsense docs tables (feature removed end to end)
+
+Revision ID: 146
+Revises: 145
+Create Date: 2026-05-28
+
+Removes the SurfSense product-documentation feature: the
+``surfsense_docs_documents`` and ``surfsense_docs_chunks`` tables (created
+in revision 60) and the GIN trigram index on the title column (added in
+revision 67). The docs were seeded at startup from local MDX files, so no
+user data is lost. Downgrade recreates the tables and indexes.
+"""
+
+from collections.abc import Sequence
+
+from alembic import op
+from app.config import config
+
+# revision identifiers, used by Alembic.
+revision: str = "146"
+down_revision: str | None = "145"
+branch_labels: str | Sequence[str] | None = None
+depends_on: str | Sequence[str] | None = None
+
+# Embedding dimension is required to recreate the vector columns on downgrade.
+EMBEDDING_DIM = config.embedding_model_instance.dimension
+
+
+def upgrade() -> None:
+    """Drop surfsense docs tables and all their indexes."""
+    # Trigram index from revision 67
+    op.execute("DROP INDEX IF EXISTS idx_surfsense_docs_title_trgm")
+
+    # Full-text search indexes
+    op.execute("DROP INDEX IF EXISTS surfsense_docs_chunks_search_index")
+    op.execute("DROP INDEX IF EXISTS surfsense_docs_documents_search_index")
+
+    # Vector indexes
+    op.execute("DROP INDEX IF EXISTS surfsense_docs_chunks_vector_index")
+    op.execute("DROP INDEX IF EXISTS surfsense_docs_documents_vector_index")
+
+    # B-tree indexes
+    op.execute("DROP INDEX IF EXISTS ix_surfsense_docs_chunks_document_id")
+    op.execute("DROP INDEX IF EXISTS ix_surfsense_docs_documents_updated_at")
+    op.execute("DROP INDEX IF EXISTS ix_surfsense_docs_documents_content_hash")
+    op.execute("DROP INDEX IF EXISTS ix_surfsense_docs_documents_source")
+
+    # Tables (chunks first due to FK)
+    op.execute("DROP TABLE IF EXISTS surfsense_docs_chunks")
+    op.execute("DROP TABLE IF EXISTS surfsense_docs_documents")
+
+
+def downgrade() -> None:
+    """Recreate surfsense docs tables and indexes (reverses revisions 60 + 67)."""
+    op.execute(
+        f"""
+        CREATE TABLE IF NOT EXISTS surfsense_docs_documents (
+            id SERIAL PRIMARY KEY,
+            created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(),
+            source VARCHAR NOT NULL UNIQUE,
+            title VARCHAR NOT NULL,
+            content TEXT NOT NULL,
+            content_hash VARCHAR NOT NULL,
+            embedding vector({EMBEDDING_DIM}),
+            updated_at TIMESTAMP WITH TIME ZONE
+        );
+        """
+    )
+    op.execute(
+        f"""
+        CREATE TABLE IF NOT EXISTS surfsense_docs_chunks (
+            id SERIAL PRIMARY KEY,
+            created_at TIMESTAMP WITH TIME ZONE NOT NULL DEFAULT NOW(),
+            content TEXT NOT NULL,
+            embedding vector({EMBEDDING_DIM}),
+            document_id INTEGER NOT NULL REFERENCES surfsense_docs_documents(id) ON DELETE CASCADE
+        );
+        """
+    )
+
+    # B-tree indexes
+    op.execute(
+        "CREATE INDEX IF NOT EXISTS ix_surfsense_docs_documents_source ON surfsense_docs_documents(source)"
+    )
+    op.execute(
+        "CREATE INDEX IF NOT EXISTS ix_surfsense_docs_documents_content_hash ON surfsense_docs_documents(content_hash)"
+    )
+    op.execute(
+        "CREATE INDEX IF NOT EXISTS ix_surfsense_docs_documents_updated_at ON surfsense_docs_documents(updated_at)"
+    )
+    op.execute(
+        "CREATE INDEX IF NOT EXISTS ix_surfsense_docs_chunks_document_id ON surfsense_docs_chunks(document_id)"
+    )
+
+    # Vector indexes
+    op.execute(
+        """
+        CREATE INDEX IF NOT EXISTS surfsense_docs_documents_vector_index
+        ON surfsense_docs_documents USING hnsw (embedding public.vector_cosine_ops);
+        """
+    )
+    op.execute(
+        """
+        CREATE INDEX IF NOT EXISTS surfsense_docs_chunks_vector_index
+        ON surfsense_docs_chunks USING hnsw (embedding public.vector_cosine_ops);
+        """
+    )
+
+    # Full-text search indexes
+    op.execute(
+        """
+        CREATE INDEX IF NOT EXISTS surfsense_docs_documents_search_index
+        ON surfsense_docs_documents USING gin (to_tsvector('english', content));
+        """
+    )
+    op.execute(
+        """
+        CREATE INDEX IF NOT EXISTS surfsense_docs_chunks_search_index
+        ON surfsense_docs_chunks USING gin (to_tsvector('english', content));
+        """
+    )
+
+    # Trigram index from revision 67
+    op.execute(
+        """
+        CREATE INDEX IF NOT EXISTS idx_surfsense_docs_title_trgm
+        ON surfsense_docs_documents USING gin (title gin_trgm_ops);
+        """
+    )

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/citations/on.md

@@ -4,8 +4,8 @@ never invent ids you didn't see. Citation ids are resolved by exact-match
 lookup; a wrong id silently breaks the link, so when in doubt, omit.
 
 ### Channel A — chunk blocks injected this turn
-When `search_surfsense_docs` or `web_search` returns `<document>` /
+When `web_search` returns `<document>` / `<chunk id='…'>` blocks in this
-`<chunk id='…'>` blocks in this turn:
+turn:
 
 1. For each factual statement taken from those chunks, add
    `[citation:chunk_id]` using the **exact** id from a visible

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/dynamic_context/private.md

@@ -20,8 +20,8 @@ it to resolve paths the user describes in natural language ("my Q2 roadmap",
 delegating to a specialist.
 
 `<document>` and `<chunk id='…'>` blocks are chunked indexed content returned
-by KB search (from `search_surfsense_docs`, or backing `<priority_documents>`).
+by KB search (backing `<priority_documents>`). Each chunk carries a stable
-Each chunk carries a stable `id` attribute.
+`id` attribute.
 
 If a block doesn't appear this turn, work from the conversation alone.
 </dynamic_context>

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/dynamic_context/team.md

@@ -20,8 +20,8 @@ week's planning notes") into concrete document references before delegating
 to a specialist.
 
 `<document>` and `<chunk id='…'>` blocks are chunked indexed content returned
-by KB search (from `search_surfsense_docs`, or backing `<priority_documents>`).
+by KB search (backing `<priority_documents>`). Each chunk carries a stable
-Each chunk carries a stable `id` attribute.
+`id` attribute.
 
 If a block doesn't appear this turn, work from the conversation alone.
 </dynamic_context>

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/kb_first.md

@@ -1,19 +1,21 @@
 <knowledge_base_first>
 CRITICAL — ground factual answers in what you actually receive this turn:
 - injected workspace context (see `<dynamic_context>`),
-- results from your own tool calls (`search_surfsense_docs`, `web_search`,
+- results from your own tool calls (`web_search`, `scrape_webpage`),
-  `scrape_webpage`),
 - or substantive summaries returned by a `task` specialist you invoked.
 
 Do **not** answer factual or informational questions from general knowledge
 unless the user explicitly authorises it after you say you couldn't find
 enough in those sources. The flow when nothing is found:
 
-1. Say you couldn't find enough in their workspace, docs, or tool output.
+1. Say you couldn't find enough in their workspace or tool output.
 2. Ask: *"Would you like me to answer from my general knowledge instead?"*
 3. Only answer from general knowledge after a clear yes.
 
 This rule does NOT apply to: casual conversation · meta-questions about
 SurfSense ("what can you do?") · formatting or analysis of content already
 in chat · clear rewrite/edit instructions · lightweight web research.
+
+For "how do I use SurfSense" / product-documentation questions, point the
+user to https://www.surfsense.com/docs.
 </knowledge_base_first>

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/providers/anthropic.md

@@ -5,7 +5,7 @@ Structured reasoning:
 - For non-trivial work, `<thinking>` / short `<plan>` before tool calls is fine.
 
 Professional objectivity:
-- Accuracy over flattery; verify with **search_surfsense_docs**, **web_search**, **scrape_webpage**, or **task** when unsure — don’t invent connector access.
+- Accuracy over flattery; verify with **web_search**, **scrape_webpage**, or **task** when unsure — don’t invent connector access.
 
 Task management:
 - For 3+ steps, use todo tooling; update statuses promptly.

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/providers/deepseek.md

@@ -13,6 +13,6 @@ Attribution:
 
 Tool calls:
 - Parallelise independent calls.
-- Prefer **search_surfsense_docs** for SurfSense docs/product questions before **web_search** when that fits the ask.
+- For SurfSense docs/product questions, point the user to https://www.surfsense.com/docs.
 - Don’t invent paths, chunk ids, or URLs — only values from tools or the user.
 </provider_hints>

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/providers/google.md

@@ -7,7 +7,7 @@ Output style:
 - GitHub-flavoured Markdown; monospace-friendly.
 
 Workflow (Understand → Plan → Act → Verify):
-1. **Understand:** parse the ask; use **search_surfsense_docs** / injected workspace context before guessing.
+1. **Understand:** parse the ask; use injected workspace context before guessing.
 2. **Plan:** for multi-step work, a short plan first.
 3. **Act:** only with tools you actually have on this agent (see `<tools>` and `<tool_routing>`). Connector work → **task**.
 4. **Verify:** re-read or re-search only when it materially reduces risk.

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/providers/openai_classic.md

@@ -15,6 +15,7 @@ Output style:
 
 Tool calls:
 - Parallelise independent calls in one turn.
-- Prefer **search_surfsense_docs** for SurfSense-product questions, **web_search** / **scrape_webpage**
+- For SurfSense-product questions, point the user to https://www.surfsense.com/docs;
-  for fresh public facts; integrations and heavy workflows → **task**.
+  use **web_search** / **scrape_webpage** for fresh public facts; integrations and
+  heavy workflows → **task**.
 </provider_hints>

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/routing.md

@@ -3,10 +3,7 @@ You have two execution channels. Pick the one that owns the work — never
 simulate one with the other.
 
 ### 1. Direct tools (you call them yourself)
-- `search_surfsense_docs` — SurfSense product docs (setup, configuration,
+- `web_search` — search the public web (anything outside the workspace KB).
-  connector docs, feature behavior).
-- `web_search` — search the public web (anything outside SurfSense docs and
-  the workspace KB).
 - `scrape_webpage` — fetch the body of a specific public URL.
 - `update_memory` — curate persistent memory (see `<memory_protocol>`).
 - `write_todos` — maintain a structured plan when the turn series spans
@@ -14,6 +11,10 @@ simulate one with the other.
   `in_progress` **before** the `task` call that handles it, `completed`
   once the call returns. Skip for single-step requests.
 
+**Questions about how to use SurfSense itself** (setup, configuration,
+connectors, feature behavior) — point the user to the documentation:
+https://www.surfsense.com/docs. There is no docs-search tool; give the link.
+
 **You have NO filesystem tools.** Any read, write, edit, move, rename, or
 search inside the user's workspace goes through `task(knowledge_base, …)` —
 never via `write_file`, `ls`, or any direct file operation.

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/tools/search_surfsense_docs/__init__.py

@@ -1 +0,0 @@
-"""``search_surfsense_docs`` — description + few-shot examples."""

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/tools/search_surfsense_docs/description.md

@@ -1,10 +0,0 @@
-- `search_surfsense_docs` — Search official SurfSense documentation (product
-  help).
-  - Use when the user asks how SurfSense itself works — setup, configuration,
-    connector documentation, feature behavior, anything covered in the
-    product docs.
-  - Not a substitute for `task` when the user wants actions inside a
-    connected service (Gmail, Slack, Jira, Notion, etc.).
-  - Args: `query`, `top_k` (default 10).
-  - Returns doc excerpts; chunk ids may appear for attribution — see
-    `<citations>` for the contract.

surfsense_backend/app/agents/multi_agent_chat/main_agent/system_prompt/prompts/tools/search_surfsense_docs/example.md

@@ -1,15 +0,0 @@
-<example>
-user: "How do I install SurfSense?"
-→ search_surfsense_docs(query="installation setup")
-</example>
-
-<example>
-user: "What connectors does SurfSense support?"
-→ search_surfsense_docs(query="available connectors integrations")
-</example>
-
-<example>
-user: "How do I set up the Notion connector?"
-→ search_surfsense_docs(query="Notion connector setup configuration")
-(Changing data inside Notion itself → `task(notion, …)`, not this tool.)
-</example>

surfsense_backend/app/agents/multi_agent_chat/main_agent/tools/index.py

@@ -6,7 +6,6 @@ Connector integrations, MCP, deliverables, etc. are delegated via ``task`` subag
 from __future__ import annotations
 
 MAIN_AGENT_SURFSENSE_TOOL_NAMES_ORDERED: tuple[str, ...] = (
-    "search_surfsense_docs",
     "web_search",
     "scrape_webpage",
     "update_memory",

surfsense_backend/app/agents/multi_agent_chat/subagents/builtins/research/system_prompt.md

@@ -8,7 +8,6 @@ Gather and synthesize evidence using SurfSense research tools with clear citatio
 <available_tools>
 - `web_search`
 - `scrape_webpage`
-- `search_surfsense_docs`
 </available_tools>
 
 <tool_policy>

surfsense_backend/app/agents/multi_agent_chat/subagents/builtins/research/tools/__init__.py

@@ -1,11 +1,9 @@
-"""Research-stage tools: web search, scrape, and in-product doc search."""
+"""Research-stage tools: web search and scrape."""
 
 from .scrape_webpage import create_scrape_webpage_tool
-from .search_surfsense_docs import create_search_surfsense_docs_tool
 from .web_search import create_web_search_tool
 
 __all__ = [
     "create_scrape_webpage_tool",
-    "create_search_surfsense_docs_tool",
     "create_web_search_tool",
 ]

surfsense_backend/app/agents/multi_agent_chat/subagents/builtins/research/tools/index.py

@@ -9,7 +9,6 @@ from langchain_core.tools import BaseTool
 from app.agents.new_chat.permissions import Ruleset
 
 from .scrape_webpage import create_scrape_webpage_tool
-from .search_surfsense_docs import create_search_surfsense_docs_tool
 from .web_search import create_web_search_tool
 
 NAME = "research"
@@ -27,5 +26,4 @@ def load_tools(
             available_connectors=d.get("available_connectors"),
         ),
         create_scrape_webpage_tool(firecrawl_api_key=d.get("firecrawl_api_key")),
-        create_search_surfsense_docs_tool(db_session=d["db_session"]),
     ]

surfsense_backend/app/agents/multi_agent_chat/subagents/builtins/research/tools/search_surfsense_docs.py

@@ -1,145 +0,0 @@
-"""Semantic search over pre-indexed in-app documentation chunks for user how-to questions."""
-
-import asyncio
-import json
-
-from langchain_core.tools import tool
-from sqlalchemy import select
-from sqlalchemy.ext.asyncio import AsyncSession
-
-from app.db import SurfsenseDocsChunk, SurfsenseDocsDocument
-from app.utils.document_converters import embed_text
-from app.utils.surfsense_docs import surfsense_docs_public_url
-
-
-def format_surfsense_docs_results(results: list[tuple]) -> str:
-    """Format (chunk, document) rows as XML with ``doc-`` chunk IDs for citations and UI routing."""
-    if not results:
-        return "No relevant Surfsense documentation found for your query."
-
-    # Group chunks by document
-    grouped: dict[int, dict] = {}
-    for chunk, doc in results:
-        public_url = surfsense_docs_public_url(doc.source)
-        if doc.id not in grouped:
-            grouped[doc.id] = {
-                "document_id": f"doc-{doc.id}",
-                "document_type": "SURFSENSE_DOCS",
-                "title": doc.title,
-                "url": public_url,
-                "metadata": {"source": doc.source, "public_url": public_url},
-                "chunks": [],
-            }
-        grouped[doc.id]["chunks"].append(
-            {
-                "chunk_id": f"doc-{chunk.id}",
-                "content": chunk.content,
-            }
-        )
-
-    # Render XML matching format_documents_for_context structure
-    parts: list[str] = []
-    for g in grouped.values():
-        metadata_json = json.dumps(g["metadata"], ensure_ascii=False)
-
-        parts.append("<document>")
-        parts.append("<document_metadata>")
-        parts.append(f"  <document_id>{g['document_id']}</document_id>")
-        parts.append(f"  <document_type>{g['document_type']}</document_type>")
-        parts.append(f"  <title><![CDATA[{g['title']}]]></title>")
-        parts.append(f"  <url><![CDATA[{g['url']}]]></url>")
-        parts.append(f"  <metadata_json><![CDATA[{metadata_json}]]></metadata_json>")
-        parts.append("</document_metadata>")
-        parts.append("")
-        parts.append("<document_content>")
-
-        for ch in g["chunks"]:
-            parts.append(
-                f"  <chunk id='{ch['chunk_id']}'><![CDATA[{ch['content']}]]></chunk>"
-            )
-
-        parts.append("</document_content>")
-        parts.append("</document>")
-        parts.append("")
-
-    return "\n".join(parts).strip()
-
-
-async def search_surfsense_docs_async(
-    query: str,
-    db_session: AsyncSession,
-    top_k: int = 10,
-) -> str:
-    """
-    Search Surfsense documentation using vector similarity.
-
-    Args:
-        query: The search query about Surfsense usage
-        db_session: Database session for executing queries
-        top_k: Number of results to return
-
-    Returns:
-        Formatted string with relevant documentation content
-    """
-    # Get embedding for the query
-    query_embedding = await asyncio.to_thread(embed_text, query)
-
-    # Vector similarity search on chunks, joining with documents
-    stmt = (
-        select(SurfsenseDocsChunk, SurfsenseDocsDocument)
-        .join(
-            SurfsenseDocsDocument,
-            SurfsenseDocsChunk.document_id == SurfsenseDocsDocument.id,
-        )
-        .order_by(SurfsenseDocsChunk.embedding.op("<=>")(query_embedding))
-        .limit(top_k)
-    )
-
-    result = await db_session.execute(stmt)
-    rows = result.all()
-
-    return format_surfsense_docs_results(rows)
-
-
-def create_search_surfsense_docs_tool(db_session: AsyncSession):
-    """
-    Factory function to create the search_surfsense_docs tool.
-
-    Args:
-        db_session: Database session for executing queries
-
-    Returns:
-        A configured tool function for searching Surfsense documentation
-    """
-
-    @tool
-    async def search_surfsense_docs(query: str, top_k: int = 10) -> str:
-        """
-        Search Surfsense documentation for help with using the application.
-
-        Use this tool when the user asks questions about:
-        - How to use Surfsense features
-        - Installation and setup instructions
-        - Configuration options and settings
-        - Troubleshooting common issues
-        - Available connectors and integrations
-        - Browser extension usage
-        - API documentation
-
-        This searches the official Surfsense documentation that was indexed
-        at deployment time. It does NOT search the user's personal knowledge base.
-
-        Args:
-            query: The search query about Surfsense usage or features
-            top_k: Number of documentation chunks to retrieve (default: 10)
-
-        Returns:
-            Relevant documentation content formatted with chunk IDs for citations
-        """
-        return await search_surfsense_docs_async(
-            query=query,
-            db_session=db_session,
-            top_k=top_k,
-        )
-
-    return search_surfsense_docs

surfsense_backend/app/agents/new_chat/feature_flags.py

@@ -104,7 +104,7 @@ class AgentFeatureFlags:
     # ``tools/google_drive``, ``tools/dropbox``, ``tools/onedrive``,
     # ``tools/google_calendar``, ``tools/confluence``, ``tools/discord``,
     # ``tools/teams``, ``tools/luma``, ``connected_accounts``,
-    # ``update_memory``, ``search_surfsense_docs``) now acquire fresh
+    # ``update_memory``) now acquire fresh
     # short-lived ``AsyncSession`` instances per call via
     # :data:`async_session_maker`. The factory still accepts ``db_session``
     # for registry compatibility but ``del``'s it immediately — see any

surfsense_backend/app/agents/new_chat/mention_resolver.py

@@ -73,9 +73,8 @@ class ResolvedMentionSet:
     ``@Project Roadmap`` is never shadowed by a shorter prefix
     ``@Project``).
 
-    ``mentioned_document_ids`` collapses doc + surfsense_doc chips into
+    ``mentioned_document_ids`` is an ordered, deduped list consumed by
-    a single ordered, deduped list because the priority middleware
+    the priority middleware downstream — see
-    treats them uniformly downstream — see
     ``KnowledgePriorityMiddleware._compute_priority_paths``.
     """
 
@@ -103,7 +102,6 @@ async def resolve_mentions(
     search_space_id: int,
     mentioned_documents: list[MentionedDocumentInfo] | None,
     mentioned_document_ids: list[int] | None = None,
-    mentioned_surfsense_doc_ids: list[int] | None = None,
     mentioned_folder_ids: list[int] | None = None,
 ) -> ResolvedMentionSet:
     """Resolve every @-mention chip on a turn into virtual paths.
@@ -111,8 +109,7 @@ async def resolve_mentions(
     The function takes both the ``mentioned_documents`` discriminated
     list (chip metadata used for substitution + persistence) and the
     parallel id arrays (``mentioned_document_ids``,
-    ``mentioned_surfsense_doc_ids``, ``mentioned_folder_ids``) for two
+    ``mentioned_folder_ids``) for two reasons:
-    reasons:
 
     * Legacy clients that haven't migrated to the unified chip list
       still send the id arrays — we treat the union as authoritative.
@@ -142,7 +139,6 @@ async def resolve_mentions(
         dict.fromkeys(
             [
                 *(mentioned_document_ids or []),
-                *(mentioned_surfsense_doc_ids or []),
                 *chip_doc_ids,
             ]
         )

surfsense_backend/app/agents/new_chat/prompts/base/citations_on.md

@@ -59,14 +59,13 @@ Do NOT cite document_id. Always use the chunk id.
 - NEVER create your own citation format - use the exact chunk_id values from the documents in the [citation:chunk_id] format
 - NEVER format citations as clickable links or as markdown links like "([citation:5](https://example.com))". Always use plain square brackets only
 - NEVER make up chunk IDs if you are unsure about the chunk_id. It is better to omit the citation than to guess
-- Copy the EXACT chunk id from the XML - if it says `<chunk id='doc-123'>`, use [citation:doc-123]
+- Copy the EXACT chunk id from the XML - if it says `<chunk id='5'>`, use [citation:5]
 - If the chunk id is a URL like `<chunk id='https://example.com/page'>`, use [citation:https://example.com/page]
 </citation_format>
 
 <citation_examples>
 CORRECT citation formats:
 - [citation:5] (numeric chunk ID from knowledge base)
-- [citation:doc-123] (for Surfsense documentation chunks)
 - [citation:https://example.com/article] (URL chunk ID from web search results)
 - [citation:chunk_id1], [citation:chunk_id2], [citation:chunk_id3] (multiple citations)
 

surfsense_backend/app/agents/new_chat/prompts/base/kb_only_policy_private.md

@@ -7,7 +7,7 @@ CRITICAL RULE — KNOWLEDGE BASE FIRST, NEVER DEFAULT TO GENERAL KNOWLEDGE:
   2. Ask the user: "Would you like me to answer from my general knowledge instead?"
   3. ONLY provide a general-knowledge answer AFTER the user explicitly says yes.
 - This policy does NOT apply to:
-  * Casual conversation, greetings, or meta-questions about SurfSense itself (e.g., "what can you do?")
+  * Casual conversation, greetings, or meta-questions about SurfSense itself (e.g., "what can you do?"). For "how do I use SurfSense" / product-documentation questions, point the user to https://www.surfsense.com/docs.
   * Formatting, summarization, or analysis of content already present in the conversation
   * Following user instructions that are clearly task-oriented (e.g., "rewrite this in bullet points")
   * Tool-usage actions like generating reports, podcasts, images, or scraping webpages

surfsense_backend/app/agents/new_chat/prompts/base/kb_only_policy_team.md

@@ -7,7 +7,7 @@ CRITICAL RULE — KNOWLEDGE BASE FIRST, NEVER DEFAULT TO GENERAL KNOWLEDGE:
   2. Ask: "Would you like me to answer from my general knowledge instead?"
   3. ONLY provide a general-knowledge answer AFTER a team member explicitly says yes.
 - This policy does NOT apply to:
-  * Casual conversation, greetings, or meta-questions about SurfSense itself (e.g., "what can you do?")
+  * Casual conversation, greetings, or meta-questions about SurfSense itself (e.g., "what can you do?"). For "how do I use SurfSense" / product-documentation questions, point the user to https://www.surfsense.com/docs.
   * Formatting, summarization, or analysis of content already present in the conversation
   * Following user instructions that are clearly task-oriented (e.g., "rewrite this in bullet points")
   * Tool-usage actions like generating reports, podcasts, images, or scraping webpages

surfsense_backend/app/agents/new_chat/prompts/base/tool_routing_private.md

@@ -13,6 +13,7 @@ When to use which tool:
 - Knowledge base content (Notion, GitHub, files, notes) → automatically searched
 - Real-time public web data → call web_search
 - Reading a specific webpage → call scrape_webpage
+- SurfSense product / how-to questions (setup, configuration, connectors, feature behavior) → point the user to the documentation: https://www.surfsense.com/docs
 
 **`task` subagents (when to delegate):**
 - **`linear_specialist`** — Linear-only investigations and tool use.

surfsense_backend/app/agents/new_chat/prompts/base/tool_routing_team.md

@@ -13,6 +13,7 @@ When to use which tool:
 - Knowledge base content (Notion, GitHub, files, notes) → automatically searched
 - Real-time public web data → call web_search
 - Reading a specific webpage → call scrape_webpage
+- SurfSense product / how-to questions (setup, configuration, connectors, feature behavior) → point the user to the documentation: https://www.surfsense.com/docs
 
 **`task` subagents (when to delegate):**
 - **`linear_specialist`** — Linear-only investigations and tool use.

surfsense_backend/app/agents/new_chat/prompts/composer.py

@@ -151,7 +151,6 @@ def _read_fragment(subpath: str) -> str:
 # Ordered for reading flow: fundamentals first, then artifact generators,
 # then memory at the end (mirrors the legacy ``_ALL_TOOL_NAMES_ORDERED``).
 ALL_TOOL_NAMES_ORDERED: tuple[str, ...] = (
-    "search_surfsense_docs",
     "web_search",
     "generate_podcast",
     "generate_video_presentation",

surfsense_backend/app/agents/new_chat/prompts/examples/search_surfsense_docs.md

@@ -1,9 +0,0 @@
-
-- User: "How do I install SurfSense?"
-  - Call: `search_surfsense_docs(query="installation setup")`
-- User: "What connectors does SurfSense support?"
-  - Call: `search_surfsense_docs(query="available connectors integrations")`
-- User: "How do I set up the Notion connector?"
-  - Call: `search_surfsense_docs(query="Notion connector setup configuration")`
-- User: "How do I use Docker to run SurfSense?"
-  - Call: `search_surfsense_docs(query="Docker installation setup")`

surfsense_backend/app/agents/new_chat/prompts/tools/search_surfsense_docs.md

@@ -1,7 +0,0 @@
-
-- search_surfsense_docs: Search the official SurfSense documentation.
-  - Use this tool when the user asks anything about SurfSense itself (the application they are using).
-  - Args:
-    - query: The search query about SurfSense
-    - top_k: Number of documentation chunks to retrieve (default: 10)
-  - Returns: Documentation content with chunk IDs for citations (prefixed with 'doc-', e.g., [citation:doc-123])

surfsense_backend/app/agents/new_chat/skills/builtin/email-drafting/SKILL.md

@@ -1,7 +1,6 @@
 ---
 name: email-drafting
 description: Draft an email matching the user's voice, with structured intent and CTA
-allowed-tools: search_surfsense_docs
 ---
 
 # Email drafting

surfsense_backend/app/agents/new_chat/skills/builtin/kb-research/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: kb-research
 description: Structured approach to finding and synthesizing information from the user's knowledge base
-allowed-tools: search_surfsense_docs, scrape_webpage, read_file, ls_tree, grep, web_search
+allowed-tools: scrape_webpage, read_file, ls_tree, grep, web_search
 ---
 
 # Knowledge-base research

surfsense_backend/app/agents/new_chat/skills/builtin/meeting-prep/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: meeting-prep
 description: Pull together briefing materials before a scheduled meeting
-allowed-tools: search_surfsense_docs, web_search, scrape_webpage, read_file
+allowed-tools: web_search, scrape_webpage, read_file
 ---
 
 # Meeting preparation

surfsense_backend/app/agents/new_chat/skills/builtin/report-writing/SKILL.md

@@ -1,7 +1,7 @@
 ---
 name: report-writing
 description: How to scope, draft, and revise a Markdown report artifact via generate_report
-allowed-tools: generate_report, search_surfsense_docs, read_file
+allowed-tools: generate_report, read_file
 ---
 
 # Report writing

surfsense_backend/app/agents/new_chat/skills/builtin/slack-summary/SKILL.md

@@ -1,7 +1,6 @@
 ---
 name: slack-summary
 description: Distill a Slack channel or thread into actionable summary
-allowed-tools: search_surfsense_docs
 ---
 
 # Slack summarization

surfsense_backend/app/agents/new_chat/subagents/config.py

@@ -46,7 +46,6 @@ logger = logging.getLogger(__name__)
 # ``glob``, ``grep``) plus the SurfSense-side read tools.
 EXPLORE_READ_TOOLS: frozenset[str] = frozenset(
     {
-        "search_surfsense_docs",
         "web_search",
         "scrape_webpage",
         "read_file",
@@ -61,7 +60,6 @@ EXPLORE_READ_TOOLS: frozenset[str] = frozenset(
 # is needed, the parent should hand off to ``explore`` first.
 REPORT_WRITER_TOOLS: frozenset[str] = frozenset(
     {
-        "search_surfsense_docs",
         "read_file",
         "generate_report",
     }
@@ -222,7 +220,6 @@ EXPLORE_SYSTEM_PROMPT = """You are the **explore** subagent for SurfSense.
 Conduct read-only research across the user's knowledge base, the web, and any documents the parent agent has surfaced. Return a synthesized answer with explicit citations — never speculate beyond the sources you have actually inspected.
 
 ## Tools available
-- `search_surfsense_docs` — fast hybrid search over the user's knowledge base.
 - `web_search` — only when the user's KB clearly does not contain the answer.
 - `scrape_webpage` — to read a URL the user or the search results provided.
 - `read_file`, `ls`, `glob`, `grep` — to inspect specific documents or trees the parent has flagged.
@@ -242,7 +239,7 @@ Produce a single high-quality report deliverable using `generate_report`. The pa
 
 ## Workflow
 1. **Outline first.** Before calling `generate_report`, write a one-paragraph outline of the sections you plan to produce. Confirm the outline reflects the parent's instructions.
-2. **Source resolution.** Decide whether to call `search_surfsense_docs` and `read_file` for any final-checks, or whether the parent's earlier tool calls already cover the source set.
+2. **Source resolution.** Decide whether to call `read_file` for any final-checks, or whether the parent's earlier tool calls already cover the source set.
 3. **One report.** Call `generate_report` exactly once with `source_strategy` chosen per the topic and chat history (see the `report-writing` skill).
 4. **Confirm.** End with a one-sentence summary in your final message — never paste the report back into chat; the artifact card renders itself.
 """

surfsense_backend/app/agents/new_chat/tools/__init__.py

@@ -5,7 +5,6 @@ This module contains all the tools available to the SurfSense agent.
 To add a new tool, see the documentation in registry.py.
 
 Available tools:
-- search_surfsense_docs: Search Surfsense documentation for usage help
 - generate_podcast: Generate audio podcasts from content
 - generate_video_presentation: Generate video presentations with slides and narration
 - generate_image: Generate images from text descriptions using AI models
@@ -31,7 +30,6 @@ from .registry import (
     get_tool_by_name,
 )
 from .scrape_webpage import create_scrape_webpage_tool
-from .search_surfsense_docs import create_search_surfsense_docs_tool
 from .update_memory import create_update_memory_tool, create_update_team_memory_tool
 from .video_presentation import create_generate_video_presentation_tool
 
@@ -47,7 +45,6 @@ __all__ = [
     "create_generate_podcast_tool",
     "create_generate_video_presentation_tool",
     "create_scrape_webpage_tool",
-    "create_search_surfsense_docs_tool",
     "create_update_memory_tool",
     "create_update_team_memory_tool",
     "format_documents_for_context",

surfsense_backend/app/agents/new_chat/tools/registry.py

@@ -101,7 +101,6 @@ from .podcast import create_generate_podcast_tool
 from .report import create_generate_report_tool
 from .resume import create_generate_resume_tool
 from .scrape_webpage import create_scrape_webpage_tool
-from .search_surfsense_docs import create_search_surfsense_docs_tool
 from .teams import (
     create_list_teams_channels_tool,
     create_read_teams_messages_tool,
@@ -258,15 +257,6 @@ BUILTIN_TOOLS: list[ToolDefinition] = [
         ),
         requires=[],
     ),
-    # Surfsense documentation search tool
-    ToolDefinition(
-        name="search_surfsense_docs",
-        description="Search Surfsense documentation for help with using the application",
-        factory=lambda deps: create_search_surfsense_docs_tool(
-            db_session=deps["db_session"],
-        ),
-        requires=["db_session"],
-    ),
     # =========================================================================
     # SERVICE ACCOUNT DISCOVERY
     # Generic tool for the LLM to discover connected accounts and resolve

surfsense_backend/app/agents/new_chat/tools/search_surfsense_docs.py

@@ -1,174 +0,0 @@
-"""
-Surfsense documentation search tool.
-
-This tool allows the agent to search the pre-indexed Surfsense documentation
-to help users with questions about how to use the application.
-
-The documentation is indexed at deployment time from MDX files and stored
-in dedicated tables (surfsense_docs_documents, surfsense_docs_chunks).
-"""
-
-import asyncio
-import json
-
-from langchain_core.tools import tool
-from sqlalchemy import select
-from sqlalchemy.ext.asyncio import AsyncSession
-
-from app.db import SurfsenseDocsChunk, SurfsenseDocsDocument, async_session_maker
-from app.utils.document_converters import embed_text
-from app.utils.surfsense_docs import surfsense_docs_public_url
-
-
-def format_surfsense_docs_results(results: list[tuple]) -> str:
-    """
-    Format search results into XML structure for the LLM context.
-
-    Uses the same XML structure as format_documents_for_context from knowledge_base.py
-    but with 'doc-' prefix on chunk IDs. This allows:
-    - LLM to use consistent [citation:doc-XXX] format
-    - Frontend to detect 'doc-' prefix and route to surfsense docs endpoint
-
-    Args:
-        results: List of (chunk, document) tuples from the database query
-
-    Returns:
-        Formatted XML string with documentation content and citation-ready chunks
-    """
-    if not results:
-        return "No relevant Surfsense documentation found for your query."
-
-    # Group chunks by document
-    grouped: dict[int, dict] = {}
-    for chunk, doc in results:
-        public_url = surfsense_docs_public_url(doc.source)
-        if doc.id not in grouped:
-            grouped[doc.id] = {
-                "document_id": f"doc-{doc.id}",
-                "document_type": "SURFSENSE_DOCS",
-                "title": doc.title,
-                "url": public_url,
-                "metadata": {"source": doc.source, "public_url": public_url},
-                "chunks": [],
-            }
-        grouped[doc.id]["chunks"].append(
-            {
-                "chunk_id": f"doc-{chunk.id}",
-                "content": chunk.content,
-            }
-        )
-
-    # Render XML matching format_documents_for_context structure
-    parts: list[str] = []
-    for g in grouped.values():
-        metadata_json = json.dumps(g["metadata"], ensure_ascii=False)
-
-        parts.append("<document>")
-        parts.append("<document_metadata>")
-        parts.append(f"  <document_id>{g['document_id']}</document_id>")
-        parts.append(f"  <document_type>{g['document_type']}</document_type>")
-        parts.append(f"  <title><![CDATA[{g['title']}]]></title>")
-        parts.append(f"  <url><![CDATA[{g['url']}]]></url>")
-        parts.append(f"  <metadata_json><![CDATA[{metadata_json}]]></metadata_json>")
-        parts.append("</document_metadata>")
-        parts.append("")
-        parts.append("<document_content>")
-
-        for ch in g["chunks"]:
-            parts.append(
-                f"  <chunk id='{ch['chunk_id']}'><![CDATA[{ch['content']}]]></chunk>"
-            )
-
-        parts.append("</document_content>")
-        parts.append("</document>")
-        parts.append("")
-
-    return "\n".join(parts).strip()
-
-
-async def search_surfsense_docs_async(
-    query: str,
-    db_session: AsyncSession,
-    top_k: int = 10,
-) -> str:
-    """
-    Search Surfsense documentation using vector similarity.
-
-    Args:
-        query: The search query about Surfsense usage
-        db_session: Database session for executing queries
-        top_k: Number of results to return
-
-    Returns:
-        Formatted string with relevant documentation content
-    """
-    # Get embedding for the query
-    query_embedding = await asyncio.to_thread(embed_text, query)
-
-    # Vector similarity search on chunks, joining with documents
-    stmt = (
-        select(SurfsenseDocsChunk, SurfsenseDocsDocument)
-        .join(
-            SurfsenseDocsDocument,
-            SurfsenseDocsChunk.document_id == SurfsenseDocsDocument.id,
-        )
-        .order_by(SurfsenseDocsChunk.embedding.op("<=>")(query_embedding))
-        .limit(top_k)
-    )
-
-    result = await db_session.execute(stmt)
-    rows = result.all()
-
-    return format_surfsense_docs_results(rows)
-
-
-def create_search_surfsense_docs_tool(db_session: AsyncSession):
-    """
-    Factory function to create the search_surfsense_docs tool.
-
-    The tool acquires its own short-lived ``AsyncSession`` per call via
-    :data:`async_session_maker` so the closure is safe to share across
-    HTTP requests by the compiled-agent cache. Capturing a per-request
-    session here would surface stale/closed sessions on cache hits.
-
-    Args:
-        db_session: Reserved for registry compatibility. Per-call sessions
-            are opened via :data:`async_session_maker` inside the tool body.
-
-    Returns:
-        A configured tool function for searching Surfsense documentation
-    """
-    del db_session  # per-call session — see docstring
-
-    @tool
-    async def search_surfsense_docs(query: str, top_k: int = 10) -> str:
-        """
-        Search Surfsense documentation for help with using the application.
-
-        Use this tool when the user asks questions about:
-        - How to use Surfsense features
-        - Installation and setup instructions
-        - Configuration options and settings
-        - Troubleshooting common issues
-        - Available connectors and integrations
-        - Browser extension usage
-        - API documentation
-
-        This searches the official Surfsense documentation that was indexed
-        at deployment time. It does NOT search the user's personal knowledge base.
-
-        Args:
-            query: The search query about Surfsense usage or features
-            top_k: Number of documentation chunks to retrieve (default: 10)
-
-        Returns:
-            Relevant documentation content formatted with chunk IDs for citations
-        """
-        async with async_session_maker() as db_session:
-            return await search_surfsense_docs_async(
-                query=query,
-                db_session=db_session,
-                top_k=top_k,
-            )
-
-    return search_surfsense_docs

surfsense_backend/app/app.py

@@ -43,7 +43,6 @@ from app.rate_limiter import get_real_client_ip, limiter
 from app.routes import router as crud_router
 from app.routes.auth_routes import router as auth_router
 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
 from app.utils.perf import log_system_snapshot
 
@@ -576,13 +575,6 @@ async def lifespan(app: FastAPI):
     initialize_llm_router()
     initialize_image_gen_router()
     initialize_vision_llm_router()
-    try:
-        await asyncio.wait_for(seed_surfsense_docs(), timeout=120)
-    except TimeoutError:
-        logging.getLogger(__name__).warning(
-            "Surfsense docs seeding timed out after 120s — skipping. "
-            "Docs will be indexed on the next restart."
-        )
 
     # Phase 1.7 — JIT warmup. Bounded so a stuck warmup never delays
     # worker readiness. ``shield`` so Uvicorn cancelling startup

surfsense_backend/app/db.py

@@ -1150,46 +1150,6 @@ class Chunk(BaseModel, TimestampMixin):
     document = relationship("Document", back_populates="chunks")
 
 
-class SurfsenseDocsDocument(BaseModel, TimestampMixin):
-    """
-    Surfsense documentation storage.
-    Indexed at migration time from MDX files.
-    """
-
-    __tablename__ = "surfsense_docs_documents"
-
-    source = Column(
-        String, nullable=False, unique=True, index=True
-    )  # File path: "connectors/slack.mdx"
-    title = Column(String, nullable=False)
-    content = Column(Text, nullable=False)
-    content_hash = Column(String, nullable=False, index=True)  # For detecting changes
-    embedding = Column(Vector(config.embedding_model_instance.dimension))
-    updated_at = Column(TIMESTAMP(timezone=True), nullable=True, index=True)
-
-    chunks = relationship(
-        "SurfsenseDocsChunk",
-        back_populates="document",
-        cascade="all, delete-orphan",
-    )
-
-
-class SurfsenseDocsChunk(BaseModel, TimestampMixin):
-    """Chunk storage for Surfsense documentation."""
-
-    __tablename__ = "surfsense_docs_chunks"
-
-    content = Column(Text, nullable=False)
-    embedding = Column(Vector(config.embedding_model_instance.dimension))
-
-    document_id = Column(
-        Integer,
-        ForeignKey("surfsense_docs_documents.id", ondelete="CASCADE"),
-        nullable=False,
-    )
-    document = relationship("SurfsenseDocsDocument", back_populates="chunks")
-
-
 class Podcast(BaseModel, TimestampMixin):
     """Podcast model for storing generated podcasts."""
 
@@ -2680,11 +2640,6 @@ async def setup_indexes():
                 "CREATE INDEX IF NOT EXISTS idx_documents_search_space_updated ON documents (search_space_id, updated_at DESC NULLS LAST) INCLUDE (id, title, document_type)"
             )
         )
-        await conn.execute(
-            text(
-                "CREATE INDEX IF NOT EXISTS idx_surfsense_docs_title_trgm ON surfsense_docs_documents USING gin (title gin_trgm_ops)"
-            )
-        )
 
 
 async def create_db_and_tables():

surfsense_backend/app/routes/__init__.py

@@ -55,7 +55,6 @@ from .search_source_connectors_routes import router as search_source_connectors_
 from .search_spaces_routes import router as search_spaces_router
 from .slack_add_connector_route import router as slack_add_connector_router
 from .stripe_routes import router as stripe_router
-from .surfsense_docs_routes import router as surfsense_docs_router
 from .team_memory_routes import router as team_memory_router
 from .teams_add_connector_route import router as teams_add_connector_router
 from .video_presentations_routes import router as video_presentations_router
@@ -108,7 +107,6 @@ router.include_router(new_llm_config_router)  # LLM configs with prompt configur
 router.include_router(model_list_router)  # Dynamic model catalogue from OpenRouter
 router.include_router(logs_router)
 router.include_router(circleback_webhook_router)  # Circleback meeting webhooks
-router.include_router(surfsense_docs_router)  # Surfsense documentation for citations
 router.include_router(notifications_router)  # Notifications with Zero sync
 router.include_router(
     mcp_oauth_router

surfsense_backend/app/routes/new_chat_routes.py

@@ -1785,7 +1785,6 @@ async def handle_new_chat(
                 user_id=str(user.id),
                 llm_config_id=llm_config_id,
                 mentioned_document_ids=request.mentioned_document_ids,
-                mentioned_surfsense_doc_ids=request.mentioned_surfsense_doc_ids,
                 mentioned_folder_ids=request.mentioned_folder_ids,
                 mentioned_connector_ids=request.mentioned_connector_ids,
                 mentioned_connectors=mentioned_connectors_payload,
@@ -2278,7 +2277,6 @@ async def regenerate_response(
                     user_id=str(user.id),
                     llm_config_id=llm_config_id,
                     mentioned_document_ids=request.mentioned_document_ids,
-                    mentioned_surfsense_doc_ids=request.mentioned_surfsense_doc_ids,
                     mentioned_folder_ids=request.mentioned_folder_ids,
                     mentioned_connector_ids=request.mentioned_connector_ids,
                     mentioned_connectors=mentioned_connectors_payload,

surfsense_backend/app/routes/surfsense_docs_routes.py

@@ -1,172 +0,0 @@
-"""
-Routes for Surfsense documentation.
-
-These endpoints support the citation system for Surfsense docs,
-allowing the frontend to fetch document details when a user clicks
-on a [citation:doc-XXX] link.
-"""
-
-from fastapi import APIRouter, Depends, HTTPException
-from sqlalchemy import func, select
-from sqlalchemy.ext.asyncio import AsyncSession
-from sqlalchemy.orm import selectinload
-
-from app.db import (
-    SurfsenseDocsChunk,
-    SurfsenseDocsDocument,
-    User,
-    get_async_session,
-)
-from app.schemas import PaginatedResponse
-from app.schemas.surfsense_docs import (
-    SurfsenseDocsChunkRead,
-    SurfsenseDocsDocumentRead,
-    SurfsenseDocsDocumentWithChunksRead,
-)
-from app.users import current_active_user
-from app.utils.surfsense_docs import surfsense_docs_public_url
-
-router = APIRouter()
-
-
-@router.get(
-    "/surfsense-docs/by-chunk/{chunk_id}",
-    response_model=SurfsenseDocsDocumentWithChunksRead,
-)
-async def get_surfsense_doc_by_chunk_id(
-    chunk_id: int,
-    session: AsyncSession = Depends(get_async_session),
-    user: User = Depends(current_active_user),
-):
-    """
-    Retrieves a Surfsense documentation document based on a chunk ID.
-
-    This endpoint is used by the frontend to resolve [citation:doc-XXX] links.
-    """
-    try:
-        # Get the chunk
-        chunk_result = await session.execute(
-            select(SurfsenseDocsChunk).filter(SurfsenseDocsChunk.id == chunk_id)
-        )
-        chunk = chunk_result.scalars().first()
-
-        if not chunk:
-            raise HTTPException(
-                status_code=404,
-                detail=f"Surfsense docs chunk with id {chunk_id} not found",
-            )
-
-        # Get the associated document with all its chunks
-        document_result = await session.execute(
-            select(SurfsenseDocsDocument)
-            .options(selectinload(SurfsenseDocsDocument.chunks))
-            .filter(SurfsenseDocsDocument.id == chunk.document_id)
-        )
-        document = document_result.scalars().first()
-
-        if not document:
-            raise HTTPException(
-                status_code=404,
-                detail="Surfsense docs document not found",
-            )
-
-        # Sort chunks by ID
-        sorted_chunks = sorted(document.chunks, key=lambda x: x.id)
-
-        return SurfsenseDocsDocumentWithChunksRead(
-            id=document.id,
-            title=document.title,
-            source=document.source,
-            public_url=surfsense_docs_public_url(document.source),
-            content=document.content,
-            chunks=[
-                SurfsenseDocsChunkRead(id=c.id, content=c.content)
-                for c in sorted_chunks
-            ],
-        )
-    except HTTPException:
-        raise
-    except Exception as e:
-        raise HTTPException(
-            status_code=500,
-            detail=f"Failed to retrieve Surfsense documentation: {e!s}",
-        ) from e
-
-
-@router.get(
-    "/surfsense-docs",
-    response_model=PaginatedResponse[SurfsenseDocsDocumentRead],
-)
-async def list_surfsense_docs(
-    page: int = 0,
-    page_size: int = 50,
-    title: str | None = None,
-    session: AsyncSession = Depends(get_async_session),
-    user: User = Depends(current_active_user),
-):
-    """
-    List all Surfsense documentation documents.
-
-    Args:
-        page: Zero-based page index.
-        page_size: Number of items per page (default: 50).
-        title: Optional title filter (case-insensitive substring match).
-        session: Database session (injected).
-        user: Current authenticated user (injected).
-
-    Returns:
-        PaginatedResponse[SurfsenseDocsDocumentRead]: Paginated list of Surfsense docs.
-    """
-    try:
-        # Base query
-        query = select(SurfsenseDocsDocument)
-        count_query = select(func.count()).select_from(SurfsenseDocsDocument)
-
-        # Filter by title if provided
-        if title and title.strip():
-            query = query.filter(SurfsenseDocsDocument.title.ilike(f"%{title}%"))
-            count_query = count_query.filter(
-                SurfsenseDocsDocument.title.ilike(f"%{title}%")
-            )
-
-        # Get total count
-        total_result = await session.execute(count_query)
-        total = total_result.scalar() or 0
-
-        # Calculate offset
-        offset = page * page_size
-
-        # Get paginated results
-        result = await session.execute(
-            query.order_by(SurfsenseDocsDocument.title).offset(offset).limit(page_size)
-        )
-        docs = result.scalars().all()
-
-        # Convert to response format
-        items = [
-            SurfsenseDocsDocumentRead(
-                id=doc.id,
-                title=doc.title,
-                source=doc.source,
-                public_url=surfsense_docs_public_url(doc.source),
-                content=doc.content,
-                created_at=doc.created_at,
-                updated_at=doc.updated_at,
-            )
-            for doc in docs
-        ]
-
-        has_more = (offset + len(items)) < total
-
-        return PaginatedResponse(
-            items=items,
-            total=total,
-            page=page,
-            page_size=page_size,
-            has_more=has_more,
-        )
-    except Exception as e:
-        raise HTTPException(
-            status_code=500,
-            detail=f"Failed to list Surfsense documentation: {e!s}",
-        ) from e

surfsense_backend/app/schemas/new_chat.py

@@ -239,9 +239,6 @@ class NewChatRequest(BaseModel):
     mentioned_document_ids: list[int] | None = (
         None  # Optional document IDs mentioned with @ in the chat
     )
-    mentioned_surfsense_doc_ids: list[int] | None = (
-        None  # Optional SurfSense documentation IDs mentioned with @ in the chat
-    )
     mentioned_folder_ids: list[int] | None = Field(
         default=None,
         description=(
@@ -326,7 +323,6 @@ class RegenerateRequest(BaseModel):
         None  # New user query (for edit). None = reload with same query
     )
     mentioned_document_ids: list[int] | None = None
-    mentioned_surfsense_doc_ids: list[int] | None = None
     mentioned_folder_ids: list[int] | None = Field(
         default=None,
         description=(

surfsense_backend/app/schemas/surfsense_docs.py

@@ -1,43 +0,0 @@
-"""
-Schemas for Surfsense documentation.
-"""
-
-from datetime import datetime
-
-from pydantic import BaseModel, ConfigDict
-
-
-class SurfsenseDocsChunkRead(BaseModel):
-    """Schema for a Surfsense docs chunk."""
-
-    id: int
-    content: str
-
-    model_config = ConfigDict(from_attributes=True)
-
-
-class SurfsenseDocsDocumentRead(BaseModel):
-    """Schema for a Surfsense docs document (without chunks)."""
-
-    id: int
-    title: str
-    source: str
-    public_url: str
-    content: str
-    created_at: datetime | None = None
-    updated_at: datetime | None = None
-
-    model_config = ConfigDict(from_attributes=True)
-
-
-class SurfsenseDocsDocumentWithChunksRead(BaseModel):
-    """Schema for a Surfsense docs document with its chunks."""
-
-    id: int
-    title: str
-    source: str
-    public_url: str
-    content: str
-    chunks: list[SurfsenseDocsChunkRead]
-
-    model_config = ConfigDict(from_attributes=True)

surfsense_backend/app/tasks/chat/stream_new_chat.py

@@ -25,7 +25,6 @@ from uuid import UUID
 import anyio
 from langchain_core.messages import HumanMessage
 from sqlalchemy.future import select
-from sqlalchemy.orm import selectinload
 
 from app.agents.multi_agent_chat import create_multi_agent_chat_deep_agent
 from app.agents.new_chat.chat_deepagent import create_surfsense_deep_agent
@@ -55,7 +54,6 @@ from app.db import (
     NewChatThread,
     Report,
     SearchSourceConnectorType,
-    SurfsenseDocsDocument,
     async_session_maker,
     shielded_async_session,
 )
@@ -77,7 +75,6 @@ from app.tasks.chat.streaming.helpers.interrupt_inspector import (
 )
 from app.utils.content_utils import bootstrap_history_from_db
 from app.utils.perf import get_perf_logger, log_system_snapshot, trim_native_heap
-from app.utils.surfsense_docs import surfsense_docs_public_url
 from app.utils.user_message_multimodal import build_human_message_content
 
 _background_tasks: set[asyncio.Task] = set()
@@ -198,58 +195,6 @@ def _extract_chunk_parts(chunk: Any) -> dict[str, Any]:
     return out
 
 
-def format_mentioned_surfsense_docs_as_context(
-    documents: list[SurfsenseDocsDocument],
-) -> str:
-    """Format mentioned SurfSense documentation as context for the agent."""
-    if not documents:
-        return ""
-
-    context_parts = ["<mentioned_surfsense_docs>"]
-    context_parts.append(
-        "The user has explicitly mentioned the following SurfSense documentation pages. "
-        "These are official documentation about how to use SurfSense and should be used to answer questions about the application. "
-        "Use [citation:CHUNK_ID] format for citations (e.g., [citation:doc-123])."
-    )
-
-    for doc in documents:
-        public_url = surfsense_docs_public_url(doc.source)
-        metadata_json = json.dumps(
-            {"source": doc.source, "public_url": public_url}, ensure_ascii=False
-        )
-
-        context_parts.append("<document>")
-        context_parts.append("<document_metadata>")
-        context_parts.append(f"  <document_id>doc-{doc.id}</document_id>")
-        context_parts.append("  <document_type>SURFSENSE_DOCS</document_type>")
-        context_parts.append(f"  <title><![CDATA[{doc.title}]]></title>")
-        context_parts.append(f"  <url><![CDATA[{public_url}]]></url>")
-        context_parts.append(
-            f"  <metadata_json><![CDATA[{metadata_json}]]></metadata_json>"
-        )
-        context_parts.append("</document_metadata>")
-        context_parts.append("")
-        context_parts.append("<document_content>")
-
-        if hasattr(doc, "chunks") and doc.chunks:
-            for chunk in doc.chunks:
-                context_parts.append(
-                    f"  <chunk id='doc-{chunk.id}'><![CDATA[{chunk.content}]]></chunk>"
-                )
-        else:
-            context_parts.append(
-                f"  <chunk id='doc-0'><![CDATA[{doc.content}]]></chunk>"
-            )
-
-        context_parts.append("</document_content>")
-        context_parts.append("</document>")
-        context_parts.append("")
-
-    context_parts.append("</mentioned_surfsense_docs>")
-
-    return "\n".join(context_parts)
-
-
 def extract_todos_from_deepagents(command_output) -> dict:
     """
     Extract todos from deepagents' TodoListMiddleware Command output.
@@ -837,7 +782,6 @@ async def stream_new_chat(
     user_id: str | None = None,
     llm_config_id: int = -1,
     mentioned_document_ids: list[int] | None = None,
-    mentioned_surfsense_doc_ids: list[int] | None = None,
     mentioned_folder_ids: list[int] | None = None,
     mentioned_connector_ids: list[int] | None = None,
     mentioned_connectors: list[dict[str, Any]] | None = None,
@@ -869,7 +813,6 @@ async def stream_new_chat(
         llm_config_id: The LLM configuration ID (default: -1 for first global config)
         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
         mentioned_folder_ids: Optional list of knowledge-base folder IDs mentioned with @ (cloud mode)
         checkpoint_id: Optional checkpoint ID to rewind/fork from (for edit/reload operations)
 
@@ -1295,19 +1238,7 @@ async def stream_new_chat(
 
         # Mentioned KB documents are now handled by KnowledgeBaseSearchMiddleware
         # which merges them into the scoped filesystem with full document
-        # structure. Only SurfSense docs and report context are inlined here.
+        # structure. Only report context is inlined here.
-
-        # Fetch mentioned SurfSense docs if any
-        mentioned_surfsense_docs: list[SurfsenseDocsDocument] = []
-        if mentioned_surfsense_doc_ids:
-            result = await session.execute(
-                select(SurfsenseDocsDocument)
-                .options(selectinload(SurfsenseDocsDocument.chunks))
-                .filter(
-                    SurfsenseDocsDocument.id.in_(mentioned_surfsense_doc_ids),
-                )
-            )
-            mentioned_surfsense_docs = list(result.scalars().all())
 
         # Fetch the most recent report(s) in this thread so the LLM can
         # easily find report_id for versioning decisions, instead of
@@ -1341,10 +1272,7 @@ async def stream_new_chat(
         agent_user_query = user_query
         accepted_folder_ids: list[int] = []
         if fs_mode == FilesystemMode.CLOUD.value and (
-            mentioned_document_ids
+            mentioned_document_ids or mentioned_folder_ids or mentioned_documents
-            or mentioned_surfsense_doc_ids
-            or mentioned_folder_ids
-            or mentioned_documents
         ):
             from app.schemas.new_chat import (
                 MentionedDocumentInfo as _MentionedDocumentInfo,
@@ -1370,23 +1298,17 @@ async def stream_new_chat(
                 search_space_id=search_space_id,
                 mentioned_documents=chip_objs,
                 mentioned_document_ids=mentioned_document_ids,
-                mentioned_surfsense_doc_ids=mentioned_surfsense_doc_ids,
                 mentioned_folder_ids=mentioned_folder_ids,
             )
             agent_user_query = substitute_in_text(user_query, resolved.token_to_path)
             accepted_folder_ids = resolved.mentioned_folder_ids
 
-        # Format the user query with context (SurfSense docs + reports only).
+        # Format the user query with context (reports only).
         # Uses ``agent_user_query`` so the LLM sees backtick-wrapped paths
         # instead of bare ``@title`` tokens.
         final_query = agent_user_query
         context_parts = []
 
-        if mentioned_surfsense_docs:
-            context_parts.append(
-                format_mentioned_surfsense_docs_as_context(mentioned_surfsense_docs)
-            )
-
         if mentioned_connectors:
             connector_lines = []
             for connector in mentioned_connectors:
@@ -1617,12 +1539,8 @@ async def stream_new_chat(
         stream_result.content_builder = AssistantContentBuilder()
 
         # Initial thinking step - analyzing the request
-        if mentioned_surfsense_docs:
+        initial_title = "Understanding your request"
-            initial_title = "Analyzing referenced content"
+        action_verb = "Processing"
-            action_verb = "Analyzing"
-        else:
-            initial_title = "Understanding your request"
-            action_verb = "Processing"
 
         processing_parts = []
         if user_query.strip():
@@ -1633,18 +1551,6 @@ async def stream_new_chat(
         else:
             processing_parts.append("(message)")
 
-        if mentioned_surfsense_docs:
-            doc_names = []
-            for doc in mentioned_surfsense_docs:
-                title = doc.title
-                if len(title) > 30:
-                    title = title[:27] + "..."
-                doc_names.append(title)
-            if len(doc_names) == 1:
-                processing_parts.append(f"[{doc_names[0]}]")
-            else:
-                processing_parts.append(f"[{len(doc_names)} docs]")
-
         initial_items = [f"{action_verb}: {' '.join(processing_parts)}"]
         initial_step_id = "thinking-1"
 
@@ -1664,10 +1570,10 @@ async def stream_new_chat(
             items=initial_items,
         )
 
-        # These ORM objects (with eagerly-loaded chunks) can be very large.
+        # These ORM objects can be large. They're only needed to build context
-        # They're only needed to build context strings already copied into
+        # strings already copied into final_query / langchain_messages —
-        # final_query / langchain_messages — release them before streaming.
+        # release them before streaming.
-        del mentioned_surfsense_docs, recent_reports
+        del recent_reports
         del langchain_messages, final_query
 
         # Check if this is the first assistant response so we can generate

surfsense_backend/app/tasks/chat/streaming/context/__init__.py

@@ -1,15 +1,11 @@
-"""Pre-agent context shaping: mentioned-doc rendering and todos extraction."""
+"""Pre-agent context shaping: todos extraction."""
 
 from __future__ import annotations
 
 from app.tasks.chat.streaming.context.deepagents_todos import (
     extract_todos_from_deepagents,
 )
-from app.tasks.chat.streaming.context.mentioned_docs import (
-    format_mentioned_surfsense_docs_as_context,
-)
 
 __all__ = [
     "extract_todos_from_deepagents",
-    "format_mentioned_surfsense_docs_as_context",
 ]

surfsense_backend/app/tasks/chat/streaming/context/mentioned_docs.py

@@ -1,58 +0,0 @@
-"""Render user-mentioned SurfSense docs as XML context for the agent."""
-
-from __future__ import annotations
-
-import json
-
-from app.db import SurfsenseDocsDocument
-from app.utils.surfsense_docs import surfsense_docs_public_url
-
-
-def format_mentioned_surfsense_docs_as_context(
-    documents: list[SurfsenseDocsDocument],
-) -> str:
-    if not documents:
-        return ""
-
-    context_parts = ["<mentioned_surfsense_docs>"]
-    context_parts.append(
-        "The user has explicitly mentioned the following SurfSense documentation pages. "
-        "These are official documentation about how to use SurfSense and should be used to answer questions about the application. "
-        "Use [citation:CHUNK_ID] format for citations (e.g., [citation:doc-123])."
-    )
-
-    for doc in documents:
-        public_url = surfsense_docs_public_url(doc.source)
-        metadata_json = json.dumps(
-            {"source": doc.source, "public_url": public_url}, ensure_ascii=False
-        )
-
-        context_parts.append("<document>")
-        context_parts.append("<document_metadata>")
-        context_parts.append(f"  <document_id>doc-{doc.id}</document_id>")
-        context_parts.append("  <document_type>SURFSENSE_DOCS</document_type>")
-        context_parts.append(f"  <title><![CDATA[{doc.title}]]></title>")
-        context_parts.append(f"  <url><![CDATA[{public_url}]]></url>")
-        context_parts.append(
-            f"  <metadata_json><![CDATA[{metadata_json}]]></metadata_json>"
-        )
-        context_parts.append("</document_metadata>")
-        context_parts.append("")
-        context_parts.append("<document_content>")
-
-        if hasattr(doc, "chunks") and doc.chunks:
-            for chunk in doc.chunks:
-                context_parts.append(
-                    f"  <chunk id='doc-{chunk.id}'><![CDATA[{chunk.content}]]></chunk>"
-                )
-        else:
-            context_parts.append(
-                f"  <chunk id='doc-0'><![CDATA[{doc.content}]]></chunk>"
-            )
-
-        context_parts.append("</document_content>")
-        context_parts.append("</document>")
-        context_parts.append("")
-
-    context_parts.append("</mentioned_surfsense_docs>")
-    return "\n".join(context_parts)

surfsense_backend/app/tasks/chat/streaming/flows/new_chat/initial_thinking_step.py

@@ -1,8 +1,8 @@
 """Build and emit the first ``thinking-1`` step for a new-chat turn.
 
 The step title and "Processing X" items are derived from what the user sent
-(text snippet, image count, mentioned doc titles) so the FE can render a
+(text snippet, image count) so the FE can render a meaningful placeholder
-meaningful placeholder while the agent stream warms up.
+while the agent stream warms up.
 
 ``thinking-1`` is the canonical id for this step — every subsequent
 ``thinking-N`` produced by ``stream_agent_events`` folds into the same
@@ -15,7 +15,6 @@ from collections.abc import Iterator
 from dataclasses import dataclass
 from typing import Any
 
-from app.db import SurfsenseDocsDocument
 from app.services.new_streaming_service import VercelStreamingService
 
 
@@ -37,14 +36,9 @@ def build_initial_thinking_step(
     *,
     user_query: str,
     user_image_data_urls: list[str] | None,
-    mentioned_surfsense_docs: list[SurfsenseDocsDocument],
 ) -> InitialThinkingStep:
-    if mentioned_surfsense_docs:
+    title = "Understanding your request"
-        title = "Analyzing referenced content"
+    action_verb = "Processing"
-        action_verb = "Analyzing"
-    else:
-        title = "Understanding your request"
-        action_verb = "Processing"
 
     processing_parts: list[str] = []
     if user_query.strip():
@@ -55,18 +49,6 @@ def build_initial_thinking_step(
     else:
         processing_parts.append("(message)")
 
-    if mentioned_surfsense_docs:
-        doc_names: list[str] = []
-        for doc in mentioned_surfsense_docs:
-            t = doc.title
-            if len(t) > 30:
-                t = t[:27] + "..."
-            doc_names.append(t)
-        if len(doc_names) == 1:
-            processing_parts.append(f"[{doc_names[0]}]")
-        else:
-            processing_parts.append(f"[{len(doc_names)} docs]")
-
     items = [f"{action_verb}: {' '.join(processing_parts)}"]
     return InitialThinkingStep(step_id="thinking-1", title=title, items=items)
 

surfsense_backend/app/tasks/chat/streaming/flows/new_chat/input_state.py

@@ -5,20 +5,17 @@ Pipeline:
   1. **History bootstrap** — only for cloned chats with no LangGraph checkpoint
      yet; flips the per-thread ``needs_history_bootstrap`` flag back to False
      once the rows are loaded.
-  2. **Mentioned SurfSense docs** — eager-load chunks so the formatter has the
+  2. **Recent reports** — top 3 by id desc with non-null content, so the LLM
-     full content without a second roundtrip.
-  3. **Recent reports** — top 3 by id desc with non-null content, so the LLM
      can resolve ``report_id`` for versioning without spelunking history.
-  4. **@-mention resolve** (cloud mode) — substitute ``@title`` tokens in the
+  3. **@-mention resolve** (cloud mode) — substitute ``@title`` tokens in the
      query with canonical ``\`/documents/...\``` paths the LLM expects.
-  5. **Context block render** — XML-wrap surfsense docs + reports, prepend to
+  4. **Context block render** — XML-wrap recent reports, prepend to the
-     the rewritten query, optionally prefix with display name for SEARCH_SPACE
+     rewritten query, optionally prefix with display name for SEARCH_SPACE
      visibility.
-  6. **HumanMessage** — multimodal content if images are attached.
+  5. **HumanMessage** — multimodal content if images are attached.
 
 Returns the assembled ``input_state`` dict plus side-channel data the
-orchestrator needs downstream (``accepted_folder_ids`` for runtime context;
+orchestrator needs downstream (``accepted_folder_ids`` for runtime context).
-``mentioned_surfsense_docs`` for the initial thinking step).
 """
 
 from __future__ import annotations
@@ -30,7 +27,6 @@ from typing import Any
 from langchain_core.messages import HumanMessage
 from sqlalchemy.ext.asyncio import AsyncSession
 from sqlalchemy.future import select
-from sqlalchemy.orm import selectinload
 
 from app.agents.new_chat.filesystem_selection import FilesystemMode
 from app.agents.new_chat.mention_resolver import resolve_mentions, substitute_in_text
@@ -38,10 +34,6 @@ from app.db import (
     ChatVisibility,
     NewChatThread,
     Report,
-    SurfsenseDocsDocument,
-)
-from app.tasks.chat.streaming.context.mentioned_docs import (
-    format_mentioned_surfsense_docs_as_context,
 )
 from app.utils.content_utils import bootstrap_history_from_db
 from app.utils.user_message_multimodal import build_human_message_content
@@ -55,13 +47,10 @@ class NewChatInputState:
 
     ``input_state`` is fed straight to the agent. ``accepted_folder_ids``
     feeds the runtime context (the resolver may have dropped some chips).
-    ``mentioned_surfsense_docs`` is consumed by the initial thinking-step
-    builder for the FE placeholder before the agent stream starts.
     """
 
     input_state: dict[str, Any]
     accepted_folder_ids: list[int]
-    mentioned_surfsense_docs: list[SurfsenseDocsDocument]
 
 
 async def build_new_chat_input_state(
@@ -72,7 +61,6 @@ async def build_new_chat_input_state(
     user_query: str,
     user_image_data_urls: list[str] | None,
     mentioned_document_ids: list[int] | None,
-    mentioned_surfsense_doc_ids: list[int] | None,
     mentioned_folder_ids: list[int] | None,
     mentioned_documents: list[dict[str, Any]] | None,
     needs_history_bootstrap: bool,
@@ -96,15 +84,6 @@ async def build_new_chat_input_state(
             thread.needs_history_bootstrap = False
             await session.commit()
 
-    mentioned_surfsense_docs: list[SurfsenseDocsDocument] = []
-    if mentioned_surfsense_doc_ids:
-        result = await session.execute(
-            select(SurfsenseDocsDocument)
-            .options(selectinload(SurfsenseDocsDocument.chunks))
-            .filter(SurfsenseDocsDocument.id.in_(mentioned_surfsense_doc_ids))
-        )
-        mentioned_surfsense_docs = list(result.scalars().all())
-
     # Top 3 reports keyed by id desc (newest first) with content present,
     # surfaced inline so the LLM resolves ``report_id`` for versioning without
     # digging through conversation history.
@@ -125,14 +104,12 @@ async def build_new_chat_input_state(
         user_query=user_query,
         filesystem_mode=filesystem_mode,
         mentioned_document_ids=mentioned_document_ids,
-        mentioned_surfsense_doc_ids=mentioned_surfsense_doc_ids,
         mentioned_folder_ids=mentioned_folder_ids,
         mentioned_documents=mentioned_documents,
     )
 
     final_query = _render_query_with_context(
         agent_user_query=agent_user_query,
-        mentioned_surfsense_docs=mentioned_surfsense_docs,
         recent_reports=recent_reports,
     )
 
@@ -154,7 +131,6 @@ async def build_new_chat_input_state(
     return NewChatInputState(
         input_state=input_state,
         accepted_folder_ids=accepted_folder_ids,
-        mentioned_surfsense_docs=mentioned_surfsense_docs,
     )
 
 
@@ -165,7 +141,6 @@ async def _resolve_mentions_for_query(
     user_query: str,
     filesystem_mode: str,
     mentioned_document_ids: list[int] | None,
-    mentioned_surfsense_doc_ids: list[int] | None,
     mentioned_folder_ids: list[int] | None,
     mentioned_documents: list[dict[str, Any]] | None,
 ) -> tuple[str, list[int]]:
@@ -187,10 +162,7 @@ async def _resolve_mentions_for_query(
     accepted_folder_ids: list[int] = []
 
     has_any_mention = bool(
-        mentioned_document_ids
+        mentioned_document_ids or mentioned_folder_ids or mentioned_documents
-        or mentioned_surfsense_doc_ids
-        or mentioned_folder_ids
-        or mentioned_documents
     )
     if filesystem_mode != FilesystemMode.CLOUD.value or not has_any_mention:
         return agent_user_query, accepted_folder_ids
@@ -214,7 +186,6 @@ async def _resolve_mentions_for_query(
         search_space_id=search_space_id,
         mentioned_documents=chip_objs,
         mentioned_document_ids=mentioned_document_ids,
-        mentioned_surfsense_doc_ids=mentioned_surfsense_doc_ids,
         mentioned_folder_ids=mentioned_folder_ids,
     )
     agent_user_query = substitute_in_text(user_query, resolved.token_to_path)
@@ -225,17 +196,11 @@ async def _resolve_mentions_for_query(
 def _render_query_with_context(
     *,
     agent_user_query: str,
-    mentioned_surfsense_docs: list[SurfsenseDocsDocument],
     recent_reports: list[Report],
 ) -> str:
-    """Prepend surfsense-docs + recent-reports XML blocks to the user query."""
+    """Prepend recent-reports XML block to the user query."""
     context_parts: list[str] = []
 
-    if mentioned_surfsense_docs:
-        context_parts.append(
-            format_mentioned_surfsense_docs_as_context(mentioned_surfsense_docs)
-        )
-
     if recent_reports:
         report_lines: list[str] = []
         for r in recent_reports:

surfsense_backend/app/tasks/chat/streaming/flows/new_chat/orchestrator.py

@@ -123,7 +123,6 @@ async def stream_new_chat(
     user_id: str | None = None,
     llm_config_id: int = -1,
     mentioned_document_ids: list[int] | None = None,
-    mentioned_surfsense_doc_ids: list[int] | None = None,
     mentioned_folder_ids: list[int] | None = None,
     mentioned_documents: list[dict[str, Any]] | None = None,
     checkpoint_id: str | None = None,
@@ -435,7 +434,6 @@ async def stream_new_chat(
             user_query=user_query,
             user_image_data_urls=user_image_data_urls,
             mentioned_document_ids=mentioned_document_ids,
-            mentioned_surfsense_doc_ids=mentioned_surfsense_doc_ids,
             mentioned_folder_ids=mentioned_folder_ids,
             mentioned_documents=mentioned_documents,
             needs_history_bootstrap=needs_history_bootstrap,
@@ -447,7 +445,6 @@ async def stream_new_chat(
         )
         input_state = assembled.input_state
         accepted_folder_ids = assembled.accepted_folder_ids
-        mentioned_surfsense_docs = assembled.mentioned_surfsense_docs
         _perf_log.info(
             "[stream_new_chat] History bootstrap + doc/report queries in %.3fs",
             time.perf_counter() - _t0,
@@ -560,7 +557,6 @@ async def stream_new_chat(
         initial_step = build_initial_thinking_step(
             user_query=user_query,
             user_image_data_urls=user_image_data_urls,
-            mentioned_surfsense_docs=mentioned_surfsense_docs,
         )
         for sse in iter_initial_thinking_step_frame(
             initial_step,
@@ -575,7 +571,7 @@ async def stream_new_chat(
         # Drop the heavy ORM objects + the container that holds them so they
         # aren't retained for the entire streaming duration. ``input_state``
         # already carries the langchain_messages list independently.
-        del assembled, mentioned_surfsense_docs
+        del assembled
 
         title_task = spawn_title_task(
             chat_id=chat_id,

surfsense_backend/app/tasks/surfsense_docs_indexer.py

@@ -1,249 +0,0 @@
-"""
-Surfsense documentation indexer.
-Indexes MDX documentation files at startup.
-"""
-
-import hashlib
-import logging
-import re
-from datetime import UTC, datetime
-from pathlib import Path
-
-from sqlalchemy import delete as sa_delete, select
-from sqlalchemy.ext.asyncio import AsyncSession
-from sqlalchemy.orm import selectinload
-from sqlalchemy.orm.attributes import set_committed_value
-
-from app.config import config
-from app.db import SurfsenseDocsChunk, SurfsenseDocsDocument, async_session_maker
-from app.utils.document_converters import embed_text
-
-logger = logging.getLogger(__name__)
-
-
-async def _safe_set_docs_chunks(
-    session: AsyncSession, document: SurfsenseDocsDocument, chunks: list
-) -> None:
-    """safe_set_chunks variant for the SurfsenseDocsDocument/Chunk models."""
-    if document.id is not None:
-        await session.execute(
-            sa_delete(SurfsenseDocsChunk).where(
-                SurfsenseDocsChunk.document_id == document.id
-            )
-        )
-        for chunk in chunks:
-            chunk.document_id = document.id
-
-    set_committed_value(document, "chunks", chunks)
-    session.add_all(chunks)
-
-
-# Path to docs relative to project root
-DOCS_DIR = (
-    Path(__file__).resolve().parent.parent.parent.parent
-    / "surfsense_web"
-    / "content"
-    / "docs"
-)
-
-
-def parse_mdx_frontmatter(content: str) -> tuple[str, str]:
-    """
-    Parse MDX file to extract frontmatter title and content.
-
-    Args:
-        content: Raw MDX file content
-
-    Returns:
-        Tuple of (title, content_without_frontmatter)
-    """
-    # Match frontmatter between --- markers
-    frontmatter_pattern = r"^---\s*\n(.*?)\n---\s*\n"
-    match = re.match(frontmatter_pattern, content, re.DOTALL)
-
-    if match:
-        frontmatter = match.group(1)
-        content_without_frontmatter = content[match.end() :]
-
-        # Extract title from frontmatter
-        title_match = re.search(r"^title:\s*(.+)$", frontmatter, re.MULTILINE)
-        title = title_match.group(1).strip() if title_match else "Untitled"
-
-        # Remove quotes if present
-        title = title.strip("\"'")
-
-        return title, content_without_frontmatter.strip()
-
-    return "Untitled", content.strip()
-
-
-def get_all_mdx_files() -> list[Path]:
-    """
-    Get all MDX files from the docs directory.
-
-    Returns:
-        List of Path objects for each MDX file
-    """
-    if not DOCS_DIR.exists():
-        logger.warning(f"Docs directory not found: {DOCS_DIR}")
-        return []
-
-    return list(DOCS_DIR.rglob("*.mdx"))
-
-
-def generate_surfsense_docs_content_hash(content: str) -> str:
-    """Generate SHA-256 hash for Surfsense docs content."""
-    return hashlib.sha256(content.encode("utf-8")).hexdigest()
-
-
-def create_surfsense_docs_chunks(content: str) -> list[SurfsenseDocsChunk]:
-    """
-    Create chunks from Surfsense documentation content.
-
-    Args:
-        content: Document content to chunk
-
-    Returns:
-        List of SurfsenseDocsChunk objects with embeddings
-    """
-    return [
-        SurfsenseDocsChunk(
-            content=chunk.text,
-            embedding=embed_text(chunk.text),
-        )
-        for chunk in config.chunker_instance.chunk(content)
-    ]
-
-
-async def index_surfsense_docs(session: AsyncSession) -> tuple[int, int, int, int]:
-    """
-    Index all Surfsense documentation files.
-
-    Args:
-        session: SQLAlchemy async session
-
-    Returns:
-        Tuple of (created, updated, skipped, deleted) counts
-    """
-    created = 0
-    updated = 0
-    skipped = 0
-    deleted = 0
-
-    # Get all existing docs from database
-    existing_docs_result = await session.execute(
-        select(SurfsenseDocsDocument).options(
-            selectinload(SurfsenseDocsDocument.chunks)
-        )
-    )
-    existing_docs = {doc.source: doc for doc in existing_docs_result.scalars().all()}
-
-    # Track which sources we've processed
-    processed_sources = set()
-
-    # Get all MDX files
-    mdx_files = get_all_mdx_files()
-    logger.info(f"Found {len(mdx_files)} MDX files to index")
-
-    for mdx_file in mdx_files:
-        try:
-            source = str(mdx_file.relative_to(DOCS_DIR))
-            processed_sources.add(source)
-
-            # Read file content
-            raw_content = mdx_file.read_text(encoding="utf-8")
-            title, content = parse_mdx_frontmatter(raw_content)
-            content_hash = generate_surfsense_docs_content_hash(raw_content)
-
-            if source in existing_docs:
-                existing_doc = existing_docs[source]
-
-                # Check if content changed
-                if existing_doc.content_hash == content_hash:
-                    logger.debug(f"Skipping unchanged: {source}")
-                    skipped += 1
-                    continue
-
-                # Content changed - update document
-                logger.info(f"Updating changed document: {source}")
-
-                # Create new chunks
-                chunks = create_surfsense_docs_chunks(content)
-
-                # Update document fields
-                existing_doc.title = title
-                existing_doc.content = content
-                existing_doc.content_hash = content_hash
-                existing_doc.embedding = embed_text(content)
-                await _safe_set_docs_chunks(session, existing_doc, chunks)
-                existing_doc.updated_at = datetime.now(UTC)
-
-                updated += 1
-            else:
-                # New document - create it
-                logger.info(f"Creating new document: {source}")
-
-                chunks = create_surfsense_docs_chunks(content)
-
-                document = SurfsenseDocsDocument(
-                    source=source,
-                    title=title,
-                    content=content,
-                    content_hash=content_hash,
-                    embedding=embed_text(content),
-                    chunks=chunks,
-                    updated_at=datetime.now(UTC),
-                )
-
-                session.add(document)
-                created += 1
-
-        except Exception as e:
-            logger.error(f"Error processing {mdx_file}: {e}", exc_info=True)
-            continue
-
-    # Delete documents for removed files
-    for source, doc in existing_docs.items():
-        if source not in processed_sources:
-            logger.info(f"Deleting removed document: {source}")
-            await session.delete(doc)
-            deleted += 1
-
-    # Commit all changes
-    await session.commit()
-
-    logger.info(
-        f"Indexing complete: {created} created, {updated} updated, "
-        f"{skipped} skipped, {deleted} deleted"
-    )
-
-    return created, updated, skipped, deleted
-
-
-async def seed_surfsense_docs() -> tuple[int, int, int, int]:
-    """
-    Seed Surfsense documentation into the database.
-
-    This function indexes all MDX files from the docs directory.
-    It handles creating, updating, and deleting docs based on content changes.
-
-    Returns:
-        Tuple of (created, updated, skipped, deleted) counts
-        Returns (0, 0, 0, 0) if an error occurs
-    """
-    logger.info("Starting Surfsense docs indexing...")
-
-    try:
-        async with async_session_maker() as session:
-            created, updated, skipped, deleted = await index_surfsense_docs(session)
-
-        logger.info(
-            f"Surfsense docs indexing complete: "
-            f"created={created}, updated={updated}, skipped={skipped}, deleted={deleted}"
-        )
-
-        return created, updated, skipped, deleted
-
-    except Exception as e:
-        logger.error(f"Failed to seed Surfsense docs: {e}", exc_info=True)
-        return 0, 0, 0, 0

surfsense_backend/app/utils/surfsense_docs.py

@@ -1,13 +0,0 @@
-"""Utilities for SurfSense's built-in documentation index."""
-
-from pathlib import PurePosixPath
-
-DOCS_PUBLIC_ROOT = PurePosixPath("/docs")
-
-
-def surfsense_docs_public_url(source: str) -> str:
-    """Return the public docs route for an indexed documentation source path."""
-    docs_path = PurePosixPath(source).with_suffix("")
-    if docs_path.name == "index":
-        docs_path = docs_path.parent
-    return (DOCS_PUBLIC_ROOT / docs_path).as_posix()

surfsense_backend/scripts/seed_surfsense_docs.py

@@ -1,40 +0,0 @@
-#!/usr/bin/env python
-"""
-Seed Surfsense documentation into the database.
-
-CLI wrapper for the seed_surfsense_docs function.
-Can be run manually for debugging or re-indexing.
-
-Usage:
-    python scripts/seed_surfsense_docs.py
-"""
-
-import asyncio
-import sys
-from pathlib import Path
-
-# Add the parent directory to the path so we can import app modules
-sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
-
-from app.tasks.surfsense_docs_indexer import seed_surfsense_docs
-
-
-def main():
-    """CLI entry point for seeding Surfsense docs."""
-    print("=" * 50)
-    print("  Surfsense Documentation Seeding")
-    print("=" * 50)
-
-    created, updated, skipped, deleted = asyncio.run(seed_surfsense_docs())
-
-    print()
-    print("Results:")
-    print(f"  Created: {created}")
-    print(f"  Updated: {updated}")
-    print(f"  Skipped: {skipped}")
-    print(f"  Deleted: {deleted}")
-    print("=" * 50)
-
-
-if __name__ == "__main__":
-    main()

surfsense_backend/tests/unit/agents/new_chat/test_default_permissions_layering.py

@@ -60,7 +60,6 @@ class TestReadOnlyToolsAllowed:
             "glob",
             "web_search",
             "scrape_webpage",
-            "search_surfsense_docs",
             "get_connected_accounts",
             "write_todos",
             "task",

surfsense_backend/tests/unit/agents/new_chat/test_specialized_subagents.py

@@ -22,12 +22,6 @@ from app.agents.new_chat.subagents.config import (
 # ---------------------------------------------------------------------------
 
 
-@tool
-def search_surfsense_docs(query: str) -> str:
-    """Search the user's KB."""
-    return ""
-
-
 @tool
 def web_search(query: str) -> str:
     """Search the public web."""
@@ -95,7 +89,6 @@ def generate_report(topic: str) -> str:
 
 
 ALL_TOOLS = [
-    search_surfsense_docs,
     web_search,
     scrape_webpage,
     read_file,
@@ -161,7 +154,7 @@ class TestReportWriterSubagent:
         names = {t.name for t in spec["tools"]}  # type: ignore[index]
         assert names == REPORT_WRITER_TOOLS & {t.name for t in ALL_TOOLS}
         assert "generate_report" in names
-        assert "search_surfsense_docs" in names
+        assert "read_file" in names
 
     def test_deny_rules_block_writes_but_allow_generate_report(self) -> None:
         spec = build_report_writer_subagent(tools=ALL_TOOLS)
@@ -272,9 +265,9 @@ class TestFilterToolsWarningSuppression:
             # Allowed set asks for two registry tools (one present, one
             # not) plus a bunch of middleware-provided names.
             _filter_tools(
-                [search_surfsense_docs],
+                [web_search],
                 allowed_names={
-                    "search_surfsense_docs",
+                    "web_search",
                     "scrape_webpage",  # legitimately missing → should warn
                     "read_file",  # mw-provided → suppressed
                     "ls",
@@ -322,7 +315,6 @@ class TestDenyPatternsCoverage:
 
     def test_deny_patterns_do_not_match_safe_read_tools(self) -> None:
         canonical_reads = [
-            "search_surfsense_docs",
             "read_file",
             "ls_tree",
             "grep",

surfsense_backend/tests/unit/tasks/chat/streaming/test_parallel_refactor_parity.py

@@ -25,7 +25,6 @@ from __future__ import annotations
 
 import asyncio
 import inspect
-from dataclasses import dataclass
 from typing import Any
 from unittest.mock import AsyncMock, patch
 
@@ -140,45 +139,28 @@ def test_orchestrators_are_async_generator_functions() -> None:
 # ------------------------------------------------------------ initial thinking
 
 
-@dataclass
-class _FakeSurfsenseDoc:
-    """Stand-in for ``SurfsenseDocsDocument`` with just the field we read."""
-
-    title: str
-
-
 @pytest.mark.parametrize(
-    "user_query, image_urls, docs, expected_title, expected_action",
+    "user_query, image_urls, expected_title, expected_action",
     [
-        ("hello world", None, [], "Understanding your request", "Processing"),
+        ("hello world", None, "Understanding your request", "Processing"),
         (
             "",
             ["data:image/png;base64,AAA"],
-            [],
             "Understanding your request",
             "Processing",
         ),
-        ("", None, [], "Understanding your request", "Processing"),
+        ("", None, "Understanding your request", "Processing"),
-        (
-            "doc question",
-            None,
-            [_FakeSurfsenseDoc(title="My Doc")],
-            "Analyzing referenced content",
-            "Analyzing",
-        ),
     ],
 )
 def test_initial_thinking_step_branches(
     user_query: str,
     image_urls: list[str] | None,
-    docs: list[Any],
     expected_title: str,
     expected_action: str,
 ) -> None:
     step = build_initial_thinking_step(
         user_query=user_query,
         user_image_data_urls=image_urls,
-        mentioned_surfsense_docs=docs,  # type: ignore[arg-type]
     )
     assert step.step_id == "thinking-1"
     assert step.title == expected_title
@@ -191,7 +173,6 @@ def test_initial_thinking_step_truncates_long_query() -> None:
     step = build_initial_thinking_step(
         user_query=long_query,
         user_image_data_urls=None,
-        mentioned_surfsense_docs=[],
     )
     # 80-char truncation + ellipsis, sandwiched after "Processing: ".
     assert "..." in step.items[0]
@@ -200,16 +181,6 @@ def test_initial_thinking_step_truncates_long_query() -> None:
     assert payload.startswith("x" * 80) and payload.endswith("...")
 
 
-def test_initial_thinking_step_collapses_many_doc_names() -> None:
-    docs = [_FakeSurfsenseDoc(title=f"Doc {i}") for i in range(5)]
-    step = build_initial_thinking_step(
-        user_query="q",
-        user_image_data_urls=None,
-        mentioned_surfsense_docs=docs,  # type: ignore[arg-type]
-    )
-    assert "[5 docs]" in step.items[0]
-
-
 # ------------------------------------------------------------ capability gate
 
 

surfsense_web/app/dashboard/[search_space_id]/automations/components/builder/mention-task-input.tsx

@@ -89,10 +89,10 @@ function removeFirstToken(text: string, token: string): string {
 
 /**
  * Task input that reuses the chat ``@`` mention experience -- the same
- * ``InlineMentionEditor`` + ``DocumentMentionPicker`` as the composer, minus
+ * ``InlineMentionEditor`` + ``DocumentMentionPicker`` as the composer. The
- * SurfSense product docs. The editor is the source of truth while mounted;
+ * editor is the source of truth while mounted; ``onChange`` reports both the
- * ``onChange`` reports both the plain text (chips rendered as ``@Title``) and
+ * plain text (chips rendered as ``@Title``) and the structured mention list
- * the structured mention list so the builder can persist IDs for the run.
+ * so the builder can persist IDs for the run.
  */
 export function MentionTaskInput({
 	searchSpaceId,
@@ -233,7 +233,6 @@ export function MentionTaskInput({
 							<DocumentMentionPicker
 								ref={pickerRef}
 								searchSpaceId={searchSpaceId}
-								includeSurfsenseDocs={false}
 								onSelectionChange={handleSelection}
 								onDone={closePopover}
 								initialSelectedDocuments={mentions}

surfsense_web/app/dashboard/[search_space_id]/new-chat/[[...chat_id]]/page.tsx

@@ -740,15 +740,6 @@ export default function NewChatPage() {
 			queryFn: () => documentsApiService.searchDocumentTitles({ queryParams: prefetchParams }),
 			staleTime: 60 * 1000,
 		});
-
-		queryClient.prefetchQuery({
-			queryKey: ["surfsense-docs-mention", "", false],
-			queryFn: () =>
-				documentsApiService.getSurfsenseDocs({
-					queryParams: { page: 0, page_size: 20 },
-				}),
-			staleTime: 3 * 60 * 1000,
-		});
 	}, [searchSpaceId, queryClient]);
 
 	// Handle scroll to comment from URL query params (e.g., from inbox item click)
@@ -949,7 +940,6 @@ export default function NewChatPage() {
 			trackChatMessageSent(searchSpaceId, currentThreadId, {
 				hasAttachments: userImages.length > 0,
 				hasMentionedDocuments:
-					mentionedDocumentIds.surfsense_doc_ids.length > 0 ||
 					mentionedDocumentIds.document_ids.length > 0 ||
 					mentionedDocumentIds.folder_ids.length > 0 ||
 					mentionedDocumentIds.connector_ids.length > 0,
@@ -1027,12 +1017,11 @@ export default function NewChatPage() {
 
 				// Get mentioned document IDs for context (separate fields for backend)
 				const hasDocumentIds = mentionedDocumentIds.document_ids.length > 0;
-				const hasSurfsenseDocIds = mentionedDocumentIds.surfsense_doc_ids.length > 0;
 				const hasFolderIds = mentionedDocumentIds.folder_ids.length > 0;
 				const hasConnectorIds = mentionedDocumentIds.connector_ids.length > 0;
 
 				// Clear mentioned documents after capturing them
-				if (hasDocumentIds || hasSurfsenseDocIds || hasFolderIds || hasConnectorIds) {
+				if (hasDocumentIds || hasFolderIds || hasConnectorIds) {
 					setMentionedDocuments([]);
 				}
 
@@ -1054,9 +1043,6 @@ export default function NewChatPage() {
 							mentioned_document_ids: hasDocumentIds
 								? mentionedDocumentIds.document_ids
 								: undefined,
-							mentioned_surfsense_doc_ids: hasSurfsenseDocIds
-								? mentionedDocumentIds.surfsense_doc_ids
-								: undefined,
 							mentioned_folder_ids: hasFolderIds ? mentionedDocumentIds.folder_ids : undefined,
 							mentioned_connector_ids: hasConnectorIds
 								? mentionedDocumentIds.connector_ids
@@ -1947,18 +1933,14 @@ export default function NewChatPage() {
 				const selection = await getAgentFilesystemSelection(searchSpaceId, {
 					localFilesystemEnabled,
 				});
-				// Partition the source mentions back into doc/surfsense_doc/folder
+				// Partition the source mentions back into doc/folder id buckets
-				// id buckets so the regenerate route can pass them to
+				// so the regenerate route can pass them to ``stream_new_chat``
-				// ``stream_new_chat`` and the priority middleware sees the
+				// and the priority middleware sees the same ``[USER-MENTIONED]``
-				// same ``[USER-MENTIONED]`` priority entries the original
+				// priority entries the original turn did. Without this partition
-				// turn did. Without this partition the regenerate flow
+				// the regenerate flow silently dropped the agent's mention
-				// silently dropped the agent's mention awareness — same
+				// awareness — same architectural bug we fixed on the new-chat path.
-				// architectural bug we fixed on the new-chat path.
-				const regenerateSurfsenseDocIds = sourceMentionedDocs
-					.filter((d) => d.kind === "doc" && d.document_type === "SURFSENSE_DOCS")
-					.map((d) => d.id);
 				const regenerateDocIds = sourceMentionedDocs
-					.filter((d) => d.kind === "doc" && d.document_type !== "SURFSENSE_DOCS")
+					.filter((d) => d.kind === "doc")
 					.map((d) => d.id);
 				const regenerateFolderIds = sourceMentionedDocs
 					.filter((d) => d.kind === "folder")
@@ -1973,8 +1955,6 @@ export default function NewChatPage() {
 					client_platform: selection.client_platform,
 					local_filesystem_mounts: selection.local_filesystem_mounts,
 					mentioned_document_ids: regenerateDocIds.length > 0 ? regenerateDocIds : undefined,
-					mentioned_surfsense_doc_ids:
-						regenerateSurfsenseDocIds.length > 0 ? regenerateSurfsenseDocIds : undefined,
 					mentioned_folder_ids: regenerateFolderIds.length > 0 ? regenerateFolderIds : undefined,
 					mentioned_connector_ids:
 						regenerateConnectors.length > 0 ? regenerateConnectors.map((d) => d.id) : undefined,

surfsense_web/atoms/chat/mentioned-documents.atom.ts

@@ -102,10 +102,7 @@ export const mentionedDocumentIdsAtom = atom((get) => {
 	const folders = deduped.filter((m) => m.kind === "folder");
 	const connectors = deduped.filter((m) => m.kind === "connector");
 	return {
-		surfsense_doc_ids: docs
+		document_ids: docs.map((doc) => doc.id),
-			.filter((doc) => doc.document_type === "SURFSENSE_DOCS")
-			.map((doc) => doc.id),
-		document_ids: docs.filter((doc) => doc.document_type !== "SURFSENSE_DOCS").map((doc) => doc.id),
 		folder_ids: folders.map((f) => f.id),
 		connector_ids: connectors.map((c) => c.id),
 		connectors: connectors.map((c) => ({

surfsense_web/components/assistant-ui/inline-citation.tsx

@@ -1,16 +1,13 @@
 "use client";
 
-import { useQuery } from "@tanstack/react-query";
 import { useSetAtom } from "jotai";
-import { ExternalLink, FileText } from "lucide-react";
+import { FileText } from "lucide-react";
-import dynamic from "next/dynamic";
 import type { FC } from "react";
 import { useState } from "react";
 import { openCitationPanelAtom } from "@/atoms/citation/citation-panel.atom";
 import { useCitationMetadata } from "@/components/assistant-ui/citation-metadata-context";
 import { CitationPanelContent } from "@/components/citation-panel/citation-panel";
 import { Citation } from "@/components/tool-ui/citation";
-import { CitationHoverPopover } from "@/components/tool-ui/citation/citation-hover-popover";
 import { Button } from "@/components/ui/button";
 import {
 	Drawer,
@@ -19,21 +16,8 @@ import {
 	DrawerHeader,
 	DrawerTitle,
 } from "@/components/ui/drawer";
-import { Spinner } from "@/components/ui/spinner";
 import { Tooltip, TooltipContent, TooltipTrigger } from "@/components/ui/tooltip";
 import { useMediaQuery } from "@/hooks/use-media-query";
-import { documentsApiService } from "@/lib/apis/documents-api.service";
-import { cacheKeys } from "@/lib/query-client/cache-keys";
-
-// Lazily load MarkdownViewer here to break the static import cycle:
-// `markdown-viewer.tsx` → `citation-renderer.tsx` → `inline-citation.tsx`
-// would otherwise pull `markdown-viewer.tsx` back in at module-init time.
-// Only `SurfsenseDocCitation` (popover body) ever renders this viewer, so
-// the lazy boundary is invisible to most call paths.
-const MarkdownViewer = dynamic(
-	() => import("@/components/markdown-viewer").then((m) => m.MarkdownViewer),
-	{ ssr: false, loading: () => <Spinner size="xs" /> }
-);
 
 interface InlineCitationProps {
 	chunkId: number;
@@ -41,9 +25,7 @@ interface InlineCitationProps {
 }
 
 /**
- * Inline citation badge for knowledge-base chunks (numeric chunk IDs) and
+ * Inline citation badge for knowledge-base chunks (numeric chunk IDs).
- * Surfsense documentation chunks (`isDocsChunk`). Negative chunk IDs render as
- * a static "doc" pill (anonymous/synthetic uploads).
  *
  * Numeric KB chunks: clicking opens the citation panel in the right
  * sidebar (alongside the chat — does not replace it). The panel shows
@@ -51,12 +33,13 @@ interface InlineCitationProps {
  * `chunk_window`), with the cited one highlighted and an option to
  * expand the window or jump into the full document via the editor panel.
  *
- * Surfsense docs chunks: rendered as a hover-controlled shadcn Popover that
+ * Negative chunk IDs and legacy SurfSense-docs chunks (`isDocsChunk`) render
- * lazily fetches and previews the cited chunk inline, since those docs aren't
+ * as a static, non-interactive "doc" pill. The SurfSense product-docs feature
- * indexed into the user's search space and have no tab to open.
+ * was removed, so those markers are inert (no fetch, no preview) — they only
+ * survive in old persisted messages.
  */
 export const InlineCitation: FC<InlineCitationProps> = ({ chunkId, isDocsChunk = false }) => {
-	if (chunkId < 0) {
+	if (chunkId < 0 || isDocsChunk) {
 		return (
 			<Tooltip>
 				<TooltipTrigger asChild>
@@ -68,15 +51,11 @@ export const InlineCitation: FC<InlineCitationProps> = ({ chunkId, isDocsChunk =
 						doc
 					</span>
 				</TooltipTrigger>
-				<TooltipContent>Uploaded document</TooltipContent>
+				<TooltipContent>{isDocsChunk ? "Documentation reference" : "Uploaded document"}</TooltipContent>
 			</Tooltip>
 		);
 	}
 
-	if (isDocsChunk) {
-		return <SurfsenseDocCitation chunkId={chunkId} />;
-	}
-
 	return <NumericChunkCitation chunkId={chunkId} />;
 };
 
@@ -127,128 +106,6 @@ const NumericChunkCitation: FC<{ chunkId: number }> = ({ chunkId }) => {
 	);
 };
 
-const SurfsenseDocCitation: FC<{ chunkId: number }> = ({ chunkId }) => {
-	const isTouchLike = useMediaQuery("(hover: none), (pointer: coarse)");
-	const [mobilePreviewOpen, setMobilePreviewOpen] = useState(false);
-	const docQuery = useSurfsenseDocPreviewQuery(chunkId, mobilePreviewOpen);
-
-	const handleMobileClick = () => {
-		setMobilePreviewOpen(true);
-	};
-
-	return (
-		<>
-			<CitationHoverPopover
-				id={`doc-${chunkId}`}
-				contentClassName="w-96 max-w-[calc(100vw-2rem)] p-0"
-				align="start"
-				trigger={(hoverProps) => (
-					<Button
-						type="button"
-						variant="ghost"
-						size={null}
-						onClick={isTouchLike ? handleMobileClick : undefined}
-						className="ml-0.5 inline-flex h-5 min-w-5 items-center justify-center gap-0.5 rounded-md bg-popover px-1.5 text-[11px] font-medium text-popover-foreground/80 align-baseline"
-						aria-label={`Show Surfsense documentation chunk ${chunkId}`}
-						title="Surfsense documentation"
-						{...hoverProps}
-					>
-						<FileText className="size-3" />
-						doc
-					</Button>
-				)}
-			>
-				<SurfsenseDocPreview chunkId={chunkId} />
-			</CitationHoverPopover>
-			<Drawer
-				open={mobilePreviewOpen}
-				onOpenChange={setMobilePreviewOpen}
-				shouldScaleBackground={false}
-			>
-				<DrawerContent className="max-h-[85vh] z-80" overlayClassName="z-80">
-					<DrawerHandle />
-					<DrawerHeader className="pb-0">
-						<DrawerTitle>Surfsense documentation</DrawerTitle>
-					</DrawerHeader>
-					<SurfsenseDocPreviewContent
-						chunkId={chunkId}
-						query={docQuery}
-						contentClassName="max-h-[60vh]"
-					/>
-				</DrawerContent>
-			</Drawer>
-		</>
-	);
-};
-
-function useSurfsenseDocPreviewQuery(chunkId: number, enabled = true) {
-	return useQuery({
-		queryKey: cacheKeys.documents.byChunk(`doc-${chunkId}`),
-		queryFn: () => documentsApiService.getSurfsenseDocByChunk(chunkId),
-		staleTime: 5 * 60 * 1000,
-		enabled,
-	});
-}
-
-type SurfsenseDocPreviewQuery = ReturnType<typeof useSurfsenseDocPreviewQuery>;
-
-const SurfsenseDocPreview: FC<{ chunkId: number }> = ({ chunkId }) => {
-	const query = useSurfsenseDocPreviewQuery(chunkId);
-
-	return <SurfsenseDocPreviewContent chunkId={chunkId} query={query} />;
-};
-
-const SurfsenseDocPreviewContent: FC<{
-	chunkId: number;
-	query: SurfsenseDocPreviewQuery;
-	contentClassName?: string;
-}> = ({ chunkId, query, contentClassName = "max-h-72" }) => {
-	const { data, isLoading, error } = query;
-
-	const citedChunk = data?.chunks.find((c) => c.id === chunkId) ?? data?.chunks[0];
-
-	return (
-		<>
-			<div className="flex items-center justify-between gap-2 border-b px-3 py-2">
-				<div className="min-w-0">
-					<p className="truncate text-sm font-medium">{data?.title ?? "Surfsense documentation"}</p>
-					<p className="text-[11px] text-muted-foreground">Chunk #{chunkId}</p>
-				</div>
-				{data?.public_url && (
-					<a
-						href={data.public_url}
-						target="_blank"
-						rel="noopener noreferrer"
-						className="inline-flex shrink-0 items-center gap-1 rounded-md px-2 py-1 text-[11px] font-medium text-primary hover:bg-primary/10"
-					>
-						<ExternalLink className="size-3" />
-						Open
-					</a>
-				)}
-			</div>
-			<div className={`${contentClassName} overflow-auto px-3 py-2 text-sm`}>
-				{isLoading && (
-					<div className="flex items-center gap-2 py-4 text-muted-foreground">
-						<Spinner size="xs" />
-						<span className="text-xs">Loading…</span>
-					</div>
-				)}
-				{error && (
-					<p className="py-4 text-xs text-destructive">
-						{error instanceof Error ? error.message : "Failed to load chunk"}
-					</p>
-				)}
-				{!isLoading && !error && citedChunk?.content && (
-					<MarkdownViewer content={citedChunk.content} maxLength={1500} enableCitations />
-				)}
-				{!isLoading && !error && !citedChunk?.content && (
-					<p className="py-4 text-xs text-muted-foreground">No content available.</p>
-				)}
-			</div>
-		</>
-	);
-};
-
 import { tryGetHostname } from "@/lib/url";
 
 interface UrlCitationProps {

surfsense_web/components/assistant-ui/thread.tsx

@@ -1593,7 +1593,7 @@ interface ToolGroup {
 const TOOL_GROUPS: ToolGroup[] = [
 	{
 		label: "Research",
-		tools: ["search_surfsense_docs", "scrape_webpage"],
+		tools: ["scrape_webpage"],
 	},
 	{
 		label: "Generate",

surfsense_web/components/layout/ui/sidebar/DocumentsSidebar.tsx

@@ -90,7 +90,6 @@ const DesktopLocalTabContent = dynamic(
 );
 
 const NON_DELETABLE_DOCUMENT_TYPES: readonly string[] = [
-	"SURFSENSE_DOCS",
 	"USER_MEMORY",
 	"TEAM_MEMORY",
 ];

surfsense_web/components/new-chat/document-mention-picker.tsx

@@ -3,14 +3,7 @@
 import { useQuery as useZeroQuery } from "@rocicorp/zero/react";
 import { keepPreviousData, useQuery } from "@tanstack/react-query";
 import { useAtomValue } from "jotai";
-import {
+import { ChevronLeft, ChevronRight, Files, Folder as FolderIcon, Unplug } from "lucide-react";
-	BookOpen,
-	ChevronLeft,
-	ChevronRight,
-	Files,
-	Folder as FolderIcon,
-	Unplug,
-} from "lucide-react";
 import {
 	Fragment,
 	forwardRef,
@@ -57,13 +50,6 @@ interface DocumentMentionPickerProps {
 	onDone: () => void;
 	initialSelectedDocuments?: MentionedDocumentInfo[];
 	externalSearch?: string;
-	/**
-	 * Whether to surface the "SurfSense Docs" (product documentation) branch
-	 * and include those docs in search results. Defaults to ``true`` so the
-	 * chat composer is unchanged; callers like the automation task input pass
-	 * ``false`` to reference only the user's own knowledge base + connectors.
-	 */
-	includeSurfsenseDocs?: boolean;
 }
 
 const PAGE_SIZE = 20;
@@ -74,7 +60,6 @@ const RECENTS_STORAGE_PREFIX = "surfsense:composer-mention-recents:v1:";
 
 type BrowseView =
 	| { kind: "root" }
-	| { kind: "surfsense-docs" }
 	| { kind: "files-folders" }
 	| { kind: "connectors" }
 	| { kind: "connector-type"; connectorType: string; title: string };
@@ -241,7 +226,6 @@ export const DocumentMentionPicker = forwardRef<
 		onDone,
 		initialSelectedDocuments = [],
 		externalSearch = "",
-		includeSurfsenseDocs = true,
 	},
 	ref
 ) {
@@ -298,15 +282,6 @@ export const DocumentMentionPicker = forwardRef<
 		[searchSpaceId, debouncedSearch, isSearchValid]
 	);
 
-	const surfsenseDocsQueryParams = useMemo(() => {
-		const params: { page: number; page_size: number; title?: string } = {
-			page: 0,
-			page_size: PAGE_SIZE,
-		};
-		if (isSearchValid) params.title = debouncedSearch.trim();
-		return params;
-	}, [debouncedSearch, isSearchValid]);
-
 	const { data: titleSearchResults, isLoading: isTitleSearchLoading } = useQuery({
 		queryKey: ["document-titles", titleSearchParams],
 		queryFn: ({ signal }) =>
@@ -316,15 +291,6 @@ export const DocumentMentionPicker = forwardRef<
 		placeholderData: keepPreviousData,
 	});
 
-	const { data: surfsenseDocs, isLoading: isSurfsenseDocsLoading } = useQuery({
-		queryKey: ["surfsense-docs-mention", debouncedSearch, isSearchValid],
-		queryFn: ({ signal }) =>
-			documentsApiService.getSurfsenseDocs({ queryParams: surfsenseDocsQueryParams }, signal),
-		staleTime: 3 * 60 * 1000,
-		enabled: includeSurfsenseDocs && (!hasSearch || isSearchValid),
-		placeholderData: keepPreviousData,
-	});
-
 	const filterBySearchTerm = useCallback(
 		(docs: Pick<Document, "id" | "title" | "document_type">[]) => {
 			if (!isSearchValid) return docs;
@@ -338,23 +304,13 @@ export const DocumentMentionPicker = forwardRef<
 		if (currentPage !== 0) return;
 		const combinedDocs: Pick<Document, "id" | "title" | "document_type">[] = [];
 
-		if (includeSurfsenseDocs && surfsenseDocs?.items) {
-			for (const doc of surfsenseDocs.items) {
-				combinedDocs.push({
-					id: doc.id,
-					title: doc.title,
-					document_type: "SURFSENSE_DOCS",
-				});
-			}
-		}
-
 		if (titleSearchResults?.items) {
 			combinedDocs.push(...titleSearchResults.items);
 			setHasMore(titleSearchResults.has_more);
 		}
 
 		setAccumulatedDocuments(filterBySearchTerm(combinedDocs));
-	}, [titleSearchResults, surfsenseDocs, currentPage, filterBySearchTerm, includeSurfsenseDocs]);
+	}, [titleSearchResults, currentPage, filterBySearchTerm]);
 
 	const loadNextPage = useCallback(async () => {
 		if (isLoadingMore || !hasMore) return;
@@ -391,14 +347,6 @@ export const DocumentMentionPicker = forwardRef<
 		return accumulatedDocuments.filter((doc) => doc.title.toLowerCase().includes(searchLower));
 	}, [accumulatedDocuments, deferredSearch, isSingleCharSearch]);
 
-	const surfsenseDocsList = useMemo(
-		() => actualDocuments.filter((doc) => doc.document_type === "SURFSENSE_DOCS"),
-		[actualDocuments]
-	);
-	const userDocsList = useMemo(
-		() => actualDocuments.filter((doc) => doc.document_type !== "SURFSENSE_DOCS"),
-		[actualDocuments]
-	);
 	const folderMentions = useMemo(() => {
 		const all = (zeroFolders ?? []).map((f) => makeFolderMention({ id: f.id, title: f.name }));
 		if (!hasSearch) return all;
@@ -463,7 +411,6 @@ export const DocumentMentionPicker = forwardRef<
 		() => new Set(initialSelectedDocuments.map((d) => getMentionDocKey(d))),
 		[initialSelectedDocuments]
 	);
-	const showSurfsenseDocsRoot = includeSurfsenseDocs && surfsenseDocsList.length > 0;
 
 	const selectMention = useCallback(
 		(mention: MentionedDocumentInfo) => {
@@ -487,16 +434,6 @@ export const DocumentMentionPicker = forwardRef<
 
 	const rootNodes = useMemo<ComposerSuggestionNode<ResourceNodeValue>[]>(() => {
 		const nodes: ComposerSuggestionNode<ResourceNodeValue>[] = [...recentRootNodes];
-		if (showSurfsenseDocsRoot) {
-			nodes.push({
-				id: "surfsense-docs",
-				label: "SurfSense Docs",
-				subtitle: "Browse product documentation",
-				icon: <BookOpen className="size-4" />,
-				type: "branch",
-				value: { kind: "view", view: { kind: "surfsense-docs" } },
-			});
-		}
 		nodes.push(
 			{
 				id: "files-folders",
@@ -519,7 +456,7 @@ export const DocumentMentionPicker = forwardRef<
 			}
 		);
 		return nodes;
-	}, [activeConnectors.length, recentRootNodes, showSurfsenseDocsRoot]);
+	}, [activeConnectors.length, recentRootNodes]);
 
 	const searchNodes = useMemo<ComposerSuggestionNode<ResourceNodeValue>[]>(() => {
 		const searchLower = (isSingleCharSearch ? deferredSearch : debouncedSearch)
@@ -582,19 +519,6 @@ export const DocumentMentionPicker = forwardRef<
 
 	const browseNodes = useMemo<ComposerSuggestionNode<ResourceNodeValue>[]>(() => {
 		if (view.kind === "root") return rootNodes;
-		if (view.kind === "surfsense-docs") {
-			return surfsenseDocsList.map((doc) => {
-				const mention = makeDocMention(doc);
-				return {
-					id: getMentionDocKey(mention),
-					label: doc.title,
-					icon: getConnectorIcon(doc.document_type, "size-4"),
-					type: "item" as const,
-					disabled: selectedKeys.has(getMentionDocKey(mention)),
-					value: { kind: "mention" as const, mention },
-				};
-			});
-		}
 		if (view.kind === "files-folders") {
 			const folders = folderMentions.map((mention) => ({
 				id: getMentionDocKey(mention),
@@ -605,7 +529,7 @@ export const DocumentMentionPicker = forwardRef<
 				disabled: selectedKeys.has(getMentionDocKey(mention)),
 				value: { kind: "mention" as const, mention },
 			}));
-			const docs = userDocsList.map((doc) => {
+			const docs = actualDocuments.map((doc) => {
 				const mention = makeDocMention(doc);
 				return {
 					id: getMentionDocKey(mention),
@@ -652,13 +576,12 @@ export const DocumentMentionPicker = forwardRef<
 				};
 			});
 	}, [
+		actualDocuments,
 		activeConnectors,
 		connectorTypeEntries,
 		folderMentions,
 		rootNodes,
 		selectedKeys,
-		surfsenseDocsList,
-		userDocsList,
 		view,
 	]);
 
@@ -708,27 +631,23 @@ export const DocumentMentionPicker = forwardRef<
 
 	const isRootBrowseView = !hasSearch && view.kind === "root";
 	const isVisibleViewLoading = hasSearch
-		? isTitleSearchLoading || isSurfsenseDocsLoading || isConnectorsLoading
+		? isTitleSearchLoading || isConnectorsLoading
-		: view.kind === "surfsense-docs"
+		: view.kind === "files-folders"
-			? isSurfsenseDocsLoading
+			? isTitleSearchLoading
-			: view.kind === "files-folders"
+			: view.kind === "connectors" || view.kind === "connector-type"
-				? isTitleSearchLoading
+				? isConnectorsLoading
-				: view.kind === "connectors" || view.kind === "connector-type"
+				: false;
-					? isConnectorsLoading
-					: false;
 	const actualLoading =
 		isVisibleViewLoading && !isSingleCharSearch && visibleNodes.length === 0 && !isRootBrowseView;
 
 	const title =
 		hasSearch || view.kind === "root"
 			? null
-			: view.kind === "surfsense-docs"
+			: view.kind === "files-folders"
-				? "SurfSense Docs"
+				? "Files & Folders"
-				: view.kind === "files-folders"
+				: view.kind === "connectors"
-					? "Files & Folders"
+					? "Connectors"
-					: view.kind === "connectors"
+					: view.title;
-						? "Connectors"
-						: view.title;
 
 	return (
 		<ComposerSuggestionList

surfsense_web/contracts/enums/connectorIcons.tsx

@@ -1,6 +1,5 @@
 import { IconUsersGroup } from "@tabler/icons-react";
 import {
-	BookOpen,
 	Brain,
 	File,
 	FileText,
@@ -119,8 +118,6 @@ export const getConnectorIcon = (connectorType: EnumConnectorName | string, clas
 			return <FileText {...iconProps} />;
 		case "EXTENSION":
 			return <Webhook {...iconProps} />;
-		case "SURFSENSE_DOCS":
-			return <BookOpen {...iconProps} />;
 		case "USER_MEMORY":
 		case "TEAM_MEMORY":
 			return <Brain {...iconProps} />;

surfsense_web/contracts/enums/toolIcons.tsx

@@ -1,5 +1,4 @@
 import {
-	BookOpen,
 	Brain,
 	Calendar,
 	FileEdit,
@@ -47,7 +46,6 @@ const TOOL_ICONS: Record<string, LucideIcon> = {
 	// Web / search
 	scrape_webpage: ScanLine,
 	web_search: Globe,
-	search_surfsense_docs: BookOpen,
 	// Automations
 	create_automation: Workflow,
 	// Memory
@@ -152,7 +150,6 @@ const TOOL_DISPLAY_NAMES: Record<string, string> = {
 	// Web / search
 	scrape_webpage: "Read webpage",
 	web_search: "Search the web",
-	search_surfsense_docs: "Search knowledge base",
 	// Automations
 	create_automation: "Create automation",
 	// Memory

surfsense_web/contracts/types/document.types.ts

@@ -27,7 +27,6 @@ export const documentTypeEnum = z.enum([
 	"CIRCLEBACK",
 	"OBSIDIAN_CONNECTOR",
 	"LOCAL_FOLDER_FILE",
-	"SURFSENSE_DOCS",
 	"NOTE",
 	"USER_MEMORY",
 	"TEAM_MEMORY",
@@ -77,27 +76,6 @@ export const documentWithChunks = document.extend({
 	chunk_start_index: z.number().optional().default(0),
 });
 
-/**
- * Surfsense documentation schemas
- * Follows the same pattern as document/documentWithChunks
- */
-export const surfsenseDocsChunk = z.object({
-	id: z.number(),
-	content: z.string(),
-});
-
-export const surfsenseDocsDocument = z.object({
-	id: z.number(),
-	title: z.string(),
-	source: z.string(),
-	public_url: z.string(),
-	content: z.string(),
-});
-
-export const surfsenseDocsDocumentWithChunks = surfsenseDocsDocument.extend({
-	chunks: z.array(surfsenseDocsChunk),
-});
-
 /**
  * Get documents
  */
@@ -284,32 +262,6 @@ export const getDocumentChunksResponse = z.object({
 	has_more: z.boolean(),
 });
 
-/**
- * Get Surfsense docs by chunk
- */
-export const getSurfsenseDocsByChunkRequest = z.object({
-	chunk_id: z.number(),
-});
-
-export const getSurfsenseDocsByChunkResponse = surfsenseDocsDocumentWithChunks;
-
-/**
- * List Surfsense docs
- */
-export const getSurfsenseDocsRequest = z.object({
-	queryParams: paginationQueryParams.extend({
-		title: z.string().optional(),
-	}),
-});
-
-export const getSurfsenseDocsResponse = z.object({
-	items: z.array(surfsenseDocsDocument),
-	total: z.number(),
-	page: z.number(),
-	page_size: z.number(),
-	has_more: z.boolean(),
-});
-
 /**
  * Update document
  */
@@ -358,13 +310,6 @@ export type DeleteDocumentResponse = z.infer<typeof deleteDocumentResponse>;
 export type DocumentTypeEnum = z.infer<typeof documentTypeEnum>;
 export type DocumentSortBy = z.infer<typeof documentSortByEnum>;
 export type SortOrder = z.infer<typeof sortOrderEnum>;
-export type SurfsenseDocsChunk = z.infer<typeof surfsenseDocsChunk>;
-export type SurfsenseDocsDocument = z.infer<typeof surfsenseDocsDocument>;
-export type SurfsenseDocsDocumentWithChunks = z.infer<typeof surfsenseDocsDocumentWithChunks>;
-export type GetSurfsenseDocsByChunkRequest = z.infer<typeof getSurfsenseDocsByChunkRequest>;
-export type GetSurfsenseDocsByChunkResponse = z.infer<typeof getSurfsenseDocsByChunkResponse>;
-export type GetSurfsenseDocsRequest = z.infer<typeof getSurfsenseDocsRequest>;
-export type GetSurfsenseDocsResponse = z.infer<typeof getSurfsenseDocsResponse>;
 export type GetDocumentChunksRequest = z.infer<typeof getDocumentChunksRequest>;
 export type GetDocumentChunksResponse = z.infer<typeof getDocumentChunksResponse>;
 export type ChunkRead = z.infer<typeof chunkRead>;

surfsense_web/lib/apis/documents-api.service.ts

@@ -12,7 +12,6 @@ import {
 	type GetDocumentsRequest,
 	type GetDocumentsStatusRequest,
 	type GetDocumentTypeCountsRequest,
-	type GetSurfsenseDocsRequest,
 	getDocumentByChunkRequest,
 	getDocumentByChunkResponse,
 	getDocumentChunksRequest,
@@ -25,9 +24,6 @@ import {
 	getDocumentsStatusResponse,
 	getDocumentTypeCountsRequest,
 	getDocumentTypeCountsResponse,
-	getSurfsenseDocsByChunkResponse,
-	getSurfsenseDocsRequest,
-	getSurfsenseDocsResponse,
 	type SearchDocumentsRequest,
 	type SearchDocumentTitlesRequest,
 	searchDocumentsRequest,
@@ -363,48 +359,6 @@ class DocumentsApiService {
 		);
 	};
 
-	/**
-	 * Get Surfsense documentation by chunk ID
-	 * Used for resolving [citation:doc-XXX] citations
-	 */
-	getSurfsenseDocByChunk = async (chunkId: number) => {
-		return baseApiService.get(
-			`/api/v1/surfsense-docs/by-chunk/${chunkId}`,
-			getSurfsenseDocsByChunkResponse
-		);
-	};
-
-	/**
-	 * List all Surfsense documentation documents
-	 * @param request - The request with query params
-	 * @param signal - Optional AbortSignal for request cancellation
-	 */
-	getSurfsenseDocs = async (request: GetSurfsenseDocsRequest, signal?: AbortSignal) => {
-		const parsedRequest = getSurfsenseDocsRequest.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: ${errorMessage}`);
-		}
-
-		// Transform query params to be string values
-		const transformedQueryParams = parsedRequest.data.queryParams
-			? Object.fromEntries(
-					Object.entries(parsedRequest.data.queryParams).map(([k, v]) => [k, String(v)])
-				)
-			: undefined;
-
-		const queryParams = transformedQueryParams
-			? new URLSearchParams(transformedQueryParams).toString()
-			: "";
-
-		const url = `/api/v1/surfsense-docs?${queryParams}`;
-
-		return baseApiService.get(url, getSurfsenseDocsResponse, { signal });
-	};
-
 	/**
 	 * Update a document
 	 */

surfsense_web/lib/chat/thread-persistence.ts

@@ -221,7 +221,6 @@ export interface RegenerateParams {
 		content: string;
 	}>;
 	mentionedDocumentIds?: number[];
-	mentionedSurfsenseDocIds?: number[];
 }
 
 /**

surfsense_web/lib/documents/document-type-labels.ts

@@ -25,7 +25,6 @@ export function getDocumentTypeLabel(type: string): string {
 		CIRCLEBACK: "Circleback",
 		OBSIDIAN_CONNECTOR: "Obsidian",
 		LOCAL_FOLDER_FILE: "Local Folder",
-		SURFSENSE_DOCS: "SurfSense Docs",
 		NOTE: "Note",
 		COMPOSIO_GOOGLE_DRIVE_CONNECTOR: "Composio Google Drive",
 		COMPOSIO_GMAIL_CONNECTOR: "Composio Gmail",

surfsense_web/lib/query-client/cache-keys.ts

@@ -30,7 +30,6 @@ export const cacheKeys = {
 		withQueryParams: (queries: GetDocumentsRequest["queryParams"]) =>
 			["documents-with-queries", ...stableEntries(queries)] as const,
 		document: (documentId: string) => ["document", documentId] as const,
-		byChunk: (chunkId: string) => ["documents", "by-chunk", chunkId] as const,
 	},
 	logs: {
 		list: (searchSpaceId?: number | string) => ["logs", "list", searchSpaceId] as const,