Relocate three leaf filesystem-cluster modules to the shared kernel and flip
all 38 importers. No re-export shims needed (no frozen single-agent importer).
This also resolves the pre-existing shared->new_chat back-edge from
shared/receipt_command.py onto filesystem_state.
filesystem_backends is intentionally deferred to slice 5: it depends on
new_chat middleware (kb_postgres_backend, multi_root_local_folder_backend)
that have not yet moved, so relocating it now would create a shared->new_chat edge.
Promote the filesystem mode contracts (FilesystemMode, FilesystemSelection,
ClientPlatform, LocalFilesystemMount) out of `new_chat` into the cross-agent
`app/agents/shared` kernel.
Pure leaf consumed across the whole multi-agent filesystem middleware/tool tree,
the chat flows/monolith, routes and tests. git mv (content unchanged) + flipped
all ~48 importers. A re-export shim remains at new_chat/filesystem_selection.py
only for the not-yet-retired single-agent (chat_deepagent).
Also updated the stream parity test's annotation normalizer to strip the new
app.agents.shared.filesystem_selection. prefix (the dataclasses' __module__
changed with the move), keeping monolith<->flows signature parity intact.
Behavior-preserving: only import paths change. 1326 tests green.
Promote the agent feature-flag resolver (AgentFeatureFlags / get_flags) out of
`new_chat` into the cross-agent `app/agents/shared` kernel.
feature_flags is a pure leaf consumed across the multi-agent middleware stack,
the chat routes, and tests. Moved it via git mv (content unchanged) and flipped
all 37 importers to app.agents.shared.feature_flags. A thin re-export shim
remains at new_chat/feature_flags.py only for the not-yet-retired single-agent
(chat_deepagent); it goes away with the single-agent deletion.
Behavior-preserving: only import paths change. 1243 tests green.
Continue promoting the shared agent toolkit out of `new_chat` into the
cross-agent `app/agents/shared` kernel.
- state_reducers.py: clean move (no single-agent importer); all 7 importers
flipped to app.agents.shared.state_reducers.
- context.py: moved to app.agents.shared.context; flipped the multi-agent,
app, automations, chat-flows and monolith importers. A thin re-export shim
remains at new_chat/context.py because the not-yet-retired single-agent
(chat_deepagent) and the new_chat package __init__ still import it; the shim
goes away with the single-agent deletion.
- Updated the stream parity test's annotation normalizer to strip the new
app.agents.shared.context. prefix (SurfSenseContextSchema.__module__ changed
with the move), keeping monolith<->flows signature parity intact.
Behavior-preserving: definitions unchanged; only import paths move. 1219 tests green.
First slice of promoting the shared agent toolkit out of the misnamed
`new_chat` package into the cross-agent `app/agents/shared` kernel.
`errors.py` is a leaf module (no intra-package deps) consumed by the
multi-agent chat, the chat streaming flows/monolith, and tests — i.e. it is
shared infrastructure, not single-agent code. Moved it verbatim to
`app.agents.shared.errors` and flipped all 12 importers. No re-export shim
remains since zero importers needed it.
Behavior-preserving: identical class/enum definitions; only the import path
changes. 1208 agent + chat-task tests green.
The multi-agent factory reached into the single-agent factory module
(chat_deepagent) for `_map_connectors_to_searchable_types`. Move this
agent-agnostic helper (and its two lookup tables) into a dedicated
`connector_searchable_types` module and point both factories at it.
Behavior-preserving: the function body is unchanged; only its home and
visibility (now public `map_connectors_to_searchable_types`) change. This
removes the cross-dependency on the dying single-agent module so it can be
retired later without breaking the multi-agent path.
- Enhanced lambda function formatting in `_after_commit` for better clarity.
- Simplified generator expression in `_match_condition` for improved readability.
- Streamlined function signature in `_eligible` for consistency.
- Updated imports and refactored anonymous chat routes to use a new agent creation method.
- Added a new function `_load_anon_document` to handle document loading from Redis.
- Improved UI components by replacing legacy structures with modern alternatives, including alerts and separators.
- Refactored quota-related components to utilize new alert structures for better user feedback.
- Cleaned up unused variables and optimized component states for performance.
- 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.
Single tool exposed to the main agent. The main agent passes a natural-language
`intent`; a focused drafter sub-LLM turns it into a full AutomationCreate JSON;
that JSON is surfaced via request_approval (action_type "automation_create") so
the user can edit/approve it on a frontend card; on approval the tool persists
via AutomationService. Three phases, one tool call.
Scope split:
- main agent sees only `intent: str` (no schema knowledge leaks into the calling
graph) — prompt fragments scoped accordingly.
- drafter sub-LLM owns the schema + few-shot intent→JSON examples — lives in
the generating graph's prompt (tools/automation/prompt.py).
Files:
- main_agent/tools/automation/{create.py, prompt.py, __init__.py}: new tool
+ drafter system prompt with two few-shot intent→JSON examples.
- system_prompt/prompts/tools/create_automation/{description.md, example.md}:
intent-only guidance for the main agent.
- main_agent/tools/index.py: add create_automation to the main-agent allowlist.
- new_chat/tools/registry.py: deferred-import factory to break the
multi_agent_chat ↔ registry cycle; one ToolDefinition entry.
- Added new environment variables for controlling task execution limits, including `SURFSENSE_SUBAGENT_INVOKE_TIMEOUT_SECONDS`, `SURFSENSE_TASK_BATCH_CONCURRENCY`, and `SURFSENSE_TASK_BATCH_MAX_SIZE`.
- Updated documentation to reflect new batch processing capabilities for `task` calls, allowing for concurrent execution of multiple subagent tasks.
- Improved error handling and receipt generation for deliverables, ensuring consistent feedback on task status.
- Refactored middleware to incorporate search space ID for better task management.
Resolves: surfsense_backend/app/agents/new_chat/middleware/memory_injection.py
- Took both imports: upstream moved MEMORY_HARD_LIMIT/SOFT_LIMIT to
app.services.memory; kept our perf-logger import for timing.
Pulls in upstream changes:
- Memory document feature (services/memory refactor, removal of
app.agents.new_chat.memory_extraction and background extraction in
stream_new_chat — agent now drives memory via update_memory tool).
- BACKEND_URL env refactor across web tool-ui/editor/chat/dashboard/lib.
- GitHub Actions backend test workflow + pre-commit biome bump.
- Token-display polish in MessageInfoDropdown; save_memory no-update
sentinel.
Verified: 1723 unit tests pass, ruff clean. No semantic regression in
stream_new_chat (their memory-extraction deletion and our preflight
removal touch different functions).
Collapse the invalidate + warmup pair into a single
refresh_mcp_tools_cache_for_connector(connector_id, search_space_id)
helper and scope live discovery to the one connector that changed
instead of the whole search space.
- new mcp_tool.discover_single_mcp_connector: load one connector,
refresh OAuth if needed, force live MCP discovery so its cached_tools
row is rewritten; returned wrappers are discarded since the in-process
LRU is rebuilt lazily on the next user query
- mcp_tools_cache.refresh_mcp_tools_cache_for_connector: synchronously
evicts the per-space LRU (LRU keys cannot scope finer) and schedules
the per-connector prefetch via loop.create_task
- routes (OAuth callback, MCP POST, MCP PUT) collapse their two
back-to-back calls into a single refresh call; DELETE handlers keep
using bare invalidate_mcp_tools_cache (nothing to prefetch)
No new automated tests: the new functions are I/O glue (DB + network)
where mocked unit tests would test implementation rather than behavior.
The existing 9 unit tests for the cached_tools data shape are unchanged.
Skip the ~1-3s MCP initialize + list_tools handshake on every cache miss
by reading tool definitions from the connector row we already load. Lazy
populate on first miss, self-heal on corrupt cache, zero schema migration.
Splits the OpenAI-family gate into per-param predicates so AZURE and
AZURE_OPENAI configs now receive prompt_cache_key for backend routing
affinity (Microsoft auto-caches GPT-4o+ deployments at >=1024 tokens;
the key clusters same-prefix requests on the same GPU pool and raises
hit rate on turn 2+). prompt_cache_retention stays opted out for Azure
because litellm 1.83.14's Azure transformer would drop it silently;
revisit when Azure's supported params list is updated.
Adds an optional planner LLM role wired through KnowledgePriorityMiddleware
so KB query rewriting, date extraction, and recency classification run on a
cheap model (e.g. gpt-4o-mini, Haiku, Azure nano) instead of the user's
chat LLM. Operators opt in by setting is_planner: true on exactly one
global config; without it, behavior is unchanged.
_create_document and _update_document run on the chat critical path
when the filesystem subagent writes via the user's chat turn. Both
called embed_texts synchronously inside an async coroutine, blocking
the event loop for the duration of the embed.
embed_texts holds a threading.Lock and runs a sync embedding call inside
search_knowledge_base, an async coroutine on the KB priority middleware
critical path. Blocking the event loop here stalls every other coroutine
on the worker (SSE keepalives, concurrent chat requests, background
tasks). Wrap in asyncio.to_thread so the embed runs on the default
executor pool while the loop keeps serving.
Renames the SurfSense HITL extension decision-type from "always" to
"approve_always" so it sits in the same verb-first family as "approve",
"reject", and "edit". The Python constant is now SURFSENSE_DECISION_APPROVE_ALWAYS;
the wire value, the permission-domain decision_type, and the FE union members
all match (no wire/internal mismatch).
Both the multi_agent_chat permission middleware and the legacy new_chat one
accept the new wire value; the FE types.ts union is updated accordingly.
The "context.always" payload key is intentionally left untouched - it's the
patterns-to-promote field, semantically distinct from the decision type.
The FE permission card needs mcp_connector_id, mcp_server, and
tool_description in the interrupt context to render "Always Allow"
against the right connected account. Thread the tool through the
ask pipeline:
- pack_subagent → build_permission_mw(tools=...) → PermissionMiddleware
(tools_by_name) → request_permission_decision(tool=...) →
build_permission_ask_payload(tool=...) projects card fields out of
BaseTool.
- mcp_tool.py: stdio path now stashes mcp_connector_id in metadata for
parity with the HTTP path.
- Updated the `_forced_rewrite` function to strip whitespace from the extracted text and added a warning log if the response is empty, preventing potential issues with empty rewrites.
