Tool retrieval 2

CHANGELOG.md

@@ -11,6 +11,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Python interpreter tool.
 - Auto alembic upgrade.
 - New utterances in false positive semantic route.
+- Tool pre-selection.
 - Ephys tool.
 
 ## Changed

backend/.env.example

@@ -22,6 +22,7 @@ NEUROAGENT_TOOLS__ENTITYCORE__URL=
 NEUROAGENT_TOOLS__BLUENAAS_URL=
 NEUROAGENT_TOOLS__THUMBNAIL_GENERATION__URL=
 NEUROAGENT_TOOLS__WHITELISTED_TOOL_REGEX=
+NEUROAGENT_TOOLS__MIN_TOOL_SELECTION=
 
 
 NEUROAGENT_LLM__SUGGESTION_MODEL=

backend/alembic/versions/825dd56cabf4_add_tool_selection_table.py

@@ -0,0 +1,41 @@
+"""Add tool_selection table
+
+Revision ID: 825dd56cabf4
+Revises: 529e44b33a67
+Create Date: 2025-07-09 16:05:31.480188
+
+"""
+
+from typing import Sequence, Union
+
+import sqlalchemy as sa
+
+from alembic import op
+
+# revision identifiers, used by Alembic.
+revision: str = "825dd56cabf4"
+down_revision: Union[str, None] = "529e44b33a67"
+branch_labels: Union[str, Sequence[str], None] = None
+depends_on: Union[str, Sequence[str], None] = None
+
+
+def upgrade() -> None:
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.create_table(
+        "tool_selection",
+        sa.Column("id", sa.String(), nullable=False),
+        sa.Column("selected_tools", sa.String(), nullable=False),
+        sa.Column("message_id", sa.UUID(), nullable=False),
+        sa.ForeignKeyConstraint(
+            ["message_id"],
+            ["messages.message_id"],
+        ),
+        sa.PrimaryKeyConstraint("id"),
+    )
+    # ### end Alembic commands ###
+
+
+def downgrade() -> None:
+    # ### commands auto generated by Alembic - please adjust! ###
+    op.drop_table("tool_selection")
+    # ### end Alembic commands ###

backend/pyproject.toml

@@ -69,7 +69,7 @@ preview = true
 
 [tool.ruff]
 line-length = 88
-target-version = "py310"
+target-version = "py311"
 exclude = ["src/neuroagent/tools/autogenerated_types"]
 
 [tool.ruff.lint]

backend/src/neuroagent/app/app_utils.py

@@ -5,10 +5,11 @@
 import re
 import uuid
 from pathlib import Path
-from typing import Any, Sequence
+from typing import Any, Literal, Sequence
 
 import yaml
 from fastapi import HTTPException
+from openai import AsyncOpenAI
 from pydantic import BaseModel, ConfigDict, Field
 from redis import asyncio as aioredis
 from semantic_router import Route
@@ -34,6 +35,7 @@
     ToolCallVercel,
 )
 from neuroagent.schemas import EmbeddedBrainRegions
+from neuroagent.tools.base_tool import BaseTool
 
 logger = logging.getLogger(__name__)
 
@@ -469,3 +471,87 @@ def parse_redis_data(
         remaining=remaining,
         reset_in=reset_in,
     )
+
+
+async def filter_tools_by_conversation(
+    openai_messages: list[dict[str, str]],
+    tool_list: list[type[BaseTool]],
+    user_content: str,
+    openai_client: AsyncOpenAI,
+    min_tool_selection: int,
+) -> list[type[BaseTool]]:
+    """
+    Filter tools based on conversation relevance.
+
+    Args:
+        openai_messages: List of OpenAI formatted messages
+        tool_list: List of available tools
+        user_content: Current user message content
+        openai_client: OpenAI client instance
+        settings: Application settings
+
+    Returns
+    -------
+        List of filtered tools relevant to the conversation
+    """
+    if not tool_list:
+        return []
+
+    if len(tool_list) < min_tool_selection:
+        return tool_list
+
+    # Remove the content of tool responses to save tokens
+    for message in openai_messages:
+        if message["role"] == "tool":
+            message["content"] = "..."
+
+    # Add the current user message
+    openai_messages.append({"role": "user", "content": user_content})
+
+    system_prompt = f"""TASK: Filter tools for AI agent based on conversation relevance.
+
+INSTRUCTIONS:
+1. Analyze the conversation to identify required capabilities
+2. Select at least {min_tool_selection} of the most relevant tools by name only
+3. BIAS TOWARD INCLUSION: If uncertain about a tool's relevance, include it - better to provide too many tools than too few
+4. Only exclude tools that are clearly irrelevant to the conversation
+5. Output format: comma-separated list of tool names
+6. Do not respond to user queries - only filter tools
+7. Each tool must be selected only once.
+
+OUTPUT: [tool_name1, tool_name2, ...]
+
+AVAILABLE TOOLS:
+{chr(10).join(f"{tool.name}: {tool.description}" for tool in tool_list)}
+"""
+
+    tool_names = [tool.name for tool in tool_list]
+    TOOL_NAMES_LITERAL = Literal[*tool_names]  # type: ignore
+
+    class ToolSelection(BaseModel):
+        """Data class for tool selection by an LLM."""
+
+        selected_tools: list[TOOL_NAMES_LITERAL] = Field(
+            min_length=min_tool_selection,
+            description=f"List of selected tool names, minimum {min_tool_selection} items. Must contain all of the tools relevant to the conversation.",
+        )
+
+    try:
+        response = await openai_client.beta.chat.completions.parse(
+            messages=[{"role": "system", "content": system_prompt}, *openai_messages],  # type: ignore
+            model="gpt-4o-mini",
+            response_format=ToolSelection,
+        )
+
+        if response.choices[0].message.parsed:
+            selected_tools = response.choices[0].message.parsed.selected_tools
+            logger.info(
+                f"QUERY: {user_content}, #TOOLS: {len(selected_tools)}, SELECTED TOOLS: {selected_tools}"
+            )
+            return [tool for tool in tool_list if tool.name in selected_tools]
+        else:
+            logger.warning("No parsed response from OpenAI, returning empty list")
+            return []
+    except Exception as e:
+        logger.error(f"Error filtering tools: {e}")
+        return []

backend/src/neuroagent/app/config.py

@@ -117,6 +117,7 @@ class SettingsTools(BaseModel):
     entitycore: SettingsEntityCore = SettingsEntityCore()
     web_search: SettingsWebSearch = SettingsWebSearch()
     thumbnail_generation: SettingsThumbnailGeneration = SettingsThumbnailGeneration()
+    min_tool_selection: int = 10
     whitelisted_tool_regex: str | None = None
 
     model_config = ConfigDict(frozen=True)

backend/src/neuroagent/app/database/sql_schemas.py

@@ -73,6 +73,7 @@ class Messages(Base):
     tool_calls: Mapped[list["ToolCalls"]] = relationship(
         "ToolCalls", back_populates="message", cascade="all, delete-orphan"
     )
+    selected_tools: Mapped[list["ToolCalls"]] = relationship("ToolSelection")
 
 
 class ToolCalls(Base):
@@ -88,3 +89,16 @@ class ToolCalls(Base):
         UUID, ForeignKey("messages.message_id")
     )
     message: Mapped[Messages] = relationship("Messages", back_populates="tool_calls")
+
+
+class ToolSelection(Base):
+    """SQL table used for storing the tool selected for a query."""
+
+    __tablename__ = "tool_selection"
+    id: Mapped[uuid.UUID] = mapped_column(
+        UUID, primary_key=True, default=lambda: uuid.uuid4()
+    )
+    selected_tools: Mapped[str] = mapped_column(String, nullable=False)
+    message_id: Mapped[uuid.UUID] = mapped_column(
+        UUID, ForeignKey("messages.message_id")
+    )

backend/src/neuroagent/app/dependencies.py

@@ -20,7 +20,7 @@
 from starlette.status import HTTP_401_UNAUTHORIZED
 
 from neuroagent.agent_routine import AgentsRoutine
-from neuroagent.app.app_utils import validate_project
+from neuroagent.app.app_utils import filter_tools_by_conversation, validate_project
 from neuroagent.app.config import Settings
 from neuroagent.app.database.sql_schemas import Threads
 from neuroagent.app.schemas import OpenRouterModelResponse, UserInfo
@@ -102,6 +102,7 @@
     WebSearchTool,
 )
 from neuroagent.tools.base_tool import BaseTool
+from neuroagent.utils import messages_to_openai_content
 
 logger = logging.getLogger(__name__)
 
@@ -244,6 +245,33 @@ async def get_user_info(
         raise HTTPException(status_code=404, detail="User info url not provided.")
 
 
+async def get_thread(
+    user_info: Annotated[UserInfo, Depends(get_user_info)],
+    thread_id: str,
+    session: Annotated[AsyncSession, Depends(get_session)],
+) -> Threads:
+    """Check if the current thread / user matches."""
+    thread_result = await session.execute(
+        select(Threads).where(
+            Threads.user_id == user_info.sub, Threads.thread_id == thread_id
+        )
+    )
+    thread = thread_result.scalars().one_or_none()
+    if not thread:
+        raise HTTPException(
+            status_code=404,
+            detail={
+                "detail": "Thread not found.",
+            },
+        )
+    validate_project(
+        groups=user_info.groups,
+        virtual_lab_id=thread.vlab_id,
+        project_id=thread.project_id,
+    )
+    return thread
+
+
 def get_mcp_client(request: Request) -> MCPClient | None:
     """Get the MCP client from the app state."""
     if request.app.state.mcp_client is None:
@@ -415,6 +443,36 @@ async def get_selected_tools(
         return selected_tools
 
 
+async def filtered_tools(
+    request: Request,
+    thread: Annotated[Threads, Depends(get_thread)],
+    tool_list: Annotated[list[type[BaseTool]], Depends(get_selected_tools)],
+    openai_client: Annotated[AsyncOpenAI, Depends(get_openai_client)],
+    settings: Annotated[Settings, Depends(get_settings)],
+) -> list[type[BaseTool]]:
+    """Based on the current conversation, select relevant tools."""
+    if request.method == "GET":
+        return tool_list
+
+    # Awaiting here makes downstream calls already loaded so no performance issue
+    messages = await thread.awaitable_attrs.messages
+    if not tool_list:
+        return []
+
+    openai_messages = await messages_to_openai_content(messages)
+
+    body = await request.json()
+    user_content = body["content"]
+
+    return await filter_tools_by_conversation(
+        openai_messages=openai_messages,
+        tool_list=tool_list,
+        user_content=user_content,
+        openai_client=openai_client,
+        min_tool_selection=settings.tools.min_tool_selection,
+    )
+
+
 @cache
 def get_rules_dir() -> Path:
     """Get the path to the rules directory."""
@@ -476,7 +534,7 @@ def get_system_prompt(rules_dir: Annotated[Path, Depends(get_rules_dir)]) -> str
 
 
 def get_starting_agent(
-    tool_list: Annotated[list[type[BaseTool]], Depends(get_selected_tools)],
+    tool_list: Annotated[list[type[BaseTool]], Depends(filtered_tools)],
     system_prompt: Annotated[str, Depends(get_system_prompt)],
 ) -> Agent:
     """Get the starting agent."""
@@ -488,33 +546,6 @@ def get_starting_agent(
     return agent
 
 
-async def get_thread(
-    user_info: Annotated[UserInfo, Depends(get_user_info)],
-    thread_id: str,
-    session: Annotated[AsyncSession, Depends(get_session)],
-) -> Threads:
-    """Check if the current thread / user matches."""
-    thread_result = await session.execute(
-        select(Threads).where(
-            Threads.user_id == user_info.sub, Threads.thread_id == thread_id
-        )
-    )
-    thread = thread_result.scalars().one_or_none()
-    if not thread:
-        raise HTTPException(
-            status_code=404,
-            detail={
-                "detail": "Thread not found.",
-            },
-        )
-    validate_project(
-        groups=user_info.groups,
-        virtual_lab_id=thread.vlab_id,
-        project_id=thread.project_id,
-    )
-    return thread
-
-
 def get_semantic_routes(request: Request) -> SemanticRouter | None:
     """Get the semantic route object for basic guardrails."""
     return request.app.state.semantic_router

backend/src/neuroagent/app/routers/qa.py

@@ -32,11 +32,7 @@
     validate_project,
 )
 from neuroagent.app.config import Settings
-from neuroagent.app.database.sql_schemas import (
-    Entity,
-    Messages,
-    Threads,
-)
+from neuroagent.app.database.sql_schemas import Entity, Messages, Threads, ToolSelection
 from neuroagent.app.dependencies import (
     get_accounting_session_factory,
     get_agents_routine,
@@ -304,15 +300,8 @@ async def stream_chat_agent(
         agent.model = agent.model.removeprefix("openai/")
         agents_routine.client = openai_client
 
-    messages: list[Messages] = await thread.awaitable_attrs.messages
-    # Since the session is not reinstantiated in stream.py
-    # we need to lazy load the tool_calls in advance since in
-    # any case they will be needed to convert the db schema
-    # to OpenAI messages
-    for msg in messages:
-        if msg.entity == Entity.AI_TOOL:
-            # This awaits the lazy loading, ensuring tool_calls is populated now.
-            await msg.awaitable_attrs.tool_calls
+    # No need to await since it has been awaited in tool filtering dependency
+    messages: list[Messages] = thread.messages
 
     if (
         not messages
@@ -326,6 +315,9 @@ async def stream_chat_agent(
                 content=json.dumps({"role": "user", "content": user_request.content}),
                 is_complete=True,
                 model=None,
+                selected_tools=[
+                    ToolSelection(selected_tools=tool.name) for tool in agent.tools
+                ],
             )
         )
 

backend/src/neuroagent/rules/ai-message-formatting.mdc

@@ -3,12 +3,11 @@ description: AI-message formatting guidelines
 ---
 # Message formatting guidelines
 
-## Structure and Organization
-- Use hierarchical headers (##, ###) to organize information by categories and subcategories
-# AI Message Formatting Guidelines
+- Always use rich markdown formatting.
 
 ## Content Structure Guidelines
 
+- Use hierarchical headers (##, ###) to organize information by categories and subcategories
 - Create detailed subsections for each specific area or entity
 - Group related items under appropriate subheaders
 - Use descriptive section titles that specify the exact areas or categories