feat: Intelligence Layer Phase 1 — orchestrator service
Adds the Gemini API orchestrator (ReAct tool loop → Claude responder):
Orchestrator engine + router:
- orchestrator_engine.py: Gemini API tool loop, Claude CLI handoff
- routers/orchestrator.py: POST /orchestrate (async job queue), GET /orchestrate/{job_id}
Tools (cortex/tools/):
- web.py: DuckDuckGo web search (no key required)
- ae_knowledge.py: ae_journal_search + ae_journal_entry_create (AE V3 API)
- ae_tasks.py: ae_task_list (reads agents_sync Kanban filesystem)
- files.py: file_read (path-allowlisted to safe dirs)
Config + deps:
- config.py: orchestrator, DuckDuckGo, and AE API settings
- requirements.txt: google-genai, duckduckgo-search
- .env.default: reference config with all new keys documented
Docs:
- CLAUDE.md, README.md, documentation/ added to repo
- Port references updated 7331 → 8000 throughout
- Default model updated to gemini-2.5-flash
Tested: ae_task_list, ae_journal_search, web_search all working end-to-end.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Scott Idem
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cortex/tools/__init__.py
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cortex/tools/__init__.py
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"""
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Orchestrator tool registry.
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Each tool has two parts:
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1. A Gemini FunctionDeclaration — tells the model what the tool does and what args it takes
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2. A Python async callable — the actual implementation
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To add a new tool:
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1. Implement it in a tools/<domain>.py module
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2. Import it here and add (declaration, callable) to _REGISTRY
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3. Add a FunctionDeclaration below and include it in TOOL_DECLARATIONS
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IMPORTANT: These tools are separate from the ae_* MCP tools used by the fleet agents.
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Do not modify the ae_* MCP server to support orchestrator needs.
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"""
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from google.genai import types
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from tools.web import search as _web_search
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from tools.ae_knowledge import journal_search as _ae_journal_search
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from tools.ae_knowledge import journal_entry_create as _ae_journal_entry_create
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from tools.ae_tasks import task_list as _ae_task_list
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from tools.files import file_read as _file_read
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# ---------------------------------------------------------------------------
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# Gemini function declarations
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# ---------------------------------------------------------------------------
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_web_search_declaration = types.FunctionDeclaration(
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name="web_search",
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description=(
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"Search the web for current information. Use this when you need up-to-date "
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"facts, news, documentation, or anything not in your training data."
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),
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"query": types.Schema(
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type=types.Type.STRING,
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description="The search query string",
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),
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"max_results": types.Schema(
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type=types.Type.INTEGER,
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description="Number of results to return (default 5, max 10)",
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),
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},
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required=["query"],
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),
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)
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_ae_journal_search_declaration = types.FunctionDeclaration(
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name="ae_journal_search",
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description=(
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"Search the Aether Journals knowledge base by keyword. "
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"Use this to look up notes, documentation, meeting summaries, or any saved knowledge. "
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"Always search before creating a new entry to avoid duplicates."
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),
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"query": types.Schema(
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type=types.Type.STRING,
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description="Keyword or phrase to search for",
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),
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"journal_id": types.Schema(
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type=types.Type.STRING,
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description=(
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"Optional: scope search to a specific journal by its id_random. "
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"Omit to search all journals."
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),
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),
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"max_results": types.Schema(
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type=types.Type.INTEGER,
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description="Maximum number of entries to return (default 10)",
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),
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},
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required=["query"],
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),
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)
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_ae_journal_entry_create_declaration = types.FunctionDeclaration(
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name="ae_journal_entry_create",
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description=(
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"Create a new entry in an Aether Journal. "
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"Use this to save notes, summaries, or any content the user wants to store. "
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"Always call ae_journal_search first to check for existing entries on the same topic."
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),
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"journal_id": types.Schema(
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type=types.Type.STRING,
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description=(
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"The id_random of the target journal. "
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"Ask the user which journal to write to if not specified."
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),
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),
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"title": types.Schema(
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type=types.Type.STRING,
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description="Entry title",
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),
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"content": types.Schema(
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type=types.Type.STRING,
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description="Full entry content (markdown supported)",
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),
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"summary": types.Schema(
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type=types.Type.STRING,
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description="Optional short summary (1-2 sentences)",
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),
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"tags": types.Schema(
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type=types.Type.STRING,
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description="Optional comma-separated tags (e.g. 'wireguard, networking, homelab')",
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),
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},
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required=["journal_id", "title", "content"],
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),
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)
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_ae_task_list_declaration = types.FunctionDeclaration(
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name="ae_task_list",
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description=(
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"List tasks from the agents_sync Kanban board (todo and in-progress). "
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"Use this when asked about current work, pending tasks, or project status."
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),
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"include_done": types.Schema(
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type=types.Type.BOOLEAN,
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description="If true, also include completed tasks (default false)",
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),
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},
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),
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)
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_file_read_declaration = types.FunctionDeclaration(
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name="file_read",
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description=(
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"Read a local file and return its contents. "
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"Allowed directories: ~/agents_sync/, ~/OSIT_dev/, ~/DgrZone_Nextcloud/, ~/OSIT_Nextcloud/. "
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"Use this to read documentation, notes, CLAUDE.md files, or config references. "
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"If given a directory path, returns a directory listing instead."
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),
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parameters=types.Schema(
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type=types.Type.OBJECT,
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properties={
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"path": types.Schema(
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type=types.Type.STRING,
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description=(
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"Absolute or home-relative path to the file "
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"(e.g. ~/agents_sync/CLAUDE.md or /home/scott/agents_sync/tasks/01_todo/)"
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),
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),
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"max_lines": types.Schema(
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type=types.Type.INTEGER,
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description="Optional line limit (default 500)",
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),
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},
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required=["path"],
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),
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)
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# ---------------------------------------------------------------------------
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# Registry: maps tool name → async callable
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# ---------------------------------------------------------------------------
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_CALLABLES: dict[str, callable] = {
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"web_search": _web_search,
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"ae_journal_search": _ae_journal_search,
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"ae_journal_entry_create": _ae_journal_entry_create,
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"ae_task_list": _ae_task_list,
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"file_read": _file_read,
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}
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# Gemini Tool object — pass this to GenerateContentConfig
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TOOL_DECLARATIONS = [
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types.Tool(function_declarations=[
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_web_search_declaration,
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_ae_journal_search_declaration,
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_ae_journal_entry_create_declaration,
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_ae_task_list_declaration,
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_file_read_declaration,
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])
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]
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async def call_tool(name: str, args: dict) -> str:
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"""Dispatch a tool call by name. Returns result as a string."""
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fn = _CALLABLES.get(name)
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if fn is None:
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return f"Unknown tool: {name}"
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return await fn(**args)
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