mirror of
https://github.com/open-jarvis/OpenJarvis.git
synced 2026-07-28 14:07:55 +00:00
feat: add jarvis deep-research-setup CLI command
Auto-detects local sources (Apple Notes, iMessage, Obsidian), ingests them into ~/.openjarvis/knowledge.db via IngestionPipeline + SyncEngine, and launches an interactive Deep Research chat session with Qwen3.5 via Ollama. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Jon Saad-Falcon
co-authored by
Claude Sonnet 4.6
Claude Sonnet 4.6
parent
bf3549856a
commit
bebb604a23
@@ -14,6 +14,7 @@ from openjarvis.cli.chat_cmd import chat
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from openjarvis.cli.compose_cmd import compose
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from openjarvis.cli.config_cmd import config
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from openjarvis.cli.connect_cmd import connect
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from openjarvis.cli.deep_research_setup_cmd import deep_research_setup
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from openjarvis.cli.daemon_cmd import restart, start, status, stop
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from openjarvis.cli.doctor_cmd import doctor
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from openjarvis.cli.eval_cmd import eval_group
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@@ -91,6 +92,7 @@ cli.add_command(registry, "registry")
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cli.add_command(config, "config")
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cli.add_command(scan, "scan")
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cli.add_command(connect, "connect")
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cli.add_command(deep_research_setup, "deep-research-setup")
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def main() -> None:
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@@ -0,0 +1,258 @@
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"""``jarvis deep-research-setup`` — auto-detect local sources, ingest, and chat.
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Walks the user through connecting local data sources (Apple Notes, iMessage,
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Obsidian), ingesting them into a shared KnowledgeStore, and launching an
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interactive Deep Research chat session with Qwen3.5 via Ollama.
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"""
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from __future__ import annotations
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import sys
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from pathlib import Path
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from typing import Any, Dict, List, Optional
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import click
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from rich.console import Console
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from rich.table import Table
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from openjarvis.connectors.pipeline import IngestionPipeline
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from openjarvis.connectors.store import KnowledgeStore
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from openjarvis.connectors.sync_engine import SyncEngine
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from openjarvis.core.config import DEFAULT_CONFIG_DIR
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# ---------------------------------------------------------------------------
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# Constants
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# ---------------------------------------------------------------------------
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_DEFAULT_NOTES_DB = (
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Path.home()
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/ "Library"
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/ "Group Containers"
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/ "group.com.apple.notes"
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/ "NoteStore.sqlite"
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)
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_DEFAULT_IMESSAGE_DB = Path.home() / "Library" / "Messages" / "chat.db"
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_OLLAMA_MODEL = "qwen3.5:4b"
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# ---------------------------------------------------------------------------
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# Detection
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# ---------------------------------------------------------------------------
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def detect_local_sources(
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*,
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notes_db_path: Optional[Path] = None,
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imessage_db_path: Optional[Path] = None,
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obsidian_vault_path: Optional[Path] = None,
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) -> List[Dict[str, Any]]:
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"""Return a list of available local sources with their config.
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Each entry is a dict with keys: ``connector_id``, ``display_name``,
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``config`` (kwargs for the connector constructor).
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"""
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sources: List[Dict[str, Any]] = []
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notes_path = notes_db_path or _DEFAULT_NOTES_DB
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if notes_path.exists():
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sources.append({
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"connector_id": "apple_notes",
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"display_name": "Apple Notes",
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"config": {"db_path": str(notes_path)},
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})
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imessage_path = imessage_db_path or _DEFAULT_IMESSAGE_DB
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if imessage_path.exists():
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sources.append({
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"connector_id": "imessage",
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"display_name": "iMessage",
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"config": {"db_path": str(imessage_path)},
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})
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if obsidian_vault_path and obsidian_vault_path.is_dir():
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sources.append({
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"connector_id": "obsidian",
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"display_name": "Obsidian / Markdown",
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"config": {"vault_path": str(obsidian_vault_path)},
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})
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return sources
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# ---------------------------------------------------------------------------
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# Ingestion
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# ---------------------------------------------------------------------------
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def _instantiate_connector(connector_id: str, config: Dict[str, Any]) -> Any:
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"""Lazily import and instantiate a connector by ID."""
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if connector_id == "apple_notes":
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from openjarvis.connectors.apple_notes import AppleNotesConnector
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return AppleNotesConnector(db_path=config.get("db_path", ""))
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elif connector_id == "imessage":
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from openjarvis.connectors.imessage import IMessageConnector
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return IMessageConnector(db_path=config.get("db_path", ""))
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elif connector_id == "obsidian":
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from openjarvis.connectors.obsidian import ObsidianConnector
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return ObsidianConnector(vault_path=config.get("vault_path", ""))
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else:
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msg = f"Unknown connector: {connector_id}"
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raise ValueError(msg)
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def ingest_sources(
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sources: List[Dict[str, Any]],
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store: KnowledgeStore,
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) -> int:
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"""Connect and ingest all sources into the KnowledgeStore.
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Returns total chunks indexed across all sources.
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"""
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pipeline = IngestionPipeline(store)
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engine = SyncEngine(pipeline)
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total = 0
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for src in sources:
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connector = _instantiate_connector(src["connector_id"], src["config"])
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chunks = engine.sync(connector)
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total += chunks
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return total
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# ---------------------------------------------------------------------------
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# Chat launch
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# ---------------------------------------------------------------------------
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def _launch_chat(store: KnowledgeStore, console: Console) -> None:
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"""Start an interactive Deep Research chat session."""
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from openjarvis.agents.deep_research import DeepResearchAgent
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from openjarvis.connectors.retriever import TwoStageRetriever
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from openjarvis.engine.ollama import OllamaEngine
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from openjarvis.tools.knowledge_search import KnowledgeSearchTool
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console.print("\n[bold]Setting up Deep Research agent...[/bold]")
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# Engine
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engine = OllamaEngine()
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if not engine.health():
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console.print(
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"[red]Ollama is not running.[/red] Start it with: "
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"[bold]ollama serve[/bold]"
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)
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return
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models = engine.list_models()
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if _OLLAMA_MODEL not in models and f"{_OLLAMA_MODEL}:latest" not in models:
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base_name = _OLLAMA_MODEL.split(":")[0]
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matching = [m for m in models if m.startswith(base_name)]
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if not matching:
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console.print(
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f"[yellow]Model {_OLLAMA_MODEL} not found.[/yellow] "
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f"Pull it with: [bold]ollama pull {_OLLAMA_MODEL}[/bold]"
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)
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return
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# Retriever + tool
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retriever = TwoStageRetriever(store)
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search_tool = KnowledgeSearchTool(retriever=retriever)
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# Agent
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agent = DeepResearchAgent(
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engine=engine,
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model=_OLLAMA_MODEL,
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tools=[search_tool],
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interactive=True,
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)
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console.print(
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f"[green]Ready![/green] Using [bold]{_OLLAMA_MODEL}[/bold] via Ollama.\n"
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"Type your research question. Type [bold]/quit[/bold] to exit.\n"
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)
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# REPL
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while True:
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try:
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query = console.input("[bold blue]research>[/bold blue] ").strip()
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except (EOFError, KeyboardInterrupt):
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break
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if not query:
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continue
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if query.lower() in ("/quit", "/exit", "quit", "exit"):
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break
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try:
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result = agent.run(query)
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console.print(f"\n{result.content}\n")
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if result.metadata and result.metadata.get("sources"):
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console.print("[dim]Sources:[/dim]")
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for s in result.metadata["sources"]:
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console.print(f" [dim]- {s}[/dim]")
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console.print()
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except Exception as exc: # noqa: BLE001
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console.print(f"[red]Error: {exc}[/red]\n")
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# ---------------------------------------------------------------------------
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# CLI command
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# ---------------------------------------------------------------------------
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@click.command("deep-research-setup")
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@click.option(
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"--obsidian-vault",
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type=click.Path(exists=True, file_okay=False),
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default=None,
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help="Path to an Obsidian vault directory.",
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)
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@click.option("--skip-chat", is_flag=True, help="Ingest only, don't launch chat.")
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def deep_research_setup(obsidian_vault: Optional[str], skip_chat: bool) -> None:
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"""Auto-detect local data sources, ingest, and launch Deep Research chat."""
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console = Console()
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console.print("\n[bold]Deep Research Setup[/bold]\n")
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# 1. Detect
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vault_path = Path(obsidian_vault) if obsidian_vault else None
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sources = detect_local_sources(obsidian_vault_path=vault_path)
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if not sources:
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console.print(
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"[yellow]No local data sources detected.[/yellow]\n"
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"On macOS, ensure Full Disk Access is granted in "
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"System Settings > Privacy & Security."
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)
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sys.exit(1)
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# 2. Confirm
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table = Table(title="Detected Sources")
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table.add_column("Source", style="bold")
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table.add_column("Status", style="green")
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for src in sources:
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table.add_row(src["display_name"], "ready")
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console.print(table)
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console.print()
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if not click.confirm("Ingest these sources?", default=True):
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sys.exit(0)
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# 3. Ingest
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db_path = DEFAULT_CONFIG_DIR / "knowledge.db"
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db_path.parent.mkdir(parents=True, exist_ok=True)
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store = KnowledgeStore(str(db_path))
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console.print("\n[bold]Ingesting...[/bold]")
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for src in sources:
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connector = _instantiate_connector(src["connector_id"], src["config"])
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pipeline = IngestionPipeline(store)
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engine = SyncEngine(pipeline)
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chunks = engine.sync(connector)
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console.print(f" {src['display_name']}: [green]{chunks} chunks[/green]")
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console.print(f"\n[bold green]Done![/bold green] {store.count()} total chunks in {db_path}\n")
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# 4. Chat
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if skip_chat:
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return
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_launch_chat(store, console)
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@@ -0,0 +1,139 @@
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"""Tests for the deep-research-setup CLI command."""
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from __future__ import annotations
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import gzip
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import sqlite3
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from pathlib import Path
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from typing import List
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import pytest
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from openjarvis.connectors._stubs import Document
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# ---------------------------------------------------------------------------
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# Helpers
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# ---------------------------------------------------------------------------
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def _create_fake_notes_db(db_path: Path) -> None:
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"""Create a minimal Apple Notes SQLite database."""
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conn = sqlite3.connect(str(db_path))
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conn.executescript("""
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CREATE TABLE ZICCLOUDSYNCINGOBJECT (
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Z_PK INTEGER PRIMARY KEY,
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ZTITLE TEXT,
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ZTITLE1 TEXT,
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ZMODIFICATIONDATE REAL,
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ZIDENTIFIER TEXT,
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ZNOTE INTEGER
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);
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CREATE TABLE ZICNOTEDATA (
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Z_PK INTEGER PRIMARY KEY,
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ZDATA BLOB,
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ZNOTE INTEGER
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);
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""")
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content = gzip.compress(b"Test note about meetings")
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conn.execute(
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"INSERT INTO ZICCLOUDSYNCINGOBJECT VALUES (1, NULL, 'Test Note', 694310400.0, 'n1', 1)"
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)
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conn.execute("INSERT INTO ZICNOTEDATA VALUES (1, ?, 1)", (content,))
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conn.commit()
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conn.close()
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def _create_fake_imessage_db(db_path: Path) -> None:
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"""Create a minimal iMessage SQLite database."""
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conn = sqlite3.connect(str(db_path))
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conn.executescript("""
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CREATE TABLE handle (ROWID INTEGER PRIMARY KEY, id TEXT);
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CREATE TABLE chat (ROWID INTEGER PRIMARY KEY, chat_identifier TEXT, display_name TEXT);
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CREATE TABLE chat_message_join (chat_id INTEGER, message_id INTEGER);
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CREATE TABLE message (
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ROWID INTEGER PRIMARY KEY, text TEXT, handle_id INTEGER,
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date INTEGER, is_from_me INTEGER
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);
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""")
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conn.execute("INSERT INTO handle VALUES (1, '+15551234567')")
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conn.execute("INSERT INTO chat VALUES (1, '+15551234567', 'Test Chat')")
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conn.execute("INSERT INTO chat_message_join VALUES (1, 1)")
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conn.execute("INSERT INTO message VALUES (1, 'Hello from test', 1, 694310400000000000, 0)")
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conn.commit()
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conn.close()
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# ---------------------------------------------------------------------------
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# Tests
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# ---------------------------------------------------------------------------
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def test_detect_local_sources(tmp_path: Path) -> None:
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"""Auto-detection finds Apple Notes and iMessage when DBs exist."""
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from openjarvis.cli.deep_research_setup_cmd import detect_local_sources
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notes_db = tmp_path / "NoteStore.sqlite"
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imessage_db = tmp_path / "chat.db"
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_create_fake_notes_db(notes_db)
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_create_fake_imessage_db(imessage_db)
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sources = detect_local_sources(
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notes_db_path=notes_db,
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imessage_db_path=imessage_db,
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obsidian_vault_path=None,
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)
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ids = [s["connector_id"] for s in sources]
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assert "apple_notes" in ids
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assert "imessage" in ids
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def test_detect_skips_missing_sources(tmp_path: Path) -> None:
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"""Auto-detection skips sources whose files don't exist."""
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from openjarvis.cli.deep_research_setup_cmd import detect_local_sources
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sources = detect_local_sources(
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notes_db_path=tmp_path / "nonexistent.sqlite",
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imessage_db_path=tmp_path / "nonexistent.db",
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obsidian_vault_path=None,
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)
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assert len(sources) == 0
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def test_detect_includes_obsidian_when_vault_exists(tmp_path: Path) -> None:
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"""Auto-detection includes Obsidian when vault path exists."""
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from openjarvis.cli.deep_research_setup_cmd import detect_local_sources
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vault = tmp_path / "vault"
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vault.mkdir()
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(vault / "note.md").write_text("# Hello")
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sources = detect_local_sources(
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notes_db_path=tmp_path / "nonexistent.sqlite",
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imessage_db_path=tmp_path / "nonexistent.db",
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obsidian_vault_path=vault,
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)
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ids = [s["connector_id"] for s in sources]
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assert "obsidian" in ids
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def test_ingest_sources(tmp_path: Path) -> None:
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"""ingest_sources connects and ingests documents into KnowledgeStore."""
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from openjarvis.cli.deep_research_setup_cmd import detect_local_sources, ingest_sources
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from openjarvis.connectors.store import KnowledgeStore
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notes_db = tmp_path / "NoteStore.sqlite"
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_create_fake_notes_db(notes_db)
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sources = detect_local_sources(
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notes_db_path=notes_db,
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imessage_db_path=tmp_path / "nonexistent.db",
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obsidian_vault_path=None,
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)
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db_path = tmp_path / "knowledge.db"
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store = KnowledgeStore(str(db_path))
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total = ingest_sources(sources, store)
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assert total > 0
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assert store.count() > 0
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store.close()
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