Config research provider/model, CLI

src/haiku/rag/app.py

@@ -9,6 +9,7 @@ from haiku.rag.client import HaikuRAG
 from haiku.rag.config import Config
 from haiku.rag.mcp import create_mcp_server
 from haiku.rag.monitor import FileWatcher
+from haiku.rag.research.orchestrator import ResearchOrchestrator
 from haiku.rag.store.models.chunk import Chunk
 from haiku.rag.store.models.document import Document
 
@@ -78,6 +79,83 @@ class HaikuRAGApp:
             except Exception as e:
                 self.console.print(f"[red]Error: {e}[/red]")
 
+    async def research(
+        self, question: str, max_iterations: int = 3, verbose: bool = False
+    ):
+        """Run multi-agent research on a question."""
+        async with HaikuRAG(db_path=self.db_path) as client:
+            try:
+                # Create orchestrator with default config or fallback to QA
+                orchestrator = ResearchOrchestrator()
+
+                if verbose:
+                    self.console.print(
+                        f"[bold cyan]Starting research with {orchestrator.provider}:{orchestrator.model}[/bold cyan]"
+                    )
+                    self.console.print(f"[bold blue]Question:[/bold blue] {question}")
+                    self.console.print()
+
+                # Conduct research
+                report = await orchestrator.conduct_research(
+                    question=question,
+                    client=client,
+                    max_iterations=max_iterations,
+                )
+
+                # Display the report
+                self.console.print("[bold green]Research Report[/bold green]")
+                self.console.rule()
+
+                # Title and Executive Summary
+                self.console.print(f"[bold]{report.title}[/bold]")
+                self.console.print()
+                self.console.print("[bold cyan]Executive Summary:[/bold cyan]")
+                self.console.print(report.executive_summary)
+                self.console.print()
+
+                # Main Findings
+                if report.main_findings:
+                    self.console.print("[bold cyan]Main Findings:[/bold cyan]")
+                    for finding in report.main_findings:
+                        self.console.print(f"• {finding}")
+                    self.console.print()
+
+                # Themes
+                if report.themes:
+                    self.console.print("[bold cyan]Key Themes:[/bold cyan]")
+                    for theme, explanation in report.themes.items():
+                        self.console.print(f"• [bold]{theme}[/bold]: {explanation}")
+                    self.console.print()
+
+                # Conclusions
+                if report.conclusions:
+                    self.console.print("[bold cyan]Conclusions:[/bold cyan]")
+                    for conclusion in report.conclusions:
+                        self.console.print(f"• {conclusion}")
+                    self.console.print()
+
+                # Recommendations
+                if report.recommendations:
+                    self.console.print("[bold cyan]Recommendations:[/bold cyan]")
+                    for rec in report.recommendations:
+                        self.console.print(f"• {rec}")
+                    self.console.print()
+
+                # Limitations
+                if report.limitations:
+                    self.console.print("[bold yellow]Limitations:[/bold yellow]")
+                    for limitation in report.limitations:
+                        self.console.print(f"• {limitation}")
+                    self.console.print()
+
+                # Sources Summary
+                if report.sources_summary:
+                    self.console.print("[bold cyan]Sources:[/bold cyan]")
+                    self.console.print(report.sources_summary)
+
+            except Exception as e:
+                self.console.print(f"[red]Error during research: {e}[/red]")
+
     async def rebuild(self):
         async with HaikuRAG(db_path=self.db_path, skip_validation=True) as client:
             try:

src/haiku/rag/cli.py

@@ -235,6 +235,38 @@ def ask(
     asyncio.run(app.ask(question=question, cite=cite))
 
 
+@cli.command("research", help="Run multi-agent research and output a concise report")
+def research(
+    question: str = typer.Argument(
+        help="The research question to investigate",
+    ),
+    max_iterations: int = typer.Option(
+        3,
+        "--max-iterations",
+        "-n",
+        help="Maximum search/analyze iterations",
+    ),
+    db: Path = typer.Option(
+        Config.DEFAULT_DATA_DIR / "haiku.rag.lancedb",
+        "--db",
+        help="Path to the LanceDB database file",
+    ),
+    verbose: bool = typer.Option(
+        False,
+        "--verbose",
+        help="Show verbose progress output",
+    ),
+):
+    app = HaikuRAGApp(db_path=db)
+    asyncio.run(
+        app.research(
+            question=question,
+            max_iterations=max_iterations,
+            verbose=verbose,
+        )
+    )
+
+
 @cli.command("settings", help="Display current configuration settings")
 def settings():
     app = HaikuRAGApp(db_path=Path())  # Don't need actual DB for settings

src/haiku/rag/config.py

@@ -29,6 +29,10 @@ class AppConfig(BaseModel):
     QA_PROVIDER: str = "ollama"
     QA_MODEL: str = "qwen3"
 
+    # Research defaults (fallback to QA if not provided via env)
+    RESEARCH_PROVIDER: str = ""
+    RESEARCH_MODEL: str = ""
+
     CHUNK_SIZE: int = 256
     CONTEXT_CHUNK_RADIUS: int = 0
 

src/haiku/rag/research/orchestrator.py

@@ -1,10 +1,9 @@
-"""Research orchestrator agent that coordinates specialized agents."""
-
 from typing import Any
 
 from pydantic import BaseModel, Field
 from pydantic_ai import RunContext
 
+from haiku.rag.config import Config
 from haiku.rag.research.analysis_agent import AnalysisAgent, AnalysisResult
 from haiku.rag.research.base import BaseResearchAgent
 from haiku.rag.research.clarification_agent import (
@@ -32,10 +31,11 @@ class ResearchPlan(BaseModel):
 class ResearchOrchestrator(BaseResearchAgent):
     """Orchestrator agent that coordinates the research workflow."""
 
-    def __init__(self, provider: str, model: str):
+    def __init__(
+        self, provider: str = Config.RERANK_PROVIDER, model: str = Config.RERANK_MODEL
+    ):
         super().__init__(provider, model, output_type=ResearchPlan)
 
-        # Initialize specialized agents
         self.search_agent = SearchSpecialistAgent(provider, model)
         self.analysis_agent = AnalysisAgent(provider, model)
         self.clarification_agent = ClarificationAgent(provider, model)

tests/research/test_orchestrator.py

@@ -51,6 +51,20 @@ def create_mock_chunk(chunk_id: str, content: str, score: float = 0.8):
 class TestResearchOrchestrator:
     """Test suite for ResearchOrchestrator."""
 
+    def test_orchestrator_uses_config_defaults(self):
+        """Test that orchestrator uses config defaults when no args provided."""
+        orchestrator = ResearchOrchestrator()
+
+        # Should use RESEARCH_PROVIDER/MODEL if set, else QA_PROVIDER/MODEL
+        assert orchestrator.provider is not None
+        assert orchestrator.model is not None
+
+        # All agents should use the same provider/model
+        assert orchestrator.search_agent.provider == orchestrator.provider
+        assert orchestrator.search_agent.model == orchestrator.model
+        assert orchestrator.analysis_agent.provider == orchestrator.provider
+        assert orchestrator.analysis_agent.model == orchestrator.model
+
     def test_orchestrator_initialization(self):
         """Test that orchestrator initializes all agents correctly."""
         orchestrator = ResearchOrchestrator(provider="openai", model="gpt-4")