Add filter to simple qa agent

CHANGELOG.md

@@ -1,6 +1,19 @@
 # Changelog
 ## [Unreleased]
 
+### Added
+
+- **Search Filter for Graphs**: Research and Deep QA graphs now support `search_filter` parameter to restrict searches to specific documents
+  - Set `state.search_filter` to a SQL WHERE clause (e.g., `"id IN ('doc1', 'doc2')"`) before running the graph
+  - Enables document-scoped research workflows
+  - CLI: `haiku-rag research "question" --filter "uri LIKE '%paper%'"`
+  - CLI: `haiku-rag ask "question" --filter "title = 'My Doc'"`
+  - Python: `client.ask(question, filter="...")` and `agent.answer(question, filter="...")`
+- **AG-UI Research Example**: Added bidirectional state demonstration with document filter
+  - New `/api/documents` endpoint to list available documents
+  - Frontend document selector component with search and multi-select
+  - Demonstrates client-to-server state flow via AG-UI protocol
+
 ## [0.20.0] - 2025-12-10
 
 ### Added

docs/cli.md

@@ -149,9 +149,9 @@ Show verbose output with deep QA:
 haiku-rag ask "What are the main features and architecture of haiku.rag?" --deep --verbose
 ```
 
-Filter to specific documents with deep QA:
+Filter to specific documents:
 ```bash
-haiku-rag ask "What are the main findings?" --deep --filter "uri LIKE '%paper%'"
+haiku-rag ask "What are the main findings?" --filter "uri LIKE '%paper%'"
 ```
 
 The QA agent searches your documents for relevant information and provides a comprehensive answer. When available, citations use the document title; otherwise they fall back to the URI.
@@ -161,7 +161,7 @@ Flags:
 - `--cite`: Include citations showing which documents were used
 - `--deep`: Decompose the question into sub-questions answered in parallel before synthesizing a final answer
 - `--verbose`: Show planning, searching, evaluation, and synthesis steps (only with `--deep`)
-- `--filter`: Restrict searches to documents matching the filter (only with `--deep`)
+- `--filter`: Restrict searches to documents matching the filter (see [Filtering Search Results](python.md#filtering-search-results))
 
 ## Research
 

haiku_rag_slim/haiku/rag/app.py

@@ -363,7 +363,7 @@ class HaikuRAGApp:
                         if cite:
                             citations = result.citations
                 else:
-                    answer, citations = await self.client.ask(question)
+                    answer, citations = await self.client.ask(question, filter=filter)
 
                 self.console.print(f"[bold blue]Question:[/bold blue] {question}")
                 self.console.print()

haiku_rag_slim/haiku/rag/cli.py

@@ -309,7 +309,7 @@ def ask(
         None,
         "--filter",
         "-f",
-        help="SQL WHERE clause to filter documents (only with --deep)",
+        help="SQL WHERE clause to filter documents (e.g., \"uri LIKE '%arxiv%'\")",
     ),
 ):
     app = create_app(db)

haiku_rag_slim/haiku/rag/client.py

@@ -1229,13 +1229,17 @@ class HaikuRAG:
         return final_results + passthrough
 
     async def ask(
-        self, question: str, system_prompt: str | None = None
+        self,
+        question: str,
+        system_prompt: str | None = None,
+        filter: str | None = None,
     ) -> "tuple[str, list[Citation]]":
         """Ask a question using the configured QA agent.
 
         Args:
             question: The question to ask.
             system_prompt: Optional custom system prompt for the QA agent.
+            filter: SQL WHERE clause to filter documents.
 
         Returns:
             Tuple of (answer text, list of resolved citations).
@@ -1243,7 +1247,7 @@ class HaikuRAG:
         from haiku.rag.qa import get_qa_agent
 
         qa_agent = get_qa_agent(self, config=self._config, system_prompt=system_prompt)
-        return await qa_agent.answer(question)
+        return await qa_agent.answer(question, filter=filter)
 
     async def visualize_chunk(self, chunk: Chunk) -> list:
         """Render page images with bounding box highlights for a chunk.

haiku_rag_slim/haiku/rag/qa/agent.py

@@ -15,6 +15,7 @@ class Dependencies(BaseModel):
     model_config = {"arbitrary_types_allowed": True}
     client: HaikuRAG
     search_results: list[SearchResult] = []
+    search_filter: str | None = None
 
 
 class QuestionAnswerAgent:
@@ -46,7 +47,9 @@ class QuestionAnswerAgent:
             Returns results with chunk IDs and relevance scores.
             Reference results by their chunk_id in cited_chunks.
             """
-            results = await ctx.deps.client.search(query, limit=limit)
+            results = await ctx.deps.client.search(
+                query, limit=limit, filter=ctx.deps.search_filter
+            )
             results = await ctx.deps.client.expand_context(results)
             # Store results for citation resolution
             ctx.deps.search_results = results
@@ -54,13 +57,19 @@ class QuestionAnswerAgent:
             parts = [r.format_for_agent() for r in results]
             return "\n\n".join(parts) if parts else "No results found."
 
-    async def answer(self, question: str) -> tuple[str, list[Citation]]:
+    async def answer(
+        self, question: str, filter: str | None = None
+    ) -> tuple[str, list[Citation]]:
         """Answer a question using the RAG system.
 
+        Args:
+            question: The question to answer
+            filter: SQL WHERE clause to filter documents
+
         Returns:
             Tuple of (answer text, list of resolved citations)
         """
-        deps = Dependencies(client=self._client)
+        deps = Dependencies(client=self._client, search_filter=filter)
         result = await self._agent.run(question, deps=deps)
         citations = resolve_citations(result.output.cited_chunks, deps.search_results)
         return result.output.answer, citations