Merge pull request #263 from ggozad/feat/state-deltas

Send delta snapshots instead of full snapshots in AGUI

CHANGELOG.md

@@ -17,10 +17,11 @@
 
 ### Changed
 
-- **Selective Citation Filtering**: Synthesis steps now select only relevant citations instead of including all
+- **AG-UI State Delta Updates**: Web application now sends `StateDeltaEvent` (JSON Patch RFC 6902) instead of full `StateSnapshotEvent` for state updates
-  - LLM receives `<available_citations>` with chunk IDs and content previews
+  - Reduces bandwidth when state grows large (e.g., 50 Q&As with citations)
-  - LLM populates `cited_chunks` with only chunks that directly support the answer
+  - First request still sends full snapshot; subsequent requests send only changes
-  - `ResearchReport` now has `cited_chunks` and `citations` fields; removed `sources_summary`
+  - Backend logging shows incoming/outgoing state events for debugging
+
 
 ## [0.27.1] - 2026-01-27
 

app/backend/main.py

@@ -79,38 +79,71 @@ async def stream_chat(request: Request) -> Response:
     accept = request.headers.get("accept", SSE_CONTENT_TYPE)
     run_input = AGUIAdapter.build_run_input(body)
 
-    # Restore session state from incoming AG-UI state (look under namespaced key)
+    # Restore session state from incoming AG-UI state
-    initial_qa_history: list[QAResponse] = []
+    session_state = ChatSessionState(session_id="")  # New session: empty session_id
-    session_id: str | None = None
-    document_filter: list[str] = []
-    initial_context: str | None = None
     state = getattr(run_input, "state", None)
-    if state:
+    if state and AGUI_STATE_KEY in state:
-        chat_state = state.get(AGUI_STATE_KEY, state)
+        chat_state = state[AGUI_STATE_KEY]
-        if "qa_history" in chat_state:
+        if chat_state and chat_state.get("session_id"):
-            initial_qa_history = [
+            session_state = ChatSessionState(
-                QAResponse(**qa) for qa in chat_state.get("qa_history", [])
+                session_id=chat_state["session_id"],
-            ]
+                qa_history=[
-        session_id = chat_state.get("session_id")
+                    QAResponse(**qa) for qa in chat_state.get("qa_history", [])
-        document_filter = chat_state.get("document_filter", [])
+                ],
-        initial_context = chat_state.get("initial_context")
+                document_filter=chat_state.get("document_filter", []),
+                initial_context=chat_state.get("initial_context"),
+                citation_registry=chat_state.get("citation_registry", {}),
+            )
+            logger.info(
+                f"Incoming state: session={session_state.session_id[:8]}, "
+                f"qa_history={len(session_state.qa_history)}, "
+                f"citations={len(session_state.citation_registry)}"
+            )
+        else:
+            logger.info("Incoming state: new session")
+    else:
+        logger.info("Incoming state: new session")
 
     deps = ChatDeps(
         client=get_client(db_path),
         config=Config,
-        session_state=ChatSessionState(
+        session_state=session_state,
-            qa_history=initial_qa_history,
-            document_filter=document_filter,
-            initial_context=initial_context,
-            **({"session_id": session_id} if session_id else {}),
-        ),
         state_key=AGUI_STATE_KEY,
     )
 
     # Use AGUIAdapter for streaming
     adapter = AGUIAdapter(agent=chat_agent, run_input=run_input, accept=accept)
     event_stream = adapter.run_stream(deps=deps)
-    sse_event_stream = adapter.encode_stream(event_stream)
+
+    async def logged_event_stream():
+        async for event in event_stream:
+            event_type = getattr(event, "type", None)
+            if event_type and "state" in str(event_type).lower():
+                delta = getattr(event, "delta", None)
+                snapshot = getattr(event, "snapshot", None)
+                if delta is not None:
+                    logger.info(f"Outgoing StateDeltaEvent: {len(delta)} ops")
+                    for op in delta:
+                        # Extract key from path like /haiku.rag.chat/qa_history/0
+                        parts = op["path"].split("/")
+                        key = "/".join(parts[2:]) if len(parts) > 2 else op["path"]
+                        logger.info(f"  {op['op']} {key}")
+                elif snapshot is not None:
+                    chat_state = snapshot.get(AGUI_STATE_KEY, {})
+                    sid = chat_state.get("session_id", "")[:8] if chat_state else ""
+                    qa_len = len(chat_state.get("qa_history", [])) if chat_state else 0
+                    reg_len = (
+                        len(chat_state.get("citation_registry", {}))
+                        if chat_state
+                        else 0
+                    )
+                    logger.info(
+                        f"Outgoing StateSnapshotEvent: session={sid}, "
+                        f"qa={qa_len}, keys={reg_len}"
+                    )
+            yield event
+
+    sse_event_stream = adapter.encode_stream(logged_event_stream())
 
     return StreamingResponse(
         sse_event_stream,

app/frontend/components/Chat.tsx

@@ -47,6 +47,7 @@ interface ChatSessionState {
 	qa_history: QAResponse[];
 	session_context: SessionContext | null;
 	document_filter: string[];
+	citation_registry: Record<string, number>;
 }
 
 // AG-UI state is namespaced under AGUI_STATE_KEY
@@ -404,6 +405,7 @@ function ChatContentInner() {
 					qa_history: [],
 					session_context: null,
 					document_filter: [],
+					citation_registry: {},
 				},
 			},
 		},
@@ -429,6 +431,8 @@ function ChatContentInner() {
 				qa_history: agentState?.[AGUI_STATE_KEY]?.qa_history ?? [],
 				session_context: agentState?.[AGUI_STATE_KEY]?.session_context ?? null,
 				document_filter: selected,
+				citation_registry:
+					agentState?.[AGUI_STATE_KEY]?.citation_registry ?? {},
 			},
 		});
 	};
@@ -445,6 +449,8 @@ function ChatContentInner() {
 				qa_history: agentState?.[AGUI_STATE_KEY]?.qa_history ?? [],
 				session_context: agentState?.[AGUI_STATE_KEY]?.session_context ?? null,
 				document_filter: agentState?.[AGUI_STATE_KEY]?.document_filter ?? [],
+				citation_registry:
+					agentState?.[AGUI_STATE_KEY]?.citation_registry ?? {},
 			},
 		});
 	};

docs/configuration/prompts.md

@@ -71,7 +71,7 @@ prompts:
 
 Replace the research report synthesis prompt by setting `prompts.synthesis`. This controls how the multi-agent research workflow generates its final report.
 
-The prompt should produce a `ResearchReport` with: `title`, `executive_summary`, `main_findings`, `conclusions`, `recommendations`, `limitations`, and `cited_chunks`.
+The prompt should produce a `ResearchReport` with: `title`, `executive_summary`, `main_findings`, `conclusions`, `recommendations`, `limitations`, and `sources_summary`.
 
 **Example:**
 
@@ -87,13 +87,12 @@ prompts:
     - conclusions: 2-4 bullet points
     - recommendations: 2-5 actionable recommendations
     - limitations: 1-3 limitations or gaps
-    - cited_chunks: List of chunk IDs that directly support the report
+    - sources_summary: Brief description of sources used
 
     Guidelines:
     - Base all content strictly on collected evidence
     - Be specific and objective
     - Avoid meta-commentary like "This report covers..."
-    - Only include chunks in cited_chunks that directly support claims in the report
 ```
 
 ## Picture Description Prompt

haiku_rag_slim/haiku/rag/agents/chat/agent.py

@@ -1,7 +1,7 @@
 import asyncio
 import math
+import uuid
 
-from ag_ui.core import EventType, StateSnapshotEvent
 from pydantic_ai import Agent, RunContext, ToolReturn
 
 from haiku.rag.agents.chat.context import (
@@ -20,6 +20,7 @@ from haiku.rag.agents.chat.state import (
     build_document_filter,
     build_multi_document_filter,
     combine_filters,
+    emit_state_event,
 )
 from haiku.rag.agents.research.dependencies import ResearchContext
 from haiku.rag.agents.research.graph import build_conversational_graph
@@ -94,11 +95,9 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
             limit: Number of results to return (default: 5)
         """
         # Build session filter from document_filter
-        session_filter = None
+        session_filter = build_multi_document_filter(
-        if ctx.deps.session_state and ctx.deps.session_state.document_filter:
+            ctx.deps.session_state.document_filter
-            session_filter = build_multi_document_filter(
+        )
-                ctx.deps.session_state.document_filter
-            )
 
         # Build tool filter from document_name parameter
         tool_filter = build_document_filter(document_name) if document_name else None
@@ -116,12 +115,16 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
         if not results:
             return ToolReturn(return_value="No results found.")
 
-        # Build citation infos using stable registry indices
+        new_state = ctx.deps.session_state.model_copy(deep=True)
+        if not new_state.session_id:
+            new_state.session_id = str(uuid.uuid4())
+
+        # Build citation infos using the copy's registry
         citation_infos = []
         for r in results:
             chunk_id = r.chunk_id or ""
-            if ctx.deps.session_state is not None and chunk_id:
+            if chunk_id:
-                index = ctx.deps.session_state.get_or_assign_index(chunk_id)
+                index = new_state.get_or_assign_index(chunk_id)
             else:
                 index = len(citation_infos) + 1
             citation_infos.append(
@@ -137,26 +140,10 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
                 )
             )
 
-        # Build new state with citations and registry
+        # Update new_state with citations and fresh session_context
-        session_id = ctx.deps.session_state.session_id if ctx.deps.session_state else ""
+        new_state.citations = citation_infos
-        new_state = ChatSessionState(
+        if new_state.session_id:
-            session_id=session_id,
+            new_state.session_context = get_cached_session_context(new_state.session_id)
-            citations=citation_infos,
-            qa_history=(
-                ctx.deps.session_state.qa_history if ctx.deps.session_state else []
-            ),
-            session_context=get_cached_session_context(session_id)
-            if session_id
-            else None,
-            document_filter=(
-                ctx.deps.session_state.document_filter if ctx.deps.session_state else []
-            ),
-            citation_registry=(
-                ctx.deps.session_state.citation_registry
-                if ctx.deps.session_state
-                else {}
-            ),
-        )
 
         # Return detailed results for the agent to present
         result_lines = []
@@ -173,19 +160,14 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
             line += f"\n    {snippet}"
             result_lines.append(line)
 
-        snapshot = new_state.model_dump(mode="json")
+        state_event = emit_state_event(
-        if ctx.deps.state_key:
+            ctx.deps.session_state, new_state, ctx.deps.state_key
-            snapshot = {ctx.deps.state_key: snapshot}
+        )
 
         return ToolReturn(
             return_value=f"Found {len(results)} results:\n\n"
             + "\n\n".join(result_lines),
-            metadata=[
+            metadata=[state_event] if state_event else None,
-                StateSnapshotEvent(
-                    type=EventType.STATE_SNAPSHOT,
-                    snapshot=snapshot,
-                )
-            ],
         )
 
     @agent.tool
@@ -204,11 +186,9 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
             document_name: Optional document name/title to search within (e.g., "tbmed593", "army manual")
         """
         # Build session filter from document_filter
-        session_filter = None
+        session_filter = build_multi_document_filter(
-        if ctx.deps.session_state and ctx.deps.session_state.document_filter:
+            ctx.deps.session_state.document_filter
-            session_filter = build_multi_document_filter(
+        )
-                ctx.deps.session_state.document_filter
-            )
 
         # Build tool filter from document_name parameter
         tool_filter = build_document_filter(document_name) if document_name else None
@@ -218,23 +198,19 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
 
         # Build and run the conversational research graph
         graph = build_conversational_graph(config=ctx.deps.config)
-        session_id = ctx.deps.session_state.session_id if ctx.deps.session_state else ""
+        session_id = ctx.deps.session_state.session_id
 
         # Get session context from server cache for planning, fallback to initial_context
-        cached_context = get_cached_session_context(session_id) if session_id else None
+        cached_context = get_cached_session_context(session_id)
         session_context = (
             cached_context.render_markdown()
             if cached_context and cached_context.summary
-            else (
+            else ctx.deps.session_state.initial_context
-                ctx.deps.session_state.initial_context
-                if ctx.deps.session_state
-                else None
-            )
         )
 
         # Find relevant prior answers from qa_history
         prior_answers = []
-        if ctx.deps.session_state and ctx.deps.session_state.qa_history:
+        if ctx.deps.session_state.qa_history:
             embedder = get_embedder(ctx.deps.config)
             question_embedding = await embedder.embed_query(question)
 
@@ -281,14 +257,14 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
 
         result = await graph.run(state=state, deps=deps)
 
-        # Build citation infos using stable registry indices
+        new_state = ctx.deps.session_state.model_copy(deep=True)
+        if not new_state.session_id:
+            new_state.session_id = str(uuid.uuid4())
+
+        # Build citation infos using the copy's registry
         citation_infos = []
         for c in result.citations:
-            # Use registry for stable indices across calls
+            index = new_state.get_or_assign_index(c.chunk_id)
-            if ctx.deps.session_state is not None:
-                index = ctx.deps.session_state.get_or_assign_index(c.chunk_id)
-            else:
-                index = len(citation_infos) + 1
             citation_infos.append(
                 Citation(
                     index=index,
@@ -302,54 +278,37 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
                 )
             )
 
-        # Accumulate Q&A in session state with full citation metadata
+        # Add Q&A to the copy's history
-        if ctx.deps.session_state is not None:
+        qa_response = QAResponse(
-            qa_response = QAResponse(
+            question=question,
-                question=question,
+            answer=result.answer,
-                answer=result.answer,
+            confidence=result.confidence,
-                confidence=result.confidence,
-                citations=citation_infos,
-            )
-            ctx.deps.session_state.qa_history.append(qa_response)
-            # Enforce FIFO limit
-            if len(ctx.deps.session_state.qa_history) > MAX_QA_HISTORY:
-                ctx.deps.session_state.qa_history = ctx.deps.session_state.qa_history[
-                    -MAX_QA_HISTORY:
-                ]
-
-            # Spawn background task to update session context
-            # Cancel any previous summarization for this session
-            if session_id in _summarization_tasks:
-                _summarization_tasks[session_id].cancel()
-
-            task = asyncio.create_task(
-                _update_context_background(
-                    qa_history=list(ctx.deps.session_state.qa_history),
-                    config=ctx.deps.config,
-                    session_state=ctx.deps.session_state,
-                )
-            )
-            _summarization_tasks[session_id] = task
-            task.add_done_callback(lambda t: _summarization_tasks.pop(session_id, None))
-
-        # Build new state with citations, qa_history, and registry
-        new_state = ChatSessionState(
-            session_id=session_id,
             citations=citation_infos,
-            qa_history=(
+        )
-                ctx.deps.session_state.qa_history if ctx.deps.session_state else []
+        new_state.qa_history.append(qa_response)
-            ),
+        # Enforce FIFO limit
-            session_context=get_cached_session_context(session_id)
+        if len(new_state.qa_history) > MAX_QA_HISTORY:
-            if session_id
+            new_state.qa_history = new_state.qa_history[-MAX_QA_HISTORY:]
-            else None,
+
-            document_filter=(
+        # Update citations and session_context
-                ctx.deps.session_state.document_filter if ctx.deps.session_state else []
+        new_state.citations = citation_infos
-            ),
+        if new_state.session_id:
-            citation_registry=(
+            new_state.session_context = get_cached_session_context(new_state.session_id)
-                ctx.deps.session_state.citation_registry
+
-                if ctx.deps.session_state
+        # Spawn background task to update session context
-                else {}
+        if new_state.session_id in _summarization_tasks:
-            ),
+            _summarization_tasks[new_state.session_id].cancel()
+
+        task = asyncio.create_task(
+            _update_context_background(
+                qa_history=list(new_state.qa_history),
+                config=ctx.deps.config,
+                session_state=new_state,
+            )
+        )
+        _summarization_tasks[new_state.session_id] = task
+        task.add_done_callback(
+            lambda t, sid=new_state.session_id: _summarization_tasks.pop(sid, None)
         )
 
         # Format answer with citation references using stable indices
@@ -358,18 +317,13 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
             citation_refs = " ".join(f"[{c.index}]" for c in citation_infos)
             answer_text = f"{answer_text}\n\nSources: {citation_refs}"
 
-        snapshot = new_state.model_dump(mode="json")
+        state_event = emit_state_event(
-        if ctx.deps.state_key:
+            ctx.deps.session_state, new_state, ctx.deps.state_key
-            snapshot = {ctx.deps.state_key: snapshot}
+        )
 
         return ToolReturn(
             return_value=answer_text,
-            metadata=[
+            metadata=[state_event] if state_event else None,
-                StateSnapshotEvent(
-                    type=EventType.STATE_SNAPSHOT,
-                    snapshot=snapshot,
-                )
-            ],
         )
 
     @agent.tool
@@ -387,12 +341,7 @@ def create_chat_agent(config: AppConfig) -> Agent[ChatDeps, str]:
         page_size = 50
         offset = (page - 1) * page_size
 
-        # Build session filter from document_filter
+        doc_filter = build_multi_document_filter(ctx.deps.session_state.document_filter)
-        doc_filter = None
-        if ctx.deps.session_state and ctx.deps.session_state.document_filter:
-            doc_filter = build_multi_document_filter(
-                ctx.deps.session_state.document_filter
-            )
 
         docs = await ctx.deps.client.list_documents(
             limit=page_size, offset=offset, filter=doc_filter

haiku_rag_slim/haiku/rag/agents/chat/state.py

@@ -3,6 +3,8 @@ from dataclasses import dataclass, field
 from datetime import datetime
 from typing import Any
 
+import jsonpatch
+from ag_ui.core import EventType, StateDeltaEvent
 from pydantic import BaseModel, Field
 
 from haiku.rag.agents.research.models import Citation, SearchAnswer
@@ -106,14 +108,14 @@ class ChatDeps:
     client: HaikuRAG
     config: AppConfig
     search_results: list[SearchResult] | None = None
-    session_state: ChatSessionState | None = None
+    session_state: ChatSessionState = field(
+        default_factory=lambda: ChatSessionState(session_id="")
+    )
     state_key: str | None = None
 
     @property
-    def state(self) -> dict[str, Any] | None:
+    def state(self) -> dict[str, Any]:
         """Get current state for AG-UI protocol."""
-        if self.session_state is None:
-            return None
         snapshot = self.session_state.model_dump()
         if self.state_key:
             return {self.state_key: snapshot}
@@ -131,29 +133,24 @@ class ChatDeps:
             if isinstance(nested, dict):
                 state_data = nested
         # Update session_state from incoming state
-        if self.session_state is not None:
+        if "qa_history" in state_data:
-            if "qa_history" in state_data:
+            self.session_state.qa_history = [
-                self.session_state.qa_history = [
+                QAResponse(**qa) if isinstance(qa, dict) else qa
-                    QAResponse(**qa) if isinstance(qa, dict) else qa
+                for qa in state_data.get("qa_history", [])
-                    for qa in state_data.get("qa_history", [])
+            ]
-                ]
+        if "citations" in state_data:
-            if "citations" in state_data:
+            self.session_state.citations = [
-                self.session_state.citations = [
+                Citation(**c) if isinstance(c, dict) else c
-                    Citation(**c) if isinstance(c, dict) else c
+                for c in state_data.get("citations", [])
-                    for c in state_data.get("citations", [])
+            ]
-                ]
+        if state_data.get("session_id"):
-            if state_data.get("session_id"):
+            self.session_state.session_id = state_data["session_id"]
-                self.session_state.session_id = state_data["session_id"]
+        if "document_filter" in state_data:
-            if "document_filter" in state_data:
+            self.session_state.document_filter = state_data.get("document_filter", [])
-                self.session_state.document_filter = state_data.get(
+        if "citation_registry" in state_data:
-                    "document_filter", []
+            self.session_state.citation_registry = state_data["citation_registry"]
-                )
+        if "initial_context" in state_data:
-            if "citation_registry" in state_data:
+            self.session_state.initial_context = state_data.get("initial_context")
-                self.session_state.citation_registry = state_data["citation_registry"]
-            if "initial_context" in state_data:
-                self.session_state.initial_context = state_data.get("initial_context")
-            # NOTE: session_context is server-managed; we don't accept it from the client
-            # to maintain server-side ownership of conversation summarization
 
 
 @dataclass
@@ -194,3 +191,26 @@ def combine_filters(filter1: str | None, filter2: str | None) -> str | None:
     if len(filters) == 1:
         return filters[0]
     return f"({filters[0]}) AND ({filters[1]})"
+
+
+def emit_state_event(
+    current_state: ChatSessionState,
+    new_state: ChatSessionState,
+    state_key: str | None = None,
+) -> StateDeltaEvent | None:
+    """Emit state delta against current state, or None if no changes."""
+    new_snapshot = new_state.model_dump(mode="json")
+    wrapped_new = {state_key: new_snapshot} if state_key else new_snapshot
+
+    current_snapshot = current_state.model_dump(mode="json")
+    wrapped_current = {state_key: current_snapshot} if state_key else current_snapshot
+
+    patch = jsonpatch.make_patch(wrapped_current, wrapped_new)
+
+    if not patch.patch:
+        return None
+
+    return StateDeltaEvent(
+        type=EventType.STATE_DELTA,
+        delta=patch.patch,
+    )

haiku_rag_slim/haiku/rag/agents/qa/prompts.py

@@ -26,11 +26,7 @@ Each result includes:
 - Type: content type like paragraph, table, code, list_item (when available)
 - Content: the actual text
 
-Citation guidelines:
+In your response, include the chunk IDs you used in cited_chunks.
-- In cited_chunks, include ONLY chunk IDs that directly support your answer.
-- Do NOT cite chunks that are merely related or that you reviewed but did not use.
-- Quality over quantity: fewer relevant citations are better than many marginal ones.
-- Use the EXACT, COMPLETE chunk IDs (full UUIDs).
 
 Guidelines:
 - Base answers strictly on retrieved content - do not use external knowledge

haiku_rag_slim/haiku/rag/agents/research/graph.py

@@ -32,7 +32,6 @@ from haiku.rag.utils import build_prompt, get_model
 def format_context_for_prompt(
     context: ResearchContext,
     include_pending_questions: bool = True,
-    include_citations: bool = False,
 ) -> str:
     """Format the research context as XML for prompts.
 
@@ -40,8 +39,6 @@ def format_context_for_prompt(
         context: The research context to format.
         include_pending_questions: Whether to include pending sub-questions.
             Set to False for synthesis prompts where pending questions aren't relevant.
-        include_citations: Whether to include available citations for selection.
-            Set to True for synthesis prompts where the LLM should select relevant citations.
     """
     context_data: dict[str, object] = {}
 
@@ -64,26 +61,6 @@ def format_context_for_prompt(
             for qa in context.qa_responses
         ]
 
-    if include_citations and context.qa_responses:
-        seen_chunks: set[str] = set()
-        available_citations: list[dict[str, str]] = []
-        for qa in context.qa_responses:
-            for c in qa.citations:
-                if c.chunk_id not in seen_chunks:
-                    seen_chunks.add(c.chunk_id)
-                    content_preview = (
-                        c.content[:500] + "..." if len(c.content) > 500 else c.content
-                    )
-                    available_citations.append(
-                        {
-                            "chunk_id": c.chunk_id,
-                            "document": c.document_title or c.document_uri,
-                            "content": content_preview,
-                        }
-                    )
-        if available_citations:
-            context_data["available_citations"] = available_citations
-
     return format_as_xml(context_data, root_tag="context")
 
 
@@ -110,7 +87,7 @@ async def _plan_step_logic(
         else plan_prompt
     )
 
-    plan_agent: Agent[ResearchDependencies, ResearchPlan] = Agent(  # type: ignore[assignment]
+    plan_agent: Agent[ResearchDependencies, ResearchPlan] = Agent(  # type: ignore[invalid-assignment]
         model=get_model(model_config, config),
         output_type=ResearchPlan,
         instructions=effective_plan_prompt,
@@ -177,7 +154,7 @@ async def _search_one_step_logic(
         deps.semaphore = asyncio.Semaphore(state.max_concurrency)
 
     async with deps.semaphore:
-        agent: Agent[ResearchDependencies, RawSearchAnswer] = Agent(  # type: ignore[assignment]
+        agent: Agent[ResearchDependencies, RawSearchAnswer] = Agent(  # type: ignore[invalid-assignment]
             model=get_model(model_config, config),
             output_type=ToolOutput(RawSearchAnswer, max_retries=3),
             instructions=search_prompt,
@@ -303,7 +280,7 @@ def build_research_graph(
         state = ctx.state
         deps = ctx.deps
 
-        agent: Agent[ResearchDependencies, EvaluationResult] = Agent(  # type: ignore[assignment]
+        agent: Agent[ResearchDependencies, EvaluationResult] = Agent(  # type: ignore[invalid-assignment]
             model=get_model(model_config, config),
             output_type=EvaluationResult,
             instructions=decision_prompt,
@@ -364,7 +341,7 @@ def build_research_graph(
         state = ctx.state
         deps = ctx.deps
 
-        agent: Agent[ResearchDependencies, ResearchReport] = Agent(  # type: ignore[assignment]
+        agent: Agent[ResearchDependencies, ResearchReport] = Agent(  # type: ignore[invalid-assignment]
             model=get_model(model_config, config),
             output_type=ResearchReport,
             instructions=synthesis_prompt,
@@ -373,10 +350,7 @@ def build_research_graph(
             deps_type=ResearchDependencies,
         )
 
-        # Include available citations for the LLM to select from
+        context_xml = format_context_for_prompt(state.context)
-        context_xml = format_context_for_prompt(
-            state.context, include_pending_questions=False, include_citations=True
-        )
         prompt = (
             "Generate a comprehensive research report based on all gathered information.\n\n"
             f"{context_xml}\n\n"
@@ -387,21 +361,7 @@ def build_research_graph(
             context=state.context,
         )
         result = await agent.run(prompt, deps=agent_deps)
-        report = result.output
+        return result.output
-
-        citation_lookup: dict[str, Citation] = {}
-        for qa in state.context.qa_responses:
-            for c in qa.citations:
-                if c.chunk_id not in citation_lookup:
-                    citation_lookup[c.chunk_id] = c
-
-        resolved_citations: list[Citation] = []
-        for chunk_id in report.cited_chunks:
-            if chunk_id in citation_lookup:
-                resolved_citations.append(citation_lookup[chunk_id])
-        report.citations = resolved_citations
-
-        return report
 
     # Build the graph structure
     collect_answers = g.join(
@@ -519,19 +479,17 @@ def build_conversational_graph(
         state = ctx.state
         deps = ctx.deps
 
-        # Use RawSearchAnswer so LLM can select which chunks to cite
+        agent: Agent[ResearchDependencies, ConversationalAnswer] = Agent(  # type: ignore[invalid-assignment]
-        agent: Agent[ResearchDependencies, RawSearchAnswer] = Agent(  # type: ignore[assignment]
             model=get_model(config.research.model, config),
-            output_type=RawSearchAnswer,
+            output_type=ConversationalAnswer,
             instructions=conversational_prompt,
             retries=3,
             output_retries=3,
             deps_type=ResearchDependencies,
         )
 
-        # Include available citations for the LLM to select from
         context_xml = format_context_for_prompt(
-            state.context, include_pending_questions=False, include_citations=True
+            state.context, include_pending_questions=False
         )
         prompt = f"Answer the question based on the gathered evidence.\n\n{context_xml}"
         agent_deps = ResearchDependencies(
@@ -539,23 +497,20 @@ def build_conversational_graph(
             context=state.context,
         )
         result = await agent.run(prompt, deps=agent_deps)
-        raw_answer = result.output
 
-        citation_lookup: dict[str, Citation] = {}
+        # Collect unique citations from qa_responses (dedupe by chunk_id)
+        seen_chunks: set[str] = set()
+        unique_citations: list[Citation] = []
         for qa in state.context.qa_responses:
             for c in qa.citations:
-                if c.chunk_id not in citation_lookup:
+                if c.chunk_id not in seen_chunks:
-                    citation_lookup[c.chunk_id] = c
+                    seen_chunks.add(c.chunk_id)
-
+                    unique_citations.append(c)
-        filtered_citations: list[Citation] = []
-        for chunk_id in raw_answer.cited_chunks:
-            if chunk_id in citation_lookup:
-                filtered_citations.append(citation_lookup[chunk_id])
 
         return ConversationalAnswer(
-            answer=raw_answer.answer,
+            answer=result.output.answer,
-            citations=filtered_citations,
+            citations=unique_citations,
-            confidence=raw_answer.confidence,
+            confidence=result.output.confidence,
         )
 
     # Build the graph structure (simplified: plan → search → synthesize)

haiku_rag_slim/haiku/rag/agents/research/models.py

@@ -163,11 +163,6 @@ class ResearchReport(BaseModel):
     recommendations: list[str] = Field(
         description="Actionable recommendations based on findings", default=[]
     )
-    cited_chunks: list[str] = Field(
+    sources_summary: str = Field(
-        default_factory=list,
+        description="Summary of sources used and their reliability"
-        description="Chunk IDs selected by synthesis as directly supporting the report",
-    )
-    citations: list[Citation] = Field(
-        default_factory=list,
-        description="Resolved citations with full metadata",
     )

haiku_rag_slim/haiku/rag/agents/research/prompts.py

@@ -116,7 +116,6 @@ Goals:
 2. Present findings clearly and concisely.
 3. Draw evidence-based conclusions and recommendations.
 4. State limitations and uncertainties transparently.
-5. Select only the citations that directly support your final answer.
 
 Report guidelines (map to output fields):
 - title: concise (5-12 words), informative.
@@ -128,17 +127,10 @@ Report guidelines (map to output fields):
 - conclusions: list of plain strings, 2-4 bullets following logically from findings.
 - recommendations: list of plain strings, 2-5 actionable bullets tied to findings.
 - limitations: list of plain strings, 1-3 bullets describing constraints or uncertainties.
-- cited_chunks: list of chunk IDs that DIRECTLY support your report.
+- sources_summary: single string listing sources with document paths and page numbers.
 
 All list fields must contain plain strings only, not objects.
 
-Citation selection:
-- Review the <available_citations> section in the context.
-- Include ONLY chunk IDs whose content directly supports specific claims in your report.
-- Do NOT include chunks that are merely related, tangential, or were reviewed but unused.
-- Quality over quantity: fewer relevant citations are better than many marginal ones.
-- Use the EXACT chunk IDs from the available_citations (full UUIDs).
-
 Style:
 - Base all content solely on the collected evidence.
 - Be professional, objective, and specific.
@@ -149,11 +141,9 @@ CONVERSATIONAL_SYNTHESIS_PROMPT = """Generate a direct, conversational answer
 to the question based on the gathered evidence.
 
 Output:
-- query: Echo the original question being answered.
 - answer: Direct, comprehensive answer with a natural, helpful tone.
   Write the actual answer, not a description of what you found.
   Use as many sentences as needed to fully address the question.
-- cited_chunks: List of chunk IDs that DIRECTLY support your answer.
 - confidence: Score from 0.0 to 1.0 indicating answer quality.
 
 Guidelines:
@@ -163,11 +153,4 @@ Guidelines:
 - Use formatting (bullet points, numbered lists) when it improves clarity.
 - Do NOT use meta-commentary like "Based on the research..." or "The evidence shows..."
   Instead, directly state the information.
-- If the evidence is incomplete, acknowledge limitations briefly.
+- If the evidence is incomplete, acknowledge limitations briefly."""
-
-Citation selection:
-- Review the <available_citations> section in the context.
-- Include ONLY chunk IDs whose content directly supports specific statements in your answer.
-- Do NOT include chunks that are merely related, tangential, or were reviewed but unused.
-- Quality over quantity: fewer relevant citations are better than many marginal ones.
-- Use the EXACT chunk IDs from available_citations (full UUIDs)."""

haiku_rag_slim/haiku/rag/app.py

@@ -416,9 +416,10 @@ class HaikuRAGApp:
                         self.console.print("[bold cyan]Key Findings:[/bold cyan]")
                         for finding in report.main_findings:
                             self.console.print(f"• {finding}")
-                    if report.citations:
+                    if report.sources_summary:
-                        for renderable in format_citations_rich(report.citations):
+                        self.console.print()
-                            self.console.print(renderable)
+                        self.console.print("[bold cyan]Sources:[/bold cyan]")
+                        self.console.print(report.sources_summary)
                 else:
                     self.console.print("[yellow]No answer generated.[/yellow]")
             else:
@@ -512,10 +513,10 @@ class HaikuRAGApp:
                     self.console.print(f"• {limitation}")
                 self.console.print()
 
-            # Sources
+            # Sources Summary
-            if report.citations:
+            if report.sources_summary:
-                for renderable in format_citations_rich(report.citations):
+                self.console.print("[bold cyan]Sources:[/bold cyan]")
-                    self.console.print(renderable)
+                self.console.print(report.sources_summary)
 
     async def rebuild(self, mode: RebuildMode = RebuildMode.FULL):
         async with HaikuRAG(

haiku_rag_slim/haiku/rag/chat/app.py

@@ -6,6 +6,7 @@ from datetime import datetime
 from pathlib import Path
 from typing import TYPE_CHECKING, Any
 
+import jsonpatch
 from ag_ui.core import EventType
 from pydantic_ai import (
     Agent,
@@ -99,13 +100,14 @@ class ChatApp(App):
         self.client: HaikuRAG | None = None
         self.config = get_config()
         self.agent: Agent[ChatDeps, str] | None = None
-        self.session_state: ChatSessionState | None = None
+        self.session_state = ChatSessionState()
         self._is_processing = False
         self._tool_call_widgets: dict[str, Any] = {}
         self._last_citations: list[Citation] = []
         self._current_worker: Worker[None] | None = None
         self._message_history: list[ModelMessage] = []
         self._document_filter: list[str] = []
+        self._agui_state_snapshot: dict[str, Any] = {}
 
     def compose(self) -> "ComposeResult":
         """Compose the UI layout."""
@@ -185,20 +187,33 @@ class ChatApp(App):
                 widget = self._tool_call_widgets[tool_call_id]
                 chat_history.mark_tool_complete(widget)
 
-            # Extract citations from StateSnapshotEvent in tool metadata
+            # Extract citations from state events in tool metadata
             result = getattr(event, "result", None)
             metadata = getattr(result, "metadata", None) if result else None
             if metadata:
                 for meta_event in metadata:
-                    if (
+                    if not hasattr(meta_event, "type"):
-                        hasattr(meta_event, "type")
+                        continue
-                        and meta_event.type == EventType.STATE_SNAPSHOT
+
-                    ):
+                    if meta_event.type == EventType.STATE_SNAPSHOT:
                         snapshot = getattr(meta_event, "snapshot", {})
+                        self._agui_state_snapshot = snapshot
                         chat_state = snapshot.get(AGUI_STATE_KEY, snapshot)
-                        self._last_citations = [
+                        citations = chat_state.get("citations", [])
-                            Citation(**c) for c in chat_state["citations"]
+                        self._last_citations = [Citation(**c) for c in citations]
-                        ]
+
+                    elif meta_event.type == EventType.STATE_DELTA:
+                        delta = getattr(meta_event, "delta", [])
+                        if delta:
+                            patch = jsonpatch.JsonPatch(delta)
+                            self._agui_state_snapshot = patch.apply(
+                                self._agui_state_snapshot
+                            )
+                        chat_state = self._agui_state_snapshot.get(
+                            AGUI_STATE_KEY, self._agui_state_snapshot
+                        )
+                        citations = chat_state.get("citations", [])
+                        self._last_citations = [Citation(**c) for c in citations]
 
     async def _event_stream_handler(
         self,
@@ -252,6 +267,12 @@ class ChatApp(App):
         await chat_history.show_thinking()
 
         try:
+            # Initialize AGUI state snapshot from session state for delta application
+            if self.session_state:
+                self._agui_state_snapshot = {
+                    AGUI_STATE_KEY: self.session_state.model_dump(mode="json")
+                }
+
             deps = ChatDeps(
                 client=self.client,
                 config=self.config,
@@ -304,6 +325,7 @@ class ChatApp(App):
         await chat_history.clear_messages()
         self._last_citations.clear()
         self._message_history.clear()
+        self._agui_state_snapshot = {}
         # Reset context lock and session state (reset to CLI value)
         self._context_locked = False
         self.session_state = ChatSessionState(

haiku_rag_slim/pyproject.toml

@@ -24,6 +24,7 @@ classifiers = [
 dependencies = [
     "docling-core==2.60.1",
     "httpx>=0.28.1",
+    "jsonpatch>=1.33",
     "lancedb==0.27.0",
     "pathspec>=1.0.3",
     "pydantic>=2.12.5",

pyproject.toml

@@ -75,7 +75,7 @@ dev = [
     "pydantic-ai-slim[bedrock]",
     "pydantic-ai-slim[google]",
     "pydantic-ai-slim[groq]",
-    "ty>=0.0.12",
+    "ty>=0.0.14",
     "pytest>=9.0.2",
     "pytest-asyncio>=1.3.0",
     "pytest-cov>=7.0.0",

tests/agents/chat/test_chat_agent.py

@@ -1,6 +1,7 @@
 from pathlib import Path
 
 import pytest
+from ag_ui.core import StateDeltaEvent, StateSnapshotEvent
 
 from haiku.rag.agents.chat import (
     AGUI_STATE_KEY,
@@ -10,12 +11,39 @@ from haiku.rag.agents.chat import (
     SearchAgent,
     create_chat_agent,
 )
+from haiku.rag.agents.chat.context import get_cached_session_context
 from haiku.rag.agents.chat.state import MAX_QA_HISTORY
 from haiku.rag.agents.research.models import Citation
 from haiku.rag.client import HaikuRAG
 from haiku.rag.config import Config
 
 
+def extract_state_from_result(result, state_key: str = AGUI_STATE_KEY) -> dict | None:
+    """Extract emitted state from agent result's tool return metadata.
+
+    For deltas, applies the patch to an empty state to get the final state.
+    """
+    import jsonpatch
+
+    for message in result.all_messages():
+        if hasattr(message, "parts"):
+            for part in message.parts:
+                if hasattr(part, "metadata") and part.metadata:
+                    for meta in part.metadata:
+                        if isinstance(meta, StateSnapshotEvent):
+                            return meta.snapshot.get(state_key)
+                        elif isinstance(meta, StateDeltaEvent):
+                            # Apply delta to empty state to get final state
+                            empty_state = {
+                                state_key: ChatSessionState(session_id="").model_dump(
+                                    mode="json"
+                                )
+                            }
+                            patched = jsonpatch.apply_patch(empty_state, meta.delta)
+                            return patched.get(state_key)
+    return None
+
+
 @pytest.fixture(scope="module")
 def vcr_cassette_dir():
     return str(Path(__file__).parent.parent.parent / "cassettes" / "test_chat_agent")
@@ -36,7 +64,9 @@ def test_chat_deps_initialization(temp_db_path):
     assert deps.client is client
     assert deps.config is Config
     assert deps.search_results is None
-    assert deps.session_state is None
+    assert deps.session_state is not None
+    assert deps.session_state.qa_history == []
+    assert deps.session_state.citations == []
 
     client.close()
 
@@ -449,11 +479,10 @@ async def test_chat_agent_ask_adds_citations(allow_model_requests, temp_db_path)
         )
 
         agent = create_chat_agent(Config)
-        session_state = ChatSessionState(session_id="test-citations")
         deps = ChatDeps(
             client=client,
             config=Config,
-            session_state=session_state,
+            state_key=AGUI_STATE_KEY,
         )
 
         # Ask a question that should use the ask tool with citations
@@ -463,8 +492,12 @@ async def test_chat_agent_ask_adds_citations(allow_model_requests, temp_db_path)
         )
 
         assert result.output is not None
+
+        # Extract emitted state from result metadata
+        emitted_state = extract_state_from_result(result)
+        assert emitted_state is not None
         # The qa_history should have been updated with the new Q&A
-        assert len(session_state.qa_history) >= 1
+        assert len(emitted_state.get("qa_history", [])) >= 1
 
 
 @pytest.mark.asyncio
@@ -483,16 +516,12 @@ async def test_chat_agent_ask_triggers_background_summarization(
         )
 
         agent = create_chat_agent(Config)
-        session_state = ChatSessionState(session_id="test-summarization")
         deps = ChatDeps(
             client=client,
             config=Config,
-            session_state=session_state,
+            state_key=AGUI_STATE_KEY,
         )
 
-        # Initially no session_context
-        assert session_state.session_context is None
-
         # Ask a question
         result = await agent.run(
             "What is the highest count class in the DocLayNet dataset?",
@@ -500,19 +529,27 @@ async def test_chat_agent_ask_triggers_background_summarization(
         )
 
         assert result.output is not None
-        assert len(session_state.qa_history) >= 1
+
+        # Extract emitted state to get the session_id
+        emitted_state = extract_state_from_result(result)
+        assert emitted_state is not None
+        session_id = emitted_state.get("session_id")
+        assert session_id is not None
+        assert len(emitted_state.get("qa_history", [])) >= 1
 
         # Wait for background task to complete
-        # The task should update session_state.session_context
+        # The task caches session_context server-side
+        cached_context = None
         for _ in range(50):  # Wait up to 5 seconds
-            if session_state.session_context is not None:
+            cached_context = get_cached_session_context(session_id)
+            if cached_context is not None:
                 break
             await asyncio.sleep(0.1)
 
         # Verify session_context was populated by background task
-        assert session_state.session_context is not None
+        assert cached_context is not None
-        assert session_state.session_context.summary != ""
+        assert cached_context.summary != ""
-        assert session_state.session_context.last_updated is not None
+        assert cached_context.last_updated is not None
 
 
 @pytest.mark.asyncio
@@ -536,52 +573,60 @@ async def test_chat_agent_ask_with_prior_answer_retrieval(
         )
 
         agent = create_chat_agent(Config)
-        session_state = ChatSessionState(session_id="test-prior-answers")
+        deps1 = ChatDeps(
-        deps = ChatDeps(
             client=client,
             config=Config,
-            session_state=session_state,
+            state_key=AGUI_STATE_KEY,
         )
 
         # First ask - establishes qa_history
         result1 = await agent.run(
             "What are the class labels in DocLayNet?",
-            deps=deps,
+            deps=deps1,
         )
         assert result1.output is not None
-        assert len(session_state.qa_history) == 1
+
-        # First question should NOT have embedding yet (set lazily on next ask)
+        # Extract emitted state from first call
-        assert session_state.qa_history[0].question_embedding is None
+        state1 = extract_state_from_result(result1)
+        assert state1 is not None
+        assert len(state1.get("qa_history", [])) == 1
+        session_id = state1.get("session_id")
+        assert session_id is not None
 
         # Wait for background summarization to complete
         for _ in range(50):
-            if session_state.session_context is not None:
+            if get_cached_session_context(session_id) is not None:
                 break
             await asyncio.sleep(0.1)
 
+        # Create new session state from emitted state for second call
+        # (simulating client sending state back to server)
+        session_state2 = ChatSessionState(
+            session_id=session_id,
+            qa_history=[QAResponse(**qa) for qa in state1.get("qa_history", [])],
+            citation_registry=state1.get("citation_registry", {}),
+        )
+        deps2 = ChatDeps(
+            client=client,
+            config=Config,
+            session_state=session_state2,
+            state_key=AGUI_STATE_KEY,
+        )
+
         # Second ask - similar question triggers prior answer retrieval
         # This will embed the first question and compare similarity
         result2 = await agent.run(
             "Tell me about DocLayNet class labels",
-            deps=deps,
+            deps=deps2,
         )
         assert result2.output is not None
-        # qa_history should now have 2 entries
-        assert len(session_state.qa_history) == 2
 
-        # First question should now have embedding (set during second ask's recall check)
+        # The important thing is that prior answer retrieval happened
-        assert session_state.qa_history[0].question_embedding is not None
+        # We can verify this by checking session_state2 was used (embedding added)
+        assert session_state2.qa_history[0].question_embedding is not None
         # Embedding should be a list of floats
-        assert isinstance(session_state.qa_history[0].question_embedding, list)
+        assert isinstance(session_state2.qa_history[0].question_embedding, list)
-        assert len(session_state.qa_history[0].question_embedding) > 0
+        assert len(session_state2.qa_history[0].question_embedding) > 0
-
-        # Verify prior answer was reused without new searches:
-        # Second answer's citations should be subset of first answer's citations
-        first_chunk_ids = {c.chunk_id for c in session_state.qa_history[0].citations}
-        second_chunk_ids = {c.chunk_id for c in session_state.qa_history[1].citations}
-        assert second_chunk_ids <= first_chunk_ids, (
-            "Second answer should reuse prior citations, not perform new searches"
-        )
 
 
 def test_fifo_limit_enforcement():

tests/agents/chat/test_state.py

@@ -1,5 +1,7 @@
 import uuid
 
+from ag_ui.core import StateDeltaEvent
+
 from haiku.rag.agents.chat.state import (
     MAX_QA_HISTORY,
     ChatSessionState,
@@ -144,8 +146,8 @@ def test_chat_deps_state_getter_without_namespace():
     assert state["session_id"] == "test-123"
 
 
-def test_chat_deps_state_getter_returns_none_without_session():
+def test_chat_deps_state_getter_returns_default_state():
-    """Test ChatDeps.state getter returns None when no session_state."""
+    """Test ChatDeps.state getter returns default state when not explicitly set."""
     from unittest.mock import MagicMock
 
     from haiku.rag.agents.chat.state import ChatDeps
@@ -156,10 +158,13 @@ def test_chat_deps_state_getter_returns_none_without_session():
     deps = ChatDeps(
         client=mock_client,
         config=mock_config,
-        session_state=None,
     )
 
-    assert deps.state is None
+    state = deps.state
+    assert state is not None
+    assert "session_id" in state
+    assert state["qa_history"] == []
+    assert state["citations"] == []
 
 
 def test_chat_deps_state_setter_updates_from_namespaced_state():
@@ -221,8 +226,8 @@ def test_chat_deps_state_setter_handles_none():
     assert deps.session_state.session_id == "original"
 
 
-def test_chat_deps_state_setter_without_session_state():
+def test_chat_deps_state_setter_updates_default_state():
-    """Test ChatDeps.state setter does nothing when session_state is None."""
+    """Test ChatDeps.state setter updates the default session_state."""
     from unittest.mock import MagicMock
 
     from haiku.rag.agents.chat.state import ChatDeps
@@ -233,13 +238,15 @@ def test_chat_deps_state_setter_without_session_state():
     deps = ChatDeps(
         client=mock_client,
         config=mock_config,
-        session_state=None,
     )
 
-    # Should not raise even with valid incoming state
+    original_session_id = deps.session_state.session_id
-    deps.state = {"session_id": "test", "qa_history": [], "citations": []}
 
-    assert deps.session_state is None
+    # Update with incoming state
+    deps.state = {"session_id": "updated-123", "qa_history": [], "citations": []}
+
+    assert deps.session_state.session_id == "updated-123"
+    assert deps.session_state.session_id != original_session_id
 
 
 def test_chat_deps_state_setter_with_citation_dicts():
@@ -641,3 +648,88 @@ def test_chat_session_state_model_dump_json_serializes_datetime():
     # datetime should be serialized as ISO string, not datetime object
     assert isinstance(snapshot["session_context"]["last_updated"], str)
     assert snapshot["session_context"]["last_updated"] == "2025-01-27T12:00:00"
+
+
+def test_emit_state_event_returns_none_when_no_changes():
+    """emit_state_event returns None when states are identical."""
+    from haiku.rag.agents.chat.state import emit_state_event
+
+    state = ChatSessionState(session_id="test-123", qa_history=[], citations=[])
+
+    event = emit_state_event(state, state)
+
+    assert event is None
+
+
+def test_emit_state_event_returns_delta_with_changes():
+    """emit_state_event returns StateDeltaEvent with JSON Patch ops for changes."""
+    from ag_ui.core import EventType, StateDeltaEvent
+
+    from haiku.rag.agents.chat.state import emit_state_event
+
+    current_state = ChatSessionState(session_id="test-123", qa_history=[], citations=[])
+    new_state = ChatSessionState(
+        session_id="test-123",
+        qa_history=[QAResponse(question="Q1", answer="A1", confidence=0.9)],
+        citations=[],
+    )
+
+    event = emit_state_event(current_state, new_state)
+
+    assert isinstance(event, StateDeltaEvent)
+    assert event.type == EventType.STATE_DELTA
+    assert len(event.delta) > 0
+    # Delta should contain an "add" operation for the new qa_history entry
+    ops = event.delta
+    qa_history_op = next((op for op in ops if "/qa_history" in op["path"]), None)
+    assert qa_history_op is not None
+
+
+def test_emit_state_event_delta_with_state_key():
+    """emit_state_event wraps delta paths with state_key namespace."""
+    from ag_ui.core import StateDeltaEvent
+
+    from haiku.rag.agents.chat.state import AGUI_STATE_KEY, emit_state_event
+
+    current_state = ChatSessionState(session_id="test-123", qa_history=[])
+    new_state = ChatSessionState(
+        session_id="test-123",
+        qa_history=[QAResponse(question="Q1", answer="A1", confidence=0.9)],
+    )
+
+    event = emit_state_event(current_state, new_state, state_key=AGUI_STATE_KEY)
+
+    assert isinstance(event, StateDeltaEvent)
+    # Paths should be namespaced under state_key
+    for op in event.delta:
+        assert op["path"].startswith(f"/{AGUI_STATE_KEY}")
+
+
+def test_emit_state_event_delta_produces_valid_patch():
+    """emit_state_event delta can be applied to reproduce new state."""
+    import jsonpatch
+
+    from haiku.rag.agents.chat.state import emit_state_event
+
+    current_state = ChatSessionState(
+        session_id="test-123",
+        qa_history=[QAResponse(question="Q1", answer="A1", confidence=0.9)],
+        citations=[],
+    )
+    new_state = ChatSessionState(
+        session_id="test-123",
+        qa_history=[
+            QAResponse(question="Q1", answer="A1", confidence=0.9),
+            QAResponse(question="Q2", answer="A2", confidence=0.8),
+        ],
+        citations=[],
+    )
+
+    event = emit_state_event(current_state, new_state)
+    assert isinstance(event, StateDeltaEvent)
+
+    # Apply patch to current state and verify it produces new state
+    current_snapshot = current_state.model_dump(mode="json")
+    patched = jsonpatch.apply_patch(current_snapshot, event.delta)
+    new_snapshot = new_state.model_dump(mode="json")
+    assert patched == new_snapshot

tests/agents/research/test_research_graph.py

@@ -184,46 +184,3 @@ def test_format_context_for_prompt_with_prior_answers():
     assert "<prior_answers>" in result
     assert "Sub question?" in result
     assert "The answer is here." in result
-
-
-def test_format_context_for_prompt_with_citations():
-    """Test format_context_for_prompt includes available_citations when requested."""
-    from haiku.rag.agents.research.dependencies import ResearchContext
-    from haiku.rag.agents.research.graph import format_context_for_prompt
-    from haiku.rag.agents.research.models import Citation, SearchAnswer
-
-    context = ResearchContext(original_question="Main question?")
-    context.add_qa_response(
-        SearchAnswer(
-            query="Sub question?",
-            answer="The answer is here.",
-            confidence=0.9,
-            cited_chunks=["chunk-123", "chunk-456"],
-            citations=[
-                Citation(
-                    document_id="doc-1",
-                    chunk_id="chunk-123",
-                    document_uri="test://doc1",
-                    document_title="Test Document",
-                    content="This is the chunk content.",
-                ),
-                Citation(
-                    document_id="doc-1",
-                    chunk_id="chunk-456",
-                    document_uri="test://doc1",
-                    document_title="Test Document",
-                    content="More chunk content here.",
-                ),
-            ],
-        )
-    )
-
-    result_without = format_context_for_prompt(context, include_citations=False)
-    assert "<available_citations>" not in result_without
-
-    result_with = format_context_for_prompt(context, include_citations=True)
-    assert "<available_citations>" in result_with
-    assert "chunk-123" in result_with
-    assert "chunk-456" in result_with
-    assert "Test Document" in result_with
-    assert "This is the chunk content." in result_with

tests/chat/test_chat_app.py

@@ -282,6 +282,235 @@ async def test_clear_chat_resets_session(temp_db_path: Path):
             assert app.session_state.session_id != original_session_id
 
 
+@pytest.mark.asyncio
+async def test_handle_stream_event_extracts_citations_from_state_snapshot(
+    temp_db_path: Path,
+):
+    """Test that _handle_stream_event extracts citations from STATE_SNAPSHOT events."""
+    from ag_ui.core import EventType, StateSnapshotEvent
+    from pydantic_ai import FunctionToolResultEvent
+    from pydantic_ai.messages import ToolReturnPart
+
+    from haiku.rag.agents.chat.state import AGUI_STATE_KEY
+    from haiku.rag.chat.app import ChatApp
+
+    mock_client = AsyncMock()
+    mock_client.__aenter__ = AsyncMock(return_value=mock_client)
+    mock_client.__aexit__ = AsyncMock(return_value=None)
+
+    with patch("haiku.rag.chat.app.HaikuRAG", return_value=mock_client):
+        app = ChatApp(temp_db_path, read_only=True)
+
+        async with app.run_test():
+            # Create a STATE_SNAPSHOT event with citations
+            snapshot_event = StateSnapshotEvent(
+                type=EventType.STATE_SNAPSHOT,
+                snapshot={
+                    AGUI_STATE_KEY: {
+                        "session_id": "test",
+                        "citations": [
+                            {
+                                "index": 1,
+                                "document_id": "doc1",
+                                "chunk_id": "chunk1",
+                                "document_uri": "test.pdf",
+                                "document_title": "Test Doc",
+                                "content": "Test content",
+                            }
+                        ],
+                        "qa_history": [],
+                        "citation_registry": {"chunk1": 1},
+                    }
+                },
+            )
+
+            # Create a tool result with the snapshot in metadata
+            tool_return = ToolReturnPart(
+                tool_name="search",
+                content="Found results",
+                tool_call_id="test-call-1",
+                metadata=[snapshot_event],
+            )
+
+            event = FunctionToolResultEvent(result=tool_return)
+
+            # Handle the event
+            await app._handle_stream_event(event)
+
+            # Citations should be extracted
+            assert len(app._last_citations) == 1
+            assert app._last_citations[0].chunk_id == "chunk1"
+
+
+@pytest.mark.asyncio
+async def test_handle_stream_event_extracts_citations_from_state_delta(
+    temp_db_path: Path,
+):
+    """Test that _handle_stream_event extracts citations from STATE_DELTA events.
+
+    This test demonstrates that state deltas need to be applied to extract citations.
+    After the first STATE_SNAPSHOT, subsequent tool calls emit STATE_DELTA events
+    containing JSON Patch operations.
+    """
+    from ag_ui.core import EventType, StateDeltaEvent, StateSnapshotEvent
+    from pydantic_ai import FunctionToolResultEvent
+    from pydantic_ai.messages import ToolReturnPart
+
+    from haiku.rag.agents.chat.state import AGUI_STATE_KEY
+    from haiku.rag.chat.app import ChatApp
+
+    mock_client = AsyncMock()
+    mock_client.__aenter__ = AsyncMock(return_value=mock_client)
+    mock_client.__aexit__ = AsyncMock(return_value=None)
+
+    with patch("haiku.rag.chat.app.HaikuRAG", return_value=mock_client):
+        app = ChatApp(temp_db_path, read_only=True)
+
+        async with app.run_test():
+            # First, handle a STATE_SNAPSHOT to establish initial state
+            initial_snapshot = StateSnapshotEvent(
+                type=EventType.STATE_SNAPSHOT,
+                snapshot={
+                    AGUI_STATE_KEY: {
+                        "session_id": "test",
+                        "citations": [],
+                        "qa_history": [],
+                        "citation_registry": {},
+                    }
+                },
+            )
+            tool_return1 = ToolReturnPart(
+                tool_name="search",
+                content="Initial search",
+                tool_call_id="test-call-1",
+                metadata=[initial_snapshot],
+            )
+            event1 = FunctionToolResultEvent(result=tool_return1)
+            await app._handle_stream_event(event1)
+            assert len(app._last_citations) == 0
+
+            # Now handle a STATE_DELTA event that adds citations
+            delta_event = StateDeltaEvent(
+                type=EventType.STATE_DELTA,
+                delta=[
+                    {
+                        "op": "replace",
+                        "path": f"/{AGUI_STATE_KEY}/citations",
+                        "value": [
+                            {
+                                "index": 1,
+                                "document_id": "doc1",
+                                "chunk_id": "chunk1",
+                                "document_uri": "test.pdf",
+                                "document_title": "Test Doc",
+                                "content": "Test content from delta",
+                            }
+                        ],
+                    },
+                    {
+                        "op": "add",
+                        "path": f"/{AGUI_STATE_KEY}/citation_registry/chunk1",
+                        "value": 1,
+                    },
+                ],
+            )
+            tool_return2 = ToolReturnPart(
+                tool_name="ask",
+                content="Answer with citations",
+                tool_call_id="test-call-2",
+                metadata=[delta_event],
+            )
+            event2 = FunctionToolResultEvent(result=tool_return2)
+
+            # Handle the delta event
+            await app._handle_stream_event(event2)
+
+            # Citations should be extracted from the delta
+            assert len(app._last_citations) == 1
+            assert app._last_citations[0].chunk_id == "chunk1"
+            assert app._last_citations[0].content == "Test content from delta"
+
+
+@pytest.mark.asyncio
+async def test_handle_stream_event_delta_with_preinitialized_state(
+    temp_db_path: Path,
+):
+    """Test delta handling when _agui_state_snapshot is pre-initialized.
+
+    This is the actual TUI scenario: session_state exists from the start,
+    so the agent emits deltas (not snapshots) even on the first tool call.
+    The TUI pre-initializes _agui_state_snapshot from session_state.
+    """
+    from ag_ui.core import EventType, StateDeltaEvent
+    from pydantic_ai import FunctionToolResultEvent
+    from pydantic_ai.messages import ToolReturnPart
+
+    from haiku.rag.agents.chat.state import AGUI_STATE_KEY
+    from haiku.rag.chat.app import ChatApp
+
+    mock_client = AsyncMock()
+    mock_client.__aenter__ = AsyncMock(return_value=mock_client)
+    mock_client.__aexit__ = AsyncMock(return_value=None)
+
+    with patch("haiku.rag.chat.app.HaikuRAG", return_value=mock_client):
+        app = ChatApp(temp_db_path, read_only=True)
+
+        async with app.run_test():
+            # Pre-initialize _agui_state_snapshot (simulating what _run_agent does)
+            app._agui_state_snapshot = {
+                AGUI_STATE_KEY: {
+                    "session_id": "test",
+                    "citations": [],
+                    "qa_history": [],
+                    "citation_registry": {},
+                    "document_filter": [],
+                    "initial_context": None,
+                    "session_context": None,
+                }
+            }
+
+            # Now handle a STATE_DELTA event directly (no prior snapshot event)
+            delta_event = StateDeltaEvent(
+                type=EventType.STATE_DELTA,
+                delta=[
+                    {
+                        "op": "replace",
+                        "path": f"/{AGUI_STATE_KEY}/citations",
+                        "value": [
+                            {
+                                "index": 1,
+                                "document_id": "doc1",
+                                "chunk_id": "chunk1",
+                                "document_uri": "test.pdf",
+                                "document_title": "Test Doc",
+                                "content": "Content from first delta",
+                            }
+                        ],
+                    },
+                    {
+                        "op": "add",
+                        "path": f"/{AGUI_STATE_KEY}/citation_registry/chunk1",
+                        "value": 1,
+                    },
+                ],
+            )
+            tool_return = ToolReturnPart(
+                tool_name="ask",
+                content="Answer with citations",
+                tool_call_id="test-call-1",
+                metadata=[delta_event],
+            )
+            event = FunctionToolResultEvent(result=tool_return)
+
+            # Handle the delta event
+            await app._handle_stream_event(event)
+
+            # Citations should be extracted from the delta
+            assert len(app._last_citations) == 1
+            assert app._last_citations[0].chunk_id == "chunk1"
+            assert app._last_citations[0].content == "Content from first delta"
+
+
 @pytest.mark.asyncio
 async def test_citation_expand_collapse_with_enter(temp_db_path: Path):
     """Test that pressing Enter on a focused citation toggles expand/collapse."""

tests/test_app.py

@@ -349,6 +349,7 @@ async def test_ask_with_deep(app: HaikuRAGApp, monkeypatch):
         executive_summary="Deep research answer",
         main_findings=["Finding 1"],
         conclusions=["Conclusion 1"],
+        sources_summary="Sources",
     )
 
     mock_graph = AsyncMock()
@@ -386,6 +387,7 @@ async def test_ask_with_deep_and_cite(app: HaikuRAGApp, monkeypatch):
         executive_summary="Deep research answer",
         main_findings=["Finding 1"],
         conclusions=["Conclusion 1"],
+        sources_summary="Sources",
     )
 
     mock_graph = AsyncMock()

tests/test_mcp.py

@@ -277,6 +277,7 @@ async def test_mcp_research_question():
             main_findings=["Finding 1"],
             conclusions=["Conclusion 1"],
             recommendations=["Recommendation 1"],
+            sources_summary="Sources used",
         )
 
         with (

uv.lock

@@ -1335,7 +1335,7 @@ dev = [
     { name = "pytest-cov", specifier = ">=7.0.0" },
     { name = "pytest-recording", specifier = ">=0.13.4" },
     { name = "ruff", specifier = ">=0.14.13" },
-    { name = "ty", specifier = ">=0.0.12" },
+    { name = "ty", specifier = ">=0.0.14" },
 ]
 
 [[package]]
@@ -1368,6 +1368,7 @@ source = { editable = "haiku_rag_slim" }
 dependencies = [
     { name = "docling-core" },
     { name = "httpx" },
+    { name = "jsonpatch" },
     { name = "lancedb" },
     { name = "pathspec" },
     { name = "pydantic" },
@@ -1429,6 +1430,7 @@ requires-dist = [
     { name = "docling", marker = "extra == 'docling'", specifier = "==2.69.1" },
     { name = "docling-core", specifier = "==2.60.1" },
     { name = "httpx", specifier = ">=0.28.1" },
+    { name = "jsonpatch", specifier = ">=1.33" },
     { name = "lancedb", specifier = "==0.27.0" },
     { name = "mxbai-rerank", marker = "extra == 'mxbai'", specifier = ">=0.1.6" },
     { name = "opencv-python-headless", marker = "extra == 'docling'", specifier = ">=4.13.0.90" },
@@ -4984,27 +4986,26 @@ wheels = [
 
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