View documents, group search results under questions
This commit is contained in:
Yiorgis Gozadinos
parent
cc3d1c7e43
commit
a3e37dce5a
3 changed files with 527 additions and 232 deletions
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@ -21,21 +21,30 @@ class ResearchState(BaseModel):
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phase: str = "idle" # idle|planning|searching|analyzing|evaluating|done
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status: str = "" # Human-readable message
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# Research plan
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plan: list[dict] = [] # [{id, question, status: pending|searching|done}]
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# Research plan with embedded search results
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plan: list[
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dict
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] = [] # [{id, question, status: pending|searching|done, search_results: {type, results: [...]}}]
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current_question_index: int = 0
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# Search results (live updates)
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current_search: dict | None = (
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None # {query, type, results: [{chunk, score, expanded}]}
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)
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# Accumulated findings
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insights: list[dict] = [] # [{summary, confidence, sources}]
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insights: list[
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dict
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] = [] # [{summary, confidence, source_refs: [{chunk_id, document_uri, document_title, chunk_position}]}]
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# Document registry - tracks all referenced documents
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document_registry: dict[
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str, dict
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] = {} # {doc_uri: {title, chunks_referenced: [chunk_id]}}
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# Document viewer state
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current_document: dict | None = None # {uri, title, content, total_chunks}
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# Final output
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confidence: float = 0.0
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final_report: dict | None = None
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final_report: dict | None = (
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None # {title, summary, findings, conclusions, citations: [{document_uri, document_title, chunk_ids}]}
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)
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@dataclass
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@ -69,17 +78,28 @@ You work step-by-step with the user to conduct deep research on complex question
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Your workflow:
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1. When user asks a question, propose a research plan (3-5 sub-questions)
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2. Wait for user approval before proceeding
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3. For each sub-question:
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3. For each sub-question IN ORDER (0, 1, 2, etc.):
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- Announce what you're searching for
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- Execute search and show results with scores
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- Extract insights from the results
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- Execute search_question for that question ID
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- IMMEDIATELY extract insights using extract_insights_from_results with the SAME question ID
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- Ask user if they want to continue to next question
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4. Evaluate overall confidence in your findings
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5. Ask user if confident enough or should search more
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6. Synthesize final report with citations
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6. Synthesize final report with complete citations
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CRITICAL RULES:
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- ALWAYS call search_question BEFORE extract_insights_from_results for each question
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- Process questions in sequence: search Q0 → extract Q0 → search Q1 → extract Q1, etc.
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- NEVER skip ahead to extract insights for a question you haven't searched yet
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Document Viewing:
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- Users can request to view the full content of any cited document
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- When a user asks to "show document X" or "view source Y", use the get_full_document tool
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- Document URIs are tracked automatically as you search
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- The final report includes structured citations linking back to source documents
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Be transparent: always announce what you're doing before you do it.
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Show search scores, explain your reasoning, and involve the user in decisions.
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Show search scores, explain your reasoning, cite your sources, and involve the user in decisions.
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""",
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)
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@ -181,31 +201,56 @@ Return ONLY a JSON array of sub-questions, like: ["Question 1?", "Question 2?",
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else:
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expanded_map = {}
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# Process results
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# Process results and update document registry
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results = []
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for chunk, score in search_results:
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# Update document registry
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doc_uri = chunk.document_uri or "unknown"
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doc_title = chunk.document_title or chunk.document_uri or "Unknown"
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if doc_uri not in ctx.deps.state.document_registry:
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ctx.deps.state.document_registry[doc_uri] = {
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"title": doc_title,
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"chunks_referenced": [],
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}
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if (
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chunk.id
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not in ctx.deps.state.document_registry[doc_uri]["chunks_referenced"]
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):
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ctx.deps.state.document_registry[doc_uri]["chunks_referenced"].append(
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chunk.id
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)
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# Check if this chunk was expanded
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if chunk.id in expanded_map:
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expanded_chunk, _ = expanded_map[chunk.id]
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result_data = {
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"chunk": expanded_chunk.content[:500], # Truncate for display
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"chunk_id": chunk.id,
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"document_uri": doc_uri,
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"document_title": doc_title,
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"chunk_position": chunk.order,
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"full_chunk_content": expanded_chunk.content,
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"score": round(score, 3),
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"source": chunk.document_title or chunk.document_uri or "Unknown",
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"expanded": True,
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}
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else:
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result_data = {
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"chunk": chunk.content[:500], # Truncate for display
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"chunk_id": chunk.id,
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"document_uri": doc_uri,
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"document_title": doc_title,
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"chunk_position": chunk.order,
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"full_chunk_content": chunk.content,
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"score": round(score, 3),
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"source": chunk.document_title or chunk.document_uri or "Unknown",
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"expanded": False,
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}
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results.append(result_data)
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# Update state
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ctx.deps.state.current_search = {
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"query": question,
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# Store search results in the plan item
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plan[question_id]["search_results"] = {
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"type": search_type,
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"results": results,
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}
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@ -218,29 +263,52 @@ Return ONLY a JSON array of sub-questions, like: ["Question 1?", "Question 2?",
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@agent.tool
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async def extract_insights_from_results(
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ctx: RunContext[ResearchDeps],
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question_id: int,
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) -> StateSnapshotEvent:
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"""Extract key insights from current search results."""
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current_search = ctx.deps.state.current_search
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if not current_search:
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raise ValueError("No current search results to analyze")
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"""Extract key insights from search results for a specific question.
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IMPORTANT: You must call search_question for this question_id BEFORE calling this tool.
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This tool requires that search results already exist for the given question.
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Args:
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question_id: ID of the question whose results to analyze
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"""
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plan = ctx.deps.state.plan
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if question_id >= len(plan):
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raise ValueError(f"Question ID {question_id} not found in plan")
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question_item = plan[question_id]
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if "search_results" not in question_item:
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raise ValueError(
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f"No search results found for question ID {question_id}. "
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f"You must call search_question(question_id={question_id}) first before extracting insights."
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)
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search_results = question_item["search_results"]
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# Update state
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ctx.deps.state.phase = "analyzing"
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ctx.deps.state.status = "Extracting insights from results..."
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# Build context from results
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context = "\n\n".join(
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[f"[Source: {r['source']}] {r['chunk']}" for r in current_search["results"]]
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)
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# Build context from results with chunk IDs for reference
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context_parts = []
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for idx, r in enumerate(search_results["results"]):
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context_parts.append(
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f"[Result {idx}] [Source: {r['document_title']}] {r['full_chunk_content']}"
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)
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context = "\n\n".join(context_parts)
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# Use LLM to extract insights
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extract_prompt = f"""Analyze these search results and extract 1-3 key insights that help answer the question: "{current_search["query"]}"
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question_text = question_item["question"]
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extract_prompt = f"""Analyze these search results and extract 1-3 key insights that help answer the question: "{question_text}"
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Search Results:
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{context}
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For each insight, reference which result numbers (0, 1, 2, etc.) support it.
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Return a JSON array of insights with format:
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[{{"summary": "brief insight", "confidence": 0.0-1.0, "sources": ["source1", "source2"]}}]"""
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[{{"summary": "brief insight", "confidence": 0.0-1.0, "result_indices": [0, 1, ...]}}]"""
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response = await ctx.deps.client.ask(extract_prompt)
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@ -248,22 +316,48 @@ Return a JSON array of insights with format:
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import json
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try:
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new_insights = json.loads(response)
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raw_insights = json.loads(response)
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except json.JSONDecodeError:
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# Fallback: create simple insight
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new_insights = [
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# Fallback: create simple insight referencing all results
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raw_insights = [
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{
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"summary": response[:200],
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"confidence": 0.7,
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"sources": [r["source"] for r in current_search["results"][:3]],
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"result_indices": list(
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range(min(3, len(search_results["results"])))
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),
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}
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]
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# Convert result indices to structured source references
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new_insights = []
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for insight in raw_insights:
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result_indices = insight.get("result_indices", [])
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source_refs = []
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for idx in result_indices:
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if 0 <= idx < len(search_results["results"]):
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result = search_results["results"][idx]
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source_refs.append(
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{
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"chunk_id": result["chunk_id"],
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"document_uri": result["document_uri"],
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"document_title": result["document_title"],
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"chunk_position": result["chunk_position"],
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}
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)
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new_insights.append(
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{
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"summary": insight["summary"],
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"confidence": insight.get("confidence", 0.7),
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"source_refs": source_refs,
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}
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)
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# Add to accumulated insights
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ctx.deps.state.insights.extend(new_insights)
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# Clear current search
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ctx.deps.state.current_search = None
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ctx.deps.state.status = f"Extracted {len(new_insights)} insights"
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print("[AGENT] Insights extracted, sending state snapshot")
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@ -336,17 +430,28 @@ Return JSON: {{"confidence": 0.0-1.0, "gaps": ["gap1", "gap2"], "recommendation"
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ctx.deps.state.phase = "synthesizing"
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ctx.deps.state.status = "Generating final report..."
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# Build summary of insights with source information
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insights_summary = []
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for i in insights:
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source_titles = [ref["document_title"] for ref in i.get("source_refs", [])]
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unique_sources = list(
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dict.fromkeys(source_titles)
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) # Preserve order, remove duplicates
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insights_summary.append(
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f"- {i['summary']} (sources: {', '.join(unique_sources[:2])})"
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)
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# Build report prompt
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report_prompt = f"""Generate a comprehensive research report answering: "{ctx.deps.state.question}"
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Based on these insights:
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{chr(10).join([f"- {i['summary']} (sources: {', '.join(i.get('sources', [])[:2])})" for i in insights])}
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{chr(10).join(insights_summary)}
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Create a structured report with:
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- Executive Summary (2-3 sentences)
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- Main Findings (bullet points)
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- Conclusions
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- Sources
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- Sources (list the document titles mentioned above)
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Return JSON with format:
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{{
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@ -371,11 +476,23 @@ Return JSON with format:
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"summary": response[:300],
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"findings": [i["summary"] for i in insights],
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"conclusions": ["See findings above"],
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"sources": list(
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set([s for i in insights for s in i.get("sources", [])])
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),
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"sources": [],
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}
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# Build structured citations from document registry
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citations = []
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for doc_uri, doc_info in ctx.deps.state.document_registry.items():
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citations.append(
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{
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"document_uri": doc_uri,
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"document_title": doc_info["title"],
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"chunk_ids": doc_info["chunks_referenced"],
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}
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)
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# Add citations to report
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report["citations"] = citations
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# Update state
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ctx.deps.state.final_report = report
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ctx.deps.state.phase = "done"
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@ -384,4 +501,54 @@ Return JSON with format:
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return _as_state_snapshot(ctx)
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@agent.tool
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async def get_full_document(
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ctx: RunContext[ResearchDeps],
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document_uri: str,
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) -> StateSnapshotEvent:
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"""Retrieve and display the full content of a document by its URI.
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Args:
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document_uri: The URI identifier of the document to retrieve
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"""
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# Update state
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ctx.deps.state.status = f"Retrieving document: {document_uri}"
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# Get document from haiku.rag
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document = await ctx.deps.client.get_document_by_uri(document_uri)
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if document is None:
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ctx.deps.state.status = f"Document not found: {document_uri}"
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ctx.deps.state.current_document = {
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"uri": document_uri,
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"title": "Not Found",
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"content": f"Document with URI '{document_uri}' was not found in the database.",
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"total_chunks": 0,
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}
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else:
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# Get all chunks for this document to count them
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all_chunks = await ctx.deps.client.search(
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query="", # Empty query to get all chunks
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limit=1000,
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search_type="fts",
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)
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chunks_for_doc = [
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c for c, _ in all_chunks if c.document_uri == document_uri
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]
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ctx.deps.state.current_document = {
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"uri": document.uri or document_uri,
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"title": document.title or "Untitled",
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"content": document.content,
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"total_chunks": len(chunks_for_doc),
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"metadata": document.metadata,
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}
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ctx.deps.state.status = (
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f"Retrieved document: {document.title or document_uri}"
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)
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print(f"[AGENT] Document retrieved: {document_uri}")
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return _as_state_snapshot(ctx)
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return agent
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@ -9,31 +9,55 @@ import { CopilotChat } from "@copilotkit/react-ui";
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import "@copilotkit/react-ui/styles.css";
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import StateDisplay from "./StateDisplay";
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interface SourceRef {
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chunk_id: string;
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document_uri: string;
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document_title: string;
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chunk_position: number;
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}
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interface ResearchState {
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question: string;
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phase: string; // idle|planning|searching|analyzing|evaluating|done
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phase: string;
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status: string;
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plan: Array<{
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id: number;
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question: string;
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status: string; // pending|searching|done
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status: string;
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search_results?: {
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type: string;
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results: Array<{
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chunk: string;
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chunk_id: string;
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document_uri: string;
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document_title: string;
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chunk_position: number;
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full_chunk_content: string;
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score: number;
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expanded: boolean;
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}>;
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};
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}>;
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current_question_index: number;
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current_search: {
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query: string;
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type: string;
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results?: Array<{
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chunk: string;
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score: number;
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source: string;
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expanded: boolean;
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}>;
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} | null;
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insights: Array<{
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summary: string;
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confidence: number;
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sources: string[];
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source_refs: SourceRef[];
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}>;
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document_registry: Record<
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string,
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{
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title: string;
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chunks_referenced: string[];
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}
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>;
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current_document: {
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uri: string;
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title: string;
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content: string;
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total_chunks: number;
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metadata?: Record<string, unknown>;
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} | null;
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confidence: number;
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final_report: {
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title: string;
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@ -41,6 +65,11 @@ interface ResearchState {
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findings: string[];
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conclusions: string[];
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sources: string[];
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citations: Array<{
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document_uri: string;
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document_title: string;
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chunk_ids: string[];
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}>;
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} | null;
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}
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@ -54,8 +83,9 @@ function AgentContent() {
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status: "",
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plan: [],
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current_question_index: 0,
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current_search: null,
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insights: [],
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document_registry: {},
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current_document: null,
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confidence: 0.0,
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final_report: null,
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},
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@ -76,9 +106,7 @@ function AgentContent() {
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phaseMessage = "Planning research...";
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break;
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case "searching":
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phaseMessage = newState.current_search
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? `Searching: ${newState.current_search.query}`
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: "Searching...";
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phaseMessage = "Searching...";
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break;
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case "analyzing":
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phaseMessage = "Extracting insights...";
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@ -2,6 +2,13 @@
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import { useState } from "react";
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interface SourceRef {
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chunk_id: string;
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document_uri: string;
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document_title: string;
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chunk_position: number;
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}
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interface ResearchState {
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question: string;
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phase: string;
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||||
|
|
@ -10,23 +17,40 @@ interface ResearchState {
|
|||
id: number;
|
||||
question: string;
|
||||
status: string;
|
||||
search_results?: {
|
||||
type: string;
|
||||
results: Array<{
|
||||
chunk: string;
|
||||
chunk_id: string;
|
||||
document_uri: string;
|
||||
document_title: string;
|
||||
chunk_position: number;
|
||||
full_chunk_content: string;
|
||||
score: number;
|
||||
expanded: boolean;
|
||||
}>;
|
||||
};
|
||||
}>;
|
||||
current_question_index: number;
|
||||
current_search: {
|
||||
query: string;
|
||||
type: string;
|
||||
results?: Array<{
|
||||
chunk: string;
|
||||
score: number;
|
||||
source: string;
|
||||
expanded: boolean;
|
||||
}>;
|
||||
} | null;
|
||||
insights: Array<{
|
||||
summary: string;
|
||||
confidence: number;
|
||||
sources: string[];
|
||||
source_refs: SourceRef[];
|
||||
}>;
|
||||
document_registry: Record<
|
||||
string,
|
||||
{
|
||||
title: string;
|
||||
chunks_referenced: string[];
|
||||
}
|
||||
>;
|
||||
current_document: {
|
||||
uri: string;
|
||||
title: string;
|
||||
content: string;
|
||||
total_chunks: number;
|
||||
metadata?: Record<string, unknown>;
|
||||
} | null;
|
||||
confidence: number;
|
||||
final_report: {
|
||||
title: string;
|
||||
|
|
@ -34,6 +58,11 @@ interface ResearchState {
|
|||
findings: string[];
|
||||
conclusions: string[];
|
||||
sources: string[];
|
||||
citations: Array<{
|
||||
document_uri: string;
|
||||
document_title: string;
|
||||
chunk_ids: string[];
|
||||
}>;
|
||||
} | null;
|
||||
}
|
||||
|
||||
|
|
@ -46,11 +75,15 @@ export default function StateDisplay({ state }: StateDisplayProps) {
|
|||
Record<string, boolean>
|
||||
>({
|
||||
plan: true,
|
||||
search: true,
|
||||
insights: true,
|
||||
report: true,
|
||||
document: true,
|
||||
});
|
||||
|
||||
const [expandedQuestions, setExpandedQuestions] = useState<
|
||||
Record<number, boolean>
|
||||
>({});
|
||||
|
||||
const toggleSection = (section: string) => {
|
||||
setExpandedSections((prev) => ({
|
||||
...prev,
|
||||
|
|
@ -58,6 +91,13 @@ export default function StateDisplay({ state }: StateDisplayProps) {
|
|||
}));
|
||||
};
|
||||
|
||||
const toggleQuestion = (questionId: number) => {
|
||||
setExpandedQuestions((prev) => ({
|
||||
...prev,
|
||||
[questionId]: !prev[questionId],
|
||||
}));
|
||||
};
|
||||
|
||||
// Phase indicator
|
||||
const phases = [
|
||||
"idle",
|
||||
|
|
@ -271,174 +311,170 @@ export default function StateDisplay({ state }: StateDisplayProps) {
|
|||
<div
|
||||
key={item.id}
|
||||
style={{
|
||||
padding: "0.75rem",
|
||||
marginBottom: "0.5rem",
|
||||
background: "white",
|
||||
borderRadius: "4px",
|
||||
marginBottom: "0.5rem",
|
||||
border: "1px solid #e2e8f0",
|
||||
display: "flex",
|
||||
gap: "0.75rem",
|
||||
overflow: "hidden",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => toggleQuestion(item.id)}
|
||||
style={{
|
||||
fontSize: "1.25rem",
|
||||
color:
|
||||
item.status === "done"
|
||||
? "#48bb78"
|
||||
: item.status === "searching"
|
||||
? "#4299e1"
|
||||
: "#a0aec0",
|
||||
width: "100%",
|
||||
display: "flex",
|
||||
gap: "0.75rem",
|
||||
padding: "0.75rem",
|
||||
background: "white",
|
||||
border: "none",
|
||||
cursor: "pointer",
|
||||
textAlign: "left",
|
||||
alignItems: "center",
|
||||
}}
|
||||
>
|
||||
{item.status === "done"
|
||||
? "✓"
|
||||
: item.status === "searching"
|
||||
? "🔍"
|
||||
: "⏳"}
|
||||
</div>
|
||||
<div style={{ flex: 1 }}>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
color: "#4a5568",
|
||||
fontSize: "1.25rem",
|
||||
color:
|
||||
item.status === "done"
|
||||
? "#48bb78"
|
||||
: item.status === "searching"
|
||||
? "#4299e1"
|
||||
: "#a0aec0",
|
||||
flexShrink: 0,
|
||||
}}
|
||||
>
|
||||
{item.question}
|
||||
{item.status === "done"
|
||||
? "✓"
|
||||
: item.status === "searching"
|
||||
? "🔍"
|
||||
: "⏳"}
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
|
||||
{/* Current Search Results */}
|
||||
{state.current_search && (
|
||||
<div
|
||||
style={{
|
||||
background: "white",
|
||||
borderRadius: "8px",
|
||||
boxShadow: "0 1px 3px rgba(0,0,0,0.1)",
|
||||
overflow: "hidden",
|
||||
}}
|
||||
>
|
||||
<button
|
||||
type="button"
|
||||
onClick={() => toggleSection("search")}
|
||||
style={{
|
||||
width: "100%",
|
||||
display: "flex",
|
||||
justifyContent: "space-between",
|
||||
alignItems: "center",
|
||||
padding: "0.75rem",
|
||||
background: "#edf2f7",
|
||||
border: "1px solid #e2e8f0",
|
||||
borderRadius: "4px",
|
||||
cursor: "pointer",
|
||||
fontSize: "1rem",
|
||||
fontWeight: "600",
|
||||
color: "#2d3748",
|
||||
}}
|
||||
>
|
||||
<span>
|
||||
Search Results: {state.current_search.query.substring(0, 50)}...
|
||||
</span>
|
||||
<span>{expandedSections.search ? "▼" : "▶"}</span>
|
||||
</button>
|
||||
{expandedSections.search && (
|
||||
<div
|
||||
style={{
|
||||
padding: "1rem",
|
||||
background: "#f7fafc",
|
||||
border: "1px solid #e2e8f0",
|
||||
borderTop: "none",
|
||||
borderRadius: "0 0 4px 4px",
|
||||
}}
|
||||
>
|
||||
{state.current_search.results && (
|
||||
<div>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
color: "#718096",
|
||||
marginBottom: "0.5rem",
|
||||
}}
|
||||
>
|
||||
Type: {state.current_search.type} |{" "}
|
||||
{state.current_search.results.length} results
|
||||
</div>
|
||||
{state.current_search.results.map((result, idx) => (
|
||||
<div
|
||||
key={`${result.source}-${idx}`}
|
||||
style={{
|
||||
padding: "0.75rem",
|
||||
background: "white",
|
||||
borderRadius: "4px",
|
||||
marginBottom: "0.5rem",
|
||||
border: "1px solid #e2e8f0",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
display: "flex",
|
||||
justifyContent: "space-between",
|
||||
marginBottom: "0.5rem",
|
||||
}}
|
||||
>
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
fontWeight: "600",
|
||||
color: "#4a5568",
|
||||
}}
|
||||
>
|
||||
{result.source}
|
||||
</span>
|
||||
<div style={{ display: "flex", gap: "0.5rem" }}>
|
||||
{result.expanded && (
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
padding: "0.125rem 0.5rem",
|
||||
background: "#bee3f8",
|
||||
color: "#2c5282",
|
||||
borderRadius: "4px",
|
||||
}}
|
||||
>
|
||||
Expanded
|
||||
</span>
|
||||
)}
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
fontWeight: "bold",
|
||||
color:
|
||||
result.score > 0.8
|
||||
? "#48bb78"
|
||||
: result.score > 0.6
|
||||
? "#ed8936"
|
||||
: "#a0aec0",
|
||||
}}
|
||||
>
|
||||
{result.score.toFixed(2)}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<div style={{ flex: 1 }}>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
color: "#718096",
|
||||
lineHeight: "1.4",
|
||||
color: "#4a5568",
|
||||
}}
|
||||
>
|
||||
{result.chunk}...
|
||||
{item.question}
|
||||
</div>
|
||||
{item.search_results && (
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
color: "#718096",
|
||||
marginTop: "0.25rem",
|
||||
}}
|
||||
>
|
||||
{item.search_results.results.length} results
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
{item.search_results && (
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
color: "#718096",
|
||||
}}
|
||||
>
|
||||
{expandedQuestions[item.id] ? "▼" : "▶"}
|
||||
</span>
|
||||
)}
|
||||
</button>
|
||||
|
||||
{/* Search Results nested inside question */}
|
||||
{expandedQuestions[item.id] && item.search_results && (
|
||||
<div
|
||||
style={{
|
||||
padding: "1rem",
|
||||
background: "#f7fafc",
|
||||
borderTop: "1px solid #e2e8f0",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
color: "#718096",
|
||||
marginBottom: "0.5rem",
|
||||
fontWeight: "600",
|
||||
}}
|
||||
>
|
||||
Search Type: {item.search_results.type}
|
||||
</div>
|
||||
{item.search_results.results.map((result, idx) => (
|
||||
<div
|
||||
key={`${result.chunk_id}-${idx}`}
|
||||
style={{
|
||||
padding: "0.75rem",
|
||||
background: "white",
|
||||
borderRadius: "4px",
|
||||
marginBottom: "0.5rem",
|
||||
border: "1px solid #e2e8f0",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
display: "flex",
|
||||
justifyContent: "space-between",
|
||||
marginBottom: "0.5rem",
|
||||
}}
|
||||
>
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
fontWeight: "600",
|
||||
color: "#2d3748",
|
||||
}}
|
||||
>
|
||||
{result.document_title}
|
||||
</span>
|
||||
<div style={{ display: "flex", gap: "0.5rem" }}>
|
||||
{result.expanded && (
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
padding: "0.125rem 0.5rem",
|
||||
background: "#bee3f8",
|
||||
color: "#2c5282",
|
||||
borderRadius: "4px",
|
||||
}}
|
||||
>
|
||||
Expanded
|
||||
</span>
|
||||
)}
|
||||
<span
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
fontWeight: "bold",
|
||||
color:
|
||||
result.score > 0.8
|
||||
? "#48bb78"
|
||||
: result.score > 0.6
|
||||
? "#ed8936"
|
||||
: "#a0aec0",
|
||||
}}
|
||||
>
|
||||
{result.score.toFixed(2)}
|
||||
</span>
|
||||
</div>
|
||||
</div>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
color: "#718096",
|
||||
lineHeight: "1.4",
|
||||
}}
|
||||
>
|
||||
{result.chunk}...
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
)}
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
|
|
@ -520,7 +556,7 @@ export default function StateDisplay({ state }: StateDisplayProps) {
|
|||
color: "#718096",
|
||||
}}
|
||||
>
|
||||
{insight.sources.length} sources
|
||||
{insight.source_refs?.length || 0} sources
|
||||
</span>
|
||||
</div>
|
||||
<div
|
||||
|
|
@ -528,10 +564,30 @@ export default function StateDisplay({ state }: StateDisplayProps) {
|
|||
fontSize: "0.875rem",
|
||||
color: "#2d3748",
|
||||
lineHeight: "1.5",
|
||||
marginBottom: "0.5rem",
|
||||
}}
|
||||
>
|
||||
{insight.summary}
|
||||
</div>
|
||||
{insight.source_refs && insight.source_refs.length > 0 && (
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
color: "#718096",
|
||||
marginTop: "0.5rem",
|
||||
}}
|
||||
>
|
||||
<span style={{ fontWeight: "600" }}>Sources: </span>
|
||||
{insight.source_refs.map((ref, refIdx) => (
|
||||
<span key={ref.chunk_id}>
|
||||
{refIdx > 0 && ", "}
|
||||
<span style={{ fontSize: "0.75rem" }}>
|
||||
{ref.document_title}
|
||||
</span>
|
||||
</span>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
|
|
@ -672,21 +728,65 @@ export default function StateDisplay({ state }: StateDisplayProps) {
|
|||
marginBottom: "0.5rem",
|
||||
}}
|
||||
>
|
||||
Sources
|
||||
Citations
|
||||
</h4>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
color: "#718096",
|
||||
lineHeight: "1.4",
|
||||
}}
|
||||
>
|
||||
{state.final_report.sources.map((source) => (
|
||||
<div key={source} style={{ marginBottom: "0.25rem" }}>
|
||||
{source}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
{state.final_report.citations &&
|
||||
state.final_report.citations.length > 0 ? (
|
||||
<div
|
||||
style={{
|
||||
display: "flex",
|
||||
flexDirection: "column",
|
||||
gap: "0.5rem",
|
||||
}}
|
||||
>
|
||||
{state.final_report.citations.map((citation) => (
|
||||
<div
|
||||
key={citation.document_uri}
|
||||
style={{
|
||||
padding: "0.5rem",
|
||||
background: "#f7fafc",
|
||||
borderRadius: "4px",
|
||||
border: "1px solid #e2e8f0",
|
||||
}}
|
||||
>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.875rem",
|
||||
fontWeight: "600",
|
||||
color: "#2d3748",
|
||||
marginBottom: "0.25rem",
|
||||
}}
|
||||
>
|
||||
{citation.document_title}
|
||||
</div>
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
color: "#718096",
|
||||
}}
|
||||
>
|
||||
{citation.chunk_ids.length} chunk
|
||||
{citation.chunk_ids.length !== 1 ? "s" : ""}{" "}
|
||||
referenced
|
||||
</div>
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
) : (
|
||||
<div
|
||||
style={{
|
||||
fontSize: "0.75rem",
|
||||
color: "#718096",
|
||||
lineHeight: "1.4",
|
||||
}}
|
||||
>
|
||||
{state.final_report.sources?.map((source) => (
|
||||
<div key={source} style={{ marginBottom: "0.25rem" }}>
|
||||
{source}
|
||||
</div>
|
||||
))}
|
||||
</div>
|
||||
)}
|
||||
</div>
|
||||
</div>
|
||||
)}
|
||||
|
|
|
|||
Loading…
Reference in a new issue