修复多次RAG检索溯源覆盖

app.py

@@ -31,6 +31,7 @@ from workflow_registry import WORKFLOW_CONFIG, VALID_ROUTE_FLAGS
 from main_agent import extract_conversation_title
 from workflows.history_manager import filter_image_urls, preprocess_from_request
 from config import set_request_user_config
+from utils.source_citations import merge_rag_source_citations
 from checkpointer_config import (
     CheckpointerManager,
     checkpointer_manager
@@ -473,7 +474,7 @@ async def stream_main_agent_execution(
         agent_task = asyncio.create_task(run_agent())
 
         execution_complete_received = False
-        rag_result = []
+        rag_result = {}
         graph_result = []
         while True:
             try:
@@ -493,16 +494,7 @@ async def stream_main_agent_execution(
                     if title == "知识库搜索工具" and result and isinstance(result, dict):
                         print("===============================", result)
                         rag_result_raw = result.get("sourceCitation", {})
-                        rag_result = {}
+                        merge_rag_source_citations(rag_result, rag_result_raw)
-                        for doc_name, chunks in rag_result_raw.items():
-                            if isinstance(chunks, list):
-                                rag_result[doc_name] = [
-                                    {k: v for k, v in item.items() if k != "text"}
-                                    if isinstance(item, dict) else item
-                                    for item in chunks
-                                ]
-                            else:
-                                rag_result[doc_name] = chunks
                     elif title == "图谱检索工具" and result and isinstance(result, dict):
                         print("===============================", result)
                         graph_result = result.get("xxxx.graph", [])

utils/source_citations.py

@@ -0,0 +1,71 @@
+"""Utilities for accumulating RAG source citations across multiple searches."""
+
+import json
+from typing import Any, Dict
+
+
+def _citation_item_key(item: Any) -> str:
+    """Build a stable identity for one RAG citation chunk."""
+    if not isinstance(item, dict):
+        return json.dumps(item, ensure_ascii=False, sort_keys=True, default=str)
+
+    chunk_id = item.get("id")
+    if chunk_id not in (None, ""):
+        return f"id:{chunk_id}"
+
+    location = {
+        "file_id": item.get("file_id"),
+        "page_idx": item.get("page_idx"),
+        "positions": item.get("positions"),
+    }
+    if any(value not in (None, "", []) for value in location.values()):
+        return "location:" + json.dumps(
+            location, ensure_ascii=False, sort_keys=True, default=str
+        )
+
+    # index/score may differ between rewritten queries and do not identify a source.
+    fallback = {
+        key: value
+        for key, value in item.items()
+        if key not in {"index", "score", "text"}
+    }
+    return "fallback:" + json.dumps(
+        fallback, ensure_ascii=False, sort_keys=True, default=str
+    )
+
+
+def merge_rag_source_citations(
+    accumulated: Dict[str, Any], incoming: Any
+) -> Dict[str, Any]:
+    """
+    Append a RAG call's citations without losing earlier calls or duplicating chunks.
+
+    Citation text is intentionally removed here because the stream response has never
+    exposed it; the full text remains available inside the workflow for answer generation.
+    """
+    if not isinstance(incoming, dict) or not incoming:
+        return accumulated
+
+    for doc_name, chunks in incoming.items():
+        if isinstance(chunks, list):
+            target = accumulated.setdefault(doc_name, [])
+            if not isinstance(target, list):
+                # Be defensive about malformed/legacy data while preserving both values.
+                target = [target]
+                accumulated[doc_name] = target
+
+            seen = {_citation_item_key(item) for item in target}
+            for item in chunks:
+                sanitized_item = (
+                    {key: value for key, value in item.items() if key != "text"}
+                    if isinstance(item, dict)
+                    else item
+                )
+                item_key = _citation_item_key(sanitized_item)
+                if item_key not in seen:
+                    target.append(sanitized_item)
+                    seen.add(item_key)
+        elif doc_name not in accumulated:
+            accumulated[doc_name] = chunks
+
+    return accumulated