Update app.py

app.py

@@ -188,8 +188,8 @@ You are a PDF research agent with a single tool: mcp_test_search(query: string,
 Act iteratively:
   1) Split the user question into 1–4 focused sub-queries. Subqueries should be asked as natural language questions in the english language, not just keywords.
   2) For each sub-query, call mcp_test_search (k=5 by default; increase to up to 10 if you need to go deep).
-  3) You will receive the output of mcp_test_search as a list of indices correspondinf to page numbers. Print them out and stop generating. You will be fed the corresponding pages as images in a follow-up message.
-  3) Stop early when confident; otherwise refine and repeat, up to 4 iterations and 20 searches in total. If info is missing, try to continue searching using new keywords and queries.
+  3) You will receive the output of mcp_test_search as a list of indices corresponding to page numbers. Print them out and stop generating. You will be fed the corresponding pages as images in a follow-up message.
+  3) Stop early when confident; otherwise refine and repeat, running new searches. Up to 4 iterations and 20 searches in total. If info is missing, try to continue searching using new keywords and queries.
 
 Workflow:
   • Use ONLY the provided images for grounding and cite as (p.<page>).
@@ -258,7 +258,7 @@ def stream_agent(question: str,
 
     # Shared mutable state for each round
     round_state: Dict[str, Any] = {
-        "last_search_indices": None,
+        "last_search_indices": [],
         "final_text": "",
         "summary_text": "",
     }
@@ -269,9 +269,9 @@ def stream_agent(question: str,
         """
         nonlocal prev_response_id
 
-        round_state["last_search_indices"] = None
-        round_state["final_text"] = ""
-        round_state["summary_text"] = ""
+        round_state["last_search_indices"] = []
+        # round_state["final_text"] = ""
+        # round_state["summary_text"] = ""
 
         # Build the user content for this round
         parts: List[Dict[str, Any]] = []
@@ -349,7 +349,7 @@ def stream_agent(question: str,
                             tool_result_buffer += str(delta_text)
                             parsed_now = _maybe_parse_indices(tool_result_buffer)
                             if parsed_now:
-                                round_state["last_search_indices"] = parsed_now
+                                round_state["last_search_indices"] += parsed_now
                                 log_lines.append(f"[tool-result] indices={parsed_now}")
                                 yield round_state["final_text"] or " ", round_state["summary_text"] or " ", "\n".join(log_lines[-400:])