fix(deep_research): resolve DeepResearchAgent returning None

When DeepResearchTool's inner initiate_chat() calls terminate via tool
execution (confirm_summary, generate_subquestions, confirm_answer), the
default _last_msg_as_summary extracts content from the last
sender->recipient message, which is a tool_call with content=None.
This causes result.summary to return an empty string, making the
DeepResearchAgent return None to the user.

Add _extract_last_result_with_prefix() static method that walks
chat_result.chat_history in reverse to find the actual answer message
by its expected prefix, falling back to result.summary when no match
is found. Replace all 3 bare return result.summary calls with this
helper.

Includes 5 unit tests covering: prefix extraction, multiple matches,
fallback to summary, None content handling, and empty history.

Fixes #1770

Co-authored-by: Copilot <223556219+Copilot@users.noreply.github.com>

Author: Aviral Dua

autogen/tools/experimental/deep_research/deep_research.py

@@ -76,6 +76,22 @@ class DeepResearchTool(Tool):
 
     ANSWER_CONFIRMED_PREFIX = "Answer confirmed:"
 
+    @staticmethod
+    def _extract_last_result_with_prefix(chat_result: Any, prefix: str) -> str:
+        """Extract the last message starting with the given prefix from a ChatResult's history.
+
+        When a chat terminates via a tool call (e.g. confirm_summary), the default
+        ``last_msg`` summary method returns empty because the last sender→recipient
+        message is a tool_call with ``content=None``. This helper walks the chat
+        history in reverse and returns the first message whose content starts with
+        *prefix*, falling back to ``chat_result.summary``.
+        """
+        for msg in reversed(chat_result.chat_history):
+            content = msg.get("content") or ""
+            if isinstance(content, str) and content.startswith(prefix):
+                return content
+        return chat_result.summary
+
     def __init__(
         self,
         llm_config: LLMConfig | dict[str, Any],
@@ -132,8 +148,10 @@ def delegate_research_task(
                 str: The answer to the research task.
             """
 
-            @self.summarizer_agent.register_for_execution()
-            @self.critic_agent.register_for_llm(description="Call this method to confirm the final answer.")
+            @self.summarizer_agent.register_for_execution(silent_override=True)
+            @self.critic_agent.register_for_llm(
+                description="Call this method to confirm the final answer.", silent_override=True
+            )
             def confirm_summary(answer: str, reasoning: str) -> str:
                 return f"{self.ANSWER_CONFIRMED_PREFIX}" + answer + "\nReasoning: " + reasoning
 
@@ -142,10 +160,10 @@ def confirm_summary(answer: str, reasoning: str) -> str:
                 max_web_steps=max_web_steps,
             )
 
-            self.summarizer_agent.register_for_llm(description="Split the question into subquestions and get answers.")(
-                split_question_and_answer_subquestions
-            )
-            self.critic_agent.register_for_execution()(split_question_and_answer_subquestions)
+            self.summarizer_agent.register_for_llm(
+                description="Split the question into subquestions and get answers.", silent_override=True
+            )(split_question_and_answer_subquestions)
+            self.critic_agent.register_for_execution(silent_override=True)(split_question_and_answer_subquestions)
 
             result = self.critic_agent.initiate_chat(
                 self.summarizer_agent,
@@ -154,7 +172,7 @@ def confirm_summary(answer: str, reasoning: str) -> str:
                 clear_history=False,
             )
 
-            return result.summary
+            return DeepResearchTool._extract_last_result_with_prefix(result, self.ANSWER_CONFIRMED_PREFIX)
 
         super().__init__(
             name=delegate_research_task.__name__,
@@ -228,7 +246,7 @@ def split_question_and_answer_subquestions(
                 message="Analyse and gather subqestions for the following question: " + question,
             )
 
-            return result.summary
+            return DeepResearchTool._extract_last_result_with_prefix(result, DeepResearchTool.SUBQUESTIONS_ANSWER_PREFIX)
 
         return split_question_and_answer_subquestions
 
@@ -326,4 +344,4 @@ def confirm_answer(answer: str) -> str:
             message="Please find the answer to this question: " + question,
         )
 
-        return result.summary
+        return DeepResearchTool._extract_last_result_with_prefix(result, DeepResearchTool.ANSWER_CONFIRMED_PREFIX)

test/tools/experimental/deep_research/test_deep_research.py

@@ -8,12 +8,72 @@
 
 from autogen import LLMConfig
 from autogen.agentchat import AssistantAgent
+from autogen.agentchat.chat import ChatResult
 from autogen.import_utils import run_for_optional_imports
 from autogen.tools.dependency_injection import Depends, on
 from autogen.tools.experimental import DeepResearchTool
 from test.credentials import Credentials
 
 
+class TestExtractLastResultWithPrefix:
+    """Unit tests for _extract_last_result_with_prefix (issue #1770)."""
+
+    def test_extracts_answer_from_tool_result_message(self) -> None:
+        """When chat terminates via tool call, the confirmed answer is in the history."""
+        chat_result = ChatResult(
+            chat_history=[
+                {"role": "assistant", "content": "Let me research that."},
+                {"role": "assistant", "content": None, "tool_calls": [{"function": {"name": "confirm_summary"}}]},
+                {"role": "tool", "content": "Answer confirmed: Brussels is the capital of Belgium"},
+            ],
+            summary="",
+        )
+        result = DeepResearchTool._extract_last_result_with_prefix(chat_result, "Answer confirmed:")
+        assert result == "Answer confirmed: Brussels is the capital of Belgium"
+
+    def test_returns_last_match_when_multiple_prefixed_messages(self) -> None:
+        """When multiple messages match the prefix, returns the last one."""
+        chat_result = ChatResult(
+            chat_history=[
+                {"role": "tool", "content": "Answer confirmed: First attempt"},
+                {"role": "assistant", "content": "That needs improvement."},
+                {"role": "tool", "content": "Answer confirmed: Refined answer"},
+            ],
+            summary="",
+        )
+        result = DeepResearchTool._extract_last_result_with_prefix(chat_result, "Answer confirmed:")
+        assert result == "Answer confirmed: Refined answer"
+
+    def test_falls_back_to_summary_when_no_prefix_found(self) -> None:
+        """When no message matches, falls back to chat_result.summary."""
+        chat_result = ChatResult(
+            chat_history=[
+                {"role": "assistant", "content": "Some other message"},
+            ],
+            summary="fallback summary",
+        )
+        result = DeepResearchTool._extract_last_result_with_prefix(chat_result, "Answer confirmed:")
+        assert result == "fallback summary"
+
+    def test_handles_none_content_gracefully(self) -> None:
+        """Messages with content=None (tool calls) should not crash."""
+        chat_result = ChatResult(
+            chat_history=[
+                {"role": "assistant", "content": None},
+                {"role": "assistant"},
+            ],
+            summary="",
+        )
+        result = DeepResearchTool._extract_last_result_with_prefix(chat_result, "Answer confirmed:")
+        assert result == ""
+
+    def test_handles_empty_chat_history(self) -> None:
+        """Empty chat history falls back to summary."""
+        chat_result = ChatResult(chat_history=[], summary="")
+        result = DeepResearchTool._extract_last_result_with_prefix(chat_result, "Answer confirmed:")
+        assert result == ""
+
+
 @run_for_optional_imports(
     ["langchain_openai", "browser_use"],
     "browser-use",