Reuse last request from message history if no user prompt was provided (#1955)

Author: DouweM

pydantic_ai_slim/pydantic_ai/_agent_graph.py

@@ -183,6 +183,16 @@ async def _prepare_messages(
 
         if user_prompt is not None:
             parts.append(_messages.UserPromptPart(user_prompt))
+        elif (
+            len(parts) == 0
+            and message_history
+            and (last_message := message_history[-1])
+            and isinstance(last_message, _messages.ModelRequest)
+        ):
+            # Drop last message that came from history and reuse its parts
+            messages.pop()
+            parts.extend(last_message.parts)
+
         return messages, _messages.ModelRequest(parts, instructions=instructions)
 
     async def _reevaluate_dynamic_prompts(

tests/test_agent.py

@@ -1417,6 +1417,36 @@ async def ret_a(x: str) -> str:
     assert result2.new_messages_json().startswith(b'[{"parts":[{"content":"Hello again",')
 
 
+def test_run_with_history_and_no_user_prompt():
+    messages: list[ModelMessage] = [
+        ModelRequest(parts=[UserPromptPart(content='Hello')], instructions='Original instructions'),
+    ]
+
+    m = TestModel()
+    agent = Agent(m, instructions='New instructions')
+
+    result = agent.run_sync(message_history=messages)
+    assert result.all_messages() == snapshot(
+        [
+            ModelRequest(
+                parts=[
+                    UserPromptPart(
+                        content='Hello',
+                        timestamp=IsDatetime(),
+                    )
+                ],
+                instructions='New instructions',
+            ),
+            ModelResponse(
+                parts=[TextPart(content='success (no tool calls)')],
+                usage=Usage(requests=1, request_tokens=51, response_tokens=4, total_tokens=55),
+                model_name='test',
+                timestamp=IsDatetime(),
+            ),
+        ]
+    )
+
+
 def test_empty_tool_calls():
     def empty(_: list[ModelMessage], _info: AgentInfo) -> ModelResponse:
         return ModelResponse(parts=[])