Add manual opener tool calls to Assistant model and API

- Introduced `manual_opener_tool_calls` field in the Assistant model to support custom tool calls.
- Updated AssistantBase and AssistantUpdate schemas to include the new field.
- Implemented normalization and migration logic for handling manual opener tool calls in the API.
- Enhanced runtime metadata to include manual opener tool calls in responses.
- Updated tests to validate the new functionality and ensure proper handling of tool calls.
- Refactored tool ID normalization to support legacy tool names for backward compatibility.

engine/tests/test_tool_call_flow.py

@@ -282,6 +282,74 @@ async def test_generated_opener_uses_tool_capable_turn_when_tools_available(monk
     assert called.get("user_text") == ""
 
 
+@pytest.mark.asyncio
+async def test_manual_opener_tool_calls_emit_assistant_tool_call(monkeypatch):
+    pipeline, events = _build_pipeline(monkeypatch, [[LLMStreamEvent(type="done")]])
+    pipeline.apply_runtime_overrides(
+        {
+            "generatedOpenerEnabled": False,
+            "greeting": "你好，欢迎来电",
+            "output": {"mode": "text"},
+            "tools": [
+                {
+                    "type": "function",
+                    "executor": "client",
+                    "waitForResponse": False,
+                    "function": {
+                        "name": "text_msg_prompt",
+                        "description": "Show prompt dialog",
+                        "parameters": {"type": "object", "properties": {"msg": {"type": "string"}}},
+                    },
+                }
+            ],
+            "manualOpenerToolCalls": [
+                {"toolName": "text_msg_prompt", "arguments": {"msg": "请先选择业务类型"}}
+            ],
+        }
+    )
+
+    await pipeline.emit_initial_greeting()
+
+    tool_events = [event for event in events if event.get("type") == "assistant.tool_call"]
+    assert len(tool_events) == 1
+    assert tool_events[0].get("tool_name") == "text_msg_prompt"
+    assert tool_events[0].get("arguments") == {"msg": "请先选择业务类型"}
+
+
+@pytest.mark.asyncio
+async def test_manual_opener_legacy_voice_message_prompt_is_normalized(monkeypatch):
+    pipeline, events = _build_pipeline(monkeypatch, [[LLMStreamEvent(type="done")]])
+    pipeline.apply_runtime_overrides(
+        {
+            "generatedOpenerEnabled": False,
+            "greeting": "",
+            "output": {"mode": "text"},
+            "tools": [
+                {
+                    "type": "function",
+                    "executor": "client",
+                    "waitForResponse": False,
+                    "function": {
+                        "name": "voice_message_prompt",
+                        "description": "Speak prompt",
+                        "parameters": {"type": "object", "properties": {"msg": {"type": "string"}}},
+                    },
+                }
+            ],
+            "manualOpenerToolCalls": [
+                {"toolName": "voice_message_prompt", "arguments": {"msg": "您好"}}
+            ],
+        }
+    )
+
+    await pipeline.emit_initial_greeting()
+
+    tool_events = [event for event in events if event.get("type") == "assistant.tool_call"]
+    assert len(tool_events) == 1
+    assert tool_events[0].get("tool_name") == "voice_msg_prompt"
+    assert tool_events[0].get("arguments") == {"msg": "您好"}
+
+
 @pytest.mark.asyncio
 async def test_ws_message_parses_tool_call_results():
     msg = parse_client_message(