fix format

main.py

@@ -476,6 +476,7 @@ def main():
         base_url=args.base_url,
         model_name=args.model,
         api_key=args.apikey,
+        lang=args.lang,
     )
 
     agent_config = AgentConfig(

phone_agent/actions/handler.py

@@ -285,7 +285,7 @@ def parse_action(response: str) -> dict[str, Any]:
         if response.startswith("do"):
             # Use AST parsing instead of eval for safety
             try:
-                tree = ast.parse(response, mode='eval')
+                tree = ast.parse(response, mode="eval")
                 if not isinstance(tree.body, ast.Call):
                     raise ValueError("Expected a function call")
 

phone_agent/config/i18n.py

@@ -19,6 +19,10 @@ MESSAGES_ZH = {
     "step": "步骤",
     "task": "任务",
     "result": "结果",
+    "performance_metrics": "性能指标",
+    "time_to_first_token": "首 Token 延迟 (TTFT)",
+    "time_to_thinking_end": "思考完成延迟",
+    "total_inference_time": "总推理时间",
 }
 
 # English messages
@@ -40,6 +44,10 @@ MESSAGES_EN = {
     "step": "Step",
     "task": "Task",
     "result": "Result",
+    "performance_metrics": "Performance Metrics",
+    "time_to_first_token": "Time to First Token (TTFT)",
+    "time_to_thinking_end": "Time to Thinking End",
+    "total_inference_time": "Total Inference Time",
 }
 
 

phone_agent/model/client.py

@@ -1,11 +1,14 @@
 """Model client for AI inference using OpenAI-compatible API."""
 
 import json
+import time
 from dataclasses import dataclass, field
 from typing import Any
 
 from openai import OpenAI
 
+from phone_agent.config.i18n import get_message
+
 
 @dataclass
 class ModelConfig:
@@ -19,6 +22,7 @@ class ModelConfig:
     top_p: float = 0.85
     frequency_penalty: float = 0.2
     extra_body: dict[str, Any] = field(default_factory=dict)
+    lang: str = "cn"  # Language for UI messages: 'cn' or 'en'
 
 
 @dataclass
@@ -28,6 +32,10 @@ class ModelResponse:
     thinking: str
     action: str
     raw_content: str
+    # Performance metrics
+    time_to_first_token: float | None = None  # Time to first token (seconds)
+    time_to_thinking_end: float | None = None  # Time to thinking end (seconds)
+    total_time: float | None = None  # Total inference time (seconds)
 
 
 class ModelClient:
@@ -55,6 +63,11 @@ class ModelClient:
         Raises:
             ValueError: If the response cannot be parsed.
         """
+        # Start timing
+        start_time = time.time()
+        time_to_first_token = None
+        time_to_thinking_end = None
+
         stream = self.client.chat.completions.create(
             messages=messages,
             model=self.config.model_name,
@@ -70,6 +83,7 @@ class ModelClient:
         buffer = ""  # Buffer to hold content that might be part of a marker
         action_markers = ["finish(message=", "do(action="]
         in_action_phase = False  # Track if we've entered the action phase
+        first_token_received = False
 
         for chunk in stream:
             if len(chunk.choices) == 0:
@@ -78,6 +92,11 @@ class ModelClient:
                 content = chunk.choices[0].delta.content
                 raw_content += content
 
+                # Record time to first token
+                if not first_token_received:
+                    time_to_first_token = time.time() - start_time
+                    first_token_received = True
+
                 if in_action_phase:
                     # Already in action phase, just accumulate content without printing
                     continue
@@ -94,6 +113,11 @@ class ModelClient:
                         print()  # Print newline after thinking is complete
                         in_action_phase = True
                         marker_found = True
+
+                        # Record time to thinking end
+                        if time_to_thinking_end is None:
+                            time_to_thinking_end = time.time() - start_time
+
                         break
 
                 if marker_found:
@@ -115,10 +139,39 @@ class ModelClient:
                     print(buffer, end="", flush=True)
                     buffer = ""
 
+        # Calculate total time
+        total_time = time.time() - start_time
+
         # Parse thinking and action from response
         thinking, action = self._parse_response(raw_content)
 
-        return ModelResponse(thinking=thinking, action=action, raw_content=raw_content)
+        # Print performance metrics
+        lang = self.config.lang
+        print()
+        print("=" * 50)
+        print(f"⏱️  {get_message('performance_metrics', lang)}:")
+        print("-" * 50)
+        if time_to_first_token is not None:
+            print(
+                f"{get_message('time_to_first_token', lang)}: {time_to_first_token:.3f}s"
+            )
+        if time_to_thinking_end is not None:
+            print(
+                f"{get_message('time_to_thinking_end', lang)}:        {time_to_thinking_end:.3f}s"
+            )
+        print(
+            f"{get_message('total_inference_time', lang)}:          {total_time:.3f}s"
+        )
+        print("=" * 50)
+
+        return ModelResponse(
+            thinking=thinking,
+            action=action,
+            raw_content=raw_content,
+            time_to_first_token=time_to_first_token,
+            time_to_thinking_end=time_to_thinking_end,
+            total_time=total_time,
+        )
 
     def _parse_response(self, content: str) -> tuple[str, str]:
         """

scripts/check_deployment_en.py

@@ -41,19 +41,31 @@ Usage examples:
     )
 
     parser.add_argument(
-        "--max-tokens", type=int, default=3000, help="Maximum generation tokens (default: 3000)"
+        "--max-tokens",
+        type=int,
+        default=3000,
+        help="Maximum generation tokens (default: 3000)",
     )
 
     parser.add_argument(
-        "--temperature", type=float, default=0.0, help="Sampling temperature (default: 0.0)"
+        "--temperature",
+        type=float,
+        default=0.0,
+        help="Sampling temperature (default: 0.0)",
     )
 
     parser.add_argument(
-        "--top_p", type=float, default=0.85, help="Nucleus sampling parameter (default: 0.85)"
+        "--top_p",
+        type=float,
+        default=0.85,
+        help="Nucleus sampling parameter (default: 0.85)",
     )
 
     parser.add_argument(
-        "--frequency_penalty", type=float, default=0.2, help="Frequency penalty parameter (default: 0.2)"
+        "--frequency_penalty",
+        type=float,
+        default=0.2,
+        help="Frequency penalty parameter (default: 0.2)",
     )
 
     args = parser.parse_args()
@@ -103,7 +115,9 @@ Usage examples:
             print(f"  - Completion tokens: {response.usage.completion_tokens}")
             print(f"  - Total tokens: {response.usage.total_tokens}")
 
-        print(f"\nPlease evaluate the above inference result to determine if the model deployment meets expectations.")
+        print(
+            f"\nPlease evaluate the above inference result to determine if the model deployment meets expectations."
+        )
 
     except Exception as e:
         print(f"\nError occurred while calling API:")