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fix format

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This commit is contained in:
liuyongbin
2025-12-14 14:03:41 +08:00
parent b18993adf7
commit b1ddd98552
5 changed files with 83 additions and 7 deletions
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1
main.py
View File

@@ -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(

2
phone_agent/actions/handler.py
View File

@@ -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")

8
phone_agent/config/i18n.py
View File

@@ -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",
}

55
phone_agent/model/client.py
View File

@@ -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]:
"""

24
scripts/check_deployment_en.py
View File

@@ -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:")