add logging of prefix of tool call and tool response
This commit is contained in:
@@ -164,7 +164,8 @@ def _process_single_prompt(
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enabled_toolsets=selected_toolsets,
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save_trajectories=False, # We handle saving ourselves
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verbose_logging=config.get("verbose", False),
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ephemeral_system_prompt=config.get("ephemeral_system_prompt")
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ephemeral_system_prompt=config.get("ephemeral_system_prompt"),
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log_prefix_chars=config.get("log_prefix_chars", 100)
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)
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# Run the agent with task_id to ensure each task gets its own isolated VM
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@@ -323,11 +324,12 @@ class BatchRunner:
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model: str = "claude-opus-4-20250514",
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num_workers: int = 4,
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verbose: bool = False,
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ephemeral_system_prompt: str = None
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ephemeral_system_prompt: str = None,
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log_prefix_chars: int = 100,
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):
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"""
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Initialize the batch runner.
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Args:
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dataset_file (str): Path to the dataset JSONL file with 'prompt' field
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batch_size (int): Number of prompts per batch
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@@ -340,6 +342,7 @@ class BatchRunner:
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num_workers (int): Number of parallel workers
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verbose (bool): Enable verbose logging
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ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
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log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
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"""
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self.dataset_file = Path(dataset_file)
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self.batch_size = batch_size
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@@ -352,6 +355,7 @@ class BatchRunner:
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self.num_workers = num_workers
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self.verbose = verbose
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self.ephemeral_system_prompt = ephemeral_system_prompt
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self.log_prefix_chars = log_prefix_chars
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# Validate distribution
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if not validate_distribution(distribution):
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@@ -507,7 +511,8 @@ class BatchRunner:
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"base_url": self.base_url,
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"api_key": self.api_key,
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"verbose": self.verbose,
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"ephemeral_system_prompt": self.ephemeral_system_prompt
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"ephemeral_system_prompt": self.ephemeral_system_prompt,
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"log_prefix_chars": self.log_prefix_chars
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}
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# Get completed prompts set
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@@ -650,11 +655,12 @@ def main(
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resume: bool = False,
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verbose: bool = False,
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list_distributions: bool = False,
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ephemeral_system_prompt: str = None
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ephemeral_system_prompt: str = None,
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log_prefix_chars: int = 100,
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):
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"""
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Run batch processing of agent prompts from a dataset.
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Args:
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dataset_file (str): Path to JSONL file with 'prompt' field in each entry
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batch_size (int): Number of prompts per batch
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@@ -669,6 +675,7 @@ def main(
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verbose (bool): Enable verbose logging (default: False)
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list_distributions (bool): List available toolset distributions and exit
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ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
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log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
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Examples:
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# Basic usage
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@@ -729,9 +736,10 @@ def main(
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model=model,
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num_workers=num_workers,
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verbose=verbose,
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ephemeral_system_prompt=ephemeral_system_prompt
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ephemeral_system_prompt=ephemeral_system_prompt,
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log_prefix_chars=log_prefix_chars
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)
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runner.run(resume=resume)
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except Exception as e:
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30
run_agent.py
30
run_agent.py
@@ -65,7 +65,8 @@ class AIAgent:
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disabled_toolsets: List[str] = None,
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save_trajectories: bool = False,
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verbose_logging: bool = False,
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ephemeral_system_prompt: str = None
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ephemeral_system_prompt: str = None,
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log_prefix_chars: int = 100,
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):
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"""
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Initialize the AI Agent.
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@@ -81,6 +82,7 @@ class AIAgent:
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save_trajectories (bool): Whether to save conversation trajectories to JSONL files (default: False)
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verbose_logging (bool): Enable verbose logging for debugging (default: False)
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ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
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log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
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"""
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self.model = model
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self.max_iterations = max_iterations
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@@ -88,6 +90,7 @@ class AIAgent:
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self.save_trajectories = save_trajectories
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self.verbose_logging = verbose_logging
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self.ephemeral_system_prompt = ephemeral_system_prompt
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self.log_prefix_chars = log_prefix_chars
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# Store toolset filtering options
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self.enabled_toolsets = enabled_toolsets
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@@ -474,9 +477,9 @@ class AIAgent:
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print(f"❌ Invalid JSON in tool call arguments: {e}")
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function_args = {}
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# Preview tool call arguments (first 20 chars)
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# Preview tool call arguments
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args_str = json.dumps(function_args, ensure_ascii=False)
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args_preview = args_str[:20] + "..." if len(args_str) > 20 else args_str
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args_preview = args_str[:self.log_prefix_chars] + "..." if len(args_str) > self.log_prefix_chars else args_str
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print(f" 📞 Tool {i}: {function_name}({list(function_args.keys())}) - {args_preview}")
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tool_start_time = time.time()
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@@ -498,8 +501,8 @@ class AIAgent:
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"tool_call_id": tool_call.id
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})
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# Preview tool response (first 20 chars)
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response_preview = function_result[:20] + "..." if len(function_result) > 20 else function_result
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# Preview tool response
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response_preview = function_result[:self.log_prefix_chars] + "..." if len(function_result) > self.log_prefix_chars else function_result
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print(f" ✅ Tool {i} completed in {tool_duration:.2f}s - {response_preview}")
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# Delay between tool calls
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@@ -582,7 +585,7 @@ class AIAgent:
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def main(
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query: str = None,
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model: str = "claude-opus-4-20250514",
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model: str = "claude-opus-4-20250514",
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api_key: str = None,
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base_url: str = "https://api.anthropic.com/v1/",
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max_turns: int = 10,
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@@ -590,25 +593,27 @@ def main(
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disabled_toolsets: str = None,
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list_tools: bool = False,
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save_trajectories: bool = False,
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verbose: bool = False
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verbose: bool = False,
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log_prefix_chars: int = 20
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):
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"""
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Main function for running the agent directly.
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Args:
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query (str): Natural language query for the agent. Defaults to Python 3.13 example.
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model (str): Model name to use. Defaults to claude-opus-4-20250514.
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api_key (str): API key for authentication. Uses ANTHROPIC_API_KEY env var if not provided.
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base_url (str): Base URL for the model API. Defaults to https://api.anthropic.com/v1/
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max_turns (int): Maximum number of API call iterations. Defaults to 10.
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enabled_toolsets (str): Comma-separated list of toolsets to enable. Supports predefined
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toolsets (e.g., "research", "development", "safe").
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enabled_toolsets (str): Comma-separated list of toolsets to enable. Supports predefined
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toolsets (e.g., "research", "development", "safe").
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Multiple toolsets can be combined: "web,vision"
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disabled_toolsets (str): Comma-separated list of toolsets to disable (e.g., "terminal")
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list_tools (bool): Just list available tools and exit
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save_trajectories (bool): Save conversation trajectories to JSONL files. Defaults to False.
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verbose (bool): Enable verbose logging for debugging. Defaults to False.
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log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses. Defaults to 20.
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Toolset Examples:
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- "research": Web search, extract, crawl + vision tools
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"""
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@@ -725,7 +730,8 @@ def main(
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enabled_toolsets=enabled_toolsets_list,
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disabled_toolsets=disabled_toolsets_list,
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save_trajectories=save_trajectories,
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verbose_logging=verbose
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verbose_logging=verbose,
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log_prefix_chars=log_prefix_chars
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)
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except RuntimeError as e:
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print(f"❌ Failed to initialize agent: {e}")
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