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add logging of prefix of tool call and tool response

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hjc-puro
2025-11-07 14:43:44 -05:00
parent 2d8f6c46f1
commit 0c618482c4
2 changed files with 34 additions and 20 deletions
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24
batch_runner.py
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@@ -164,7 +164,8 @@ def _process_single_prompt(
enabled_toolsets=selected_toolsets,
save_trajectories=False, # We handle saving ourselves
verbose_logging=config.get("verbose", False),
ephemeral_system_prompt=config.get("ephemeral_system_prompt")
ephemeral_system_prompt=config.get("ephemeral_system_prompt"),
log_prefix_chars=config.get("log_prefix_chars", 100)
)
# Run the agent with task_id to ensure each task gets its own isolated VM
@@ -323,11 +324,12 @@ class BatchRunner:
model: str = "claude-opus-4-20250514",
num_workers: int = 4,
verbose: bool = False,
ephemeral_system_prompt: str = None
ephemeral_system_prompt: str = None,
log_prefix_chars: int = 100,
):
"""
Initialize the batch runner.
Args:
dataset_file (str): Path to the dataset JSONL file with 'prompt' field
batch_size (int): Number of prompts per batch
@@ -340,6 +342,7 @@ class BatchRunner:
num_workers (int): Number of parallel workers
verbose (bool): Enable verbose logging
ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
"""
self.dataset_file = Path(dataset_file)
self.batch_size = batch_size
@@ -352,6 +355,7 @@ class BatchRunner:
self.num_workers = num_workers
self.verbose = verbose
self.ephemeral_system_prompt = ephemeral_system_prompt
self.log_prefix_chars = log_prefix_chars
# Validate distribution
if not validate_distribution(distribution):
@@ -507,7 +511,8 @@ class BatchRunner:
"base_url": self.base_url,
"api_key": self.api_key,
"verbose": self.verbose,
"ephemeral_system_prompt": self.ephemeral_system_prompt
"ephemeral_system_prompt": self.ephemeral_system_prompt,
"log_prefix_chars": self.log_prefix_chars
}
# Get completed prompts set
@@ -650,11 +655,12 @@ def main(
resume: bool = False,
verbose: bool = False,
list_distributions: bool = False,
ephemeral_system_prompt: str = None
ephemeral_system_prompt: str = None,
log_prefix_chars: int = 100,
):
"""
Run batch processing of agent prompts from a dataset.
Args:
dataset_file (str): Path to JSONL file with 'prompt' field in each entry
batch_size (int): Number of prompts per batch
@@ -669,6 +675,7 @@ def main(
verbose (bool): Enable verbose logging (default: False)
list_distributions (bool): List available toolset distributions and exit
ephemeral_system_prompt (str): System prompt used during agent execution but NOT saved to trajectories (optional)
log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses (default: 20)
Examples:
# Basic usage
@@ -729,9 +736,10 @@ def main(
model=model,
num_workers=num_workers,
verbose=verbose,
ephemeral_system_prompt=ephemeral_system_prompt
ephemeral_system_prompt=ephemeral_system_prompt,
log_prefix_chars=log_prefix_chars
)
runner.run(resume=resume)
except Exception as e: