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Add logging for first 100 chars of the tool call args json / tool response #9

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Merged
teknium1 merged 2 commits into from
Nov 15, 2025
Merged

Add logging for first 100 chars of the tool call args json / tool response #9

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2d8f6c4
log first 20 chars
hjc-puro Nov 7, 2025
0c61848
add logging of prefix of tool call and tool response
hjc-puro Nov 7, 2025
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24 changes: 16 additions & 8 deletions batch_runner.py
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Original file line number Diff line number Diff line change
Expand Up @@ -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
Expand Down Expand Up @@ -323,11 +324,12 @@ def __init__(
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
Expand All @@ -340,6 +342,7 @@ def __init__(
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
Expand All @@ -352,6 +355,7 @@ def __init__(
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):
Expand Down Expand Up @@ -507,7 +511,8 @@ def run(self, resume: bool = False):
"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
Expand Down Expand Up @@ -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
Expand All @@ -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
Expand Down Expand Up @@ -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:
Expand Down
37 changes: 24 additions & 13 deletions run_agent.py
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Original file line number Diff line number Diff line change
Expand Up @@ -65,7 +65,8 @@ def __init__(
disabled_toolsets: List[str] = None,
save_trajectories: bool = False,
verbose_logging: bool = False,
ephemeral_system_prompt: str = None
ephemeral_system_prompt: str = None,
log_prefix_chars: int = 100,
):
"""
Initialize the AI Agent.
Expand All @@ -81,13 +82,15 @@ def __init__(
save_trajectories (bool): Whether to save conversation trajectories to JSONL files (default: False)
verbose_logging (bool): Enable verbose logging for debugging (default: False)
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.model = model
self.max_iterations = max_iterations
self.tool_delay = tool_delay
self.save_trajectories = save_trajectories
self.verbose_logging = verbose_logging
self.ephemeral_system_prompt = ephemeral_system_prompt
self.log_prefix_chars = log_prefix_chars

# Store toolset filtering options
self.enabled_toolsets = enabled_toolsets
Expand Down Expand Up @@ -474,7 +477,10 @@ def run_conversation(
print(f"❌ Invalid JSON in tool call arguments: {e}")
function_args = {}

print(f" 📞 Tool {i}: {function_name}({list(function_args.keys())})")
# Preview tool call arguments
args_str = json.dumps(function_args, ensure_ascii=False)
args_preview = args_str[:self.log_prefix_chars] + "..." if len(args_str) > self.log_prefix_chars else args_str
print(f" 📞 Tool {i}: {function_name}({list(function_args.keys())}) - {args_preview}")

tool_start_time = time.time()

Expand All @@ -483,19 +489,21 @@ def run_conversation(

tool_duration = time.time() - tool_start_time
result_preview = function_result[:200] if len(function_result) > 200 else function_result

if self.verbose_logging:
logging.debug(f"Tool {function_name} completed in {tool_duration:.2f}s")
logging.debug(f"Tool result preview: {result_preview}...")

# Add tool result to conversation
messages.append({
"role": "tool",
"content": function_result,
"tool_call_id": tool_call.id
})

print(f" ✅ Tool {i} completed in {tool_duration:.2f}s")

# Preview tool response
response_preview = function_result[:self.log_prefix_chars] + "..." if len(function_result) > self.log_prefix_chars else function_result
print(f" ✅ Tool {i} completed in {tool_duration:.2f}s - {response_preview}")

# Delay between tool calls
if self.tool_delay > 0 and i < len(assistant_message.tool_calls):
Expand Down Expand Up @@ -577,33 +585,35 @@ def chat(self, message: str) -> str:

def main(
query: str = None,
model: str = "claude-opus-4-20250514",
model: str = "claude-opus-4-20250514",
api_key: str = None,
base_url: str = "https://api.anthropic.com/v1/",
max_turns: int = 10,
enabled_toolsets: str = None,
disabled_toolsets: str = None,
list_tools: bool = False,
save_trajectories: bool = False,
verbose: bool = False
verbose: bool = False,
log_prefix_chars: int = 20
):
"""
Main function for running the agent directly.

Args:
query (str): Natural language query for the agent. Defaults to Python 3.13 example.
model (str): Model name to use. Defaults to claude-opus-4-20250514.
api_key (str): API key for authentication. Uses ANTHROPIC_API_KEY env var if not provided.
base_url (str): Base URL for the model API. Defaults to https://api.anthropic.com/v1/
max_turns (int): Maximum number of API call iterations. Defaults to 10.
enabled_toolsets (str): Comma-separated list of toolsets to enable. Supports predefined
toolsets (e.g., "research", "development", "safe").
enabled_toolsets (str): Comma-separated list of toolsets to enable. Supports predefined
toolsets (e.g., "research", "development", "safe").
Multiple toolsets can be combined: "web,vision"
disabled_toolsets (str): Comma-separated list of toolsets to disable (e.g., "terminal")
list_tools (bool): Just list available tools and exit
save_trajectories (bool): Save conversation trajectories to JSONL files. Defaults to False.
verbose (bool): Enable verbose logging for debugging. Defaults to False.

log_prefix_chars (int): Number of characters to show in log previews for tool calls/responses. Defaults to 20.

Toolset Examples:
- "research": Web search, extract, crawl + vision tools
"""
Expand Down Expand Up @@ -720,7 +730,8 @@ def main(
enabled_toolsets=enabled_toolsets_list,
disabled_toolsets=disabled_toolsets_list,
save_trajectories=save_trajectories,
verbose_logging=verbose
verbose_logging=verbose,
log_prefix_chars=log_prefix_chars
)
except RuntimeError as e:
print(f"❌ Failed to initialize agent: {e}")
Expand Down