๐ง Claude AI for Business AutomationMay 22, 2026โ
Tests passing
Claude Conversation Logger
This tool facilitates structured logging of interactions with Claude AI, allowing developers to record and analyze conversations for business insights. It supports tagging messages by category (e.g., 'marketing', 'customer support') and exporting logs as CSV or JSON. This is particularly useful for monitoring AI-driven processes and auditing business automation reliability.
What It Does
- Real-time logging: Logs interactions with Claude AI in real-time.
- Tagging and categorization: Add tags or categories to each interaction for better organization.
- Export options: Save logs in CSV or JSON format for further analysis.
Installation
1. Clone the repository or download the script.
2. Install the required dependencies:
pip install -r requirements.txtUsage
Run the script using the following command:
python claude_conversation_logger.py --prompt "Your prompt here" --tag "category" --export "logs.csv" --format "csv" --api_key "your_openai_api_key"Example
python claude_conversation_logger.py --prompt "What is the weather today?" --tag "weather" --export "weather_logs.json" --format "json" --api_key "your_openai_api_key"Source Code
import argparse
import json
import csv
import os
from datetime import datetime
import pandas as pd
from openai import ChatCompletion
class ClaudeConversationLogger:
def __init__(self, api_key):
self.api_key = api_key
self.logs = []
def log_interaction(self, prompt, response, tags):
timestamp = datetime.now().isoformat()
self.logs.append({
"timestamp": timestamp,
"prompt": prompt,
"response": response,
"tags": tags
})
def export_logs(self, file_path, file_format):
if file_format == "csv":
df = pd.DataFrame(self.logs)
df.to_csv(file_path, index=False)
elif file_format == "json":
with open(file_path, "w") as f:
json.dump(self.logs, f, indent=4)
else:
raise ValueError("Unsupported file format. Use 'csv' or 'json'.")
def interact_with_claude(self, prompt):
try:
response = ChatCompletion.create(
model="claude-v1",
messages=[{"role": "user", "content": prompt}]
)
return response.choices[0].message["content"]
except Exception as e:
raise RuntimeError(f"Error interacting with Claude: {e}")
def main():
parser = argparse.ArgumentParser(description="Claude Conversation Logger")
parser.add_argument("--prompt", required=True, help="Prompt to send to Claude")
parser.add_argument("--tag", required=True, help="Tag or category for the interaction")
parser.add_argument("--export", required=True, help="File path to export logs (CSV or JSON)")
parser.add_argument("--format", choices=["csv", "json"], required=True, help="Export file format")
parser.add_argument("--api_key", required=True, help="OpenAI API key")
args = parser.parse_args()
logger = ClaudeConversationLogger(api_key=args.api_key)
try:
response = logger.interact_with_claude(args.prompt)
logger.log_interaction(args.prompt, response, args.tag)
logger.export_logs(args.export, args.format)
print(f"Logs successfully exported to {args.export}")
except Exception as e:
print(f"Error: {e}")
if __name__ == "__main__":
main()Community
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Details
- Tool Name
- claude_conversation_logger
- Category
- Claude AI for Business Automation
- Generated
- May 22, 2026
- Tests
- Passing โ
Quick Install
Clone just this tool:
git clone --depth 1 --filter=blob:none --sparse \ https://github.com/ptulin/autoaiforge.git cd autoaiforge git sparse-checkout set generated_tools/2026-05-22/claude_conversation_logger cd generated_tools/2026-05-22/claude_conversation_logger pip install -r requirements.txt 2>/dev/null || true python claude_conversation_logger.py