简单日志示例

这是一段代码片段，可以帮助您处理研究任务的流式日志。

from typing import Dict, Any
import asyncio
from gpt_researcher import GPTResearcher

class CustomLogsHandler:
    """A custom Logs handler class to handle JSON data."""
    def __init__(self):
        self.logs = []  # Initialize logs to store data

    async def send_json(self, data: Dict[str, Any]) -> None:
        """Send JSON data and log it."""
        self.logs.append(data)  # Append data to logs
        print(f"My custom Log: {data}")  # For demonstration, print the log

async def run():
    # Define the necessary parameters with sample values
    
    query = "What happened in the latest burning man floods?"
    report_type = "research_report"  # Type of report to generate
    report_source = "online"  # Could specify source like 'online', 'books', etc.
    tone = "informative"  # Tone of the report ('informative', 'casual', etc.)
    config_path = None  # Path to a config file, if needed
    
    # Initialize researcher with a custom WebSocket
    custom_logs_handler = CustomLogsHandler()

    researcher = GPTResearcher(
        query=query,
        report_type=report_type,
        report_source=report_source,
        tone=tone,
        config_path=config_path,
        websocket=custom_logs_handler
    )

    await researcher.conduct_research()  # Conduct the research
    report = await researcher.write_report()  # Write the research report

    return report

# Run the asynchronous function using asyncio
if __name__ == "__main__":
    asyncio.run(run())

研究过程中的数据将被记录并存储在 CustomLogsHandler 实例中。您可以根据应用程序的需要自定义日志记录行为。

以下是输出示例

{
    "type": "logs",
    "content": "added_source_url",
    "output": "✅ Added source url to research: https://www.npr.org/2023/09/28/1202110410/how-rumors-and-conspiracy-theories-got-in-the-way-of-mauis-fire-recovery\n",
    "metadata": "https://www.npr.org/2023/09/28/1202110410/how-rumors-and-conspiracy-theories-got-in-the-way-of-mauis-fire-recovery"
}

metadata 字段将包含与日志条目相关的任何元数据。让上述脚本运行完成，以获得给定研究任务的完整日志输出。