app.py

import logging
import json
import gradio as gr
from dotenv import load_dotenv
from datetime import datetime
from agents.accountability_agent import AccountabilityAgent
from agents.outline_agent import OutlineAgent
from agents.research_agent import ResearchAgent
from agents.synthesis_agent import SynthesisAgent
from agents.thinking_ladder_agent import ThinkingLadderAgent

logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")

load_dotenv()

outline_agent = OutlineAgent()
research_agent = ResearchAgent()
thinking_ladder_agent = ThinkingLadderAgent()
synthesis_agent = SynthesisAgent()
accountability_agent = AccountabilityAgent()

logs = []

def save_logs_to_json(logs):
    timestamp = datetime.now().strftime("%Y%m%d_%H%M%S")
    filename = f'logs_{timestamp}.json'
    with open(filename, 'w') as f:
        json.dump(logs, f, indent=4)

def main(query: str) -> tuple[str, str, float]:
    log_entry = {}
    
    logging.info(f"Received query: {query}")
    log_entry['query'] = query

    main_title, themes, metrics_a = outline_agent.run(query)
    logging.info(f"OutlineAgent output - Main Title: {main_title}, Themes: {themes}, Metrics: {metrics_a}")
    log_entry['outline_agent'] = {
        'main_title': main_title,
        'themes': themes,
        'metrics': metrics_a
    }
    
    sources, metrics_b = research_agent.run(themes)
    logging.info(f"ResearchAgent output - Sources: {sources}, Metrics: {metrics_b}")
    log_entry['research_agent'] = {
        'sources': sources,
        'metrics': metrics_b
    }

    classified_sources, metrics_c = thinking_ladder_agent.run(themes, sources)
    logging.info(f"ThinkingLadderAgent output - Classified Sources: {classified_sources}, Metrics: {metrics_c}")
    log_entry['thinking_ladder_agent'] = {
        'classified_sources': classified_sources,
        'metrics': metrics_c
    }

    synthesis, metrics_d = synthesis_agent.run(main_title, themes, classified_sources)
    logging.info(f"SynthesisAgent output - Synthesis: {synthesis}, Metrics: {metrics_d}")
    log_entry['synthesis_agent'] = {
        'synthesis': synthesis,
        'metrics': metrics_d
    }

    accountability, metrics_e = accountability_agent.run(query, synthesis)
    logging.info(f"AccountabilityAgent output - Accountability: {accountability}, Metrics: {metrics_e}")
    log_entry['accountability_agent'] = {
        'accountability': accountability,
        'metrics': metrics_e
    }

    cost = sum(list(map(lambda metrics: metrics["cost"], [metrics_a, metrics_b, metrics_c, metrics_d, metrics_e])))
    logging.info(f"Total Cost: {cost}")
    log_entry['total_cost'] = cost
    
    logs.append(log_entry)
    save_logs_to_json(logs)

    return synthesis, accountability, cost


gr.Interface(
    fn=main,
    inputs=gr.Textbox(label="Query:"),
    outputs=[gr.Markdown(label="Generated Synthesis:"), gr.Markdown(label="Accountability:"), gr.Number(label="Cost ($):")],
).launch()