flask_api.py

import os
import io
import json
import tempfile
import pandas as pd
from flask import Flask, request, jsonify, send_file
from flask_cors import CORS
from dotenv import load_dotenv
from groq_llms import LLMHandler

# Load environment variables
load_dotenv()

app = Flask(__name__)
CORS(app)  # Enable CORS for all routes

# Initialize LLM Handler
llm_handler = LLMHandler()


def process_csv(file, user_prompt):
    """
    Process CSV file and generate responses using LLMHandler

    Args:
        file (werkzeug.datastructures.FileStorage): Uploaded CSV file
        user_prompt (str): Prompt for invitation generation

    Returns:
        pandas.DataFrame: DataFrame with generated invitations
    """
    try:
        # Read CSV directly from file storage
        df = pd.read_csv(file)
        responses = []

        for _, row in df.iterrows():
            try:
                response = llm_handler.generate_response(user_prompt, row.to_dict())
                responses.append(response)
            except Exception as e:
                responses.append(f"Error: {e}")

        df["Generated Text"] = responses
        return df
    except Exception as e:
        raise ValueError(f"Error processing CSV: {str(e)}")

@app.route('/generate-questions', methods=['POST'])
def generate_questions():
    """
    Generate questions based on initial context

    Request Payload:
    {
        "context": "Initial context for invitation"
    }

    Returns:
        JSON array of questions
    """
    data = request.json
    context = data.get('context', '')

    try:
        questions = llm_handler.generate_questions(context)
        return jsonify(questions)
    except Exception as e:
        return jsonify({"error": str(e)}), 500


@app.route('/generate-final-prompt', methods=['POST'])
def generate_final_prompt():
    """
    Generate final prompt based on context, questions, and answers

    Request Payload:
    {
        "context": "Initial context",
        "questions": [...],
        "answers": {...}
    }

    Returns:
        Generated final prompt
    """
    data = request.json
    context = data.get('context', '')
    questions = data.get('questions', [])
    answers = data.get('answers', {})

    try:
        final_prompt = llm_handler.generate_final_prompt(context, questions, answers)
        return jsonify({"prompt": final_prompt})
    except Exception as e:
        return jsonify({"error": str(e)}), 500


@app.route('/process-invitations', methods=['POST'])
def process_invitations():
    """
    Process CSV file and generate invitations

    Request Parameters:
    - file: CSV file
    - prompt: Invitation generation prompt

    Returns:
        Processed CSV file with generated invitations
    """
    if 'file' not in request.files:
        return jsonify({"error": "No file uploaded"}), 400

    file = request.files['file']
    user_prompt = request.form.get('prompt', '')

    if file.filename == '':
        return jsonify({"error": "No selected file"}), 400

    try:
        # Process CSV and generate invitations
        processed_df = process_csv(file, user_prompt)

        # Save processed DataFrame to a bytes buffer
        output = io.BytesIO()
        processed_df.to_csv(output, index=False)
        output.seek(0)

        # Return the file
        return send_file(
            output,
            mimetype='text/csv',
            as_attachment=True,
            download_name='generated_invitations.csv'
        )
    except Exception as e:
        return jsonify({"error": str(e)}), 500


if __name__ == '__main__':
    # Configurable port, defaults to 5000
    port = int(os.environ.get('PORT', 5000))
    app.run(host='0.0.0.0', port=port, debug=True)