app.py

from flask import Flask, request, jsonify
from flask_cors import CORS
import requests
from bs4 import BeautifulSoup
import os

app = Flask(__name__)
CORS(app)

# Gemini API key
GEMINI_API_KEY = "AIzaSyA7xnPR4Mv27-E-bBhiJmY4l4my_KlpuwY"  # Replace with your real API key
if not GEMINI_API_KEY:
    raise ValueError("GEMINI_API_KEY not set")

GEMINI_ENDPOINT = f"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.0-flash:generateContent?key={GEMINI_API_KEY}"

# Fixed URLs to scrape
FIXED_URLS = [
    "https://www.bou.ac.bd/",
    "https://bousst.edu.bd/"
]

def scrape_sites():
    all_text = ""
    headers = {
        "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 Chrome/91.0 Safari/537.36"
    }
    for url in FIXED_URLS:
        try:
            response = requests.get(url, headers=headers, timeout=10)
            soup = BeautifulSoup(response.text, 'html.parser')
            text = soup.get_text(separator=' ')
            all_text += text + "\n\n"
        except Exception as e:
            print(f"Error scraping {url}: {e}")
    return all_text[:3000]  # limit to 3000 chars

def ask_gemini(context, question):
    try:
        prompt = f"Context: {context}\n\nQuestion: {question}"
        payload = {
            "contents": [
                {
                    "parts": [
                        {"text": prompt}
                    ]
                }
            ]
        }

        response = requests.post(
            GEMINI_ENDPOINT,
            headers={"Content-Type": "application/json"},
            json=payload,
            timeout=15
        )
        response.raise_for_status()
        data = response.json()

        return data['candidates'][0]['content']['parts'][0]['text'].strip()

    except Exception as e:
        return f"Gemini API error: {str(e)}"

@app.route("/ask", methods=["POST"])
def ask():
    data = request.get_json()
    question = data.get("question", "").strip()
    if not question:
        return jsonify({"answer": "Please provide a question."})

    context = scrape_sites()
    answer = ask_gemini(context, question)
    return jsonify({"answer": answer})

if __name__ == '__main__':
    app.run(debug=True)

















# from flask import Flask, request, jsonify
# from flask_cors import CORS
# import requests
# from bs4 import BeautifulSoup
# from openai import OpenAI  # DeepSeek-compatible client

# app = Flask(__name__)
# CORS(app)

# # DeepSeek API key
# DEEPSEEK_API_KEY = "sk-9875cb19f5a54d49a59bc8db8cece52d"  # Replace with your actual key
# if not DEEPSEEK_API_KEY:
#     raise ValueError("DEEPSEEK_API_KEY not set")

# # Initialize DeepSeek-compatible client
# client = OpenAI(
#     api_key=DEEPSEEK_API_KEY,
#     base_url="https://api.deepseek.com"
# )

# # Fixed URLs to scrape
# FIXED_URLS = [
#     "https://www.bou.ac.bd/",
#     "https://bousst.edu.bd/"
# ]

# def scrape_sites():
#     all_text = ""
#     headers = {
#         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 Chrome/91.0 Safari/537.36"
#     }
#     for url in FIXED_URLS:
#         try:
#             response = requests.get(url, headers=headers, timeout=10)
#             soup = BeautifulSoup(response.text, 'html.parser')
#             text = soup.get_text(separator=' ')
#             all_text += text + "\n\n"
#         except Exception as e:
#             print(f"Error scraping {url}: {e}")
#     return all_text[:3000]  # limit to 3000 chars


# def ask_deepseek(context, question):
#     try:
#         messages = [
#             {"role": "system", "content": "You are a helpful assistant that answers questions based on the given context."},
#             {"role": "user", "content": f"Context: {context}\n\nQuestion: {question}"}
#         ]

#         response = client.chat.completions.create(
#             model="deepseek-chat",
#             messages=messages,
#             max_tokens=300,
#             temperature=0.7,
#         )

#         answer = response.choices[0].message.content.strip()
#         return answer

#     except Exception as e:
#         return f"DeepSeek API error: {str(e)}"


# @app.route("/ask", methods=["POST"])
# def ask():
#     data = request.get_json()
#     question = data.get("question", "").strip()
#     if not question:
#         return jsonify({"answer": "Please provide a question."})

#     context = scrape_sites()
#     answer = ask_deepseek(context, question)
#     return jsonify({"answer": answer})


# if __name__ == '__main__':
#     app.run(debug=True)



















# # from flask import Flask, request, jsonify
# # from flask_cors import CORS
# # import requests
# # from bs4 import BeautifulSoup
# # import os
# # import openai

# # app = Flask(__name__)
# # CORS(app)

# # # OpenAI API key from environment variable
# # OPENAI_API_KEY="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"
# # if not OPENAI_API_KEY:
# #     raise ValueError("OPENAI_API_KEY environment variable not set")

# # openai.api_key = OPENAI_API_KEY

# # # Fixed URLs to scrape
# # FIXED_URLS = [
# #     "https://www.bou.ac.bd/",
# #     "https://bousst.edu.bd/"
# # ]

# # def scrape_sites():
# #     all_text = ""
# #     headers = {
# #         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 Chrome/91.0 Safari/537.36"
# #     }
# #     for url in FIXED_URLS:
# #         try:
# #             response = requests.get(url, headers=headers, timeout=10)
# #             soup = BeautifulSoup(response.text, 'html.parser')
# #             text = soup.get_text(separator=' ')
# #             all_text += text + "\n\n"
# #         except Exception as e:
# #             print(f"Error scraping {url}: {e}")
# #     return all_text[:3000]  # limit to 3000 chars


# # import openai

# # openai.api_key = OPENAI_API_KEY

# # def ask_openai(context, question):
# #     try:
# #         messages = [
# #             {"role": "system", "content": "You are a helpful assistant that answers questions based on the given context."},
# #             {"role": "user", "content": f"Context: {context}\n\nQuestion: {question}"}
# #         ]

# #         response = openai.chat.completions.create(
# #             model="gpt-3.5-turbo",
# #             messages=messages,
# #             max_tokens=300,
# #             temperature=0.7,
# #         )

# #         answer = response.choices[0].message.content.strip()
# #         return answer

# #     except Exception as e:
# #         return f"OpenAI API error: {str(e)}"


# # @app.route("/ask", methods=["POST"])
# # def ask():
# #     data = request.get_json()
# #     question = data.get("question", "").strip()
# #     if not question:
# #         return jsonify({"answer": "Please provide a question."})

# #     context = scrape_sites()
# #     answer = ask_openai(context, question)
# #     return jsonify({"answer": answer})

# # if __name__ == '__main__':
# #     app.run(debug=True)











# # # from flask import Flask, request, jsonify
# # # from flask_cors import CORS
# # # import requests
# # # from bs4 import BeautifulSoup
# # # import os

# # # app = Flask(__name__)
# # # CORS(app)

# # # # Hugging Face API setup
# # # HUGGINGFACE_API_URL = "https://api-inference.huggingface.co/models/deepseek-ai/deepseek-llm-7b-chat"
# # # HUGGINGFACE_TOKEN = os.getenv("token_hf")

# # # if not HUGGINGFACE_TOKEN:
# # #     raise ValueError("HUGGINGFACE_TOKEN environment variable not set")

# # # HEADERS = {
# # #     "Authorization": f"Bearer {HUGGINGFACE_TOKEN}"
# # # }

# # # # Fixed URLs to scrape
# # # FIXED_URLS = [
# # #     "https://www.bou.ac.bd/",
# # #     "https://bousst.edu.bd/"
# # # ]

# # # # Scrape and extract text from the target websites
# # # def scrape_sites():
# # #     all_text = ""
# # #     headers = {
# # #         "User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 Chrome/91.0 Safari/537.36"
# # #     }

# # #     for url in FIXED_URLS:
# # #         try:
# # #             response = requests.get(url, headers=headers, timeout=10)
# # #             soup = BeautifulSoup(response.text, 'html.parser')
# # #             text = soup.get_text(separator=' ')
# # #             all_text += text + "\n\n"
# # #         except Exception as e:
# # #             print(f"Error scraping {url}: {e}")

# # #     return all_text[:3000]  # Limit to 3000 characters for performance

# # # # Send context + question to Hugging Face API
# # # def ask_deepseek(context, question):
# # #     payload = {
# # #         "inputs": f"Context: {context}\n\nQuestion: {question}",
# # #         "parameters": {"max_new_tokens": 300}
# # #     }

# # #     try:
# # #         res = requests.post(HUGGINGFACE_API_URL, headers=HEADERS, json=payload)
# # #         result = res.json()
# # #         print("Hugging Face response:", result)

# # #         if isinstance(result, list) and "generated_text" in result[0]:
# # #             return result[0]["generated_text"].split("Question:")[-1].strip()
# # #         else:
# # #             return f"DeepSeek error: {result.get('error', 'Unknown error')}"
# # #     except Exception as e:
# # #         return f"Error contacting DeepSeek API: {e}"

# # # # API endpoint
# # # @app.route("/ask", methods=["POST"])
# # # def ask():
# # #     data = request.get_json()
# # #     question = data.get("question", "").strip()

# # #     if not question:
# # #         return jsonify({"answer": "Please provide a question."})

# # #     context = scrape_sites()
# # #     answer = ask_deepseek(context, question)
# # #     return jsonify({"answer": answer})

# # # if __name__ == '__main__':
# # #     app.run(debug=True)