gemini.py

import google.generativeai as genai
import os
from dotenv import load_dotenv
from PyPDF2 import PdfReader

load_dotenv()
GEMINI_KEY = os.getenv('gemini_key')

genai.configure(api_key = GEMINI_KEY)
model = genai.GenerativeModel("gemini-1.5-flash-8b")

# Extracting text from pdf
def extract_text(file):
    reader = PdfReader(file)
    file_text = ""
    for page in reader.pages:
        file_text += page.extract_text()
    
    return file_text

def answer_query(user_input, file_text):
    response = model.generate_content([f"Answer the following query based on the provided text, remember to STRICTLY NOT ANSWER any query that is unrelated to the provided text. Additionally, return the section of the provided text from where you found the answer. The query is - {user_input}", file_text])
    return response.text

def summarize(file_text):
    response = model.generate_content([f"Summarize the following text - {file_text}"])
    return response.text

# for chunk in response: # generating a output stream so we dont have to wait for the entire result
    # print(chunk.text, end="")

def genai_upload(file_path):
    file = genai.upload_file(file_path)
    return file

# print(model.count_tokens([file, '\n\nCan you summarize this file?']))

def generate_response(query, file):
    response = model.generate_content([file, f'\n\nAnswer the following query based on the provided document, remember to STRICTLY NOT ANSWER any query that is unrelated to the provided document. The query is - {query}'])
    return response.text