Itinai.com futuristic ui icon design 3d sci fi computer scree 53325f5e 8707 4993 866c f93d7a06d6eb 3
Itinai.com futuristic ui icon design 3d sci fi computer scree 53325f5e 8707 4993 866c f93d7a06d6eb 3

Build an AI-Powered PDF Interaction System in Google Colab with Gemini Flash 1.5

Building an AI-Powered PDF Interaction System

This tutorial outlines the steps to create an AI-driven PDF interaction system using Google Colab, Gemini Flash 1.5, PyMuPDF, and the Google Generative AI API. By utilizing these technologies, users can upload a PDF, extract its text, and ask questions to receive intelligent responses.

Step 1: Install Required Dependencies

Begin by installing the necessary libraries:

  !pip install -q -U google-generativeai PyMuPDF python-dotenv
  

These libraries facilitate natural language interactions and efficient text extraction from PDFs.

Step 2: Upload PDF Files

Use the following code to upload files from your local device:

  from google.colab import files
  uploaded = files.upload()
  

This allows you to select and upload a PDF file for processing.

Step 3: Extract Text from PDF

Utilize PyMuPDF to extract text from the uploaded PDF:

  import fitz

  def extract_pdf_text(pdf_path):
      doc = fitz.open(pdf_path)
      full_text = ""
      for page in doc:
          full_text += page.get_text()
      return full_text

  pdf_file_path = '/content/Paper.pdf'
  document_text = extract_pdf_text(pdf_path=pdf_file_path)
  print("Document text extracted!")
  print(document_text[:1000])
  

This function reads the PDF and retrieves its text content, enabling further analysis.

Step 4: Set Up the Google API Key

Store your Google API key securely as an environment variable:

  import os
  os.environ["GOOGLE_API_KEY"] = 'Use your own API key here'
  

This key allows access to the Google Generative AI services.

Step 5: Query the AI Model

Configure and query the Gemini Flash model:

  import google.generativeai as genai

  genai.configure(api_key=os.environ["GOOGLE_API_KEY"])

  model_name = "models/gemini-1.5-flash-001"

  def query_gemini_flash(question, context):
      model = genai.GenerativeModel(model_name=model_name)
      prompt = f"""
  Context: {context[:20000]}

  Question: {question}

  Answer:
  """
      response = model.generate_content(prompt)
      return response.text

  pdf_text = extract_pdf_text("/content/Paper.pdf")

  question = "Summarize the key findings of this document."
  answer = query_gemini_flash(question, pdf_text)
  print("Gemini Flash Answer:")
  print(answer)
  

This setup enables automated summarization and intelligent question answering from the PDF.

Conclusion

By following this tutorial, you have built an interactive PDF interaction system in Google Colab. This solution simplifies information extraction and querying from PDFs, leveraging advanced AI models.

Further Engagement

Explore how AI can transform your business processes. Identify automation opportunities and key performance indicators to measure the impact of your AI initiatives. Start small, gather data, and gradually expand your AI applications.

For assistance in managing AI in your business, contact us at hello@itinai.ru or reach out via Telegram, X, or LinkedIn.


Itinai.com office ai background high tech quantum computing 0002ba7c e3d6 4fd7 abd6 cfe4e5f08aeb 0

Vladimir Dyachkov, Ph.D
Editor-in-Chief itinai.com

I believe that AI is only as powerful as the human insight guiding it.

Unleash Your Creative Potential with AI Agents

Competitors are already using AI Agents

Business Problems We Solve

  • Automation of internal processes.
  • Optimizing AI costs without huge budgets.
  • Training staff, developing custom courses for business needs
  • Integrating AI into client work, automating first lines of contact

Large and Medium Businesses

Startups

Offline Business

100% of clients report increased productivity and reduced operati

AI news and solutions