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📘 PDF Insight Engine

Built with 💡 by Kavya Bhardwaj

The PDF Insight Engine is an AI-powered tool designed to extract valuable insights from PDF documents. It combines advanced embedding models, semantic vector storage, and powerful language-generation APIs to provide interactive and detailed answers based on your uploaded documents.

🚀 What This Tool Does

Given any PDF document, the engine:

  • 📄 Extracts text accurately from PDFs.
  • 🔖 Breaks documents into semantic chunks.
  • 🧠 Generates embeddings using Sentence Transformers.
  • 🔍 Stores and retrieves information efficiently via Pinecone Vectorstore.
  • ✨ Provides refined, detailed answers using Cohere’s generative models.

🧠 Technologies Used

Component Technology Used
PDF Text Extraction ✅ LangChain (PyPDFLoader)
Semantic Embeddings ✅ SentenceTransformers (all-MiniLM-L6-v2)
Vector Database ✅ Pinecone Vectorstore
Enhanced Responses ✅ Cohere API (command-xlarge)
Text Processing ✅ LangChain Text Splitter, NLTK
OCR (Optional) ✅ Poppler, Tesseract

🧩 Smart Features

  • ✅ Intelligent semantic chunking of text.
  • ✅ Rapid similarity-based search for document querying.
  • ✅ Cohere API integration for contextually refined answers.
  • ✅ Supports fallback and retry logic for robust processing.

📦 How to Run

1. Clone the Repository

git clone https://github.com/Kavya071/PDF-Insight-Engine.git
cd PDF-Insight-Engine

2. Install Dependencies

pip install openai==0.27.2 langchain-community sentence_transformers pinecone-client cohere nltk unstructured
sudo apt-get install poppler-utils tesseract-ocr

3. Set Up API Keys

Replace the placeholders with your actual API keys:

PINECONE_API_KEY = "your_pinecone_api_key"
COHERE_API_KEY = "your_cohere_api_key"

4. Run the Application

Launch the notebook (PDF_Insight.ipynb) in Google Colab or locally:

jupyter notebook PDF_Insight.ipynb

Then follow the prompts to upload PDFs and enter queries interactively.

📧 Contact

Feel free to connect:

✉️ bhardwajkavya099@gmail.com

Built with 💡 by Kavya Bhardwaj