📚 pdfquest - Your Study Buddy! 🚀

pdfquest is here to make studying smarter, not harder! Are you a student prepping for exams or a researcher deep-diving into stacks of PDFs? With pdfquest, you can focus on just the information you need, getting answers straight from your own notes, research papers, or study guides. No extra fluff, just the facts, right from your sources! 🌟

🌐 Try pdfquest Live!

Check out the live app here: pdfquest

🎉 What is pdfquest?

pdfquest is a question-answering app powered by Retrieval-Augmented Generation (RAG). It digs through your PDF documents, pulls out only the relevant sections, and gives you concise, context-based answers. It’s like a search engine, but for your own study material—perfect for tackling exam prep and research projects!

🔍 Why pdfquest?

• Streamlined Study: Skip the skimming! Ask a question, and pdfquest fetches the answer from your uploaded files.
• Context Matters: Only the context you provide matters, so your answers are authentic and sourced.
• Exam Hero: Great for focusing on the most relevant material, especially when time is ticking!

🚀 Key Features

• RAG-powered Q&A: Ask questions and get answers directly from your documents.
• Fast Vector Search: Uses FAISS embeddings for fast, accurate search results.
• Document Splitting: Breaks down large PDFs into manageable chunks so nothing is missed.
• Interactive UI: Simple Streamlit interface—type in your question and go!
• Accurate Responses: Uses only the provided context, ensuring answers come from your source material.

🛠️ How It Works

1. Load Documents: Import your PDFs (e.g., research papers, lecture notes).
2. Split and Embed: Each document is split and embedded into a searchable vector space.
3. Ask Away: Type in a question, and pdfquest retrieves relevant document parts to answer you, with no outside info mixed in.

🔧 Built With

• Streamlit: The app’s front-end, making it simple and interactive.
• LangChain: Framework for handling document retrieval and RAG.
• FAISS: Fast vector database for accurate content search.
• Groq AI and HuggingFace: For AI-powered processing and embedding creation.

🏁 Get Started

1. Clone the Repo:

   git clone https://github.com/yourusername/pdfquest.git
   cd pdfquest

2. Install Requirements:

   pip install -r requirements.txt

3. Set Up API Keys: In the root folder, create a .env file and add your API keys:

   OPENAI_API_KEY="your_openai_key"
   GROQ_API_KEY="your_groq_key"
   HF_TOKEN="your_huggingface_token"
   

4. Run the App:

   streamlit run app.py

5. Ask Your First Question:

   • Upload PDFs and ask questions—pdfquest will pull the best answer from your content.

🧑‍🎓 Example Use Case

Studying for an exam? Instead of reading everything, upload your lecture notes and research papers to pdfquest. Just ask specific questions, like “What is the process of photosynthesis?” or “Summarize the main points of Chapter 3,” and get precise answers. 💥

📜 Sample Code Snippet

from langchain_community.vectorstores import FAISS
from langchain_core.prompts import ChatPromptTemplate

# A sample prompt for Q&A
prompt = ChatPromptTemplate.from_template(
    """
    Answer based on the provided context.
    <context>
    {context}
    <context>
    Question: {input}
    """
)

🤝 Contributions

Ideas to improve pdfquest? Feel free to fork, tweak, and submit a pull request! Join us in making studying easier for everyone!

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Enjoy smarter study sessions with pdfquest! 🧠💬