Question Answer Generator App
If you’re looking for a powerful and easy-to-use tool for generating question and answer pairs, then the Question Answer Generator App is the perfect solution. This app utilizes Mistral LLM, Langchain, and FastAPI to provide a seamless and efficient experience for users.
How it Works
The Question Answer Generator App leverages state-of-the-art language models such as Mistral LLM and Langchain to generate accurate and relevant answers to any given question. These language models have been trained on a vast amount of text data, allowing them to understand and interpret natural language in a meaningful way.
FastAPI is used as the backend framework to handle user requests and provide responses in a fast and efficient manner. With FastAPI, the Question Answer Generator App is able to handle a large number of concurrent users without sacrificing performance.
Features
Some key features of the Question Answer Generator App include:
- Intuitive user interface for easy navigation
- Ability to generate question and answer pairs for any given input text
- Support for multiple languages and text formats
- Fast and accurate response times
Get Started
To start using the Question Answer Generator App, simply enter your input text into the provided text box and click the “Generate” button. The app will then use Mistral LLM and Langchain to generate question and answer pairs based on the input text.
Whether you’re a student looking to study for exams or a researcher in need of quick answers to your questions, the Question Answer Generator App is the perfect tool for you. Try it out today and experience the power of Mistral LLM, Langchain, and FastAPI in action!
Hello I am using mistral 7b for generating summary. It takes 50 seconds to generate answer could you please tell me some ways to reduce inference time.
I have tried other models too, gptq model and few inference library.
Thanks for the video. Had a question.. why did you have smaller chunk sizes for the answer splitter compared to the question splitter?
How to download the gguf file ?
hi,thanks for your sharing,I have an question about this app,for the size of docs and the number of QAs,do they have limits?
🎯 Key Takeaways for quick navigation:
00:00 🤖 Introduction to building a Question Answer generator app using open source tools
Key takeaways:
– The app will generate question and answer pairs from a given PDF document
– It will use Mistral, a new large language model, Langchain for orchestration, and FastAPI for the API
03:10 🛡️ Loading the model and preprocessing the PDF
Key takeaways:
– Loading the Mistral model with Transformers
– Preprocessing the PDF to extract text and split into chunks
08:38 💼 Creating the FastAPI endpoints
Key takeaways:
– Creating the index, upload, and analyze endpoints
– Upload endpoint saves the PDF and analyze generates the QA pairs
– Returning results as JSON using FastAPI response
13:47 🧠 Defining the LLMs and chains
Key takeaways:
– Creating the question generation and answer retrieval chains
– Using Langchain for orchestrating the LLM
– Storing embeddings in Fast vector store
23:32 📝 Writing the CSV output
Key takeaways:
– Writing a function to output the QA pairs to a CSV file
– Checking if output folder exists, creating it if needed
– Writing the rows with questions and answers
38:52 ▶️ Running the application
Key takeaways:
– Starting the FastAPI app server
– Uploading a PDF and generating QA pairs
-Downloading the CSV output file with questions and answers
Made with HARPA AI
Thanks a lot for the work
hello sir, can you please make a video for deploying medical chatbot in cloud, I really want that.
Thanks Sonu❤
Your video is literally 24 hours late for me. Same exact challenge was provided by college along with Summarizer and Content Chunking. I referred to your Chatbot video with local LLM and completed the project. Thanks for the content.
🚀🚀🚀
What do you do with these kind of warnings:
Number of tokens (667) exceeded maximum context length (512).
how do you prep the pdf files for ingestion… i always get some kinda of encoding error
Thanks for this video tutorial and your source code…. And, from Q&A data. Can this model continue to generate long-form content based on this data?
Works fine…. Thank you
thank you sir it was a great video, your content is so helpful and easy to understand, sir i have small request can you make the chat bot for searching in pdf with highly accurate information in pdf using mistral, langchain, and fastapi?, this will realy help full for us thank so much
Great video 👍 in the reverse use case u hava QA pairs stored in multiple documents. I know u can do fine tuningwith these pairs. But I have not seen yet a method to do RAG based on this QA documents….
Can I use this question and answer pairs to make my own dataset for intruct fine tuning right?
Thanks for the this video, obviously it can help in order to create a data set for fine tuning a model.
my query is what is we have to generate more then 1 contextual question from a single paragraph ,? How to improvise then?
Kindly do with gpu as well
Just what I needed! Thanks! Can you please make a video on how to train this model with Q/A pairs? Also with support on GPU?