🚀 Introducing my latest application, Docu Talk

[Antoine3]

Hey Streamlit Community!

I’m excited to share Docu Talk, a Streamlit-powered web app that lets you create custom Chat Bots from your PDF documents in just seconds!

Key Features:
AI-Powered Responses: Structured and formatted replies based on document content
Cloud Integration: Secure communication with cloud-stored files via Gemini
Machine Learning Optimization: Predicts response times using historical data

Streamlit-Powered Frontend:
Google/Microsoft/Email Authentication (thanks to Streamlit 1.42.0!)
Session & Cookie Management for user persistence
Dynamic HTML Components for an interactive UI

Security & Deployment:
Encrypted Password Storage with hashing
Whitelisted Database Access via VPC/NAT for enhanced security
Cloud Deployment on Google Cloud Run & Streamlit Cloud
Automated Email Service with AWS SES
Secure File Storage using Google Cloud Storage

Code Quality & Best Practices:
Linted & Verified with ruff
Modular Architecture (authentication, pages, services…)

Try the App: https://docu-talk-ai-apps.streamlit.app
Explore the Open-Source Code: GitHub Repo

Would love to hear your feedback!

streamlit #Python #MachineLearning ai #ChatBots #OpenSource #TechInnovation #GoogleCloud aws #SoftwareEngineering #DevCommunity

[mojsilo]

@Antoine3 nice work! how do you perform search on the document? I don’t see you put it into vector database or anything.

[Antoine3]

Thank you @mojsilo ! Yes, there is no RAG, but “in-context processing”, capable of handling up to 1,000 pages of documents with Gemini!

In-context processing is becoming increasingly interesting compared to RAG for several reasons: models can accept longer inputs, generate faster, and are becoming less and less expensive