Query-Bot is an open-source chat application built with Python, LangChain, and Streamlit. It leverages OpenAI's GPT-3.5 Turbo to ingest and index user-provided documents, enabling interactive, context-aware question answering via a clean web interface.
AI Platforms & Frameworks
Document Processing
Personal Assistants
#document search
#PDF ingestion
#AI question answering
#text chunking
#vector embeddings
#GPT-3.5 turbo
#Knowledge Base
#custom QA bot
#no-code interface
#document indexing
#file upload
#interactive chat
#cloud deployment
#local deployment
#OpenAI-Integration
#User-Friendly UI
#contextual answers
#Document Formats
#Streamlit application
#extensible framework
...
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Query-Bot
Query-Bot is an open-source chat application built with Python, LangChain, and Streamlit. It leverages OpenAI's GPT-3.5 Turbo to ingest and index user-provided documents, enabling interactive, context-aware question answering via a clean web interface.
AI Platforms & Frameworks
Document Processing
Personal Assistants
#document search
#PDF ingestion
#AI question answering
#text chunking
#vector embeddings
#GPT-3.5 turbo
#Knowledge Base
#custom QA bot
#no-code interface
#document indexing
#file upload
#interactive chat
#cloud deployment
#local deployment
#OpenAI-Integration
#User-Friendly UI
#contextual answers
#Document Formats
#Streamlit application
#extensible framework
...
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What is Query-Bot?
Query-Bot integrates document ingestion, text chunking, and vector embeddings to build a searchable index from PDFs, text files, and Word documents. Using LangChain and OpenAI GPT-3.5 Turbo, it processes user queries by retrieving relevant document passages and generating concise answers. The Streamlit-based UI allows users to upload files, track conversation history, and adjust settings. It can be deployed locally or on cloud environments, offering an extensible framework for custom agents and knowledge bases.
Who will use Query-Bot?
- Software developers
- Data scientists
- Researchers
- Business analysts
- Educators
How to use the Query-Bot?
- Step1: Clone the repository and navigate to its directory
- Step2: Install dependencies via pip install -r requirements.txt
- Step3: Set your OPENAI_API_KEY environment variable
- Step4: Prepare and place documents in the designated folder
- Step5: Run the app with streamlit run app.py
- Step6: Open the displayed local URL and start querying documents
Platform
- web
- mac
- windows
- linux
Query-Bot's Core Features & Benefits
The Core Features
- Document ingestion from PDFs, text, and Word
- Vector index creation with embeddings
- Interactive chat UI with Streamlit
- Context-aware question answering
- Configurable chain and index settings
The Benefits
- Quick deployment of a custom QA bot
- No-code document querying interface
- Open-source extensibility
- Support for multiple document formats
- Leverages powerful GPT-3.5 Turbo model
Query-Bot's Main Use Cases & Applications
- Customer support knowledge base querying
- Internal document search for teams
- Academic research assistant
- E-learning and training content Q&A
- Legal and compliance document exploration
FAQs of Query-Bot
Query-Bot Company Information
Query-Bot Reviews
5/5
Query-Bot's Main Competitors and alternatives?
- LlamaIndex
- Haystack
- LangChain Chatbot Templates
- Chatbot UI
- DocuQA
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