Overview
context-window is perfect for any application that needs to answer questions from your documents. The strict RAG approach ensures accurate, verifiable answers without hallucinations.Document Q&A Systems
Build chatbots and assistants that answer questions from your documentation.Knowledge Base Bot
Perfect for: Customer support, internal documentation, help centers
Product Documentation Assistant
- 24/7 availability
- Instant answers
- Always up-to-date with your docs
- Reduces support ticket volume
Research Assistant
Query across multiple research papers, articles, or books.Academic Research
Perfect for: Literature reviews, research synthesis, academic writing
Market Research Analysis
Business Intelligence
Answer questions from reports, presentations, and internal documents.Executive Dashboard Bot
Perfect for: Executive summaries, data analysis, business reporting
Study Tool & Education
Create AI tutors that answer questions from textbooks and lecture notes.Study Assistant
Interactive Learning Platform
Perfect for: E-learning platforms, homework help, exam preparation
Customer Support
Build support bots that answer from product documentation and FAQs.Support Ticket Automation
Multi-Channel Support
Perfect for: Help desks, chatbots, automated support systems
Legal & Compliance
Search and query through contracts, policies, and legal documents.Contract Analysis
Policy Compliance Checker
Perfect for: Due diligence, compliance checks, contract review
Content Discovery
Find relevant information across large document collections.Document Search Engine
Internal Wiki Search
Perfect for: Enterprise search, knowledge management, archive exploration
Specialized Applications
Medical Information Assistant
Real Estate Property Search
Recipe & Cooking Assistant
Choosing the Right Configuration
Different use cases need different settings:High Accuracy
Legal, medical, compliance
- Model:
gpt-4o - Chunk size: 1500
- topK: 5-10
- scoreThreshold: 0.75-0.85
Fast Response
Customer support, chatbots
- Model:
gpt-4o-mini - Chunk size: 1000
- topK: 5
- scoreThreshold: 0.7
Comprehensive
Research, analysis
- Model:
gpt-4o - Chunk size: 1500
- topK: 10-15
- scoreThreshold: 0
Cost-Effective
FAQ, simple queries
- Model:
gpt-4o-mini - Chunk size: 2000
- topK: 5
- scoreThreshold: 0.6
Next Steps
Examples
See complete code examples
Best Practices
Optimize for your use case
API Reference
Explore all configuration options
Getting Started
Build your first application