Paper QA
LLM Chain for answering questions from documents with citations
Pricing
Free tier
Flat rate
Adoption
→StableLicense
Open Source
Data freshness
UnverifiedOverview
What is Paper QA?
Paper QA is a tool that uses large language models to answer questions from documents while providing proper citations. It's useful for researchers and writers who need accurate, cited information.
Key differentiator
“Paper QA stands out by integrating large language models for question answering directly into document analysis, providing automatic citations which is crucial for academic and research purposes.”
Capability profile
Capability Radar
Honest assessment
Strengths & Weaknesses
↑ Strengths
↓ Weaknesses
API requires Python-specific patterns, TypeScript SDK is community-maintained
v0.1 to v0.2 migration required rewriting chain definitions
Documentation and community examples primarily focus on English documents
Processing time increases exponentially with the size of input documents, leading to slow response times for large datasets
Fit analysis
Who is it for?
✓ Best for
Academic researchers who need to cite sources accurately in their work
Content creators looking for a tool that can generate citations automatically
Developers building question-answering systems that require citation support
✕ Not a fit for
Teams needing real-time responses as the processing time might be longer due to LLM inference
Projects with strict data privacy requirements, as it may involve handling sensitive documents
Cost structure
Pricing
Free Tier
Available
Open source — free to use
Starts at
$0
Model
Flat rate
Enterprise
None
Performance benchmarks
How Fast Is It?
Ecosystem
Relationships
Alternatives
Works well with
Integrations
Next step
Get Started with Paper QA
Step-by-step setup guide with code examples and common gotchas.