Ross ROSS = Recommend OSS · open-source software intelligence for agents

run-llama/sec-insights

A real world full-stack application using LlamaIndex observed · 2026-08-28

github.com/run-llama/sec-insights · homepage · TypeScript · MIT (permissive) observed · 2026-08-28

Health v2 · maintenance only

33/100

  • Activity 11
  • Release rhythm 35
  • Longevity 78

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1093
  • days_rel: n/a
  • days_push: 539
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

2609 stars · 694 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

SEC Insights is a full-stack reference application built by LlamaIndex that uses RAG to answer questions about SEC 10-K and 10-Q financial documents. It features a React/Next.js frontend with a PDF viewer and citation highlighting, plus a FastAPI backend with streaming LLM responses and tool-based quantitative answers.

Use cases

  • ask questions about SEC 10-K and 10-Q filings
  • build a production RAG application from a reference codebase
  • chat with multiple financial documents simultaneously
  • view paragraph-level citations with PDF highlighting
  • deploy a full-stack LLM app to Vercel and Render
  • learn how to stream LLM responses with server-sent events

When to choose

  • you want a complete real-world example of a production RAG application
  • you need document Q&A with source citations over PDFs
  • you want to fork a solid foundation for your own LlamaIndex-based app
  • you need multi-document comparison chat with reasoning step streaming

When to avoid

  • you need a lightweight library to embed in an existing app rather than a full application
  • your documents are not financial filings and you don't want to adapt the ingestion pipeline
  • you need on-premise LLM inference without API-based models or tools

Facets

application · maturity active

rag chatbot llm-inference pdf-viewer web-framework api-framework search-engine large-language-models fintech pdf web-development artificial-intelligence self-hosted python cross-platform llamaindex sec-filings financial-documents nextjs fastapi citation-highlighting streaming full-stack-example vercel render retrieval-augmented-generation web-server docker nodejs

2 sources

Member repositories

RepositoryRoleHealth v2
run-llama/sec-insightsmain33

For agents

markdown · JSON · MCP: product_card(name="run-llama/sec-insights")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem