SEC 10-K analysis example DAG using LlamaIndex for Common.ai provider#67671
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Two Dags demonstrating a multi-company financial research pipeline
using real SEC 10-K filings fetched live from the EDGAR public API:
- Indexing DAG (weekly): fetches 10-K filings by stock ticker,
extracts Risk Factors and MD&A sections, builds per-company
vector indexes via LlamaIndexEmbeddingOperator with DTM fan-out.
- Analysis DAG (on-demand): analyst submits tickers and a comparison
question via HITLEntryOperator, LLM decomposes into company-specific
sub-questions (N decided at runtime), retrieves from per-company
indexes via DTM, synthesizes a structured report (AnalysisReport
Pydantic model with UsageLimits), formats for human review, and
gates on ApprovalOperator.
Features showcased: Dynamic Task Mapping, structured LLM output,
UsageLimits, HITL input and approval, live external API integration,
DAG-level Params.
Default tickers: AAPL, MSFT, UBER, LYFT, AMZN.
gopidesupavan
approved these changes
May 30, 2026
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Two Dags demonstrating a multi-company financial research pipeline using real SEC 10-K filings fetched live from the EDGAR public API:
Features showcased: Dynamic Task Mapping, structured LLM output, UsageLimits, HITL input and approval, and live external API integration.
Default tickers: AAPL, MSFT, UBER, LYFT, AMZN.
Was generative AI tooling used to co-author this PR?
Generated-by: [Claude] following the guidelines