KnowledgeLM 🧠
A research companion for NotebookLM that automates the collection of NSE company filings. Designed to be operated by AI agents (Claude Code, Gemini CLI, etc.).
🚀 Instant Setup (AI Agents)
Install the knowledgelm-nse agent skill using:
npx skills add eggmasonvalue/knowledgelm-nse
This skill allows your AI agent to batch download a comprehensive bundle of investor materials(exchange filings - .pdfs and parsed XBRLs) and valuepickr forum thread for Indian publicly listed companies and optionally integrate them into NotebookLM for deep fundamental analysis.
✨ Features
- Agent-First: Optimized for LLMs with a standardized Agent Skill, and strictly formatted JSON output to
stdoutto preserve the context window. - Batch Downloads: NSE lacks bulk extraction; KnowledgeLM fetches filings by category in seconds via
fetch nse. - Granular XBRL Parsing: Extracts fine-grained facts (Personnel Changes/Resignations, Board Outcomes, Shareholder Meetings) into clean JSON using our standalone, highly optimized
nse-xbrl-parseroffline resolution engine. - Issue Documents: IPO prospectus, rights offers, QIP placements, information memoranda, and scheme documents — unified across 5 NSE endpoints.
- Markdown Conversion: Built-in
convertcommands to transform PDFs into LLM-ready Markdown. - NotebookLM Synergy: Purpose-built commands to facilitate source injection and bundled prompt templates for audio overviews.
- ValuePickr Forum Export: Export entire forum threads to clean, research-ready PDFs with reference extraction via
fetch vp. Besides, Valuepickr forum thread .pdfs are formatted for a distraction-free reading experience for humans. - Interactive UI: Browse and download individual filings (Resignations, Press Releases, etc.) via Streamlit.
🐧 ARM / Linux Setup
On ARM Linux devices, official Selenium Manager binaries are unavailable. You must manually install chromedriver using your system's package manager.
# Example (Debian/Ubuntu/Termux):
sudo apt install chromium-driver # Package names vary
Requirement: Ensure chromedriver is available in your $PATH.
🛠️ Manual Installation & Usage
CLI Usage
# Install from PyPI
uv tool install knowledgelm --upgrade
# Fetch corporate filings (NSE)
knowledgelm fetch nse HDFCBANK --start 2024-01-01 --end 2025-01-26 --datasets transcripts,annual_reports
# Fetch personnel changes/resignations (XBRL)
knowledgelm fetch nse RELIANCE --start 2024-01-01 --end 2025-01-26 --datasets personnel
# Fetch issue documents (IPO, rights, QIP, schemes)
knowledgelm fetch nse SWIGGY --start 2020-01-01 --end 2025-12-31 --datasets issue_documents
# Export forum thread (ValuePickr)
knowledgelm fetch vp "https://forum.valuepickr.com/t/hdfc-bank-limited/123" --symbol HDFCBANK
# Convert downloaded PDFs to Markdown
knowledgelm convert dir "./HDFCBANK_sources/transcripts/"
Web UI
Launch the interactive dashboard:
uv run streamlit run src/knowledgelm/app.py
📂 Project Structure
.agent/: AI Agent resources, skills, and prompt templates..context/: Living documentation (Architecture, Design, Changelog).src/: Core logic and Streamlit app.tests/: Unit and integration tests.
See .context/ARCHITECTURE.md for detailed diagrams.
📄 License
Distributed under the MIT License. See LICENSE for more information.
Metadata
Release files for knowledgelm 5.1.0
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| knowledgelm-5.1.0.tar.gz | 153.2 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| knowledgelm-5.1.0-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 191.8 kB
Release files / knowledgelm-5.1.0.tar.gz
| Download URL | knowledgelm-5.1.0.tar.gz |
|---|---|
| Size | 153.2 kB |
| Tags | Source |
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Release files / knowledgelm-5.1.0-py3-none-any.whl
| Download URL | knowledgelm-5.1.0-py3-none-any.whl |
|---|---|
| Size | 38.7 kB |
| Tags | Python 3 |
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SHA-256 checksum How to use checksums |
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No |
| Uploaded via |
twine/6.1.0 CPython/3.13.7
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