skills.rest
coinvest518
coinvest518COMMUNITY
Explore all skills by this author →
WebsiteGitHub

knowledge-base

Ingest PDFs, text files, and Markdown into Mem0 and AstraDB.

Updated Mar 18, 2026
Search Tags:#documents#search#memory#knowledge-base#ingest#mem0#astradb
One-click install
npx skills add https://github.com/coinvest518/deepagents-LANGCLAW --skill knowledge-base-coinvest518
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: knowledge-base
Source: https://github.com/coinvest518/deepagents-LANGCLAW/tree/main/libs/cli/deepagents_cli/built_in_skills/knowledge-base
Command: npx skills add https://github.com/coinvest518/deepagents-LANGCLAW --skill knowledge-base-coinvest518

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pypdf, mem0ai, astrapy, and includes scripts (resource) components.

What problem does it solve?

Ingests PDFs, text files, and Markdown into the agent's long-term memory for fast retrieval and contextual awareness across conversations.

Core Features & Use Cases

  • Ingest documents into Mem0 semantic memory for fast retrieval.
  • Store a durable backup in AstraDB for cross-session access.
  • Use cases include "remember this report", "read this PDF", and "search my docs" to answer questions from ingested content.

Quick Start

Ingest a PDF or document to store it in memory for future queries.

Frequently Asked Questions about knowledge-base

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I ingest PDFs and Markdown files into agent memory for cross-session retrieval?▼

You ingest PDFs, text files, and Markdown into agent memory by storing them in Mem0 semantic memory and AstraDB. This provides fast contextual recall and durable retrieval across multiple conversations.

What is the best way to remember documents across different AI conversations?▼

The best way to remember documents across conversations is ingesting them into Mem0 semantic memory for fast recall, backed by a durable AstraDB store. This ensures long-term retention and cross-session access.

Do I need an API key to ingest documents into Mem0 and AstraDB?▼

Yes, you need environment variables configured for Mem0 and AstraDB. Specifically, set MEM0_API_KEY and/or ASTRA_DB_API_KEY plus ASTRA_DB_ENDPOINT before ingesting documents for durable retrieval.

Can I search my ingested PDFs and text files directly from agent memory?▼

Yes, you can search ingested PDFs and text files directly from agent memory. The semantic memory mechanism allows you to query your stored documents to answer questions from previously ingested content.

Does this document ingestion approach work for long-term retention of Markdown and text?▼

Yes, this approach works for long-term retention of Markdown, text, and PDF files. It applies to use cases requiring persistent storage by combining Mem0 for quick recall with AstraDB for durable backup.

What are the limitations of using Mem0 and AstraDB for document memory?▼

Limitations include requiring specific environment variables like MEM0_API_KEY and ASTRA_DB_ENDPOINT for operation. It is strictly designed for ingesting PDFs, text, and Markdown, not for live database querying or real-time data streaming.

Related Skills

Explore More Data & Analytics Skills→
beyonaibeyonai
45

by-doc-to-markdown

Convert PDF, Word, Excel, and PowerPoint documents into Markdown files.

Community
Intermediate
Synaptic-Labs-AISynaptic-Labs-AI
71

pact-memory

Store and retrieve structured memories in a SQLite-backed store for PACT agents.

Official
Advanced
ThiNepoThiNepo
2

langchain-rag

Creates Retrieval-Augmented Generation pipelines with Chroma, FAISS, and Pinecone vector stores.

Community
Advanced
shalevaminshalevamin

rag-architect

Designs and implements RAG systems with chunking, embedding generation, vector stores, hybrid search, reranking, and evaluation.

Community
Advanced