E
Engram
Core Concepts

Knowledge Base

Turn Engram into a domain expert. Crawls external documentation sites, vectorizes the content into the local Qdrant doc_knowledge collection, and answers complex questions with citation-backed accuracy.

Recursive Crawler

Intelligently traverses documentation pages, respecting domain boundaries and separating code blocks from prose.

Local Vector Store

Uses Qdrant's doc_knowledge collection to store 768-dimensional embeddings on your disk. No data ever leaves your machine.

RAG Pipeline

Retrieval-Augmented Generation fetches the exact documentation snippet needed to ground the AI's answer.

Interface Options

Engram provides two ways to interact with your knowledge base: a visual dashboard for ease of use, and a CLI tool for automation.

Knowledge Base
https://flask.palletsprojects.com/
Ingest
How do I create a route in Flask?
AI: To create a route in Flask, use the @app.route() decorator.

# Example
@app.route("/")
def hello():
  return "Hello World"

Technical Setup

01Install Dependencies

The crawler requires specific Python libraries for scraping and vector storage. Ensure these are in your backend container.

text
beautifulsoup4
requests
qdrant-client

02Git Exclusion

Qdrant data lives in a Docker named volume and never appears as a local directory. If you run Qdrant outside Docker during development, exclude any local data directories from version control.

gitignore
# .gitignore — add if running Qdrant locally outside Docker
qdrant_storage/