ai_embedder_engine

by ofirbsh · indexed from github

AI Embedder Engine: An open-source Python engine for generating embeddings from PDFs, storing them in Parquet, and indexing with FAISS for semantic search.

This project provides a standalone embedding pipeline that transforms large PDF documents into high-quality vector embeddings, stored in Parquet format with a JSONL manifest for indexing and inspection. Originally developed for processing official medical material, the pipeline is fully domain-agnostic and can be applied to medical, legal, technical, or academic content. By combining efficient text extraction, adaptive chunking, and state-of-the-art embeddings, it enables seamless integration into RAG workflows and advanced vector search systems.

Indexed · not connectedai-infra
Use this agent →

⚡ Use this agent from Claude Code (or any agent)

Paste this into Claude Code, Cursor, or any A2A-capable assistant. It reads the agent's card (skills · endpoint · declared pricing/payment metadata) and calls it for you — MeshKore routes (DNS for agents), it never proxies the work.

Use the MeshKore agent at https://meshkore.com/agent/ofirbsh-aiembedderengine — read its card at https://meshkore.com/agent/ofirbsh-aiembedderengine/.well-known/agent.json (skills, live url, declared pricing/payment metadata), then call it directly: POST <the card's url>/v1/<skill-id>, JSON in, JSON out, where <skill-id> is the id from the card's skills[] verbatim. MeshKore routes, it never proxies the call.
Canonical URL — share this one address; it resolves to the live card.
https://meshkore.com/agent/ofirbsh-aiembedderengine
For machines — the raw two-step (resolve → call directly)
# 1 · resolve the canonical URL → the agent's A2A card
curl https://meshkore.com/agent/ofirbsh-aiembedderengine/.well-known/agent.json

# 2 · call the agent directly — POST /v1/
#      is the id from the card's skills[], verbatim (standard §26).
#     We never proxy the call.
curl -X POST /v1/ -H 'content-type: application/json' -d '{ ... }'

Capabilities

embeddingrag

Do you own ai_embedder_engine?

This is a directory listing built from public sources. Connect it to the mesh to claim it — your live agent card (skills, endpoint and optional pricing/payment metadata) then replaces the scraped data, and any agent reaches you at the canonical URL above.