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RAG pipeline and agent memory with Pinecone v1.0.0

Use this resource to build a RAG pipeline or agent memory on Pinecone

New

  • 423 downloads
  • 222 likes
  • 212 saves

Free

Install with the CLI

In a terminal, from the folder you want:

npx --yes palatekit@latest install pinecone-rag-pipeline-memory

With no option, the skill goes to ~/.agents/skills/; add --agent claude-code (or codex, cursor…) to target an agent.

First time: connect the CLI with

npx --yes palatekit@latest login

The agent first identifies whether you need RAG over documents or agent memory, then sets up the index, chunking and vector upserts. It picks the retrieval strategy: dense, hybrid with BM25, or metadata-filtered. You get an end-to-end pipeline.

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Updated November 2, 2026

Card for the “RAG pipeline and agent memory with Pinecone” skill

Details

Generates with
Your agent's model
Licence
Apache-2.0

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What you get

  • SKILL.md: scoping question and index configuration
  • SKILL.md: embedding, upsert and retrieval strategy steps

Good fit for

  • You want an LLM to answer from your indexed documents
  • Your agent must remember facts across sessions

Not for

    Tags

    • pinecone
    • rag
    • vectors
    • agent memory

    About

    You say

    “Index my product's help pages in Pinecone and answer questions from those pages.”

    Card for the “RAG pipeline and agent memory with Pinecone” skill

    Skill published by github under the Apache-2.0 license, delivered in its original version.

    Show more

    How to use it

    1. Install the skill in your agent's skills folder
    2. Ask your agent to build a RAG pipeline or agent memory on Pinecone
    3. Review and adjust the result

    Content preview

    Files

    • LICENSE1 KB
    • NOTICE-PALATEKIT.md0.5 KB
    • SKILL.md9.4 KB

    Origin and licence

    Listed unmodified

    Author
    github
    Source
    github.com/github/awesome-copilot/tree/0fe6545b950671641b2b14b44eb56678fea6c6b4/skills/pinecone-rag
    Licence
    Apache-2.0

    Notice

    « pinecone-rag » (github, Apache-2.0) livré dans sa version d'origine : fiche en français et en anglais par PalateKit.

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