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Multi-GPT

Multi-GPT AI Agent
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Overview

An experimental Python system in which multiple GPT-based specialists collaborate on a task.

Multi-GPT is the sidhq repository derived from an early Auto-GPT implementation. It combines specialist agents, short- and long-term memory, web research and file operations. It is distinct from mentioning multiple custom GPTs inside ChatGPT.

The documented setup uses Python, an OpenAI API key and optional memory backends such as Redis, Pinecone, Milvus or Weaviate. Users authorize one command or a bounded sequence from the terminal, or deliberately enable continuous mode. The repository’s last recorded push is from 2023, so adopting it means reviewing old dependencies and model endpoints rather than expecting a maintained hosted product.

Product overview

Capabilities, pricing and fit

An experimental Python system in which multiple GPT-based specialists collaborate on a task.

Information as of October 14, 2026

What it can do

  • Specialist collaboration

    Multiple expert agents share work and exchange messages.[1]

  • Execution approval

    Approve individual commands or a chosen number of steps.[1]

  • Memory options

    Configure local memory or supported external backends.[1]

Where it fits best

  • Studying early collaborating-agent designs[1]
  • Experimenting with approval-controlled task loops[1]

Pricing and availability

MIT source is available. Model API calls, optional vector databases and compute cost extra; old dependency and API compatibility may require maintenance work.[1]

Access: Developer-managed application or research environment.[1]

Sources (1)
  1. github.com — Product and availabilityOfficial site · checked 2026-10-14

Autonomy level

72/100

Our subjective rating of how independently the product carries out its documented tasks, considering the human setup, input, approval and review it needs. This is not a measured success rate.

Reasoning: Multi-GPT can iterate on a supplied task with cooperating specialists, web access, memory and file tools. Its standard terminal workflow asks the user to authorize commands or a bounded sequence; continuous mode is an explicit choice. People configure keys and execution access, control the budget and review results.

Comparisons


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Some of the use cases of Multi-GPT:

  • Studying early collaborating-agent designs
  • Experimenting with approval-controlled task loops

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Popularity level: 48%

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