# trypromptly/LLMStack

No-code multi-agent framework to build LLM Agents, workflows and applications with your data

Repository: https://github.com/trypromptly/LLMStack
Canonical: https://ross.abutalabs.com/products/llmstack
Homepage: https://llmstack.trypromptly.com
Language: Python
License: NOASSERTION
License Family: other
Topics: ai, generative-ai, llm-chain, llm-framework, llmops, llms, no-code-ai, platform, agents, ai-agents-framework, llm-agents
Last push: 2024-12-11T19:59:51+00:00

## Health v2 (maintenance only)
Score: 30/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 40, longevity 80
- inputs: {"age_days": 1124, "days_push": 630, "days_rel": 667, "gap_med": 25.5, "n_releases_24m": 3}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2311, forks 349 (observed 2026-08-28T04:06:36.064412+00:00)

## What it is
LLMStack is a no-code platform for building generative AI agents, workflows, and chatbots by chaining multiple LLMs and connecting them to your own data. It is self-hostable via pip or Docker and includes a web-based app builder, data source ingestion, and sharing with granular permissions.

## Use cases
- build ai agents without coding
- create chatbots connected to my own documents
- chain multiple llm providers in one workflow
- ingest pdfs and websites as knowledge for an llm app
- trigger ai workflows from slack or discord
- self-host a no-code llm app builder
- build multi-agent pipelines with my business data

## When to choose
- you want a visual, no-code builder for LLM agents and chatbots
- you need to connect diverse data sources (PDFs, URLs, Notion, Google Drive) to LLM apps
- you want to self-host on your own infrastructure or cloud
- you need multi-provider model support (OpenAI, Cohere, Stability, Hugging Face)

## When to avoid
- you prefer writing agent logic in code rather than a visual builder
- you need a lightweight library to embed in an existing Python app
- you cannot run Docker for background jobs or browser automation
- you need a fully permissive license (license is custom/NOASSERTION)

## Facets
- artifact type: framework
- maturity: active
- function: agent-framework, rag, chatbot, llm-inference, workflow-automation, web-framework
- domain: artificial-intelligence, large-language-models, chatbots, self-hosted, web-development
- platform: python, self-hosted, windows
- tags: no-code, llm-chaining, multi-agent, generative-ai, data-connectors, slack-integration, discord-integration, app-builder, ai-agents, retrieval-augmented-generation, docker, web-server, linux, macos

## Member repositories
- trypromptly/LLMStack (main) score 30

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:36.064412+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:39:32.780617+00:00, confidence not recorded.
  - readme: https://github.com/trypromptly/LLMStack (fetched 2026-08-28T04:06:36.064412+00:00, sha a05312a4f47d)
  - homepage: https://llmstack.trypromptly.com (fetched 2026-08-29T10:19:39.809536+00:00, sha 7e91f7cd9058)
  - site_page: https://docs.trypromptly.com/llmstack/introduction (fetched 2026-08-29T10:19:39.812179+00:00, sha 602ed8e66315)
  - site_page: https://docs.trypromptly.com/getting-started/ui (fetched 2026-08-29T10:19:39.814329+00:00, sha e6b5ab0ea71d)
- Data as of 2026-08-30T08:39:29.467469+00:00.