--- title: "botpress vs rags" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/botpress-botpress-vs-run-llama-rags" tools: ["botpress-botpress", "run-llama-rags"] --- # botpress vs rags Neutral, constraint-first comparison with live GitHub stats. | | [botpress](/tools/botpress-botpress.md) | [rags](/tools/run-llama-rags.md) | | --- | --- | --- | | Tagline | The open-source hub to build & deploy GPT/LLM Agents | Build ChatGPT over your data using natural language with RAGs | | Stars | 14,772 | 6,546 | | Forks | 2,274 | 660 | | Open issues | 21 | 38 | | Language | TypeScript | Python | | Adopt for | Botpress is an open-source platform for developing GPT and LLM-powered chatbots and conversational assistants, featuring robust integrations, developer tools, bot examples, and plugins. | RAGs is a Python-based Streamlit app designed to build Retriever-Augmented Generation pipelines using natural language instructions and configurations. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | AI Agents, Developer Tools | AI Agents, Data & Retrieval | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [botpress](/tools/botpress-botpress.md) | [rags](/tools/run-llama-rags.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 824d | | Open issues (now) | 21 | 38 | | Security scan | No lockfile | 39 low (39 low) | | Full report | [trust report](/tools/botpress-botpress/trust.md) | [trust report](/tools/run-llama-rags/trust.md) | **Typed relationship:** botpress _(alternative)_ rags Both RAGs and botpress are focused on the development of chatbots and agents, including those powered by GPT/LLMs. ## Decision facts: botpress - **Adopt for:** Botpress is an open-source platform for developing GPT and LLM-powered chatbots and conversational assistants, featuring robust integrations, developer tools, bot examples, and plugins. ## Decision facts: rags - **Pricing:** freemium - RAGs is open-source under MIT license. Costs arise from any third-party API usage such as OpenAI and are not covered by RAGs itself. - **Requirements:** Min 4 GB RAM; RAGs requires an internet connection to interact with external APIs like OpenAI.; Ensure you configure your environment with the necessary API keys and secrets as per the installation guide. - **Adopt for:** RAGs is a Python-based Streamlit app designed to build Retriever-Augmented Generation pipelines using natural language instructions and configurations. ## Choose when ### Choose botpress if… - botpress is primarily TypeScript; rags is Python. - Both RAGs and botpress are focused on the development of chatbots and agents, including those powered by GPT/LLMs. - Tags unique to botpress: botpress, ai, nlp, chatgpt. - Also covers Developer Tools. - When you need a flexible platform to quickly develop advanced AI agents using OpenAI's models. ### Choose rags if… - rags is primarily Python; botpress is TypeScript. - Pricing: RAGs is open-source under MIT license. Costs arise from any third-party API usage such as OpenAI and are not covered by RAGs itself.. - Requirements: Min 4 GB RAM; RAGs requires an internet connection to interact with external APIs like OpenAI.; Ensure you configure your environment with the necessary API keys and secrets as per the installation guide.. - Both RAGs and botpress are focused on the development of chatbots and agents, including those powered by GPT/LLMs. - Tags unique to rags: streamlit, rag. - Also covers Data & Retrieval. - Use RAGs if you want an interactive way to configure and query your data with simple textual instructions through an intuitive UI in a Streamlit app. ## When NOT to use botpress - Avoid choosing Botpress when your use case does not need or cannot justify the investment in OpenAI-based models like GPT-4. - If your chatbot requirements fit better within simpler rule-based systems, consider more basic chatbot development frameworks instead. - Do not opt for this solution if you prefer proprietary developer tools over open-source alternatives. ## When NOT to use rags - Avoid RAGs if you need full customization of the backend logic and don't want the constraints imposed by the Streamlit interface. - Not recommended for environments with strict security policies that forbid the use of external APIs like OpenAI, unless you have the capability to replace those services. ## Common questions ### What is the difference between botpress and rags? botpress: The open-source hub to build & deploy GPT/LLM Agents. rags: Build ChatGPT over your data using natural language with RAGs. See the comparison table for live GitHub stats and shared categories. ### When should I choose botpress over rags? Choose botpress over rags when botpress is primarily TypeScript; rags is Python; Both RAGs and botpress are focused on the development of chatbots and agents, including those powered by GPT/LLMs; Tags unique to botpress: botpress, ai, nlp, chatgpt; Also covers Developer Tools; When you need a flexible platform to quickly develop advanced AI agents using OpenAI's models. ### When should I choose rags over botpress? Choose rags over botpress when rags is primarily Python; botpress is TypeScript; Pricing: RAGs is open-source under MIT license. Costs arise from any third-party API usage such as OpenAI and are not covered by RAGs itself.; Requirements: Min 4 GB RAM; RAGs requires an internet connection to interact with external APIs like OpenAI.; Ensure you configure your environment with the necessary API keys and secrets as per the installation guide.; Both RAGs and botpress are focused on the development of chatbots and agents, including those powered by GPT/LLMs; Tags unique to rags: streamlit, rag; Also covers Data & Retrieval; Use RAGs if you want an interactive way to configure and query your data with simple textual instructions through an intuitive UI in a Streamlit app. ### When should I avoid botpress? Avoid choosing Botpress when your use case does not need or cannot justify the investment in OpenAI-based models like GPT-4. If your chatbot requirements fit better within simpler rule-based systems, consider more basic chatbot development frameworks instead. Do not opt for this solution if you prefer proprietary developer tools over open-source alternatives. ### When should I avoid rags? Avoid RAGs if you need full customization of the backend logic and don't want the constraints imposed by the Streamlit interface. Not recommended for environments with strict security policies that forbid the use of external APIs like OpenAI, unless you have the capability to replace those services. ### Is botpress or rags more popular on GitHub? botpress has more GitHub stars (14,772 vs 6,546). Stars measure visibility, not whether either tool fits your constraints. ### Are botpress and rags open source? Yes - both are open-source projects on GitHub (botpress: MIT, rags: MIT). ### Where can I find alternatives to botpress or rags? GraphCanon lists graph-backed alternatives at /tools/botpress-botpress/alternatives and /tools/run-llama-rags/alternatives (/tools/botpress-botpress/alternatives.md, /tools/run-llama-rags/alternatives.md), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at /compare/botpress-botpress-vs-run-llama-rags.md mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, botpress or rags? botpress: Very active. rags: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for botpress and rags? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: botpress: /tools/botpress-botpress/trust; rags: /tools/run-llama-rags/trust. --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=botpress-botpress`](/api/graphcanon/graph?tool=botpress-botpress) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_