Comparison
RD-Agent vs awesome-llm-apps
Verdict
Pick RD-Agent if rD-Agent is an automation tool for AI-driven R&D processes, focusing on data and model development using Python with support from Docker installations; pick awesome-llm-apps if awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python.
Markdown twin · RD-Agent alternatives · awesome-llm-apps alternatives
GraphCanon updated Sep 20, 2026
11views this month
vs
Trust & integrity
| Signal | RD-Agent | awesome-llm-apps |
|---|---|---|
| Maintenance | Active (14d since push) As of Aug 19, 2026 · github_public_v1 | Very active (4d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Aug 19, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- RD-Agent
- Automating high-value R&D processes through AI-driven data science and model development.
- awesome-llm-apps
- Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.
Stars
- RD-Agent
- 14k
- awesome-llm-apps
- 136k
Forks
- RD-Agent
- 1.8k
- awesome-llm-apps
- 20k
Open issues
- RD-Agent
- 198
- awesome-llm-apps
- 10
Language
- RD-Agent
- Python
- awesome-llm-apps
- Python
Adopt for
- RD-Agent
- RD-Agent is an automation tool for AI-driven R&D processes, focusing on data and model development using Python with support from Docker installations.
- awesome-llm-apps
- awesome-llm-apps is a collection of over 100 AI Agent and Retrieval Augmented Generation (RAG) applications that enable users to quickly implement, customize, and deploy practical use cases in Python.
Persona
- RD-Agent
- -
- awesome-llm-apps
- -
Runtime
- RD-Agent
- -
- awesome-llm-apps
- -
License
- RD-Agent
- MIT
- awesome-llm-apps
- The Apache-2.0 license allows users to freely use, modify, and distribute the projects found in awesome-llm-apps under specific conditions outlined by the license.
Last pushed
- RD-Agent
- Aug 4, 2026
- awesome-llm-apps
- Sep 2, 2026
Categories
- RD-Agent
- AI Agents, Data & Retrieval, Model Training
- awesome-llm-apps
- AI Agents, Data & Retrieval
Trust and health
Maintenance
- RD-Agent
- Active (82%)
- awesome-llm-apps
- Very active (96%)
Days since push
- RD-Agent
- 14d
- awesome-llm-apps
- 4d
Open issues (now)
- RD-Agent
- 198
- awesome-llm-apps
- 10
Stars delta
- RD-Agent
- +332 (30d)
- awesome-llm-apps
- +5.2k (30d)
Open issues delta
- RD-Agent
- +5 (30d)
- awesome-llm-apps
- -3 (30d)
Owner type
- RD-Agent
- Organization
- awesome-llm-apps
- User
OSV dependency advisories
- RD-Agent
- Published findings
- awesome-llm-apps
- No lockfile (source not queried)
Full report
- RD-Agent
- Trust report
- awesome-llm-apps
- Trust report
Shared compatibility
- Python · RD-Agent: Python runtime · awesome-llm-apps: Python runtime
Choose RD-Agent if…
- License: RD-Agent is MIT, awesome-llm-apps is Apache-2.0.
- Pricing: RD-Agent operates under the MIT license allowing free use of the tool. Its framework for R&D automation can be expanded with premium services for enterprise-level support and integration if needed..
- Requirements: Requires Docker; Ensure Docker is installed beforehand and accessible without `sudo` by the current user for RD-Agent operation.; Supports Python installations via PyPI or development setup from source, which also requires installation of dependencies as per the documentation..
- Tags unique to RD-Agent: agent, ai, automation, data-mining.
- Also covers Model Training.
- When you require automation in high-value R&D tasks that revolve around data science and model development within the AI domain.
When NOT to use RD-Agent
- When the need arises to work in an environment where Python cannot be used or there is a requirement for another programming language framework that complements existing infrastructure better.
- If your development team lacks expertise with Docker and is not willing or able to adopt it, as most scenarios within RD-Agent require a solid Docker setup.
Choose awesome-llm-apps if…
- License: awesome-llm-apps is Apache-2.0, RD-Agent is MIT.
- Pricing: Free with open-source licensing, but commercial exploitation is allowed..
- Tags unique to awesome-llm-apps: agents, applications, customizable, deployable.
- When you need quick implementations of various real-world use cases for AI Agents and RAG.
When NOT to use awesome-llm-apps
- If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch.
- When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (microsoft/RD-Agent) · observed Sep 20, 2026
- GitHub forks (microsoft/RD-Agent) · observed Sep 20, 2026
- Last push (microsoft/RD-Agent) · observed Aug 4, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (Shubhamsaboo/awesome-llm-apps) · observed Sep 20, 2026
- GitHub forks (Shubhamsaboo/awesome-llm-apps) · observed Sep 20, 2026
- Last push (Shubhamsaboo/awesome-llm-apps) · observed Sep 2, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: RD-Agent 14k · awesome-llm-apps 136k (synced Sep 20, 2026).
Common questions
- What is the difference between RD-Agent and awesome-llm-apps?
- RD-Agent: Automating high-value R&D processes through AI-driven data science and model development.. awesome-llm-apps: Over 100 runnable AI Agent and RAG apps to clone, tweak, and deploy.. See the comparison table for live GitHub stats and shared categories.
- When should I choose RD-Agent over awesome-llm-apps?
- Choose RD-Agent over awesome-llm-apps when License: RD-Agent is MIT, awesome-llm-apps is Apache-2.0; Pricing: RD-Agent operates under the MIT license allowing free use of the tool. Its framework for R&D automation can be expanded with premium services for enterprise-level support and integration if needed.; Requirements: Requires Docker; Ensure Docker is installed beforehand and accessible without
sudoby the current user for RD-Agent operation.; Supports Python installations via PyPI or development setup from source, which also requires installation of dependencies as per the documentation.; Tags unique to RD-Agent: agent, ai, automation, data-mining; Also covers Model Training; When you require automation in high-value R&D tasks that revolve around data science and model development within the AI domain. - When should I choose awesome-llm-apps over RD-Agent?
- Choose awesome-llm-apps over RD-Agent when License: awesome-llm-apps is Apache-2.0, RD-Agent is MIT; Pricing: Free with open-source licensing, but commercial exploitation is allowed.; Tags unique to awesome-llm-apps: agents, applications, customizable, deployable; When you need quick implementations of various real-world use cases for AI Agents and RAG.
- When should I avoid RD-Agent?
- When the need arises to work in an environment where Python cannot be used or there is a requirement for another programming language framework that complements existing infrastructure better. If your development team lacks expertise with Docker and is not willing or able to adopt it, as most scenarios within RD-Agent require a solid Docker setup.
- When should I avoid awesome-llm-apps?
- If your project requires highly specialized customization beyond what the provided apps can offer out-of-the-box, as deep integration might be required from scratch. When you are looking for a fully managed service or support directly from developers; this repository is more about self-service and community interaction.
- Is RD-Agent or awesome-llm-apps more popular on GitHub?
- awesome-llm-apps has more GitHub stars (136,444 vs 14,275). Stars measure visibility, not whether either tool fits your constraints.
- Are RD-Agent and awesome-llm-apps open source?
- Yes - both are open-source projects on GitHub (RD-Agent: MIT, awesome-llm-apps: Apache-2.0).
- Where can I find alternatives to RD-Agent or awesome-llm-apps?
- GraphCanon lists graph-backed alternatives at RD-Agent alternatives and awesome-llm-apps alternatives (RD-Agent markdown twin, awesome-llm-apps markdown twin), ranked by typed relationship edges rather than popularity votes.
- Is there a machine-readable version of this comparison?
- Yes. The markdown twin at this comparison mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, RD-Agent or awesome-llm-apps?
- RD-Agent: Active. awesome-llm-apps: Very active. 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 RD-Agent and awesome-llm-apps?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: RD-Agent trust report; awesome-llm-apps trust report.