Comparison
ragflow vs AdalFlow
Verdict
Pick ragflow if rAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license; pick AdalFlow if adalFlow is designed to streamline the development and automatic optimization of LLM applications.
Markdown twin · ragflow alternatives · AdalFlow alternatives
GraphCanon updated Sep 20, 2026
6views this month
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Trust & integrity
| Signal | ragflow | AdalFlow |
|---|---|---|
| Maintenance | Very active (0d since push) As of Sep 18, 2026 · github_public_v1 | Slowing (101d since push) As of Sep 7, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 7, 2026 · github_public_v1 |
| OSV dependency advisories | Published findings As of Sep 18, 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
- ragflow
- Retrieval-Augmented Generation (RAG) engine with agent capabilities
- AdalFlow
- The library to build & auto-optimize LLM applications.
Stars
- ragflow
- 91k
- AdalFlow
- 4.2k
Forks
- ragflow
- 11k
- AdalFlow
- 387
Open issues
- ragflow
- 1.4k
- AdalFlow
- 68
Language
- ragflow
- Go
- AdalFlow
- Python
Adopt for
- ragflow
- RAGFlow is an open-source RAG engine that integrates agent capabilities to enhance context management for LLMs, built in Go under the Apache-2.0 license.
- AdalFlow
- AdalFlow is designed to streamline the development and automatic optimization of LLM applications.
Persona
- ragflow
- -
- AdalFlow
- -
Runtime
- ragflow
- -
- AdalFlow
- -
License
- ragflow
- Apache-2.0
- AdalFlow
- MIT
Last pushed
- ragflow
- Sep 18, 2026
- AdalFlow
- May 29, 2026
Categories
- ragflow
- AI Agents, Data & Retrieval
- AdalFlow
- AI Agents, Data & Retrieval, LLM Frameworks, Model Training
Trust and health
Maintenance
- ragflow
- Very active (96%)
- AdalFlow
- Slowing (36%)
Days since push
- ragflow
- 0d
- AdalFlow
- 101d
Open issues (now)
- ragflow
- 1.4k
- AdalFlow
- 68
Stars delta
- ragflow
- +4.4k (30d)
- AdalFlow
- +17 (30d)
Open issues delta
- ragflow
- -553 (30d)
- AdalFlow
- 0 (30d)
OSV dependency advisories
- ragflow
- Published findings
- AdalFlow
- No lockfile (source not queried)
Full report
- ragflow
- Trust report
- AdalFlow
- Trust report
Choose ragflow if…
- ragflow is primarily Go; AdalFlow is Python.
- License: ragflow is Apache-2.0, AdalFlow is MIT.
- Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search.
- ragflow ships Docker support for self-hosted deployment.
- When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management.
When NOT to use ragflow
- If your project does not require integration with external LLM and embedding services, as RAGFlow relies on these services.
- If you are looking for a lightweight solution, as RAGFlow's Docker image is approximately 2 GB in size.
- When you prefer tools that do not require building a Docker image, as RAGFlow's setup involves creating a Docker image.
Choose AdalFlow if…
- AdalFlow is primarily Python; ragflow is Go.
- License: AdalFlow is MIT, ragflow is Apache-2.0.
- Tags unique to AdalFlow: agent, ai, auto-prompting, bm25.
- Also covers LLM Frameworks, Model Training.
- When you are working on projects that require advanced AI agents or chatbots with auto-prompting features, as AdalFlow can handle these needs comprehensively.
When NOT to use AdalFlow
- Avoid using AdalFlow if your project does not benefit from auto-optimization features or does not involve LLM applications, as its specialized capabilities might introduce unnecessary complexity.
- AdalFlow may not be the best choice for projects where custom or low-level control over all aspects of the AI model training and optimization is required, given it's designed to streamline processes.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (infiniflow/ragflow) · observed Sep 20, 2026
- GitHub forks (infiniflow/ragflow) · observed Sep 20, 2026
- Last push (infiniflow/ragflow) · observed Sep 18, 2026
- License file (Apache-2.0) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Sep 18, 2026
- Trust scan (lockfile / OSV) · observed Sep 18, 2026
- GitHub stars (SylphAI-Inc/AdalFlow) · observed Sep 20, 2026
- GitHub forks (SylphAI-Inc/AdalFlow) · observed Sep 20, 2026
- Last push (SylphAI-Inc/AdalFlow) · observed May 29, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: ragflow 91k · AdalFlow 4.2k (synced Sep 20, 2026).
Common questions
- What is the difference between ragflow and AdalFlow?
- ragflow: Retrieval-Augmented Generation (RAG) engine with agent capabilities. AdalFlow: The library to build & auto-optimize LLM applications.. See the comparison table for live GitHub stats and shared categories.
- When should I choose ragflow over AdalFlow?
- Choose ragflow over AdalFlow when ragflow is primarily Go; AdalFlow is Python; License: ragflow is Apache-2.0, AdalFlow is MIT; Tags unique to ragflow: agent-harness, agentic-ai, agentic-retrieval, agentic-search; ragflow ships Docker support for self-hosted deployment; When you need an open-source RAG engine that can integrate with external LLM and embedding services to enhance context management.
- When should I choose AdalFlow over ragflow?
- Choose AdalFlow over ragflow when AdalFlow is primarily Python; ragflow is Go; License: AdalFlow is MIT, ragflow is Apache-2.0; Tags unique to AdalFlow: agent, ai, auto-prompting, bm25; Also covers LLM Frameworks, Model Training; When you are working on projects that require advanced AI agents or chatbots with auto-prompting features, as AdalFlow can handle these needs comprehensively.
- When should I avoid ragflow?
- If your project does not require integration with external LLM and embedding services, as RAGFlow relies on these services. If you are looking for a lightweight solution, as RAGFlow's Docker image is approximately 2 GB in size. When you prefer tools that do not require building a Docker image, as RAGFlow's setup involves creating a Docker image.
- When should I avoid AdalFlow?
- Avoid using AdalFlow if your project does not benefit from auto-optimization features or does not involve LLM applications, as its specialized capabilities might introduce unnecessary complexity. AdalFlow may not be the best choice for projects where custom or low-level control over all aspects of the AI model training and optimization is required, given it's designed to streamline processes.
- Is ragflow or AdalFlow more popular on GitHub?
- ragflow has more GitHub stars (90,923 vs 4,213). Stars measure visibility, not whether either tool fits your constraints.
- Are ragflow and AdalFlow open source?
- Yes - both are open-source projects on GitHub (ragflow: Apache-2.0, AdalFlow: MIT).
- Where can I find alternatives to ragflow or AdalFlow?
- GraphCanon lists graph-backed alternatives at ragflow alternatives and AdalFlow alternatives (ragflow markdown twin, AdalFlow 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, ragflow or AdalFlow?
- ragflow: Very active. AdalFlow: Slowing. 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 ragflow and AdalFlow?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: ragflow trust report; AdalFlow trust report.