GraphCanon
Home/Compare/ragflow vs AdalFlow

Comparison

ragflow vs AdalFlow

Verdict

Pick ragflow if rAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released 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 2w

ragflow logo

ragflow

infiniflow/ragflow

★ 87kpushed Jul 31, 2026
vs
AdalFlow logo

AdalFlow

SylphAI-Inc/AdalFlow

★ 4.2kpushed May 29, 2026

Trust & integrity

SignalragflowAdalFlow
Maintenance
Very active (0d since push)
As of 3w · github_public_v1
Steady (70d since push)
As of 2w · github_public_v1
Provenance
Not a fork · Organization account
As of 3w · github_public_v1
Not a fork · Organization account
As of 2w · github_public_v1
OSV dependency advisories
Published findings
As of 1mo · osv@v1
No lockfile (source not queried)
As of 1mo · 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
ragflow trust reportAdalFlow trust reportTrust methodology

Tagline

ragflow
Retrieval-Augmented Generation engine with agent capabilities
AdalFlow
The library to build & auto-optimize LLM applications.

Stars

ragflow
87k
AdalFlow
4.2k

Forks

ragflow
10k
AdalFlow
384

Open issues

ragflow
2.0k
AdalFlow
68

Language

ragflow
Go
AdalFlow
Python

Adopt for

ragflow
RAGFlow is a Retrieval-Augmented Generation (RAG) engine that integrates AI agents for enhanced context management in LLM applications, built using Go language and released 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 License
AdalFlow
MIT

Last pushed

ragflow
Jul 31, 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
Steady (60%)

Days since push

ragflow
0d
AdalFlow
70d

Open issues (now)

ragflow
2.0k
AdalFlow
68

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.
  • Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services..
  • Tags unique to ragflow: agentic-ai, context management, rag, retrieval-augmented-generation.
  • ragflow ships Docker support for self-hosted deployment.
  • - You need an integrated RAG system with AI agent capabilities for better context management in your applications.

When NOT to use ragflow

  • - If you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go.
  • - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB).
  • - You cannot use external LLM services and embedding services, as RAGFlow relies on them to function.
GitHubDetails

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.
GitHubDetails

Explore

ragflow trust report →AdalFlow trust report →AI Agents category →Data & Retrieval category →LLM Frameworks category →Model Training category →All comparisonsStack workflowsTrending tools

Sources

Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.

GitHub stars on cards: ragflow 87k · AdalFlow 4.2k (synced Aug 1, 2026).

Common questions

What is the difference between ragflow and AdalFlow?
ragflow: Retrieval-Augmented Generation 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; Requirements: Requires Docker; Docker image size is approximately 2 GB; build process requires access to external LLM and embedding services.; Tags unique to ragflow: agentic-ai, context management, rag, retrieval-augmented-generation; ragflow ships Docker support for self-hosted deployment; - You need an integrated RAG system with AI agent capabilities for better context management in your applications.
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 you specifically require a non-Golang developed RAG engine, as RAGFlow is built entirely in Go. - Your setup does not support or need Docker (RAGFlow requires building a Docker image that is approximately 2 GB). - You cannot use external LLM services and embedding services, as RAGFlow relies on them to function.
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 (86,541 vs 4,196). 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: Steady. 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.

Was this helpful?

Anonymous feedback helps us improve pages and translations.