Comparison
txtai vs rag-fusion
Verdict
Pick txtai if txtai is an all-in-one AI framework that supports semantic search, LLM orchestration, and language model workflows, making it suitable for projects that require comprehensive AI capabilities in Python; pick rag-fusion if rAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR.
Markdown twin · txtai alternatives · rag-fusion alternatives
GraphCanon updated Sep 20, 2026
7views this month
Trust & integrity
| Signal | txtai | rag-fusion |
|---|---|---|
| Maintenance | Very active (2d since push) As of Sep 18, 2026 · github_public_v1 | Slowing (146d since push) As of Sep 20, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Sep 18, 2026 · github_public_v1 | Not a fork · Personal account As of Sep 20, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) 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
- txtai
- All-in-one AI framework for semantic search, LLM orchestration and language model workflows
- rag-fusion
- multi-query generation + Reciprocal Rank Fusion for retrieval-augmented generation
Stars
- txtai
- 13k
- rag-fusion
- 958
Forks
- txtai
- 891
- rag-fusion
- 114
Open issues
- txtai
- 10
- rag-fusion
- 0
Language
- txtai
- Python
- rag-fusion
- Python
Adopt for
- txtai
- txtai is an all-in-one AI framework that supports semantic search, LLM orchestration, and language model workflows, making it suitable for projects that require comprehensive AI capabilities in Python.
- rag-fusion
- RAG-Fusion leverages multi-query generation and Reciprocal Rank Fusion for enhanced retrieval-augmented generation tasks, supporting evaluations via NFCorpus/BEIR.
Persona
- txtai
- -
- rag-fusion
- -
Runtime
- txtai
- -
- rag-fusion
- -
License
- txtai
- Apache-2.0
- rag-fusion
- MIT
Last pushed
- txtai
- Sep 15, 2026
- rag-fusion
- Apr 26, 2026
Categories
- txtai
- AI Agents, Data & Retrieval, Evaluation & Observability, Inference & Serving, Model Training, Vector Databases
- rag-fusion
- Data & Retrieval, Evaluation & Observability
Trust and health
Maintenance
- txtai
- Very active (96%)
- rag-fusion
- Slowing (36%)
Days since push
- txtai
- 2d
- rag-fusion
- 146d
Open issues (now)
- txtai
- 10
- rag-fusion
- 0
Stars delta
- txtai
- +69 (30d)
- rag-fusion
- +12 (30d)
Owner type
- txtai
- Organization
- rag-fusion
- User
Full report
- txtai
- Trust report
- rag-fusion
- Trust report
Shared compatibility
- Python · txtai: Python runtime · rag-fusion: Python runtime
Choose txtai if…
- License: txtai is Apache-2.0, rag-fusion is MIT.
- Tags unique to txtai: agents, ai, ai-agents, embeddings.
- Also covers AI Agents, Inference & Serving, Model Training, Vector Databases.
- When you need a comprehensive framework that integrates semantic search, LLM orchestration, and language model workflows in a single package.
When NOT to use txtai
- If your project strictly requires a framework that is not Python-based, as txtai is specifically designed for Python environments.
- When you need a tool that focuses solely on a specific aspect of AI, such as only semantic search or only LLM orchestration, as txtai's all-in-one approach might introduce unnecessary complexity.
- If your project cannot accommodate the Apache-2.0 license, as txtai is distributed under this license and may not be suitable for projects with different licensing requirements.
Choose rag-fusion if…
- License: rag-fusion is MIT, txtai is Apache-2.0.
- Tags unique to rag-fusion: chromadb, openai, python, rag-fusion.
- For enhancing precision in retrieval-augmented generation tasks needing complex query processing
When NOT to use rag-fusion
- If you require real-time performance, as multi-query generation may introduce latency
- In scenarios where only simple keyword-based search suffices without the need for advanced fusion techniques
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (neuml/txtai) · observed Sep 20, 2026
- GitHub forks (neuml/txtai) · observed Sep 20, 2026
- Last push (neuml/txtai) · observed Sep 15, 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 (Raudaschl/rag-fusion) · observed Sep 20, 2026
- GitHub forks (Raudaschl/rag-fusion) · observed Sep 20, 2026
- Last push (Raudaschl/rag-fusion) · observed Apr 26, 2026
- License file (MIT) · observed Sep 20, 2026
- Decision facts (enrichment) · observed Jul 15, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: txtai 13k · rag-fusion 958 (synced Sep 20, 2026).
Common questions
- What is the difference between txtai and rag-fusion?
- txtai: All-in-one AI framework for semantic search, LLM orchestration and language model workflows. rag-fusion: multi-query generation + Reciprocal Rank Fusion for retrieval-augmented generation. See the comparison table for live GitHub stats and shared categories.
- When should I choose txtai over rag-fusion?
- Choose txtai over rag-fusion when License: txtai is Apache-2.0, rag-fusion is MIT; Tags unique to txtai: agents, ai, ai-agents, embeddings; Also covers AI Agents, Inference & Serving, Model Training, Vector Databases; When you need a comprehensive framework that integrates semantic search, LLM orchestration, and language model workflows in a single package.
- When should I choose rag-fusion over txtai?
- Choose rag-fusion over txtai when License: rag-fusion is MIT, txtai is Apache-2.0; Tags unique to rag-fusion: chromadb, openai, python, rag-fusion; For enhancing precision in retrieval-augmented generation tasks needing complex query processing.
- When should I avoid txtai?
- If your project strictly requires a framework that is not Python-based, as txtai is specifically designed for Python environments. When you need a tool that focuses solely on a specific aspect of AI, such as only semantic search or only LLM orchestration, as txtai's all-in-one approach might introduce unnecessary complexity. If your project cannot accommodate the Apache-2.0 license, as txtai is distributed under this license and may not be suitable for projects with different licensing requirements.
- When should I avoid rag-fusion?
- If you require real-time performance, as multi-query generation may introduce latency In scenarios where only simple keyword-based search suffices without the need for advanced fusion techniques
- Is txtai or rag-fusion more popular on GitHub?
- txtai has more GitHub stars (12,959 vs 958). Stars measure visibility, not whether either tool fits your constraints.
- Are txtai and rag-fusion open source?
- Yes - both are open-source projects on GitHub (txtai: Apache-2.0, rag-fusion: MIT).
- Where can I find alternatives to txtai or rag-fusion?
- GraphCanon lists graph-backed alternatives at txtai alternatives and rag-fusion alternatives (txtai markdown twin, rag-fusion 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, txtai or rag-fusion?
- txtai: Very active. rag-fusion: 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 txtai and rag-fusion?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: txtai trust report; rag-fusion trust report.