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Comparison

RAG-FiT vs filco

Verdict

Pick RAG-FiT if rAG-FiT is a Python framework that enables developers to fine-tune large language models specifically for Retriever-Augmented Generation (RAG) tasks, with strengths in evaluation and information retrieval; pick filco if filco is a Python-based project that focuses on dialog generation, fact verification, and question answering using models like Flan-T5 and LLaMA2, with Dense Passage Retriever for retrieving relevant.

Markdown twin · RAG-FiT alternatives · filco alternatives

GraphCanon updated Sep 20, 2026

RAG-FiT logo

RAG-FiT

IntelLabs/RAG-FiT

★ 768pushed Jun 8, 2026
vs
filco logo

filco

zorazrw/filco

★ 199pushed Apr 6, 2024

Trust & integrity

SignalRAG-FiTfilco
Maintenance
Slowing (102d since push)
As of Sep 19, 2026 · github_public_v1
Dormant (894d since push)
As of Sep 18, 2026 · github_public_v1
Provenance
Not a fork · Organization account
As of Sep 19, 2026 · github_public_v1
Not a fork · Personal account
As of Sep 18, 2026 · github_public_v1
OSV dependency advisories
No lockfile (source not queried)
As of Jul 11, 2026 · osv@v1
Published findings
As of Sep 18, 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
RAG-FiT trust reportfilco trust reportTrust methodology

Tagline

RAG-FiT
Framework for enhancing LLMs for RAG tasks using fine-tuning
filco
Learning to Filter Context for Retrieval-Augmented Generation

Stars

RAG-FiT
768
filco
199

Forks

RAG-FiT
62
filco
20

Open issues

RAG-FiT
1
filco
2

Language

RAG-FiT
Python
filco
Python

Adopt for

RAG-FiT
RAG-FiT is a Python framework that enables developers to fine-tune large language models specifically for Retriever-Augmented Generation (RAG) tasks, with strengths in evaluation and information retrieval.
filco
Filco is a Python-based project that focuses on dialog generation, fact verification, and question answering using models like Flan-T5 and LLaMA2, with Dense Passage Retriever for retrieving relevant Wikipedia passages.

Persona

RAG-FiT
-
filco
-

Runtime

RAG-FiT
-
filco
-

License

RAG-FiT
RAG-FiT operates under the Apache-2.0 license, providing a permissive free software license that permits reuse within proprietary software.
filco
CC-BY-SA-4.0

Last pushed

RAG-FiT
Jun 8, 2026
filco
Apr 6, 2024

Categories

RAG-FiT
Evaluation & Observability, Model Training
filco
Data & Retrieval, Model Training

Trust and health

Maintenance

RAG-FiT
Slowing (36%)
filco
Dormant (18%)

Days since push

RAG-FiT
102d
filco
894d

Open issues (now)

RAG-FiT
1
filco
2

Stars delta

RAG-FiT
0 (30d)
filco
+1 (30d)

Owner type

RAG-FiT
Organization
filco
User

OSV dependency advisories

RAG-FiT
No lockfile (source not queried)
filco
Published findings

Full report

RAG-FiT
Trust report
filco
Trust report

Shared compatibility

  • Python · RAG-FiT: Python runtime · filco: Python runtime

Choose RAG-FiT if…

  • License: RAG-FiT is Apache-2.0, filco is CC-BY-SA-4.0.
  • Requirements: This framework requires proficiency in Python and an understanding of RAG tasks to be effectively utilized..
  • Tags unique to RAG-FiT: evaluation, fine-tuning, information retrieval, llm.
  • Also covers Evaluation & Observability.
  • When seeking to improve performance of LLMs in NLP tasks requiring RAG capabilities, like question-answering or semantic search

When NOT to use RAG-FiT

  • If project needs are more aligned with traditional fine-tuning methods that do not specifically enhance RAG capabilities, another tool might be more suitable
  • In scenarios where the development team lacks proficiency in Python, as RAG-FiT is Python-based and may have a steeper learning curve for non-Python developers
GitHubDetails

Choose filco if…

  • License: filco is CC-BY-SA-4.0, RAG-FiT is Apache-2.0.
  • Tags unique to filco: dialog-generation, fact-verification, flan-t5, llama2.
  • Also covers Data & Retrieval.
  • When you need to generate dialogues that require fact verification and question answering capabilities, leveraging models like Flan-T5 and LLaMA2.

When NOT to use filco

  • If your project does not require the use of Flan-T5 or LLaMA2 models for dialog generation, fact verification, or question answering.
  • When you do not need to retrieve relevant Wikipedia passages using Dense Passage Retriever.
  • If your project does not involve the use of preprocessed datasets with top-5 retrieved passages from Wikipedia.
GitHubDetails

Explore

RAG-FiT trust report →filco trust report →Evaluation & Observability category →Model Training category →Data & Retrieval 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: RAG-FiT 768 · filco 199 (synced Sep 20, 2026).

Common questions

What is the difference between RAG-FiT and filco?
RAG-FiT: Framework for enhancing LLMs for RAG tasks using fine-tuning. filco: Learning to Filter Context for Retrieval-Augmented Generation. See the comparison table for live GitHub stats and shared categories.
When should I choose RAG-FiT over filco?
Choose RAG-FiT over filco when License: RAG-FiT is Apache-2.0, filco is CC-BY-SA-4.0; Requirements: This framework requires proficiency in Python and an understanding of RAG tasks to be effectively utilized.; Tags unique to RAG-FiT: evaluation, fine-tuning, information retrieval, llm; Also covers Evaluation & Observability; When seeking to improve performance of LLMs in NLP tasks requiring RAG capabilities, like question-answering or semantic search.
When should I choose filco over RAG-FiT?
Choose filco over RAG-FiT when License: filco is CC-BY-SA-4.0, RAG-FiT is Apache-2.0; Tags unique to filco: dialog-generation, fact-verification, flan-t5, llama2; Also covers Data & Retrieval; When you need to generate dialogues that require fact verification and question answering capabilities, leveraging models like Flan-T5 and LLaMA2.
When should I avoid RAG-FiT?
If project needs are more aligned with traditional fine-tuning methods that do not specifically enhance RAG capabilities, another tool might be more suitable In scenarios where the development team lacks proficiency in Python, as RAG-FiT is Python-based and may have a steeper learning curve for non-Python developers
When should I avoid filco?
If your project does not require the use of Flan-T5 or LLaMA2 models for dialog generation, fact verification, or question answering. When you do not need to retrieve relevant Wikipedia passages using Dense Passage Retriever. If your project does not involve the use of preprocessed datasets with top-5 retrieved passages from Wikipedia.
Is RAG-FiT or filco more popular on GitHub?
RAG-FiT has more GitHub stars (768 vs 199). Stars measure visibility, not whether either tool fits your constraints.
Are RAG-FiT and filco open source?
Yes - both are open-source projects on GitHub (RAG-FiT: Apache-2.0, filco: CC-BY-SA-4.0).
Where can I find alternatives to RAG-FiT or filco?
GraphCanon lists graph-backed alternatives at RAG-FiT alternatives and filco alternatives (RAG-FiT markdown twin, filco 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, RAG-FiT or filco?
RAG-FiT: Slowing. filco: 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 RAG-FiT and filco?
GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: RAG-FiT trust report; filco trust report.

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