---
title: "in-context-ralm vs filco"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/ai21labs-in-context-ralm-vs-zorazrw-filco"
tools: ["ai21labs-in-context-ralm", "zorazrw-filco"]
---

# in-context-ralm vs filco

*GraphCanon updated Sep 20, 2026*

## Verdict

Pick in-context-ralm if in-context-ralm is a Python-based tool for reproducing experiments on WikiText-103 from AI21 Labs' paper on In-Context Retrieval-Augmented Language Models, leveraging Transformers and Pyserini libraries; 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 Wikipedia passages.

[in-context-ralm](https://github.com/AI21Labs/in-context-ralm) reports 295 GitHub stars, 28 forks, and 4 open issues, last pushed Dec 20, 2023. [filco](https://arxiv.org/pdf/2311.08377.pdf) has 199 stars, 20 forks, and 2 open issues, last pushed Apr 6, 2024. Figures are from public GitHub metadata via [in-context-ralm's repository](https://github.com/AI21Labs/in-context-ralm) and [filco's repository](https://github.com/zorazrw/filco).

| | [in-context-ralm](/tools/ai21labs-in-context-ralm.md) | [filco](/tools/zorazrw-filco.md) |
| --- | --- | --- |
| Tagline | In-Context Retrieval-Augmented Language Models | Learning to Filter Context for Retrieval-Augmented Generation |
| Stars | 295 | 199 |
| Forks | 28 | 20 |
| Open issues | 4 | 2 |
| Language | Python | Python |
| Adopt for | in-context-ralm is a Python-based tool for reproducing experiments on WikiText-103 from AI21 Labs' paper on In-Context Retrieval-Augmented Language Models, leveraging Transformers and Pyserini libraries. | 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 | - | - |
| Runtime | - | - |
| License | Apache-2.0 | CC-BY-SA-4.0 |
| Categories | Evaluation & Observability, Model Training | Data & Retrieval, Model Training |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [in-context-ralm](/tools/ai21labs-in-context-ralm.md) | [filco](/tools/zorazrw-filco.md) |
| --- | --- | --- |
| Maintenance | Archived (8%) | Dormant (18%) |
| Days since push | 1003d | 894d |
| Archived on GitHub | Yes | No |
| Open issues (now) | 4 | 2 |
| Stars delta | 0 (30d) | +1 (30d) |
| Owner type | Organization | User |
| Full report | [trust report](/tools/ai21labs-in-context-ralm/trust.md) | [trust report](/tools/zorazrw-filco/trust.md) |

## Shared compatibility

- **Python**: [in-context-ralm](/tools/ai21labs-in-context-ralm.md) - Python runtime; [filco](/tools/zorazrw-filco.md) - Python runtime

## Decision facts: in-context-ralm

- **Requirements:** Min 8 GB RAM; Ensure Python 3.8 is installed.; Java 11 is required for BM25 preparation with Pyserini.; CUDA-specific Pytorch installation is recommended for optimal performance.
- **Adopt for:** in-context-ralm is a Python-based tool for reproducing experiments on WikiText-103 from AI21 Labs' paper on In-Context Retrieval-Augmented Language Models, leveraging Transformers and Pyserini libraries.

## Decision facts: filco

- **Adopt for:** 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.

## Choose when

### Choose in-context-ralm if…

- License: in-context-ralm is Apache-2.0, filco is CC-BY-SA-4.0.
- Requirements: Min 8 GB RAM; Ensure Python 3.8 is installed.; Java 11 is required for BM25 preparation with Pyserini.; CUDA-specific Pytorch installation is recommended for optimal performance..
- Tags unique to in-context-ralm: in-context ralm, language models, pyserini, python.
- Also covers Evaluation & Observability.
- Use in-context-ralm when you need to reproduce experiments on WikiText-103 as detailed in AI21 Labs' paper.

### Choose filco if…

- License: filco is CC-BY-SA-4.0, in-context-ralm 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 in-context-ralm

- Do not use in-context-ralm if your project does not involve the WikiText-103 dataset or the specific language models tested in the AI21 Labs paper.
- Avoid using this tool if you do not require the specific setup involving Pyserini for BM25 retrieval, as it necessitates Java 11 and setting the JAVA_HOME environment variable.
- Do not use in-context-ralm if your project does not align with the Apache-2.0 license terms.

## 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.

## Common questions

### What is the difference between in-context-ralm and filco?

in-context-ralm: In-Context Retrieval-Augmented Language Models. filco: Learning to Filter Context for Retrieval-Augmented Generation. See the comparison table for live GitHub stats and shared categories.

### When should I choose in-context-ralm over filco?

Choose in-context-ralm over filco when License: in-context-ralm is Apache-2.0, filco is CC-BY-SA-4.0; Requirements: Min 8 GB RAM; Ensure Python 3.8 is installed.; Java 11 is required for BM25 preparation with Pyserini.; CUDA-specific Pytorch installation is recommended for optimal performance.; Tags unique to in-context-ralm: in-context ralm, language models, pyserini, python; Also covers Evaluation & Observability; Use in-context-ralm when you need to reproduce experiments on WikiText-103 as detailed in AI21 Labs' paper.

### When should I choose filco over in-context-ralm?

Choose filco over in-context-ralm when License: filco is CC-BY-SA-4.0, in-context-ralm 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 in-context-ralm?

Do not use in-context-ralm if your project does not involve the WikiText-103 dataset or the specific language models tested in the AI21 Labs paper. Avoid using this tool if you do not require the specific setup involving Pyserini for BM25 retrieval, as it necessitates Java 11 and setting the JAVA_HOME environment variable. Do not use in-context-ralm if your project does not align with the Apache-2.0 license terms.

### 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 in-context-ralm or filco more popular on GitHub?

in-context-ralm has more GitHub stars (295 vs 199). Stars measure visibility, not whether either tool fits your constraints.

### Are in-context-ralm and filco open source?

Yes - both are open-source projects on GitHub (in-context-ralm: Apache-2.0, filco: CC-BY-SA-4.0).

### Where can I find alternatives to in-context-ralm or filco?

GraphCanon lists graph-backed alternatives at [in-context-ralm alternatives](/tools/ai21labs-in-context-ralm/alternatives) and [filco alternatives](/tools/zorazrw-filco/alternatives) ([in-context-ralm markdown twin](/tools/ai21labs-in-context-ralm/alternatives.md), [filco markdown twin](/tools/zorazrw-filco/alternatives.md)), 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](/compare/ai21labs-in-context-ralm-vs-zorazrw-filco.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, in-context-ralm or filco?

in-context-ralm: Archived. 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 in-context-ralm and filco?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [in-context-ralm trust report](/tools/ai21labs-in-context-ralm/trust); [filco trust report](/tools/zorazrw-filco/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=ai21labs-in-context-ralm`](/api/graphcanon/graph?tool=ai21labs-in-context-ralm)
- LLM index: [/llms.txt](/llms.txt)
- Full corpus: [/llms-full.txt](/llms-full.txt)

_GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_