---
title: "OpenChat vs llm-app"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/opencx-labs-openchat-vs-pathwaycom-llm-app"
tools: ["opencx-labs-openchat", "pathwaycom-llm-app"]
---

# OpenChat vs llm-app

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick OpenChat when openChat is primarily JavaScript; llm-app is Jupyter Notebook; pick llm-app when llm-app is primarily Jupyter Notebook; OpenChat is JavaScript.

[OpenChat](https://open.cx) reports 5.2k GitHub stars, 644 forks, and 37 open issues, last pushed Feb 27, 2024. [llm-app](https://pathway.com/developers/templates/) has 59k stars, 1.4k forks, and 10 open issues, last pushed Jul 5, 2026. Figures are from public GitHub metadata via [OpenChat's repository](https://github.com/opencx-labs/OpenChat) and [llm-app's repository](https://github.com/pathwaycom/llm-app).

| | [OpenChat](/tools/opencx-labs-openchat.md) | [llm-app](/tools/pathwaycom-llm-app.md) |
| --- | --- | --- |
| Tagline | LLMs custom-chatbots console ⚡ | Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. |
| Stars | 5,240 | 59,068 |
| Forks | 644 | 1,432 |
| Open issues | 37 | 10 |
| Language | JavaScript | Jupyter Notebook |
| Adopt for | - | llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | MIT |
| Categories | LLM Frameworks, Vector Databases | Data & Retrieval, LLM Frameworks, Vector Databases |

## Trust and health

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

| | [OpenChat](/tools/opencx-labs-openchat.md) | [llm-app](/tools/pathwaycom-llm-app.md) |
| --- | --- | --- |
| Maintenance | Archived (8%) | Very active (96%) |
| Days since push | 864d | 5d |
| Archived on GitHub | Yes | No |
| Open issues (now) | 37 | 10 |
| Security scan | No criticals | No lockfile |
| Full report | [trust report](/tools/opencx-labs-openchat/trust.md) | [trust report](/tools/pathwaycom-llm-app/trust.md) |

## Decision facts: llm-app

- **Requirements:** Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.
- **Adopt for:** llm-app offers pre-configured cloud deployment templates designed specifically for creating AI-driven applications such as chatbots and machine learning projects leveraging Hugging Face models. It supports direct integrz

## Choose when

### Choose OpenChat if…

- OpenChat is primarily JavaScript; llm-app is Jupyter Notebook.
- Tags unique to OpenChat: javascript.
- OpenChat ships Docker support for self-hosted deployment.

### Choose llm-app if…

- llm-app is primarily Jupyter Notebook; OpenChat is JavaScript.
- Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others..
- Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation.
- Also covers Data & Retrieval.
- - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.

## When NOT to use OpenChat

- OpenChat is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

## When NOT to use llm-app

- - You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app.
- - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.

## Common questions

### What is the difference between OpenChat and llm-app?

OpenChat: LLMs custom-chatbots console ⚡. llm-app: Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data.. See the comparison table for live GitHub stats and shared categories.

### When should I choose OpenChat over llm-app?

Choose OpenChat over llm-app when OpenChat is primarily JavaScript; llm-app is Jupyter Notebook; Tags unique to OpenChat: javascript; OpenChat ships Docker support for self-hosted deployment.

### When should I choose llm-app over OpenChat?

Choose llm-app over OpenChat when llm-app is primarily Jupyter Notebook; OpenChat is JavaScript; Requirements: Requires Docker; The tool is Docker-friendly and designed to ensure synchronization with cloud-based storage solutions among others.; Tags unique to llm-app: chatbot, hugging-face, llm, retrieval-augmented-generation; Also covers Data & Retrieval; - You need a ready-to-run solution that directly integrates with various data sources like Sharepoint, Google Drive, S3, Kafka, PostgreSQL, and live APIs.

### When should I avoid OpenChat?

OpenChat is archived on GitHub. Prefer an active alternative unless you maintain a private fork or need a frozen dependency. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Vector Databases: Don't reach for a dedicated vector DB under ~100k vectors; pgvector on your existing Postgres is simpler to operate.

### When should I avoid llm-app?

- You require custom deployment configurations that extend beyond the pre-set cloud templates available through llm-app. - There’s a need for tightly integrated support with data sources or APIs not explicitly mentioned, such as specialized CRM systems (Salesforce), which may lack direct template support in llm-app.

### Is OpenChat or llm-app more popular on GitHub?

llm-app has more GitHub stars (59,068 vs 5,240). Stars measure visibility, not whether either tool fits your constraints.

### Are OpenChat and llm-app open source?

Yes - both are open-source projects on GitHub (OpenChat: MIT, llm-app: MIT).

### Where can I find alternatives to OpenChat or llm-app?

GraphCanon lists graph-backed alternatives at [OpenChat alternatives](/tools/opencx-labs-openchat/alternatives) and [llm-app alternatives](/tools/pathwaycom-llm-app/alternatives) ([OpenChat markdown twin](/tools/opencx-labs-openchat/alternatives.md), [llm-app markdown twin](/tools/pathwaycom-llm-app/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/opencx-labs-openchat-vs-pathwaycom-llm-app.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, OpenChat or llm-app?

OpenChat: Archived. llm-app: Very active. 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 OpenChat and llm-app?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [OpenChat trust report](/tools/opencx-labs-openchat/trust); [llm-app trust report](/tools/pathwaycom-llm-app/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=opencx-labs-openchat`](/api/graphcanon/graph?tool=opencx-labs-openchat)
- 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/_
