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AI CLIENT / CONVERSATIONS & PROMPTS
Chatbox
A cross-platform AI client for organizing model conversations, reusable prompts and readable answers, with a free community edition and local-model connections.
Official repository example of Chatbox conversation formatting; the pictured interface is an earlier versionExplore the image ↓
What you can do with it
What this tool is for
Chatbox is useful for people who want a consistent AI chat interface without organizing their work around a single model website. The community client connects to supported providers and can also connect to local models through a service such as Ollama. It provides conversation organization, reusable instructions and formatting, while the connected model supplies the actual response.
The free route is the community software plus a suitable local model service. Installing the client does not download every model or grant access to paid APIs. The official product also advertises file chat, knowledge features, search and Work Mode; availability depends on the particular release and service. Check that distinction before assuming a feature shown on the commercial website is included in every community build.
01
An editing companion
02
Technical study notes
03
Bilingual rewriting
04
A local chat front end
A closer look at the product
Official product image. Click to inspect the details.
Product interface and examples
Key features, practical tasks
Capabilities in practice
- Multiple provider connections: Configure a supported provider once, then use its available models in a familiar interface. Check model names and account access instead of assuming a website subscription automatically authorizes a different API.
- Local-model access: Connect Ollama or another documented local route. Chatbox is the client, so the separate runtime must already be running and reachable before local chat can work.
- Reusable prompts: Keep recurring writing, explanation or translation instructions together. A useful preset specifies the audience, source boundaries and output format, reducing the need to paste a long setup every time.
- Message context: Quote relevant messages and keep unrelated projects in separate conversations. Supplying a focused excerpt often works better than relying on a long thread to retain every earlier detail.
- Readable answers: Markdown, mathematical notation and highlighted code make technical explanations easier to review. Correct visual formatting does not establish that a formula, reference or code example is accurate.
- Desktop conveniences: Streaming responses, keyboard shortcuts and a dark theme make repeated chat work more comfortable. These interface features do not change the speed or reasoning quality of the upstream model.
- Broader product ecosystem: Official web and mobile options complement the desktop application. The product site also presents document, knowledge and agent workflows; verify the selected edition and any service allowance before relying on them.
Get started, step by step
- 01
Choose the intended edition
- 02
Connect a provider
- 03
Prepare one reusable prompt
- 04
Review and preserve the result
A practical first workflow
A practical first workflow
- Choose the intended edition. Read the community repository and obtain an official build for your platform. Distinguish the community client from a bundled hosted AI service.
- Connect a provider. For the local free route, start the model runtime and select the appropriate connection. For a paid API, use the intended account and check its usage conditions.
- Prepare one reusable prompt. Define the task, audience and output structure, then start with a short input whose correct interpretation you already know.
- Review and preserve the result. Check factual changes and source gaps. Keep important reviewed content and configuration recoverable before upgrading or changing devices.
Example prompt or task: Rewrite the supplied paragraph for a beginner. Preserve names and numbers, define unfamiliar terms and flag any claim that cannot be established from the paragraph. Do not add new product features.
This is an editorial starting task. Compare two short results using the same source and requirements; do not judge model quality from formatting alone.
Find the right plan for you
Free community client
Explore official plans ↗Free software Model services can charge separately
The community client and Chatbox’s bundled AI services have different terms. A local model requires its own runtime.
What is free and what can cost extra
The repository identifies the community edition as GPLv3 software. It can be used with a separately installed local model service, avoiding per-request cloud inference charges while using your own hardware. Model storage, RAM and electricity remain part of the local setup.
Chatbox’s bundled hosted services and third-party model APIs are separate. Their allowances, paid plans and supported features can change. This listing does not promise a fixed number of free cloud messages or that every advertised Work Mode or knowledge feature is included in the community release.
A few things worth knowing
Frequently asked questions
What is free in Chatbox?
The community client is free under GPLv3. Connected inference services have their own costs; a local runtime provides a route without cloud per-request charges.
Does Chatbox include a local model?
The client can connect to local model services, but the runtime and model weights must be prepared separately.
Is all my data automatically offline?
No. Local conversation storage and local inference are different. A configured cloud provider still receives the content required for its request.
Why does sending a message fail?
Check the selected provider, endpoint reachability, credentials and model access. A working client interface does not prove the remote model service is available.
Does a provider quota error mean the client is broken?
Often it describes the connected provider account. Inspect that account’s current allowance and billing rather than repeatedly reinstalling Chatbox.
Are the website and community features identical?
Not necessarily. Check the installed edition and current release notes before planning around a feature presented elsewhere in the product ecosystem.
Can I use prompts across tasks?
Yes, reusable instructions help, but keep task-specific source material and unrelated conversations separate so old context does not distort a new request.
The details behind your decision
Explore platforms, inputs and outputs, licensing, and access requirements.
Four useful starting projects
Four useful starting projects
- An editing companion: Save tone, audience and terminology requirements. Give each draft a new conversation and compare the edited text with the original facts before publishing.
- Technical study notes: Ask a model to explain a small code sample or equation, using readable formatting. Check the explanation against course material or official documentation.
- Bilingual rewriting: Request a translation and a separate list of ambiguous terms. Keep product names and important numbers fixed instead of letting a fluency-focused rewrite silently change them.
- A local chat front end: Use the free client with a local runtime for bounded note processing. Test the model connection with a short task before introducing longer documents.
Platforms, inputs, outputs and setup
Platforms, inputs, outputs and setup
Community desktop builds cover Windows, macOS and Linux; the official product also lists web, iOS and Android access. Match the operating system and processor to the actual download, and do not assume desktop settings or locally stored conversations automatically synchronize to another device.
The client renders text, code and mathematical content supplied by models. File, image and knowledge workflows require appropriate application support and model capabilities. A text-only model does not become a vision model merely because another edition of the interface displays an image-upload control.
Data, permissions and licensing
Data, permissions and licensing
The community project describes local data storage, but requests to remote providers necessarily cross a network boundary. Review which model is selected before entering private material and distinguish local files from content sent for generation.
GPLv3 applies to the community code. Model licenses, provider terms and the rights to submitted files are separate. The official repository illustration on this page shows an earlier interface and is included to demonstrate formatting, not to claim that every current menu has the same appearance.
Sources, documentation and help
Official sources and review date
Official sources and review date
Reviewed October 3, 2026. Product facts come from the official sources below. Suggested projects, prompts and review methods are FindGoodAI editorial guidance, not measured performance results.
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