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OvidijusParsiunas
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OvidijusParsiunas/deep-chat

Fully customizable AI chatbot component for your website

TypeScript ◇ ai MIT
★3.7KSTARS
⑂454FORKS
!39ISSUES
🏆#1,304GLOBAL RANK
🔥5DAYS TRENDING
🚀
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Star History

Continuous Observations
Interactive star growth chart for OvidijusParsiunas/deep-chat
CSV

Momentum

+93

STARS · LAST 30 DAYS

3

PER DAY

#184

MOST-STARRED TypeScript

Window7 days30 days90 days
Stars gained+21+93+270
Per day333
Forks gained+2+9+23

deep-chat gained 93 stars in the last 30 days, about 3 a day, and now has 3.7K. It is about 4 years old and has averaged roughly 931 stars a year. It ranks #184 among TypeScript repositories and #1,304 across all languages on GitHubRepo.

Trending Record

deep-chat has maintained a continuous presence across global trending indexes, peaking at #800. Below is the 30-day activity profile:

💡 Overview

deep-chat is an open-source project written in TypeScript: Fully customizable AI chatbot component for your website.

Engineered for speed, consistency, and developer ease, it solves common hurdles in ai, ai-chatbot, chat. It provides clear interfaces, comprehensive configuration options, and seamless integration with existing tools across the modern development stack.

⚡ Key Features

1

Optimized execution pipeline written in TypeScript for predictable speed.

2

Zero-friction configuration with comprehensive sensible defaults out of the box.

3

Cross-platform runtime support across Linux, macOS, and Windows environments.

4

Strong typing and modular architecture designed for easy extension and maintainability.

5

Standardized CLI and API interfaces for smooth integration into CI/CD workflows.

6

Active community maintenance with regular dependency updates and security patches.

📥 Installation

terminal
$ npm install deep-chat

⚙ System Requirements

Platforms

  • • macOS
  • • Linux
  • • Windows

Runtime & Dependencies

Node.js >= 18, npm, pnpm or bun

Architecture

x86_64, ARM64 (Apple Silicon & Graviton)

🧠 How It Works

deep-chat coordinates its core functionality through a modular TypeScript pipeline. It parses configuration parameters, validates inputs, and resolves dependencies asynchronously. By minimizing runtime overhead and keeping allocations localized, it delivers predictable performance in both local development environments and automated production workloads.

🎯 Production Use Cases

Autonomous AI Agents

Orchestrate intelligent workflows and tool-calling routines with deep-chat.

Model Inference & Prompting

Integrate fast, local or cloud-hosted generative AI models directly into production code.

Context Memory & RAG

Augment language models with dynamic vector retrieval and structured project memory.

Developer Productivity

Automate repetitive engineering tasks, code generation, and test creation using AI agents.

🚀 Getting Started

1

Install deep-chat using your package manager: `npm install deep-chat`

2

Initialize your project workspace or configuration file for deep-chat.

3

Import deep-chat into your codebase or invoke it directly from your terminal.

4

Execute your test suite or run `deep-chat --help` to verify successful setup.

👍 Strengths

Active community backing with 3,721 GitHub stars and verified adoption.
Permissive open-source distribution under the MIT license.
Built in TypeScript for high execution speed and developer familiarity.
Cross-platform compatibility across modern Linux, macOS, and Windows environments.
Clean modular design allowing flexible configuration and pipeline integration.

⚠️ Considerations

Requires familiarity with TypeScript and modern CLI workflows.
Ecosystem extensions may require manual configuration depending on environment constraints.
Active development roadmap means breaking API changes may occur across major versions.

⇄ Alternatives & Direct Competitors

💡
Open Source Alternative to OpenAI API & ChatGPT Replaces proprietary subscriptions (Pay-per-token pricing with zero private data guarantees) with self-hosted freedom.
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👥 Who Should Use This

Developers and engineering teams building with TypeScript, seeking reliable, tested, and actively maintained tooling for production workloads.

🏆 Nearby in the Rankings

OvidijusParsiunas/deep-chat is currently ranked #1,304 by stars across every repository tracked on GitHubRepo. These are adjacent projects:

RankRepositoryLanguageStarsAction
#1,298 openrewrite/rewrite Java ★ 3.8K Compare ↗
#1,300 blacktop/ipsw Go ★ 3.7K Compare ↗
#1,301 lunarphp/lunar PHP ★ 3.7K Compare ↗
#1,302 thoughtbot/clearance Ruby ★ 3.7K Compare ↗
#1,303 0x90d/videoduplicatefinder C# ★ 3.7K Compare ↗
#1,304 OvidijusParsiunas/deep-chat This Project TypeScript ★ 3.7K
#1,305 pluginaweek/state_machine Ruby ★ 3.7K Compare ↗
#1,306 microsoft/mcp C# ★ 3.7K Compare ↗
#1,306 yaojingang/GEOFlow PHP ★ 3.7K Compare ↗
#1,308 spring-io/initializr Java ★ 3.7K Compare ↗
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Frequently Asked Questions

What does deep-chat do? +

Fully customizable AI chatbot component for your website

What language is deep-chat written in? +

The primary language is TypeScript. Topics include: ai, ai-chatbot, chat, chatbot, chatgpt.

Is deep-chat actively maintained? +

Yes, the last recorded push was on Sep 27, 2026 with 39 open issues being tracked.

How many stars does deep-chat have? +

deep-chat has 3,723 stars and 454 forks on GitHub.

How does deep-chat rank among GitHub repositories? +

With 3,723 stars, OvidijusParsiunas/deep-chat is ranked #1,304 globally across all repositories tracked on GitHubRepo and #184 among TypeScript projects.

What license is deep-chat distributed under? +

The repository reports a MIT license. Always verify the repository LICENSE file for legal terms.

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