chatlas
A simple and consistent interface for chatting with LLMs
Decision gist · record as of 2026-08-14
Yes. Chatlas is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem—provider abstraction for LLM chat apps. MIT licensing is permissive. The 11 dependencies are all stable, widely-used packages. Install it if you're building multi-provider LLM chat applications or want to avoid vendor lock-in.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later.
- You must provide API credentials (e.g., OPENAI_API_KEY environment variable) for the chosen model provider.
- Low install friction with a pure Python wheel.
License · maintenance · safety
MIT (permissive) — MIT license (permissive) means you can use, modify, and distribute chatlas freely in commercial and private projects with minimal restrictions.
last release 2026-08-12 (2 days) · last repo commit 2026-08-14 · 174 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 131,545 downloads/mo, #11,585 on PyPI
Alternatives
Verify before relying
pip install chatlas
from chatlas import ChatOpenAI
chat = ChatOpenAI(
model="gpt-4-mini",
system_prompt="You are a helpful assistant."
)
chat.chat("Hello, how are you?")- Whether all 11 runtime dependencies are strictly required or if some are optional for specific providers.
- Performance characteristics and latency overhead compared to direct provider SDK calls.
- Exact scope of tool registration and function calling support across different providers.
What it is and what it does
Chatlas is a Python library that abstracts away the differences between LLM providers (OpenAI, Anthropic, and others) by offering a single, consistent Chat client interface. Instead of learning each provider's API separately, you instantiate a Chat client for your chosen model, set a system prompt, register tools, and call a single chat() method. The library handles credential management, message formatting, and tool calling under the hood.
It's built on top of widely-used dependencies like httpx, pydantic, and openai, and targets developers building multi-turn conversational applications who want to avoid vendor lock-in or easily swap providers. The package is in active development (released 2026-08-12, last commit 2026-08-14) and supports Python 3.10 through 3.14.
Use it for
- Build a chatbot that can switch between OpenAI and Anthropic models without rewriting client code.
- Register Python functions as tools so the LLM can call them autonomously during conversation.
- Prototype LLM applications quickly without learning each provider's specific API and authentication patterns.
- Manage multi-turn conversations with consistent message history and system prompt handling across providers.
- Deploy chat applications that abstract provider details, making it easier to migrate or A/B test models.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
Chatlas is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem—provider abstraction for LLM chat apps. MIT licensing is permissive. The 11 dependencies are all stable, widely-used packages. Install it if you're building multi-provider LLM chat applications or want to avoid vendor lock-in.
Install
chatlas on PyPI
Before you install
Low install friction with a pure Python wheel. Active maintenance with a release 2 days old and last commit on 2026-08-14. Depends on 11 runtime packages including httpx, openai, pydantic, and rich—all widely used and stable.
Requires Python 3.10 or later. You must provide API credentials (e.g., OPENAI_API_KEY environment variable) for the chosen model provider.
License in practice
MIT license (permissive) means you can use, modify, and distribute chatlas freely in commercial and private projects with minimal restrictions.
Quickstart
pip install chatlas
from chatlas import ChatOpenAI
chat = ChatOpenAI(
model="gpt-4-mini",
system_prompt="You are a helpful assistant."
)
chat.chat("Hello, how are you?")Verify before relying
- Whether all 11 runtime dependencies are strictly required or if some are optional for specific providers.
- Performance characteristics and latency overhead compared to direct provider SDK calls.
- Exact scope of tool registration and function calling support across different providers.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 11 packageshttpxhttpx2jinja2openaiopentelemetry-apiorjsonplatformdirspydanticrequestsrichtyping-extensions |
| Maintenance | Actively maintained 2 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 131,545 / month, #11,585 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14 |
Evidence: chatlas-0.21.1-py3-none-any.whl
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