langchain-baseten
Integration package connecting Baseten and LangChain
Decision gist · record as of 2026-08-14
Yes. The package is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and provides straightforward integration for developers already using LangChain who want to use Baseten models. Install friction is low and Python version support is current. Suitable for production use if you have a Baseten account and models deployed.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.10 or later and a valid Baseten API key (set via BASETEN_API_KEY environment variable or passed directly).
- Low friction installation with three runtime dependencies.
- Package is actively maintained with a recent release (18 days old) and no known vulnerabilities.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for commercial and open-source projects.
last release 2026-07-27 (18 days) · last repo commit 2026-07-31
0 known vulnerabilities (OSV.dev, 2026-08-14) · 116,100 downloads/mo, #12,218 on PyPI
Alternatives
Verify before relying
pip install langchain-baseten
from langchain_baseten import ChatBaseten
model = ChatBaseten(
model="zai-org/GLM-5.2",
api_key="your-api-key"
)
response = model.invoke("Hello, how are you?")- Whether Baseten's Performance Client dependency introduces any system-level requirements or compilation steps.
- Specific latency or throughput characteristics when using Model APIs vs. dedicated deployment URLs.
- Whether custom models deployed to Baseten require additional configuration beyond model URL and API key.
What it is and what it does
langchain-baseten bridges Baseten's hosted language models and embeddings into LangChain's ecosystem. It provides two main classes: ChatBaseten for conversational models and BasetenEmbeddings for vector generation. Both support Baseten's Model APIs (using model slugs on shared infrastructure) and dedicated deployment URLs for custom or performance-optimized models.
The package handles authentication via API key and environment variables, manages HTTP communication with Baseten's endpoints, and wraps responses in LangChain's standard message and embedding formats. It depends on langchain-core for the base interfaces, langchain-openai for OpenAI-compatible protocol handling, and baseten-performance-client for optimized embedding operations.
Use it for
- Build a chatbot using Baseten-hosted models (e.g., GLM-5.2) within a LangChain application without custom API code.
- Generate embeddings for semantic search or RAG pipelines using Baseten's dedicated embedding deployments.
- Switch between shared Model APIs and custom dedicated deployments without changing application code.
- Integrate Baseten models into LangChain chains and agents that already use other LangChain providers.
- Use environment variables to manage Baseten credentials across development and production deployments.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
The package is actively maintained, has no known vulnerabilities, carries a permissive MIT license, and provides straightforward integration for developers already using LangChain who want to use Baseten models. Install friction is low and Python version support is current. Suitable for production use if you have a Baseten account and models deployed.
Install
langchain-baseten on PyPI
Before you install
Low friction installation with three runtime dependencies. Package is actively maintained with a recent release (18 days old) and no known vulnerabilities.
Requires Python 3.10 or later and a valid Baseten API key (set via BASETEN_API_KEY environment variable or passed directly).
License in practice
MIT license permits unrestricted use, modification, and distribution with minimal restrictions—suitable for commercial and open-source projects.
Quickstart
pip install langchain-baseten
from langchain_baseten import ChatBaseten
model = ChatBaseten(
model="zai-org/GLM-5.2",
api_key="your-api-key"
)
response = model.invoke("Hello, how are you?")Verify before relying
- Whether Baseten's Performance Client dependency introduces any system-level requirements or compilation steps.
- Specific latency or throughput characteristics when using Model APIs vs. dedicated deployment URLs.
- Whether custom models deployed to Baseten require additional configuration beyond model URL and API key.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <4.0.0,>=3.10.0 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesbaseten-performance-clientlangchain-corelangchain-openai |
| Maintenance | Actively maintained 18 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 116,100 / month, #12,218 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 :: 3Programming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Scientific/Engineering :: Artificial Intelligence |
Evidence: langchain_baseten-0.2.3-py3-none-any.whl
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See also baseten-performance-client · langchain-sambanova · unique-toolkit · langchain-elasticsearch · llama-index-embeddings-langchain · langchain-together · langchain-cohere · langchain-google-genai · langchain-openai · langchain-ibm