llama-index-llms-ibm
llama-index llms IBM watsonx.ai integration
Decision gist · record as of 2026-08-14
Yes, if you are already using LlamaIndex and need to integrate IBM watsonx.ai models. The package has low install friction, permissive licensing, and active maintenance. No known vulnerabilities. Install it as a straightforward provider plugin for LlamaIndex.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires IBM Cloud API key set as WATSONX_APIKEY environment variable and a valid watsonx.ai project or space ID.
- Low install friction with three runtime dependencies.
- Actively maintained as of the latest release.
License · maintenance · safety
MIT (permissive) — MIT license permits commercial and private use with minimal restrictions.
last release 2026-02-17 (178 days)
0 known vulnerabilities (OSV.dev, 2026-08-14) · 87,198 downloads/mo, #13,810 on PyPI
Alternatives
Verify before relying
pip install llama-index-llms-ibm
from llama_index.llms.ibm import WatsonxLLM
watsonx_llm = WatsonxLLM(
model_id="ibm/granite-4-h-small",
url="YOUR_URL",
project_id="YOUR_PROJECT_ID"
)
response = watsonx_llm.complete("What is generative AI?")- Whether all IBM watsonx.ai foundation models are supported or only a subset.
- Performance characteristics and latency expectations for different model sizes.
- Rate limiting or quota behavior when calling IBM's API through this integration.
What it is and what it does
This package bridges LlamaIndex's LLM abstraction layer with IBM's watsonx.ai foundation models. It wraps the ibm-watsonx-ai SDK to let you call IBM models (like granite variants) using LlamaIndex's standard completion and chat interfaces, supporting both synchronous and streaming modes.
You instantiate a WatsonxLLM class with your IBM Cloud credentials, project ID, and model choice, then call .complete(), .chat(), .stream_complete(), or .stream_chat() just as you would with any other LlamaIndex LLM provider. The package handles authentication, parameter marshalling, and response parsing against the IBM API.
Use it for
- Build a RAG pipeline using LlamaIndex with IBM's foundation models as the inference backend.
- Stream responses from IBM watsonx.ai models in a chat application via LlamaIndex.
- Experiment with different IBM granite models without rewriting your LlamaIndex application code.
- Use IBM watsonx.ai in a multi-provider LLM setup where LlamaIndex abstracts the provider differences.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are already using LlamaIndex and need to integrate IBM watsonx.ai models.
The package has low install friction, permissive licensing, and active maintenance. No known vulnerabilities. Install it as a straightforward provider plugin for LlamaIndex.
Install
llama-index-llms-ibm on PyPI
Before you install
Low install friction with three runtime dependencies. Actively maintained as of the latest release.
Requires IBM Cloud API key set as WATSONX_APIKEY environment variable and a valid watsonx.ai project or space ID.
License in practice
MIT license permits commercial and private use with minimal restrictions.
Quickstart
pip install llama-index-llms-ibm
from llama_index.llms.ibm import WatsonxLLM
watsonx_llm = WatsonxLLM(
model_id="ibm/granite-4-h-small",
url="YOUR_URL",
project_id="YOUR_PROJECT_ID"
)
response = watsonx_llm.complete("What is generative AI?")Verify before relying
- Whether all IBM watsonx.ai foundation models are supported or only a subset.
- Performance characteristics and latency expectations for different model sizes.
- Rate limiting or quota behavior when calling IBM's API through this integration.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release <3.14,>=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 3 packagesibm-watsonx-aillama-index-corepyarrow |
| Maintenance | Actively maintained 178 days since the last release |
| First released | |
| Downloads | 87,198 / month, #13,810 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
Evidence: llama_index_llms_ibm-0.7.0.post1-py3-none-any.whl
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See also ibm-watsonx-ai · llama-index-embeddings-ibm · langchain-ibm · llama-index-llms-vertex · llama-index-llms-openai · llama-index-llms-gemini · ai21 · llama-index-llms-openai-like · llama-index-multi-modal-llms-openai · llama-index-llms-google-genai