Fix LlamaIndexHook docs to stop claiming Ollama/vLLM support - #72013
Merged
gopidesupavan merged 1 commit intoSep 4, 2026
Merged
Conversation
uros-b
approved these changes
Aug 24, 2026
Member
|
+1, LGTM! |
ColtenOuO
reviewed
Aug 24, 2026
Contributor
There was a problem hiding this comment.
Thanks! LGTM overall
Should we also update provider.yaml in this PR?
The connection UI and the provider registry both read from provider.yaml, so the claim this PR is removing is still visible to users.
Two places in the llamaindex connection-types entry still carry it:
- hook-class-name: airflow.providers.common.ai.hooks.llamaindex.LlamaIndexHook
hook-name: "LlamaIndex"
connection-type: llamaindex
external-services:
- OpenAI
- Ollama # <--
- vLLM # <--
ui-field-behaviour:
...
placeholders:
host: "https://api.openai.com/v1 (optional, for custom endpoints / Ollama)" # <--I think we should also remove that and re-generate the get_provider_info.py
WDYT
ColtenOuO
reviewed
Aug 24, 2026
Lee-W
force-pushed
the
fix-common-ai-llamaindex-scope
branch
from
August 25, 2026 12:21
d18390e to
0f61a77
Compare
The class docstring, the host field description, and the UI placeholder said host= could point LlamaIndexHook at Ollama or vLLM. get_llm() and get_embedding_model() return LlamaIndex's OpenAI / OpenAIEmbedding classes, which validate model= client-side against LlamaIndex's OpenAI-only model-name allowlists before any request is sent, so an Ollama/vLLM model name is rejected regardless of host. Document the real constraint and why it exists instead of the non-existent Ollama/vLLM support.
Lee-W
force-pushed
the
fix-common-ai-llamaindex-scope
branch
from
August 27, 2026 11:42
0f61a77 to
f46ed37
Compare
Member
Author
|
|
gopidesupavan
approved these changes
Sep 4, 2026
imrichardwu
pushed a commit
to imrichardwu/airflow
that referenced
this pull request
Sep 11, 2026
…72013) The class docstring, the host field description, and the UI placeholder said host= could point LlamaIndexHook at Ollama or vLLM. get_llm() and get_embedding_model() return LlamaIndex's OpenAI / OpenAIEmbedding classes, which validate model= client-side against LlamaIndex's OpenAI-only model-name allowlists before any request is sent, so an Ollama/vLLM model name is rejected regardless of host. Document the real constraint and why it exists instead of the non-existent Ollama/vLLM support.
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
4 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
The class docstring, the host field description, and the UI placeholder said host= could point LlamaIndexHook at Ollama or vLLM. get_llm() and get_embedding_model() return LlamaIndex's OpenAI / OpenAIEmbedding classes, which validate model= client-side against LlamaIndex's OpenAI-only model-name allowlists before any request is sent, so an Ollama/vLLM model name is rejected regardless of host. Document the real constraint and why it exists instead of the non-existent Ollama/vLLM support.
Was generative AI tooling used to co-author this PR?
Generated-by: [Tool Name] following the guidelines
{pr_number}.significant.rst, in airflow-core/newsfragments. You can add this file in a follow-up commit after the PR is created so you know the PR number.