feat: add component lifecycle handling

[anakin87]

Related Issues

• fixes https://github.com/deepset-ai/haystack-private/issues/384

Proposed Changes:

Discussed in https://github.com/deepset-ai/haystack-private/issues/384#issuecomment-4740431488

How did you test it?

• CI, new tests
• opened a PR on core integrations to spot issues in the inheriting components from touched OpenAI components: try lifecycle Haystack branch haystack-core-integrations#3467
  • several failures, also unrelated (I think we should start testing v3 branch soon on core integrations)
  • took a look at failures related to modified OpenAI components: I think we might fix them with some if/else to temporarily be compatible with Haystack 2.x and 3.x
• also tried to implement the new lifecycle handling approach to other integrations (Bedrock, Nvidia and Sentence Transformers) to see if it holds and it turned out to be feasible

Notes for the reviewer

This PR is big. I created a single one to test everything.
Once we agree on the general approach, I'd be happy to split it into smaller parts if you prefer.

Checklist

• I have read the contributors guidelines and the code of conduct.
• I have updated the related issue with new insights and changes.
• I have added unit tests and updated the docstrings.
• I've used one of the conventional commit types for my PR title: fix:, feat:, build:, chore:, ci:, docs:, style:, refactor:, perf:, test: and added ! in case the PR includes breaking changes.
• I have documented my code.
• I have added a release note file, following the contributors guidelines.
• I have run pre-commit hooks and fixed any issue.

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Project	Deployment	Actions	Updated (UTC)
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Coverage report

Click to see where and how coverage changed

File	Statements	Missing	Coverage	Coverage (new stmts)	Lines missing
haystack/components/agents
agent.py
haystack/components/embedders
azure_document_embedder.py
azure_text_embedder.py
openai_document_embedder.py					250, 295-302, 375-379
openai_text_embedder.py					221-223, 241-245
haystack/components/evaluators
llm_evaluator.py
haystack/components/extractors
llm_metadata_extractor.py
haystack/components/extractors/image
llm_document_content_extractor.py
haystack/components/fetchers
link_content.py					192-200, 267
haystack/components/generators
openai_image_generator.py
haystack/components/generators/chat
azure.py					213
fallback.py
openai.py
openai_responses.py
haystack/components/preprocessors
embedding_based_document_splitter.py
recursive_splitter.py
haystack/components/query
query_expander.py
haystack/components/rankers
llm_ranker.py					320-321
haystack/components/retrievers
multi_query_embedding_retriever.py
multi_query_text_retriever.py
multi_retriever.py
haystack/components/routers
llm_messages_router.py
haystack/core/pipeline
base.py
pipeline.py
haystack/core/super_component
super_component.py					67
Project Total

The report is truncated to 25 files out of 26. To see the full report, please visit the workflow summary page.

This report was generated by python-coverage-comment-action

[sjrl]

Looks good! Would be nice if @mpangrazzi could also give it a lookover before merging

[mpangrazzi]

Looks good! I've left a minor comment, your choice if to handle it or not.

[mpangrazzi]

Minor thing, but I was thinking that warm_up_async and warm_up are relying on a single self._warmed_up flag.

One could expect that warm_up warms up sync resources (ie sync client), and warm_up_async the async ones. So this single flag could be a bit inconsistent with other components behaviour. WDYT?

[anakin87]

Good point. I'll fix this.

[claude]

Code review

No issues found. Checked for bugs and CLAUDE.md compliance.

[claude]

Code review

No issues found. Checked for bugs and CLAUDE.md compliance.