Bump haystack-ai from 2.5.0 to 2.29.0

[dependabot]

Bumps haystack-ai from 2.5.0 to 2.29.0.

Release notes

Sourced from haystack-ai's releases.

v2.29.0

⭐️ Highlights

🔍 Combine Retrievers with MultiRetriever and TextEmbeddingRetriever

Two new retriever components make it easier to build hybrid search pipelines. MultiRetriever runs multiple text retrievers in parallel and merges their results into a single deduplicated list, ranked by reciprocal rank fusion by default. You can selectively enable or disable individual retrievers at runtime using the active_retrievers parameter. This is useful when you want to skip the embedding retriever for short or keyword-only queries, for example.

TextEmbeddingRetriever wraps an embedding-based retriever together with a text embedder into a single component, making it compatible with MultiRetriever by implementing the TextRetriever protocol. Here's how to combine BM25 and embedding retrieval in a single component:

from haystack.components.retrievers import MultiRetriever, TextEmbeddingRetriever
from haystack.components.retrievers.in_memory import InMemoryBM25Retriever, InMemoryEmbeddingRetriever
from haystack.components.embedders import SentenceTransformersTextEmbedder
retriever = MultiRetriever(
retrievers={
"bm25": InMemoryBM25Retriever(document_store=doc_store),
"embedding": TextEmbeddingRetriever(
retriever=InMemoryEmbeddingRetriever(document_store=doc_store),
text_embedder=SentenceTransformersTextEmbedder(model="sentence-transformers/all-MiniLM-L6-v2"),
),
},
top_k=3,
)
Run all retrievers
result = retriever.run(query="green energy sources")
Run only the BM25 retriever
result = retriever.run(query="green energy sources", active_retrievers=["bm25"])

⬆️ Upgrade Notes

• LLM.run and LLM.run_async no longer accept messages and streaming_callback as positional arguments — they must now be passed as keyword arguments. Update any direct calls accordingly:

  # Before
  llm.run([message], my_callback)
  After
  llm.run(messages=[message], streaming_callback=my_callback)

🚀 New Features

• Add run_async to CacheChecker, enabling it to be used in AsyncPipeline without blocking the event loop.

⚡️ Enhancement Notes

... (truncated)

Commits

• 63929e0 bump version to 2.29.0
• 42ad2af bump version to 2.29.0-rc2
• b0c6603 feat!: Update LLM component to dynamically set messages as required or option...
• 6e19535 bump version to 2.29.0-rc1
• 505a606 docs: add FalkorDB integration documentation (#11293)
• 67f99b8 docs: highlight image support in Agents (#11291)
• 6a9f89a build(deps): bump actions/add-to-project from 1.0.2 to 2.0.0 (#11263)
• 8a63653 docs: sync Core Integrations API reference (docling) on Docusaurus (#11292)
• 29e41eb docs: add DoclingServeConverter documentation page (#11276)
• 392d4c0 docs: better highlight mcp integration with Agent (#11290)
• Additional commits viewable in compare view

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[dependabot]

Superseded by #9.