Update haystack-ai requirement from >=2.9.0 to >=2.28.0

[dependabot]

Updates the requirements on haystack-ai to permit the latest version.

Release notes

Sourced from haystack-ai's releases.

v2.28.0

Release Notes

v2.28.0

Upgrade Notes

• As part of the migration from requests to httpx, request_with_retry and async_request_with_retry (in haystack.utils.requests_utils) no longer raise requests.exceptions.RequestException on failure; they now raise httpx.HTTPError instead. This also affects HuggingFaceTEIRanker, which relies on these utilities. Users catching requests.exceptions.RequestException should update their code to catch httpx.HTTPError.

• The LLM component now requires user_prompt to be provided at initialization and it must contain at least one Jinja2 template variable (e.g. {{ variable_name }}). This ensures the component always exposes at least one required input socket, which is necessary for correct pipeline scheduling.

  required_variables now defaults to "*" (all variables in user_prompt are required), and passing an empty list raises a ValueError.

  If you are affected: update any code that instantiates LLM without a user_prompt, or with a user_prompt that has no template variables, to include at least one variable.

  Before:

  llm = LLM(chat_generator=OpenAIChatGenerator(), system_prompt="You are helpful.")

  After:

  llm = LLM(
      chat_generator=OpenAIChatGenerator(),
      system_prompt="You are helpful.",
      user_prompt='{% message role="user" %}{{ query }}{% endmessage %}',
  )

• Agent.run() and Agent.run_async() now require messages as an explicit argument (no longer optional). If you were relying on the default None value in Haystack version 2.26 or 2.27, pass an empty list instead:

  agent.run(messages=[], ...)

  LLM.run() and LLM.run_async() are unaffected — they still accept None and default to an empty list internally.

New Features

• Tools and components can now declare a State (or State | None) parameter in their signature to receive the live agent State object at invocation time — no extra wiring needed.

  For function-based tools created with @tool or create_tool_from_function, add a state parameter annotated as State:

  from haystack.components.agents import State
  from haystack.tools import tool
  @​tool

... (truncated)

Commits

• 66af637 bump version to 2.28.0
• 3ac0aae bump version to 2.28.0-rc2
• 484f227 refactor!: Make user_prompt required in LLM (#11152)
• 8d2dfa4 bump version to 2.28.0-rc1
• 26c4a2e fix: require messages input parameter in Agent component (#11147)
• c2d1bb8 docs: added YAML example to OpenAIGenerator (#11145)
• 3b5e774 docs: add YAML example to DocumentSplitter documentation (#11142)
• aa6454f docs: add chatpromptbuilder yaml (#11143)
• f297288 docs: add YAML example to OpenAIChatGenerator (#11146)
• 5bd14f3 docs: fix Langfuse Agent tracing snippet (#11137)
• Additional commits viewable in compare view

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