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Add AIMLAPI workflow and update examples
Introduces a new GitHub Actions workflow for AIMLAPI integration testing. Updates example scripts to add noqa comments for print statements and refines message list construction. Modifies AIMLAPIChatGenerator to include an explicit 'openai_endpoint' parameter and clarifies a type ignore comment.
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‎.github/workflows/aimlapi.yml‎

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# This workflow comes from https://github.com/ofek/hatch-mypyc
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# https://github.com/ofek/hatch-mypyc/blob/5a198c0ba8660494d02716cfc9d79ce4adfb1442/.github/workflows/test.yml
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name: Test / aimlapi
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on:
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schedule:
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- cron: "0 0 * * *"
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pull_request:
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paths:
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- "integrations/aimlapi/**"
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- "!integrations/aimlapi/*.md"
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- ".github/workflows/aimlapi.yml"
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defaults:
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run:
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working-directory: integrations/aimlapi
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concurrency:
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group: aimlapi-${{ github.head_ref }}
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cancel-in-progress: true
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env:
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PYTHONUNBUFFERED: "1"
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FORCE_COLOR: "1"
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AIMLAPI_API_KEY: ${{ secrets.AIMLAPI_API_KEY }}
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jobs:
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run:
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name: Python ${{ matrix.python-version }} on ${{ startsWith(matrix.os, 'macos-') && 'macOS' || startsWith(matrix.os, 'windows-') && 'Windows' || 'Linux' }}
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runs-on: ${{ matrix.os }}
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strategy:
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fail-fast: false
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matrix:
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os: [ubuntu-latest, windows-latest, macos-latest]
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python-version: ["3.9", "3.13"]
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steps:
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- name: Support longpaths
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if: matrix.os == 'windows-latest'
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working-directory: .
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run: git config --system core.longpaths true
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- uses: actions/checkout@v5
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- name: Set up Python ${{ matrix.python-version }}
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uses: actions/setup-python@v6
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with:
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python-version: ${{ matrix.python-version }}
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- name: Install Hatch
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run: pip install --upgrade hatch
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- name: Lint
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if: matrix.python-version == '3.9' && runner.os == 'Linux'
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run: hatch run fmt-check && hatch run test:types
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- name: Generate docs
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if: matrix.python-version == '3.9' && runner.os == 'Linux'
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run: hatch run docs
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- name: Run tests
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run: hatch run test:cov-retry
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- name: Run unit tests with lowest direct dependencies
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run: |
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hatch run uv pip compile pyproject.toml --resolution lowest-direct --output-file requirements_lowest_direct.txt
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hatch run uv pip install -r requirements_lowest_direct.txt
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hatch run test:unit
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# Since this integration inherits from OpenAIChatGenerator, we run ALL tests with Haystack main branch to catch regressions
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- name: Nightly - run tests with Haystack main branch
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if: github.event_name == 'schedule'
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run: |
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hatch env prune
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hatch run uv pip install git+https://github.com/deepset-ai/haystack.git@main
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hatch run test:all
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- name: Send event to Datadog for nightly failures
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if: failure() && github.event_name == 'schedule'
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uses: ./.github/actions/send_failure
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with:
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title: |
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Core integrations nightly tests failure: ${{ github.workflow }}
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api-key: ${{ secrets.CORE_DATADOG_API_KEY }}

‎integrations/aimlapi/examples/aimlapi_basic_example.py‎

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def main() -> None:
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"""Generate a response without using any tools."""
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generator = AIMLAPIChatGenerator(
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model="openai/gpt-5-chat-latest"
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)
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generator = AIMLAPIChatGenerator(model="openai/gpt-5-chat-latest")
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messages = [
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ChatMessage.from_system("You are a concise assistant."),
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reply = generator.run(messages=messages)["replies"][0]
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print(f"assistant response: {reply.text}")
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print(f"assistant response: {reply.text}") # noqa: T201
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if __name__ == "__main__":

‎integrations/aimlapi/examples/aimlapi_with_tools_example.py‎

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tool_invoker = ToolInvoker(tools=[weather_tool])
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client = AIMLAPIChatGenerator(
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model="openai/gpt-5-mini-2025-08-07"
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)
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client = AIMLAPIChatGenerator(model="openai/gpt-5-mini-2025-08-07")
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messages = [
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ChatMessage.from_system(
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"You help users by calling the provided tools when they are relevant."
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),
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ChatMessage.from_system("You help users by calling the provided tools when they are relevant."),
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ChatMessage.from_user("What's the weather in Tokyo today?"),
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]
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print("Requesting a tool call from the model...")
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print("Requesting a tool call from the model...") # noqa: T201
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tool_request = client.run(
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messages=messages,
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tools=[weather_tool],
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generation_kwargs={
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"tool_choice": {"type": "function", "function": {"name": "weather"}}
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},
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generation_kwargs={"tool_choice": {"type": "function", "function": {"name": "weather"}}},
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)["replies"][0]
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print(f"assistant tool request: {tool_request}")
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print(f"assistant tool request: {tool_request}") # noqa: T201
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if not tool_request.tool_calls:
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print("No tool call was produced by the model.")
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print("No tool call was produced by the model.") # noqa: T201
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return
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tool_messages = tool_invoker.run(messages=[tool_request])["tool_messages"]
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for tool_message in tool_messages:
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for tool_result in tool_message.tool_call_results:
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print(f"tool output: {tool_result.result}")
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print(f"tool output: {tool_result.result}") # noqa: T201
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follow_up_messages = messages + [tool_request, *tool_messages]
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follow_up_messages = [*messages, tool_request, *tool_messages]
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final_reply = client.run(
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messages=follow_up_messages,
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tools=[weather_tool],
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generation_kwargs={"tool_choice": "none"},
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)["replies"][0]
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print(f"assistant final answer: {final_reply.text}")
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print(f"assistant final answer: {final_reply.text}") # noqa: T201
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if __name__ == "__main__":

‎integrations/aimlapi/src/haystack_integrations/components/generators/aimlapi/chat/chat_generator.py‎

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return {
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"model": self.model,
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"messages": aimlapi_formatted_messages,
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"messages": aimlapi_formatted_messages, # type: ignore[arg-type] # openai expects list of specific message types
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"stream": streaming_callback is not None,
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"n": num_responses,
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**aimlapi_tools,
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"extra_body": {**generation_kwargs},
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"extra_headers": {**extra_headers},
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"openai_endpoint": "create",
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}

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