mirror of
https://github.com/deepset-ai/haystack.git
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296e31c182
* Starting to refactor type util tests to be more systematic * refactoring * Expand tests * Update to type utils * Add missing subclass check * Expand and refactor tests, introduce type_validation Literal * More test refactoring * Test refactoring, adding type validation variable to pipeline base * Update relaxed version of type checking to pass all newly added tests * trim whitespace * Add tests * cleanup * Updates docstrings * Add reno * docs * Fix mypy and add docstrings * Changes based on advice from Tobi * Remove unused imports * Doc strings * Add connection type validation to to_dict and from_dict * Update tests * Fix test * Also save connection_type_validation at global pipeline level * Fix tests * Remove connection type validation from the connect level, only keep at pipeline level * Formatting * Fix tests * formatting
312 lines
14 KiB
Python
312 lines
14 KiB
Python
# SPDX-FileCopyrightText: 2022-present deepset GmbH <info@deepset.ai>
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#
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# SPDX-License-Identifier: Apache-2.0
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import os
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import pytest
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from openai import OpenAIError
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from haystack import Pipeline
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from haystack.components.generators.chat import AzureOpenAIChatGenerator
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from haystack.components.generators.utils import print_streaming_chunk
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from haystack.dataclasses import ChatMessage, ToolCall
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from haystack.tools.tool import Tool
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from haystack.utils.auth import Secret
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@pytest.fixture
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def tools():
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tool_parameters = {"type": "object", "properties": {"city": {"type": "string"}}, "required": ["city"]}
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tool = Tool(
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name="weather",
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description="useful to determine the weather in a given location",
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parameters=tool_parameters,
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function=lambda x: x,
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)
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return [tool]
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class TestAzureOpenAIChatGenerator:
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def test_init_default(self, monkeypatch):
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monkeypatch.setenv("AZURE_OPENAI_API_KEY", "test-api-key")
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component = AzureOpenAIChatGenerator(azure_endpoint="some-non-existing-endpoint")
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assert component.client.api_key == "test-api-key"
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assert component.azure_deployment == "gpt-4o-mini"
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assert component.streaming_callback is None
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assert not component.generation_kwargs
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def test_init_fail_wo_api_key(self, monkeypatch):
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monkeypatch.delenv("AZURE_OPENAI_API_KEY", raising=False)
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monkeypatch.delenv("AZURE_OPENAI_AD_TOKEN", raising=False)
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with pytest.raises(OpenAIError):
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AzureOpenAIChatGenerator(azure_endpoint="some-non-existing-endpoint")
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def test_init_with_parameters(self, tools):
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component = AzureOpenAIChatGenerator(
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api_key=Secret.from_token("test-api-key"),
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azure_endpoint="some-non-existing-endpoint",
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streaming_callback=print_streaming_chunk,
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generation_kwargs={"max_tokens": 10, "some_test_param": "test-params"},
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tools=tools,
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tools_strict=True,
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)
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assert component.client.api_key == "test-api-key"
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assert component.azure_deployment == "gpt-4o-mini"
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assert component.streaming_callback is print_streaming_chunk
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assert component.generation_kwargs == {"max_tokens": 10, "some_test_param": "test-params"}
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assert component.tools == tools
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assert component.tools_strict
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def test_to_dict_default(self, monkeypatch):
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monkeypatch.setenv("AZURE_OPENAI_API_KEY", "test-api-key")
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component = AzureOpenAIChatGenerator(azure_endpoint="some-non-existing-endpoint")
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data = component.to_dict()
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assert data == {
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"type": "haystack.components.generators.chat.azure.AzureOpenAIChatGenerator",
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"init_parameters": {
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"api_key": {"env_vars": ["AZURE_OPENAI_API_KEY"], "strict": False, "type": "env_var"},
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"azure_ad_token": {"env_vars": ["AZURE_OPENAI_AD_TOKEN"], "strict": False, "type": "env_var"},
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"api_version": "2023-05-15",
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"azure_endpoint": "some-non-existing-endpoint",
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"azure_deployment": "gpt-4o-mini",
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"organization": None,
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"streaming_callback": None,
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"generation_kwargs": {},
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"timeout": 30.0,
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"max_retries": 5,
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"default_headers": {},
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"tools": None,
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"tools_strict": False,
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},
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}
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def test_to_dict_with_parameters(self, monkeypatch):
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monkeypatch.setenv("ENV_VAR", "test-api-key")
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component = AzureOpenAIChatGenerator(
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api_key=Secret.from_env_var("ENV_VAR", strict=False),
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azure_ad_token=Secret.from_env_var("ENV_VAR1", strict=False),
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azure_endpoint="some-non-existing-endpoint",
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timeout=2.5,
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max_retries=10,
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generation_kwargs={"max_tokens": 10, "some_test_param": "test-params"},
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)
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data = component.to_dict()
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assert data == {
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"type": "haystack.components.generators.chat.azure.AzureOpenAIChatGenerator",
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"init_parameters": {
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"api_key": {"env_vars": ["ENV_VAR"], "strict": False, "type": "env_var"},
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"azure_ad_token": {"env_vars": ["ENV_VAR1"], "strict": False, "type": "env_var"},
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"api_version": "2023-05-15",
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"azure_endpoint": "some-non-existing-endpoint",
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"azure_deployment": "gpt-4o-mini",
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"organization": None,
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"streaming_callback": None,
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"timeout": 2.5,
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"max_retries": 10,
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"generation_kwargs": {"max_tokens": 10, "some_test_param": "test-params"},
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"tools": None,
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"tools_strict": False,
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"default_headers": {},
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},
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}
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def test_from_dict(self, monkeypatch):
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monkeypatch.setenv("AZURE_OPENAI_API_KEY", "test-api-key")
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monkeypatch.setenv("AZURE_OPENAI_AD_TOKEN", "test-ad-token")
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data = {
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"type": "haystack.components.generators.chat.azure.AzureOpenAIChatGenerator",
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"init_parameters": {
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"api_key": {"env_vars": ["AZURE_OPENAI_API_KEY"], "strict": False, "type": "env_var"},
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"azure_ad_token": {"env_vars": ["AZURE_OPENAI_AD_TOKEN"], "strict": False, "type": "env_var"},
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"api_version": "2023-05-15",
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"azure_endpoint": "some-non-existing-endpoint",
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"azure_deployment": "gpt-4o-mini",
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"organization": None,
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"streaming_callback": None,
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"generation_kwargs": {},
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"timeout": 30.0,
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"max_retries": 5,
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"default_headers": {},
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"tools": [
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{
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"type": "haystack.tools.tool.Tool",
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"data": {
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"description": "description",
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"function": "builtins.print",
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"name": "name",
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"parameters": {"x": {"type": "string"}},
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},
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}
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],
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"tools_strict": False,
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},
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}
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generator = AzureOpenAIChatGenerator.from_dict(data)
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assert isinstance(generator, AzureOpenAIChatGenerator)
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assert generator.api_key == Secret.from_env_var("AZURE_OPENAI_API_KEY", strict=False)
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assert generator.azure_ad_token == Secret.from_env_var("AZURE_OPENAI_AD_TOKEN", strict=False)
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assert generator.api_version == "2023-05-15"
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assert generator.azure_endpoint == "some-non-existing-endpoint"
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assert generator.azure_deployment == "gpt-4o-mini"
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assert generator.organization is None
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assert generator.streaming_callback is None
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assert generator.generation_kwargs == {}
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assert generator.timeout == 30.0
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assert generator.max_retries == 5
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assert generator.default_headers == {}
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assert generator.tools == [
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Tool(name="name", description="description", parameters={"x": {"type": "string"}}, function=print)
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]
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assert generator.tools_strict == False
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def test_pipeline_serialization_deserialization(self, tmp_path, monkeypatch):
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monkeypatch.setenv("AZURE_OPENAI_API_KEY", "test-api-key")
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generator = AzureOpenAIChatGenerator(azure_endpoint="some-non-existing-endpoint")
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p = Pipeline()
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p.add_component(instance=generator, name="generator")
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assert p.to_dict() == {
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"metadata": {},
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"max_runs_per_component": 100,
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"connection_type_validation": True,
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"components": {
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"generator": {
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"type": "haystack.components.generators.chat.azure.AzureOpenAIChatGenerator",
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"init_parameters": {
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"azure_endpoint": "some-non-existing-endpoint",
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"azure_deployment": "gpt-4o-mini",
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"organization": None,
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"api_version": "2023-05-15",
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"streaming_callback": None,
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"generation_kwargs": {},
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"timeout": 30.0,
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"max_retries": 5,
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"api_key": {"type": "env_var", "env_vars": ["AZURE_OPENAI_API_KEY"], "strict": False},
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"azure_ad_token": {"type": "env_var", "env_vars": ["AZURE_OPENAI_AD_TOKEN"], "strict": False},
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"default_headers": {},
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"tools": None,
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"tools_strict": False,
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},
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}
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},
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"connections": [],
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}
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p_str = p.dumps()
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q = Pipeline.loads(p_str)
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assert p.to_dict() == q.to_dict(), "Pipeline serialization/deserialization w/ AzureOpenAIChatGenerator failed."
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@pytest.mark.integration
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@pytest.mark.skipif(
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not os.environ.get("AZURE_OPENAI_API_KEY", None) or not os.environ.get("AZURE_OPENAI_ENDPOINT", None),
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reason=(
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"Please export env variables called AZURE_OPENAI_API_KEY containing "
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"the Azure OpenAI key, AZURE_OPENAI_ENDPOINT containing "
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"the Azure OpenAI endpoint URL to run this test."
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),
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)
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def test_live_run(self):
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chat_messages = [ChatMessage.from_user("What's the capital of France")]
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component = AzureOpenAIChatGenerator(organization="HaystackCI")
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results = component.run(chat_messages)
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assert len(results["replies"]) == 1
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message: ChatMessage = results["replies"][0]
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assert "Paris" in message.text
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assert "gpt-4o-mini" in message.meta["model"]
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assert message.meta["finish_reason"] == "stop"
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@pytest.mark.integration
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@pytest.mark.skipif(
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not os.environ.get("AZURE_OPENAI_API_KEY", None) or not os.environ.get("AZURE_OPENAI_ENDPOINT", None),
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reason=(
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"Please export env variables called AZURE_OPENAI_API_KEY containing "
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"the Azure OpenAI key, AZURE_OPENAI_ENDPOINT containing "
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"the Azure OpenAI endpoint URL to run this test."
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),
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)
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def test_live_run_with_tools(self, tools):
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chat_messages = [ChatMessage.from_user("What's the weather like in Paris?")]
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component = AzureOpenAIChatGenerator(organization="HaystackCI", tools=tools)
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results = component.run(chat_messages)
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assert len(results["replies"]) == 1
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message = results["replies"][0]
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assert not message.texts
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assert not message.text
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assert message.tool_calls
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tool_call = message.tool_call
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assert isinstance(tool_call, ToolCall)
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assert tool_call.tool_name == "weather"
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assert tool_call.arguments == {"city": "Paris"}
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assert message.meta["finish_reason"] == "tool_calls"
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# additional tests intentionally omitted as they are covered by test_openai.py
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class TestAzureOpenAIChatGeneratorAsync:
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def test_init_should_also_create_async_client_with_same_args(self, tools):
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component = AzureOpenAIChatGenerator(
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api_key=Secret.from_token("test-api-key"),
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azure_endpoint="some-non-existing-endpoint",
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streaming_callback=print_streaming_chunk,
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generation_kwargs={"max_tokens": 10, "some_test_param": "test-params"},
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tools=tools,
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tools_strict=True,
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)
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assert component.async_client.api_key == "test-api-key"
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assert component.azure_deployment == "gpt-4o-mini"
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assert component.streaming_callback is print_streaming_chunk
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assert component.generation_kwargs == {"max_tokens": 10, "some_test_param": "test-params"}
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assert component.tools == tools
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assert component.tools_strict
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@pytest.mark.integration
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@pytest.mark.skipif(
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not os.environ.get("AZURE_OPENAI_API_KEY", None) or not os.environ.get("AZURE_OPENAI_ENDPOINT", None),
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reason=(
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"Please export env variables called AZURE_OPENAI_API_KEY containing "
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"the Azure OpenAI key, AZURE_OPENAI_ENDPOINT containing "
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"the Azure OpenAI endpoint URL to run this test."
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),
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)
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@pytest.mark.asyncio
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async def test_live_run_async(self):
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chat_messages = [ChatMessage.from_user("What's the capital of France")]
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component = AzureOpenAIChatGenerator(generation_kwargs={"n": 1})
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results = await component.run_async(chat_messages)
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assert len(results["replies"]) == 1
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message: ChatMessage = results["replies"][0]
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assert "Paris" in message.text
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assert "gpt-4o" in message.meta["model"]
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assert message.meta["finish_reason"] == "stop"
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@pytest.mark.integration
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@pytest.mark.skipif(
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not os.environ.get("AZURE_OPENAI_API_KEY", None) or not os.environ.get("AZURE_OPENAI_ENDPOINT", None),
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reason=(
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"Please export env variables called AZURE_OPENAI_API_KEY containing "
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"the Azure OpenAI key, AZURE_OPENAI_ENDPOINT containing "
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"the Azure OpenAI endpoint URL to run this test."
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),
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)
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@pytest.mark.asyncio
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async def test_live_run_with_tools_async(self, tools):
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chat_messages = [ChatMessage.from_user("What's the weather like in Paris?")]
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component = AzureOpenAIChatGenerator(tools=tools)
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results = await component.run_async(chat_messages)
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assert len(results["replies"]) == 1
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message = results["replies"][0]
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assert not message.texts
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assert not message.text
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assert message.tool_calls
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tool_call = message.tool_call
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assert isinstance(tool_call, ToolCall)
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assert tool_call.tool_name == "weather"
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assert tool_call.arguments == {"city": "Paris"}
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assert message.meta["finish_reason"] == "tool_calls"
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# additional tests intentionally omitted as they are covered by test_openai.py
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