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feat: GPT4Generator (#5744)
* add gpt4generator * add e2e * add tests * reno * fix e2e * Update test/preview/components/generators/openai/test_gpt4_generator.py Co-authored-by: Stefano Fiorucci <44616784+anakin87@users.noreply.github.com> --------- Co-authored-by: Stefano Fiorucci <44616784+anakin87@users.noreply.github.com>
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@ -2,21 +2,21 @@ import os
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import pytest
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import openai
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from haystack.preview.components.generators.openai.gpt35 import GPT35Generator
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from haystack.preview.components.generators.openai.gpt4 import GPT4Generator
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@pytest.mark.skipif(
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not os.environ.get("OPENAI_API_KEY", None),
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reason="Export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.",
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)
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def test_gpt35_generator_run():
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component = GPT35Generator(api_key=os.environ.get("OPENAI_API_KEY"), n=1)
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@pytest.mark.parametrize("generator_class,model_name", [(GPT35Generator, "gpt-3.5"), (GPT4Generator, "gpt-4")])
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def test_gpt35_generator_run(generator_class, model_name):
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component = generator_class(api_key=os.environ.get("OPENAI_API_KEY"), n=1)
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results = component.run(prompt="What's the capital of France?")
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assert len(results["replies"]) == 1
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assert "Paris" in results["replies"][0]
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assert len(results["metadata"]) == 1
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assert "gpt-3.5-turbo" in results["metadata"][0]["model"]
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assert model_name in results["metadata"][0]["model"]
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assert "stop" == results["metadata"][0]["finish_reason"]
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@ -24,8 +24,9 @@ def test_gpt35_generator_run():
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not os.environ.get("OPENAI_API_KEY", None),
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reason="Export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.",
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)
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def test_gpt35_generator_run_wrong_model_name():
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component = GPT35Generator(model_name="something-obviously-wrong", api_key=os.environ.get("OPENAI_API_KEY"), n=1)
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@pytest.mark.parametrize("generator_class", [GPT35Generator, GPT4Generator])
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def test_gpt35_generator_run_wrong_model_name(generator_class):
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component = generator_class(model_name="something-obviously-wrong", api_key=os.environ.get("OPENAI_API_KEY"), n=1)
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with pytest.raises(openai.InvalidRequestError, match="The model `something-obviously-wrong` does not exist"):
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component.run(prompt="What's the capital of France?")
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@ -34,7 +35,8 @@ def test_gpt35_generator_run_wrong_model_name():
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not os.environ.get("OPENAI_API_KEY", None),
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reason="Export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.",
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)
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def test_gpt35_generator_run_streaming():
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@pytest.mark.parametrize("generator_class,model_name", [(GPT35Generator, "gpt-3.5"), (GPT4Generator, "gpt-4")])
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def test_gpt35_generator_run_streaming(generator_class, model_name):
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class Callback:
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def __init__(self):
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self.responses = ""
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@ -44,14 +46,14 @@ def test_gpt35_generator_run_streaming():
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return chunk
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callback = Callback()
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component = GPT35Generator(os.environ.get("OPENAI_API_KEY"), streaming_callback=callback, n=1)
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component = generator_class(os.environ.get("OPENAI_API_KEY"), streaming_callback=callback, n=1)
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results = component.run(prompt="What's the capital of France?")
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assert len(results["replies"]) == 1
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assert "Paris" in results["replies"][0]
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assert len(results["metadata"]) == 1
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assert "gpt-3.5-turbo" in results["metadata"][0]["model"]
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assert model_name in results["metadata"][0]["model"]
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assert "stop" == results["metadata"][0]["finish_reason"]
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assert callback.responses == results["replies"][0]
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@ -13,6 +13,9 @@ from haystack.preview import component, default_from_dict, default_to_dict, Dese
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logger = logging.getLogger(__name__)
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API_BASE_URL = "https://api.openai.com/v1"
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@dataclass
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class _ChatMessage:
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content: str
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@ -44,7 +47,7 @@ class GPT35Generator:
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model_name: str = "gpt-3.5-turbo",
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system_prompt: Optional[str] = None,
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streaming_callback: Optional[Callable] = None,
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api_base_url: str = "https://api.openai.com/v1",
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api_base_url: str = API_BASE_URL,
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**kwargs,
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):
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"""
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71
haystack/preview/components/generators/openai/gpt4.py
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71
haystack/preview/components/generators/openai/gpt4.py
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@ -0,0 +1,71 @@
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from typing import Optional, Callable
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import logging
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from haystack.preview import component
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from haystack.preview.components.generators.openai.gpt35 import GPT35Generator, API_BASE_URL
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logger = logging.getLogger(__name__)
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@component
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class GPT4Generator(GPT35Generator):
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"""
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LLM Generator compatible with GPT4 large language models.
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Queries the LLM using OpenAI's API. Invocations are made using OpenAI SDK ('openai' package)
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See [OpenAI GPT4 API](https://platform.openai.com/docs/guides/chat) for more details.
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"""
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def __init__(
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self,
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api_key: str,
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model_name: str = "gpt-4",
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system_prompt: Optional[str] = None,
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streaming_callback: Optional[Callable] = None,
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api_base_url: str = API_BASE_URL,
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**kwargs,
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):
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"""
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Creates an instance of GPT4Generator for OpenAI's GPT-4 model.
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:param api_key: The OpenAI API key.
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:param model_name: The name of the model to use.
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:param system_prompt: An additional message to be sent to the LLM at the beginning of each conversation.
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Typically, a conversation is formatted with a system message first, followed by alternating messages from
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the 'user' (the "queries") and the 'assistant' (the "responses"). The system message helps set the behavior
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of the assistant. For example, you can modify the personality of the assistant or provide specific
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instructions about how it should behave throughout the conversation.
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:param streaming_callback: A callback function that is called when a new token is received from the stream.
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The callback function should accept two parameters: the token received from the stream and **kwargs.
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The callback function should return the token to be sent to the stream. If the callback function is not
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provided, the token is printed to stdout.
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:param api_base_url: The OpenAI API Base url, defaults to `https://api.openai.com/v1`.
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:param kwargs: Other parameters to use for the model. These parameters are all sent directly to the OpenAI
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endpoint. See OpenAI [documentation](https://platform.openai.com/docs/api-reference/chat) for more details.
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Some of the supported parameters:
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- `max_tokens`: The maximum number of tokens the output text can have.
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- `temperature`: What sampling temperature to use. Higher values mean the model will take more risks.
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Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.
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- `top_p`: An alternative to sampling with temperature, called nucleus sampling, where the model
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considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens
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comprising the top 10% probability mass are considered.
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- `n`: How many completions to generate for each prompt. For example, if the LLM gets 3 prompts and n is 2,
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it will generate two completions for each of the three prompts, ending up with 6 completions in total.
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- `stop`: One or more sequences after which the LLM should stop generating tokens.
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- `presence_penalty`: What penalty to apply if a token is already present at all. Bigger values mean
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the model will be less likely to repeat the same token in the text.
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- `frequency_penalty`: What penalty to apply if a token has already been generated in the text.
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Bigger values mean the model will be less likely to repeat the same token in the text.
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- `logit_bias`: Add a logit bias to specific tokens. The keys of the dictionary are tokens and the
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values are the bias to add to that token.
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"""
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super().__init__(
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api_key=api_key,
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model_name=model_name,
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system_prompt=system_prompt,
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streaming_callback=streaming_callback,
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api_base_url=api_base_url,
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**kwargs,
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)
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@ -0,0 +1,3 @@
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preview:
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- Adds `GPT4Generator`, an LLM component based on `GPT35Generator`
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110
test/preview/components/generators/openai/test_gpt4_generator.py
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110
test/preview/components/generators/openai/test_gpt4_generator.py
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@ -0,0 +1,110 @@
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from unittest.mock import patch, Mock
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import pytest
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from haystack.preview.components.generators.openai.gpt4 import GPT4Generator, API_BASE_URL
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from haystack.preview.components.generators.openai.gpt35 import default_streaming_callback
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class TestGPT4Generator:
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@pytest.mark.unit
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def test_init_default(self):
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component = GPT4Generator(api_key="test-api-key")
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assert component.system_prompt is None
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assert component.api_key == "test-api-key"
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assert component.model_name == "gpt-4"
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assert component.streaming_callback is None
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assert component.api_base_url == API_BASE_URL
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assert component.model_parameters == {}
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@pytest.mark.unit
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def test_init_with_parameters(self):
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callback = lambda x: x
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component = GPT4Generator(
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api_key="test-api-key",
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model_name="gpt-4-32k",
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system_prompt="test-system-prompt",
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max_tokens=10,
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some_test_param="test-params",
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streaming_callback=callback,
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api_base_url="test-base-url",
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)
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assert component.system_prompt == "test-system-prompt"
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assert component.api_key == "test-api-key"
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assert component.model_name == "gpt-4-32k"
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assert component.streaming_callback == callback
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assert component.api_base_url == "test-base-url"
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assert component.model_parameters == {"max_tokens": 10, "some_test_param": "test-params"}
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@pytest.mark.unit
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def test_to_dict_default(self):
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component = GPT4Generator(api_key="test-api-key")
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data = component.to_dict()
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assert data == {
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"type": "GPT4Generator",
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"init_parameters": {
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"api_key": "test-api-key",
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"model_name": "gpt-4",
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"system_prompt": None,
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"streaming_callback": None,
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"api_base_url": API_BASE_URL,
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},
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}
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@pytest.mark.unit
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def test_to_dict_with_parameters(self):
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component = GPT4Generator(
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api_key="test-api-key",
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model_name="gpt-4-32k",
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system_prompt="test-system-prompt",
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max_tokens=10,
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some_test_param="test-params",
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streaming_callback=default_streaming_callback,
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api_base_url="test-base-url",
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)
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data = component.to_dict()
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assert data == {
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"type": "GPT4Generator",
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"init_parameters": {
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"api_key": "test-api-key",
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"model_name": "gpt-4-32k",
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"system_prompt": "test-system-prompt",
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"max_tokens": 10,
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"some_test_param": "test-params",
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"api_base_url": "test-base-url",
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"streaming_callback": "haystack.preview.components.generators.openai.gpt35.default_streaming_callback",
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},
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}
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@pytest.mark.unit
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def test_from_dict_default(self):
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data = {"type": "GPT4Generator", "init_parameters": {"api_key": "test-api-key"}}
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component = GPT4Generator.from_dict(data)
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assert component.system_prompt is None
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assert component.api_key == "test-api-key"
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assert component.model_name == "gpt-4"
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assert component.streaming_callback is None
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assert component.api_base_url == API_BASE_URL
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assert component.model_parameters == {}
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@pytest.mark.unit
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def test_from_dict(self):
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data = {
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"type": "GPT4Generator",
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"init_parameters": {
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"api_key": "test-api-key",
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"model_name": "gpt-4-32k",
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"system_prompt": "test-system-prompt",
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"max_tokens": 10,
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"some_test_param": "test-params",
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"api_base_url": "test-base-url",
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"streaming_callback": "haystack.preview.components.generators.openai.gpt35.default_streaming_callback",
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},
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}
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component = GPT4Generator.from_dict(data)
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assert component.system_prompt == "test-system-prompt"
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assert component.api_key == "test-api-key"
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assert component.model_name == "gpt-4-32k"
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assert component.streaming_callback == default_streaming_callback
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assert component.api_base_url == "test-base-url"
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assert component.model_parameters == {"max_tokens": 10, "some_test_param": "test-params"}
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