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Remove unnecessary GPT4Generator class (#5863)

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* Remove GPT4Generator class

* Rename GPT35Generator to GPTGenerator

* Fix tests

* Release notes
This commit is contained in:
Silvano Cerza 2023-09-22 11:05:06 +02:00 committed by GitHub
parent f3dc9edd26
commit cc4f95bf51
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5 changed files with 44 additions and 227 deletions
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8
haystack/preview/components/generators/openai/gpt35.py → haystack/preview/components/generators/openai/gpt.py
View File

@ -33,12 +33,12 @@ def default_streaming_callback(chunk):
@component
class GPT35Generator:
class GPTGenerator:
"""
LLM Generator compatible with GPT3.5 (ChatGPT) large language models.
LLM Generator compatible with GPT (ChatGPT) large language models.
Queries the LLM using OpenAI's API. Invocations are made using OpenAI SDK ('openai' package)
See [OpenAI GPT3.5 API](https://platform.openai.com/docs/guides/chat) for more details.
See [OpenAI GPT API](https://platform.openai.com/docs/guides/chat) for more details.
"""
def __init__(
@ -115,7 +115,7 @@ class GPT35Generator:
)
@classmethod
def from_dict(cls, data: Dict[str, Any]) -> "GPT35Generator":
def from_dict(cls, data: Dict[str, Any]) -> "GPTGenerator":
"""
Deserialize this component from a dictionary.
"""

71
haystack/preview/components/generators/openai/gpt4.py
View File

@ -1,71 +0,0 @@
from typing import Optional, Callable
import logging
from haystack.preview import component
from haystack.preview.components.generators.openai.gpt35 import GPT35Generator, API_BASE_URL
logger = logging.getLogger(__name__)
@component
class GPT4Generator(GPT35Generator):
"""
LLM Generator compatible with GPT4 large language models.
Queries the LLM using OpenAI's API. Invocations are made using OpenAI SDK ('openai' package)
See [OpenAI GPT4 API](https://platform.openai.com/docs/guides/chat) for more details.
"""
def __init__(
self,
api_key: str,
model_name: str = "gpt-4",
system_prompt: Optional[str] = None,
streaming_callback: Optional[Callable] = None,
api_base_url: str = API_BASE_URL,
**kwargs,
):
"""
Creates an instance of GPT4Generator for OpenAI's GPT-4 model.
:param api_key: The OpenAI API key.
:param model_name: The name of the model to use.
:param system_prompt: An additional message to be sent to the LLM at the beginning of each conversation.
Typically, a conversation is formatted with a system message first, followed by alternating messages from
the 'user' (the "queries") and the 'assistant' (the "responses"). The system message helps set the behavior
of the assistant. For example, you can modify the personality of the assistant or provide specific
instructions about how it should behave throughout the conversation.
:param streaming_callback: A callback function that is called when a new token is received from the stream.
The callback function should accept two parameters: the token received from the stream and **kwargs.
The callback function should return the token to be sent to the stream. If the callback function is not
provided, the token is printed to stdout.
:param api_base_url: The OpenAI API Base url, defaults to `https://api.openai.com/v1`.
:param kwargs: Other parameters to use for the model. These parameters are all sent directly to the OpenAI
endpoint. See OpenAI [documentation](https://platform.openai.com/docs/api-reference/chat) for more details.
Some of the supported parameters:
- `max_tokens`: The maximum number of tokens the output text can have.
- `temperature`: What sampling temperature to use. Higher values mean the model will take more risks.
Try 0.9 for more creative applications, and 0 (argmax sampling) for ones with a well-defined answer.
- `top_p`: An alternative to sampling with temperature, called nucleus sampling, where the model
considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens
comprising the top 10% probability mass are considered.
- `n`: How many completions to generate for each prompt. For example, if the LLM gets 3 prompts and n is 2,
it will generate two completions for each of the three prompts, ending up with 6 completions in total.
- `stop`: One or more sequences after which the LLM should stop generating tokens.
- `presence_penalty`: What penalty to apply if a token is already present at all. Bigger values mean
the model will be less likely to repeat the same token in the text.
- `frequency_penalty`: What penalty to apply if a token has already been generated in the text.
Bigger values mean the model will be less likely to repeat the same token in the text.
- `logit_bias`: Add a logit bias to specific tokens. The keys of the dictionary are tokens and the
values are the bias to add to that token.
"""
super().__init__(
api_key=api_key,
model_name=model_name,
system_prompt=system_prompt,
streaming_callback=streaming_callback,
api_base_url=api_base_url,
**kwargs,
)

2
releasenotes/notes/chatgpt-llm-generator-d043532654efe684.yaml
View File

@ -1,2 +1,2 @@
preview:
- Introduce `GPT35Generator`, a class that can generate completions using OpenAI Chat models like GPT3.5 and GPT4.
- Introduce `GPTGenerator`, a class that can generate completions using OpenAI Chat models like GPT3.5 and GPT4.

110
test/preview/components/generators/openai/test_gpt4_generator.py
View File

@ -1,110 +0,0 @@
from unittest.mock import patch, Mock
import pytest
from haystack.preview.components.generators.openai.gpt4 import GPT4Generator, API_BASE_URL
from haystack.preview.components.generators.openai.gpt35 import default_streaming_callback
class TestGPT4Generator:
@pytest.mark.unit
def test_init_default(self):
component = GPT4Generator(api_key="test-api-key")
assert component.system_prompt is None
assert component.api_key == "test-api-key"
assert component.model_name == "gpt-4"
assert component.streaming_callback is None
assert component.api_base_url == API_BASE_URL
assert component.model_parameters == {}
@pytest.mark.unit
def test_init_with_parameters(self):
callback = lambda x: x
component = GPT4Generator(
api_key="test-api-key",
model_name="gpt-4-32k",
system_prompt="test-system-prompt",
max_tokens=10,
some_test_param="test-params",
streaming_callback=callback,
api_base_url="test-base-url",
)
assert component.system_prompt == "test-system-prompt"
assert component.api_key == "test-api-key"
assert component.model_name == "gpt-4-32k"
assert component.streaming_callback == callback
assert component.api_base_url == "test-base-url"
assert component.model_parameters == {"max_tokens": 10, "some_test_param": "test-params"}
@pytest.mark.unit
def test_to_dict_default(self):
component = GPT4Generator(api_key="test-api-key")
data = component.to_dict()
assert data == {
"type": "GPT4Generator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-4",
"system_prompt": None,
"streaming_callback": None,
"api_base_url": API_BASE_URL,
},
}
@pytest.mark.unit
def test_to_dict_with_parameters(self):
component = GPT4Generator(
api_key="test-api-key",
model_name="gpt-4-32k",
system_prompt="test-system-prompt",
max_tokens=10,
some_test_param="test-params",
streaming_callback=default_streaming_callback,
api_base_url="test-base-url",
)
data = component.to_dict()
assert data == {
"type": "GPT4Generator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-4-32k",
"system_prompt": "test-system-prompt",
"max_tokens": 10,
"some_test_param": "test-params",
"api_base_url": "test-base-url",
"streaming_callback": "haystack.preview.components.generators.openai.gpt35.default_streaming_callback",
},
}
@pytest.mark.unit
def test_from_dict_default(self):
data = {"type": "GPT4Generator", "init_parameters": {"api_key": "test-api-key"}}
component = GPT4Generator.from_dict(data)
assert component.system_prompt is None
assert component.api_key == "test-api-key"
assert component.model_name == "gpt-4"
assert component.streaming_callback is None
assert component.api_base_url == API_BASE_URL
assert component.model_parameters == {}
@pytest.mark.unit
def test_from_dict(self):
data = {
"type": "GPT4Generator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-4-32k",
"system_prompt": "test-system-prompt",
"max_tokens": 10,
"some_test_param": "test-params",
"api_base_url": "test-base-url",
"streaming_callback": "haystack.preview.components.generators.openai.gpt35.default_streaming_callback",
},
}
component = GPT4Generator.from_dict(data)
assert component.system_prompt == "test-system-prompt"
assert component.api_key == "test-api-key"
assert component.model_name == "gpt-4-32k"
assert component.streaming_callback == default_streaming_callback
assert component.api_base_url == "test-base-url"
assert component.model_parameters == {"max_tokens": 10, "some_test_param": "test-params"}

80
test/preview/components/generators/openai/test_gpt35_generator.py → test/preview/components/generators/openai/test_gpt_generator.py
View File

@ -6,8 +6,8 @@ import pytest
import openai
from openai.util import convert_to_openai_object
from haystack.preview.components.generators.openai.gpt35 import GPT35Generator
from haystack.preview.components.generators.openai.gpt35 import default_streaming_callback
from haystack.preview.components.generators.openai.gpt import GPTGenerator
from haystack.preview.components.generators.openai.gpt import default_streaming_callback
def mock_openai_response(messages: str, model: str = "gpt-3.5-turbo-0301", **kwargs) -> openai.ChatCompletion:
@ -42,10 +42,10 @@ def mock_openai_stream_response(messages: str, model: str = "gpt-3.5-turbo-0301"
yield convert_to_openai_object(base_dict)
class TestGPT35Generator:
class TestGPTGenerator:
@pytest.mark.unit
def test_init_default(self):
component = GPT35Generator(api_key="test-api-key")
component = GPTGenerator(api_key="test-api-key")
assert component.system_prompt is None
assert component.api_key == "test-api-key"
assert component.model_name == "gpt-3.5-turbo"
@ -56,7 +56,7 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_init_with_parameters(self):
callback = lambda x: x
component = GPT35Generator(
component = GPTGenerator(
api_key="test-api-key",
model_name="gpt-4",
system_prompt="test-system-prompt",
@ -74,10 +74,10 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_to_dict_default(self):
component = GPT35Generator(api_key="test-api-key")
component = GPTGenerator(api_key="test-api-key")
data = component.to_dict()
assert data == {
"type": "GPT35Generator",
"type": "GPTGenerator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-3.5-turbo",
@ -89,7 +89,7 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_to_dict_with_parameters(self):
component = GPT35Generator(
component = GPTGenerator(
api_key="test-api-key",
model_name="gpt-4",
system_prompt="test-system-prompt",
@ -100,7 +100,7 @@ class TestGPT35Generator:
)
data = component.to_dict()
assert data == {
"type": "GPT35Generator",
"type": "GPTGenerator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-4",
@ -108,13 +108,13 @@ class TestGPT35Generator:
"max_tokens": 10,
"some_test_param": "test-params",
"api_base_url": "test-base-url",
"streaming_callback": "haystack.preview.components.generators.openai.gpt35.default_streaming_callback",
"streaming_callback": "haystack.preview.components.generators.openai.gpt.default_streaming_callback",
},
}
@pytest.mark.unit
def test_to_dict_with_lambda_streaming_callback(self):
component = GPT35Generator(
component = GPTGenerator(
api_key="test-api-key",
model_name="gpt-4",
system_prompt="test-system-prompt",
@ -125,7 +125,7 @@ class TestGPT35Generator:
)
data = component.to_dict()
assert data == {
"type": "GPT35Generator",
"type": "GPTGenerator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-4",
@ -133,14 +133,14 @@ class TestGPT35Generator:
"max_tokens": 10,
"some_test_param": "test-params",
"api_base_url": "test-base-url",
"streaming_callback": "test_gpt35_generator.<lambda>",
"streaming_callback": "test_gpt_generator.<lambda>",
},
}
@pytest.mark.unit
def test_from_dict(self):
data = {
"type": "GPT35Generator",
"type": "GPTGenerator",
"init_parameters": {
"api_key": "test-api-key",
"model_name": "gpt-4",
@ -148,10 +148,10 @@ class TestGPT35Generator:
"max_tokens": 10,
"some_test_param": "test-params",
"api_base_url": "test-base-url",
"streaming_callback": "haystack.preview.components.generators.openai.gpt35.default_streaming_callback",
"streaming_callback": "haystack.preview.components.generators.openai.gpt.default_streaming_callback",
},
}
component = GPT35Generator.from_dict(data)
component = GPTGenerator.from_dict(data)
assert component.system_prompt == "test-system-prompt"
assert component.api_key == "test-api-key"
assert component.model_name == "gpt-4"
@ -161,9 +161,9 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_run_no_system_prompt(self):
with patch("haystack.preview.components.generators.openai.gpt35.openai.ChatCompletion") as gpt35_patch:
gpt35_patch.create.side_effect = mock_openai_response
component = GPT35Generator(api_key="test-api-key")
with patch("haystack.preview.components.generators.openai.gpt.openai.ChatCompletion") as gpt_patch:
gpt_patch.create.side_effect = mock_openai_response
component = GPTGenerator(api_key="test-api-key")
results = component.run(prompt="test-prompt-1")
assert results == {
"replies": ["response for these messages --> user: test-prompt-1"],
@ -176,7 +176,7 @@ class TestGPT35Generator:
}
],
}
gpt35_patch.create.assert_called_once_with(
gpt_patch.create.assert_called_once_with(
model="gpt-3.5-turbo",
api_key="test-api-key",
messages=[{"role": "user", "content": "test-prompt-1"}],
@ -185,9 +185,9 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_run_with_system_prompt(self):
with patch("haystack.preview.components.generators.openai.gpt35.openai.ChatCompletion") as gpt35_patch:
gpt35_patch.create.side_effect = mock_openai_response
component = GPT35Generator(api_key="test-api-key", system_prompt="test-system-prompt")
with patch("haystack.preview.components.generators.openai.gpt.openai.ChatCompletion") as gpt_patch:
gpt_patch.create.side_effect = mock_openai_response
component = GPTGenerator(api_key="test-api-key", system_prompt="test-system-prompt")
results = component.run(prompt="test-prompt-1")
assert results == {
"replies": ["response for these messages --> system: test-system-prompt - user: test-prompt-1"],
@ -200,7 +200,7 @@ class TestGPT35Generator:
}
],
}
gpt35_patch.create.assert_called_once_with(
gpt_patch.create.assert_called_once_with(
model="gpt-3.5-turbo",
api_key="test-api-key",
messages=[
@ -212,11 +212,11 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_run_with_parameters(self):
with patch("haystack.preview.components.generators.openai.gpt35.openai.ChatCompletion") as gpt35_patch:
gpt35_patch.create.side_effect = mock_openai_response
component = GPT35Generator(api_key="test-api-key", max_tokens=10)
with patch("haystack.preview.components.generators.openai.gpt.openai.ChatCompletion") as gpt_patch:
gpt_patch.create.side_effect = mock_openai_response
component = GPTGenerator(api_key="test-api-key", max_tokens=10)
component.run(prompt="test-prompt-1")
gpt35_patch.create.assert_called_once_with(
gpt_patch.create.assert_called_once_with(
model="gpt-3.5-turbo",
api_key="test-api-key",
messages=[{"role": "user", "content": "test-prompt-1"}],
@ -226,11 +226,11 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_run_stream(self):
with patch("haystack.preview.components.generators.openai.gpt35.openai.ChatCompletion") as gpt35_patch:
with patch("haystack.preview.components.generators.openai.gpt.openai.ChatCompletion") as gpt_patch:
mock_callback = Mock()
mock_callback.side_effect = default_streaming_callback
gpt35_patch.create.side_effect = mock_openai_stream_response
component = GPT35Generator(
gpt_patch.create.side_effect = mock_openai_stream_response
component = GPTGenerator(
api_key="test-api-key", system_prompt="test-system-prompt", streaming_callback=mock_callback
)
results = component.run(prompt="test-prompt-1")
@ -240,7 +240,7 @@ class TestGPT35Generator:
}
# Calls count: 10 tokens per prompt + 1 token for the role + 1 empty termination token
assert mock_callback.call_count == 12
gpt35_patch.create.assert_called_once_with(
gpt_patch.create.assert_called_once_with(
model="gpt-3.5-turbo",
api_key="test-api-key",
messages=[
@ -252,7 +252,7 @@ class TestGPT35Generator:
@pytest.mark.unit
def test_check_truncated_answers(self, caplog):
component = GPT35Generator(api_key="test-api-key")
component = GPTGenerator(api_key="test-api-key")
metadata = [
{"finish_reason": "stop"},
{"finish_reason": "content_filter"},
@ -270,8 +270,8 @@ class TestGPT35Generator:
reason="Export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.",
)
@pytest.mark.integration
def test_gpt35_generator_run(self):
component = GPT35Generator(api_key=os.environ.get("OPENAI_API_KEY"), n=1)
def test_gpt_generator_run(self):
component = GPTGenerator(api_key=os.environ.get("OPENAI_API_KEY"), n=1)
results = component.run(prompt="What's the capital of France?")
assert len(results["replies"]) == 1
assert "Paris" in results["replies"][0]
@ -284,10 +284,8 @@ class TestGPT35Generator:
reason="Export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.",
)
@pytest.mark.integration
def test_gpt35_generator_run_wrong_model_name(self):
component = GPT35Generator(
model_name="something-obviously-wrong", api_key=os.environ.get("OPENAI_API_KEY"), n=1
)
def test_gpt_generator_run_wrong_model_name(self):
component = GPTGenerator(model_name="something-obviously-wrong", api_key=os.environ.get("OPENAI_API_KEY"), n=1)
with pytest.raises(openai.InvalidRequestError, match="The model `something-obviously-wrong` does not exist"):
component.run(prompt="What's the capital of France?")
@ -296,7 +294,7 @@ class TestGPT35Generator:
reason="Export an env var called OPENAI_API_KEY containing the OpenAI API key to run this test.",
)
@pytest.mark.integration
def test_gpt35_generator_run_streaming(self):
def test_gpt_generator_run_streaming(self):
class Callback:
def __init__(self):
self.responses = ""
@ -306,7 +304,7 @@ class TestGPT35Generator:
return chunk
callback = Callback()
component = GPT35Generator(os.environ.get("OPENAI_API_KEY"), streaming_callback=callback, n=1)
component = GPTGenerator(os.environ.get("OPENAI_API_KEY"), streaming_callback=callback, n=1)
results = component.run(prompt="What's the capital of France?")
assert len(results["replies"]) == 1