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add: docs for OpenAIModel
Browse files- docs/llm.md +3 -0
- guardrails_genie/llm.py +55 -0
- mkdocs.yml +1 -0
docs/llm.md
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# LLM
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::: guardrails_genie.llm
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guardrails_genie/llm.py
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@@ -6,6 +6,17 @@ from openai.types.chat import ChatCompletion
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class OpenAIModel(weave.Model):
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model_name: str
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_openai_client: OpenAI
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system_prompt: Optional[str] = None,
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messages: Optional[list[dict]] = None,
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) -> list[dict]:
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user_prompts = [user_prompts] if isinstance(user_prompts, str) else user_prompts
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messages = list(messages) if isinstance(messages, dict) else []
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for user_prompt in user_prompts:
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messages: Optional[list[dict]] = None,
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**kwargs,
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) -> ChatCompletion:
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messages = self.create_messages(user_prompts, system_prompt, messages)
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if "response_format" in kwargs:
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response = self._openai_client.beta.chat.completions.parse(
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class OpenAIModel(weave.Model):
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"""
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A class to interface with OpenAI's language models using the Weave framework.
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This class provides methods to create structured messages and generate predictions
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using OpenAI's chat completion API. It is designed to work with both single and
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multiple user prompts, and optionally includes a system prompt to guide the model's
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responses.
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Args:
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model_name (str): The name of the OpenAI model to be used for predictions.
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"""
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model_name: str
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_openai_client: OpenAI
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system_prompt: Optional[str] = None,
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messages: Optional[list[dict]] = None,
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) -> list[dict]:
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"""
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Create a list of messages for the OpenAI chat completion API.
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This function constructs a list of messages in the format required by the
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OpenAI chat completion API. It takes user prompts, an optional system prompt,
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and an optional list of existing messages, and combines them into a single
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list of messages.
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Args:
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user_prompts (Union[str, list[str]]): A single user prompt or a list of
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user prompts to be included in the messages.
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system_prompt (Optional[str]): An optional system prompt to guide the
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model's responses. If provided, it will be added at the beginning
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of the messages list.
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messages (Optional[list[dict]]): An optional list of existing messages
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to which the new prompts will be appended. If not provided, a new
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list will be created.
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Returns:
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list[dict]: A list of messages formatted for the OpenAI chat completion API.
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"""
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user_prompts = [user_prompts] if isinstance(user_prompts, str) else user_prompts
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messages = list(messages) if isinstance(messages, dict) else []
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for user_prompt in user_prompts:
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messages: Optional[list[dict]] = None,
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**kwargs,
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) -> ChatCompletion:
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"""
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Generate a chat completion response using the OpenAI API.
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This function takes user prompts, an optional system prompt, and an optional
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list of existing messages to create a list of messages formatted for the
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OpenAI chat completion API. It then sends these messages to the OpenAI API
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to generate a chat completion response.
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Args:
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user_prompts (Union[str, list[str]]): A single user prompt or a list of
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user prompts to be included in the messages.
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system_prompt (Optional[str]): An optional system prompt to guide the
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model's responses. If provided, it will be added at the beginning
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of the messages list.
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messages (Optional[list[dict]]): An optional list of existing messages
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to which the new prompts will be appended. If not provided, a new
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list will be created.
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**kwargs: Additional keyword arguments to be passed to the OpenAI API
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for chat completion.
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Returns:
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ChatCompletion: The chat completion response from the OpenAI API.
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"""
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messages = self.create_messages(user_prompts, system_prompt, messages)
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if "response_format" in kwargs:
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response = self._openai_client.beta.chat.completions.parse(
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mkdocs.yml
CHANGED
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@@ -59,6 +59,7 @@ extra_javascript:
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nav:
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- Home: 'index.md'
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- Metrics: 'metrics.md'
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- RegexModel: 'regex_model.md'
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- Utils: 'utils.md'
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nav:
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- Home: 'index.md'
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- LLM: 'llm.md'
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- Metrics: 'metrics.md'
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- RegexModel: 'regex_model.md'
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- Utils: 'utils.md'
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