Module src.llm_api.utils

Functions

def conversation_prompt_to_instruct(conversation: list) ‑> str

Convert a conversation prompt to an instruct prompt.

Expand source code

def conversation_prompt_to_instruct(conversation: list) -> str:
    """Convert a conversation prompt to an instruct prompt."""
    prompt = ""
    for number in range(len(conversation)):
        if conversation[number].role == "system":
            prompt += "<<SYS>>" + conversation[number].content + "<</SYS>>\n"
        elif conversation[number].role == "user":
            prompt += "[USER]" + conversation[number].content + "[/USER]\n"
        elif conversation[number].role == "assistant":
            prompt += "[ASSIST]" + conversation[number].content + "[/ASSIST]\n"
        else:
            raise ValueError("Invalid message role")

    return f"<s>[INST] {prompt} [/INST]"

def generate_together_completion(prompt: str, model: str, max_tokens: int = 4000, temperature: float = 0.7, top_k: int = 50, top_p: float = 0.7) ‑> dict

Generate a completion using the Together API.

Parameters: - prompt (str): The prompt to generate the completion from. - model (str): The model to use for the completion. - max_tokens (int): The maximum number of tokens to generate. - temperature (float): The temperature parameter for the LLM. - top_k (int): The top-k parameter for the LLM. - top_p (float): The top-p parameter for the LLM.

Returns: dict: The generated completion from the LLM.

Expand source code

def generate_together_completion(
    prompt: str,
    model: str,
    max_tokens: int = 4000,
    temperature: float = 0.7,
    top_k: int = 50,
    top_p: float = 0.7,
) -> dict:
    """
    Generate a completion using the Together API.

    Parameters:
    - prompt (str): The prompt to generate the completion from.
    - model (str): The model to use for the completion.
    - max_tokens (int): The maximum number of tokens to generate.
    - temperature (float): The temperature parameter for the LLM.
    - top_k (int): The top-k parameter for the LLM.
    - top_p (float): The top-p parameter for the LLM.

    Returns:
    dict: The generated completion from the LLM.
    """
    output = together.Complete.create(
        prompt=prompt,
        model=model,
        max_tokens=max_tokens,
        temperature=temperature,
        top_k=top_k,
        top_p=top_p,
        repetition_penalty=1.1,
        stop=["</s>", "[/INST]", "[/USER]", "[INST]", "[USER]"],
    )
    return output

def get_together_text(output: dict) ‑> str

Get text response from the Together API response.

Expand source code

def get_together_text(output: dict) -> str:
    """Get text response from the Together API response."""
    try:
        return output["output"]["choices"][0]["text"]
    except KeyError:
        print(output)
        raise ValueError("Invalid response or text not found")