Learning from User Demonstration

def __build_prompt(self, demo_record: DemonstrationRecord) -> list:
    """
    Build the prompt by the user demonstration record.
    :param demo_record: The user demonstration record.
    return: The prompt.
    """
    demonstration_prompter = DemonstrationPrompter(
        self.is_visual,
        self.prompt_template,
        self.demonstration_prompt_template,
        self.api_prompt_template,
    )
    demonstration_system_prompt = (
        demonstration_prompter.system_prompt_construction()
    )
    demonstration_user_prompt = demonstration_prompter.user_content_construction(
        demo_record
    )
    demonstration_prompt = demonstration_prompter.prompt_construction(
        demonstration_system_prompt, demonstration_user_prompt
    )

    return demonstration_prompt

def __parse_response(self, response_string: str) -> dict:
    """
    Parse the response string to a dict of summary.
    :param response_string: The response string.
    return: The summary dict.
    """
    try:
        response_json = json_parser(response_string)
    except:
        response_json = None

    # Restructure the response, in case any of the keys are missing, set them to empty string.
    if response_json:
        summary = dict()
        summary["example"] = {}
        for key in [
            "Observation",
            "Thought",
            "ControlLabel",
            "ControlText",
            "Function",
            "Args",
            "Status",
            "Plan",
            "Comment",
        ]:
            summary["example"][key] = response_json.get(key, "")
        summary["Tips"] = response_json.get("Tips", "")

        return summary

@staticmethod
def create_or_update_vector_db(summaries: list, db_path: str):
    """
    Create or update the vector database.
    :param summaries: The summaries.
    :param db_path: The path of the vector database.
    """

    document_list = []

    for summary in summaries:
        request = summary["request"]
        document_list.append(Document(page_content=request, metadata=summary))

    db = FAISS.from_documents(document_list, get_hugginface_embedding())

    # Check if the db exists, if not, create a new one.
    if os.path.exists(db_path):
        prev_db = FAISS.load_local(db_path, get_hugginface_embedding())
        db.merge_from(prev_db)

    db.save_local(db_path)

    print(f"Updated vector DB successfully: {db_path}")

@staticmethod
def create_or_update_yaml(summaries: list, yaml_path: str):
    """
    Create or update the YAML file.
    :param summaries: The summaries.
    :param yaml_path: The path of the YAML file.
    """

    # Check if the file exists, if not, create a new one
    if not os.path.exists(yaml_path):
        with open(yaml_path, "w"):
            pass
        print(f"Created new YAML file: {yaml_path}")

    # Read existing data from the YAML file
    with open(yaml_path, "r") as file:
        existing_data = yaml.safe_load(file)

    # Initialize index and existing_data if file is empty
    index = len(existing_data) if existing_data else 0
    existing_data = existing_data or {}

    # Update data with new summaries
    for i, summary in enumerate(summaries):
        example = {f"example{index + i}": summary}
        existing_data.update(example)

    # Write updated data back to the YAML file
    with open(yaml_path, "w") as file:
        yaml.safe_dump(
            existing_data, file, default_flow_style=False, sort_keys=False
        )

    print(f"Updated existing YAML file successfully: {yaml_path}")

def get_summary_list(self, record: DemonstrationRecord) -> Tuple[list, float]:
    """
    Get the summary list for a record
    :param record: The demonstration record.
    return: The summary list for the user defined completion number and the cost
    """

    prompt = self.__build_prompt(record)
    response_string_list, cost = get_completions(
        prompt, "APPAGENT", use_backup_engine=True, n=self.completion_num
    )
    summaries = []
    for response_string in response_string_list:
        summary = self.__parse_response(response_string)
        if summary:
            summary["request"] = record.get_request()
            summary["app_list"] = record.get_applications()
            summaries.append(summary)

    return summaries, cost

def get_indexer(self, db_path: str):
    """
    Create a demonstration indexer.
    :db_path: The path to the database.
    """

    try:
        db = FAISS.load_local(db_path, get_hugginface_embedding())
        return db
    except:
        print_with_color(
            "Warning: Failed to load demonstration indexer from {path}.".format(
                path=db_path
            ),
            "yellow",
        )
        return None