e5add4e430
* partial * working schema builder, tested that it matches the hand-written schemas * correct another schema diff * refactor * basic working test * refactored preset creation to use yaml files * added docstring-parser * add code for dynamic function linking in agent loading * pretty schema diff printer * support pulling from ~/.memgpt/functions/*.py * clean * allow looking for system prompts in ~/.memgpt/system_prompts * create ~/.memgpt/system_prompts if it doesn't exist * pull presets from ~/.memgpt/presets in addition to examples folder * add support for loading agent configs that have additional keys --------- Co-authored-by: Sarah Wooders <sarahwooders@gmail.com>
77 lines
2.6 KiB
Python
77 lines
2.6 KiB
Python
import os
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import glob
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import yaml
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from memgpt.constants import MEMGPT_DIR
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def is_valid_yaml_format(yaml_data, function_set):
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"""
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Check if the given YAML data follows the specified format and if all functions in the yaml are part of the function_set.
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Raises ValueError if any check fails.
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:param yaml_data: The data loaded from a YAML file.
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:param function_set: A set of valid function names.
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"""
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# Check for required keys
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if not all(key in yaml_data for key in ["system_prompt", "functions"]):
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raise ValueError("YAML data is missing one or more required keys: 'system_prompt', 'functions'.")
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# Check if 'functions' is a list of strings
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if not all(isinstance(item, str) for item in yaml_data.get("functions", [])):
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raise ValueError("'functions' should be a list of strings.")
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# Check if all functions in YAML are part of function_set
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if not set(yaml_data["functions"]).issubset(function_set):
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raise ValueError("Some functions in YAML are not part of the provided function set.")
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# If all checks pass
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return True
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def load_yaml_file(file_path):
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"""
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Load a YAML file and return the data.
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:param file_path: Path to the YAML file.
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:return: Data from the YAML file.
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"""
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with open(file_path, "r") as file:
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return yaml.safe_load(file)
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def load_all_presets():
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"""Load all the preset configs in the examples directory"""
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## Load the examples
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# Get the directory in which the script is located
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script_directory = os.path.dirname(os.path.abspath(__file__))
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# Construct the path pattern
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example_path_pattern = os.path.join(script_directory, "examples", "*.yaml")
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# Listing all YAML files
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example_yaml_files = glob.glob(example_path_pattern)
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## Load the user-provided presets
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# ~/.memgpt/presets/*.yaml
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user_presets_dir = os.path.join(MEMGPT_DIR, "presets")
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# Create directory if it doesn't exist
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if not os.path.exists(user_presets_dir):
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os.makedirs(user_presets_dir)
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# Construct the path pattern
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user_path_pattern = os.path.join(user_presets_dir, "*.yaml")
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# Listing all YAML files
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user_yaml_files = glob.glob(user_path_pattern)
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# Pull from both examplesa and user-provided
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all_yaml_files = example_yaml_files + user_yaml_files
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# Loading and creating a mapping from file name to YAML data
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all_yaml_data = {}
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for file_path in all_yaml_files:
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# Extracting the base file name without the '.yaml' extension
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base_name = os.path.splitext(os.path.basename(file_path))[0]
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data = load_yaml_file(file_path)
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all_yaml_data[base_name] = data
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return all_yaml_data
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