ec2bda4966
* mark depricated API section * CLI bug fixes for azure * check azure before running * Update README.md * Update README.md * bug fix with persona loading * remove print * make errors for cli flags more clear * format * fix imports * fix imports * add prints * update lock * update config fields * cleanup config loading * commit * remove asserts * refactor configure * put into different functions * add embedding default * pass in config * fixes * allow overriding openai embedding endpoint * black * trying to patch tests (some circular import errors) * update flags and docs * patched support for local llms using endpoint and endpoint type passed via configs, not env vars * missing files * fix naming * fix import * fix two runtime errors * patch ollama typo, move ollama model question pre-wrapper, modify question phrasing to include link to readthedocs, also have a default ollama model that has a tag included * disable debug messages * made error message for failed load more informative * don't print dynamic linking function warning unless --debug * updated tests to work with new cli workflow (disabled openai config test for now) * added skips for tests when vars are missing * update bad arg * revise test to soft pass on empty string too * don't run configure twice * extend timeout (try to pass against nltk download) * update defaults * typo with endpoint type default * patch runtime errors for when model is None * catching another case of 'x in model' when model is None (preemptively) * allow overrides to local llm related config params * made model wrapper selection from a list vs raw input * update test for select instead of input * Fixed bug in endpoint when using local->openai selection, also added validation loop to manual endpoint entry * updated error messages to be more informative with links to readthedocs * add back gpt3.5-turbo --------- Co-authored-by: cpacker <packercharles@gmail.com>
62 lines
2.6 KiB
Python
62 lines
2.6 KiB
Python
from .utils import load_all_presets, is_valid_yaml_format
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from ..prompts import gpt_functions
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from ..prompts import gpt_system
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from ..functions.functions import load_all_function_sets
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DEFAULT_PRESET = "memgpt_chat"
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available_presets = load_all_presets()
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preset_options = list(available_presets.keys())
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def use_preset(preset_name, agent_config, model, persona, human, interface, persistence_manager):
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"""Storing combinations of SYSTEM + FUNCTION prompts"""
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from memgpt.agent import Agent
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from memgpt.utils import printd
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# Available functions is a mapping from:
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# function_name -> {
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# json_schema: schema
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# python_function: function
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# }
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available_functions = load_all_function_sets()
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available_presets = load_all_presets()
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if preset_name not in available_presets:
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raise ValueError(f"Preset '{preset_name}.yaml' not found")
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preset = available_presets[preset_name]
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if not is_valid_yaml_format(preset, list(available_functions.keys())):
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raise ValueError(f"Preset '{preset_name}.yaml' is not valid")
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preset_system_prompt = preset["system_prompt"]
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preset_function_set_names = preset["functions"]
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# Filter down the function set based on what the preset requested
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preset_function_set = {}
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for f_name in preset_function_set_names:
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if f_name not in available_functions:
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raise ValueError(f"Function '{f_name}' was specified in preset, but is not in function library:\n{available_functions.keys()}")
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preset_function_set[f_name] = available_functions[f_name]
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assert len(preset_function_set_names) == len(preset_function_set)
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printd(f"Available functions:\n", list(preset_function_set.keys()))
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# preset_function_set = {f_name: f_dict for f_name, f_dict in available_functions.items() if f_name in preset_function_set_names}
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# printd(f"Available functions:\n", [f_name for f_name, f_dict in preset_function_set.items()])
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# Make sure that every function the preset wanted is inside the available functions
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# assert len(preset_function_set_names) == len(preset_function_set)
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return Agent(
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config=agent_config,
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model=model,
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system=gpt_system.get_system_text(preset_system_prompt),
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functions=preset_function_set,
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interface=interface,
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persistence_manager=persistence_manager,
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persona_notes=persona,
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human_notes=human,
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# gpt-3.5-turbo tends to omit inner monologue, relax this requirement for now
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first_message_verify_mono=True if (model is not None and "gpt-4" in model) else False,
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)
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