Co-authored-by: k-boikov <64261260+k-boikov@users.noreply.github.com>pull/3599/head^2
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@ -1,9 +1,12 @@
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"""Configurator module."""
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from __future__ import annotations
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import click
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from colorama import Back, Fore, Style
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from autogpt import utils
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from autogpt.config import Config
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from autogpt.llm.llm_utils import check_model
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from autogpt.logs import logger
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from autogpt.memory import get_supported_memory_backends
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@ -45,6 +48,8 @@ def create_config(
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CFG.set_debug_mode(False)
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CFG.set_continuous_mode(False)
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CFG.set_speak_mode(False)
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CFG.set_fast_llm_model(check_model(CFG.fast_llm_model, "fast_llm_model"))
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CFG.set_smart_llm_model(check_model(CFG.smart_llm_model, "smart_llm_model"))
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if debug:
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logger.typewriter_log("Debug Mode: ", Fore.GREEN, "ENABLED")
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@ -1,6 +1,9 @@
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from __future__ import annotations
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from typing import List, Optional
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import openai
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from openai import Model
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from autogpt.config import Config
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from autogpt.llm.modelsinfo import COSTS
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@ -14,12 +17,14 @@ class ApiManager(metaclass=Singleton):
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self.total_completion_tokens = 0
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self.total_cost = 0
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self.total_budget = 0
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self.models: Optional[list[Model]] = None
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def reset(self):
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self.total_prompt_tokens = 0
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self.total_completion_tokens = 0
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self.total_cost = 0
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self.total_budget = 0.0
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self.models = None
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def create_chat_completion(
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self,
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@ -127,3 +132,17 @@ class ApiManager(metaclass=Singleton):
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float: The total budget for API calls.
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"""
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return self.total_budget
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def get_models(self) -> List[Model]:
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"""
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Get list of available GPT models.
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Returns:
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list: List of available GPT models.
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"""
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if self.models is None:
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all_models = openai.Model.list()["data"]
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self.models = [model for model in all_models if "gpt" in model["id"]]
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return self.models
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@ -3,7 +3,7 @@ from __future__ import annotations
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import functools
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import time
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from itertools import islice
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from typing import List, Optional
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from typing import List, Literal, Optional
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import numpy as np
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import openai
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@ -293,3 +293,22 @@ def create_embedding(
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) # normalize the length to one
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chunk_embeddings = chunk_embeddings.tolist()
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return chunk_embeddings
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def check_model(
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model_name: str, model_type: Literal["smart_llm_model", "fast_llm_model"]
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) -> str:
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"""Check if model is available for use. If not, return gpt-3.5-turbo."""
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api_manager = ApiManager()
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models = api_manager.get_models()
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if any(model_name in m["id"] for m in models):
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return model_name
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logger.typewriter_log(
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"WARNING: ",
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Fore.YELLOW,
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f"You do not have access to {model_name}. Setting {model_type} to "
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f"gpt-3.5-turbo.",
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)
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return "gpt-3.5-turbo"
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@ -47,6 +47,7 @@ def run_auto_gpt(
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cfg = Config()
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# TODO: fill in llm values here
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check_openai_api_key()
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create_config(
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continuous,
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continuous_limit,
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@ -118,3 +118,13 @@ class TestApiManager:
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assert api_manager.get_total_prompt_tokens() == 50
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assert api_manager.get_total_completion_tokens() == 100
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assert api_manager.get_total_cost() == (50 * 0.002 + 100 * 0.002) / 1000
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@staticmethod
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def test_get_models():
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"""Test if getting models works correctly."""
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with patch("openai.Model.list") as mock_list_models:
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mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]}
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result = api_manager.get_models()
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assert result[0]["id"] == "gpt-3.5-turbo"
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assert api_manager.models[0]["id"] == "gpt-3.5-turbo"
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@ -2,10 +2,11 @@
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Test cases for the Config class, which handles the configuration settings
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for the AI and ensures it behaves as a singleton.
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"""
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from unittest.mock import patch
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import pytest
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from openai import InvalidRequestError
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from autogpt.config import Config
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from autogpt.configurator import create_config
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def test_initial_values(config):
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@ -117,3 +118,40 @@ def test_set_debug_mode(config):
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# Reset debug mode
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config.set_debug_mode(debug_mode)
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@patch("openai.Model.list")
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def test_smart_and_fast_llm_models_set_to_gpt4(mock_list_models, config):
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"""
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Test if models update to gpt-3.5-turbo if both are set to gpt-4.
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"""
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fast_llm_model = config.fast_llm_model
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smart_llm_model = config.smart_llm_model
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config.fast_llm_model = "gpt-4"
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config.smart_llm_model = "gpt-4"
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mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]}
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create_config(
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continuous=False,
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continuous_limit=False,
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ai_settings_file="",
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prompt_settings_file="",
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skip_reprompt=False,
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speak=False,
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debug=False,
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gpt3only=False,
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gpt4only=False,
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memory_type="",
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browser_name="",
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allow_downloads=False,
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skip_news=False,
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)
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assert config.fast_llm_model == "gpt-3.5-turbo"
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assert config.smart_llm_model == "gpt-3.5-turbo"
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# Reset config
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config.set_fast_llm_model(fast_llm_model)
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config.set_smart_llm_model(smart_llm_model)
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@ -1,7 +1,11 @@
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from unittest.mock import patch
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import pytest
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from openai import InvalidRequestError
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from openai.error import APIError, RateLimitError
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from autogpt.llm import llm_utils
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from autogpt.llm.llm_utils import check_model
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@pytest.fixture(params=[RateLimitError, APIError])
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@ -131,3 +135,26 @@ def test_chunked_tokens():
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]
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output = list(llm_utils.chunked_tokens(text, "cl100k_base", 8191))
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assert output == expected_output
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def test_check_model(api_manager):
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"""
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Test if check_model() returns original model when valid.
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Test if check_model() returns gpt-3.5-turbo when model is invalid.
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"""
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with patch("openai.Model.list") as mock_list_models:
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# Test when correct model is returned
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mock_list_models.return_value = {"data": [{"id": "gpt-4"}]}
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result = check_model("gpt-4", "smart_llm_model")
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assert result == "gpt-4"
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# Reset api manager models
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api_manager.models = None
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# Test when incorrect model is returned
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mock_list_models.return_value = {"data": [{"id": "gpt-3.5-turbo"}]}
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result = check_model("gpt-4", "fast_llm_model")
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assert result == "gpt-3.5-turbo"
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# Reset api manager models
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api_manager.models = None
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