Merge branch 'fix_remove_colors_dict_bug' of https://github.com/pr-0f…

…3t/Auto-GPT into fix_remove_colors_dict_bug

.devcontainer/Dockerfile

@@ -1,26 +1,13 @@
-# [Choice] Python version (use -bullseye variants on local arm64/Apple Silicon): 3, 3.10, 3-bullseye, 3.10-bullseye, 3-buster, 3.10-buster
-ARG VARIANT=3-bullseye
+# Use an official Python base image from the Docker Hub
 FROM python:3.10
 
-RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
-    # Remove imagemagick due to https://security-tracker.debian.org/tracker/CVE-2019-10131
-    && apt-get purge -y imagemagick imagemagick-6-common
+# Install browsers
+RUN apt-get update && apt-get install -y \
+    chromium-driver firefox-esr \
+    ca-certificates
 
-# Temporary: Upgrade python packages due to https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-40897
-# They are installed by the base image (python) which does not have the patch.
-RUN python3 -m pip install --upgrade setuptools
+# Install utilities
+RUN apt-get install -y curl jq wget git
 
-# Install Chromium for web browsing
-RUN apt-get install -y chromium-driver
-
-# [Optional] If your pip requirements rarely change, uncomment this section to add them to the image.
-# COPY requirements.txt /tmp/pip-tmp/
-# RUN pip3 --disable-pip-version-check --no-cache-dir install -r /tmp/pip-tmp/requirements.txt \
-#    && rm -rf /tmp/pip-tmp
-
-# [Optional] Uncomment this section to install additional OS packages.
-# RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
-#     && apt-get -y install --no-install-recommends <your-package-list-here>
-
-# [Optional] Uncomment this line to install global node packages.
-# RUN su vscode -c "source /usr/local/share/nvm/nvm.sh && npm install -g <your-package-here>" 2>&1
+# Declare working directory
+WORKDIR /workspace/Auto-GPT

.devcontainer/devcontainer.json

@@ -1,14 +1,14 @@
 {
-  "build": {
-    "dockerfile": "./Dockerfile",
-    "context": "."
-  },
+  "dockerComposeFile": "./docker-compose.yml",
+  "service": "auto-gpt",
+  "workspaceFolder": "/workspace/Auto-GPT",
+  "shutdownAction": "stopCompose",
   "features": {
     "ghcr.io/devcontainers/features/common-utils:2": {
       "installZsh": "true",
       "username": "vscode",
-      "userUid": "1000",
-      "userGid": "1000",
+      "userUid": "6942",
+      "userGid": "6942",
       "upgradePackages": "true"
     },
     "ghcr.io/devcontainers/features/desktop-lite:1": {},

.devcontainer/docker-compose.yml

@@ -0,0 +1,19 @@
+# To boot the app run the following:
+# docker-compose run auto-gpt
+version: '3.9'
+
+services:
+  auto-gpt:
+    depends_on:
+      - redis
+    build:
+      dockerfile: .devcontainer/Dockerfile
+      context: ../
+    tty: true
+    environment:
+      MEMORY_BACKEND: ${MEMORY_BACKEND:-redis}
+      REDIS_HOST: ${REDIS_HOST:-redis}
+    volumes:
+      - ../:/workspace/Auto-GPT
+  redis:
+    image: 'redis/redis-stack-server:latest'

CONTRIBUTING.md

@@ -127,3 +127,22 @@ When you run Pytest locally:
             - Or: The test might be poorly written. In that case, you can make suggestions to change the test.
 
 In our CI pipeline, Pytest will use the cassettes and not call paid API providers, so we need your help to record the replays that you break.
+
+
+### Community Challenges
+Challenges are goals we need Auto-GPT to achieve. 
+To pick the challenge you like, go to the tests/integration/challenges folder and select the areas you would like to work on. 
+- a challenge is new if level_currently_beaten is None
+- a challenge is in progress if level_currently_beaten is greater or equal to 1
+- a challenge is beaten if level_currently_beaten = max_level
+
+Here is an example of how to run the memory challenge A and attempt to beat level 3.
+
+pytest -s tests/integration/challenges/memory/test_memory_challenge_a.py --level=3
+
+To beat a challenge, you're not allowed to change anything in the tests folder, you have to add code in the autogpt folder
+
+Challenges use cassettes. Cassettes allow us to replay your runs in our CI pipeline.
+Don't hesitate to delete the cassettes associated to the challenge you're working on if you need to. Otherwise it will keep replaying the last run.
+
+Once you've beaten a new level of a challenge, please create a pull request and we will analyze how you changed Auto-GPT to beat the challenge.

autogpt/agent/agent_manager.py

@@ -4,9 +4,8 @@
 from typing import List
 
 from autogpt.config.config import Config
-from autogpt.llm import create_chat_completion
+from autogpt.llm import Message, create_chat_completion
 from autogpt.singleton import Singleton
-from autogpt.types.openai import Message
 
 
 class AgentManager(metaclass=Singleton):

autogpt/commands/file_operations.py

@@ -264,7 +264,7 @@ def download_file(url, filename):
                         progress = f"{readable_file_size(downloaded_size)} / {readable_file_size(total_size)}"
                         spinner.update_message(f"{message} {progress}")
 
-            return f'Successfully downloaded and locally stored file: "{filename}"! (Size: {readable_file_size(total_size)})'
+            return f'Successfully downloaded and locally stored file: "{filename}"! (Size: {readable_file_size(downloaded_size)})'
     except requests.HTTPError as e:
         return f"Got an HTTP Error whilst trying to download file: {e}"
     except Exception as e:

autogpt/commands/git_operations.py

@@ -11,25 +11,25 @@
 @command(
     "clone_repository",
     "Clone Repository",
-    '"repository_url": "<repository_url>", "clone_path": "<clone_path>"',
+    '"url": "<repository_url>", "clone_path": "<clone_path>"',
     CFG.github_username and CFG.github_api_key,
     "Configure github_username and github_api_key.",
 )
 @validate_url
-def clone_repository(repository_url: str, clone_path: str) -> str:
+def clone_repository(url: str, clone_path: str) -> str:
     """Clone a GitHub repository locally.
 
     Args:
-        repository_url (str): The URL of the repository to clone.
+        url (str): The URL of the repository to clone.
         clone_path (str): The path to clone the repository to.
 
     Returns:
         str: The result of the clone operation.
     """
-    split_url = repository_url.split("//")
+    split_url = url.split("//")
     auth_repo_url = f"//{CFG.github_username}:{CFG.github_api_key}@".join(split_url)
     try:
-        Repo.clone_from(auth_repo_url, clone_path)
-        return f"""Cloned {repository_url} to {clone_path}"""
+        Repo.clone_from(url=auth_repo_url, to_path=clone_path)
+        return f"""Cloned {url} to {clone_path}"""
     except Exception as e:
         return f"Error: {str(e)}"

autogpt/llm/__init__.py

@@ -1,4 +1,13 @@
 from autogpt.llm.api_manager import ApiManager
+from autogpt.llm.base import (
+    ChatModelInfo,
+    ChatModelResponse,
+    EmbeddingModelInfo,
+    EmbeddingModelResponse,
+    LLMResponse,
+    Message,
+    ModelInfo,
+)
 from autogpt.llm.chat import chat_with_ai, create_chat_message, generate_context
 from autogpt.llm.llm_utils import (
     call_ai_function,
@@ -10,6 +19,13 @@
 
 __all__ = [
     "ApiManager",
+    "Message",
+    "ModelInfo",
+    "ChatModelInfo",
+    "EmbeddingModelInfo",
+    "LLMResponse",
+    "ChatModelResponse",
+    "EmbeddingModelResponse",
     "create_chat_message",
     "generate_context",
     "chat_with_ai",

autogpt/llm/base.py

@@ -0,0 +1,65 @@
+from dataclasses import dataclass, field
+from typing import List, TypedDict
+
+
+class Message(TypedDict):
+    """OpenAI Message object containing a role and the message content"""
+
+    role: str
+    content: str
+
+
+@dataclass
+class ModelInfo:
+    """Struct for model information.
+
+    Would be lovely to eventually get this directly from APIs, but needs to be scraped from
+    websites for now.
+
+    """
+
+    name: str
+    prompt_token_cost: float
+    completion_token_cost: float
+    max_tokens: int
+
+
+@dataclass
+class ChatModelInfo(ModelInfo):
+    """Struct for chat model information."""
+
+    pass
+
+
+@dataclass
+class EmbeddingModelInfo(ModelInfo):
+    """Struct for embedding model information."""
+
+    embedding_dimensions: int
+
+
+@dataclass
+class LLMResponse:
+    """Standard response struct for a response from an LLM model."""
+
+    model_info: ModelInfo
+    prompt_tokens_used: int = 0
+    completion_tokens_used: int = 0
+
+
+@dataclass
+class EmbeddingModelResponse(LLMResponse):
+    """Standard response struct for a response from an embedding model."""
+
+    embedding: List[float] = field(default_factory=list)
+
+    def __post_init__(self):
+        if self.completion_tokens_used:
+            raise ValueError("Embeddings should not have completion tokens used.")
+
+
+@dataclass
+class ChatModelResponse(LLMResponse):
+    """Standard response struct for a response from an LLM model."""
+
+    content: str = None

autogpt/llm/chat.py

@@ -5,13 +5,13 @@
 
 from autogpt.config import Config
 from autogpt.llm.api_manager import ApiManager
+from autogpt.llm.base import Message
 from autogpt.llm.llm_utils import create_chat_completion
 from autogpt.llm.token_counter import count_message_tokens
 from autogpt.logs import logger
 from autogpt.memory_management.store_memory import (
     save_memory_trimmed_from_context_window,
 )
-from autogpt.types.openai import Message
 
 cfg = Config()
 

autogpt/llm/llm_utils.py

@@ -10,8 +10,8 @@
 
 from autogpt.config import Config
 from autogpt.llm.api_manager import ApiManager
+from autogpt.llm.base import Message
 from autogpt.logs import logger
-from autogpt.types.openai import Message
 
 
 def retry_openai_api(

autogpt/llm/providers/openai.py

@@ -0,0 +1,37 @@
+from autogpt.llm.base import ChatModelInfo, EmbeddingModelInfo
+
+OPEN_AI_CHAT_MODELS = {
+    "gpt-3.5-turbo": ChatModelInfo(
+        name="gpt-3.5-turbo",
+        prompt_token_cost=0.002,
+        completion_token_cost=0.002,
+        max_tokens=4096,
+    ),
+    "gpt-4": ChatModelInfo(
+        name="gpt-4",
+        prompt_token_cost=0.03,
+        completion_token_cost=0.06,
+        max_tokens=8192,
+    ),
+    "gpt-4-32k": ChatModelInfo(
+        name="gpt-4-32k",
+        prompt_token_cost=0.06,
+        completion_token_cost=0.12,
+        max_tokens=32768,
+    ),
+}
+
+OPEN_AI_EMBEDDING_MODELS = {
+    "text-embedding-ada-002": EmbeddingModelInfo(
+        name="text-embedding-ada-002",
+        prompt_token_cost=0.0004,
+        completion_token_cost=0.0,
+        max_tokens=8191,
+        embedding_dimensions=1536,
+    ),
+}
+
+OPEN_AI_MODELS = {
+    **OPEN_AI_CHAT_MODELS,
+    **OPEN_AI_EMBEDDING_MODELS,
+}

autogpt/llm/token_counter.py

@@ -5,8 +5,8 @@
 
 import tiktoken
 
+from autogpt.llm.base import Message
 from autogpt.logs import logger
-from autogpt.types.openai import Message
 
 
 def count_message_tokens(

docs/testing.md

@@ -28,7 +28,7 @@ python -m pytest
         :::shell
         pytest --cov=autogpt --without-integration --without-slow-integration
 
-## Runing the linter
+## Running the linter
 
 This project uses [flake8](https://flake8.pycqa.org/en/latest/) for linting.
 We currently use the following rules: `E303,W293,W291,W292,E305,E231,E302`.

pyproject.toml

@@ -1,8 +1,25 @@
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
 [project]
-name = "auto-gpt"
-version = "0.1.0"
-description = "A GPT based ai agent"
+name = "agpt"
+version = "0.2.2"
+authors = [
+  { name="Torantulino", email="[email protected]" },
+]
 readme = "README.md"
+requires-python = ">=3.10"
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent",
+]
+description = "An open-source attempt to make GPT-4 autonomous"
+
+[project.urls]
+"Homepage" = "https://github.com/Significant-Gravitas/Auto-GPT"
+"Bug Tracker" = "https://github.com/Significant-Gravitas/Auto-GPT"
 
 [tool.black]
 line-length = 88