Merge with master

.env.template

@@ -1,6 +1,7 @@
 PINECONE_API_KEY=your-pinecone-api-key
 PINECONE_ENV=your-pinecone-region
 OPENAI_API_KEY=your-openai-api-key
+TEMPERATURE=1
 ELEVENLABS_API_KEY=your-elevenlabs-api-key
 ELEVENLABS_VOICE_1_ID=your-voice-id
 ELEVENLABS_VOICE_2_ID=your-voice-id
@@ -9,11 +10,7 @@ FAST_LLM_MODEL=gpt-3.5-turbo
 GOOGLE_API_KEY=
 CUSTOM_SEARCH_ENGINE_ID=
 USE_AZURE=False
-OPENAI_AZURE_API_BASE=your-base-url-for-azure
+EXECUTE_LOCAL_COMMANDS=False
-OPENAI_AZURE_API_VERSION=api-version-for-azure
-OPENAI_AZURE_DEPLOYMENT_ID=deployment-id-for-azure
-OPENAI_AZURE_CHAT_DEPLOYMENT_ID=deployment-id-for-azure-chat
-OPENAI_AZURE_EMBEDDINGS_DEPLOYMENT_ID=deployment-id-for-azure-embeddigs
 IMAGE_PROVIDER=dalle
 HUGGINGFACE_API_TOKEN=
 USE_MAC_OS_TTS=False

.github/PULL_REQUEST_TEMPLATE.md

@@ -26,7 +26,7 @@ By following these guidelines, your PRs are more likely to be merged quickly aft
 - [ ] I have thoroughly tested my changes with multiple different prompts.
 - [ ] I have considered potential risks and mitigations for my changes.
 - [ ] I have documented my changes clearly and comprehensively.
-- [ ] I have not snuck in any "extra" small tweaks changes <!-- Submit these as separate Pull Reqests, they are the easiest to merge! -->
+- [ ] I have not snuck in any "extra" small tweaks changes <!-- Submit these as separate Pull Requests, they are the easiest to merge! -->
 
 <!-- If you haven't added tests, please explain why. If you have, check the appropriate box. If you've ensured your PR is atomic and well-documented, check the corresponding boxes. -->
 

.github/workflows/ci.yml

@@ -32,7 +32,7 @@ jobs:
 
     - name: Lint with flake8
       continue-on-error: false
-      run: flake8 scripts/ tests/ --select E303,W293,W291,W292,E305
+      run: flake8 scripts/ tests/ --select E303,W293,W291,W292,E305,E231,E302
 
     - name: Run unittest tests with coverage
       run: |

.gitignore

@@ -7,9 +7,11 @@ package-lock.json
 auto_gpt_workspace/*
 *.mpeg
 .env
+azure.yaml
 *venv/*
 outputs/*
 ai_settings.yaml
+last_run_ai_settings.yaml
 .vscode
 .idea/*
 auto-gpt.json
@@ -19,3 +21,6 @@ log.txt
 .coverage
 coverage.xml
 htmlcov/
+
+# For Macs Dev Environs: ignoring .Desktop Services_Store
+.DS_Store

README.md

@@ -2,8 +2,8 @@
 
 ![GitHub Repo stars](https://img.shields.io/github/stars/Torantulino/auto-gpt?style=social)
 ![Twitter Follow](https://img.shields.io/twitter/follow/siggravitas?style=social)
-[![](https://dcbadge.vercel.app/api/server/PQ7VX6TY4t?style=flat)](https://discord.gg/PQ7VX6TY4t)
+[![Discord Follow](https://dcbadge.vercel.app/api/server/PQ7VX6TY4t?style=flat)](https://discord.gg/PQ7VX6TY4t)
-[![Unit Tests](https://github.com/Torantulino/Auto-GPT/actions/workflows/unit_tests.yml/badge.svg)](https://github.com/Torantulino/Auto-GPT/actions/workflows/unit_tests.yml)
+[![Unit Tests](https://github.com/Torantulino/Auto-GPT/actions/workflows/ci.yml/badge.svg)](https://github.com/Torantulino/Auto-GPT/actions/workflows/unit_tests.yml)
 
 Auto-GPT is an experimental open-source application showcasing the capabilities of the GPT-4 language model. This program, driven by GPT-4, chains together LLM "thoughts", to autonomously achieve whatever goal you set. As one of the first examples of GPT-4 running fully autonomously, Auto-GPT pushes the boundaries of what is possible with AI.
 
@@ -32,21 +32,28 @@ Your support is greatly appreciated
 
 - [Auto-GPT: An Autonomous GPT-4 Experiment](#auto-gpt-an-autonomous-gpt-4-experiment)
   - [Demo (30/03/2023):](#demo-30032023)
-  - [💖 Help Fund Auto-GPT's Development](#-help-fund-auto-gpts-development)
   - [Table of Contents](#table-of-contents)
   - [🚀 Features](#-features)
   - [📋 Requirements](#-requirements)
   - [💾 Installation](#-installation)
   - [🔧 Usage](#-usage)
+    - [Logs](#logs)
   - [🗣️ Speech Mode](#️-speech-mode)
   - [🔍 Google API Keys Configuration](#-google-api-keys-configuration)
     - [Setting up environment variables](#setting-up-environment-variables)
+  - [Redis Setup](#redis-setup)
+  - [🌲 Pinecone API Key Setup](#-pinecone-api-key-setup)
+    - [Setting up environment variables](#setting-up-environment-variables-1)
+  - [Setting Your Cache Type](#setting-your-cache-type)
+  - [View Memory Usage](#view-memory-usage)
   - [💀 Continuous Mode ⚠️](#-continuous-mode-️)
   - [GPT3.5 ONLY Mode](#gpt35-only-mode)
-  - [🖼 Image Generation](#image-generation)
+  - [🖼 Image Generation](#-image-generation)
   - [⚠️ Limitations](#️-limitations)
   - [🛡 Disclaimer](#-disclaimer)
   - [🐦 Connect with Us on Twitter](#-connect-with-us-on-twitter)
+  - [Run tests](#run-tests)
+  - [Run linter](#run-linter)
 
 ## 🚀 Features
 
@@ -70,36 +77,41 @@ Optional:
 
 To install Auto-GPT, follow these steps:
 
-0. Make sure you have all the **requirements** above, if not, install/get them.
+1. Make sure you have all the **requirements** above, if not, install/get them.
 
 _The following commands should be executed in a CMD, Bash or Powershell window. To do this, go to a folder on your computer, click in the folder path at the top and type CMD, then press enter._
 
-1. Clone the repository:
+2. Clone the repository:
    For this step you need Git installed, but you can just download the zip file instead by clicking the button at the top of this page ☝️
 
 ```
 git clone https://github.com/Torantulino/Auto-GPT.git
 ```
 
-2. Navigate to the project directory:
+3. Navigate to the project directory:
    _(Type this into your CMD window, you're aiming to navigate the CMD window to the repository you just downloaded)_
 
 ```
 cd 'Auto-GPT'
 ```
 
-3. Install the required dependencies:
+4. Install the required dependencies:
    _(Again, type this into your CMD window)_
 
 ```
 pip install -r requirements.txt
 ```
 
-4. Rename `.env.template` to `.env` and fill in your `OPENAI_API_KEY`. If you plan to use Speech Mode, fill in your `ELEVEN_LABS_API_KEY` as well.
+5. Rename `.env.template` to `.env` and fill in your `OPENAI_API_KEY`. If you plan to use Speech Mode, fill in your `ELEVEN_LABS_API_KEY` as well.
-
+  - Obtain your OpenAI API key from: https://platform.openai.com/account/api-keys.
-- Obtain your OpenAI API key from: https://platform.openai.com/account/api-keys.
+  - Obtain your ElevenLabs API key from: https://elevenlabs.io. You can view your xi-api-key using the "Profile" tab on the website.
-- Obtain your ElevenLabs API key from: https://elevenlabs.io. You can view your xi-api-key using the "Profile" tab on the website.
+  - If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and then:
-- If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and provide the `OPENAI_AZURE_API_BASE`, `OPENAI_AZURE_API_VERSION` and `OPENAI_AZURE_DEPLOYMENT_ID` values as explained here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section. Additionally you need separate deployments for both embeddings and chat. Add their ID values to `OPENAI_AZURE_CHAT_DEPLOYMENT_ID` and `OPENAI_AZURE_EMBEDDINGS_DEPLOYMENT_ID` respectively
+    - Rename `azure.yaml.template` to `azure.yaml` and provide the relevant `azure_api_base`, `azure_api_version` and all of the deployment ids for the relevant models in the `azure_model_map` section:
+      - `fast_llm_model_deployment_id` - your gpt-3.5-turbo or gpt-4 deployment id
+      - `smart_llm_model_deployment_id` - your gpt-4 deployment id
+      - `embedding_model_deployment_id` - your text-embedding-ada-002 v2 deployment id
+    - Please specify all of these values as double quoted strings
+    - details can be found here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section and here: https://learn.microsoft.com/en-us/azure/cognitive-services/openai/tutorials/embeddings?tabs=command-line for the embedding model.
 
 ## 🔧 Usage
 
@@ -115,7 +127,7 @@ python scripts/main.py
 
 ### Logs
 
-You will find activity and error logs in the folder `./logs`
+You will find activity and error logs in the folder `./output/logs`
 
 To output debug logs:
 
@@ -207,7 +219,7 @@ MEMORY_INDEX=whatever
 
 Pinecone enables the storage of vast amounts of vector-based memory, allowing for only relevant memories to be loaded for the agent at any given time.
 
-1. Go to app.pinecone.io and make an account if you don't already have one.
+1. Go to [pinecone](https://app.pinecone.io/) and make an account if you don't already have one.
 2. Choose the `Starter` plan to avoid being charged.
 3. Find your API key and region under the default project in the left sidebar.
 
@@ -233,7 +245,6 @@ export PINECONE_ENV="Your pinecone region" # something like: us-east4-gcp
 
 ```
 
-
 ## Setting Your Cache Type
 
 By default Auto-GPT is going to use LocalCache instead of redis or Pinecone.
@@ -337,11 +348,13 @@ coverage run -m unittest discover tests
 
 ## Run linter
 
-This project uses [flake8](https://flake8.pycqa.org/en/latest/) for linting. To run the linter, run the following command:
+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`. See the [flake8 rules](https://www.flake8rules.com/) for more information.
+
+To run the linter, run the following command:
 
 ```
 flake8 scripts/ tests/
 
 # Or, if you want to run flake8 with the same configuration as the CI:
-flake8 scripts/ tests/ --select E303,W293,W291,W292,E305
+flake8 scripts/ tests/ --select E303,W293,W291,W292,E305,E231,E302
 ```

ai_settings.yaml

@@ -1,7 +0,0 @@
-ai_goals:
-- Increase net worth.
-- Develop and manage multiple businesses autonomously.
-- Play to your strengths as a Large Language Model.
-ai_name: Entrepreneur-GPT
-ai_role: an AI designed to autonomously develop and run businesses with the sole goal
-  of increasing your net worth.

azure.yaml.template

@@ -0,0 +1,7 @@
+azure_api_type: azure_ad
+azure_api_base: your-base-url-for-azure
+azure_api_version: api-version-for-azure
+azure_model_map:
+    fast_llm_model_deployment_id: gpt35-deployment-id-for-azure
+    smart_llm_model_deployment_id: gpt4-deployment-id-for-azure 
+    embedding_model_deployment_id: embedding-deployment-id-for-azure

requirements.txt

@@ -16,4 +16,5 @@ redis
 orjson
 Pillow
 coverage
-flake8
+flake8
+numpy

scripts/agent_manager.py

@@ -6,6 +6,7 @@ agents = {}  # key, (task, full_message_history, model)
 # Create new GPT agent
 # TODO: Centralise use of create_chat_completion() to globally enforce token limit
 
+
 def create_agent(task, prompt, model):
     """Create a new agent and return its key"""
     global next_key

scripts/ai_config.py

@@ -2,6 +2,7 @@ import yaml
 import data
 import os
 
+
 class AIConfig:
     """
     A class object that contains the configuration information for the AI

scripts/ai_functions.py

@@ -45,6 +45,7 @@ def improve_code(suggestions: List[str], code: str) -> str:
     result_string = call_ai_function(function_string, args, description_string)
     return result_string
 
+
 def write_tests(code: str, focus: List[str]) -> str:
     """
     A function that takes in code and focus topics and returns a response from create chat completion api call.

scripts/browse.py

@@ -6,6 +6,7 @@ from urllib.parse import urlparse, urljoin
 
 cfg = Config()
 
+
 # Function to check if the URL is valid
 def is_valid_url(url):
     try:
@@ -14,49 +15,51 @@ def is_valid_url(url):
     except ValueError:
         return False
 
+
 # Function to sanitize the URL
 def sanitize_url(url):
     return urljoin(url, urlparse(url).path)
 
-# Function to make a request with a specified timeout and handle exceptions
-def make_request(url, timeout=10):
-    try:
-        response = requests.get(url, headers=cfg.user_agent_header, timeout=timeout)
-        response.raise_for_status()
-        return response
-    except requests.exceptions.RequestException as e:
-        return "Error: " + str(e)
 
 # Define and check for local file address prefixes
 def check_local_file_access(url):
     local_prefixes = ['file:///', 'file://localhost', 'http://localhost', 'https://localhost']
     return any(url.startswith(prefix) for prefix in local_prefixes)
 
+
+def get_response(url, headers=cfg.user_agent_header, timeout=10):
+    try:
+        # Restrict access to local files
+        if check_local_file_access(url):
+            raise ValueError('Access to local files is restricted')
+
+        # Most basic check if the URL is valid:
+        if not url.startswith('http://') and not url.startswith('https://'):
+            raise ValueError('Invalid URL format')
+
+        sanitized_url = sanitize_url(url)
+
+        response = requests.get(sanitized_url, headers=headers, timeout=timeout)
+
+        # Check if the response contains an HTTP error
+        if response.status_code >= 400:
+            return None, "Error: HTTP " + str(response.status_code) + " error"
+
+        return response, None
+    except ValueError as ve:
+        # Handle invalid URL format
+        return None, "Error: " + str(ve)
+
+    except requests.exceptions.RequestException as re:
+        # Handle exceptions related to the HTTP request (e.g., connection errors, timeouts, etc.)
+        return None, "Error: " + str(re)
+
+
 def scrape_text(url):
     """Scrape text from a webpage"""
-    # Basic check if the URL is valid
+    response, error_message = get_response(url)
-    if not url.startswith('http'):
+    if error_message:
-        return "Error: Invalid URL"
+        return error_message
-
-    # Restrict access to local files
-    if check_local_file_access(url):
-        return "Error: Access to local files is restricted"
-
-    # Validate the input URL
-    if not is_valid_url(url):
-        # Sanitize the input URL
-        sanitized_url = sanitize_url(url)
-
-        # Make the request with a timeout and handle exceptions
-        response = make_request(sanitized_url)
-
-        if isinstance(response, str):
-            return response
-    else:
-        # Sanitize the input URL
-        sanitized_url = sanitize_url(url)
-
-        response = requests.get(sanitized_url, headers=cfg.user_agent_header)
 
     soup = BeautifulSoup(response.text, "html.parser")
 
@@ -89,11 +92,9 @@ def format_hyperlinks(hyperlinks):
 
 def scrape_links(url):
     """Scrape links from a webpage"""
-    response = requests.get(url, headers=cfg.user_agent_header)
+    response, error_message = get_response(url)
-
+    if error_message:
-    # Check if the response contains an HTTP error
+        return error_message
-    if response.status_code >= 400:
-        return "error"
 
     soup = BeautifulSoup(response.text, "html.parser")
 
@@ -131,6 +132,7 @@ def create_message(chunk, question):
         "content": f"\"\"\"{chunk}\"\"\" Using the above text, please answer the following question: \"{question}\" -- if the question cannot be answered using the text, please summarize the text."
     }
 
+
 def summarize_text(text, question):
     """Summarize text using the LLM model"""
     if not text:

scripts/call_ai_function.py

@@ -3,6 +3,8 @@ from config import Config
 cfg = Config()
 
 from llm_utils import create_chat_completion
+
+
 # This is a magic function that can do anything with no-code. See
 # https://github.com/Torantulino/AI-Functions for more info.
 def call_ai_function(function, args, description, model=None):

scripts/chat.py

@@ -9,6 +9,7 @@ import logging
 
 cfg = Config()
 
+
 def create_chat_message(role, content):
     """
     Create a chat message with the given role and content.

scripts/commands.py

@@ -7,7 +7,7 @@ import speak
 from config import Config
 import ai_functions as ai
 from file_operations import read_file, write_to_file, append_to_file, delete_file, search_files
-from execute_code import execute_python_file
+from execute_code import execute_python_file, execute_shell
 from json_parser import fix_and_parse_json
 from image_gen import generate_image
 from duckduckgo_search import ddg
@@ -24,6 +24,7 @@ def is_valid_int(value):
     except ValueError:
         return False
 
+
 def get_command(response):
     """Parse the response and return the command name and arguments"""
     try:
@@ -103,6 +104,11 @@ def execute_command(command_name, arguments):
             return ai.write_tests(arguments["code"], arguments.get("focus"))
         elif command_name == "execute_python_file":  # Add this command
             return execute_python_file(arguments["file"])
+        elif command_name == "execute_shell":
+            if cfg.execute_local_commands:
+                return execute_shell(arguments["command_line"])
+            else:
+                return "You are not allowed to run local shell commands. To execute shell commands, EXECUTE_LOCAL_COMMANDS must be set to 'True' in your config. Do not attempt to bypass the restriction."
         elif command_name == "generate_image":
             return generate_image(arguments["prompt"])
         elif command_name == "do_nothing":
@@ -130,6 +136,7 @@ def google_search(query, num_results=8):
 
     return json.dumps(search_results, ensure_ascii=False, indent=4)
 
+
 def google_official_search(query, num_results=8):
     """Return the results of a google search using the official Google API"""
     from googleapiclient.discovery import build
@@ -166,6 +173,7 @@ def google_official_search(query, num_results=8):
     # Return the list of search result URLs
     return search_results_links
 
+
 def browse_website(url, question):
     """Browse a website and return the summary and links"""
     summary = get_text_summary(url, question)

scripts/config.py

@@ -1,6 +1,7 @@
 import abc
 import os
 import openai
+import yaml
 from dotenv import load_dotenv
 # Load environment variables from .env file
 load_dotenv()
@@ -44,15 +45,13 @@ class Config(metaclass=Singleton):
         self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 8000))
 
         self.openai_api_key = os.getenv("OPENAI_API_KEY")
-        self.use_azure = False
+        self.temperature = float(os.getenv("TEMPERATURE", "1"))
         self.use_azure = os.getenv("USE_AZURE") == 'True'
+        self.execute_local_commands = os.getenv('EXECUTE_LOCAL_COMMANDS', 'False') == 'True'
+
         if self.use_azure:
-            self.openai_api_base = os.getenv("OPENAI_AZURE_API_BASE")
+            self.load_azure_config()
-            self.openai_api_version = os.getenv("OPENAI_AZURE_API_VERSION")
+            openai.api_type = self.openai_api_type
-            self.openai_deployment_id = os.getenv("OPENAI_AZURE_DEPLOYMENT_ID")
-            self.azure_chat_deployment_id = os.getenv("OPENAI_AZURE_CHAT_DEPLOYMENT_ID")
-            self.azure_embeddigs_deployment_id = os.getenv("OPENAI_AZURE_EMBEDDINGS_DEPLOYMENT_ID")
-            openai.api_type = "azure"
             openai.api_base = self.openai_api_base
             openai.api_version = self.openai_api_version
 
@@ -74,7 +73,7 @@ class Config(metaclass=Singleton):
 
         # User agent headers to use when browsing web
         # Some websites might just completely deny request with an error code if no user agent was found.
-        self.user_agent_header = {"User-Agent":"Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"}
+        self.user_agent_header = {"User-Agent": "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_4) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.97 Safari/537.36"}
         self.redis_host = os.getenv("REDIS_HOST", "localhost")
         self.redis_port = os.getenv("REDIS_PORT", "6379")
         self.redis_password = os.getenv("REDIS_PASSWORD", "")
@@ -86,6 +85,47 @@ class Config(metaclass=Singleton):
         # Initialize the OpenAI API client
         openai.api_key = self.openai_api_key
 
+    def get_azure_deployment_id_for_model(self, model: str) -> str:
+        """
+        Returns the relevant deployment id for the model specified.
+
+        Parameters:
+            model(str): The model to map to the deployment id.
+
+        Returns:
+            The matching deployment id if found, otherwise an empty string.
+        """
+        if model == self.fast_llm_model:
+            return self.azure_model_to_deployment_id_map["fast_llm_model_deployment_id"]
+        elif model == self.smart_llm_model:
+            return self.azure_model_to_deployment_id_map["smart_llm_model_deployment_id"]
+        elif model == "text-embedding-ada-002":
+            return self.azure_model_to_deployment_id_map["embedding_model_deployment_id"]
+        else:
+            return ""
+
+    AZURE_CONFIG_FILE = os.path.join(os.path.dirname(__file__), '..', 'azure.yaml')
+
+    def load_azure_config(self, config_file: str=AZURE_CONFIG_FILE) -> None:
+        """
+        Loads the configuration parameters for Azure hosting from the specified file path as a yaml file.
+
+        Parameters:
+            config_file(str): The path to the config yaml file. DEFAULT: "../azure.yaml"
+
+        Returns:
+            None
+        """
+        try:
+            with open(config_file) as file:
+                config_params = yaml.load(file, Loader=yaml.FullLoader)
+        except FileNotFoundError:
+            config_params = {}
+        self.openai_api_type = os.getenv("OPENAI_API_TYPE", config_params.get("azure_api_type", "azure"))
+        self.openai_api_base = os.getenv("OPENAI_AZURE_API_BASE", config_params.get("azure_api_base", ""))
+        self.openai_api_version = os.getenv("OPENAI_AZURE_API_VERSION", config_params.get("azure_api_version", ""))
+        self.azure_model_to_deployment_id_map = config_params.get("azure_model_map", [])
+
     def set_continuous_mode(self, value: bool):
         """Set the continuous mode value."""
         self.continuous_mode = value

scripts/data.py

@@ -1,6 +1,7 @@
 import os
 from pathlib import Path
 
+
 def load_prompt():
     """Load the prompt from data/prompt.txt"""
     try:

scripts/data/prompt.txt

@@ -22,9 +22,10 @@ COMMANDS:
 16. Get Improved Code: "improve_code", args: "suggestions": "<list_of_suggestions>", "code": "<full_code_string>"
 17. Write Tests: "write_tests", args: "code": "<full_code_string>", "focus": "<list_of_focus_areas>"
 18. Execute Python File: "execute_python_file", args: "file": "<file>"
-19. Task Complete (Shutdown): "task_complete", args: "reason": "<reason>"
+19. Execute Shell Command, non-interactive commands only: "execute_shell", args: "command_line": "<command_line>".
-20. Generate Image: "generate_image", args: "prompt": "<prompt>"
+20. Task Complete (Shutdown): "task_complete", args: "reason": "<reason>"
-21. Do Nothing: "do_nothing", args: ""
+21. Generate Image: "generate_image", args: "prompt": "<prompt>"
+22. Do Nothing: "do_nothing", args: ""
 
 RESOURCES:
 
@@ -44,8 +45,7 @@ You should only respond in JSON format as described below
 
 RESPONSE FORMAT:
 {
-    "thoughts":
+    "thoughts": {
-    {
         "text": "thought",
         "reasoning": "reasoning",
         "plan": "- short bulleted\n- list that conveys\n- long-term plan",
@@ -54,7 +54,7 @@ RESPONSE FORMAT:
     },
     "command": {
         "name": "command name",
-        "args":{
+        "args": {
             "arg name": "value"
         }
     }

scripts/execute_code.py

@@ -1,17 +1,20 @@
 import docker
 import os
+import subprocess
+
+
+WORKSPACE_FOLDER = "auto_gpt_workspace"
 
 
 def execute_python_file(file):
     """Execute a Python file in a Docker container and return the output"""
-    workspace_folder = "auto_gpt_workspace"
 
-    print (f"Executing file '{file}' in workspace '{workspace_folder}'")
+    print (f"Executing file '{file}' in workspace '{WORKSPACE_FOLDER}'")
 
     if not file.endswith(".py"):
         return "Error: Invalid file type. Only .py files are allowed."
 
-    file_path = os.path.join(workspace_folder, file)
+    file_path = os.path.join(WORKSPACE_FOLDER, file)
 
     if not os.path.isfile(file_path):
         return f"Error: File '{file}' does not exist."
@@ -19,14 +22,31 @@ def execute_python_file(file):
     try:
         client = docker.from_env()
 
+        image_name = 'python:3.10'
+        try:
+            client.images.get(image_name)
+            print(f"Image '{image_name}' found locally")
+        except docker.errors.ImageNotFound:
+            print(f"Image '{image_name}' not found locally, pulling from Docker Hub")
+            # Use the low-level API to stream the pull response
+            low_level_client = docker.APIClient()
+            for line in low_level_client.pull(image_name, stream=True, decode=True):
+                # Print the status and progress, if available
+                status = line.get('status')
+                progress = line.get('progress')
+                if status and progress:
+                    print(f"{status}: {progress}")
+                elif status:
+                    print(status)
+
         # You can replace 'python:3.8' with the desired Python image/version
         # You can find available Python images on Docker Hub:
         # https://hub.docker.com/_/python
         container = client.containers.run(
-            'python:3.10',
+            image_name,
             f'python {file}',
             volumes={
-                os.path.abspath(workspace_folder): {
+                os.path.abspath(WORKSPACE_FOLDER): {
                     'bind': '/workspace',
                     'mode': 'ro'}},
             working_dir='/workspace',
@@ -46,3 +66,23 @@ def execute_python_file(file):
 
     except Exception as e:
         return f"Error: {str(e)}"
+
+
+def execute_shell(command_line):
+
+    current_dir = os.getcwd()
+
+    if not WORKSPACE_FOLDER in current_dir: # Change dir into workspace if necessary
+        work_dir = os.path.join(os.getcwd(), WORKSPACE_FOLDER)
+        os.chdir(work_dir)
+
+    print (f"Executing command '{command_line}' in working directory '{os.getcwd()}'")
+
+    result = subprocess.run(command_line, capture_output=True, shell=True)
+    output = f"STDOUT:\n{result.stdout}\nSTDERR:\n{result.stderr}"
+
+    # Change back to whatever the prior working dir was
+
+    os.chdir(current_dir)
+
+    return output

scripts/file_operations.py

@@ -38,7 +38,7 @@ def write_to_file(filename, text):
         directory = os.path.dirname(filepath)
         if not os.path.exists(directory):
             os.makedirs(directory)
-        with open(filepath, "w") as f:
+        with open(filepath, "w", encoding='utf-8') as f:
             f.write(text)
         return "File written to successfully."
     except Exception as e:
@@ -65,6 +65,7 @@ def delete_file(filename):
     except Exception as e:
         return "Error: " + str(e)
 
+
 def search_files(directory):
     found_files = []
 

scripts/image_gen.py

@@ -11,6 +11,7 @@ cfg = Config()
 
 working_directory = "auto_gpt_workspace"
 
+
 def generate_image(prompt):
 
     filename = str(uuid.uuid4()) + ".jpg"

scripts/llm_utils.py

@@ -4,12 +4,13 @@ cfg = Config()
 
 openai.api_key = cfg.openai_api_key
 
+
 # Overly simple abstraction until we create something better
-def create_chat_completion(messages, model=None, temperature=None, max_tokens=None)->str:
+def create_chat_completion(messages, model=None, temperature=cfg.temperature, max_tokens=None)->str:
     """Create a chat completion using the OpenAI API"""
     if cfg.use_azure:
         response = openai.ChatCompletion.create(
-            deployment_id=cfg.azure_chat_deployment_id,
+            deployment_id=cfg.get_azure_deployment_id_for_model(model),
             model=model,
             messages=messages,
             temperature=temperature,

scripts/logger.py

@@ -124,6 +124,12 @@ class Logger(metaclass=Singleton):
         self.logger.setLevel(level)
         self.typing_logger.setLevel(level)
 
+    def double_check(self, additionalText=None):
+        if not additionalText:
+            additionalText = "Please ensure you've setup and configured everything correctly. Read https://github.com/Torantulino/Auto-GPT#readme to double check. You can also create a github issue or join the discord and ask there!"
+
+        self.typewriter_log("DOUBLE CHECK CONFIGURATION", Fore.YELLOW, additionalText)
+
 
 '''
 Output stream to console using simulated typing
@@ -151,6 +157,7 @@ class TypingConsoleHandler(logging.StreamHandler):
         except Exception:
             self.handleError(record)
 
+
 class ConsoleHandler(logging.StreamHandler):
     def emit(self, record):
         msg = self.format(record)
@@ -160,13 +167,11 @@ class ConsoleHandler(logging.StreamHandler):
             self.handleError(record)
 
 
-'''
-Allows to handle custom placeholders 'title_color' and 'message_no_color'.
-To use this formatter, make sure to pass 'color', 'title' as log extras.
-'''
-
-
 class AutoGptFormatter(logging.Formatter):
+    """
+    Allows to handle custom placeholders 'title_color' and 'message_no_color'.
+    To use this formatter, make sure to pass 'color', 'title' as log extras.
+    """
     def format(self, record: LogRecord) -> str:
         if (hasattr(record, 'color')):
             record.title_color = getattr(record, 'color') + getattr(record, 'title') + " " + Style.RESET_ALL

scripts/main.py

@@ -20,16 +20,18 @@ import logging
 
 cfg = Config()
 
+
 def check_openai_api_key():
     """Check if the OpenAI API key is set in config.py or as an environment variable."""
     if not cfg.openai_api_key:
         print(
             Fore.RED +
-            "Please set your OpenAI API key in config.py or as an environment variable."
+            "Please set your OpenAI API key in .env or as an environment variable."
         )
         print("You can get your key from https://beta.openai.com/account/api-keys")
         exit(1)
 
+
 def attempt_to_fix_json_by_finding_outermost_brackets(json_string):
     if cfg.speak_mode and cfg.debug_mode:
       speak.say_text("I have received an invalid JSON response from the OpenAI API. Trying to fix it now.")
@@ -58,6 +60,7 @@ def attempt_to_fix_json_by_finding_outermost_brackets(json_string):
 
     return json_string
 
+
 def print_assistant_thoughts(assistant_reply):
     """Prints the assistant's thoughts to the console"""
     global ai_name
@@ -262,6 +265,7 @@ def prompt_user():
     config = AIConfig(ai_name, ai_role, ai_goals)
     return config
 
+
 def parse_arguments():
     """Parses the arguments passed to the script"""
     global cfg
@@ -322,132 +326,136 @@ def parse_arguments():
         supported_memory = get_supported_memory_backends()
         chosen = args.memory_type
         if not chosen in supported_memory:
-            print_to_console("ONLY THE FOLLOWING MEMORY BACKENDS ARE SUPPORTED: ", Fore.RED, f'{supported_memory}')
+            logger.typewriter_log("ONLY THE FOLLOWING MEMORY BACKENDS ARE SUPPORTED: ", Fore.RED, f'{supported_memory}')
-            print_to_console(f"Defaulting to: ", Fore.YELLOW, cfg.memory_backend)
+            logger.typewriter_log(f"Defaulting to: ", Fore.YELLOW, cfg.memory_backend)
         else:
             cfg.memory_backend = chosen
 
 
-# TODO: fill in llm values here
+def main():
-check_openai_api_key()
+    global ai_name, memory
-cfg = Config()
+    # TODO: fill in llm values here
-parse_arguments()
+    check_openai_api_key()
-logger.set_level(logging.DEBUG if cfg.debug_mode else logging.INFO)
+    parse_arguments()
-ai_name = ""
+    logger.set_level(logging.DEBUG if cfg.debug_mode else logging.INFO)
-prompt = construct_prompt()
+    ai_name = ""
-# print(prompt)
+    prompt = construct_prompt()
-# Initialize variables
+    # print(prompt)
-full_message_history = []
+    # Initialize variables
-result = None
+    full_message_history = []
-next_action_count = 0
+    result = None
-# Make a constant:
+    next_action_count = 0
-user_input = "Determine which next command to use, and respond using the format specified above:"
+    # Make a constant:
-
+    user_input = "Determine which next command to use, and respond using the format specified above:"
-# Initialize memory and make sure it is empty.
+    # Initialize memory and make sure it is empty.
-# this is particularly important for indexing and referencing pinecone memory
+    # this is particularly important for indexing and referencing pinecone memory
-memory = get_memory(cfg, init=True)
+    memory = get_memory(cfg, init=True)
-print('Using memory of type: ' + memory.__class__.__name__)
+    print('Using memory of type: ' + memory.__class__.__name__)
-
+    # Interaction Loop
-# Interaction Loop
+    loop_count = 0
-loop_count = 0
+    while True:
-while True:
+         # Discontinue if continuous limit is reached
-    # Discontinue if continuous limit is reached
+        loop_count += 1
-    loop_count += 1
+        if cfg.continuous_mode and cfg.continuous_limit > 0 and loop_count > cfg.continuous_limit:
-    if cfg.continuous_mode and cfg.continuous_limit > 0 and loop_count > cfg.continuous_limit:
+            logger.typewriter_log("Continuous Limit Reached: ", Fore.RED, f"{cfg.continuous_limit}")
-        logger.typewriter_log("Continuous Limit Reached: ", Fore.RED, f"{cfg.continuous_limit}")
-        break
-
-    # Send message to AI, get response
-    with Spinner("Thinking... "):
-        assistant_reply = chat.chat_with_ai(
-            prompt,
-            user_input,
-            full_message_history,
-            memory,
-            cfg.fast_token_limit) # TODO: This hardcodes the model to use GPT3.5. Make this an argument
-
-    # Print Assistant thoughts
-    print_assistant_thoughts(assistant_reply)
-
-    # Get command name and arguments
-    try:
-        command_name, arguments = cmd.get_command(attempt_to_fix_json_by_finding_outermost_brackets(assistant_reply))
-        if cfg.speak_mode:
-            speak.say_text(f"I want to execute {command_name}")
-    except Exception as e:
-        logger.error("Error: \n", str(e))
-
-    if not cfg.continuous_mode and next_action_count == 0:
-        ### GET USER AUTHORIZATION TO EXECUTE COMMAND ###
-        # Get key press: Prompt the user to press enter to continue or escape
-        # to exit
-        user_input = ""
-        logger.typewriter_log(
-            "NEXT ACTION: ",
-            Fore.CYAN,
-            f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}  ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}")
-        print(
-            f"Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for {ai_name}...",
-            flush=True)
-        while True:
-            console_input = utils.clean_input(Fore.MAGENTA + "Input:" + Style.RESET_ALL)
-            if console_input.lower().rstrip() == "y":
-                user_input = "GENERATE NEXT COMMAND JSON"
-                break
-            elif console_input.lower().startswith("y -"):
-                try:
-                    next_action_count = abs(int(console_input.split(" ")[1]))
-                    user_input = "GENERATE NEXT COMMAND JSON"
-                except ValueError:
-                    print("Invalid input format. Please enter 'y -n' where n is the number of continuous tasks.")
-                    continue
-                break
-            elif console_input.lower() == "n":
-                user_input = "EXIT"
-                break
-            else:
-                user_input = console_input
-                command_name = "human_feedback"
-                break
-
-        if user_input == "GENERATE NEXT COMMAND JSON":
-            logger.typewriter_log(
-            "-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
-            Fore.MAGENTA,
-            "")
-        elif user_input == "EXIT":
-            print("Exiting...", flush=True)
             break
-    else:
-        # Print command
-        logger.typewriter_log(
-            "NEXT ACTION: ",
-            Fore.CYAN,
-            f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}  ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}")
 
-    # Execute command
+        # Send message to AI, get response
-    if command_name is not None and command_name.lower().startswith( "error" ):
+        with Spinner("Thinking... "):
-        result = f"Command {command_name} threw the following error: " + arguments
+            assistant_reply = chat.chat_with_ai(
-    elif command_name == "human_feedback":
+                prompt,
-        result = f"Human feedback: {user_input}"
+                user_input,
-    else:
+                full_message_history,
-        result = f"Command {command_name} returned: {cmd.execute_command(command_name, arguments)}"
+                memory,
-        if next_action_count > 0:
+                cfg.fast_token_limit)  # TODO: This hardcodes the model to use GPT3.5. Make this an argument
-            next_action_count -= 1
 
-    memory_to_add = f"Assistant Reply: {assistant_reply} " \
+        # Print Assistant thoughts
-                    f"\nResult: {result} " \
+        print_assistant_thoughts(assistant_reply)
-                    f"\nHuman Feedback: {user_input} "
 
-    memory.add(memory_to_add)
+        # Get command name and arguments
+        try:
+            command_name, arguments = cmd.get_command(
+                attempt_to_fix_json_by_finding_outermost_brackets(assistant_reply))
+            if cfg.speak_mode:
+                speak.say_text(f"I want to execute {command_name}")
+        except Exception as e:
+            logger.error("Error: \n", str(e))
 
-    # Check if there's a result from the command append it to the message
+        if not cfg.continuous_mode and next_action_count == 0:
-    # history
+            ### GET USER AUTHORIZATION TO EXECUTE COMMAND ###
-    if result is not None:
+            # Get key press: Prompt the user to press enter to continue or escape
-        full_message_history.append(chat.create_chat_message("system", result))
+            # to exit
-        logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
+            user_input = ""
-    else:
+            logger.typewriter_log(
-        full_message_history.append(
+                "NEXT ACTION: ",
-            chat.create_chat_message(
+                Fore.CYAN,
-                "system", "Unable to execute command"))
+                f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}  ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}")
-        logger.typewriter_log("SYSTEM: ", Fore.YELLOW, "Unable to execute command")
+            print(
+                f"Enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter feedback for {ai_name}...",
+                flush=True)
+            while True:
+                console_input = utils.clean_input(Fore.MAGENTA + "Input:" + Style.RESET_ALL)
+                if console_input.lower().rstrip() == "y":
+                    user_input = "GENERATE NEXT COMMAND JSON"
+                    break
+                elif console_input.lower().startswith("y -"):
+                    try:
+                        next_action_count = abs(int(console_input.split(" ")[1]))
+                        user_input = "GENERATE NEXT COMMAND JSON"
+                    except ValueError:
+                        print("Invalid input format. Please enter 'y -n' where n is the number of continuous tasks.")
+                        continue
+                    break
+                elif console_input.lower() == "n":
+                    user_input = "EXIT"
+                    break
+                else:
+                    user_input = console_input
+                    command_name = "human_feedback"
+                    break
+
+            if user_input == "GENERATE NEXT COMMAND JSON":
+                logger.typewriter_log(
+                    "-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
+                    Fore.MAGENTA,
+                    "")
+            elif user_input == "EXIT":
+                print("Exiting...", flush=True)
+                break
+        else:
+            # Print command
+            logger.typewriter_log(
+                "NEXT ACTION: ",
+                Fore.CYAN,
+                f"COMMAND = {Fore.CYAN}{command_name}{Style.RESET_ALL}  ARGUMENTS = {Fore.CYAN}{arguments}{Style.RESET_ALL}")
+
+        # Execute command
+        if command_name is not None and command_name.lower().startswith("error"):
+            result = f"Command {command_name} threw the following error: " + arguments
+        elif command_name == "human_feedback":
+            result = f"Human feedback: {user_input}"
+        else:
+            result = f"Command {command_name} returned: {cmd.execute_command(command_name, arguments)}"
+            if next_action_count > 0:
+                next_action_count -= 1
+
+        memory_to_add = f"Assistant Reply: {assistant_reply} " \
+                        f"\nResult: {result} " \
+                        f"\nHuman Feedback: {user_input} "
+
+        memory.add(memory_to_add)
+
+        # Check if there's a result from the command append it to the message
+        # history
+        if result is not None:
+            full_message_history.append(chat.create_chat_message("system", result))
+            logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
+        else:
+            full_message_history.append(
+                chat.create_chat_message(
+                    "system", "Unable to execute command"))
+            logger.typewriter_log("SYSTEM: ", Fore.YELLOW, "Unable to execute command")
+
+
+if __name__ == "__main__":
+    main()

scripts/memory/__init__.py

@@ -1,4 +1,5 @@
 from memory.local import LocalCache
+from memory.no_memory import NoMemory
 
 # List of supported memory backends
 # Add a backend to this list if the import attempt is successful
@@ -18,6 +19,7 @@ except ImportError:
     print("Pinecone not installed. Skipping import.")
     PineconeMemory = None
 
+
 def get_memory(cfg, init=False):
     memory = None
     if cfg.memory_backend == "pinecone":
@@ -34,6 +36,8 @@ def get_memory(cfg, init=False):
                   " use Redis as a memory backend.")
         else:
             memory = RedisMemory(cfg)
+    elif cfg.memory_backend == "no_memory":
+        memory = NoMemory(cfg)
 
     if memory is None:
         memory = LocalCache(cfg)
@@ -41,6 +45,7 @@ def get_memory(cfg, init=False):
             memory.clear()
     return memory
 
+
 def get_supported_memory_backends():
     return supported_memory
 
@@ -50,4 +55,5 @@ __all__ = [
     "LocalCache",
     "RedisMemory",
     "PineconeMemory",
+    "NoMemory"
 ]

scripts/memory/base.py

@@ -2,13 +2,14 @@
 import abc
 from config import AbstractSingleton, Config
 import openai
+
 cfg = Config()
 
 
 def get_ada_embedding(text):
     text = text.replace("\n", " ")
     if cfg.use_azure:
-        return openai.Embedding.create(input=[text], engine=cfg.azure_embeddigs_deployment_id, model="text-embedding-ada-002")["data"][0]["embedding"]
+        return openai.Embedding.create(input=[text], engine=cfg.get_azure_deployment_id_for_model("text-embedding-ada-002"))["data"][0]["embedding"]
     else:
         return openai.Embedding.create(input=[text], model="text-embedding-ada-002")["data"][0]["embedding"]
 

scripts/memory/no_memory.py

@@ -0,0 +1,66 @@
+from typing import Optional, List, Any
+
+from memory.base import MemoryProviderSingleton
+
+
+class NoMemory(MemoryProviderSingleton):
+    def __init__(self, cfg):
+        """
+        Initializes the NoMemory provider.
+
+        Args:
+            cfg: The config object.
+
+        Returns: None
+        """
+        pass
+
+    def add(self, data: str) -> str:
+        """
+        Adds a data point to the memory. No action is taken in NoMemory.
+
+        Args:
+            data: The data to add.
+
+        Returns: An empty string.
+        """
+        return ""
+
+    def get(self, data: str) -> Optional[List[Any]]:
+        """
+        Gets the data from the memory that is most relevant to the given data.
+        NoMemory always returns None.
+
+        Args:
+            data: The data to compare to.
+
+        Returns: None
+        """
+        return None
+
+    def clear(self) -> str:
+        """
+        Clears the memory. No action is taken in NoMemory.
+
+        Returns: An empty string.
+        """
+        return ""
+
+    def get_relevant(self, data: str, num_relevant: int = 5) -> Optional[List[Any]]:
+        """
+        Returns all the data in the memory that is relevant to the given data.
+        NoMemory always returns None.
+
+        Args:
+            data: The data to compare to.
+            num_relevant: The number of relevant data to return.
+
+        Returns: None
+        """
+        return None
+
+    def get_stats(self):
+        """
+        Returns: An empty dictionary as there are no stats in NoMemory.
+        """
+        return {}

scripts/memory/pinecone.py

@@ -2,6 +2,8 @@
 import pinecone
 
 from memory.base import MemoryProviderSingleton, get_ada_embedding
+from logger import logger
+from colorama import Fore, Style
 
 
 class PineconeMemory(MemoryProviderSingleton):
@@ -17,6 +19,15 @@ class PineconeMemory(MemoryProviderSingleton):
         # for now this works.
         # we'll need a more complicated and robust system if we want to start with memory.
         self.vec_num = 0
+
+        try:
+            pinecone.whoami()
+        except Exception as e:
+            logger.typewriter_log("FAILED TO CONNECT TO PINECONE", Fore.RED, Style.BRIGHT + str(e) + Style.RESET_ALL)
+            logger.double_check("Please ensure you have setup and configured Pinecone properly for use. " +
+                               f"You can check out {Fore.CYAN + Style.BRIGHT}https://github.com/Torantulino/Auto-GPT#-pinecone-api-key-setup{Style.RESET_ALL} to ensure you've set up everything correctly.")
+            exit(1)
+
         if table_name not in pinecone.list_indexes():
             pinecone.create_index(table_name, dimension=dimension, metric=metric, pod_type=pod_type)
         self.index = pinecone.Index(table_name)

scripts/memory/redismem.py

@@ -7,6 +7,8 @@ from redis.commands.search.indexDefinition import IndexDefinition, IndexType
 import numpy as np
 
 from memory.base import MemoryProviderSingleton, get_ada_embedding
+from logger import logger
+from colorama import Fore, Style
 
 
 SCHEMA = [
@@ -44,6 +46,16 @@ class RedisMemory(MemoryProviderSingleton):
             db=0  # Cannot be changed
         )
         self.cfg = cfg
+
+        # Check redis connection
+        try:
+            self.redis.ping()
+        except redis.ConnectionError as e:
+            logger.typewriter_log("FAILED TO CONNECT TO REDIS", Fore.RED, Style.BRIGHT + str(e) + Style.RESET_ALL)
+            logger.double_check("Please ensure you have setup and configured Redis properly for use. " +
+                                f"You can check out {Fore.CYAN + Style.BRIGHT}https://github.com/Torantulino/Auto-GPT#redis-setup{Style.RESET_ALL} to ensure you've set up everything correctly.")
+            exit(1)
+
         if cfg.wipe_redis_on_start:
             self.redis.flushall()
         try:

scripts/speak.py

@@ -31,6 +31,7 @@ tts_headers = {
 mutex_lock = Lock() # Ensure only one sound is played at a time
 queue_semaphore = Semaphore(1) # The amount of sounds to queue before blocking the main thread
 
+
 def eleven_labs_speech(text, voice_index=0):
     """Speak text using elevenlabs.io's API"""
     tts_url = "https://api.elevenlabs.io/v1/text-to-speech/{voice_id}".format(
@@ -51,6 +52,7 @@ def eleven_labs_speech(text, voice_index=0):
         print("Response content:", response.content)
         return False
 
+
 def gtts_speech(text):
     tts = gtts.gTTS(text)
     with mutex_lock:
@@ -58,6 +60,7 @@ def gtts_speech(text):
         playsound("speech.mp3", True)
         os.remove("speech.mp3")
 
+
 def macos_tts_speech(text, voice_index=0):
     if voice_index == 0:
         os.system(f'say "{text}"')
@@ -67,6 +70,7 @@ def macos_tts_speech(text, voice_index=0):
         else:
             os.system(f'say -v Samantha "{text}"')
 
+
 def say_text(text, voice_index=0):
 
     def speak():

scripts/token_counter.py

@@ -1,6 +1,7 @@
 import tiktoken
 from typing import List, Dict
 
+
 def count_message_tokens(messages : List[Dict[str, str]], model : str = "gpt-3.5-turbo-0301") -> int:
     """
     Returns the number of tokens used by a list of messages.
@@ -41,6 +42,7 @@ def count_message_tokens(messages : List[Dict[str, str]], model : str = "gpt-3.5
     num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
     return num_tokens
 
+
 def count_string_tokens(string: str, model_name: str) -> int:
     """
     Returns the number of tokens in a text string.

tests.py

@@ -3,6 +3,6 @@ import unittest
 if __name__ == "__main__":
     # Load all tests from the 'scripts/tests' package
     suite = unittest.defaultTestLoader.discover('scripts/tests')
-    
+
     # Run the tests
     unittest.TextTestRunner().run(suite)

tests/integration/memory_tests.py

@@ -8,6 +8,7 @@ sys.path.append(str(Path(__file__).resolve().parent.parent.parent / 'scripts'))
 from config import Config
 from memory.local import LocalCache
 
+
 class TestLocalCache(unittest.TestCase):
 
     def random_string(self, length):

tests/local_cache_test.py

@@ -4,6 +4,7 @@ import sys
 sys.path.append(os.path.abspath('../scripts'))
 from memory.local import LocalCache
 
+
 def MockConfig():
     return type('MockConfig', (object,), {
         'debug_mode': False,
@@ -12,6 +13,7 @@ def MockConfig():
         'memory_index': 'auto-gpt',
     })
 
+
 class TestLocalCache(unittest.TestCase):
 
     def setUp(self):

tests/test_config.py

@@ -1,6 +1,7 @@
 import unittest
 from scripts.config import Config
 
+
 class TestConfig(unittest.TestCase):
 
     def test_singleton(self):

tests/test_json_parser.py

@@ -3,6 +3,7 @@ import tests.context
 
 from scripts.json_parser import fix_and_parse_json
 
+
 class TestParseJson(unittest.TestCase):
     def test_valid_json(self):
         # Test that a valid JSON string is parsed correctly
@@ -13,12 +14,14 @@ class TestParseJson(unittest.TestCase):
     def test_invalid_json_minor(self):
         # Test that an invalid JSON string can be fixed with gpt
         json_str = '{"name": "John", "age": 30, "city": "New York",}'
-        self.assertRaises(Exception, fix_and_parse_json, json_str, try_to_fix_with_gpt=False)
+        with self.assertRaises(Exception):
+            fix_and_parse_json(json_str, try_to_fix_with_gpt=False)
 
     def test_invalid_json_major_with_gpt(self):
         # Test that an invalid JSON string raises an error when try_to_fix_with_gpt is False
         json_str = 'BEGIN: "name": "John" - "age": 30 - "city": "New York" :END'
-        self.assertRaises(Exception, fix_and_parse_json, json_str, try_to_fix_with_gpt=False)
+        with self.assertRaises(Exception):
+             fix_and_parse_json(json_str, try_to_fix_with_gpt=False)
 
     def test_invalid_json_major_without_gpt(self):
         # Test that a REALLY invalid JSON string raises an error when try_to_fix_with_gpt is False
@@ -50,7 +53,7 @@ class TestParseJson(unittest.TestCase):
         good_obj = {
           "command": {
               "name": "browse_website",
-              "args":{
+              "args": {
                   "url": "https://github.com/Torantulino/Auto-GPT"
               }
           },
@@ -89,7 +92,7 @@ class TestParseJson(unittest.TestCase):
         good_obj = {
     "command": {
         "name": "browse_website",
-        "args":{
+        "args": {
             "url": "https://github.com/Torantulino/Auto-GPT"
         }
     },

tests/unit/json_tests.py

@@ -5,6 +5,7 @@ import sys
 sys.path.append(os.path.abspath('../scripts'))
 from json_parser import fix_and_parse_json
 
+
 class TestParseJson(unittest.TestCase):
     def test_valid_json(self):
         # Test that a valid JSON string is parsed correctly
@@ -52,7 +53,7 @@ class TestParseJson(unittest.TestCase):
         good_obj = {
           "command": {
               "name": "browse_website",
-              "args":{
+              "args": {
                   "url": "https://github.com/Torantulino/Auto-GPT"
               }
           },
@@ -91,7 +92,7 @@ class TestParseJson(unittest.TestCase):
         good_obj = {
     "command": {
         "name": "browse_website",
-        "args":{
+        "args": {
             "url": "https://github.com/Torantulino/Auto-GPT"
         }
     },

tests/unit/test_browse_scrape_links.py

@@ -0,0 +1,118 @@
+
+# Generated by CodiumAI
+
+# Dependencies:
+# pip install pytest-mock
+import pytest
+
+from scripts.browse import scrape_links
+
+"""
+Code Analysis
+
+Objective:
+The objective of the 'scrape_links' function is to scrape hyperlinks from a
+given URL and return them in a formatted way.
+
+Inputs:
+- url: a string representing the URL to be scraped.
+
+Flow:
+1. Send a GET request to the given URL using the requests library and the user agent header from the config file.
+2. Check if the response contains an HTTP error. If it does, return "error".
+3. Parse the HTML content of the response using the BeautifulSoup library.
+4. Remove any script and style tags from the parsed HTML.
+5. Extract all hyperlinks from the parsed HTML using the 'extract_hyperlinks' function.
+6. Format the extracted hyperlinks using the 'format_hyperlinks' function.
+7. Return the formatted hyperlinks.
+
+Outputs:
+- A list of formatted hyperlinks.
+
+Additional aspects:
+- The function uses the 'requests' and 'BeautifulSoup' libraries to send HTTP
+requests and parse HTML content, respectively.
+- The 'extract_hyperlinks' function is called to extract hyperlinks from the parsed HTML.
+- The 'format_hyperlinks' function is called to format the extracted hyperlinks.
+- The function checks for HTTP errors and returns "error" if any are found.
+"""
+
+
+class TestScrapeLinks:
+
+    # Tests that the function returns a list of formatted hyperlinks when
+    # provided with a valid url that returns a webpage with hyperlinks.
+    def test_valid_url_with_hyperlinks(self):
+        url = "https://www.google.com"
+        result = scrape_links(url)
+        assert len(result) > 0
+        assert isinstance(result, list)
+        assert isinstance(result[0], str)
+
+    # Tests that the function returns correctly formatted hyperlinks when given a valid url.
+    def test_valid_url(self, mocker):
+        # Mock the requests.get() function to return a response with sample HTML containing hyperlinks
+        mock_response = mocker.Mock()
+        mock_response.status_code = 200
+        mock_response.text = "<html><body><a href='https://www.google.com'>Google</a></body></html>"
+        mocker.patch('requests.get', return_value=mock_response)
+
+        # Call the function with a valid URL
+        result = scrape_links("https://www.example.com")
+
+        # Assert that the function returns correctly formatted hyperlinks
+        assert result == ["Google (https://www.google.com)"]
+
+    # Tests that the function returns "error" when given an invalid url.
+    def test_invalid_url(self, mocker):
+        # Mock the requests.get() function to return an HTTP error response
+        mock_response = mocker.Mock()
+        mock_response.status_code = 404
+        mocker.patch('requests.get', return_value=mock_response)
+
+        # Call the function with an invalid URL
+        result = scrape_links("https://www.invalidurl.com")
+
+        # Assert that the function returns "error"
+        assert "Error:" in result
+
+    # Tests that the function returns an empty list when the html contains no hyperlinks.
+    def test_no_hyperlinks(self, mocker):
+        # Mock the requests.get() function to return a response with sample HTML containing no hyperlinks
+        mock_response = mocker.Mock()
+        mock_response.status_code = 200
+        mock_response.text = "<html><body><p>No hyperlinks here</p></body></html>"
+        mocker.patch('requests.get', return_value=mock_response)
+
+        # Call the function with a URL containing no hyperlinks
+        result = scrape_links("https://www.example.com")
+
+        # Assert that the function returns an empty list
+        assert result == []
+
+    # Tests that scrape_links() correctly extracts and formats hyperlinks from
+    # a sample HTML containing a few hyperlinks.
+    def test_scrape_links_with_few_hyperlinks(self, mocker):
+        # Mock the requests.get() function to return a response with a sample HTML containing hyperlinks
+        mock_response = mocker.Mock()
+        mock_response.status_code = 200
+        mock_response.text = """
+            <html>
+                <body>
+                    <div id="google-link"><a href="https://www.google.com">Google</a></div>
+                    <div id="github"><a href="https://github.com">GitHub</a></div>
+                    <div id="CodiumAI"><a href="https://www.codium.ai">CodiumAI</a></div>
+                </body>
+            </html>
+        """
+        mocker.patch('requests.get', return_value=mock_response)
+
+        # Call the function being tested
+        result = scrape_links("https://www.example.com")
+
+        # Assert that the function returns a list of formatted hyperlinks
+        assert isinstance(result, list)
+        assert len(result) == 3
+        assert result[0] == "Google (https://www.google.com)"
+        assert result[1] == "GitHub (https://github.com)"
+        assert result[2] == "CodiumAI (https://www.codium.ai)"

tests/unit/test_browse_scrape_text.py

@@ -2,7 +2,6 @@
 # Generated by CodiumAI
 
 import requests
-import tests.context
 
 from scripts.browse import scrape_text
 
@@ -10,7 +9,8 @@ from scripts.browse import scrape_text
 Code Analysis
 
 Objective:
-The objective of the "scrape_text" function is to scrape the text content from a given URL and return it as a string, after removing any unwanted HTML tags and scripts.
+The objective of the "scrape_text" function is to scrape the text content from
+a given URL and return it as a string, after removing any unwanted HTML tags and scripts.
 
 Inputs:
 - url: a string representing the URL of the webpage to be scraped.
@@ -33,6 +33,7 @@ Additional aspects:
 - The function uses a generator expression to split the text into lines and chunks, which can improve performance for large amounts of text.
 """
 
+
 class TestScrapeText:
 
     # Tests that scrape_text() returns the expected text when given a valid URL.