Merge branch 'master' into add_website_memory

.env.template

@@ -1,19 +1,117 @@
-PINECONE_API_KEY=your-pinecone-api-key
+################################################################################
-PINECONE_ENV=your-pinecone-region
+### AUTO-GPT - GENERAL SETTINGS
+################################################################################
+# EXECUTE_LOCAL_COMMANDS - Allow local command execution (Example: False)
+EXECUTE_LOCAL_COMMANDS=False
+# BROWSE_CHUNK_MAX_LENGTH - When browsing website, define the length of chunk stored in memory
+BROWSE_CHUNK_MAX_LENGTH=4000
+# BROWSE_SUMMARY_MAX_TOKEN - Define the maximum length of the summary generated by GPT agent when browsing website
+BROWSE_SUMMARY_MAX_TOKEN=300
+# USER_AGENT - Define the user-agent used by the requests library to browse website (string)
+# 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"
+
+################################################################################
+### LLM PROVIDER
+################################################################################
+
+### OPENAI
+# OPENAI_API_KEY - OpenAI API Key (Example: my-openai-api-key)
+# TEMPERATURE - Sets temperature in OpenAI (Default: 1)
+# USE_AZURE - Use Azure OpenAI or not (Default: False)
 OPENAI_API_KEY=your-openai-api-key
 TEMPERATURE=1
-ELEVENLABS_API_KEY=your-elevenlabs-api-key
+USE_AZURE=False
-ELEVENLABS_VOICE_1_ID=your-voice-id
+
-ELEVENLABS_VOICE_2_ID=your-voice-id
+### AZURE
+# OPENAI_AZURE_API_BASE - OpenAI API base URL for Azure (Example: https://my-azure-openai-url.com)
+# OPENAI_AZURE_API_VERSION - OpenAI API version for Azure (Example: v1)
+# OPENAI_AZURE_DEPLOYMENT_ID - OpenAI deployment ID for Azure (Example: my-deployment-id)
+# OPENAI_AZURE_CHAT_DEPLOYMENT_ID - OpenAI deployment ID for Azure Chat (Example: my-deployment-id-for-azure-chat)
+# OPENAI_AZURE_EMBEDDINGS_DEPLOYMENT_ID - OpenAI deployment ID for Embedding (Example: my-deployment-id-for-azure-embeddigs)
+OPENAI_AZURE_API_BASE=your-base-url-for-azure
+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
+
+################################################################################
+### LLM MODELS
+################################################################################
+
+# SMART_LLM_MODEL - Smart language model (Default: gpt-4)
+# FAST_LLM_MODEL - Fast language model (Default: gpt-3.5-turbo)
 SMART_LLM_MODEL=gpt-4
 FAST_LLM_MODEL=gpt-3.5-turbo
-GOOGLE_API_KEY=
+
-CUSTOM_SEARCH_ENGINE_ID=
+### LLM MODEL SETTINGS
-USE_AZURE=False
+# FAST_TOKEN_LIMIT - Fast token limit for OpenAI (Default: 4000)
-EXECUTE_LOCAL_COMMANDS=False
+# SMART_TOKEN_LIMIT - Smart token limit for OpenAI (Default: 8000)
-IMAGE_PROVIDER=dalle
+# When using --gpt3onlythis needs to be set to 4000.
-HUGGINGFACE_API_TOKEN=
+FAST_TOKEN_LIMIT=4000
-USE_MAC_OS_TTS=False
+SMART_TOKEN_LIMIT=8000
-BROWSE_CHUNK_MAX_LENGTH=4000
+
-BROWSE_SUMMARY_MAX_TOKEN=300
+################################################################################
+### MEMORY
+################################################################################
+
+# MEMORY_BACKEND - Memory backend type (Default: local)
 MEMORY_BACKEND=local
+
+### PINECONE
+# PINECONE_API_KEY - Pinecone API Key (Example: my-pinecone-api-key)
+# PINECONE_ENV - Pinecone environment (region) (Example: us-west-2)
+PINECONE_API_KEY=your-pinecone-api-key
+PINECONE_ENV=your-pinecone-region
+
+### REDIS
+# REDIS_HOST - Redis host (Default: localhost)
+# REDIS_PORT - Redis port (Default: 6379)
+# REDIS_PASSWORD - Redis password (Default: "")
+# WIPE_REDIS_ON_START - Wipes data / index on start (Default: False)
+# MEMORY_INDEX - Name of index created in Redis database (Default: auto-gpt)
+REDIS_HOST=localhost
+REDIS_PORT=6379
+REDIS_PASSWORD=
+WIPE_REDIS_ON_START=False
+MEMORY_INDEX=auto-gpt
+
+################################################################################
+### IMAGE GENERATION PROVIDER
+################################################################################
+
+### OPEN AI
+# IMAGE_PROVIDER - Image provider (Example: dalle)
+IMAGE_PROVIDER=dalle
+
+### HUGGINGFACE
+# STABLE DIFFUSION
+# (Default URL: https://api-inference.huggingface.co/models/CompVis/stable-diffusion-v1-4)
+# Set in image_gen.py)
+# HUGGINGFACE_API_TOKEN - HuggingFace API token (Example: my-huggingface-api-token)
+HUGGINGFACE_API_TOKEN=your-huggingface-api-token
+
+################################################################################
+### SEARCH PROVIDER
+################################################################################
+
+### GOOGLE
+# GOOGLE_API_KEY - Google API key (Example: my-google-api-key)
+# CUSTOM_SEARCH_ENGINE_ID - Custom search engine ID (Example: my-custom-search-engine-id)
+GOOGLE_API_KEY=your-google-api-key
+CUSTOM_SEARCH_ENGINE_ID=your-custom-search-engine-id
+
+################################################################################
+### TTS PROVIDER
+################################################################################
+
+### MAC OS
+# USE_MAC_OS_TTS - Use Mac OS TTS or not (Default: False)
+USE_MAC_OS_TTS=False
+
+### ELEVENLABS
+# ELEVENLABS_API_KEY - Eleven Labs API key (Example: my-elevenlabs-api-key)
+# ELEVENLABS_VOICE_1_ID - Eleven Labs voice 1 ID (Example: my-voice-id-1)
+# ELEVENLABS_VOICE_2_ID - Eleven Labs voice 2 ID (Example: my-voice-id-2)
+ELEVENLABS_API_KEY=your-elevenlabs-api-key
+ELEVENLABS_VOICE_1_ID=your-voice-id-1
+ELEVENLABS_VOICE_2_ID=your-voice-id-2

.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: |

README.md

@@ -1,9 +1,9 @@
 # Auto-GPT: An Autonomous GPT-4 Experiment
 
 ![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)
+[![Twitter Follow](https://img.shields.io/twitter/follow/siggravitas?style=social)](https://twitter.com/SigGravitas)
-[![](https://dcbadge.vercel.app/api/server/PQ7VX6TY4t?style=flat)](https://discord.gg/PQ7VX6TY4t)
+[![Discord Follow](https://dcbadge.vercel.app/api/server/autogpt?style=flat)](https://discord.gg/autogpt)
-[![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/ci.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
 
@@ -64,38 +71,38 @@ Your support is greatly appreciated
 
 Optional:
 
-- ElevenLabs Key (If you want the AI to speak)
+- [ElevenLabs Key](https://elevenlabs.io/) (If you want the AI to speak)
 
 ## 💾 Installation
 
 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 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:
@@ -120,7 +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:
 
@@ -238,7 +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.
@@ -342,11 +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
 ```

azure.yaml.template

@@ -1,3 +1,4 @@
+azure_api_type: azure_ad
 azure_api_base: your-base-url-for-azure
 azure_api_version: api-version-for-azure
 azure_model_map:

docker-compose.yml

@@ -0,0 +1,16 @@
+# To boot the app run the following:
+# docker-compose run auto-gpt
+version: "3.9"
+
+services:
+  auto-gpt:
+    depends_on:
+      - redis
+    build: ./
+    volumes:
+      - "./scripts:/app"
+      - ".env:/app/.env"
+    profiles: ["exclude-from-up"]
+
+  redis:
+    image: "redis/redis-stack-server:latest"

requirements.txt

@@ -17,3 +17,4 @@ orjson
 Pillow
 coverage
 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

@@ -1,6 +1,7 @@
 import yaml
-import data
 import os
+from prompt import get_prompt
+
 
 class AIConfig:
     """
@@ -46,7 +47,7 @@ class AIConfig:
         """
 
         try:
-            with open(config_file) as file:
+            with open(config_file, encoding='utf-8') as file:
                 config_params = yaml.load(file, Loader=yaml.FullLoader)
         except FileNotFoundError:
             config_params = {}
@@ -90,5 +91,5 @@ class AIConfig:
         for i, goal in enumerate(self.ai_goals):
             full_prompt += f"{i+1}. {goal}\n"
 
-        full_prompt += f"\n\n{data.load_prompt()}"
+        full_prompt += f"\n\n{get_prompt()}"
         return full_prompt

scripts/ai_functions.py

@@ -1,8 +1,7 @@
-from typing import List, Optional
+from typing import List
 import json
 from config import Config
 from call_ai_function import call_ai_function
-from json_parser import fix_and_parse_json
 cfg = Config()
 
 

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.
@@ -69,7 +70,7 @@ def chat_with_ai(
             logger.debug(f"Token limit: {token_limit}")
             send_token_limit = token_limit - 1000
 
-            relevant_memory = permanent_memory.get_relevant(str(full_message_history[-9:]), 10)
+            relevant_memory = '' if len(full_message_history) ==0 else  permanent_memory.get_relevant(str(full_message_history[-9:]), 10)
 
             logger.debug(f'Memory Stats: {permanent_memory.get_stats()}')
 

scripts/commands.py

@@ -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:
@@ -135,6 +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
@@ -171,6 +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

@@ -36,6 +36,7 @@ class Config(metaclass=Singleton):
         """Initialize the Config class"""
         self.debug_mode = False
         self.continuous_mode = False
+        self.continuous_limit = 0
         self.speak_mode = False
 
         self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo")
@@ -46,14 +47,13 @@ class Config(metaclass=Singleton):
         self.browse_summary_max_token =  int(os.getenv("BROWSE_SUMMARY_MAX_TOKEN", 300))
 
         self.openai_api_key = os.getenv("OPENAI_API_KEY")
-        self.temperature = int(os.getenv("TEMPERATURE", "1"))
+        self.temperature = float(os.getenv("TEMPERATURE", "1"))
-        self.use_azure = False
         self.use_azure = os.getenv("USE_AZURE") == 'True'
         self.execute_local_commands = os.getenv('EXECUTE_LOCAL_COMMANDS', 'False') == 'True'
 
         if self.use_azure:
             self.load_azure_config()
-            openai.api_type = "azure"
+            openai.api_type = self.openai_api_type
             openai.api_base = self.openai_api_base
             openai.api_version = self.openai_api_version
 
@@ -76,7 +76,6 @@ 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 = os.getenv("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", "")
@@ -124,14 +123,19 @@ class Config(metaclass=Singleton):
                 config_params = yaml.load(file, Loader=yaml.FullLoader)
         except FileNotFoundError:
             config_params = {}
-        self.openai_api_base = config_params.get("azure_api_base", "")
+        self.openai_api_type = os.getenv("OPENAI_API_TYPE", config_params.get("azure_api_type", "azure"))
-        self.openai_api_version = config_params.get("azure_api_version", "")
+        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
 
+    def set_continuous_limit(self, value: int):
+        """Set the continuous limit value."""
+        self.continuous_limit = value
+
     def set_speak_mode(self, value: bool):
         """Set the speak mode value."""
         self.speak_mode = value

scripts/data.py

@@ -1,18 +0,0 @@
-import os
-from pathlib import Path
-
-def load_prompt():
-    """Load the prompt from data/prompt.txt"""
-    try:
-        # get directory of this file:
-        file_dir = Path(__file__).parent
-        prompt_file_path = file_dir / "data" / "prompt.txt"
-
-        # Load the prompt from data/prompt.txt
-        with open(prompt_file_path, "r") as prompt_file:
-            prompt = prompt_file.read()
-
-        return prompt
-    except FileNotFoundError:
-        print("Error: Prompt file not found", flush=True)
-        return ""

scripts/data/prompt.txt

@@ -1,64 +0,0 @@
-CONSTRAINTS:
-
-1. ~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.
-2. If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.
-3. No user assistance
-4. Exclusively use the commands listed in double quotes e.g. "command name"
-
-COMMANDS:
-
-1. Google Search: "google", args: "input": "<search>"
-5. Browse Website: "browse_website", args: "url": "<url>", "question": "<what_you_want_to_find_on_website>"
-6. Start GPT Agent: "start_agent",  args: "name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"
-7. Message GPT Agent: "message_agent", args: "key": "<key>", "message": "<message>"
-8. List GPT Agents: "list_agents", args: ""
-9. Delete GPT Agent: "delete_agent", args: "key": "<key>"
-10. Write to file: "write_to_file", args: "file": "<file>", "text": "<text>"
-11. Read file: "read_file", args: "file": "<file>"
-12. Append to file: "append_to_file", args: "file": "<file>", "text": "<text>"
-13. Delete file: "delete_file", args: "file": "<file>"
-14. Search Files: "search_files", args: "directory": "<directory>"
-15. Evaluate Code: "evaluate_code", args: "code": "<full_code_string>"
-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. Execute Shell Command, non-interactive commands only: "execute_shell", args: "command_line": "<command_line>".
-20. Task Complete (Shutdown): "task_complete", args: "reason": "<reason>"
-21. Generate Image: "generate_image", args: "prompt": "<prompt>"
-22. Do Nothing: "do_nothing", args: ""
-
-RESOURCES:
-
-1. Internet access for searches and information gathering.
-2. Long Term memory management.
-3. GPT-3.5 powered Agents for delegation of simple tasks.
-4. File output.
-
-PERFORMANCE EVALUATION:
-
-1. Continuously review and analyze your actions to ensure you are performing to the best of your abilities.
-2. Constructively self-criticize your big-picture behavior constantly.
-3. Reflect on past decisions and strategies to refine your approach.
-4. Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.
-
-You should only respond in JSON format as described below
-
-RESPONSE FORMAT:
-{
-    "thoughts":
-    {
-        "text": "thought",
-        "reasoning": "reasoning",
-        "plan": "- short bulleted\n- list that conveys\n- long-term plan",
-        "criticism": "constructive self-criticism",
-        "speak": "thoughts summary to say to user"
-    },
-    "command": {
-        "name": "command name",
-        "args":{
-            "arg name": "value"
-        }
-    }
-}
-
-Ensure the response can be parsed by Python json.loads

scripts/execute_code.py

@@ -67,6 +67,7 @@ def execute_python_file(file):
     except Exception as e:
         return f"Error: {str(e)}"
 
+
 def execute_shell(command_line):
 
     current_dir = os.getcwd()

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

@@ -1,12 +1,21 @@
+import time
 import openai
+from colorama import Fore
 from config import Config
+
 cfg = Config()
 
 openai.api_key = cfg.openai_api_key
 
+
 # Overly simple abstraction until we create something better
+# simple retry mechanism when getting a rate error or a bad gateway
 def create_chat_completion(messages, model=None, temperature=cfg.temperature, max_tokens=None)->str:
     """Create a chat completion using the OpenAI API"""
+    response = None
+    num_retries = 5
+    for attempt in range(num_retries):
+        try:
             if cfg.use_azure:
                 response = openai.ChatCompletion.create(
                     deployment_id=cfg.get_azure_deployment_id_for_model(model),
@@ -22,5 +31,22 @@ def create_chat_completion(messages, model=None, temperature=cfg.temperature, ma
                     temperature=temperature,
                     max_tokens=max_tokens
                 )
+            break
+        except openai.error.RateLimitError:
+            if cfg.debug_mode:
+                print(Fore.RED + "Error: ", "API Rate Limit Reached. Waiting 20 seconds..." + Fore.RESET)
+            time.sleep(20)
+        except openai.error.APIError as e:
+            if e.http_status == 502:
+                if cfg.debug_mode:
+                    print(Fore.RED + "Error: ", "API Bad gateway. Waiting 20 seconds..." + Fore.RESET)
+                time.sleep(20)
+            else:
+                raise
+            if attempt == num_retries - 1:
+                raise
+
+    if response is None:
+        raise RuntimeError("Failed to get response after 5 retries")
 
     return response.choices[0].message["content"]

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)
@@ -160,11 +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

@@ -3,7 +3,6 @@ import random
 import commands as cmd
 import utils
 from memory import get_memory, get_supported_memory_backends
-import data
 import chat
 from colorama import Fore, Style
 from spinner import Spinner
@@ -17,19 +16,22 @@ import yaml
 import argparse
 from logger import logger
 import logging
+from prompt import get_prompt
 
 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
@@ -168,8 +171,8 @@ def load_variables(config_file="config.yaml"):
     with open(config_file, "w") as file:
         documents = yaml.dump(config, file)
 
-    prompt = data.load_prompt()
+    prompt = get_prompt()
-    prompt_start = """Your decisions must always be made independently without seeking user assistance. Play to your strengths as a LLM and pursue simple strategies with no legal complications."""
+    prompt_start = """Your decisions must always be made independently without seeking user assistance. Play to your strengths as an LLM and pursue simple strategies with no legal complications."""
 
     # Construct full prompt
     full_prompt = f"You are {ai_name}, {ai_role}\n{prompt_start}\n\nGOALS:\n\n"
@@ -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
@@ -271,6 +275,7 @@ def parse_arguments():
 
     parser = argparse.ArgumentParser(description='Process arguments.')
     parser.add_argument('--continuous', action='store_true', help='Enable Continuous Mode')
+    parser.add_argument('--continuous-limit', '-l', type=int, dest="continuous_limit", help='Defines the number of times to run in continuous mode')
     parser.add_argument('--speak', action='store_true', help='Enable Speak Mode')
     parser.add_argument('--debug', action='store_true', help='Enable Debug Mode')
     parser.add_argument('--gpt3only', action='store_true', help='Enable GPT3.5 Only Mode')
@@ -290,6 +295,17 @@ def parse_arguments():
             "Continuous mode is not recommended. It is potentially dangerous and may cause your AI to run forever or carry out actions you would not usually authorise. Use at your own risk.")
         cfg.set_continuous_mode(True)
 
+        if args.continuous_limit:
+            logger.typewriter_log(
+                "Continuous Limit: ",
+                Fore.GREEN,
+                f"{args.continuous_limit}")
+            cfg.set_continuous_limit(args.continuous_limit)
+
+    # Check if continuous limit is used without continuous mode
+    if args.continuous_limit and not args.continuous:
+        parser.error("--continuous-limit can only be used with --continuous")
+
     if args.speak:
         logger.typewriter_log("Speak Mode: ", Fore.GREEN, "ENABLED")
         cfg.set_speak_mode(True)
@@ -310,33 +326,40 @@ 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
-parse_arguments()
+    # TODO: fill in llm values here
-logger.set_level(logging.DEBUG if cfg.debug_mode else logging.INFO)
+    check_openai_api_key()
-ai_name = ""
+    parse_arguments()
-prompt = construct_prompt()
+    logger.set_level(logging.DEBUG if cfg.debug_mode else logging.INFO)
-# print(prompt)
+    ai_name = ""
-# Initialize variables
+    prompt = construct_prompt()
-full_message_history = []
+    # print(prompt)
-result = None
+    # Initialize variables
-next_action_count = 0
+    full_message_history = []
-# Make a constant:
+    result = None
-user_input = "Determine which next command to use, and respond using the format specified above:"
+    next_action_count = 0
+    # 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.
+    # this is particularly important for indexing and referencing pinecone memory
+    memory = get_memory(cfg, init=True)
+    print('Using memory of type: ' + memory.__class__.__name__)
+    # Interaction Loop
+    loop_count = 0
+    while True:
+         # Discontinue if continuous limit is reached
+        loop_count += 1
+        if cfg.continuous_mode and cfg.continuous_limit > 0 and loop_count > cfg.continuous_limit:
+            logger.typewriter_log("Continuous Limit Reached: ", Fore.YELLOW, f"{cfg.continuous_limit}")
+            break
 
-# Initialize memory and make sure it is empty.
-# this is particularly important for indexing and referencing pinecone memory
-memory = get_memory(cfg, init=True)
-print('Using memory of type: ' + memory.__class__.__name__)
-
-# Interaction Loop
-while True:
         # Send message to AI, get response
         with Spinner("Thinking... "):
             assistant_reply = chat.chat_with_ai(
@@ -351,7 +374,8 @@ while True:
 
         # Get command name and arguments
         try:
-        command_name, arguments = cmd.get_command(attempt_to_fix_json_by_finding_outermost_brackets(assistant_reply))
+            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:
@@ -406,7 +430,7 @@ while True:
                 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" ):
+        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}"
@@ -431,3 +455,7 @@ while True:
                 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

@@ -2,10 +2,10 @@
 import abc
 from config import AbstractSingleton, Config
 import openai
-cfg = Config()
 
 cfg = Config()
 
+
 def get_ada_embedding(text):
     text = text.replace("\n", " ")
     if cfg.use_azure:

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/prompt.py

@@ -0,0 +1,63 @@
+from promptgenerator import PromptGenerator
+
+
+def get_prompt():
+    """
+    This function generates a prompt string that includes various constraints, commands, resources, and performance evaluations.
+
+    Returns:
+        str: The generated prompt string.
+    """
+
+    # Initialize the PromptGenerator object
+    prompt_generator = PromptGenerator()
+
+    # Add constraints to the PromptGenerator object
+    prompt_generator.add_constraint("~4000 word limit for short term memory. Your short term memory is short, so immediately save important information to files.")
+    prompt_generator.add_constraint("If you are unsure how you previously did something or want to recall past events, thinking about similar events will help you remember.")
+    prompt_generator.add_constraint("No user assistance")
+    prompt_generator.add_constraint('Exclusively use the commands listed in double quotes e.g. "command name"')
+
+    # Define the command list
+    commands = [
+        ("Google Search", "google", {"input": "<search>"}),
+        ("Browse Website", "browse_website", {"url": "<url>", "question": "<what_you_want_to_find_on_website>"}),
+        ("Start GPT Agent", "start_agent", {"name": "<name>", "task": "<short_task_desc>", "prompt": "<prompt>"}),
+        ("Message GPT Agent", "message_agent", {"key": "<key>", "message": "<message>"}),
+        ("List GPT Agents", "list_agents", {}),
+        ("Delete GPT Agent", "delete_agent", {"key": "<key>"}),
+        ("Write to file", "write_to_file", {"file": "<file>", "text": "<text>"}),
+        ("Read file", "read_file", {"file": "<file>"}),
+        ("Append to file", "append_to_file", {"file": "<file>", "text": "<text>"}),
+        ("Delete file", "delete_file", {"file": "<file>"}),
+        ("Search Files", "search_files", {"directory": "<directory>"}),
+        ("Evaluate Code", "evaluate_code", {"code": "<full_code_string>"}),
+        ("Get Improved Code", "improve_code", {"suggestions": "<list_of_suggestions>", "code": "<full_code_string>"}),
+        ("Write Tests", "write_tests", {"code": "<full_code_string>", "focus": "<list_of_focus_areas>"}),
+        ("Execute Python File", "execute_python_file", {"file": "<file>"}),
+        ("Execute Shell Command, non-interactive commands only", "execute_shell", { "command_line": "<command_line>"}),
+        ("Task Complete (Shutdown)", "task_complete", {"reason": "<reason>"}),
+        ("Generate Image", "generate_image", {"prompt": "<prompt>"}),
+        ("Do Nothing", "do_nothing", {}),
+    ]
+
+    # Add commands to the PromptGenerator object
+    for command_label, command_name, args in commands:
+        prompt_generator.add_command(command_label, command_name, args)
+
+    # Add resources to the PromptGenerator object
+    prompt_generator.add_resource("Internet access for searches and information gathering.")
+    prompt_generator.add_resource("Long Term memory management.")
+    prompt_generator.add_resource("GPT-3.5 powered Agents for delegation of simple tasks.")
+    prompt_generator.add_resource("File output.")
+
+    # Add performance evaluations to the PromptGenerator object
+    prompt_generator.add_performance_evaluation("Continuously review and analyze your actions to ensure you are performing to the best of your abilities.")
+    prompt_generator.add_performance_evaluation("Constructively self-criticize your big-picture behavior constantly.")
+    prompt_generator.add_performance_evaluation("Reflect on past decisions and strategies to refine your approach.")
+    prompt_generator.add_performance_evaluation("Every command has a cost, so be smart and efficient. Aim to complete tasks in the least number of steps.")
+
+    # Generate the prompt string
+    prompt_string = prompt_generator.generate_prompt_string()
+
+    return prompt_string

scripts/promptgenerator.py

@@ -0,0 +1,129 @@
+import json
+
+
+class PromptGenerator:
+    """
+    A class for generating custom prompt strings based on constraints, commands, resources, and performance evaluations.
+    """
+
+    def __init__(self):
+        """
+        Initialize the PromptGenerator object with empty lists of constraints, commands, resources, and performance evaluations.
+        """
+        self.constraints = []
+        self.commands = []
+        self.resources = []
+        self.performance_evaluation = []
+        self.response_format = {
+            "thoughts": {
+                "text": "thought",
+                "reasoning": "reasoning",
+                "plan": "- short bulleted\n- list that conveys\n- long-term plan",
+                "criticism": "constructive self-criticism",
+                "speak": "thoughts summary to say to user"
+            },
+            "command": {
+                "name": "command name",
+                "args": {
+                    "arg name": "value"
+                }
+            }
+        }
+
+    def add_constraint(self, constraint):
+        """
+        Add a constraint to the constraints list.
+
+        Args:
+            constraint (str): The constraint to be added.
+        """
+        self.constraints.append(constraint)
+
+    def add_command(self, command_label, command_name, args=None):
+        """
+        Add a command to the commands list with a label, name, and optional arguments.
+
+        Args:
+            command_label (str): The label of the command.
+            command_name (str): The name of the command.
+            args (dict, optional): A dictionary containing argument names and their values. Defaults to None.
+        """
+        if args is None:
+            args = {}
+
+        command_args = {arg_key: arg_value for arg_key,
+                        arg_value in args.items()}
+
+        command = {
+            "label": command_label,
+            "name": command_name,
+            "args": command_args,
+        }
+
+        self.commands.append(command)
+
+    def _generate_command_string(self, command):
+        """
+        Generate a formatted string representation of a command.
+
+        Args:
+            command (dict): A dictionary containing command information.
+
+        Returns:
+            str: The formatted command string.
+        """
+        args_string = ', '.join(
+            f'"{key}": "{value}"' for key, value in command['args'].items())
+        return f'{command["label"]}: "{command["name"]}", args: {args_string}'
+
+    def add_resource(self, resource):
+        """
+        Add a resource to the resources list.
+
+        Args:
+            resource (str): The resource to be added.
+        """
+        self.resources.append(resource)
+
+    def add_performance_evaluation(self, evaluation):
+        """
+        Add a performance evaluation item to the performance_evaluation list.
+
+        Args:
+            evaluation (str): The evaluation item to be added.
+        """
+        self.performance_evaluation.append(evaluation)
+
+    def _generate_numbered_list(self, items, item_type='list'):
+        """
+        Generate a numbered list from given items based on the item_type.
+
+        Args:
+            items (list): A list of items to be numbered.
+            item_type (str, optional): The type of items in the list. Defaults to 'list'.
+
+        Returns:
+            str: The formatted numbered list.
+        """
+        if item_type == 'command':
+            return "\n".join(f"{i+1}. {self._generate_command_string(item)}" for i, item in enumerate(items))
+        else:
+            return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items))
+
+    def generate_prompt_string(self):
+        """
+        Generate a prompt string based on the constraints, commands, resources, and performance evaluations.
+
+        Returns:
+            str: The generated prompt string.
+        """
+        formatted_response_format = json.dumps(self.response_format, indent=4)
+        prompt_string = (
+            f"Constraints:\n{self._generate_numbered_list(self.constraints)}\n\n"
+            f"Commands:\n{self._generate_numbered_list(self.commands, item_type='command')}\n\n"
+            f"Resources:\n{self._generate_numbered_list(self.resources)}\n\n"
+            f"Performance Evaluation:\n{self._generate_numbered_list(self.performance_evaluation)}\n\n"
+            f"You should only respond in JSON format as described below \nResponse Format: \n{formatted_response_format} \nEnsure the response can be parsed by Python json.loads"
+        )
+
+        return prompt_string

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/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/promptgenerator_tests.py

@@ -0,0 +1,101 @@
+# Import the required libraries for unit testing
+import unittest
+import sys
+import os
+
+# Add the path to the "scripts" directory to import the PromptGenerator module
+sys.path.append(os.path.abspath("../scripts"))
+from promptgenerator import PromptGenerator
+
+
+# Create a test class for the PromptGenerator, subclassed from unittest.TestCase
+class promptgenerator_tests(unittest.TestCase):
+
+    # Set up the initial state for each test method by creating an instance of PromptGenerator
+    def setUp(self):
+        self.generator = PromptGenerator()
+
+    # Test whether the add_constraint() method adds a constraint to the generator's constraints list
+    def test_add_constraint(self):
+        constraint = "Constraint1"
+        self.generator.add_constraint(constraint)
+        self.assertIn(constraint, self.generator.constraints)
+
+    # Test whether the add_command() method adds a command to the generator's commands list
+    def test_add_command(self):
+        command_label = "Command Label"
+        command_name = "command_name"
+        args = {"arg1": "value1", "arg2": "value2"}
+        self.generator.add_command(command_label, command_name, args)
+        command = {
+            "label": command_label,
+            "name": command_name,
+            "args": args,
+        }
+        self.assertIn(command, self.generator.commands)
+
+    # Test whether the add_resource() method adds a resource to the generator's resources list
+    def test_add_resource(self):
+        resource = "Resource1"
+        self.generator.add_resource(resource)
+        self.assertIn(resource, self.generator.resources)
+
+    # Test whether the add_performance_evaluation() method adds an evaluation to the generator's performance_evaluation list
+    def test_add_performance_evaluation(self):
+        evaluation = "Evaluation1"
+        self.generator.add_performance_evaluation(evaluation)
+        self.assertIn(evaluation, self.generator.performance_evaluation)
+
+    # Test whether the generate_prompt_string() method generates a prompt string with all the added constraints, commands, resources and evaluations
+    def test_generate_prompt_string(self):
+        constraints = ["Constraint1", "Constraint2"]
+        commands = [
+            {
+                "label": "Command1",
+                "name": "command_name1",
+                "args": {"arg1": "value1"},
+            },
+            {
+                "label": "Command2",
+                "name": "command_name2",
+                "args": {},
+            },
+        ]
+        resources = ["Resource1", "Resource2"]
+        evaluations = ["Evaluation1", "Evaluation2"]
+
+        # Add all the constraints, commands, resources, and evaluations to the generator
+        for constraint in constraints:
+            self.generator.add_constraint(constraint)
+        for command in commands:
+            self.generator.add_command(
+                command["label"], command["name"], command["args"])
+        for resource in resources:
+            self.generator.add_resource(resource)
+        for evaluation in evaluations:
+            self.generator.add_performance_evaluation(evaluation)
+
+        # Generate the prompt string and verify its correctness
+        prompt_string = self.generator.generate_prompt_string()
+        self.assertIsNotNone(prompt_string)
+        for constraint in constraints:
+            self.assertIn(constraint, prompt_string)
+        for command in commands:
+            self.assertIn(command["name"], prompt_string)
+
+        # Check for each key-value pair in the command args dictionary
+        for key, value in command["args"].items():
+            self.assertIn(f'"{key}": "{value}"', prompt_string)
+        for resource in resources:
+            self.assertIn(resource, prompt_string)
+        for evaluation in evaluations:
+            self.assertIn(evaluation, prompt_string)
+        self.assertIn("constraints", prompt_string.lower())
+        self.assertIn("commands", prompt_string.lower())
+        self.assertIn("resources", prompt_string.lower())
+        self.assertIn("performance evaluation", prompt_string.lower())
+
+
+# Run the tests when this script is executed
+if __name__ == '__main__':
+    unittest.main()

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"
         }
     },