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Merge branch 'master' into add_website_memory

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Maiko Bossuyt
2023-04-14 18:34:53 +02:00
committed by GitHub
parent a67818648e f6f4f1fbc0
commit 483abb1da1
17 changed files with 501 additions and 182 deletions
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23
.devcontainer/Dockerfile Normal file
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@@ -0,0 +1,23 @@
# [Choice] Python version (use -bullseye variants on local arm64/Apple Silicon): 3, 3.10, 3.9, 3.8, 3.7, 3.6, 3-bullseye, 3.10-bullseye, 3.9-bullseye, 3.8-bullseye, 3.7-bullseye, 3.6-bullseye, 3-buster, 3.10-buster, 3.9-buster, 3.8-buster, 3.7-buster, 3.6-buster
ARG VARIANT=3-bullseye
FROM python:3.8
RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
# Remove imagemagick due to https://security-tracker.debian.org/tracker/CVE-2019-10131
&& apt-get purge -y imagemagick imagemagick-6-common
# Temporary: Upgrade python packages due to https://cve.mitre.org/cgi-bin/cvename.cgi?name=CVE-2022-40897
# They are installed by the base image (python) which does not have the patch.
RUN python3 -m pip install --upgrade setuptools
# [Optional] If your pip requirements rarely change, uncomment this section to add them to the image.
# COPY requirements.txt /tmp/pip-tmp/
# RUN pip3 --disable-pip-version-check --no-cache-dir install -r /tmp/pip-tmp/requirements.txt \
# && rm -rf /tmp/pip-tmp
# [Optional] Uncomment this section to install additional OS packages.
# RUN apt-get update && export DEBIAN_FRONTEND=noninteractive \
# && apt-get -y install --no-install-recommends <your-package-list-here>
# [Optional] Uncomment this line to install global node packages.
# RUN su vscode -c "source /usr/local/share/nvm/nvm.sh && npm install -g <your-package-here>" 2>&1

39
.devcontainer/devcontainer.json Normal file
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@@ -0,0 +1,39 @@
{
"build": {
"dockerfile": "./Dockerfile",
"context": "."
},
"features": {
"ghcr.io/devcontainers/features/common-utils:2": {
"installZsh": "true",
"username": "vscode",
"userUid": "1000",
"userGid": "1000",
"upgradePackages": "true"
},
"ghcr.io/devcontainers/features/python:1": "none",
"ghcr.io/devcontainers/features/node:1": "none",
"ghcr.io/devcontainers/features/git:1": {
"version": "latest",
"ppa": "false"
}
},
// Configure tool-specific properties.
"customizations": {
// Configure properties specific to VS Code.
"vscode": {
// Set *default* container specific settings.json values on container create.
"settings": {
"python.defaultInterpreterPath": "/usr/local/bin/python"
}
}
},
// Use 'forwardPorts' to make a list of ports inside the container available locally.
// "forwardPorts": [],
// Use 'postCreateCommand' to run commands after the container is created.
// "postCreateCommand": "pip3 install --user -r requirements.txt",
// Set `remoteUser` to `root` to connect as root instead. More info: https://aka.ms/vscode-remote/containers/non-root.
"remoteUser": "vscode"
}

6
.env.template
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@@ -9,6 +9,8 @@ BROWSE_CHUNK_MAX_LENGTH=8192
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"
# AI_SETTINGS_FILE - Specifies which AI Settings file to use (defaults to ai_settings.yaml)
AI_SETTINGS_FILE=ai_settings.yaml
################################################################################
### LLM PROVIDER
@@ -108,6 +110,10 @@ CUSTOM_SEARCH_ENGINE_ID=your-custom-search-engine-id
# USE_MAC_OS_TTS - Use Mac OS TTS or not (Default: False)
USE_MAC_OS_TTS=False
### STREAMELEMENTS
# USE_BRIAN_TTS - Use Brian TTS or not (Default: False)
USE_BRIAN_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)

2
.gitignore vendored
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@@ -16,6 +16,8 @@ last_run_ai_settings.yaml
.idea/*
auto-gpt.json
log.txt
log-ingestion.txt
logs
# Coverage reports
.coverage

28
Dockerfile
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@@ -1,7 +1,23 @@
# Use an official Python base image from the Docker Hub
FROM python:3.11-slim
ENV PIP_NO_CACHE_DIR=yes
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY scripts/ .
ENTRYPOINT ["python", "main.py"]
# Set environment variables
ENV PIP_NO_CACHE_DIR=yes \
PYTHONUNBUFFERED=1 \
PYTHONDONTWRITEBYTECODE=1
# Create a non-root user and set permissions
RUN useradd --create-home appuser
WORKDIR /home/appuser
RUN chown appuser:appuser /home/appuser
USER appuser
# Copy the requirements.txt file and install the requirements
COPY --chown=appuser:appuser requirements.txt .
RUN pip install --no-cache-dir --user -r requirements.txt
# Copy the application files
COPY --chown=appuser:appuser scripts/ .
# Set the entrypoint
ENTRYPOINT ["python", "main.py"]

86
README.md
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@@ -46,6 +46,7 @@ Your support is greatly appreciated
- [Setting up environment variables](#setting-up-environment-variables-1)
- [Setting Your Cache Type](#setting-your-cache-type)
- [View Memory Usage](#view-memory-usage)
- [🧠 Memory pre-seeding](#memory-pre-seeding)
- [💀 Continuous Mode ⚠️](#-continuous-mode-️)
- [GPT3.5 ONLY Mode](#gpt35-only-mode)
- [🖼 Image Generation](#-image-generation)
@@ -65,13 +66,16 @@ Your support is greatly appreciated
## 📋 Requirements
- [Python 3.8 or later](https://www.tutorialspoint.com/how-to-install-python-in-windows)
- environments(just choose one)
- [vscode + devcontainer](https://marketplace.visualstudio.com/items?itemName=ms-vscode-remote.remote-containers): It has been configured in the .devcontainer folder and can be used directly
- [Python 3.8 or later](https://www.tutorialspoint.com/how-to-install-python-in-windows)
- [OpenAI API key](https://platform.openai.com/account/api-keys)
- [PINECONE API key](https://www.pinecone.io/)
Optional:
- [ElevenLabs Key](https://elevenlabs.io/) (If you want the AI to speak)
- [PINECONE API key](https://www.pinecone.io/) (If you want Pinecone backed memory)
- ElevenLabs Key (If you want the AI to speak)
## 💾 Installation
@@ -122,8 +126,8 @@ pip install -r requirements.txt
python scripts/main.py
```
2. After each of AUTO-GPT's actions, type "NEXT COMMAND" to authorise them to continue.
3. To exit the program, type "exit" and press Enter.
2. After each of action, enter 'y' to authorise command, 'y -N' to run N continuous commands, 'n' to exit program, or enter additional feedback for the AI.
### Logs
@@ -134,6 +138,14 @@ To output debug logs:
```
python scripts/main.py --debug
```
### Command Line Arguments
Here are some common arguments you can use when running Auto-GPT:
> Replace anything in angled brackets (<>) to a value you want to specify
* `python scripts/main.py --help` to see a list of all available command line arguments.
* `python scripts/main.py --ai-settings <filename>` to run Auto-GPT with a different AI Settings file.
* `python scripts/main.py --use-memory <memory-backend>` to specify one of 3 memory backends: `local`, `redis`, `pinecone` or 'no_memory'.
> **NOTE**: There are shorthands for some of these flags, for example `-m` for `--use-memory`. Use `python scripts/main.py --help` for more information
## 🗣️ Speech Mode
@@ -154,9 +166,10 @@ To use the `google_official_search` command, you need to set up your Google API
4. Go to the [APIs & Services Dashboard](https://console.cloud.google.com/apis/dashboard) and click "Enable APIs and Services". Search for "Custom Search API" and click on it, then click "Enable".
5. Go to the [Credentials](https://console.cloud.google.com/apis/credentials) page and click "Create Credentials". Choose "API Key".
6. Copy the API key and set it as an environment variable named `GOOGLE_API_KEY` on your machine. See setting up environment variables below.
7. Go to the [Custom Search Engine](https://cse.google.com/cse/all) page and click "Add".
8. Set up your search engine by following the prompts. You can choose to search the entire web or specific sites.
9. Once you've created your search engine, click on "Control Panel" and then "Basics". Copy the "Search engine ID" and set it as an environment variable named `CUSTOM_SEARCH_ENGINE_ID` on your machine. See setting up environment variables below.
7. [Enable](https://console.developers.google.com/apis/api/customsearch.googleapis.com) the Custom Search API on your project. (Might need to wait few minutes to propagate)
8. Go to the [Custom Search Engine](https://cse.google.com/cse/all) page and click "Add".
9. Set up your search engine by following the prompts. You can choose to search the entire web or specific sites.
10. Once you've created your search engine, click on "Control Panel" and then "Basics". Copy the "Search engine ID" and set it as an environment variable named `CUSTOM_SEARCH_ENGINE_ID` on your machine. See setting up environment variables below.
_Remember that your free daily custom search quota allows only up to 100 searches. To increase this limit, you need to assign a billing account to the project to profit from up to 10K daily searches._
@@ -225,7 +238,10 @@ Pinecone enables the storage of vast amounts of vector-based memory, allowing fo
### Setting up environment variables
Simply set them in the `.env` file.
In the `.env` file set:
- `PINECONE_API_KEY`
- `PINECONE_ENV` (something like: us-east4-gcp)
- `MEMORY_BACKEND=pinecone`
Alternatively, you can set them from the command line (advanced):
@@ -234,7 +250,7 @@ For Windows Users:
```
setx PINECONE_API_KEY "YOUR_PINECONE_API_KEY"
setx PINECONE_ENV "Your pinecone region" # something like: us-east4-gcp
setx MEMORY_BACKEND "pinecone"
```
For macOS and Linux users:
@@ -242,7 +258,7 @@ For macOS and Linux users:
```
export PINECONE_API_KEY="YOUR_PINECONE_API_KEY"
export PINECONE_ENV="Your pinecone region" # something like: us-east4-gcp
export MEMORY_BACKEND="pinecone"
```
## Setting Your Cache Type
@@ -259,6 +275,52 @@ To switch to either, change the `MEMORY_BACKEND` env variable to the value that
1. View memory usage by using the `--debug` flag :)
## 🧠 Memory pre-seeding
```
# python scripts/data_ingestion.py -h
usage: data_ingestion.py [-h] (--file FILE | --dir DIR) [--init] [--overlap OVERLAP] [--max_length MAX_LENGTH]
Ingest a file or a directory with multiple files into memory. Make sure to set your .env before running this script.
options:
-h, --help show this help message and exit
--file FILE The file to ingest.
--dir DIR The directory containing the files to ingest.
--init Init the memory and wipe its content (default: False)
--overlap OVERLAP The overlap size between chunks when ingesting files (default: 200)
--max_length MAX_LENGTH The max_length of each chunk when ingesting files (default: 4000
# python scripts/data_ingestion.py --dir seed_data --init --overlap 200 --max_length 1000
```
This script located at scripts/data_ingestion.py, allows you to ingest files into memory and pre-seed it before running Auto-GPT.
Memory pre-seeding is a technique that involves ingesting relevant documents or data into the AI's memory so that it can use this information to generate more informed and accurate responses.
To pre-seed the memory, the content of each document is split into chunks of a specified maximum length with a specified overlap between chunks, and then each chunk is added to the memory backend set in the .env file. When the AI is prompted to recall information, it can then access those pre-seeded memories to generate more informed and accurate responses.
This technique is particularly useful when working with large amounts of data or when there is specific information that the AI needs to be able to access quickly.
By pre-seeding the memory, the AI can retrieve and use this information more efficiently, saving time, API call and improving the accuracy of its responses.
You could for example download the documentation of an API, a Github repository, etc. and ingest it into memory before running Auto-GPT.
⚠️ If you use Redis as your memory, make sure to run Auto-GPT with the WIPE_REDIS_ON_START set to False in your .env file.
⚠️For other memory backend, we currently forcefully wipe the memory when starting Auto-GPT. To ingest data with those memory backend, you can call the data_ingestion.py script anytime during an Auto-GPT run.
Memories will be available to the AI immediately as they are ingested, even if ingested while Auto-GPT is running.
In the example above, the script initializes the memory, ingests all files within the seed_data directory into memory with an overlap between chunks of 200 and a maximum length of each chunk of 4000.
Note that you can also use the --file argument to ingest a single file into memory and that the script will only ingest files within the auto_gpt_workspace directory.
You can adjust the max_length and overlap parameters to fine-tune the way the docuents are presented to the AI when it "recall" that memory:
- Adjusting the overlap value allows the AI to access more contextual information from each chunk when recalling information, but will result in more chunks being created and therefore increase memory backend usage and OpenAI API requests.
- Reducing the max_length value will create more chunks, which can save prompt tokens by allowing for more message history in the context, but will also increase the number of chunks.
- Increasing the max_length value will provide the AI with more contextual information from each chunk, reducing the number of chunks created and saving on OpenAI API requests. However, this may also use more prompt tokens and decrease the overall context available to the AI.
## 💀 Continuous Mode ⚠️
Run the AI **without** user authorisation, 100% automated.
@@ -357,4 +419,4 @@ 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,E231,E302
```
```

4
scripts/ai_config.py
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@@ -70,8 +70,8 @@ class AIConfig:
"""
config = {"ai_name": self.ai_name, "ai_role": self.ai_role, "ai_goals": self.ai_goals}
with open(config_file, "w") as file:
yaml.dump(config, file)
with open(config_file, "w", encoding='utf-8') as file:
yaml.dump(config, file, allow_unicode=True)
def construct_full_prompt(self) -> str:
"""

2
scripts/call_ai_function.py
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@@ -13,7 +13,7 @@ def call_ai_function(function, args, description, model=None):
model = cfg.smart_llm_model
# For each arg, if any are None, convert to "None":
args = [str(arg) if arg is not None else "None" for arg in args]
# parse args to comma seperated string
# parse args to comma separated string
args = ", ".join(args)
messages = [
{

5
scripts/config.py
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@@ -38,7 +38,9 @@ class Config(metaclass=Singleton):
self.continuous_mode = False
self.continuous_limit = 0
self.speak_mode = False
self.skip_reprompt = False
self.ai_settings_file = os.getenv("AI_SETTINGS_FILE", "ai_settings.yaml")
self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo")
self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4")
self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 4000))
@@ -64,6 +66,9 @@ class Config(metaclass=Singleton):
self.use_mac_os_tts = False
self.use_mac_os_tts = os.getenv("USE_MAC_OS_TTS")
self.use_brian_tts = False
self.use_brian_tts = os.getenv("USE_BRIAN_TTS")
self.google_api_key = os.getenv("GOOGLE_API_KEY")
self.custom_search_engine_id = os.getenv("CUSTOM_SEARCH_ENGINE_ID")

70
scripts/data_ingestion.py Normal file
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@@ -0,0 +1,70 @@
import argparse
import logging
from config import Config
from memory import get_memory
from file_operations import ingest_file, search_files
cfg = Config()
def configure_logging():
logging.basicConfig(filename='log-ingestion.txt',
filemode='a',
format='%(asctime)s,%(msecs)d %(name)s %(levelname)s %(message)s',
datefmt='%H:%M:%S',
level=logging.DEBUG)
return logging.getLogger('AutoGPT-Ingestion')
def ingest_directory(directory, memory, args):
"""
Ingest all files in a directory by calling the ingest_file function for each file.
:param directory: The directory containing the files to ingest
:param memory: An object with an add() method to store the chunks in memory
"""
try:
files = search_files(directory)
for file in files:
ingest_file(file, memory, args.max_length, args.overlap)
except Exception as e:
print(f"Error while ingesting directory '{directory}': {str(e)}")
def main():
logger = configure_logging()
parser = argparse.ArgumentParser(description="Ingest a file or a directory with multiple files into memory. Make sure to set your .env before running this script.")
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("--file", type=str, help="The file to ingest.")
group.add_argument("--dir", type=str, help="The directory containing the files to ingest.")
parser.add_argument("--init", action='store_true', help="Init the memory and wipe its content (default: False)", default=False)
parser.add_argument("--overlap", type=int, help="The overlap size between chunks when ingesting files (default: 200)", default=200)
parser.add_argument("--max_length", type=int, help="The max_length of each chunk when ingesting files (default: 4000)", default=4000)
args = parser.parse_args()
# Initialize memory
memory = get_memory(cfg, init=args.init)
print('Using memory of type: ' + memory.__class__.__name__)
if args.file:
try:
ingest_file(args.file, memory, args.max_length, args.overlap)
print(f"File '{args.file}' ingested successfully.")
except Exception as e:
logger.error(f"Error while ingesting file '{args.file}': {str(e)}")
print(f"Error while ingesting file '{args.file}': {str(e)}")
elif args.dir:
try:
ingest_directory(args.dir, memory, args)
print(f"Directory '{args.dir}' ingested successfully.")
except Exception as e:
logger.error(f"Error while ingesting directory '{args.dir}': {str(e)}")
print(f"Error while ingesting directory '{args.dir}': {str(e)}")
else:
print("Please provide either a file path (--file) or a directory name (--dir) inside the auto_gpt_workspace directory as input.")
if __name__ == "__main__":
main()

54
scripts/file_operations.py
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@@ -20,6 +20,29 @@ def safe_join(base, *paths):
return norm_new_path
def split_file(content, max_length=4000, overlap=0):
"""
Split text into chunks of a specified maximum length with a specified overlap
between chunks.
:param text: The input text to be split into chunks
:param max_length: The maximum length of each chunk, default is 4000 (about 1k token)
:param overlap: The number of overlapping characters between chunks, default is no overlap
:return: A generator yielding chunks of text
"""
start = 0
content_length = len(content)
while start < content_length:
end = start + max_length
if end + overlap < content_length:
chunk = content[start:end+overlap]
else:
chunk = content[start:content_length]
yield chunk
start += max_length - overlap
def read_file(filename):
"""Read a file and return the contents"""
try:
@@ -31,6 +54,37 @@ def read_file(filename):
return "Error: " + str(e)
def ingest_file(filename, memory, max_length=4000, overlap=200):
"""
Ingest a file by reading its content, splitting it into chunks with a specified
maximum length and overlap, and adding the chunks to the memory storage.
:param filename: The name of the file to ingest
:param memory: An object with an add() method to store the chunks in memory
:param max_length: The maximum length of each chunk, default is 4000
:param overlap: The number of overlapping characters between chunks, default is 200
"""
try:
print(f"Working with file {filename}")
content = read_file(filename)
content_length = len(content)
print(f"File length: {content_length} characters")
chunks = list(split_file(content, max_length=max_length, overlap=overlap))
num_chunks = len(chunks)
for i, chunk in enumerate(chunks):
print(f"Ingesting chunk {i + 1} / {num_chunks} into memory")
memory_to_add = f"Filename: {filename}\n" \
f"Content part#{i + 1}/{num_chunks}: {chunk}"
memory.add(memory_to_add)
print(f"Done ingesting {num_chunks} chunks from {filename}.")
except Exception as e:
print(f"Error while ingesting file '{filename}': {str(e)}")
def write_to_file(filename, text):
"""Write text to a file"""
try:

3
scripts/logger.py
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@@ -24,7 +24,8 @@ For console handler: simulates typing
class Logger(metaclass=Singleton):
def __init__(self):
# create log directory if it doesn't exist
log_dir = os.path.join('..', 'logs')
this_files_dir_path = os.path.dirname(__file__)
log_dir = os.path.join(this_files_dir_path, '../logs')
if not os.path.exists(log_dir):
os.makedirs(log_dir)

314
scripts/main.py
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@@ -129,64 +129,14 @@ def print_assistant_thoughts(assistant_reply):
logger.error("Error: \n", call_stack)
def load_variables(config_file="config.yaml"):
"""Load variables from yaml file if it exists, otherwise prompt the user for input"""
try:
with open(config_file) as file:
config = yaml.load(file, Loader=yaml.FullLoader)
ai_name = config.get("ai_name")
ai_role = config.get("ai_role")
ai_goals = config.get("ai_goals")
except FileNotFoundError:
ai_name = ""
ai_role = ""
ai_goals = []
# Prompt the user for input if config file is missing or empty values
if not ai_name:
ai_name = utils.clean_input("Name your AI: ")
if ai_name == "":
ai_name = "Entrepreneur-GPT"
if not ai_role:
ai_role = utils.clean_input(f"{ai_name} is: ")
if ai_role == "":
ai_role = "an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth."
if not ai_goals:
print("Enter up to 5 goals for your AI: ")
print("For example: \nIncrease net worth, Grow Twitter Account, Develop and manage multiple businesses autonomously'")
print("Enter nothing to load defaults, enter nothing when finished.")
ai_goals = []
for i in range(5):
ai_goal = utils.clean_input(f"Goal {i+1}: ")
if ai_goal == "":
break
ai_goals.append(ai_goal)
if len(ai_goals) == 0:
ai_goals = ["Increase net worth", "Grow Twitter Account", "Develop and manage multiple businesses autonomously"]
# Save variables to yaml file
config = {"ai_name": ai_name, "ai_role": ai_role, "ai_goals": ai_goals}
with open(config_file, "w") as file:
documents = yaml.dump(config, file)
prompt = get_prompt()
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"
for i, goal in enumerate(ai_goals):
full_prompt += f"{i+1}. {goal}\n"
full_prompt += f"\n\n{prompt}"
return full_prompt
def construct_prompt():
"""Construct the prompt for the AI to respond to"""
config = AIConfig.load()
if config.ai_name:
config = AIConfig.load(cfg.ai_settings_file)
if cfg.skip_reprompt and config.ai_name:
logger.typewriter_log("Name :", Fore.GREEN, config.ai_name)
logger.typewriter_log("Role :", Fore.GREEN, config.ai_role)
logger.typewriter_log("Goals:", Fore.GREEN, config.ai_goals)
elif config.ai_name:
logger.typewriter_log(
f"Welcome back! ",
Fore.GREEN,
@@ -274,13 +224,15 @@ def parse_arguments():
cfg.set_speak_mode(False)
parser = argparse.ArgumentParser(description='Process arguments.')
parser.add_argument('--continuous', action='store_true', help='Enable Continuous Mode')
parser.add_argument('--continuous', '-c', 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')
parser.add_argument('--gpt4only', action='store_true', help='Enable GPT4 Only Mode')
parser.add_argument('--use-memory', '-m', dest="memory_type", help='Defines which Memory backend to use')
parser.add_argument('--skip-reprompt', '-y', dest='skip_reprompt', action='store_true', help='Skips the re-prompting messages at the beginning of the script')
parser.add_argument('--ai-settings', '-C', dest='ai_settings_file', help="Specifies which ai_settings.yaml file to use, will also automatically skip the re-prompt.")
args = parser.parse_args()
if args.debug:
@@ -318,10 +270,6 @@ def parse_arguments():
logger.typewriter_log("GPT4 Only Mode: ", Fore.GREEN, "ENABLED")
cfg.set_fast_llm_model(cfg.smart_llm_model)
if args.debug:
logger.typewriter_log("Debug Mode: ", Fore.GREEN, "ENABLED")
cfg.set_debug_mode(True)
if args.memory_type:
supported_memory = get_supported_memory_backends()
chosen = args.memory_type
@@ -331,6 +279,24 @@ def parse_arguments():
else:
cfg.memory_backend = chosen
if args.skip_reprompt:
logger.typewriter_log("Skip Re-prompt: ", Fore.GREEN, "ENABLED")
cfg.skip_reprompt = True
if args.ai_settings_file:
file = args.ai_settings_file
# Validate file
(validated, message) = utils.validate_yaml_file(file)
if not validated:
logger.typewriter_log("FAILED FILE VALIDATION", Fore.RED, message)
logger.double_check()
exit(1)
logger.typewriter_log("Using AI Settings File:", Fore.GREEN, file)
cfg.ai_settings_file = file
cfg.skip_reprompt = True
def main():
global ai_name, memory
@@ -351,110 +317,148 @@ def main():
# 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
agent = Agent(
ai_name=ai_name,
memory=memory,
full_message_history=full_message_history,
next_action_count=next_action_count,
prompt=prompt,
user_input=user_input
)
agent.start_interaction_loop()
# 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)
class Agent:
"""Agent class for interacting with Auto-GPT.
# 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))
Attributes:
ai_name: The name of the agent.
memory: The memory object to use.
full_message_history: The full message history.
next_action_count: The number of actions to execute.
prompt: The prompt to use.
user_input: The user input.
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
"""
def __init__(self,
ai_name,
memory,
full_message_history,
next_action_count,
prompt,
user_input):
self.ai_name = ai_name
self.memory = memory
self.full_message_history = full_message_history
self.next_action_count = next_action_count
self.prompt = prompt
self.user_input = user_input
if user_input == "GENERATE NEXT COMMAND JSON":
logger.typewriter_log(
"-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
Fore.MAGENTA,
"")
elif user_input == "EXIT":
print("Exiting...", flush=True)
def start_interaction_loop(self):
# 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
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
# Send message to AI, get response
with Spinner("Thinking... "):
assistant_reply = chat.chat_with_ai(
self.prompt,
self.user_input,
self.full_message_history,
self.memory,
cfg.fast_token_limit) # TODO: This hardcodes the model to use GPT3.5. Make this an argument
memory_to_add = f"Assistant Reply: {assistant_reply} " \
f"\nResult: {result} " \
f"\nHuman Feedback: {user_input} "
# Print Assistant thoughts
print_assistant_thoughts(assistant_reply)
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
# 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 not cfg.continuous_mode and self.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
self.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 {self.ai_name}...",
flush=True)
while True:
console_input = utils.clean_input(Fore.MAGENTA + "Input:" + Style.RESET_ALL)
if console_input.lower().rstrip() == "y":
self.user_input = "GENERATE NEXT COMMAND JSON"
break
elif console_input.lower().startswith("y -"):
try:
self.next_action_count = abs(int(console_input.split(" ")[1]))
self.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":
self.user_input = "EXIT"
break
else:
self.user_input = console_input
command_name = "human_feedback"
break
if self.user_input == "GENERATE NEXT COMMAND JSON":
logger.typewriter_log(
"-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=",
Fore.MAGENTA,
"")
elif self.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: {self.user_input}"
else:
result = f"Command {command_name} returned: {cmd.execute_command(command_name, arguments)}"
if self.next_action_count > 0:
self.next_action_count -= 1
memory_to_add = f"Assistant Reply: {assistant_reply} " \
f"\nResult: {result} " \
f"\nHuman Feedback: {self.user_input} "
self.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:
self.full_message_history.append(chat.create_chat_message("system", result))
logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result)
else:
self.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__":

2
scripts/memory/__init__.py
View File

@@ -3,7 +3,7 @@ from memory.no_memory import NoMemory
# List of supported memory backends
# Add a backend to this list if the import attempt is successful
supported_memory = ['local']
supported_memory = ['local', 'no_memory']
try:
from memory.redismem import RedisMemory

24
scripts/speak.py
View File

@@ -53,6 +53,24 @@ def eleven_labs_speech(text, voice_index=0):
return False
def brian_speech(text):
"""Speak text using Brian with the streamelements API"""
tts_url = f"https://api.streamelements.com/kappa/v2/speech?voice=Brian&text={text}"
response = requests.get(tts_url)
if response.status_code == 200:
with mutex_lock:
with open("speech.mp3", "wb") as f:
f.write(response.content)
playsound("speech.mp3")
os.remove("speech.mp3")
return True
else:
print("Request failed with status code:", response.status_code)
print("Response content:", response.content)
return False
def gtts_speech(text):
tts = gtts.gTTS(text)
with mutex_lock:
@@ -76,7 +94,11 @@ def say_text(text, voice_index=0):
def speak():
if not cfg.elevenlabs_api_key:
if cfg.use_mac_os_tts == 'True':
macos_tts_speech(text, voice_index)
macos_tts_speech(text)
elif cfg.use_brian_tts == 'True':
success = brian_speech(text)
if not success:
gtts_speech(text)
else:
gtts_speech(text)
else:

6
scripts/spinner.py
View File

@@ -17,10 +17,10 @@ class Spinner:
def spin(self):
"""Spin the spinner"""
while self.running:
sys.stdout.write(next(self.spinner) + " " + self.message + "\r")
sys.stdout.write(f"{next(self.spinner)} {self.message}\r")
sys.stdout.flush()
time.sleep(self.delay)
sys.stdout.write('\r' + ' ' * (len(self.message) + 2) + '\r')
sys.stdout.write(f"\r{' ' * (len(self.message) + 2)}\r")
def __enter__(self):
"""Start the spinner"""
@@ -32,5 +32,5 @@ class Spinner:
"""Stop the spinner"""
self.running = False
self.spinner_thread.join()
sys.stdout.write('\r' + ' ' * (len(self.message) + 2) + '\r')
sys.stdout.write(f"\r{' ' * (len(self.message) + 2)}\r")
sys.stdout.flush()

15
scripts/utils.py
View File

@@ -1,3 +1,7 @@
import yaml
from colorama import Fore
def clean_input(prompt: str=''):
try:
return input(prompt)
@@ -6,3 +10,14 @@ def clean_input(prompt: str=''):
print("Quitting...")
exit(0)
def validate_yaml_file(file: str):
try:
with open(file) as file:
yaml.load(file, Loader=yaml.FullLoader)
except FileNotFoundError:
return (False, f"The file {Fore.CYAN}`{file}`{Fore.RESET} wasn't found")
except yaml.YAMLError as e:
return (False, f"There was an issue while trying to read with your AI Settings file: {e}")
return (True, f"Successfully validated {Fore.CYAN}`{file}`{Fore.RESET}!")