Merge branch 'master' into security-and-robustness-improvements
commit
e9e4f11b4a
|
@ -2,13 +2,14 @@ PINECONE_API_KEY=your-pinecone-api-key
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|||
PINECONE_ENV=your-pinecone-region
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||||
OPENAI_API_KEY=your-openai-api-key
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ELEVENLABS_API_KEY=your-elevenlabs-api-key
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SMART_LLM_MODEL="gpt-4"
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FAST_LLM_MODEL="gpt-3.5-turbo"
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SMART_LLM_MODEL=gpt-4
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FAST_LLM_MODEL=gpt-3.5-turbo
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GOOGLE_API_KEY=
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CUSTOM_SEARCH_ENGINE_ID=
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USE_AZURE=False
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OPENAI_API_BASE=your-base-url-for-azure
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OPENAI_API_VERSION=api-version-for-azure
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OPENAI_DEPLOYMENT_ID=deployment-id-for-azure
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OPENAI_AZURE_API_BASE=your-base-url-for-azure
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OPENAI_AZURE_API_VERSION=api-version-for-azure
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OPENAI_AZURE_DEPLOYMENT_ID=deployment-id-for-azure
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IMAGE_PROVIDER=dalle
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HUGGINGFACE_API_TOKEN=
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HUGGINGFACE_API_TOKEN=
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USE_MAC_OS_TTS=False
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|
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@ -12,3 +12,4 @@ outputs/*
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ai_settings.yaml
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.vscode
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auto-gpt.json
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log.txt
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@ -59,7 +59,7 @@ Your support is greatly appreciated
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## 📋 Requirements
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- [Python 3.8 or later](https://www.tutorialspoint.com/how-to-install-python-in-windows)
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- OpenAI API key
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- PINECONE API key
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- [PINECONE API key](https://www.pinecone.io/)
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Optional:
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- ElevenLabs Key (If you want the AI to speak)
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@ -92,8 +92,8 @@ pip install -r requirements.txt
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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.
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- Obtain your OpenAI API key from: https://platform.openai.com/account/api-keys.
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- Obtain your ElevenLabs API key from: https://beta.elevenlabs.io. You can view your xi-api-key using the "Profile" tab on the website.
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- If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and provide the `OPENAI_API_BASE`, `OPENAI_API_VERSION` and `OPENAI_DEPLOYMENT_ID` values as explained here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section
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- Obtain your ElevenLabs API key from: https://elevenlabs.io. You can view your xi-api-key using the "Profile" tab on the website.
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- If you want to use GPT on an Azure instance, set `USE_AZURE` to `True` and provide the `OPENAI_AZURE_API_BASE`, `OPENAI_AZURE_API_VERSION` and `OPENAI_AZURE_DEPLOYMENT_ID` values as explained here: https://pypi.org/project/openai/ in the `Microsoft Azure Endpoints` section
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## 🔧 Usage
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@ -179,8 +179,7 @@ MEMORY_INDEX=whatever
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## 🌲 Pinecone API Key Setup
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Pinecone enable a vector based memory so a vast memory can be stored and only relevant memories
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are loaded for the agent at any given time.
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Pinecone enables the storage of vast amounts of vector-based memory, allowing for only relevant memories to be loaded for the agent at any given time.
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1. Go to app.pinecone.io and make an account if you don't already have one.
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2. Choose the `Starter` plan to avoid being charged.
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@ -34,7 +34,7 @@ class AIConfig:
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@classmethod
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def load(cls: object, config_file: str=SAVE_FILE) -> object:
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"""
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Returns class object with parameters (ai_name, ai_role, ai_goals) loaded from yaml file if yaml file exists,
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Returns class object with parameters (ai_name, ai_role, ai_goals) loaded from yaml file if yaml file exists,
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else returns class with no parameters.
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Parameters:
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|
@ -42,7 +42,7 @@ class AIConfig:
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config_file (int): The path to the config yaml file. DEFAULT: "../ai_settings.yaml"
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Returns:
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cls (object): A instance of given cls object
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cls (object): A instance of given cls object
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"""
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try:
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@ -61,11 +61,11 @@ class AIConfig:
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"""
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Saves the class parameters to the specified file yaml file path as a yaml file.
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|
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Parameters:
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Parameters:
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config_file(str): The path to the config yaml file. DEFAULT: "../ai_settings.yaml"
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Returns:
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None
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None
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"""
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config = {"ai_name": self.ai_name, "ai_role": self.ai_role, "ai_goals": self.ai_goals}
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@ -76,7 +76,7 @@ class AIConfig:
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"""
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Returns a prompt to the user with the class information in an organized fashion.
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Parameters:
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Parameters:
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None
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Returns:
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@ -92,4 +92,3 @@ class AIConfig:
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full_prompt += f"\n\n{data.load_prompt()}"
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return full_prompt
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|
|
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@ -27,7 +27,7 @@ def evaluate_code(code: str) -> List[str]:
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def improve_code(suggestions: List[str], code: str) -> str:
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"""
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A function that takes in code and suggestions and returns a response from create chat completion api call.
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A function that takes in code and suggestions and returns a response from create chat completion api call.
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Parameters:
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suggestions (List): A list of suggestions around what needs to be improved.
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|
|
|
@ -27,11 +27,20 @@ def make_request(url, timeout=10):
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except requests.exceptions.RequestException as e:
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return "Error: " + str(e)
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# Define and check for local file address prefixes
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def check_local_file_access(url):
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local_prefixes = ['file:///', 'file://localhost', 'http://localhost', 'https://localhost']
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return any(url.startswith(prefix) for prefix in local_prefixes)
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def scrape_text(url):
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"""Scrape text from a webpage"""
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# Basic check if the URL is valid
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if not url.startswith('http'):
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return "Error: Invalid URL"
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# Restrict access to local files
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if check_local_file_access(url):
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return "Error: Access to local files is restricted"
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# Validate the input URL
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if not is_valid_url(url):
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|
@ -155,4 +164,4 @@ def summarize_text(text, question):
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max_tokens=300,
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)
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return final_summary
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return final_summary
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@ -63,10 +63,10 @@ def chat_with_ai(
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"""
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model = cfg.fast_llm_model # TODO: Change model from hardcode to argument
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# Reserve 1000 tokens for the response
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if cfg.debug:
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print(f"Token limit: {token_limit}")
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send_token_limit = token_limit - 1000
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relevant_memory = permanent_memory.get_relevant(str(full_message_history[-5:]), 10)
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|
|
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@ -42,9 +42,6 @@ def get_command(response):
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# Use an empty dictionary if 'args' field is not present in 'command' object
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arguments = command.get("args", {})
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|
||||
if not arguments:
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arguments = {}
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||||
|
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return command_name, arguments
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except json.decoder.JSONDecodeError:
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return "Error:", "Invalid JSON"
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|
|
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@ -33,11 +33,11 @@ class Config(metaclass=Singleton):
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|||
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def __init__(self):
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"""Initialize the Config class"""
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self.debug = False
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self.debug_mode = False
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self.continuous_mode = False
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self.speak_mode = False
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|
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self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo")
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self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo")
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self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4")
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self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 4000))
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self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 8000))
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@ -46,15 +46,18 @@ class Config(metaclass=Singleton):
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self.use_azure = False
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self.use_azure = os.getenv("USE_AZURE") == 'True'
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if self.use_azure:
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self.openai_api_base = os.getenv("OPENAI_API_BASE")
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self.openai_api_version = os.getenv("OPENAI_API_VERSION")
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self.openai_deployment_id = os.getenv("OPENAI_DEPLOYMENT_ID")
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self.openai_api_base = os.getenv("OPENAI_AZURE_API_BASE")
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self.openai_api_version = os.getenv("OPENAI_AZURE_API_VERSION")
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self.openai_deployment_id = os.getenv("OPENAI_AZURE_DEPLOYMENT_ID")
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openai.api_type = "azure"
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openai.api_base = self.openai_api_base
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openai.api_version = self.openai_api_version
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self.elevenlabs_api_key = os.getenv("ELEVENLABS_API_KEY")
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self.use_mac_os_tts = False
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self.use_mac_os_tts = os.getenv("USE_MAC_OS_TTS")
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self.google_api_key = os.getenv("GOOGLE_API_KEY")
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self.custom_search_engine_id = os.getenv("CUSTOM_SEARCH_ENGINE_ID")
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@ -86,9 +89,6 @@ class Config(metaclass=Singleton):
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"""Set the speak mode value."""
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self.speak_mode = value
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def set_debug_mode(self, value: bool):
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self.debug_mode = value
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def set_fast_llm_model(self, value: str):
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"""Set the fast LLM model value."""
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self.fast_llm_model = value
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|
@ -131,4 +131,4 @@ class Config(metaclass=Singleton):
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def set_debug_mode(self, value: bool):
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"""Set the debug mode value."""
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self.debug = value
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self.debug_mode = value
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|
|
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@ -24,7 +24,7 @@ def read_file(filename):
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|||
"""Read a file and return the contents"""
|
||||
try:
|
||||
filepath = safe_join(working_directory, filename)
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with open(filepath, "r") as f:
|
||||
with open(filepath, "r", encoding='utf-8') as f:
|
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content = f.read()
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return content
|
||||
except Exception as e:
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|
|
|
@ -71,11 +71,11 @@ def fix_and_parse_json(
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return json_str
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else:
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||||
raise e
|
||||
|
||||
|
||||
|
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|
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def fix_json(json_str: str, schema: str) -> str:
|
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"""Fix the given JSON string to make it parseable and fully complient with the provided schema."""
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||||
|
||||
|
||||
# Try to fix the JSON using gpt:
|
||||
function_string = "def fix_json(json_str: str, schema:str=None) -> str:"
|
||||
args = [f"'''{json_str}'''", f"'''{schema}'''"]
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|
|
|
@ -76,7 +76,7 @@ def balance_braces(json_string: str) -> str:
|
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json.loads(json_string)
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||||
return json_string
|
||||
except json.JSONDecodeError as e:
|
||||
raise e
|
||||
pass
|
||||
|
||||
|
||||
def fix_invalid_escape(json_str: str, error_message: str) -> str:
|
||||
|
@ -88,7 +88,7 @@ def fix_invalid_escape(json_str: str, error_message: str) -> str:
|
|||
json.loads(json_str)
|
||||
return json_str
|
||||
except json.JSONDecodeError as e:
|
||||
if cfg.debug:
|
||||
if cfg.debug_mode:
|
||||
print('json loads error - fix invalid escape', e)
|
||||
error_message = str(e)
|
||||
return json_str
|
||||
|
@ -103,12 +103,12 @@ def correct_json(json_str: str) -> str:
|
|||
"""
|
||||
|
||||
try:
|
||||
if cfg.debug:
|
||||
if cfg.debug_mode:
|
||||
print("json", json_str)
|
||||
json.loads(json_str)
|
||||
return json_str
|
||||
except json.JSONDecodeError as e:
|
||||
if cfg.debug:
|
||||
if cfg.debug_mode:
|
||||
print('json loads error', e)
|
||||
error_message = str(e)
|
||||
if error_message.startswith('Invalid \\escape'):
|
||||
|
@ -119,7 +119,7 @@ def correct_json(json_str: str) -> str:
|
|||
json.loads(json_str)
|
||||
return json_str
|
||||
except json.JSONDecodeError as e:
|
||||
if cfg.debug:
|
||||
if cfg.debug_mode:
|
||||
print('json loads error - add quotes', e)
|
||||
error_message = str(e)
|
||||
if balanced_str := balance_braces(json_str):
|
||||
|
|
|
@ -1,6 +1,7 @@
|
|||
import json
|
||||
import random
|
||||
import commands as cmd
|
||||
import utils
|
||||
from memory import get_memory
|
||||
import data
|
||||
import chat
|
||||
|
@ -8,17 +9,24 @@ from colorama import Fore, Style
|
|||
from spinner import Spinner
|
||||
import time
|
||||
import speak
|
||||
from enum import Enum, auto
|
||||
import sys
|
||||
from config import Config
|
||||
from json_parser import fix_and_parse_json
|
||||
from ai_config import AIConfig
|
||||
import traceback
|
||||
import yaml
|
||||
import argparse
|
||||
import logging
|
||||
|
||||
cfg = Config()
|
||||
|
||||
def configure_logging():
|
||||
logging.basicConfig(filename='log.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')
|
||||
|
||||
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:
|
||||
|
@ -29,7 +37,6 @@ def check_openai_api_key():
|
|||
print("You can get your key from https://beta.openai.com/account/api-keys")
|
||||
exit(1)
|
||||
|
||||
|
||||
def print_to_console(
|
||||
title,
|
||||
title_color,
|
||||
|
@ -39,10 +46,12 @@ def print_to_console(
|
|||
max_typing_speed=0.01):
|
||||
"""Prints text to the console with a typing effect"""
|
||||
global cfg
|
||||
global logger
|
||||
if speak_text and cfg.speak_mode:
|
||||
speak.say_text(f"{title}. {content}")
|
||||
print(title_color + title + " " + Style.RESET_ALL, end="")
|
||||
if content:
|
||||
logger.info(title + ': ' + content)
|
||||
if isinstance(content, list):
|
||||
content = " ".join(content)
|
||||
words = content.split()
|
||||
|
@ -133,12 +142,12 @@ def load_variables(config_file="config.yaml"):
|
|||
|
||||
# Prompt the user for input if config file is missing or empty values
|
||||
if not ai_name:
|
||||
ai_name = input("Name your AI: ")
|
||||
ai_name = utils.clean_input("Name your AI: ")
|
||||
if ai_name == "":
|
||||
ai_name = "Entrepreneur-GPT"
|
||||
|
||||
if not ai_role:
|
||||
ai_role = input(f"{ai_name} is: ")
|
||||
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."
|
||||
|
||||
|
@ -148,7 +157,7 @@ def load_variables(config_file="config.yaml"):
|
|||
print("Enter nothing to load defaults, enter nothing when finished.")
|
||||
ai_goals = []
|
||||
for i in range(5):
|
||||
ai_goal = input(f"Goal {i+1}: ")
|
||||
ai_goal = utils.clean_input(f"Goal {i+1}: ")
|
||||
if ai_goal == "":
|
||||
break
|
||||
ai_goals.append(ai_goal)
|
||||
|
@ -161,7 +170,7 @@ def load_variables(config_file="config.yaml"):
|
|||
documents = yaml.dump(config, file)
|
||||
|
||||
prompt = data.load_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."""
|
||||
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."""
|
||||
|
||||
# Construct full prompt
|
||||
full_prompt = f"You are {ai_name}, {ai_role}\n{prompt_start}\n\nGOALS:\n\n"
|
||||
|
@ -181,7 +190,7 @@ def construct_prompt():
|
|||
Fore.GREEN,
|
||||
f"Would you like me to return to being {config.ai_name}?",
|
||||
speak_text=True)
|
||||
should_continue = input(f"""Continue with the last settings?
|
||||
should_continue = utils.clean_input(f"""Continue with the last settings?
|
||||
Name: {config.ai_name}
|
||||
Role: {config.ai_role}
|
||||
Goals: {config.ai_goals}
|
||||
|
@ -216,7 +225,7 @@ def prompt_user():
|
|||
"Name your AI: ",
|
||||
Fore.GREEN,
|
||||
"For example, 'Entrepreneur-GPT'")
|
||||
ai_name = input("AI Name: ")
|
||||
ai_name = utils.clean_input("AI Name: ")
|
||||
if ai_name == "":
|
||||
ai_name = "Entrepreneur-GPT"
|
||||
|
||||
|
@ -231,7 +240,7 @@ def prompt_user():
|
|||
"Describe your AI's role: ",
|
||||
Fore.GREEN,
|
||||
"For example, 'an AI designed to autonomously develop and run businesses with the sole goal of increasing your net worth.'")
|
||||
ai_role = input(f"{ai_name} is: ")
|
||||
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."
|
||||
|
||||
|
@ -243,7 +252,7 @@ def prompt_user():
|
|||
print("Enter nothing to load defaults, enter nothing when finished.", flush=True)
|
||||
ai_goals = []
|
||||
for i in range(5):
|
||||
ai_goal = input(f"{Fore.LIGHTBLUE_EX}Goal{Style.RESET_ALL} {i+1}: ")
|
||||
ai_goal = utils.clean_input(f"{Fore.LIGHTBLUE_EX}Goal{Style.RESET_ALL} {i+1}: ")
|
||||
if ai_goal == "":
|
||||
break
|
||||
ai_goals.append(ai_goal)
|
||||
|
@ -279,22 +288,16 @@ def parse_arguments():
|
|||
print_to_console("Speak Mode: ", Fore.GREEN, "ENABLED")
|
||||
cfg.set_speak_mode(True)
|
||||
|
||||
if args.debug:
|
||||
print_to_console("Debug Mode: ", Fore.GREEN, "ENABLED")
|
||||
cfg.set_debug_mode(True)
|
||||
|
||||
if args.gpt3only:
|
||||
print_to_console("GPT3.5 Only Mode: ", Fore.GREEN, "ENABLED")
|
||||
cfg.set_smart_llm_model(cfg.fast_llm_model)
|
||||
|
||||
if args.debug:
|
||||
print_to_console("Debug Mode: ", Fore.GREEN, "ENABLED")
|
||||
cfg.set_debug_mode(True)
|
||||
|
||||
|
||||
# TODO: fill in llm values here
|
||||
check_openai_api_key()
|
||||
cfg = Config()
|
||||
logger = configure_logging()
|
||||
parse_arguments()
|
||||
ai_name = ""
|
||||
prompt = construct_prompt()
|
||||
|
@ -344,7 +347,7 @@ while True:
|
|||
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 = input(Fore.MAGENTA + "Input:" + Style.RESET_ALL)
|
||||
console_input = utils.clean_input(Fore.MAGENTA + "Input:" + Style.RESET_ALL)
|
||||
if console_input.lower() == "y":
|
||||
user_input = "GENERATE NEXT COMMAND JSON"
|
||||
break
|
||||
|
@ -405,4 +408,3 @@ while True:
|
|||
chat.create_chat_message(
|
||||
"system", "Unable to execute command"))
|
||||
print_to_console("SYSTEM: ", Fore.YELLOW, "Unable to execute command")
|
||||
|
||||
|
|
|
@ -4,6 +4,8 @@ import requests
|
|||
from config import Config
|
||||
cfg = Config()
|
||||
import gtts
|
||||
import threading
|
||||
from threading import Lock, Semaphore
|
||||
|
||||
|
||||
# TODO: Nicer names for these ids
|
||||
|
@ -14,6 +16,9 @@ tts_headers = {
|
|||
"xi-api-key": cfg.elevenlabs_api_key
|
||||
}
|
||||
|
||||
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(
|
||||
|
@ -23,10 +28,11 @@ def eleven_labs_speech(text, voice_index=0):
|
|||
tts_url, headers=tts_headers, json=formatted_message)
|
||||
|
||||
if response.status_code == 200:
|
||||
with open("speech.mpeg", "wb") as f:
|
||||
f.write(response.content)
|
||||
playsound("speech.mpeg")
|
||||
os.remove("speech.mpeg")
|
||||
with mutex_lock:
|
||||
with open("speech.mpeg", "wb") as f:
|
||||
f.write(response.content)
|
||||
playsound("speech.mpeg", True)
|
||||
os.remove("speech.mpeg")
|
||||
return True
|
||||
else:
|
||||
print("Request failed with status code:", response.status_code)
|
||||
|
@ -35,15 +41,29 @@ def eleven_labs_speech(text, voice_index=0):
|
|||
|
||||
def gtts_speech(text):
|
||||
tts = gtts.gTTS(text)
|
||||
tts.save("speech.mp3")
|
||||
playsound("speech.mp3")
|
||||
os.remove("speech.mp3")
|
||||
with mutex_lock:
|
||||
tts.save("speech.mp3")
|
||||
playsound("speech.mp3", True)
|
||||
os.remove("speech.mp3")
|
||||
|
||||
def macos_tts_speech(text):
|
||||
os.system(f'say "{text}"')
|
||||
|
||||
def say_text(text, voice_index=0):
|
||||
if not cfg.elevenlabs_api_key:
|
||||
gtts_speech(text)
|
||||
else:
|
||||
success = eleven_labs_speech(text, voice_index)
|
||||
if not success:
|
||||
gtts_speech(text)
|
||||
|
||||
def speak():
|
||||
if not cfg.elevenlabs_api_key:
|
||||
if cfg.use_mac_os_tts == 'True':
|
||||
macos_tts_speech(text)
|
||||
else:
|
||||
gtts_speech(text)
|
||||
else:
|
||||
success = eleven_labs_speech(text, voice_index)
|
||||
if not success:
|
||||
gtts_speech(text)
|
||||
|
||||
queue_semaphore.release()
|
||||
|
||||
queue_semaphore.acquire(True)
|
||||
thread = threading.Thread(target=speak)
|
||||
thread.start()
|
||||
|
|
|
@ -0,0 +1,8 @@
|
|||
def clean_input(prompt: str=''):
|
||||
try:
|
||||
return input(prompt)
|
||||
except KeyboardInterrupt:
|
||||
print("You interrupted Auto-GPT")
|
||||
print("Quitting...")
|
||||
exit(0)
|
||||
|
|
@ -37,7 +37,7 @@ Additional aspects:
|
|||
|
||||
class TestScrapeText:
|
||||
|
||||
# Tests that scrape_text() returns the expected text when given a valid URL.
|
||||
# Tests that scrape_text() returns the expected text when given a valid URL.
|
||||
def test_scrape_text_with_valid_url(self, mocker):
|
||||
# Mock the requests.get() method to return a response with expected text
|
||||
expected_text = "This is some sample text"
|
||||
|
@ -50,7 +50,7 @@ class TestScrapeText:
|
|||
url = "http://www.example.com"
|
||||
assert scrape_text(url) == expected_text
|
||||
|
||||
# Tests that the function returns an error message when an invalid or unreachable url is provided.
|
||||
# Tests that the function returns an error message when an invalid or unreachable url is provided.
|
||||
def test_invalid_url(self, mocker):
|
||||
# Mock the requests.get() method to raise an exception
|
||||
mocker.patch("requests.get", side_effect=requests.exceptions.RequestException)
|
||||
|
@ -60,7 +60,7 @@ class TestScrapeText:
|
|||
error_message = scrape_text(url)
|
||||
assert "Error:" in error_message
|
||||
|
||||
# Tests that the function returns an empty string when the html page contains no text to be scraped.
|
||||
# Tests that the function returns an empty string when the html page contains no text to be scraped.
|
||||
def test_no_text(self, mocker):
|
||||
# Mock the requests.get() method to return a response with no text
|
||||
mock_response = mocker.Mock()
|
||||
|
@ -72,7 +72,7 @@ class TestScrapeText:
|
|||
url = "http://www.example.com"
|
||||
assert scrape_text(url) == ""
|
||||
|
||||
# Tests that the function returns an error message when the response status code is an http error (>=400).
|
||||
# Tests that the function returns an error message when the response status code is an http error (>=400).
|
||||
def test_http_error(self, mocker):
|
||||
# Mock the requests.get() method to return a response with a 404 status code
|
||||
mocker.patch('requests.get', return_value=mocker.Mock(status_code=404))
|
||||
|
@ -83,7 +83,7 @@ class TestScrapeText:
|
|||
# Check that the function returns an error message
|
||||
assert result == "Error: HTTP 404 error"
|
||||
|
||||
# Tests that scrape_text() properly handles HTML tags.
|
||||
# Tests that scrape_text() properly handles HTML tags.
|
||||
def test_scrape_text_with_html_tags(self, mocker):
|
||||
# Create a mock response object with HTML containing tags
|
||||
html = "<html><body><p>This is <b>bold</b> text.</p></body></html>"
|
||||
|
@ -96,4 +96,4 @@ class TestScrapeText:
|
|||
result = scrape_text("https://www.example.com")
|
||||
|
||||
# Check that the function properly handles HTML tags
|
||||
assert result == "This is bold text."
|
||||
assert result == "This is bold text."
|
||||
|
|
Loading…
Reference in New Issue