From da7c4ecad9b32d1c7f73b6a471a4004365ef566b Mon Sep 17 00:00:00 2001 From: Code7G <111247923+Code7G@users.noreply.github.com> Date: Thu, 23 Nov 2023 19:37:03 +0100 Subject: [PATCH] Major changes to the code and documentation Updated: (DAIA.py, run.py, think.py, OS_controll dir, utils dir, README.md, Design dir) Added: (setup.py, GPT4V, OS_controller.py, Evaluator dir) Removed: (openaicaller.py, OS_controll dir files, Actions dir) And added much more documentation. --- DAIA.py | 13 +- .../Actions/DVAI.py | 1 - .../Actions/action_runner.py | 1 - .../Actions/action_viewer.py | 1 - .../OS_control/DAIA_client_control.py | 27 - .../OS_control/Server_files/python-installer | 7 - .../OS_control/Server_files/python_install.sh | 53 - .../OS_control/Server_files/server.py | 36 - .../Server_files/server_activate.sh | 3 - .../OS_control/Server_files/server_setup.md | 5 - .../Thinker/thinking.py | 458 --------- DAIA_(GPT-4-Turbo-with-Vision)/run.py | 300 ------ DAIA_GPT4V/DVAI/GPT_4_with_Vision.py | 74 ++ .../Memory/memory.py | 0 DAIA_GPT4V/OS_control/os_controller.py | 39 + .../Optimizer/optimization.py | 0 DAIA_GPT4V/Thinker/thinking.py | 593 ++++++++++++ DAIA_GPT4V/run.py | 170 ++++ Design/.$DAIA (GPT Vision).drawio.bkp | 800 +++++++++++++++ Design/DAIA (GPT Vision) progress.drawio | 914 ++++++++++++++++++ Design/DAIA (GPT Vision) progress.png | Bin 0 -> 498336 bytes Design/DAIA (GPT Vision).drawio | 16 +- Design/DAIA.drawio | 376 +++---- README.md | 49 +- requirements.txt | 3 +- utils/openaicaller.py | 219 ----- utils/openaicaller.py.md | 137 --- utils/setup.py | 10 + utils/tokens.py | 39 - 29 files changed, 2837 insertions(+), 1507 deletions(-) delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/Actions/DVAI.py delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_runner.py delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_viewer.py delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/OS_control/DAIA_client_control.py delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python-installer delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python_install.sh delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server.py delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_activate.sh delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_setup.md delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/Thinker/thinking.py delete mode 100644 DAIA_(GPT-4-Turbo-with-Vision)/run.py create mode 100644 DAIA_GPT4V/DVAI/GPT_4_with_Vision.py rename {DAIA_(GPT-4-Turbo-with-Vision) => DAIA_GPT4V}/Memory/memory.py (100%) create mode 100644 DAIA_GPT4V/OS_control/os_controller.py rename {DAIA_(GPT-4-Turbo-with-Vision) => DAIA_GPT4V}/Optimizer/optimization.py (100%) create mode 100644 DAIA_GPT4V/Thinker/thinking.py create mode 100644 DAIA_GPT4V/run.py create mode 100644 Design/.$DAIA (GPT Vision).drawio.bkp create mode 100644 Design/DAIA (GPT Vision) progress.drawio create mode 100644 Design/DAIA (GPT Vision) progress.png delete mode 100644 utils/openaicaller.py delete mode 100644 utils/openaicaller.py.md create mode 100644 utils/setup.py delete mode 100644 utils/tokens.py diff --git a/DAIA.py b/DAIA.py index 4de2f6b..0240ce0 100644 --- a/DAIA.py +++ b/DAIA.py @@ -1,9 +1,8 @@ -import asyncio -#from +from DAIA_GPT4V.run import run from config import openai_api_key -async def main(key: str = None) -> None: +def main(key: str = None) -> None: # Checking API Key if not key or len(key) <= 0 or key == "": input_api_key = "" @@ -21,7 +20,9 @@ async def main(key: str = None) -> None: # User Interaction try: option = int( - input("\nOptions\n[1] DAIA_GoalTimed\n[2] DAIA_Constant\n\nSelect Option: ") + input( + "\nOptions\n[1] DAIA_GPT-4-with-Vision\n[2] DAIA_Continues\n\nSelect Option: " + ) ) except ValueError: @@ -30,7 +31,7 @@ async def main(key: str = None) -> None: match option: case 1: - return await run(api_key=key) + return run(api_key=key) case 2: return print("Currently Unavaiable.") @@ -40,4 +41,4 @@ async def main(key: str = None) -> None: if __name__ == "__main__": - asyncio.run(main(openai_api_key)) + main(openai_api_key) diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/Actions/DVAI.py b/DAIA_(GPT-4-Turbo-with-Vision)/Actions/DVAI.py deleted file mode 100644 index 6451ea7..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/Actions/DVAI.py +++ /dev/null @@ -1 +0,0 @@ -# Digital Vision Artificial Intelligence diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_runner.py b/DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_runner.py deleted file mode 100644 index b5a3956..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_runner.py +++ /dev/null @@ -1 +0,0 @@ -# Functions for runing actions of the DAIA diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_viewer.py b/DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_viewer.py deleted file mode 100644 index 2c75e1e..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/Actions/action_viewer.py +++ /dev/null @@ -1 +0,0 @@ -# Functions for viewing the resoult of the runned functions diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/DAIA_client_control.py b/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/DAIA_client_control.py deleted file mode 100644 index 8aa79e6..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/DAIA_client_control.py +++ /dev/null @@ -1,27 +0,0 @@ -import socket - - -def send_instruction(host_ip, port, instruction): - HOST = host_ip # Server IP address - PORT = port # Port number - - # Create a socket object - client_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) - - # Connect to the server - client_socket.connect((HOST, PORT)) - - # Send instructions to the server - client_socket.sendall(instruction.encode()) - - # Receive feedback from the server - feedback = client_socket.recv(1024).decode() - - # Close the socket - client_socket.close() - - return feedback - - -feedback = send_instruction("IP address", "port as int", "the first test") -print(feedback) diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python-installer b/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python-installer deleted file mode 100644 index 99d83c0..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python-installer +++ /dev/null @@ -1,7 +0,0 @@ - -404 Not Found - -

404 Not Found

-
nginx
- - diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python_install.sh b/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python_install.sh deleted file mode 100644 index bd47357..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/python_install.sh +++ /dev/null @@ -1,53 +0,0 @@ -#!/bin/bash - -# Check the operating system -unameOut="$(uname -s)" -case "${unameOut}" in - Linux*) os="linux";; - Darwin*) os="mac";; - CYGWIN*|MINGW*|MSYS*) os="windows";; - *) os="unknown";; -esac - -# Determine the download URL based on the operating system -if [ "${os}" = "linux" ]; then - url="https://www.python.org/ftp/python/3.x.x/Python-3.x.x.tgz" # Replace 3.x.x with the desired version - -elif [ "${os}" = "mac" ]; then - url="https://www.python.org/ftp/python/3.x.x/python-3.x.x-macosx10.x.pkg" # Replace 3.x.x with the desired version - -elif [ "${os}" = "windows" ]; then - url="https://www.python.org/ftp/python/3.x.x/python-3.x.x.exe" # Replace 3.x.x with the desired version - -else - echo "Unsupported operating system." - exit 1 -fi - -# Download and install Python -echo "Downloading Python..." -curl -o python-installer.${ext} ${url} # Replace python-installer.${ext} with the desired output file name and extension - -echo "Installing Python..." - -if [ "${os}" = "linux" ]; then - tar -xzvf python-installer.${ext} # Extract the downloaded tarball - cd Python-3.x.x/ # Replace Python-3.x.x with the extracted directory name - ./configure --enable-optimizations - make -j8 - sudo make altinstall - -elif [ "${os}" = "mac" ]; then - sudo installer -pkg python-installer.${ext} -target / # Replace python-installer.${ext} with the downloaded package file name - -elif [ "${os}" = "windows" ]; then - python-installer.${ext} # Replace python-installer.${ext} with the downloaded installer file name - -else - echo "Unsupported operating system." - exit 1 -fi - -# Verify the installation -echo "Python installation completed." -python3 --version \ No newline at end of file diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server.py b/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server.py deleted file mode 100644 index b4fc3dc..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server.py +++ /dev/null @@ -1,36 +0,0 @@ -import socket - - -HOST = "0.0.0.0" # Client IP address -PORT = 1234 # Port number - -# Create a socket object -server_socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) - -# Bind the socket to a specific address and port -server_socket.bind((HOST, PORT)) - -# Listen for incoming connections -server_socket.listen(1) - -# Accept a connection from a client -client_socket, client_address = server_socket.accept() - -# Receive instructions from the client -instructions = client_socket.recv(1024).decode() - -# Example: Process instructions and perform actions -feedback = "" -if instructions == "do_action": - print("Do action (test)") -# ... add more instructions and corresponding feedback as needed - -# Take a screen_shot and save it as feedback -feedback = "screen-shot*" - -# Send feedback back to the client -client_socket.sendall(feedback.encode()) - -# Close the connection -client_socket.close() -server_socket.close() diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_activate.sh b/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_activate.sh deleted file mode 100644 index bf8a75c..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_activate.sh +++ /dev/null @@ -1,3 +0,0 @@ -#!/Server_files - -python3 server.py \ No newline at end of file diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_setup.md b/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_setup.md deleted file mode 100644 index e07f036..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/OS_control/Server_files/server_setup.md +++ /dev/null @@ -1,5 +0,0 @@ -# This will be needed for the DAIA client connection to function - -Please add the current directory `Server_filesΒ΄ to the machine that you want to be the server. -After that run the python_install.sh file to install python if python is not yet installed. -Then run the `server_activate.shΒ΄ file on the server machine. \ No newline at end of file diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/Thinker/thinking.py b/DAIA_(GPT-4-Turbo-with-Vision)/Thinker/thinking.py deleted file mode 100644 index 9164d9e..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/Thinker/thinking.py +++ /dev/null @@ -1,458 +0,0 @@ -from utils.openaicaller import caller, models_max_tokens -from DAIA_GoalTimed.Memory.memory import Memory -from utils.tokens import num_tokens_from_messages - - -class Think: - def __init__(self, key: str, goal: str, goal_id: int): - self.openai_api_key = key - self.goal = goal - self.goal_id = goal_id - - async def goal_completer(self, suggestions: str): - real_suggestions = self.get_suggestions(suggestions) - for suggestion in real_suggestions: - sub_suggestions = await self.suggestion_splitter(suggestion) - - # Process the first level of suggestions - # for suggestion in self.suggestions: - # explanation = self.suggestion_explainer(suggestion, ...) - # action = self.action(explanation, ...) - # - # # Continue processing sub-suggestions as long as the action is False - # while action == False: - # sub_suggestions = self.suggestion_splitter(explanation, ...) - # - # # Process each sub-suggestion - # for sub_suggestion in sub_suggestions: - # sub_explanation = self.suggestion_explainer(sub_suggestion, ...) - # sub_action = self.action(sub_explanation, ...) - # - # # Continue processing sub-sub-suggestions as long as the sub-action is False - # while sub_action == False: - # sub_sub_suggestions = self.suggestion_splitter(sub_explanation, ...) - # - # # Process each sub-sub-suggestion - # for sub_sub_suggestion in sub_sub_suggestions: - # sub_sub_explanation = self.suggestion_explainer(sub_sub_suggestion, ...) - # sub_sub_action = self.action(sub_sub_explanation) - # - # if sub_sub_action == False: - # # Continue processing sub-sub-suggestions - # continue - # else: - # # Do the action for sub-sub-suggestion - # pass - # - # # Check if there are more sub-sub-suggestions - # if not sub_sub_suggestions: - # sub_action = True # Exit the sub-action loop if there are no more sub-sub-suggestions - # - # # Do the action for sub-suggestion - # pass - # - # # Check if there are more sub-suggestions - # if not sub_suggestions: - # action = True # Exit the action loop if there are no more sub-suggestions - # - # print(f'Action {suggestion} done') - # pass - - # OR - - # for suggestion in self.suggestions: - # explanation = self.suggestion_explainer(suggestion, ...) - # action = self.action(explanation, ...) - # - # if action == False: - # sub_suggestions = self.suggestion_splitter(explanation, ...) - # - # for sub_suggestion in sub_suggestions: - # sub_explanation = self.suggestion_explainer(sub_suggestion, ...) - # sub_action = self.action(explanation, ...) - # - # if sub_action == False: - # sub_sub_suggestions = self.suggestion_splitter(sub_explanation, ...) - # - # for sub_sub_suggestion in sub_sub_suggestions: - # sub_sub_explanation = self.suggestion_explainer(sub_sub_suggestion, ...) - # sub_sub_action = self.action(sub_sub_explanation) - # - # if sub_sub_action == False: - # # Do the same.... - # - # else: - # pass - # # Do the action - # - # else: - # pass - # # Do the action - # - # else: - # pass - # # Do the action - - def action_compleation(): - pass - # Compleate actions - - async def action( - self, - suggestion: str, - os: str, - commands: str, - screen_data: str, - previous_data: str, - ): - str_commands = "" - for command in commands: - str_commands = str(command) + "\n" - - while True: - executable = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": f""" -Can you determine if the provided suggestion, along with the given commands and current screen data, is specific enough to be executed on the {os}? Please provide the first command with its expected outcome to complete the suggestion if it is possible. Consider the following information: - -Given commands: -{str_commands} - -Previous data: -{previous_data} - -Current screen information: -{screen_data} - -Suggestion: -{suggestion} - -If the suggestion is sufficiently specific and can be carried out on the {os} using the provided commands and current screen data, please type the first command along with its expected outcome, like this: -1. [command][perameter of command or none] (expected outcome) - -If the suggestion is not specific enough, please state "Not specific" -""", - } - ], - ) - - if executable == "Not specific" or executable == '"Not specific"': - return False - - else: - return executable - - async def suggestion_explainer(self, suggestion: str): - previous_info = await self.short_remember( - f""" -You have a goal you want to achieve. -You have already gotten some information on the steps to achieving your goal. -So, based on the previous steps and information you must ask someone a question that will give you the information to complete your current step to progress toward achieving your goal. - -your goal = {self.goal} -your previous steps and information = >>previous context missing<< -your current step = {suggestion} - -What would that question be? (respond only with the question) -""" - ) - - prompt = f""" -You have a goal you want to achieve. -You have already gotten some information on the steps to achieving your goal. -So, based on the previous steps and information you must ask someone a question that will give you the information to complete your current step to progress toward achieving your goal. - -your goal = {self.goal} -your previous steps and information = {previous_info} -your current step = {suggestion} - -What would that question be? (respond only with the question) -""" - - # print(f'Previous info for {suggestion}: {previous_info}\n \n') - - question = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": prompt, - } - ], - ) - - question = question["choices"][0]["message"]["content"] - - await self.save_action(action1=prompt, action2=question, category=0) - - # print(f'Prompt for {suggestion}: {previous_info}\n \n') - - suggestion_suggestions = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": f""" -{question} -""", - } - ], - ) - - await self.save_action( - action1=question, - action2=suggestion_suggestions["choices"][0]["message"]["content"], - category=0, - ) - - # print(f'Explanation for {suggestion}: {suggestion_suggestions}\n \n') - - return suggestion_suggestions["choices"][0]["message"]["content"] - - async def suggestion_splitter(self, suggestion: str): - explanation = await self.suggestion_explainer(suggestion) - previous_data = await self.short_remember( - f""" -What are the suggestions in the response based on the given response and previous data? - -Previous data: >>previous data missing<< -Response: {explanation} - -Please provide the suggestions sequentially, without any additional text. For instance: -1. Suggestion -2. Suggestion -Additional suggestions mentioned in the response... - -If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. - -If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: -1. Suggestion -2. Suggestion -Additional suggestions based on the provided response and previous data... -""" - ) - - prompt = f""" -What are the suggestions in the response based on the given response and previous data? - -Previous data: {previous_data} -Response: {explanation} - -Please provide the suggestions sequentially, without any additional text. For instance: -1. Suggestion -2. Suggestion -Additional suggestions mentioned in the response... - -If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. - -If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: -1. Suggestion -2. Suggestion -Additional suggestions based on the provided response and previous data... -""" - - while True: - sub_suggestions = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": prompt, - } - ], - ) - - sub_suggestions = sub_suggestions["choices"][0]["message"]["content"] - - await self.save_action(action1=prompt, action2=sub_suggestions, category=0) - - if sub_suggestions[0:5].lower() in "reject": - print( - f""" -Sub-suggestion {sub_suggestions}\n \n -""" - ) - - else: - print( - f""" -General '{suggestion}' steps: -{sub_suggestions}\n \n -""" - ) - - return sub_suggestions - - async def gpt_memory_capacity(self, data, gpt_role, gpt): - max_tokens = models_max_tokens[gpt] - message = {"role": gpt_role, "content": data} - message_list = [message] - tokens = await num_tokens_from_messages(message_list) - - if tokens < max_tokens: - return True - - else: - return False - - async def save_goal(self): - goal_summary = await self.generate_title(self.goal, "goal") - - memory = Memory() - new_goal = memory.create_goal_object(goal_summary) - memory.save_objects_in_db([new_goal]) - - return new_goal.goal_id - - async def save_goal_in_goal(self): - memory = Memory() - - goal_action = memory.create_action_object( - goal_id=self.goal_id, - title="Final Goal", - category="Goal", - full_data=self.goal, - important_data=f"The Final Goal is: {self.goal}", - ) - memory.save_objects_in_db([goal_action]) - - async def save_action(self, action1: str, action2: str, category: int): - """ - Category: - "question=>response" = int 0 - "response=>action" = int 1 - "action=>result" = int 2 - "result=>action" = int 3 - """ - - categories = [ - "question=>response", - "response=>action", - "action=>result", - "result=>action", - ] - - first = categories[category].split("=")[0] - second = categories[category].split(">")[-1] - - memory = Memory() - - data = f'[1. {first}]: "{action1}",\n[2. {second}]: "{action2}"' - title = await self.generate_title(data, f'"{first} with its {second}"') - previous_important_data = await self.short_remember( - f""" -Given the following context: ->>previous context missing<< - -And the input data: -"{data}" - -Please use the provided context to extract and present the most important data from the input. -""", - ) - - important_data = await self.get_important_data(data, previous_important_data) - - new_action = memory.create_action_object( - self.goal_id, title, categories[category], data, important_data - ) - memory.save_objects_in_db([new_action]) - - async def short_remember(self, need: str): - memory = Memory() - - previous_important_data = "" - for action in memory.get_ordered_actions_of_goal(self.goal_id, 100): - previous_important_data = previous_important_data + "".join( - f'[{getattr(action, "action_id")}. Action: (Title of action: "{getattr(action, "title")}", Important data of action: "{getattr(action, "important_data")}")]\n' - ) - - if len(previous_important_data) <= 0: - return "Nothing has hppened yet." - - previous_data = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": f""" -Given the following context: -"{previous_important_data}" - -And the input data: -"{need}" - -Please input the necessary, relevant, and concise context from the following context to complete the input. Your input should address the gaps in the provided input data, ensuring accurate responses without any future errors or issues. - -Please avoid addressing the prompt directly. Only provide the crucial context. Keep your response minimal and to the point. -""", - } - ], - ) - - # print( - # f'Previous_info: {previous_data["choices"][0]["message"]["content"]}\n \n') - - return previous_data["choices"][0]["message"]["content"] - - async def get_important_data(self, data: str, previous_data: str): - important_data = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": f""" -Given the following context: -"{previous_data}" - -And the input data: -"{data}" - -Please use the provided context to extract and present the most important data from the input. -""", - } - ], - ) - - return important_data["choices"][0]["message"]["content"] - - async def generate_title(self, data: str, item_category: str): - title = await caller.generate_response( - api_key=self.openai_api_key, - model="gpt-3.5-turbo", - messages=[ - { - "role": "user", - "content": f""" -Provide a concise title (<75 chars) describing the {item_category}. - -{item_category} = "{data}" -""", - } - ], - ) - - return title["choices"][0]["message"]["content"] - - def get_suggestions(self, suggestions: str): - suggestions_ = suggestions - for n in range(0, 40): - number = 40 - n - suggestions_ = suggestions_.replace(f"{number}.", "%_%") - - suggestions_ = suggestions_.replace("\n", "") - real_suggestions = suggestions_.split("%_%") - - if real_suggestions.count("") > 0: - real_suggestions.remove("") - - return real_suggestions diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/run.py b/DAIA_(GPT-4-Turbo-with-Vision)/run.py deleted file mode 100644 index cce71f9..0000000 --- a/DAIA_(GPT-4-Turbo-with-Vision)/run.py +++ /dev/null @@ -1,300 +0,0 @@ -import asyncio - -from pathlib import Path -from DAIA_GoalTimed.Thinker.thinking import Think -from utils.openaicaller import caller - - -async def run(api_key): - goal = input("Please enter your goal for the DAIA here: ") - - while len(goal) <= 0: - print("Goal is empty!") - goal = input("Please enter your goal for the DAIA here: ") - - think_ = Think(key=api_key, goal=goal, goal_id=-1) - goal_id = await think_.save_goal() - - think = Think(key=api_key, goal=goal, goal_id=goal_id) - await think.save_goal_in_goal() - - # personal = input(''' - # (Press ENTER to skip) - # Would you like to add some personal information to the DAIA? (this is optional, but could be helpful when dealing with goals involving payment and account info) - # (Y/N) ''') - # - # if personal.upper() == 'Y': - # crypto_wallet_addres = input( - # 'Enter your crypto wallet address here: ') - # # Credit card option - # # ... - # print('When the DAIA thinks it needs to deposit anything into your accounts, it will first ask you before doing so') - - while True: - prompt = f""" -You have a goal you want to achieve. -As your first step you want to know how to achieve your goal. So you must ask someone a question that will give you that information. - -your goal = {goal} - -What would that question be? (respond only with the question) -""" - - question = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": prompt}], - ) - - question = question["choices"][0]["message"]["content"] - - print(f"Goal question: {question}") - q_agree = input("Do you agree with the question for goal completion? (Y/N)") - - if q_agree.upper() == "N": - print("Retrying...") - - else: - break - - goal_help = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": question}], - ) - - goal_help = goal_help["choices"][0]["message"]["content"] - - await think.save_action(action1=question, action2=goal_help, category=0) - previous_data = await think.short_remember( - f""" -What are the suggestions in the response, based on the given response and previous data? - -Previous data: >> previous context missing << -Response: {goal_help} - -Please provide the suggestions sequentially, without any additional text. For instance: -1. Suggestion -2. Suggestion -Additional suggestions mentioned in the response... - -If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. - -If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: -1. Suggestion -2. Suggestion -Additional suggestions based on the provided response and previous data... -""" - ) - - prompt = f""" -What are the suggestions in the response, based on the given response and previous data? - -Previous data: {previous_data} -Response: {goal_help} - -Please provide the suggestions sequentially, without any additional text. For instance: -1. Suggestion -2. Suggestion -Additional suggestions mentioned in the response... - -If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. - -If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: -1. Suggestion -2. Suggestion -Additional suggestions based on the provided response and previous data... -""" - - suggestions = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": prompt}], - ) - - suggestions = suggestions["choices"][0]["message"]["content"] - - await think.save_action(action1=prompt, action2=suggestions, category=0) - - if suggestions[0:5].lower() in "reject": - print( - f""" -Goal {suggestions} -""" - ) - - else: - print("Goal accepted!") - print( - f""" -General goal steps: -{suggestions} -""" - ) - - second_time = False - while True: - print( - "(Press ENTER to skip) WARNING: if you skip, the suggestions will be accepted. This is the LAST MANUAL step, everything from here on is automated" - ) - agree = input( - "Do you agree with the current suggestions/processes for your goal? (Y/N)" - ) - - if second_time: - if agree.upper() == "N": - await think.save_action( - action1=f'"Sorry, but I dissagree with the current suggestions because: \n{explanation}\nCan you update the suggestions?"', - action2=f'"Yes, here are the new suggestions: \n{suggestions}"', - category=0, - ) - - explanation = input("Why do you not agree? ") - - prompt = f""" -Please try to correct your suggestions. - -Here is why I don't agree with them: -{explanation} -""" - - suggestion_correction = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[ - {"role": "user", "content": suggestion_correction}, - {"role": "user", "content": prompt}, - ], - ) - - suggestion_correction = suggestion_correction["choices"][0][ - "message" - ]["content"] - - prompt = f""" -Please provide the suggestions mentioned in the following response: - -Response: {suggestion_correction} - -List only the suggestions in a sequential manner, without any additional text. For example: -1. Suggestion -2. Suggestion -Additional suggestions mentioned in the response... - -If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. - -If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response. For example: -1. Suggestion -2. Suggestion -Additional suggestions based on the provided response... -""" - - suggestions = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": prompt}], - ) - - suggestions = suggestions["choices"][0]["message"]["content"] - - if suggestions[0:5].lower() in "reject": - print( - f""" -Goal {suggestions} -""" - ) - - else: - print("Goal accepted!") - print( - f""" -General goal steps: -{suggestions} -""" - ) - - else: - await think.save_action( - action1=f'"Sorry, but I dissagree with the current suggestions because: \n{explanation}\nCan you update the suggestions?"', - action2=f'"Yes, here are the new suggestions: \n{suggestions}"', - category=0, - ) - - print("/) Ok then, let's go!") - break - - else: - if agree.upper() == "N": - second_time = True - explanation = input("Why do you not agree? ") - - prompt = f""" -Please try to correct your suggestions. - -Here is why I don't agree with them: -{explanation} -""" - - suggestion_correction = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[ - {"role": "user", "content": suggestions}, - {"role": "user", "content": prompt}, - ], - ) - - suggestion_correction = suggestion_correction["choices"][0][ - "message" - ]["content"] - - prompt = f""" -Please provide the suggestions mentioned in the following response: - -Response: {suggestion_correction} - -List only the suggestions in a sequential manner, without any additional text. For example: -1. Suggestion -2. Suggestion -Additional suggestions mentioned in the response... - -If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. - -If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response. For example: -1. Suggestion -2. Suggestion -Additional suggestions based on the provided response... -""" - - suggestions = await caller.generate_response( - api_key=api_key, - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": prompt}], - ) - - suggestions = suggestions["choices"][0]["message"]["content"] - - if suggestions[0:5].lower() in "reject": - print( - f""" -Goal {suggestions} -""" - ) - - else: - print("Goal accepted!") - print( - f""" -General goal steps: -{suggestions} -""" - ) - - else: - print("/) Ok then, let's go!") - break - - await think.goal_completer(suggestions) - - -# think.goal_completer(suggestions) diff --git a/DAIA_GPT4V/DVAI/GPT_4_with_Vision.py b/DAIA_GPT4V/DVAI/GPT_4_with_Vision.py new file mode 100644 index 0000000..9f08020 --- /dev/null +++ b/DAIA_GPT4V/DVAI/GPT_4_with_Vision.py @@ -0,0 +1,74 @@ +from openai import OpenAI +import base64 +import requests + + +class DVAI: + """ + Digital Vision Artificial Intelligence + """ + + def __init__(self, key: str): + self.api_key = key + + self.client = OpenAI( + api_key=key, + ) + + def gpt_with_vision_by_url(self, image_url, context: str): + response = self.client.chat.completions.create( + model="gpt-4-vision-preview", + messages=[ + { + "role": "user", + "content": [ + {"type": "text", "text": context}, + { + "type": "image_url", + "image_url": { + "url": image_url, + }, + }, + ], + } + ], + ) + + return response.choices[0].message.content + + def gpt_with_vision_by_base64(self, image_path: str, context: str): + base64_image = self.encode_image(image_path) + + headers = { + "Content-Type": "application/json", + "Authorization": f"Bearer {self.api_key}", + } + + payload = { + "model": "gpt-4-vision-preview", + "messages": [ + { + "role": "user", + "content": [ + {"type": "text", "text": context}, + { + "type": "image_url", + "image_url": { + "url": f"data:image/jpeg;base64,{base64_image}" + }, + }, + ], + } + ], + "max_tokens": 1000, + } + + response = requests.post( + "https://api.openai.com/v1/chat/completions", headers=headers, json=payload + ) + + return response.json()["choices"][0]["message"]["content"] + + def encode_image(self, image_path): + with open(image_path, "rb") as image_file: + return base64.b64encode(image_file.read()).decode("utf-8") diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/Memory/memory.py b/DAIA_GPT4V/Memory/memory.py similarity index 100% rename from DAIA_(GPT-4-Turbo-with-Vision)/Memory/memory.py rename to DAIA_GPT4V/Memory/memory.py diff --git a/DAIA_GPT4V/OS_control/os_controller.py b/DAIA_GPT4V/OS_control/os_controller.py new file mode 100644 index 0000000..dbf2cde --- /dev/null +++ b/DAIA_GPT4V/OS_control/os_controller.py @@ -0,0 +1,39 @@ +import pyautogui +import platform + + +class OSController: + """ + Controll the OS using pyautogui, and get its data with the platform library + """ + + def __init__(self): + self.x = pyautogui.position()[0] + self.y = pyautogui.position()[1] + + def click(self, x, y): + pyautogui.click(x, y) + + def move_cursor_to(self, x, y): + pyautogui.moveTo(x, y, duration=0.2) + + def keyboard(self, string): + pyautogui.typewrite(string) + + def scroll(self, direction, amount): + if direction == "up": + pyautogui.scroll(-amount) + elif direction == "down": + pyautogui.scroll(amount) + + def screenshot(self, path): + screenshot = pyautogui.screenshot() + screenshot.save(path) + + def get_system_info(self): + return { + "OS": platform.system(), + "Version": platform.release(), + "Architecture": platform.processor(), + "Hostname": platform.node(), + } diff --git a/DAIA_(GPT-4-Turbo-with-Vision)/Optimizer/optimization.py b/DAIA_GPT4V/Optimizer/optimization.py similarity index 100% rename from DAIA_(GPT-4-Turbo-with-Vision)/Optimizer/optimization.py rename to DAIA_GPT4V/Optimizer/optimization.py diff --git a/DAIA_GPT4V/Thinker/thinking.py b/DAIA_GPT4V/Thinker/thinking.py new file mode 100644 index 0000000..86adfd6 --- /dev/null +++ b/DAIA_GPT4V/Thinker/thinking.py @@ -0,0 +1,593 @@ +from DAIA_GPT4V.Memory.memory import Memory +from DAIA_GPT4V.OS_control.os_controller import OSController +from DAIA_GPT4V.DVAI.GPT_4_with_Vision import DVAI +from utils.setup import setup +from openai import OpenAI +from pathlib import Path +from random import randint + + +class Think: + """ + The main class for operations involving the GPT for the DAIA + """ + + def __init__(self, key: str, goal: str, goal_id: int): + self.openai_api_key = key + self.goal = goal + self.goal_id = goal_id + + self.client = OpenAI( + api_key=key, + ) + + def goal_completer(self, suggestions: str): + setup() + + # Setup system info and commands + os_controller = OSController() + system_info = os_controller.get_system_info() + commands = [ + "click[x,y possition]", + "move_cursor_to[x,y possition]", + "keyboard[string]", + ] + + dvai = DVAI(self.openai_api_key) + + first_suggestions = self.get_suggestions(suggestions) + for suggestion in first_suggestions: + # Take a screenshot and save it + screenshot_savepath = Path( + f'DAIA/Screenshots/screenshot{"".join([str(e + randint(1, 9)) for e in range(10)])}.png' + ) + os_controller.screenshot(screenshot_savepath) + + # Get the current screen information with the screenshot (the prompt needs improvements) + prompt = f""" +Please state what is in the provided screenshot of the {str(system_info.get('OS'))} OS that relates to {suggestion} of the goal {self.goal}. +""" + screenshot_description = dvai.gpt_with_vision_by_base64( + screenshot_savepath, prompt + ) + print(f"Screenshot description: {screenshot_description}") + + executable_commands = self.action( + suggestion, + str(system_info.get("OS")), + commands, + screenshot_description, + suggestion, + ) + print(executable_commands) + break + + def action_compleation(): + pass + # Compleate a action + + def action( + self, + suggestion: str, + os: str, + commands: list, + screen_data: str, + previous_data: str, + ): + """ + Check if a suggestion is specific enough to be done with the provided commands on the OS + + (Current state: The prompt needs improvements so that the GPT can know more about the current screen data regarding the suggestion instead of just general data) + """ + + # Assemble commands as a str + str_commands = "" + for command in commands: + str_commands += str(command) + "\n" + + # The main prompt + executable = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": f""" +Can you determine if the provided suggestion, along with the given commands and current screen data, is specific enough to be executed on the {os} OS? Please provide the commands with thair expected outcome to complete the suggestion if it is possible. Consider the following information: + +Given commands: +{str_commands} + +Previous data: +{previous_data} + +Current screen information: +{screen_data} + +Suggestion: +{suggestion} + +If the suggestion is sufficiently specific and can be carried out on the {os} OS using the provided commands, please type the commands along with thair expected outcomes, like this: +1. command[perameter of command or none] (expected outcome) +2. command[perameter of command or none] (expected outcome) +3. command[perameter of command or none] (expected outcome) +Additional commands with outcomes... + +If the suggestion is not specific enough, please state "Not specific" +""", + } + ], + ) + executable = executable.choices[0].message.content + + # Check if the response returns commands or just 'Not specific' + if executable == "Not specific" or executable == '"Not specific"': + return False + + else: + return executable + + def suggestion_explainer(self, suggestion: str): + """ + Explain a suggestion. + + Suggestion (Create a account) -> explanation (To create a account do...) + """ + + # Remmember and the previous data for the prompt with this prompt + previous_info = self.short_remember( + f""" +You have a goal you want to achieve. +You have already gotten some information on the steps to achieving your goal. +So, based on the previous steps and information you must ask someone a question that will give you the information to complete your current step to progress toward achieving your goal. + +your goal = {self.goal} +your previous steps and information = >>previous context missing<< +your current step = {suggestion} + +What would that question be? (respond only with the question) +""" + ) + + # Imput the previous data into the prompt + prompt = f""" +You have a goal you want to achieve. +You have already gotten some information on the steps to achieving your goal. +So, based on the previous steps and information you must ask someone a question that will give you the information to complete your current step to progress toward achieving your goal. + +your goal = {self.goal} +your previous steps and information = {previous_info} +your current step = {suggestion} + +What would that question be? (respond only with the question) +""" + # Make GPT generate a question about the suggestion + question = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": prompt, + } + ], + ) + question = question.choices[0].message.content + self.save_action(action1=prompt, action2=question, category=0) + + # Make GPT answer its question to generate a explanation + suggestion_suggestions = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": f""" +{question} +""", + } + ], + ) + self.save_action( + action1=question, + action2=suggestion_suggestions.choices[0].message.content, + category=0, + ) + + return suggestion_suggestions.choices[0].message.content + + def suggestion_splitter(self, suggestion: str): + """ + Split a suggestion (or step) into its sub-suggestions (or steps). + + Suggestion (Create a account) -> Suggestions (['Visit the website..', 'Create account...', 'Access services..']) + """ + + # Explain the suggestion + explanation = self.suggestion_explainer(suggestion) + + # Remmember the important previous data for the prompt + previous_data = self.short_remember( + f""" +What are the suggestions in the response based on the given response and previous data? + +Previous data: >>previous data missing<< +Response: {explanation} + +Please provide the suggestions sequentially, without any additional text. For instance: +1. Suggestion +2. Suggestion +Additional suggestions mentioned in the response... + +If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. + +If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: +1. Suggestion +2. Suggestion +Additional suggestions based on the provided response and previous data... +""" + ) + + # Get the extracted previous data into the prompt + prompt = f""" +What are the suggestions in the response based on the given response and previous data? + +Previous data: {previous_data} +Response: {explanation} + +Please provide the suggestions sequentially, without any additional text. For instance: +1. Suggestion +2. Suggestion +Additional suggestions mentioned in the response... + +If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. + +If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: +1. Suggestion +2. Suggestion +Additional suggestions based on the provided response and previous data... +""" + # Use the prompt to extract the suggestions from the response + sub_suggestions = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": prompt, + } + ], + ) + sub_suggestions = sub_suggestions.choices[0].message.content + self.save_action(action1=prompt, action2=sub_suggestions, category=0) + + # Check if the response gives any suggestions and if it is a answer + if sub_suggestions[0:5].lower() in "reject": + print( + f""" +Sub-suggestion {sub_suggestions}\n \n +""" + ) + return "Rejected" + + else: + print( + f""" +General '{suggestion}' steps: +{sub_suggestions}\n \n +""" + ) + return sub_suggestions + + def explanation_to_suggestions(self, explanation: str, prev_data: bool): + """ + Split a explanation into suggestions + + Explanation (To create a account do..) -> Suggestions (['Visit the website..', 'Create account...', 'Access services..']) + """ + + if prev_data: + # Remmember the important previous data for the prompt + previous_data = self.short_remember( + f""" +What are the suggestions in the response based on the given response and previous data? + +Previous data: >>previous data missing<< +Response: {explanation} + +Please provide the suggestions sequentially, without any additional text. For instance: +1. Suggestion +2. Suggestion +Additional suggestions mentioned in the response... + +If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. + +If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: +1. Suggestion +2. Suggestion +Additional suggestions based on the provided response and previous data... +""" + ) + + # Get the extracted previous data into the prompt + prompt = f""" +What are the suggestions in the response based on the given response and previous data? + +Previous data: {previous_data} +Response: {explanation} + +Please provide the suggestions sequentially, without any additional text. For instance: +1. Suggestion +2. Suggestion +Additional suggestions mentioned in the response... + +If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. + +If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response and previous data. For example: +1. Suggestion +2. Suggestion +Additional suggestions based on the provided response and previous data... +""" + + # Use the prompt to extract the suggestions from the response + suggestions = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": prompt, + } + ], + ) + suggestions = suggestions.choices[0].message.content + self.save_action(action1=prompt, action2=suggestions, category=0) + + # Check if the response gives any suggestions and if it is a answer + if suggestions[0:5].lower() in "reject": + print( + f""" +Sub-suggestion {suggestions}\n \n +""" + ) + return "Rejected" + + else: + print( + f""" +General '{explanation}' steps: +{suggestions}\n \n +""" + ) + + else: + # Extract the suggestions from the response (without previous data) + prompt = f""" +Please provide the suggestions mentioned in the following response: + +Response: {explanation} + +List only the suggestions in a sequential manner, without any additional text. For example: +1. Suggestion +2. Suggestion +Additional suggestions mentioned in the response... + +If the response explicitly rejects providing suggestions, please type "Rejected" on the first line of your response, followed by an explanation of why no suggestions or advice were given. + +If the response does not include any suggestions or provides information other than suggestions, please generate your own suggestions based on the provided response. For example: +1. Suggestion +2. Suggestion +Additional suggestions based on the provided response... +""" + + # Use the prompt to extract the suggestions from the response + suggestions = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": prompt, + } + ], + ) + suggestions = suggestions.choices[0].message.content + self.save_action(action1=prompt, action2=suggestions, category=0) + + # Check if the response gives any suggestions and if it is a answer + if suggestions[0:5].lower() in "reject": + print( + f""" +Sub-suggestion {suggestions}\n \n +""" + ) + return "Rejected" + + else: + print( + f""" +General '{explanation}' steps: +{suggestions}\n \n +""" + ) + + return suggestions + + def short_remember(self, need: str): + """ + Remmember a short period of history in detail from the DAIA MemoryDB, + and extract the most important data out of the history for the current need prompt + + In the need prompt, you must place a '>>previous data missing<<' string where you want the GPT to input the previous data + + (the main prompt needs major improvements) + """ + + memory = Memory() + + # Get and format all of the previous action with the limit of 100 + previous_important_data = "" + for action in memory.get_ordered_actions_of_goal(self.goal_id, 100): + previous_important_data = previous_important_data + "".join( + f'[{getattr(action, "action_id")}. Action: (Title of action: "{getattr(action, "title")}", Important data of action: "{getattr(action, "important_data")}")]\n' + ) + + # If there is no history yet + if len(previous_important_data) <= 0: + return "Nothing has hppened yet." + + # The main prompt + previous_data = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": f""" +Given the following context: +"{previous_important_data}" + +And the input data: +"{need}" + +Please input the necessary, relevant, and concise context from the given following context to complete the input data's ">>previous data missing<<" area. + +Please avoid addressing the prompt directly. Only input the data that needs to be in the ">>previous data missing<<" area. Keep your response minimal and to the point. +""", + } + ], + ) + + return previous_data.choices[0].message.content + + def get_important_data(self, data: str, previous_data: str): + """ + Extract the important data out of the provided data, based on the previous data + """ + + important_data = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": f""" +Given the following context: +"{previous_data}" + +And the current input data: +"{data}" + +Please use the provided context to extract and present the most important data from the input. +""", + } + ], + ) + + return important_data.choices[0].message.content + + def generate_title(self, data: str, item_category: str): + """ + Generate a title <75 chars based on the current data item_category and the data + """ + + title = self.client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + { + "role": "user", + "content": f""" +Provide a concise title (<75 chars) describing the {item_category}. + +{item_category} = "{data}" +""", + } + ], + ) + + return title.choices[0].message.content + + def save_goal(self): + "Save a goal into the DAIA MemoryDB" + + goal_summary = self.generate_title(self.goal, "goal") + + # Save the goal + memory = Memory() + new_goal = memory.create_goal_object(goal_summary) + memory.save_objects_in_db([new_goal]) + + return new_goal.goal_id + + def save_goal_in_goal(self): + """ + Save a goal under its own goal in the DAIA MemoryDB + """ + + memory = Memory() + + # Save the goal + goal_action = memory.create_action_object( + goal_id=self.goal_id, + title="Final Goal", + category="Goal", + full_data=self.goal, + important_data=f"The Final Goal is: {self.goal}", + ) + memory.save_objects_in_db([goal_action]) + + def save_action(self, action1: str, action2: str, category: int): + """ + Save a action under its category. (The action is made out of 2 actions) + + Category/action types: + "question=>response" = int 0 + "response=>action" = int 1 + "action=>result" = int 2 + "result=>action" = int 3 + """ + + categories = [ + "question=>response", + "response=>action", + "action=>result", + "result=>action", + ] + + # Translate the int parameter into its str + first = categories[category].split("=")[0] + second = categories[category].split(">")[-1] + + memory = Memory() + + # Generate the full_data, title and important data for the action + full_data = f'[1. {first}]: "{action1}",\n[2. {second}]: "{action2}"' + title = self.generate_title(full_data, f'"{first} with its {second}"') + previous_important_data = self.short_remember( + f""" +Given the following context: +>>previous context missing<< + +And the input data: +"{full_data}" + +Please use the provided context to extract and present the most important data from the input. +""", + ) + important_data = self.get_important_data(full_data, previous_important_data) + + # Save the action + new_action = memory.create_action_object( + self.goal_id, title, categories[category], full_data, important_data + ) + memory.save_objects_in_db([new_action]) + + def get_suggestions(self, suggestions: str): + """ + Extract the suggestions out of a suggestions response from the GPT, and put them into a list + """ + + suggestions_ = suggestions + for n in range(0, 40): + number = 40 - n + suggestions_ = suggestions_.replace(f"{number}.", "%_%") + + suggestions_ = suggestions_.replace("\n", "") + real_suggestions = suggestions_.split("%_%") + + if real_suggestions.count("") > 0: + real_suggestions.remove("") + + return real_suggestions diff --git a/DAIA_GPT4V/run.py b/DAIA_GPT4V/run.py new file mode 100644 index 0000000..8c0ca8c --- /dev/null +++ b/DAIA_GPT4V/run.py @@ -0,0 +1,170 @@ +from DAIA_GPT4V.Thinker.thinking import Think +from openai import OpenAI + + +def run(api_key): + goal = input("Please enter your goal for the DAIA here: ") + + # Check if goal is empty + while len(goal) <= 0: + print("Goal is empty!") + goal = input("Please enter your goal for the DAIA here: ") + + # Save the goal and get its id (goal_id=anything, -1 is just a example, as this is changed at line 18 by using another Think class inctance) + think_ = Think(key=api_key, goal=goal, goal_id=-1) + goal_id = think_.save_goal() + + # Save the goal with its id + think = Think(key=api_key, goal=goal, goal_id=goal_id) + think.save_goal_in_goal() + + # Loop for getting a question for goal compleation, that the user agrees with + while True: + prompt = f""" +You have a goal you want to achieve. +As your first step you want to know how to achieve your goal. So you must ask someone a question that will give you that information. + +your goal = {goal} + +What would that question be? (respond only with the question) +""" + + # Set the OpenAI client + client = OpenAI( + api_key=api_key, + ) + + question = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + {"role": "user", "content": prompt}, + ], + ) + question = question.choices[0].message.content + + print(f"Goal question: {question}") + q_agree = input("Do you agree with the question for goal completion? (Y/N)") + + if q_agree.upper() == "N": + print("Retrying...") + + else: + break + + # Make the GPT response its question about the goal + goal_help = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + {"role": "user", "content": question}, + ], + ) + goal_help = goal_help.choices[0].message.content + think.save_action(action1=question, action2=goal_help, category=0) + + suggestions = think.explanation_to_suggestions(goal_help, prev_data=False) + print( + f""" +General goal steps: +{suggestions} +""" + ) + + if suggestions == "Rejected": + print("The GPT does not want to respond to the question of your goal") + + else: + second_time = False + while True: + print( + "(Press ENTER to skip) WARNING: if you skip, the suggestions will be accepted. This is the LAST MANUAL step, everything from here on is automated" + ) + agree = input( + "Do you agree with the current suggestions/processes for your goal? (Y/N)" + ) + + # The code in this if statement only executes if it is the second time + if second_time: + if agree.upper() == "N": + think.save_action( + action1=f'"Sorry, but I dissagree with the current suggestions because: \n{explanation}\nCan you update the suggestions?"', + action2=f'"Yes, here are the new suggestions: \n{suggestions}"', + category=0, + ) + + # Make the GPT correct the suggestions to the users interest + explanation = input("Why do you not agree? ") + prompt = f""" +Please try to correct your suggestions. + +Here is why I don't agree with them: +{explanation} +""" + corrected_suggestions_response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + {"role": "user", "content": corrected_suggestions_response}, + {"role": "user", "content": prompt}, + ], + ) + corrected_suggestions_response = ( + corrected_suggestions_response.choices[0].message.content + ) + + suggestions = think.explanation_to_suggestions( + corrected_suggestions_response, prev_data=False + ) + print( + f""" +General goal steps: +{suggestions} +""" + ) + + else: + think.save_action( + action1=f'"Sorry, but I dissagree with the current suggestions because: \n{explanation}\nCan you update the suggestions?"', + action2=f'"Yes, here are the new suggestions: \n{suggestions}"', + category=0, + ) + + print("/) Ok then, let's go!") + break + + else: + if agree.upper() == "N": + second_time = True + + # Make the GPT correct the suggestions to the users interest + explanation = input("Why do you not agree? ") + prompt = f""" +Please try to correct your suggestions. + +Here is why I don't agree with them: +{explanation} +""" + corrected_suggestions_response = client.chat.completions.create( + model="gpt-3.5-turbo", + messages=[ + {"role": "user", "content": suggestions}, + {"role": "user", "content": prompt}, + ], + ) + corrected_suggestions_response = ( + corrected_suggestions_response.choices[0].message.content + ) + + suggestions = think.explanation_to_suggestions( + corrected_suggestions_response, prev_data=False + ) + print( + f""" +General goal steps: +{suggestions} +""" + ) + + else: + print("/) Ok then, let's go!") + break + + think.goal_completer(suggestions) diff --git a/Design/.$DAIA (GPT Vision).drawio.bkp b/Design/.$DAIA (GPT Vision).drawio.bkp new file mode 100644 index 0000000..f84192b --- /dev/null +++ b/Design/.$DAIA (GPT Vision).drawio.bkp @@ -0,0 +1,800 @@ + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + + 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@@ - + @@ -414,7 +414,7 @@ - + @@ -424,36 +424,36 @@ - + - + - + - + - + - + - + - + - + - + @@ -462,132 +462,132 @@ - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + @@ -596,13 +596,13 @@ - + - + - + @@ -611,7 +611,7 @@ - + @@ -620,28 +620,28 @@ - + - + - + - + - + - + - + - + @@ -650,7 +650,7 @@ - + @@ -659,7 +659,7 @@ - + @@ -668,7 +668,7 @@ - + @@ -677,7 +677,7 @@ - + @@ -686,15 +686,15 @@ - + - + - + @@ -703,12 +703,12 @@ - + - + @@ -717,21 +717,21 @@ - + - + - + @@ -740,73 +740,73 @@ - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + - + diff --git a/README.md b/README.md index 92d5428..8358583 100644 --- a/README.md +++ b/README.md @@ -14,46 +14,63 @@ DAIA is a powerful Digital Artificial Intelligence Agent that enables intelligen ## 1. Introduction πŸš€ -DAIA is a cutting-edge AI agent designed to enhance your productivity by intelligently interacting with your computer. With DAIA, you can automate tasks, gather information, and perform various operations seamlessly, just like you would do yourself. +DAIA is a cutting-edge AI agent designed to enhance your productivity by intelligently interacting with your computer and compleating big goals. With DAIA, you can complate goals, automate tasks, gather information, and perform various operations seamlessly, just like you would do yourself. + +The main difference with the DAIA compared to other AI Agents is that it interacts with your computer trough a vision system (GPT-4V) and task compleation system allowing it to be capable of doing many more tasks and goals compared to other AI Agents that use the Terminal or CMD for interaction with the computer. +Furthermore the DAIA will be built with a built in memory, self evaluating and optimizing system from the start. + +![Here is our current blueprint for the DAIA and its features:](Design/DAIA%20(GPT%20Vision).png) ## 2. Features 🌟 -- **Intelligent Interaction**: DAIA can interact with your PC using natural language, making it easy to communicate your needs. +- **Intelligent Interaction**: DAIA can interact with your PC using natural language, making it easy to communicate your needs. (in progress) -- **Task Automation**: Automate repetitive tasks and processes, saving time and effort. +- **Task Automation**: Automate repetitive tasks and processes, saving time and effort. (in progress) -- **Information Retrieval**: Get real-time information, answers, and data from the web. +- **Information Retrieval**: Get real-time information, answers, and data from the web. (in progress) -- **Multi-Platform Support**: DAIA is compatible with various operating systems and applications. +- **Multi-Platform Support**: DAIA is compatible with various operating systems and applications. (in progress) -- **Customization**: Tailor DAIA to your specific needs and preferences through custom scripts and plugins. +- **Customization**: Tailor DAIA to your specific needs and preferences through custom scripts and plugins. (not done yet) -- **Memory**: Each action is saved into the memory, allowing you to start where you left. +- **Memory**: Each action is saved into the memory, allowing you to start where you left. (in progress) -- **Security**: Ensure your data and interactions are secure with robust encryption and privacy measures. +- **Security**: Ensure your data and interactions are secure with robust encryption and privacy measures. (not done yet) + +- **Endless Scalability**: DAIA can make multiple copies of itself and create its own network of DAIAs provided the computing power (in progress) + +- **Automation of Big Goals**: DAIA can automate big goals with its capability to make multiple versions of itself, therefor making the process faster (in progress) ## 3. Usage 🀝 -Once installed, you can start using DAIA by launching the application and initiating conversations or tasks. Here are some common usage scenarios: +Once installed, you can start using DAIA by launching the application and initiating conversations or goals. Here are some common usage scenarios: -- **Task Automation**: Create and schedule automated tasks to streamline your workflow. +- **Goal Compleation**: Automate and compleate goals (in progress) -- **Information Retrieval**: Ask DAIA for information, news, or data from the web. +- **Task Automation**: Create and schedule automated tasks to streamline your workflow. (not done yet) -- **Scripting and Customization**: Extend DAIA's capabilities by writing custom scripts or plugins. +- **Information Retrieval**: Ask DAIA for information, news, or data from the web. (in progress) -For detailed instructions and usage examples, consult the user manual available on the DAIA website. +- **Scripting and Customization**: Extend DAIA's capabilities by writing custom scripts or plugins. ((not done yet)) ## 4. Contribution πŸ™Œ -We welcome contributions from the DAIA community to help improve and expand the capabilities of our AI agent. Here's how you can contribute: +We welcome contributions from the DAIA community to help improve and expand the capabilities of our AI agent. It is still in its early development stage so there is a lot to be done and we urgently need your support in this effort. Here's how you can contribute: -- **Code Contributions**: If you're a developer, you can contribute to the DAIA project by submitting code improvements, bug fixes, or new features. +- **Join Our Discord Server**: If you're a developer or someone who is interested in contributing, please join our Discord server The Envedity Network at: https://discord.gg/Xrf8bjXMU6, there you can become a developer and will be able to directly contribute to the main DAIA repo with us, as well as share your feedback, suggestions, and bug reports with us and more.. -- **Feedback**: Share your feedback, suggestions, and bug reports with us. Your insights are valuable in shaping the future of DAIA. You can do this by [opening an issue](https://github.com/Envedity/DAIA/issues) on our feedback repository. +![Here is what we have already done from the blueprint:](Design/DAIA%20(GPT%20Vision)%20progress.png) + +- **Feedback**: Share your feedback, suggestions, and bug reports with us. Your insights are valuable in shaping the future of DAIA. You can do this by [opening an issue](https://github.com/Envedity/DAIA/issues) on our feedback repository or in our Discord server. + +- **Share**: Share the DAIA project with others you know to spread the word (DAIA repo link: https://github.com/Envedity/DAIA) + +- **Support (Sponsor the project)**: We appreciate your support in making DAIA even better for all users! πŸ™ +Lets build the future of AGI Together! + ## 5. License πŸ“„ DAIA is under the creative commons license. diff --git a/requirements.txt b/requirements.txt index 4216116..8c9f92b 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,5 +1,4 @@ openai python-dotenv sqlalchemy -tiktoken -black +black \ No newline at end of file diff --git a/utils/openaicaller.py b/utils/openaicaller.py deleted file mode 100644 index 29b9c71..0000000 --- a/utils/openaicaller.py +++ /dev/null @@ -1,219 +0,0 @@ -""" -This file provides a Python module that wraps the OpenAI API for making API calls. - -The module includes: - -- Functions for generating responses using chat-based models and handling API errors. -- Constants for chat and text models and their maximum token limits. -- Imports for required modules, including OpenAI and asyncio. -- A color formatting class, `bcolors`, for console output. - -The main component is the `openai_caller` class with methods: -- `__init__(self, api_key=None)`: Initializes an instance of the class and sets the API key if provided. -- `set_api_key(self, key)`: Sets the API key for OpenAI. -- `generate_response(self, **kwargs)`: Asynchronously generates a response based on the provided arguments. -- `chat_generate(self, **kwargs)`: Asynchronously generates a chat-based response, handling token limits and API errors. - -The module assumes the presence of `num_tokens_from_messages` function in a separate module called `utils.tokens`, used for token calculation. - -Refer to function and method documentation for further details. -""" - - -import openai as openai_module -import asyncio - -from openai.error import ( - APIError, - Timeout, - RateLimitError, - APIConnectionError, - InvalidRequestError, - AuthenticationError, - ServiceUnavailableError, -) -from utils.tokens import num_tokens_from_messages - - -class bcolors: - HEADER = "\033[95m" - OKBLUE = "\033[94m" - OKCYAN = "\033[96m" - OKGREEN = "\033[92m" - WARNING = "\033[93m" - FAIL = "\033[91m" - ENDC = "\033[0m" - BOLD = "\033[1m" - UNDERLINE = "\033[4m" - - -chat_models = [ - "gpt-4", - "gpt-4-32k", - "gpt-3.5-turbo", - "gpt-3.5-turbo-16k", - "gpt-3.5-turbo-0613", -] -text_models = [ - "text-davinci-003", - "text-davinci-002", - "text-curie-001", - "text-babbage-001", - "text-ada-001", -] - -models_max_tokens = { - "gpt-4": 8_192, - "gpt-4-32k": 32_768, - "gpt-3.5-turbo": 4_096, - "gpt-3.5-turbo-0613": 4_096, - "gpt-3.5-turbo-16k": 16_384, - "text-davinci-003": 4_097, - "text-davinci-002": 4_097, - "text-curie-001": 2_049, - "text-babbage-001": 2_049, - "text-ada-001": 2_049, -} - - -class openai_caller: - def __init__(self) -> None: - pass - - # async def generate_response(self, error_call=None, **kwargs): - async def generate_response(*args, **kwargs): - self = args[0] - if len(args) > 1: - error_call = args[1] - else: - - async def nothing(x): - return x - - error_call = nothing - if kwargs.get("model", "") in chat_models: - return await self.chat_generate(error_call, **kwargs) - elif kwargs.get("engine", "") in text_models: - raise NotImplementedError("Text models are not supported yet") - else: - raise ValueError("Model not found") - - async def chat_generate(self, recall_func, **kwargs): - tokens = await num_tokens_from_messages(kwargs["messages"], kwargs["model"]) - model_max_tokens = models_max_tokens[kwargs["model"]] - while tokens > model_max_tokens: - kwargs["messages"] = kwargs["messages"][1:] - print( - f"{bcolors.BOLD}{bcolors.WARNING}Warning: Too many tokens. Removing first message.{bcolors.ENDC}" - ) - tokens = await num_tokens_from_messages(kwargs["messages"], kwargs["model"]) - if kwargs.get("api_key", None) == None: - raise ValueError("API key not set") - callable = lambda: openai_module.ChatCompletion.acreate(**kwargs) - response = await self.retryal_call(recall_func, callable) - return response - - async def moderation(*args, **kwargs): - self = args[0] - if len(args) > 1: - error_call = args[1] - else: - - async def nothing(x): - return x - - error_call = nothing - callable = lambda: openai_module.Moderation.acreate(**kwargs) - response = await self.retryal_call(error_call, callable) - return response - - async def retryal_call(self, recall_func, callable): - i = 0 - response = None - while i < 10: - try: - response = await callable() - return response - except APIError as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.WARNING}APIError. This is not your fault. Retrying...{bcolors.ENDC}" - ) - await recall_func( - "`An APIError occurred. This is not your fault, it is OpenAI's fault. We apologize for the inconvenience. Retrying...`" - ) - await asyncio.sleep(10) - await recall_func() - i += 1 - except Timeout as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.WARNING}The request timed out. Retrying...{bcolors.ENDC}" - ) - await recall_func("`The request timed out. Retrying...`") - await asyncio.sleep(10) - await recall_func() - i += 1 - except RateLimitError as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.WARNING}RateLimitError. You are being rate limited. Retrying...{bcolors.ENDC}" - ) - await recall_func("`You are being rate limited. Retrying...`") - await asyncio.sleep(10) - await recall_func() - i += 1 - except APIConnectionError as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.FAIL}APIConnectionError. There is an issue with your internet connection. Please check your connection.{bcolors.ENDC}" - ) - await recall_func() - raise e - except InvalidRequestError as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.FAIL}InvalidRequestError. Please check your request.{bcolors.ENDC}" - ) - await recall_func("`InvalidRequestError. Please check your request.`") - raise e - except AuthenticationError as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.FAIL}AuthenticationError. Please check your API key and if needed, also your organization ID.{bcolors.ENDC}" - ) - await recall_func("`AuthenticationError. Please check your API key.`") - raise e - except ServiceUnavailableError as e: - print( - f"\n\n{bcolors.BOLD}{bcolors.WARNING}ServiceUnavailableError. The OpenAI API is not responding. Retrying...{bcolors.ENDC}" - ) - await recall_func("`The OpenAI API is not responding. Retrying...`") - await asyncio.sleep(10) - await recall_func() - i += 1 - finally: - if i == 10: - print( - f"\n\n{bcolors.BOLD}{bcolors.FAIL}OpenAI API is not responding. Please try again later.{bcolors.ENDC}" - ) - raise TimeoutError( - "OpenAI API is not responding. Please try again later." - ) - return response - - -caller = openai_caller() - -##testing -if __name__ == "__main__": - - async def main(): - response = await caller.generate_response( - api_key="sk-", - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "ping"}], - max_tokens=5, - temperature=0.7, - top_p=1, - frequency_penalty=0, - presence_penalty=0, - stop=["\n", " Human:", " AI:"], - ) - print(response) - - asyncio.run(main()) diff --git a/utils/openaicaller.py.md b/utils/openaicaller.py.md deleted file mode 100644 index a70ae2d..0000000 --- a/utils/openaicaller.py.md +++ /dev/null @@ -1,137 +0,0 @@ -# OpenAI Caller Script Reference - -The provided script defines a class `openai_caller` that encapsulates methods to interact with OpenAI models using the official OpenAI module. It includes error handling and retry mechanisms. Below is the detailed explanation of the code along with its features and examples. - -## Features - -### 1. Chat Models & Text Models - -The script supports the usage of various chat models and text models. The available models are defined in the `chat_models` and `text_models` lists. Currently, the text models are not supported and will raise a `NotImplementedError`. - -### 2. Retry Mechanism - -The script includes a retry mechanism to handle common API errors, timeouts, and rate limit issues. It will attempt to retry a call up to 10 times before failing. - -### 3. Error Callback Function - -An optional retry callback function (`recall_func`) can be provided to handle errors. This function should take a string argument representing the error message. If you do not care about the error message, you should still define a dummy parameter for the function. This function will be called each time an error occurs. The error will always be printed to the terminal, regardless of whether a callback function is provided or not. - -### 4. Colored Warnings & Errors - -The script uses ANSI escape codes to colorize warning and error messages in the terminal, making them more visible. - -### 5. Mandatory API Key - -The `api_key` parameter is mandatory in each call to the OpenAI models. - -### 6. Handling Too Many Tokens - -The script ensures that the number of tokens in a request does not exceed the maximum allowed tokens for the specified model. If the number of tokens in the `messages` parameter exceeds the model's maximum token limit, the script will iteratively remove the first message from the `messages` array until the total token count is within the limit. This is done using the following logic: - -```python -tokens = await num_tokens_from_messages(kwargs["messages"], kwargs["model"]) -model_max_tokens = models_max_tokens[kwargs["model"]] -while tokens > model_max_tokens: - kwargs["messages"] = kwargs["messages"][1:] - print(f"{bcolors.BOLD}{bcolors.WARNING}Warning: Too many tokens. Removing first message.{bcolors.ENDC}") - tokens = await num_tokens_from_messages(kwargs["messages"], kwargs["model"]) -``` - -This feature ensures that the request complies with the token constraints of the chosen model and automatically adapts the input by removing the earliest messages if necessary. - -## Methods - -### `generate_response(error_call=None, **kwargs)` - -This method is used to generate a response from the OpenAI models based on the provided parameters. It will figure out whether the model is a chat model or a text model and call the appropriate method. The parameters are as follows: - -- `error_call`: An optional **FIRST POSITIONAL** argument **async** function that will be called if an error occurs. That function should take a string as an argument, representing the error message. -- The parameters passed to the OpenAI model. They must include the mandatory `api_key` parameter. Theese are the same parameters as defined in the standard OpenAI module, except for the addition of the `api_key` parameter. Any parameer here will be passed transparently to the OpenAI module. - -### `chat_generate(recall_func, **kwargs)` - -An internal method used to generate chat-based responses. - -### `moderation(recall_func=None, **kwargs)` - -This method is used for moderation purposes with the OpenAI models. - -### `retryal_call(recall_func, callable)` - -An internal method that implements the retry mechanism. - -## Error Handling - -Errors are handled through retries and callback functions: - -- `APIError`: Not the user's fault. It will be retried. -- `Timeout`: Request timed out. It will be retried. -- `RateLimitError`: User is being rate-limited. It will be retried. -- `APIConnectionError`: Issue with the internet connection. It will be raised. -- `InvalidRequestError`: Issue with the request. It will be raised. -- `AuthenticationError`: Issue with the API key. It will be raised. -- `ServiceUnavailableError`: OpenAI API is not responding. It will be retried. - -## Important Note - -**Unlike the OpenAI module, in this script, the `api_key` parameter is NOT passed during the initialization of the `caller` class. Instead, it MUST be passed with each individual request.** - -## Examples - -### Example 1: Basic Chat Generation - -This example demonstrates a simple chat generation without a retry callback function. - -```python -from openaicaller import caller as openai -async def main(): - response = await openai.generate_response( - api_key="sk-your-api-key", - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "ping"}] - ) - print(response) - -asyncio.run(main()) -``` - -### Example 2: Using a Retry Callback Function - -This example shows how to define and use a custom retry callback function with the chat generation. - -```python -from openaicaller import caller as openai -def my_retry_function(error_message): #this function will be automatically called when ar error is gotten. You can define it and pass it as an argument. It is important to note that, if your function does not care of the error message, it should still take a dummy parameter as input - print(f"An error occurred: {error_message}. Retrying...") - -async def main(): - response = await openai.generate_response( - error_call=my_retry_function, - api_key="sk-your-api-key", - model="gpt-3.5-turbo", - messages=[{"role": "user", "content": "ping"}] - ) - print(response) - -asyncio.run(main()) -``` - -### Example 3: Handling Moderation - -This example demonstrates how to call the moderation method with the OpenAI caller class. - -```python -from openaicaller import caller as openai -async def main(): - response = await openai.moderation( - api_key="sk-your-api-key", - # Additional parameters as needed - ) - print(response) - -asyncio.run(main()) -``` - -## Conclusion - -The `openai_caller` class provided in this script offers a robust way to interact with OpenAI models. By including the `api_key` parameter in each request and optionally providing a custom retry callback function, users can have granular control over the API interaction, including error handling and retry mechanisms. Make sure to follow the correct usage pattern, as it differs from the standard OpenAI module. \ No newline at end of file diff --git a/utils/setup.py b/utils/setup.py new file mode 100644 index 0000000..ef0c50a --- /dev/null +++ b/utils/setup.py @@ -0,0 +1,10 @@ +from pathlib import Path +import os + + +def setup(): + paths = [Path("DAIA/Screenshots")] + + for path in paths: + if not path.exists(): + os.mkdir(path) diff --git a/utils/tokens.py b/utils/tokens.py deleted file mode 100644 index 055d75c..0000000 --- a/utils/tokens.py +++ /dev/null @@ -1,39 +0,0 @@ -""" -This file's purpose is to count the number of tokens used by a list of messages. -It is used to check if the token limit of the model is reached. - -Reference: https://github.com/openai/openai-cookbook/blob/main/examples/How_to_format_inputs_to_ChatGPT_models.ipynb -""" - -import tiktoken - - -async def num_tokens_from_messages(messages, model="gpt-3.5-turbo"): - """Returns the number of tokens used by a list of messages.""" - try: - encoding = tiktoken.encoding_for_model(model) - except KeyError: - print("Warning: model not found. Using cl100k_base encoding.") - encoding = tiktoken.get_encoding("cl100k_base") - - if model.startswith("gpt-3.5-turbo"): - tokens_per_message = ( - 4 # every message follows <|start|>{role/name}\n{content}<|end|>\n - ) - tokens_per_name = -1 # if there's a name, the role is omitted - elif model.startswith("gpt-4"): - tokens_per_message = 3 - tokens_per_name = 1 - else: - raise NotImplementedError( - f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.""" - ) - num_tokens = 0 - for message in messages: - num_tokens += tokens_per_message - for key, value in message.items(): - num_tokens += len(encoding.encode(value)) - if key == "name": - num_tokens += tokens_per_name - num_tokens += 3 # every reply is primed with <|start|>assistant<|message|> - return num_tokens