Package: commandsgpt
CommandsGPTAn implementation of GPT-4 to recognize instructions. It recognizes which commands it must run to fulfill the user's instruction, using a graph where each node is a command and the data generated by each command can be passed to other commands.Create new commands easily by describing them using natural language and coding the functions corresponding to the commands.InstallationInstall thecommandsgptmodule.pip install commandsgptIf you're using a virtual environment:pipenv install commandsgptYou also have to install the OpenAI package:pip install openaiorpipenv install openaiSet an environment variable OPENAI_API_KEY to store your OpenAI key.UsageCreate acommandsdictionary that will store the commands described in natural language.commands={"REQUEST_USER_INPUT":{"description":"Asks the user to input data through the interface.","arguments":{"message":{"description":"Message displayed to the user related to the data that will be requested (example: 'Enter your age').","type":"string"},},"generates_data":{"input":{"description":"Data entered by the user","type":"string"},},},...}Now, create the functions that will be called when the commands are executed.The name of the function is irrelevant.The first parameter must be the Config object; the second one must be the Graph object. Normally, you won't work directly with these objects, so you don't have to worry about them. Just use them as the first two parameters.The following parameters must match those described in the commands dictionary (name and data type).The return value must be a dictionary. Its keys, values and data types must match the return values described in the commands dictionary.Example of a command functionfromcommands_gpt.configimportConfigfromcommands_gpt.commands.graphsimportGraphdefrequest_user_input_command(config:Config,graph:Graph,message:str)->dict[str,Any]:input_=input(f"{message}\n*: ")results={"input":input_,}returnresultsCreate acommand_name_to_funcdictionary that will take the name of a command and return the corresponding function.Example of command_name_to_func dictionarycommand_name_to_func={"REQUEST_USER_INPUT":request_user_input_command,...}Add theessential commandsto your commands dictionaries.These are the default commands that implement core logic to the model's thinking, like an IF command.If you already defined your own core logic commands (IF command, THINK command, CALCULATE command, etc.), then you are free not to use them.fromcommands_gpt.commands.commands_funcsimportadd_essential_commandsadd_essential_commands(commands,command_name_to_func)Yourconfigobject:# keyword arguments are optionalconfig=Config("gpt-4-0314",verbosity=1,explain_graph=True,save_graph_as_file=False)Create an instruction:instruction=input("Enter your instruction: ")Create a recognizer:recognizer=ComplexRecognizer(config,commands,command_name_to_func)Pass your instruction to the recognizer model:commands_data_str=recognizer.recognize(instruction)Create the graph of commands and execute it:graph=Graph(recognizer,commands_data_str)graph.execute_commands(config)ExampleCreate two files:custom_commands.pyandmain.py.custom_commands.pyfromtypingimportAnyfrompathlibimportPathfromcommands_gpt.configimportConfigfromcommands_gpt.commands.graphsimportGraphcommands={"WRITE_TO_USER":{"description":"Writes something to the interface to communicate with the user.","arguments":{"content":{"description":"Content to write.","type":"string"},},"generates_data":{},},"REQUEST_USER_INPUT":{"description":"Asks the user to input data through the interface.","arguments":{"message":{"description":"Message displayed to the user related to the data that will be requested (example: 'Enter your age').","type":"string"},},"generates_data":{"input":{"description":"Data entered by the user","type":"string"},},},"WRITE_FILE":{"description":"Write a file.","arguments":{"content":{"description":"Content that will be written.","type":"string"},"file_path":{"description":"Complete path of the file that will be written.","type":"string"},},"generates_data":{},},}# Commands functions# The name of the function is irrelevant# The first argument must be the Config object, followed by the Graph object# The arguments must match the arguments from the commands dictionary# The return value must be a dictionary which keys must match the "generates_data" keys# The data types must match the ones declared in the commands dictionarydefwrite_to_user_command(config:Config,graph:Graph,content:str)->dict[str,Any]:print(f">>>{content}")return{}defrequest_user_input_command(config:Config,graph:Graph,message:str)->dict[str,Any]:input_=input(f"{message}\n*: ")results={"input":input_,}returnresultsdefwrite_file_command(config:Config,graph:Graph,content:str,file_path:str)->dict[str,Any]:file_dir=Path(file_path).parentassertfile_dir.exists(),f"Container directory '{file_dir}' does not exist."withopen(file_path,"w+",encoding="utf-8")asf:f.write(content)f.close()return{}# add your functions herecommand_name_to_func={"WRITE_TO_USER":write_to_user_command,"REQUEST_USER_INPUT":request_user_input_command,"WRITE_FILE":write_file_command,}main.pyfromcommands_gpt.recognizersimportComplexRecognizerfromcommands_gpt.commands.graphsimportGraphfromcommands_gpt.configimportConfigfromcustom_commandsimportcommands,command_name_to_funcfromcommands_gpt.commands.commands_funcsimportadd_essential_commandsadd_essential_commands(commands,command_name_to_func)chat_model="gpt-4-0314"config=Config(chat_model,verbosity=2,explain_graph=False,save_graph_as_file=False)instruction=input("Enter your prompt: ")recognizer=ComplexRecognizer(config,commands,command_name_to_func)commands_data_str=recognizer.recognize(instruction)graph=Graph(recognizer,commands_data_str)graph.execute_commands(config)Copyright (c) 2023, Martín Alexis Martínez Andrade.
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