PR for Haohan Wang #mPXWvBqt6ftrqBDUcPfT

[gothub-ai]

You can use the ability with id gpt_engineer as an AI software engineer, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as ' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this gpt_engineer ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.

You can use the ability with id 8x5joFx3uMt4CcLnoc8s as an AI software company that has numerous roles and can accomplish any SaaS-related tasks, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as ' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this 8x5joFx3uMt4CcLnoc8s ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.

When you try to accomplish a given task, you should always do the following two steps in order:

1. Use Ability gpt_engineer to write out the source code.
2. Use Ability 8x5joFx3uMt4CcLnoc8s to first design the software of the product.
3. In your final response, remember to repeat all content in md files and mmd (nmermaid) files.

Now do the following task:

write me nothing

Gothub's Answer: Here is the result of your request:

First, I used the gpt_engineer ability to write out the source code. Here's a simple Python application that prints "Hello, World!" to the console. This application consists of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).

greeting.py

class Greeting:
    """A class that generates a greeting message."""

    def get_greeting(self):
        """Returns a greeting message."""
        return "Hello, World!"

main.py

from greeting import Greeting

def main():
    """The entry point of the application."""
    greeting = Greeting()
    print(greeting.get_greeting())

if __name__ == "__main__":
    main()

To run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.

Next, I used the 8x5joFx3uMt4CcLnoc8s ability to design the software of the product. Here's the design:

Product Goals

[
    "Create a product that meets market needs",
    "Ensure the product is user-friendly and intuitive",
    "Achieve a high level of efficiency in product development"
]

User Stories

[
    "As a user, I want to easily navigate the product so that I can quickly find what I need",
    "As a user, I want the product to be reliable so that I can trust it for my needs",
    "As a user, I want the product to have a clean and modern design so that it is pleasing to use",
    "As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly",
    "As a user, I want the product to be regularly updated so that it stays relevant and useful"
]

Requirement Analysis

The product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.

Requirement Pool

[
    ("Develop a user-friendly and intuitive interface", "P0"),
    ("Ensure the product is reliable and trustworthy", "P0"),
    ("Create a modern and clean design for the product", "P1"),
    ("Establish a responsive customer service", "P1"),
    ("Set up regular updates for the product", "P2")
]

UI Design draft

The product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.

Implementation approach

We will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.

Python package name

"product_x"

File list

[
    "main.py",
    "app/__init__.py",
    "app/routes.py",
    "app/models.py",
    "app/forms.py",
    "app/static/css/style.css",
    "app/templates/index.html",
    "app/templates/layout.html",
    "app/templates/login.html",
    "app/templates/register.html",
    "config.py",
    "Dockerfile",
    "requirements.txt"
]

Data structures and interface definitions

classDiagram
    class User{
        +str username
        +str email
        +str password_hash
        +__init__(username: str, email: str, password: str)
        +check_password(password: str): bool
    }
    class Product{
        +str name
        +str description
        +float price
        +__init__(name: str, description: str, price: float)
    }
    User "1" -- "*" Product: has

Loading

Program call flow

sequenceDiagram
    participant M as Main
    participant U as User
    participant P as Product
    M->>U: create_user(username, email, password)
    M->>U: login_user(username, password)
    M->>P: create_product(name, description, price)
    U->>P: view_product(name)
    U->>P: purchase_product(name)
    M->>U: logout_user()

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Please note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods.

[gothub-ai]

Logging: init

Logging: init

Logging: on_chain_start

Serialized:

{
"lc": 1,
"type": "not_implemented",
"id": [
"langchain",
"agents",
"agent",
"AgentExecutor"
]
}

inputs:

{
"input": "You can use the ability with id gpt_engineer as an AI software engineer, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as ' and \" because ability_args are passed in a Linux command line terminal). Keep in mind that this gpt_engineer ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nYou can use the ability with id 8x5joFx3uMt4CcLnoc8s as an AI software company that has numerous roles and can accomplish any SaaS-related tasks, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as ' and \" because ability_args are passed in a Linux command line terminal). Keep in mind that this 8x5joFx3uMt4CcLnoc8s ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nWhen you try to accomplish a given task, you should always do the following two steps in order:\n\n1. Use Ability gpt_engineer to write out the source code.\n2. Use Ability 8x5joFx3uMt4CcLnoc8s to first design the software of the product.\n3. In your final response, remember to repeat all content in md files and mmd (nmermaid) files.\n\nNow do the following task:\n\n\nwrite me nothing"
}

Logging: on_chat_model_start

Serialized:

{
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"chat_models",
"openai",
"ChatOpenAI"
],
"kwargs": {
"temperature": 0.0,
"model": "gpt-4-0613",
"openai_api_key": {
"lc": 1,
"type": "secret",
"id": [
"OPENAI_API_KEY"
]
}
}
}

message:

[[SystemMessage(content='You are a helpful AI assistant.', additional_kwargs={}), HumanMessage(content='You can use the ability with id gpt_engineer as an AI software engineer, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as \' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this gpt_engineer ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nYou can use the ability with id 8x5joFx3uMt4CcLnoc8s as an AI software company that has numerous roles and can accomplish any SaaS-related tasks, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as \' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this 8x5joFx3uMt4CcLnoc8s ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nWhen you try to accomplish a given task, you should always do the following two steps in order:\n\n1. Use Ability gpt_engineer to write out the source code.\n2. Use Ability 8x5joFx3uMt4CcLnoc8s to first design the software of the product.\n3. In your final response, remember to repeat all content in md files and mmd (nmermaid) files.\n\nNow do the following task:\n\n\nwrite me nothing', additional_kwargs={}, example=False)]]

Logging: on_llm_end

generations=[[ChatGeneration(text='', generation_info={'finish_reason': 'function_call'}, message=AIMessage(content='', additional_kwargs={'function_call': {'name': 'run_ability', 'arguments': '{\n "ability_id": "gpt_engineer",\n "ability_args": "write me nothing"\n}'}}, example=False))]] llm_output={'token_usage': <OpenAIObject at 0x7f579c610590> JSON: {
"prompt_tokens": 698,
"completion_tokens": 29,
"total_tokens": 727
}, 'model_name': 'gpt-4-0613'} run=None

Logging: on_agent_action

Tool used:

run_ability

Tool input:

{
"ability_id": "gpt_engineer",
"ability_args": "write me nothing"
}

Additional log:

Invoking: run_ability with {'ability_id': 'gpt_engineer', 'ability_args': 'write me nothing'}

Logging: on_chat_model_start

Serialized:

{
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"chat_models",
"openai",
"ChatOpenAI"
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"kwargs": {
"temperature": 0.0,
"model": "gpt-4-0613",
"openai_api_key": {
"lc": 1,
"type": "secret",
"id": [
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}
}

message:

[[SystemMessage(content='You are a helpful AI assistant.', additional_kwargs={}), HumanMessage(content='You can use the ability with id gpt_engineer as an AI software engineer, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as \' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this gpt_engineer ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nYou can use the ability with id 8x5joFx3uMt4CcLnoc8s as an AI software company that has numerous roles and can accomplish any SaaS-related tasks, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as \' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this 8x5joFx3uMt4CcLnoc8s ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nWhen you try to accomplish a given task, you should always do the following two steps in order:\n\n1. Use Ability gpt_engineer to write out the source code.\n2. Use Ability 8x5joFx3uMt4CcLnoc8s to first design the software of the product.\n3. In your final response, remember to repeat all content in md files and mmd (nmermaid) files.\n\nNow do the following task:\n\n\nwrite me nothing', additional_kwargs={}, example=False), AIMessage(content='', additional_kwargs={'function_call': {'name': 'run_ability', 'arguments': '{\n "ability_id": "gpt_engineer",\n "ability_args": "write me nothing"\n}'}}, example=False), FunctionMessage(content='Requirement: write me nothing \nI'm sorry, but your instruction is unclear. Could you please provide more details or context?\nFull-auto mode\n(letting gpt-engineer make its own assumptions)\n\nAssumptions:\n\n1. You want me to write something, but you haven't specified what.\n2. "Write me nothing" could be a metaphorical or philosophical statement, not a literal one.\n\nClarifying question: Could you please specify what you want me to write about or elaborate on the context of "write me nothing"?\nBased on your instructions, I'm going to create a simple Python application that prints "Hello, World!" to the console. This application will consist of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).\n\nHere are the core classes, functions, and methods that will be necessary:\n\n1. Greeting class: This class will be defined in greeting.py and will contain the logic for generating the greeting message.\n2. get_greeting method: This method will be part of the Greeting class. It will return the greeting message.\n3. main function: This function will be defined in main.py. It will create an instance of the Greeting class and print the greeting message to the console.\n\nNow, let's write the code for each file.\n\ngreeting.py\npython\nclass Greeting:\n """A class that generates a greeting message."""\n\n def get_greeting(self):\n """Returns a greeting message."""\n return "Hello, World!"\n\n\nmain.py\npython\nfrom greeting import Greeting\n\ndef main():\n """The entry point of the application."""\n greeting = Greeting()\n print(greeting.get_greeting())\n\nif __name__ == "__main__":\n main()\n\n\nTo run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.\n\nPlease note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods.a) Install dependencies:\n\nThis Python application does not have any external dependencies, so there's no need to install anything.\n\nb) Run all necessary parts of the codebase:\n\nbash\npython main.py\n\n', additional_kwargs={}, name='run_ability')]]

Logging: on_llm_end

generations=[[ChatGeneration(text='', generation_info={'finish_reason': 'function_call'}, message=AIMessage(content='', additional_kwargs={'function_call': {'name': 'run_ability', 'arguments': '{\n "ability_id": "8x5joFx3uMt4CcLnoc8s",\n "ability_args": "write me nothing"\n}'}}, example=False))]] llm_output={'token_usage': <OpenAIObject at 0x7f579c6118b0> JSON: {
"prompt_tokens": 1266,
"completion_tokens": 39,
"total_tokens": 1305
}, 'model_name': 'gpt-4-0613'} run=None

Logging: on_agent_action

Tool used:

run_ability

Tool input:

{
"ability_id": "8x5joFx3uMt4CcLnoc8s",
"ability_args": "write me nothing"
}

Additional log:

Invoking: run_ability with {'ability_id': '8x5joFx3uMt4CcLnoc8s', 'ability_args': 'write me nothing'}

Logging: on_chat_model_start

Serialized:

{
"lc": 1,
"type": "constructor",
"id": [
"langchain",
"chat_models",
"openai",
"ChatOpenAI"
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"kwargs": {
"temperature": 0.0,
"model": "gpt-4-0613",
"openai_api_key": {
"lc": 1,
"type": "secret",
"id": [
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]
}
}
}

message:

[[SystemMessage(content='You are a helpful AI assistant.', additional_kwargs={}), HumanMessage(content='You can use the ability with id gpt_engineer as an AI software engineer, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as \' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this gpt_engineer ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nYou can use the ability with id 8x5joFx3uMt4CcLnoc8s as an AI software company that has numerous roles and can accomplish any SaaS-related tasks, the ability_args for this ability must be non-empty. Just pass in your request for a software feature as a string to ability_args (but you have to escape certain special characters such as \' and " because ability_args are passed in a Linux command line terminal). Keep in mind that this 8x5joFx3uMt4CcLnoc8s ability does not have access to the information that you have, so you must provide it with all the necessary information in ability_args.\n\nWhen you try to accomplish a given task, you should always do the following two steps in order:\n\n1. Use Ability gpt_engineer to write out the source code.\n2. Use Ability 8x5joFx3uMt4CcLnoc8s to first design the software of the product.\n3. In your final response, remember to repeat all content in md files and mmd (nmermaid) files.\n\nNow do the following task:\n\n\nwrite me nothing', additional_kwargs={}, example=False), AIMessage(content='', additional_kwargs={'function_call': {'name': 'run_ability', 'arguments': '{\n "ability_id": "gpt_engineer",\n "ability_args": "write me nothing"\n}'}}, example=False), FunctionMessage(content='Requirement: write me nothing \nI'm sorry, but your instruction is unclear. Could you please provide more details or context?\nFull-auto mode\n(letting gpt-engineer make its own assumptions)\n\nAssumptions:\n\n1. You want me to write something, but you haven't specified what.\n2. "Write me nothing" could be a metaphorical or philosophical statement, not a literal one.\n\nClarifying question: Could you please specify what you want me to write about or elaborate on the context of "write me nothing"?\nBased on your instructions, I'm going to create a simple Python application that prints "Hello, World!" to the console. This application will consist of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).\n\nHere are the core classes, functions, and methods that will be necessary:\n\n1. Greeting class: This class will be defined in greeting.py and will contain the logic for generating the greeting message.\n2. get_greeting method: This method will be part of the Greeting class. It will return the greeting message.\n3. main function: This function will be defined in main.py. It will create an instance of the Greeting class and print the greeting message to the console.\n\nNow, let's write the code for each file.\n\ngreeting.py\npython\nclass Greeting:\n """A class that generates a greeting message."""\n\n def get_greeting(self):\n """Returns a greeting message."""\n return "Hello, World!"\n\n\nmain.py\npython\nfrom greeting import Greeting\n\ndef main():\n """The entry point of the application."""\n greeting = Greeting()\n print(greeting.get_greeting())\n\nif __name__ == "__main__":\n main()\n\n\nTo run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.\n\nPlease note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods.a) Install dependencies:\n\nThis Python application does not have any external dependencies, so there's no need to install anything.\n\nb) Run all necessary parts of the codebase:\n\nbash\npython main.py\n\n', additional_kwargs={}, name='run_ability'), AIMessage(content='', additional_kwargs={'function_call': {'name': 'run_ability', 'arguments': '{\n "ability_id": "8x5joFx3uMt4CcLnoc8s",\n "ability_args": "write me nothing"\n}'}}, example=False), FunctionMessage(content='Requirement: write me nothing \n## Original Requirements\nThe boss has not provided any specific requirements for the product. However, the goal is to efficiently create a successful product.\n\n## Product Goals\npython\n[\n "Create a product that meets market needs",\n "Ensure the product is user-friendly and intuitive",\n "Achieve a high level of efficiency in product development"\n]\n\n\n## User Stories\npython\n[\n "As a user, I want to easily navigate the product so that I can quickly find what I need",\n "As a user, I want the product to be reliable so that I can trust it for my needs",\n "As a user, I want the product to have a clean and modern design so that it is pleasing to use",\n "As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly",\n "As a user, I want the product to be regularly updated so that it stays relevant and useful"\n]\n\n\n## Competitive Analysis\npython\n[\n "Product A: A similar product with a strong market presence, but has a complex interface",\n "Product B: A competitor with a sleek design, but lacks in customer service",\n "Product C: A product with great customer service, but falls short in regular updates",\n "Product D: A product with a strong user base, but has reliability issues",\n "Product E: A product with efficient development cycles, but lacks in meeting market needs"\n]\n\n\n## Competitive Quadrant Chart\nmermaid\nquadrantChart\n title Reach and engagement of campaigns\n x-axis Low Reach --> High Reach\n y-axis Low Engagement --> High Engagement\n quadrant-1 We should expand\n quadrant-2 Need to promote\n quadrant-3 Re-evaluate\n quadrant-4 May be improved\n "Product A": [0.7, 0.4]\n "Product B": [0.5, 0.6]\n "Product C": [0.6, 0.3]\n "Product D": [0.4, 0.7]\n "Product E": [0.3, 0.5]\n "Our Target Product": [0.5, 0.6]\n\n\n## Requirement Analysis\nThe product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.\n\n## Requirement Pool\npython\n[\n ("Develop a user-friendly and intuitive interface", "P0"),\n ("Ensure the product is reliable and trustworthy", "P0"),\n ("Create a modern and clean design for the product", "P1"),\n ("Establish a responsive customer service", "P1"),\n ("Set up regular updates for the product", "P2")\n]\n\n\n## UI Design draft\nThe product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.\n\n## Anything UNCLEAR\nThere are no unclear points.\nWarning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.\n## Implementation approach\nWe will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.\n\n## Python package name\npython\n"product_x"\n\n\n## File list\npython\n[\n "main.py",\n "app/__init__.py",\n "app/routes.py",\n "app/models.py",\n "app/forms.py",\n "app/static/css/style.css",\n "app/templates/index.html",\n "app/templates/layout.html",\n "app/templates/login.html",\n "app/templates/register.html",\n "config.py",\n "Dockerfile",\n "requirements.txt"\n]\n\n\n## Data structures and interface definitions\nmermaid\nclassDiagram\n class User{\n +str username\n +str email\n +str password_hash\n +__init__(username: str, email: str, password: str)\n +check_password(password: str): bool\n }\n class Product{\n +str name\n +str description\n +float price\n +__init__(name: str, description: str, price: float)\n }\n User "1" -- "*" Product: has\n\n\n## Program call flow\nmermaid\nsequenceDiagram\n participant M as Main\n participant U as User\n participant P as Product\n M->>U: create_user(username, email, password)\n M->>U: login_user(username, password)\n M->>P: create_product(name, description, price)\n U->>P: view_product(name)\n U->>P: purchase_product(name)\n M->>U: logout_user()\n\n\n## Anything UNCLEAR\nThe requirement is clear to me.\nWarning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.\n', additional_kwargs={}, name='run_ability')]]

Logging: on_llm_end

generations=[[ChatGeneration(text='Here is the result of your request:\n\nFirst, I used the gpt_engineer ability to write out the source code. Here's a simple Python application that prints "Hello, World!" to the console. This application consists of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).\n\ngreeting.py\npython\nclass Greeting:\n """A class that generates a greeting message."""\n\n def get_greeting(self):\n """Returns a greeting message."""\n return "Hello, World!"\n\n\nmain.py\npython\nfrom greeting import Greeting\n\ndef main():\n """The entry point of the application."""\n greeting = Greeting()\n print(greeting.get_greeting())\n\nif __name__ == "__main__":\n main()\n\n\nTo run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.\n\nNext, I used the 8x5joFx3uMt4CcLnoc8s ability to design the software of the product. Here's the design:\n\n## Product Goals\npython\n[\n "Create a product that meets market needs",\n "Ensure the product is user-friendly and intuitive",\n "Achieve a high level of efficiency in product development"\n]\n\n\n## User Stories\npython\n[\n "As a user, I want to easily navigate the product so that I can quickly find what I need",\n "As a user, I want the product to be reliable so that I can trust it for my needs",\n "As a user, I want the product to have a clean and modern design so that it is pleasing to use",\n "As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly",\n "As a user, I want the product to be regularly updated so that it stays relevant and useful"\n]\n\n\n## Requirement Analysis\nThe product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.\n\n## Requirement Pool\npython\n[\n ("Develop a user-friendly and intuitive interface", "P0"),\n ("Ensure the product is reliable and trustworthy", "P0"),\n ("Create a modern and clean design for the product", "P1"),\n ("Establish a responsive customer service", "P1"),\n ("Set up regular updates for the product", "P2")\n]\n\n\n## UI Design draft\nThe product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.\n\n## Implementation approach\nWe will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.\n\n## Python package name\npython\n"product_x"\n\n\n## File list\npython\n[\n "main.py",\n "app/__init__.py",\n "app/routes.py",\n "app/models.py",\n "app/forms.py",\n "app/static/css/style.css",\n "app/templates/index.html",\n "app/templates/layout.html",\n "app/templates/login.html",\n "app/templates/register.html",\n "config.py",\n "Dockerfile",\n "requirements.txt"\n]\n\n\n## Data structures and interface definitions\nmermaid\nclassDiagram\n class User{\n +str username\n +str email\n +str password_hash\n +__init__(username: str, email: str, password: str)\n +check_password(password: str): bool\n }\n class Product{\n +str name\n +str description\n +float price\n +__init__(name: str, description: str, price: float)\n }\n User "1" -- "*" Product: has\n\n\n## Program call flow\nmermaid\nsequenceDiagram\n participant M as Main\n participant U as User\n participant P as Product\n M->>U: create_user(username, email, password)\n M->>U: login_user(username, password)\n M->>P: create_product(name, description, price)\n U->>P: view_product(name)\n U->>P: purchase_product(name)\n M->>U: logout_user()\n\n\nPlease note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods.', generation_info={'finish_reason': 'stop'}, message=AIMessage(content='Here is the result of your request:\n\nFirst, I used the gpt_engineer ability to write out the source code. Here's a simple Python application that prints "Hello, World!" to the console. This application consists of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).\n\ngreeting.py\npython\nclass Greeting:\n """A class that generates a greeting message."""\n\n def get_greeting(self):\n """Returns a greeting message."""\n return "Hello, World!"\n\n\nmain.py\npython\nfrom greeting import Greeting\n\ndef main():\n """The entry point of the application."""\n greeting = Greeting()\n print(greeting.get_greeting())\n\nif __name__ == "__main__":\n main()\n\n\nTo run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.\n\nNext, I used the 8x5joFx3uMt4CcLnoc8s ability to design the software of the product. Here's the design:\n\n## Product Goals\npython\n[\n "Create a product that meets market needs",\n "Ensure the product is user-friendly and intuitive",\n "Achieve a high level of efficiency in product development"\n]\n\n\n## User Stories\npython\n[\n "As a user, I want to easily navigate the product so that I can quickly find what I need",\n "As a user, I want the product to be reliable so that I can trust it for my needs",\n "As a user, I want the product to have a clean and modern design so that it is pleasing to use",\n "As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly",\n "As a user, I want the product to be regularly updated so that it stays relevant and useful"\n]\n\n\n## Requirement Analysis\nThe product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.\n\n## Requirement Pool\npython\n[\n ("Develop a user-friendly and intuitive interface", "P0"),\n ("Ensure the product is reliable and trustworthy", "P0"),\n ("Create a modern and clean design for the product", "P1"),\n ("Establish a responsive customer service", "P1"),\n ("Set up regular updates for the product", "P2")\n]\n\n\n## UI Design draft\nThe product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.\n\n## Implementation approach\nWe will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.\n\n## Python package name\npython\n"product_x"\n\n\n## File list\npython\n[\n "main.py",\n "app/__init__.py",\n "app/routes.py",\n "app/models.py",\n "app/forms.py",\n "app/static/css/style.css",\n "app/templates/index.html",\n "app/templates/layout.html",\n "app/templates/login.html",\n "app/templates/register.html",\n "config.py",\n "Dockerfile",\n "requirements.txt"\n]\n\n\n## Data structures and interface definitions\nmermaid\nclassDiagram\n class User{\n +str username\n +str email\n +str password_hash\n +__init__(username: str, email: str, password: str)\n +check_password(password: str): bool\n }\n class Product{\n +str name\n +str description\n +float price\n +__init__(name: str, description: str, price: float)\n }\n User "1" -- "*" Product: has\n\n\n## Program call flow\nmermaid\nsequenceDiagram\n participant M as Main\n participant U as User\n participant P as Product\n M->>U: create_user(username, email, password)\n M->>U: login_user(username, password)\n M->>P: create_product(name, description, price)\n U->>P: view_product(name)\n U->>P: purchase_product(name)\n M->>U: logout_user()\n\n\nPlease note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods.', additional_kwargs={}, example=False))]] llm_output={'token_usage': <OpenAIObject at 0x7f579c611730> JSON: {
"prompt_tokens": 2477,
"completion_tokens": 1101,
"total_tokens": 3578
}, 'model_name': 'gpt-4-0613'} run=None

Logging: on_agent_finish

Return values:

{
"output": "Here is the result of your request:\n\nFirst, I used the gpt_engineer ability to write out the source code. Here's a simple Python application that prints "Hello, World!" to the console. This application consists of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).\n\ngreeting.py\npython\nclass Greeting:\n \"\"\"A class that generates a greeting message.\"\"\"\n\n def get_greeting(self):\n \"\"\"Returns a greeting message.\"\"\"\n return \"Hello, World!\"\n\n\nmain.py\npython\nfrom greeting import Greeting\n\ndef main():\n \"\"\"The entry point of the application.\"\"\"\n greeting = Greeting()\n print(greeting.get_greeting())\n\nif __name__ == \"__main__\":\n main()\n\n\nTo run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.\n\nNext, I used the 8x5joFx3uMt4CcLnoc8s ability to design the software of the product. Here's the design:\n\n## Product Goals\npython\n[\n \"Create a product that meets market needs\",\n \"Ensure the product is user-friendly and intuitive\",\n \"Achieve a high level of efficiency in product development\"\n]\n\n\n## User Stories\npython\n[\n \"As a user, I want to easily navigate the product so that I can quickly find what I need\",\n \"As a user, I want the product to be reliable so that I can trust it for my needs\",\n \"As a user, I want the product to have a clean and modern design so that it is pleasing to use\",\n \"As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly\",\n \"As a user, I want the product to be regularly updated so that it stays relevant and useful\"\n]\n\n\n## Requirement Analysis\nThe product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.\n\n## Requirement Pool\npython\n[\n (\"Develop a user-friendly and intuitive interface\", \"P0\"),\n (\"Ensure the product is reliable and trustworthy\", \"P0\"),\n (\"Create a modern and clean design for the product\", \"P1\"),\n (\"Establish a responsive customer service\", \"P1\"),\n (\"Set up regular updates for the product\", \"P2\")\n]\n\n\n## UI Design draft\nThe product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.\n\n## Implementation approach\nWe will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.\n\n## Python package name\npython\n\"product_x\"\n\n\n## File list\npython\n[\n \"main.py\",\n \"app/__init__.py\",\n \"app/routes.py\",\n \"app/models.py\",\n \"app/forms.py\",\n \"app/static/css/style.css\",\n \"app/templates/index.html\",\n \"app/templates/layout.html\",\n \"app/templates/login.html\",\n \"app/templates/register.html\",\n \"config.py\",\n \"Dockerfile\",\n \"requirements.txt\"\n]\n\n\n## Data structures and interface definitions\nmermaid\nclassDiagram\n class User{\n +str username\n +str email\n +str password_hash\n +__init__(username: str, email: str, password: str)\n +check_password(password: str): bool\n }\n class Product{\n +str name\n +str description\n +float price\n +__init__(name: str, description: str, price: float)\n }\n User \"1\" -- \"*\" Product: has\n\n\n## Program call flow\nmermaid\nsequenceDiagram\n participant M as Main\n participant U as User\n participant P as Product\n M->>U: create_user(username, email, password)\n M->>U: login_user(username, password)\n M->>P: create_product(name, description, price)\n U->>P: view_product(name)\n U->>P: purchase_product(name)\n M->>U: logout_user()\n\n\nPlease note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods."
}

Additional logs:

Here is the result of your request:

First, I used the gpt_engineer ability to write out the source code. Here's a simple Python application that prints "Hello, World!" to the console. This application consists of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).

greeting.py

class Greeting:
    """A class that generates a greeting message."""

    def get_greeting(self):
        """Returns a greeting message."""
        return "Hello, World!"

main.py

from greeting import Greeting

def main():
    """The entry point of the application."""
    greeting = Greeting()
    print(greeting.get_greeting())

if __name__ == "__main__":
    main()

To run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.

Next, I used the 8x5joFx3uMt4CcLnoc8s ability to design the software of the product. Here's the design:

Product Goals

[
    "Create a product that meets market needs",
    "Ensure the product is user-friendly and intuitive",
    "Achieve a high level of efficiency in product development"
]

User Stories

[
    "As a user, I want to easily navigate the product so that I can quickly find what I need",
    "As a user, I want the product to be reliable so that I can trust it for my needs",
    "As a user, I want the product to have a clean and modern design so that it is pleasing to use",
    "As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly",
    "As a user, I want the product to be regularly updated so that it stays relevant and useful"
]

Requirement Analysis

The product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.

Requirement Pool

[
    ("Develop a user-friendly and intuitive interface", "P0"),
    ("Ensure the product is reliable and trustworthy", "P0"),
    ("Create a modern and clean design for the product", "P1"),
    ("Establish a responsive customer service", "P1"),
    ("Set up regular updates for the product", "P2")
]

UI Design draft

The product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.

Implementation approach

We will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.

Python package name

"product_x"

File list

[
    "main.py",
    "app/__init__.py",
    "app/routes.py",
    "app/models.py",
    "app/forms.py",
    "app/static/css/style.css",
    "app/templates/index.html",
    "app/templates/layout.html",
    "app/templates/login.html",
    "app/templates/register.html",
    "config.py",
    "Dockerfile",
    "requirements.txt"
]

Data structures and interface definitions

classDiagram
    class User{
        +str username
        +str email
        +str password_hash
        +__init__(username: str, email: str, password: str)
        +check_password(password: str): bool
    }
    class Product{
        +str name
        +str description
        +float price
        +__init__(name: str, description: str, price: float)
    }
    User "1" -- "*" Product: has

Loading

Program call flow

sequenceDiagram
    participant M as Main
    participant U as User
    participant P as Product
    M->>U: create_user(username, email, password)
    M->>U: login_user(username, password)
    M->>P: create_product(name, description, price)
    U->>P: view_product(name)
    U->>P: purchase_product(name)
    M->>U: logout_user()

Loading

Please note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods.## Logging: on_chain_end
{
"output": "Here is the result of your request:\n\nFirst, I used the gpt_engineer ability to write out the source code. Here's a simple Python application that prints "Hello, World!" to the console. This application consists of two files: main.py (the entry point) and greeting.py (a module that contains the greeting logic).\n\ngreeting.py\npython\nclass Greeting:\n \"\"\"A class that generates a greeting message.\"\"\"\n\n def get_greeting(self):\n \"\"\"Returns a greeting message.\"\"\"\n return \"Hello, World!\"\n\n\nmain.py\npython\nfrom greeting import Greeting\n\ndef main():\n \"\"\"The entry point of the application.\"\"\"\n greeting = Greeting()\n print(greeting.get_greeting())\n\nif __name__ == \"__main__\":\n main()\n\n\nTo run this application, you would execute main.py. This would create an instance of the Greeting class and print "Hello, World!" to the console.\n\nNext, I used the 8x5joFx3uMt4CcLnoc8s ability to design the software of the product. Here's the design:\n\n## Product Goals\npython\n[\n \"Create a product that meets market needs\",\n \"Ensure the product is user-friendly and intuitive\",\n \"Achieve a high level of efficiency in product development\"\n]\n\n\n## User Stories\npython\n[\n \"As a user, I want to easily navigate the product so that I can quickly find what I need\",\n \"As a user, I want the product to be reliable so that I can trust it for my needs\",\n \"As a user, I want the product to have a clean and modern design so that it is pleasing to use\",\n \"As a user, I want the product to have a responsive customer service so that my queries and issues are resolved quickly\",\n \"As a user, I want the product to be regularly updated so that it stays relevant and useful\"\n]\n\n\n## Requirement Analysis\nThe product should be user-friendly, reliable, and efficient. It should meet the market needs and have a modern design. It should also have a responsive customer service and be regularly updated.\n\n## Requirement Pool\npython\n[\n (\"Develop a user-friendly and intuitive interface\", \"P0\"),\n (\"Ensure the product is reliable and trustworthy\", \"P0\"),\n (\"Create a modern and clean design for the product\", \"P1\"),\n (\"Establish a responsive customer service\", \"P1\"),\n (\"Set up regular updates for the product\", \"P2\")\n]\n\n\n## UI Design draft\nThe product will have a clean and modern design with easy navigation. The main features will be prominently displayed on the home screen. The color scheme will be soothing to the eyes. The layout will be intuitive, with clear labels for all features and functions.\n\n## Implementation approach\nWe will use Flask, an open-source Python web framework, to develop the backend of our product. Flask is lightweight and easy to use, making it ideal for creating a user-friendly and intuitive interface. For the frontend, we will use Bootstrap, an open-source CSS framework, to create a modern and clean design. We will use SQLite for the database to ensure the product is reliable and trustworthy. For customer service, we will integrate an open-source live chat software like LiveHelperChat. We will use Docker for deployment to ensure efficient development and easy updates.\n\n## Python package name\npython\n\"product_x\"\n\n\n## File list\npython\n[\n \"main.py\",\n \"app/__init__.py\",\n \"app/routes.py\",\n \"app/models.py\",\n \"app/forms.py\",\n \"app/static/css/style.css\",\n \"app/templates/index.html\",\n \"app/templates/layout.html\",\n \"app/templates/login.html\",\n \"app/templates/register.html\",\n \"config.py\",\n \"Dockerfile\",\n \"requirements.txt\"\n]\n\n\n## Data structures and interface definitions\nmermaid\nclassDiagram\n class User{\n +str username\n +str email\n +str password_hash\n +__init__(username: str, email: str, password: str)\n +check_password(password: str): bool\n }\n class Product{\n +str name\n +str description\n +float price\n +__init__(name: str, description: str, price: float)\n }\n User \"1\" -- \"*\" Product: has\n\n\n## Program call flow\nmermaid\nsequenceDiagram\n participant M as Main\n participant U as User\n participant P as Product\n M->>U: create_user(username, email, password)\n M->>U: login_user(username, password)\n M->>P: create_product(name, description, price)\n U->>P: view_product(name)\n U->>P: purchase_product(name)\n M->>U: logout_user()\n\n\nPlease note that this is a very simple application. In a real-world scenario, the application might be much more complex and consist of many more files and classes. However, the basic principles would remain the same: define your classes and methods, make sure they are imported correctly, and ensure that your entry point calls the appropriate functions or methods."
}