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README.md
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# MetaGPT: The Multi-Role Meta Programming Framework
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[English](./README.md) / [中文](./README_CN.md)
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## Objective
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1. Our ultimate goal is to enable GPT to train, fine-tune, and ultimately, utilize itself, aiming to achieve a level of **self-evolution.**
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1. Once GPT can optimize itself, it will have the capacity to continually improve its own performance without the constant need for manual tuning. This kind of self-evolution enables an **autonomous cycle of growth** where the AI can identify areas for its own improvement, make necessary adjustments, and implement those changes to better achieve its objectives. **It could potentially lead to an exponential growth in the system's capabilities.**
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2. Currently, we have managed to enable GPT to work in teams, collaborating to tackle more complex tasks.
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1. For instance, `startup.py` consists of **product manager / architect / project manager / engineer**, it provides the full process of a **software company.**
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2. The team can cooperate and generate **user stories / competetive analysis / requirements / data structures / apis / files etc.**
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### Philosophy
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The core assets of a software company are three: Executable Code, SOP (Standard Operating Procedures), and Team.
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There is a formula:
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```
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Executable Code = SOP(Team)
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```
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We have practiced this process and expressed the SOP in the form of code,
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and the team itself only used large language models.
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## Examples (fully generated by GPT-4)
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1. Each column here is a requirement of using the command `python startup.py <requirement>`.
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2. By default, an investment of three dollars is made for each example and the program stops once this amount is depleted.
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1. It requires around **$0.2** (GPT-4 api's costs) to generate one example with analysis and design.
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2. It requires around **$2.0** (GPT-4 api's costs) to generate one example with a full project.
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| | Design an MLOps/LLMOps framework that supports GPT-4 and other LLMs | Design a game like Candy Crush Saga | Design a RecSys like Toutiao | Design a roguelike game like NetHack | Design a search algorithm framework | Design a minimal pomodoro timer |
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|----------------------|---------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------|---------------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------------|
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| Competitive Analysis |  |  |  |  |  |  |
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| Data & API Design |  |  |  |  |  |  |
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| Sequence Flow |  |  |  |  |  |  |
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## Installation
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```bash
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# Step 1: Ensure that Python 3.9+ is installed on your system. You can check this by using:
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python --version
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# Step 2: Ensure that NPM is installed on your system. You can check this by using:
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npm --version
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# Step 3: Clone the repository to your local machine, and install it.
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git clone https://github.com/geekan/metagpt
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cd metagpt
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python setup.py install
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```
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## Configuration
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- You can configure your `OPENAI_API_KEY` in `config/key.yaml / config/config.yaml / env`
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- Priority order: `config/key.yaml > config/config.yaml > env`
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```bash
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# Copy the configuration file and make the necessary modifications.
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cp config/config.yaml config/key.yaml
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```
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| Variable Name | config/key.yaml | env |
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|--------------------------------------------|-------------------------------------------|--------------------------------|
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| OPENAI_API_KEY # Replace with your own key | OPENAI_API_KEY: "sk-..." | export OPENAI_API_KEY="sk-..." |
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| OPENAI_API_BASE # Optional | OPENAI_API_BASE: "https://<YOUR_SITE>/v1" | export OPENAI_API_BASE="https://<YOUR_SITE>/v1" |
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## Tutorial: Initiating a startup
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```shell
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python startup.py "Write a cli snake game"
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```
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After running the script, you can find your new project in the `workspace/` directory.
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### What's behind? It's a startup fully driven by GPT. You're the investor
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| A software company consists of LLM-based roles (For example only) | A software company's SOP visualization (For example only) |
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|-----------------------------------------------------------------------------------------|-------------------------------------------------------------------|
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|  |  |
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### Code walkthrough
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```python
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from metagpt.software_company import SoftwareCompany
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from metagpt.roles import ProjectManager, ProductManager, Architect, Engineer
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async def startup(idea: str, investment: str = '$3.0', n_round: int = 5):
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"""Run a startup. Be a boss."""
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company = SoftwareCompany()
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company.hire([ProductManager(), Architect(), ProjectManager(), Engineer()])
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company.invest(investment)
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company.start_project(idea)
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await company.run(n_round=n_round)
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```
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## Tutorial: single role and LLM examples
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### The framework support single role as well, here's a simple sales role use case
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```python
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from metagpt.const import DATA_PATH
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from metagpt.document_store import FaissStore
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from metagpt.roles import Sales
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store = FaissStore(DATA_PATH / 'example.pdf')
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role = Sales(profile='Sales', store=store)
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result = await role.run('Which facial cleanser is good for oily skin?')
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```
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### The framework also provide llm interfaces
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```python
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from metagpt.llm import LLM
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llm = LLM()
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await llm.aask('hello world')
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hello_msg = [{'role': 'user', 'content': 'hello'}]
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await llm.acompletion(hello_msg)
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```
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## Contact Information
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If you have any questions or feedback about this project, feel free to reach out to us. We appreciate your input!
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- **Email:** alexanderwu@fuzhi.ai
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- **GitHub Issues:** For more technical issues, you can also create a new issue in our [GitHub repository](https://github.com/geekan/metagpt/issues).
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We aim to respond to all inquiries within 2-3 business days.
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