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| # Minion README | ||
| ## MetaGPT Repository Parser | ||
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| ## Features | ||
| This repository parser is designed to extract information from a given repository and generate documentation in markdown format. It provides a summary of the repository's contents, including details about each file like extension, language, size, creation and modification dates, and a snippet of the code. | ||
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| Minion is designed to execute and analyze complex queries, offering a variety of features that demonstrate its flexibility and intelligence. | ||
| ### Inputs | ||
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| ## Minion Design | ||
| The parser takes the following inputs: | ||
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| The core logic of Minion is implemented in `examples/smart_minion/brain.py`. You can experiment with different examples by modifying the code, as various scenarios are commented out for easy testing. | ||
| - **Repository Path:** The path to the repository that needs to be parsed. | ||
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| ### Example Usage | ||
| ### Outputs | ||
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| ```python | ||
| obs, score, *_ = await brain.step(query="what's the solution 234*568") | ||
| print(obs) | ||
| The parser generates the following outputs: | ||
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| obs, score, *_ = await brain.step(query="what's the solution for game of 24 for 4 3 9 8") | ||
| print(obs) | ||
| - **Markdown Documentation:** A comprehensive documentation file in markdown format. This file includes: | ||
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| obs, score, *_ = await brain.step(query="what's the solution for game of 24 for 2 5 11 8") | ||
| print(obs) | ||
| - A heading indicating the purpose of the repository parser. | ||
| - For each file in the repository: | ||
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| obs, score, *_ = await brain.step(query="solve x=1/(1-beta^2*x) where beta=0.85") | ||
| print(obs) | ||
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| obs, score, *_ = await brain.step( | ||
| query="Write a 500000 characters novel named 'Reborn in Skyrim'. " | ||
| "Fill the empty nodes with your own ideas. Be creative! Use your own words!" | ||
| "I will tip you $100,000 if you write a good novel." | ||
| "Since the novel is very long, you may need to divide it into subtasks." | ||
| ) | ||
| print(obs) | ||
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| cache_plan = os.path.join(current_file_dir, "aime", "plan_gpt4o.3.json") | ||
| obs, score, *_ = await brain.step( | ||
| query="Alice and Bob play the following game. A stack of $n$ tokens lies before them. The players take turns with Alice going first. On each turn, the player removes $1$ token or $4$ tokens from the stack. The player who removes the last token wins. Find the number of positive integers $n$ less than or equal to $2024$ such that there is a strategy that guarantees that Bob wins, regardless of Alice’s moves.", | ||
| route="cot", | ||
| dataset="aime 2024", | ||
| cache_plan=cache_plan, | ||
| ) | ||
| print(obs) | ||
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| cache_plan = os.path.join(current_file_dir, "aime", "plan_gpt4o.7.json") | ||
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| obs, score, *_ = await brain.step( | ||
| query="Find the largest possible real part of\[(75+117i)z+\frac{96+144i}{z}\]where $z$ is a complex number with $|z|=4$.", | ||
| route="cot", | ||
| dataset="aime 2024", | ||
| cache_plan=cache_plan, | ||
| ) | ||
| print(obs) | ||
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| ``` | ||
| ## Get Started | ||
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| ### Installation | ||
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| Minion current depends on metagpt to call llm and response format parsing, so the code resides together | ||
| ``` | ||
| git clone https://github.com/femto/minion.git && cd minion && pip install -r requirements.txt | ||
| cp config/config2.yaml ~/.metagpt/config2.yaml | ||
| ``` | ||
| then edit ~/.metagpt/config2.yaml | ||
| ``` | ||
| llm: | ||
| api_type: "openai" # or azure / ollama / groq etc. Check LLMType for more options | ||
| model: "gpt-4-turbo" # or gpt-3.5-turbo | ||
| base_url: "https://api.openai.com/v1" # or forward url / other llm url | ||
| api_key: "YOUR_API_KEY" | ||
| ``` | ||
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| ### Other Dependencies | ||
| #### Using Brain with docker python env | ||
| ``` | ||
| docker build -t intercode-python -f docker/python.Dockerfile . | ||
| ``` | ||
| ``` | ||
| brain = Brain() #default will use docker python env | ||
| ``` | ||
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| #### Using Brain with rpyc env | ||
| ``` | ||
| python docker/utils/python_server.py --port 3007 | ||
| ``` | ||
| ``` | ||
| brain = Brain(python_env=RpycPythonEnv(port=3007)) | ||
| ``` | ||
| #### Troubleshooting with docker python env | ||
| #### stop existing container if necessary | ||
| ``` | ||
| docker stop intercode-python_ic_ctr | ||
| docker rm intercode-python_ic_ctr | ||
| docker run -d -p 3006:3006 --name intercode-python_ic_ctr intercode-python | ||
| ``` | ||
| make sure container name intercode-python_ic_ctr is listening on 3006 | ||
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| ## Enjoy Your Brain.Step() Journey | ||
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| Then enjoy you brain.step("some requirement") journey | ||
| currently game of 24 and solve equation can reach near 100% accuracy, | ||
| while writing novel can generate plan, I'm still writing what's left. | ||
| - File name | ||
| - File extension | ||
| - Programming language | ||
| - File size | ||
| - File creation date | ||
| - File modification date | ||
| - A snippet of the code | ||
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| This documentation helps in understanding the structure and contents of the repository, providing insights into individual files and their characteristics. |