The GenerateREADME patchflow aims to automatically generate documentation for a folder in your repository in form of a file.

How to run?

You can run it as follows:

patchwork GenerateREADME folder_path=/path/to/your/folder

by default you will need to provide the openai_api_key and the github_api_key you can pass them as arguments:

patchwork GenerateREADME openai_api_key=<Your_API_KEY> github_api_key=<Your_GH_Token> folder_path=/path/to/your/folder

What it does?

The GenerateREADME patchflow will first convert the folder into a markdown file using an open-source tool code2prompt. It will then use the file to create a prompt to be sent to gpt-3.5-turbo to generate a file. You can check the default prompt template. The generated file is then committed to the repository under a new branch and finally a pull request is created for the user to review and merge the changes.


The following are the default configurations that can be modified by the user to adapt the GenerateREADME patchflow to their needs. All the options can be set both via CLI arguments and and the yaml config file.


You can choose any LLM API as long as it has an OpenAI API compatible chat completions endpoint. Just update the default values of the following options:

- model: gpt-3.5-turbo
- client_base_url:

E.g. to use Meta’s CodeLlama model from HuggingFace you can set:

model: codellama/CodeLlama-70b-Instruct-hf
model_temperature: 0.2
model_top_p: 0.95
model_max_tokens: 2000

and pass your HuggingFace token in the openai_api_key option.

You can also use llama.cpp to run inference on CPU locally. Just install the llama-cpp-python package and run their OpenAI compatible web server as described here with the command:

python3 -m llama_cpp.server --hf_model_repo_id TheBloke/deepseek-coder-6.7B-instruct-GGUF --model 'deepseek-coder-6.7b-instruct.Q4_0.gguf'

Once the local server is running you can set:

client_base_url: http://localhost:8000/v1
model: TheBloke/deepseek-coder-6.7B-instruct-GGUF
model_temperature: 0.2
model_top_p: 0.95
model_max_tokens: 1000

and use the local model for inference.


You can restrict the kind of files to use for generating the documentation using the filter option.

filter: *.py

Suppress comments

If you do not want the comments in the file to be included set the suppress_comments option.

suppress_comments: false

Manage PRs

In addition, there are options to let you manage the PRs as you like, by setting a branch_prefix, or disabling the creation of new branches with disable_branch (commits will be made on the current branch). You can also disable PR creation with disable_pr or force push commits to existing PR with force_pr_creation.

branch_prefix: Generated-README
disable_branch: false
disable_pr: false
force_pr_creation: false

Prompt template

You can update the default prompt template. Note the use of variable {{fullContent}}. It is generated by the steps within the GenerateREADME patchflow and replaced by the actual value during the execution. The expected output response is complete content of the file with the documentation.


Here are some example PRs generated with the GenerateREADME patchflow: