Quickstart¶

This page explains the shortest path to run GitHelp locally.

The recommended way to use GitHelp is the Streamlit interface. The command-line scripts remain available for debugging and development.

1. Install the project¶

From the root of the GitHelp repository:

python -m pip install -e .

If you use the local Qwen provider, make sure the LLM dependencies are installed:

python -m pip install transformers torch accelerate

If Streamlit is not already installed:

python -m pip install streamlit

2. Launch the Streamlit app¶

From the root of the githelp repository:

streamlit run app/streamlit_app.py

The interface opens locally, usually at:

http://localhost:8501/

3. Select a project¶

In the Streamlit interface, use the Project setup section.

For the MMORE use case, either enter the local path to the MMORE repository:

/Users/<user>/path/to/mmore

or select the GitHub repository option and enter:

https://github.com/swiss-ai/mmore

For GitHub URLs, GitHelp clones the repository into data/repositories/ and then runs the same corpus, indexing, retrieval, and RAG pipeline on that local copy.

4. Build the corpus¶

Click one of the index build buttons:

Build simple index
Build MMORE index

GitHelp generates a dedicated project folder:

data/projects/<project_name>/

For MMORE, this creates for example:

data/projects/mmore/project_config.yaml
data/projects/mmore/corpus.jsonl

The generated corpus can include:

Markdown and reStructuredText documentation;
Python docstrings and signatures extracted with ast;
YAML configuration files;
a synthetic repository structure document.

5. Ask questions¶

After the corpus is built, use the Ask questions section.

Choose an indexing mode¶

GitHelp supports two indexing modes.

Simple index¶

The simple index builds a GitHelp JSONL corpus and uses the local simple retriever.

Use it when:

you want a quick setup;
you are debugging corpus extraction;
MMORE is not installed or not configured.

MMORE index¶

The MMORE index is the recommended mode for better retrieval quality.

It builds the GitHelp corpus, exports it to MMORE format, and builds the MMORE index.

Use it when:

MMORE is installed;
you want to use the main retrieval backend;
the project is ready to be indexed.

After building the MMORE index, select:

Retrieval backend: mmore

The simple backend remains available for debugging or quick corpus checks.

Example questions:

How do I configure indexing?
Which Milvus parameters are used in the ColPali config?
Where are the example configs located?

6. Inspect sources¶

By default, GitHelp displays retrieved sources under the answer.

The sidebar options let you:

show or hide retrieved sources;
show full source content;
show debug information;
switch between simple and mmore retrieval;
enable or disable LLM generation.

7. Persistent app state¶

GitHelp stores the last selected project and UI settings in:

data/app_state.json

This allows the interface to restore the previous project, corpus path, backend, and display options after closing and reopening Streamlit.

This file is local state and should normally not be committed.

8. Optional: command-line corpus build¶

The default command still works:

python scripts/build_corpus.py

It reads:

configs/project_config.yaml

and writes:

data/processed/corpus.jsonl

You can also build a project-specific corpus manually:

python scripts/build_corpus.py \
  --config data/projects/mmore/project_config.yaml \
  --output-path data/projects/mmore/corpus.jsonl

9. Optional: MMORE indexing¶

The mmore backend retrieves from an MMORE index. Building a corpus alone is not enough to update that index.

For a full MMORE-backed workflow, the steps are:

build_corpus.py
→ export_mmore_corpus.py
→ build_index.py
→ ask with backend mmore

For local development and newly built corpora, use the simple backend first.