[Doc] Add developer notes

CONTRIBUTING.md

@@ -4,6 +4,75 @@ This Project welcomes contributions, suggestions, and feedback. All contribution
 
 The Project abides by the Organization's [code of conduct](https://github.com/guidance-ai/governance/blob/main/CODE-OF-CONDUCT.md) and [trademark policy](https://github.com/guidance-ai/governance/blob/main/TRADEMARKS.md).
 
+# Development Notes
+
+We welcome contributions to `guidance`, and this document exists to provide useful information contributors.
+
+## Developer Setup
+
+The quickest way to get started is to run (in a fresh environment):
+```bash
+pip install -e .[all,test]
+```
+which should bring in all of the basic required dependencies.
+Note that if you want to use GPU acceleration, then you will need to do whatever is required to allow `torch` and `llama-cpp` to access your GPU too.
+
+There are sometimes difficulties configuring Rust during the pip installs.
+If you encounter such issues, then one work around (if you use Anaconda) is to create your environment along the lines of
+```bash
+conda create -n guidance-312 python=3.12 rust
+```
+In our experience, this has been a little more reliable.
+Similarly, to get GPU support, we have found that (after activating the environment) running
+```bash
+conda install pytorch pytorch-cuda=12.1 -c pytorch -c nvidia
+```
+works best.
+However, if you have your own means of installing Rust and CUDA, you should be able to continue using those.
+
+## Running Tests
+
+Because we run tests on GPU-equipped machines and also tests which call LLM endpoints, approval is required before our GitHub workflows will run on external Pull Requests.
+To run a basic test suite locally, we suggest:
+```bash
+python -m pytest -m "not (needs_credentials or use_gpu or server)" ./tests/
+```
+which runs our basic test suite.
+Where an LLM is required, this will default to using GPT2 on the CPU.
+To change that default, run
+```bash
+python -m pytest -m "not (needs_credentials or use_gpu or server)" --selected_model <MODELNAME> ./tests/
+```
+where `<MODELNAME>` is taken from the `AVAILABLE_MODELS` dictionary defined in `conftest.py`.
+
+## Adding LLMs to the test matrix
+
+Our tests run on a variety of LLMs.
+These fall into three categories: CPU-based, GPU-based and endpoint-based (which need credentials).
+
+### New CPU or GPU-based models
+
+Due to the limited resources of the regular GitHub runner machines, the LLM under test is a dimension of our test matrix (otherwise the GitHub runners will tend to run out of RAM and/or hard drive space).
+New models should be configured in the `AVAILABLE_MODELS` dictionary in `conftest.py`, and then that key added to the `model` list in `unit_tests.yml` or `unit_tests_gpu.yml` as appropriate.
+The model will then be available via the `selected_model` fixture for all tests.
+If you have a test which should only run for particular models, you can use the `selected_model_name` fixture to check, and call `pytest.skip()` if necessary.
+An example of this is given in `test_llama_cpp.py`.
+
+### New endpoint based models
+
+If your model requires credentials, then those will need to be added to our GitHub repository as secrets.
+The endpoint itself (and any other required information) should be configured as environment variables too.
+When the test runs, the environment variables will be set, and can then be used to configure the model as required.
+See `test_azureai_openai.py` for examples of this being done.
+The tests should also be marked as `needs_credentials` - if this is needed for the entire module, then `pytestmark` can be used - see `test_azureai_openai.py` again for this.
+
+The environment variables and secrets will also need to be configured in the `ci_tests.yml` file.
+
+## Linting
+
+We run `black` on our codebase, and plan to turn on enforcement of this in the GitHub workflows soon.
+
+
 ---
 Part of MVG-0.1-beta.
 Made with love by GitHub. Licensed under the [CC-BY 4.0 License](https://creativecommons.org/licenses/by-sa/4.0/).