refactor(test): introduce --stack-config and simplify options (#1404)

You now run the integration tests with these options:

```bash
Custom options:
  --stack-config=STACK_CONFIG
                        a 'pointer' to the stack. this can be either be:
                        (a) a template name like `fireworks`, or
                        (b) a path to a run.yaml file, or
                        (c) an adhoc config spec, e.g.
                        `inference=fireworks,safety=llama-guard,agents=meta-
                        reference`
  --env=ENV             Set environment variables, e.g. --env KEY=value
  --text-model=TEXT_MODEL
                        comma-separated list of text models. Fixture name:
                        text_model_id
  --vision-model=VISION_MODEL
                        comma-separated list of vision models. Fixture name:
                        vision_model_id
  --embedding-model=EMBEDDING_MODEL
                        comma-separated list of embedding models. Fixture name:
                        embedding_model_id
  --safety-shield=SAFETY_SHIELD
                        comma-separated list of safety shields. Fixture name:
                        shield_id
  --judge-model=JUDGE_MODEL
                        comma-separated list of judge models. Fixture name:
                        judge_model_id
  --embedding-dimension=EMBEDDING_DIMENSION
                        Output dimensionality of the embedding model to use for
                        testing. Default: 384
  --record-responses    Record new API responses instead of using cached ones.
  --report=REPORT       Path where the test report should be written, e.g.
                        --report=/path/to/report.md

```

Importantly, if you don't specify any of the models (text-model,
vision-model, etc.) the relevant tests will get **skipped!**

This will make running tests somewhat more annoying since all options
will need to be specified. We will make this easier by adding some easy
wrapper yaml configs.

## Test Plan

Example:

```bash
ashwin@ashwin-mbp ~/local/llama-stack/tests/integration (unify_tests) $ 
LLAMA_STACK_CONFIG=fireworks pytest -s -v inference/test_text_inference.py \
   --text-model meta-llama/Llama-3.2-3B-Instruct 
```
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# Llama Stack Integration Tests
You can run llama stack integration tests on either a Llama Stack Library or a Llama Stack endpoint.
To test on a Llama Stack library with certain configuration, run
We use `pytest` for parameterizing and running tests. You can see all options with:
```bash
LLAMA_STACK_CONFIG=./llama_stack/templates/cerebras/run.yaml pytest -s -v tests/api/inference/
```
or just the template name
```bash
LLAMA_STACK_CONFIG=together pytest -s -v tests/api/inference/
cd tests/integration
# this will show a long list of options, look for "Custom options:"
pytest --help
```
To test on a Llama Stack endpoint, run
Here are the most important options:
- `--stack-config`: specify the stack config to use. You have three ways to point to a stack:
- a URL which points to a Llama Stack distribution server
- a template (e.g., `fireworks`, `together`) or a path to a run.yaml file
- a comma-separated list of api=provider pairs, e.g. `inference=fireworks,safety=llama-guard,agents=meta-reference`. This is most useful for testing a single API surface.
- `--env`: set environment variables, e.g. --env KEY=value. this is a utility option to set environment variables required by various providers.
Model parameters can be influenced by the following options:
- `--text-model`: comma-separated list of text models.
- `--vision-model`: comma-separated list of vision models.
- `--embedding-model`: comma-separated list of embedding models.
- `--safety-shield`: comma-separated list of safety shields.
- `--judge-model`: comma-separated list of judge models.
- `--embedding-dimension`: output dimensionality of the embedding model to use for testing. Default: 384
Each of these are comma-separated lists and can be used to generate multiple parameter combinations.
Experimental, under development, options:
- `--record-responses`: record new API responses instead of using cached ones
- `--report`: path where the test report should be written, e.g. --report=/path/to/report.md
## Examples
Run all text inference tests with the `together` distribution:
```bash
LLAMA_STACK_BASE_URL=http://localhost:8089 pytest -s -v tests/api/inference
pytest -s -v tests/api/inference/test_text_inference.py \
--stack-config=together \
--text-model=meta-llama/Llama-3.1-8B-Instruct
```
## Report Generation
Run all text inference tests with the `together` distribution and `meta-llama/Llama-3.1-8B-Instruct`:
To generate a report, run with `--report` option
```bash
LLAMA_STACK_CONFIG=together pytest -s -v report.md tests/api/ --report
pytest -s -v tests/api/inference/test_text_inference.py \
--stack-config=together \
--text-model=meta-llama/Llama-3.1-8B-Instruct
```
## Common options
Depending on the API, there are custom options enabled
- For tests in `inference/` and `agents/, we support `--inference-model` (to be used in text inference tests) and `--vision-inference-model` (only used in image inference tests) overrides
- For tests in `vector_io/`, we support `--embedding-model` override
- For tests in `safety/`, we support `--safety-shield` override
- The param can be `--report` or `--report <path>`
If path is not provided, we do a best effort to infer based on the config / template name. For url endpoints, path is required.
Running all inference tests for a number of models:
```bash
TEXT_MODELS=meta-llama/Llama-3.1-8B-Instruct,meta-llama/Llama-3.1-70B-Instruct
VISION_MODELS=meta-llama/Llama-3.2-11B-Vision-Instruct
EMBEDDING_MODELS=all-MiniLM-L6-v2
TOGETHER_API_KEY=...
pytest -s -v tests/api/inference/ \
--stack-config=together \
--text-model=$TEXT_MODELS \
--vision-model=$VISION_MODELS \
--embedding-model=$EMBEDDING_MODELS
```
Same thing but instead of using the distribution, use an adhoc stack with just one provider (`fireworks` for inference):
```bash
FIREWORKS_API_KEY=...
pytest -s -v tests/api/inference/ \
--stack-config=inference=fireworks \
--text-model=$TEXT_MODELS \
--vision-model=$VISION_MODELS \
--embedding-model=$EMBEDDING_MODELS
```
Running Vector IO tests for a number of embedding models:
```bash
EMBEDDING_MODELS=all-MiniLM-L6-v2
pytest -s -v tests/api/vector_io/ \
--stack-config=inference=sentence-transformers,vector_io=sqlite-vec \
--embedding-model=$EMBEDDING_MODELS
```