# What does this PR do?
Cleans up how we provide sampling params. Earlier, strategy was an enum
and all params (top_p, temperature, top_k) across all strategies were
grouped. We now have a strategy union object with each strategy (greedy,
top_p, top_k) having its corresponding params.
Earlier,
```
class SamplingParams:
strategy: enum ()
top_p, temperature, top_k and other params
```
However, the `strategy` field was not being used in any providers making
it confusing to know the exact sampling behavior purely based on the
params since you could pass temperature, top_p, top_k and how the
provider would interpret those would not be clear.
Hence we introduced -- a union where the strategy and relevant params
are all clubbed together to avoid this confusion.
Have updated all providers, tests, notebooks, readme and otehr places
where sampling params was being used to use the new format.
## Test Plan
`pytest llama_stack/providers/tests/inference/groq/test_groq_utils.py`
// inference on ollama, fireworks and together
`with-proxy pytest -v -s -k "ollama"
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/inference/test_text_inference.py `
// agents on fireworks
`pytest -v -s -k 'fireworks and create_agent'
--inference-model="meta-llama/Llama-3.1-8B-Instruct"
llama_stack/providers/tests/agents/test_agents.py
--safety-shield="meta-llama/Llama-Guard-3-8B"`
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [X] Ran pre-commit to handle lint / formatting issues.
- [X] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [X] Updated relevant documentation.
- [X] Wrote necessary unit or integration tests.
---------
Co-authored-by: Hardik Shah <hjshah@fb.com>
# What does this PR do?
We are setting a default value of json for tool prompt format, which
conflicts with llama 3.2/3.3 models since they use python list. This PR
changes the defaults to None and in the code, we infer default based on
the model.
Addresses: #695
Tests:
❯ LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v
tests/client-sdk/inference/test_inference.py -k
"test_text_chat_completion"
pytest llama_stack/providers/tests/inference/test_prompt_adapter.py
Add another header so client SDKs can identify their versions which can
be used for immediate detection of possible compatibility issues. A
semver mismatch against the wrong server should be immediately flagged
and requests should be denied.
Also change `X-LlamaStack-ProviderData` to `X-LlamaStack-Provider-Data`
since that hyphenation is better.
# What does this PR do?
Contributes towards: #432
RE: https://github.com/meta-llama/llama-stack/pull/609
I missed this one while refactoring. Fixes:
```python
Traceback (most recent call last):
File "/Users/aidand/dev/llama-stack/llama_stack/distribution/server/server.py", line 191, in endpoint
return await maybe_await(value)
File "/Users/aidand/dev/llama-stack/llama_stack/distribution/server/server.py", line 155, in maybe_await
return await value
File "/Users/aidand/dev/llama-stack/llama_stack/providers/utils/telemetry/trace_protocol.py", line 101, in async_wrapper
result = await method(self, *args, **kwargs)
File "/Users/aidand/dev/llama-stack/llama_stack/distribution/routers/routers.py", line 156, in chat_completion
return await provider.chat_completion(**params)
File "/Users/aidand/dev/llama-stack/llama_stack/providers/utils/telemetry/trace_protocol.py", line 101, in async_wrapper
result = await method(self, *args, **kwargs)
File "/Users/aidand/dev/llama-stack/llama_stack/providers/remote/inference/groq/groq.py", line 127, in chat_completion
response = self._get_client().chat.completions.create(**request)
File "/Users/aidand/dev/llama-stack/llama_stack/providers/remote/inference/groq/groq.py", line 143, in _get_client
return Groq(api_key=self.config.api_key)
AttributeError: 'GroqInferenceAdapter' object has no attribute 'config'. Did you mean: '_config'?
```
## Test Plan
Environment:
```shell
export GROQ_API_KEY=<api-key>
# build.yaml and run.yaml files
wget https://raw.githubusercontent.com/aidando73/llama-stack/9165502582cd7cb178bc1dcf89955b45768ab6c1/build.yaml
wget https://raw.githubusercontent.com/aidando73/llama-stack/9165502582cd7cb178bc1dcf89955b45768ab6c1/run.yaml
# Create environment if not already
conda create --prefix ./envs python=3.10
conda activate ./envs
# Build
pip install -e . && llama stack build --config ./build.yaml --image-type conda
# Activate built environment
conda activate llamastack-groq
```
<details>
<summary>Manual</summary>
```bash
llama stack run ./run.yaml --port 5001
```
Via this Jupyter notebook:
9165502582/hello.ipynb
</details>
## Sources
Please link relevant resources if necessary.
## Before submitting
- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [x] Ran pre-commit to handle lint / formatting issues.
- [x] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
Pull Request section?
- [x] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
