llama-stack-mirror/llama_stack/distribution/ui/modules/api.py
Xi Yan 16769256b7
[llama stack ui] add native eval & inspect distro & playground pages (#541)
# What does this PR do?

New Pages Added: 

- (1) Inspect Distro
- (2) Evaluations: 
  - (a) native evaluations (including generation)
  - (b) application evaluations (no generation, scoring only)
- (3) Playground: 
  - (a) chat
  - (b) RAG  

## Test Plan

```
streamlit run app.py
```

#### Playground

https://github.com/user-attachments/assets/6ca617e8-32ca-49b2-9774-185020ff5204

#### Inspect

https://github.com/user-attachments/assets/01d52b2d-92af-4e3a-b623-a9b8ba22ba99


#### Evaluations (Generation + Scoring)

https://github.com/user-attachments/assets/345845c7-2a2b-4095-960a-9ae40f6a93cf

#### Evaluations (Scoring)

https://github.com/user-attachments/assets/6cc1659f-eba4-49ca-a0a5-7c243557b4f5


## Before submitting

- [ ] This PR fixes a typo or improves the docs (you can dismiss the
other checks if that's the case).
- [ ] Ran pre-commit to handle lint / formatting issues.
- [ ] Read the [contributor
guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md),
      Pull Request section?
- [ ] Updated relevant documentation.
- [ ] Wrote necessary unit or integration tests.
2024-12-04 09:47:09 -08:00

36 lines
1.1 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
import os
from typing import Optional
from llama_stack_client import LlamaStackClient
class LlamaStackApi:
def __init__(self):
self.client = LlamaStackClient(
base_url=os.environ.get("LLAMA_STACK_ENDPOINT", "http://localhost:5000"),
provider_data={
"fireworks_api_key": os.environ.get("FIREWORKS_API_KEY", ""),
"together_api_key": os.environ.get("TOGETHER_API_KEY", ""),
"openai_api_key": os.environ.get("OPENAI_API_KEY", ""),
},
)
def run_scoring(
self, row, scoring_function_ids: list[str], scoring_params: Optional[dict]
):
"""Run scoring on a single row"""
if not scoring_params:
scoring_params = {fn_id: None for fn_id in scoring_function_ids}
return self.client.scoring.score(
input_rows=[row], scoring_functions=scoring_params
)
llama_stack_api = LlamaStackApi()