mirror of
https://github.com/meta-llama/llama-stack.git
synced 2025-10-04 12:07:34 +00:00
ad6ea7fb91
# What does this PR do? This PR adds support for OpenAI Prompts API. Note, OpenAI does not explicitly expose the Prompts API but instead makes it available in the Responses API and in the [Prompts Dashboard](https://platform.openai.com/docs/guides/prompting#create-a-prompt). I have added the following APIs: - CREATE - GET - LIST - UPDATE - Set Default Version The Set Default Version API is made available only in the Prompts Dashboard and configures which prompt version is returned in the GET (the latest version is the default). Overall, the expected functionality in Responses will look like this: ```python from openai import OpenAI client = OpenAI() response = client.responses.create( prompt={ "id": "pmpt_68b0c29740048196bd3a6e6ac3c4d0e20ed9a13f0d15bf5e", "version": "2", "variables": { "city": "San Francisco", "age": 30, } } ) ``` ### Resolves https://github.com/llamastack/llama-stack/issues/3276 ## Test Plan Unit tests added. Integration tests can be added after client generation. ## Next Steps 1. Update Responses API to support Prompt API 2. I'll enhance the UI to implement the Prompt Dashboard. 3. Add cache for lower latency --------- Signed-off-by: Francisco Javier Arceo <farceo@redhat.com>
30 lines
1 KiB
Python
30 lines
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 random
|
|
|
|
import pytest
|
|
|
|
from llama_stack.core.prompts.prompts import PromptServiceConfig, PromptServiceImpl
|
|
from llama_stack.providers.utils.kvstore.config import SqliteKVStoreConfig
|
|
|
|
|
|
@pytest.fixture
|
|
async def temp_prompt_store(tmp_path_factory):
|
|
unique_id = f"prompt_store_{random.randint(1, 1000000)}"
|
|
temp_dir = tmp_path_factory.getbasetemp()
|
|
db_path = str(temp_dir / f"{unique_id}.db")
|
|
|
|
from llama_stack.core.datatypes import StackRunConfig
|
|
from llama_stack.providers.utils.kvstore import kvstore_impl
|
|
|
|
mock_run_config = StackRunConfig(image_name="test-distribution", apis=[], providers={})
|
|
config = PromptServiceConfig(run_config=mock_run_config)
|
|
store = PromptServiceImpl(config, deps={})
|
|
|
|
store.kvstore = await kvstore_impl(SqliteKVStoreConfig(db_path=db_path))
|
|
|
|
yield store
|