forked from phoenix-oss/llama-stack-mirror
78e2bfbe7a
# What does this PR do? **Why** - Clean up examples which we will not maintain; reduce the surface area to the minimal showcases **What** - Delete `client.py` in /apis/* - Move all scripts to unit tests - SDK sync in the future will just require running pytests **Side notes** - `bwrap` not available on Mac so code_interpreter will not work ## Test Plan ``` LLAMA_STACK_BASE_URL=http://localhost:5000 pytest -v ./tests/client-sdk ``` <img width="725" alt="image" src="https://github.com/user-attachments/assets/36bfe537-628d-43c3-8479-dcfcfe2e4035" /> ## 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). - [ ] 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.
72 lines
2 KiB
Python
72 lines
2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import pytest
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from llama_stack_client.types.memory_insert_params import Document
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def test_memory_bank(llama_stack_client):
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providers = llama_stack_client.providers.list()
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if "memory" not in providers:
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pytest.skip("No memory provider available")
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# get memory provider id
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assert len(providers["memory"]) > 0
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memory_provider_id = providers["memory"][0].provider_id
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memory_bank_id = "test_bank"
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llama_stack_client.memory_banks.register(
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memory_bank_id=memory_bank_id,
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params={
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"embedding_model": "all-MiniLM-L6-v2",
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"chunk_size_in_tokens": 512,
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"overlap_size_in_tokens": 64,
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},
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provider_id=memory_provider_id,
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)
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# list to check memory bank is successfully registered
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available_memory_banks = [
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memory_bank.identifier for memory_bank in llama_stack_client.memory_banks.list()
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]
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assert memory_bank_id in available_memory_banks
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# add documents to memory bank
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urls = [
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"memory_optimizations.rst",
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"chat.rst",
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"llama3.rst",
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"datasets.rst",
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]
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documents = [
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Document(
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document_id=f"num-{i}",
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content=f"https://raw.githubusercontent.com/pytorch/torchtune/main/docs/source/tutorials/{url}",
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mime_type="text/plain",
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metadata={},
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)
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for i, url in enumerate(urls)
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]
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llama_stack_client.memory.insert(
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bank_id=memory_bank_id,
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documents=documents,
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)
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# query documents
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response = llama_stack_client.memory.query(
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bank_id=memory_bank_id,
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query=[
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"How do I use lora",
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],
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)
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assert len(response.chunks) > 0
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assert len(response.chunks) == len(response.scores)
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contents = [chunk.content for chunk in response.chunks]
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assert "lora" in contents[0].lower()
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