wehub-resource-sync
90 lines
2.2 KiB
Python
90 lines
2.2 KiB
Python
import pytest
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from lightrag.base import QueryParam
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from lightrag.operate import naive_query
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class _FakeTokenizer:
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def encode(self, content: str) -> list[int]:
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return [ord(ch) for ch in content]
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def decode(self, tokens: list[int]) -> str:
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return "".join(chr(token) for token in tokens)
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class _FakeKVStorage:
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def __init__(self):
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self.global_config = {"enable_llm_cache": True}
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self._store = {}
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async def get_by_id(self, key):
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return self._store.get(key)
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async def upsert(self, entries):
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self._store.update(entries)
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class _FakeChunksVDB:
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cosine_better_than_threshold = 0.0
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async def query(self, *_args, **_kwargs):
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return [
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{
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"id": "chunk-1",
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"content": "LightRAG cache identity test chunk.",
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"file_path": "test.md",
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}
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]
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def _query_global_config(model: str, llm_func) -> dict:
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return {
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"tokenizer": _FakeTokenizer(),
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"role_llm_funcs": {"query": llm_func},
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"llm_cache_identities": {
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"query": {
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"role": "query",
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"binding": "openai",
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"model": model,
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"host": "https://api.example.com/v1",
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}
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},
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"min_rerank_score": 0.0,
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"max_total_tokens": 4096,
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}
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@pytest.mark.offline
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@pytest.mark.asyncio
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async def test_naive_query_partitions_query_cache_by_llm_identity():
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cache = _FakeKVStorage()
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chunks_vdb = _FakeChunksVDB()
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calls = 0
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async def query_model(*_args, **_kwargs):
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nonlocal calls
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calls += 1
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return f"answer-{calls}"
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param = QueryParam(mode="naive", enable_rerank=False)
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first = await naive_query(
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"same query",
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chunks_vdb,
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param,
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_query_global_config("model-a", query_model),
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hashing_kv=cache,
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)
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second = await naive_query(
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"same query",
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chunks_vdb,
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param,
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_query_global_config("model-b", query_model),
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hashing_kv=cache,
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)
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assert first.content == "answer-1"
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assert second.content == "answer-2"
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assert calls == 2
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assert len(cache._store) == 2
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