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feat: Qdrant Vector index support (#221)

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This PR adds support for Qdrant - https://qdrant.tech/ to be used as a vector memory.

I've unit-tested the methods to confirm that they work as intended.

To run Qdrant

```
docker run -p 6333:6333 qdrant/qdrant
```
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Anush 2024-10-23 01:20:19 +05:30 • committed by GitHub
parent 668a495aba
commit 4c3d33e6f4
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11 changed files with 242 additions and 7 deletions
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5
llama_stack/providers/tests/memory/test_memory.py
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@ -144,10 +144,11 @@ async def test_query_documents(memory_settings, sample_documents):
# Test case 5: Query with threshold on similarity score
query5 = "quantum computing" # Not directly related to any document
params5 = {"score_threshold": 0.5}
params5 = {"score_threshold": 0.2}
response5 = await memory_impl.query_documents("test_bank", query5, params5)
assert_valid_response(response5)
assert all(score >= 0.5 for score in response5.scores)
print("The scores are:", response5.scores)
assert all(score >= 0.2 for score in response5.scores)
def assert_valid_response(response: QueryDocumentsResponse):