Fix: Qdrant ids (#5515)

# Fix Qdrant ids creation

There has been a bug in how the ids were created in the Qdrant vector
store. They were previously calculated based on the texts. However,
there are some scenarios in which two documents may have the same piece
of text but different metadata, and that's a valid case. Deduplication
should be done outside of insertion.

It has been fixed and covered with the integration tests.
---------

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>

tests/integration_tests/vectorstores/test_qdrant.py

@@ -1,4 +1,5 @@
 """Test Qdrant functionality."""
+import tempfile
 from typing import Callable, Optional
 
 import pytest
@@ -247,3 +248,91 @@ def test_qdrant_embedding_interface_raises(
             embeddings=embeddings,
             embedding_function=embedding_function,
         )
+
+
+def test_qdrant_stores_duplicated_texts() -> None:
+    from qdrant_client import QdrantClient
+    from qdrant_client.http import models as rest
+
+    client = QdrantClient(":memory:")
+    collection_name = "test"
+    client.recreate_collection(
+        collection_name,
+        vectors_config=rest.VectorParams(size=10, distance=rest.Distance.COSINE),
+    )
+
+    vec_store = Qdrant(
+        client,
+        collection_name,
+        embeddings=ConsistentFakeEmbeddings(),
+    )
+    ids = vec_store.add_texts(["abc", "abc"], [{"a": 1}, {"a": 2}])
+
+    assert 2 == len(set(ids))
+    assert 2 == client.count(collection_name).count
+
+
+def test_qdrant_from_texts_stores_duplicated_texts() -> None:
+    from qdrant_client import QdrantClient
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        vec_store = Qdrant.from_texts(
+            ["abc", "abc"],
+            ConsistentFakeEmbeddings(),
+            collection_name="test",
+            path=str(tmpdir),
+        )
+        del vec_store
+
+        client = QdrantClient(path=str(tmpdir))
+        assert 2 == client.count("test").count
+
+
+@pytest.mark.parametrize("batch_size", [1, 64])
+def test_qdrant_from_texts_stores_ids(batch_size: int) -> None:
+    from qdrant_client import QdrantClient
+
+    with tempfile.TemporaryDirectory() as tmpdir:
+        ids = [
+            "fa38d572-4c31-4579-aedc-1960d79df6df",
+            "cdc1aa36-d6ab-4fb2-8a94-56674fd27484",
+        ]
+        vec_store = Qdrant.from_texts(
+            ["abc", "def"],
+            ConsistentFakeEmbeddings(),
+            ids=ids,
+            collection_name="test",
+            path=str(tmpdir),
+            batch_size=batch_size,
+        )
+        del vec_store
+
+        client = QdrantClient(path=str(tmpdir))
+        assert 2 == client.count("test").count
+        stored_ids = [point.id for point in client.scroll("test")[0]]
+        assert set(ids) == set(stored_ids)
+
+
+@pytest.mark.parametrize("batch_size", [1, 64])
+def test_qdrant_add_texts_stores_ids(batch_size: int) -> None:
+    from qdrant_client import QdrantClient
+
+    ids = [
+        "fa38d572-4c31-4579-aedc-1960d79df6df",
+        "cdc1aa36-d6ab-4fb2-8a94-56674fd27484",
+    ]
+
+    client = QdrantClient(":memory:")
+    collection_name = "test"
+    client.recreate_collection(
+        collection_name,
+        vectors_config=rest.VectorParams(size=10, distance=rest.Distance.COSINE),
+    )
+
+    vec_store = Qdrant(client, "test", ConsistentFakeEmbeddings())
+    returned_ids = vec_store.add_texts(["abc", "def"], ids=ids, batch_size=batch_size)
+
+    assert all(first == second for first, second in zip(ids, returned_ids))
+    assert 2 == client.count("test").count
+    stored_ids = [point.id for point in client.scroll("test")[0]]
+    assert set(ids) == set(stored_ids)