added testing for qdrant semantic caching

litellm/tests/test_caching.py

@@ -1629,3 +1629,108 @@ def test_caching_redis_simple(caplog, capsys):
     assert redis_async_caching_error is False
     assert redis_service_logging_error is False
     assert "async success_callback: reaches cache for logging" not in captured.out
+
+@pytest.mark.asyncio
+async def test_qdrant_semantic_cache_acompletion():
+    random_number = random.randint(
+        1, 100000
+    )  # add a random number to ensure it's always adding /reading from cache
+
+    print("Testing Qdrant Semantic Caching with acompletion")
+
+    litellm.cache = Cache(
+        type="qdrant-semantic", 
+        qdrant_host_type="cloud",
+        qdrant_url=os.getenv("QDRANT_URL"), 
+        qdrant_api_key=os.getenv("QDRANT_API_KEY"), 
+        qdrant_collection_name='test_collection', 
+        similarity_threshold=0.8, 
+        qdrant_quantization_config="binary"
+    )
+
+    response1 = await litellm.acompletion(
+        model="gpt-3.5-turbo",
+        messages=[
+            {
+                "role": "user",
+                "content": f"write a one sentence poem about: {random_number}",
+            }
+        ],
+        max_tokens=20,
+    )
+    print(f"Response1: {response1}")
+
+    random_number = random.randint(1, 100000)
+
+    response2 = await litellm.acompletion(
+        model="gpt-3.5-turbo",
+        messages=[
+            {
+                "role": "user",
+                "content": f"write a one sentence poem about: {random_number}",
+            }
+        ],
+        max_tokens=20,
+    )
+    print(f"Response2: {response2}")
+    assert response1.id == response2.id
+
+@pytest.mark.asyncio
+async def test_qdrant_semantic_cache_acompletion_stream():
+    try:
+        random_word = generate_random_word()
+        messages = [
+            {
+                "role": "user",
+                "content": f"write a joke about: {random_word}",
+            }
+        ]
+        litellm.cache = Cache(
+            type="qdrant-semantic", 
+            qdrant_host_type="cloud",
+            qdrant_url=os.getenv("QDRANT_URL"), 
+            qdrant_api_key=os.getenv("QDRANT_API_KEY"), 
+            qdrant_collection_name='test_collection', 
+            similarity_threshold=0.8, 
+            qdrant_quantization_config="binary"
+        )
+        print("Test Qdrant Semantic Caching with streaming + acompletion")
+        response_1_content = ""
+        response_2_content = ""
+
+        response1 = await litellm.acompletion(
+            model="gpt-3.5-turbo",
+            messages=messages,
+            max_tokens=40,
+            temperature=1,
+            stream=True,
+        )
+        async for chunk in response1:
+            response_1_id = chunk.id
+            response_1_content += chunk.choices[0].delta.content or ""
+
+        time.sleep(2)
+
+        response2 = await litellm.acompletion(
+            model="gpt-3.5-turbo",
+            messages=messages,
+            max_tokens=40,
+            temperature=1,
+            stream=True,
+        )
+        async for chunk in response2:
+            response_2_id = chunk.id
+            response_2_content += chunk.choices[0].delta.content or ""
+
+        print("\nResponse 1", response_1_content, "\nResponse 1 id", response_1_id)
+        print("\nResponse 2", response_2_content, "\nResponse 2 id", response_2_id)
+        assert (
+            response_1_content == response_2_content
+        ), f"Response 1 != Response 2. Same params, Response 1{response_1_content} != Response 2{response_2_content}"
+        assert (response_1_id == response_2_id), f"Response 1 id != Response 2 id, Response 1 id: {response_1_id} != Response 2 id: {response_2_id}" 
+        litellm.cache = None
+        litellm.success_callback = []
+        litellm._async_success_callback = []
+    except Exception as e:
+        print(f"{str(e)}\n\n{traceback.format_exc()}")
+        raise e