test(azure openai repro): adds example script to reproduce Azure OpenAI bug

azure_openai_repro.py

@@ -0,0 +1,68 @@
+"""
+Set API key when running test
+
+```sh
+$ AZURE_OPENAI_API_KEY="azure-openai-api-key" python <this_file>
+```
+
+Set `OPENAI_LOG=debug` to see more verbose debug logs
+
+```sh
+$ OPENAI_LOG=debug AZURE_OPENAI_API_KEY="azure-openai-api-key" python <this_file>
+```
+"""
+
+import chromadb
+import os
+from chromadb.utils.embedding_functions.openai_embedding_function import OpenAIEmbeddingFunction
+
+"""
+Constants
+"""
+# Source: https://portal.azure.com
+AZURE_ENDPOINT = "https://chroma-repro-bug.openai.azure.com/"
+
+# Source: https://azure.microsoft.com/en-us/pricing/details/cognitive-services/openai-service/#overview
+AZURE_MODEL_NAME = "text-embedding-3-small" 
+
+# Source: https://portal.azure.com
+DEPLOYMENT = "text-embedding-3-small"
+
+# Source: https://portal.azure.com
+API_VERSION = "2024-02-01"
+
+# Source: https://github.com/openai/openai-python?tab=readme-ov-file#microsoft-azure-openai
+AZURE_OPENAI_API_KEY = os.getenv("AZURE_OPENAI_API_KEY")
+if not AZURE_OPENAI_API_KEY:
+    raise ValueError("AZURE_OPENAI_API_KEY environment variable is not set")
+
+# Creates a custom embedding function that uses our Azure OpenAI deployment
+my_azure_openai_embedding_function = OpenAIEmbeddingFunction(
+    api_type="azure",
+    deployment_id=DEPLOYMENT,
+    api_version=API_VERSION,
+    api_base=AZURE_ENDPOINT,
+    model_name=AZURE_MODEL_NAME,
+    api_key=AZURE_OPENAI_API_KEY,
+)
+
+# Creates a Chroma client
+client = chromadb.Client()
+
+# Creates a Chroma collection using our custom embedding function
+collection = client.create_collection("my_collection", embedding_function=my_azure_openai_embedding_function)
+
+# Embeds some example text
+test = collection.add(
+    ids=["cat_embedding", "apple_embedding", "san_francisco_embedding"],
+    documents=["Cat", "Apple", "San Francisco"],
+)
+
+# Queries our collection for the nearest neighbors to the example text
+nearest_neighbors = collection.query(
+    query_texts=["Dog"],
+    n_results=1,
+)
+
+# Prints the nearest neighbors
+print(nearest_neighbors)