Create utils.py

utils.py

@@ -0,0 +1,37 @@
+from langchain_openai import OpenAIEmbeddings, ChatOpenAI
+from qdrant_client import QdrantClient
+
+
+def setup_openai_embeddings(api_key):
+    """Set up OpenAI embeddings."""
+    return OpenAIEmbeddings(model='text-embedding-3-small', openai_api_key=api_key)
+
+
+def setup_qdrant_client(url, api_key):
+    """Set up Qdrant client."""
+    return QdrantClient(location=url, api_key=api_key)
+
+def format_document_metadata(docs):
+    """Format metadata for each document."""
+    formatted_docs = []
+    for doc in docs:
+        metadata_str = ', '.join(f"{key}: {value}" for key, value in doc.metadata.items())
+        doc_str = f"{doc.page_content}\nMetadata: {metadata_str}"
+        formatted_docs.append(doc_str)
+    return "\n\n".join(formatted_docs)
+
+def openai_llm(api_key: str):
+    """Get a configured OpenAI language model."""
+    return ChatOpenAI(model_name="gpt-3.5-turbo", temperature=0, openai_api_key=api_key)
+
+def delete_collection(collection_name, qdrant_url, qdrant_api_key):
+    """Delete a Qdrant collection."""
+    client = setup_qdrant_client(qdrant_url, qdrant_api_key)
+    try:
+        client.delete_collection(collection_name=collection_name)
+    except Exception as e:
+        print("Failed to delete collection:", e)
+
+def is_document_embedded(filename):
+    """Check if a document is already embedded. Actual implementation needed."""
+    return False