Update app.py

app.py

@@ -1,15 +1,20 @@
+import os
+
 from langchain.vectorstores import Qdrant
 from langchain.embeddings import HuggingFaceEmbeddings
 from qdrant_client import QdrantClient
 import gradio as gr
 from transformers.utils import logging
+
 logging.set_verbosity_info()
 logger = logging.get_logger("transformers")
+qdrant_url = os.environ['QDRANT_URL']
+qdrant_api_key = os.environ['QDRANT_API_KEY']
 
 def process_text(input_text, top_k):
     embeddings = HuggingFaceEmbeddings(model_name="intfloat/multilingual-e5-base")
     client = QdrantClient(
-        path="local_qdrant", prefer_grpc=False,
+        url=qdrant_url, api_key=qdrant_api_key, prefer_grpc=False,
     )
     db = Qdrant(client=client, embeddings=embeddings, collection_name="qa_data")
     query = input_text
@@ -18,7 +23,6 @@ def process_text(input_text, top_k):
     docs = db.similarity_search_with_score(query=query, k=top_k)
     for i in docs:
         doc, score = i
-        print({"score": score, "content": doc.page_content, "metadata": doc.metadata} )
         all_answers.append(doc.metadata["source"])
 
     return "\n***\\n".join(all_answers)