Update app.py

app.py

@@ -7,35 +7,35 @@ import logging
 logger = logging.getLogger(__name__)
 
 
-logger.info('Instantiating vectordb')
-vectordb = get_db(
-    chunk_size=1000,
-    chunk_overlap=200,
-    model_name = 'intfloat/multilingual-e5-large-instruct',
-)
-
+#logger.info('Instantiating vectordb')
+#vectordb = get_db(
+#    chunk_size=1000,
+#    chunk_overlap=200,
+#    model_name = 'intfloat/multilingual-e5-large-instruct',
+#)
 
-logger.info('Instantiating chain')
-chain = get_chain(
-    vectordb,
-    repo_id="HuggingFaceH4/zephyr-7b-beta",
-    task="text-generation",
-    max_new_tokens=512,
-    top_k=30,
-    temperature=0.1,
-    repetition_penalty=1.03,
-    search_type="mmr",
-    k=3,
-    fetch_k=5,
-    template="""Use the following sentences of context to answer the question at the end.
-If you don't know the answer, that is if the answer is not in the context, then just say that you don't know, don't try to make up an answer.
-Always say "Thanks for asking!" at the end of the answer.
 
-{context}
-
-Question: {question}
-Helpful Answer:"""
-)
+#logger.info('Instantiating chain')
+#chain = get_chain(
+#    vectordb,
+#    repo_id="HuggingFaceH4/zephyr-7b-beta",
+#    task="text-generation",
+#    max_new_tokens=512,
+#    top_k=30,
+#    temperature=0.1,
+#    repetition_penalty=1.03,
+#    search_type="mmr",
+#    k=3,
+#    fetch_k=5,
+#    template="""Use the following sentences of context to answer the question at the end.
+#If you don't know the answer, that is if the answer is not in the context, then just say that you don't know, don't try to make up an answer.
+#Always say "Thanks for asking!" at the end of the answer.
+#
+#{context}
+#
+#Question: {question}
+#Helpful Answer:"""
+#)
 
 def respond(
     question,
@@ -46,12 +46,10 @@ def respond(
     top_p,
 ):
     logger.info(f'respond called by Gradio ChatInterface with question={question}')
-    return chain.invoke({'question': question})
+    #return chain.invoke({'question': question})
+    return "hello!"
 
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[