Update app.py

app.py

@@ -22,19 +22,20 @@ client = OpenAI(
     api_key=os.environ['anyscale_api_key']
 )
 
-model_name = 'mlabonne/NeuralHermes-2.5-Mistral-7B'
+#model_name = 'mlabonne/NeuralHermes-2.5-Mistral-7B'
+model_name = 'mistralai/Mixtral-8x7B-Instruct-v0.1'
 
 # Define the embedding model and the vectorstore
 embedding_model_name = 'thenlper/gte-large'
 embedding_model = SentenceTransformerEmbeddings(model_name=embedding_model_name)
 collection_name_qna = 'report_10K_db'
-persisted_vectordb_location = 'report_10K_db'
+persisted_vectordb_location = './report_10K_db'
 
 # Load the persisted vectorDB
 
 vectorstore_persisted = Chroma(
-    collection_name='report_10K_db',
-    persist_directory='./report_10K_db',
+    collection_name=collection_name_qna,
+    persist_directory=persisted_vectordb_location,
     embedding_function=embedding_model
 )
 
@@ -167,8 +168,8 @@ demo = gr.Interface(
     fn=predict,
     inputs=[textbox,company],
     outputs="text",
-    title="Information from 10-K reports",
-    description="system to streamline the extraction and analysis of key information from 10-K reports",
+    title="Insights from 10-K reports",
+    description="AI for extraction, summarization, and analysis of information from the 10-K reports",
     allow_flagging="auto",
     concurrency_limit=12
 )