Added string

app.py

@@ -7,6 +7,8 @@ from llama_index import ServiceContext, VectorStoreIndex
 from llama_index.schema import Document
 import uuid
 from llama_index.vector_stores.types import MetadataFilters, ExactMatchFilter
+from typing import List
+from pydantic import BaseModel
 
 inference_api_key = st.secrets["INFRERENCE_API_TOKEN"]
 
@@ -16,6 +18,12 @@ inference_api_key = st.secrets["INFRERENCE_API_TOKEN"]
 # llm_model_name = st.text_input(
 #     'Embed Model name', "mistralai/Mistral-7B-Instruct-v0.2")
 
+
+class PriceModel(BaseModel):
+    """Data model for price"""
+    price: str
+
+
 embed_model_name = "jinaai/jina-embedding-s-en-v1"
 llm_model_name = "mistralai/Mistral-7B-Instruct-v0.2"
 
@@ -57,12 +65,14 @@ if html_file is not None:
         documents, show_progress=True, metadata={"source": "HTML"}, service_context=service_context)
 
     query_engine = index.as_query_engine(
-        filters=filters, service_context=service_context)
+        filters=filters, service_context=service_context, response_mode="tree_summarize", output_cls=PriceModel)
 
     response = query_engine.query(query)
 
     st.write(response.response)
 
+    st.write(f'Price: {response.price}')
+
 # if st.button('Start Pipeline'):
 #     if html_file is not None and embed_model_name is not None and llm_model_name is not None and query is not None:
 #         st.write('Running Pipeline')

requirements.txt

@@ -1,3 +1,4 @@
 streamlit
 llama_index
-uuid
+uuid
+pydantic