Delete test.py

test.py

@@ -1,109 +0,0 @@
-import json
-import os
-import streamlit as st
-from cassandra.auth import PlainTextAuthProvider
-from cassandra.cluster import Cluster
-from llama_index import ServiceContext
-from llama_index import set_global_service_context
-from llama_index import VectorStoreIndex, SimpleDirectoryReader, StorageContext
-from llama_index.embeddings import GradientEmbedding
-from llama_index.llms import GradientBaseModelLLM
-from llama_index.vector_stores import CassandraVectorStore
-from copy import deepcopy
-from tempfile import NamedTemporaryFile
-
-os.environ['GRADIENT_ACCESS_TOKEN'] = "sevG6Rqb0ztaquM4xjr83SBNSYj91cux"
-os.environ['GRADIENT_WORKSPACE_ID'] = "4de36c1f-5ee6-41da-8f95-9d2fb1ded33a_workspace"
-
-@st.cache_resource
-def create_datastax_connection():
-
-    cloud_config= {'secure_connect_bundle': 'secure-connect-temp-db.zip'}
-
-    with open("temp_db-token.json") as f:
-        secrets = json.load(f)
-
-    CLIENT_ID = secrets["clientId"]
-    CLIENT_SECRET = secrets["secret"]
-
-    auth_provider = PlainTextAuthProvider(CLIENT_ID, CLIENT_SECRET)
-    cluster = Cluster(cloud=cloud_config, auth_provider=auth_provider)
-    astra_session = cluster.connect()
-    return astra_session
-
-def main():
-
-    index_placeholder = None
-    st.set_page_config(page_title = "NyayMitra", page_icon="🦙")
-    st.header('NyayMitra')
-    
-    if "conversation" not in st.session_state:
-        st.session_state.conversation = None
-
-    if "activate_chat" not in st.session_state:
-        st.session_state.activate_chat = False
-
-    if "messages" not in st.session_state:
-        st.session_state.messages = []
-
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"], avatar = message['avatar']):
-            st.markdown(message["content"])
-
-    session = create_datastax_connection()
-
-    os.environ['GRADIENT_ACCESS_TOKEN'] = "sevG6Rqb0ztaquM4xjr83SBNSYj91cux"
-    os.environ['GRADIENT_WORKSPACE_ID'] = "4de36c1f-5ee6-41da-8f95-9d2fb1ded33a_workspace"
-
-    llm = GradientBaseModelLLM(base_model_slug="llama2-7b-chat", max_tokens=400)
-    
-    embed_model = GradientEmbedding(
-        gradient_access_token = os.environ["GRADIENT_ACCESS_TOKEN"],
-        gradient_workspace_id = os.environ["GRADIENT_WORKSPACE_ID"],
-        gradient_model_slug="bge-large")
-
-    service_context = ServiceContext.from_defaults(
-    llm = llm,
-    embed_model = embed_model,
-    chunk_size=256)
-
-    set_global_service_context(service_context)
-
-    with st.sidebar:
-        st.subheader('Start your chat here')
-        if st.button('Process'):
-            with st.spinner('Processing'):
-                reader = 'data'
-                
-                documents = SimpleDirectoryReader(reader).load_data()
-                index = VectorStoreIndex.from_documents(documents,
-                                                        service_context=service_context)
-                query_engine = index.as_query_engine()
-                if "query_engine" not in st.session_state:
-                    st.session_state.query_engine = query_engine
-                st.session_state.activate_chat = True
-
-    if st.session_state.activate_chat == True:
-        if prompt := st.chat_input("Ask your question"):
-            with st.chat_message("user", avatar = '👨🏻'):
-                st.markdown(prompt)
-            st.session_state.messages.append({"role": "user", 
-                                              "avatar" :'👨🏻',
-                                              "content": prompt})
-
-            query_index_placeholder = st.session_state.query_engine
-            pdf_response = query_index_placeholder.query(prompt)
-            cleaned_response = pdf_response.response
-            with st.chat_message("assistant", avatar='🤖'):
-                st.markdown(cleaned_response)
-            st.session_state.messages.append({"role": "assistant", 
-                                              "avatar" :'🤖',
-                                              "content": cleaned_response})
-        else:
-            st.markdown(
-                ' '
-                )
-
-
-if __name__ == '__main__':
-    main()