update

app.py

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+import os
+import os.path
+import pymongo
+from pymongo.mongo_client import MongoClient
+import gradio as gr
+import certifi
+
+MONGODB_ATLAS_DB_PASSWORD = os.environ['MONGODB_ATLAS_DB_PASSWORD']
+
+
+from llama_index.vector_stores.mongodb import MongoDBAtlasVectorSearch
+
+from llama_index import (
+    VectorStoreIndex,
+    SimpleDirectoryReader,
+    StorageContext,
+    load_index_from_storage,
+)
+
+
+mongo_uri = (
+    f"mongodb+srv://arkiitkgp:{MONGODB_ATLAS_DB_PASSWORD}@genaicluster0.fgmvvsx.mongodb.net/?retryWrites=true&w=majority"
+)
+mongodb_client = pymongo.MongoClient(mongo_uri, tlsCAFile=certifi.where())
+
+# Send a ping to confirm a successful connection
+try:
+    mongodb_client.admin.command('ping')
+    print("Pinged your deployment. You successfully connected to MongoDB!")
+except Exception as e:
+    print(e)
+
+
+store = MongoDBAtlasVectorSearch(mongodb_client, db_name='testdb1', collection_name='dummyIndex', index_name='vector_index')
+# storage_context = StorageContext.from_defaults(vector_store=store)
+# documents = SimpleDirectoryReader(
+#         "temp", 
+#         file_metadata=get_metadata_from_filename, 
+#         required_exts=['.pdf', '.docx'],
+#         recursive=True,
+#     ).load_data()
+
+# construct index
+# index = VectorStoreIndex.from_documents(
+#     documents, storage_context=storage_context
+# )
+
+index = VectorStoreIndex.from_vector_store(store)
+
+
+def get_answer(query):
+    response = index.as_query_engine(streaming=True).query(query)
+    # response.print_response_stream()
+    return response
+
+
+
+###### GRADIO #################################
+
+classes = ['Class 10', 'Class 9']
+subjects = ['Science']
+
+def get_streaming_answer(input_query):
+    r = get_answer(input_query)
+    ans = ""
+    for new_tokens in r.response_gen:
+        ans += new_tokens
+        yield ans
+
+with gr.Blocks() as demo:
+    gr.Markdown("""# NCERT Tutor \n ### Type your question...""")
+    with gr.Tab("For Students"):
+        choose_class = gr.Dropdown(label= "Class", choices=classes)
+        choose_subject = gr.Dropdown(label="Subject", choices=subjects)
+        question_input = gr.Textbox(label="Enter question...")
+        submit_button = gr.Button("Ask")
+        response_output = gr.Textbox(label="Answer...")
+        
+    with gr.Tab("For Teachers"):
+        gr.Markdown("Coming soon...")
+
+    submit_button.click(fn=get_streaming_answer, inputs=question_input, outputs=response_output)
+  
+demo.launch(share=True, debug=True)

requirements.txt

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+openai==1.11.1
+llama-index==0.9.44
+pypdf==4.0.1
+gradio==4.17.0
+pymongo[srv]==3.10