Update app.py

app.py

@@ -32,7 +32,7 @@ embed_model = HuggingFaceEmbeddings(model_name="mixedbread-ai/mxbai-embed-large-
 from langchain_chroma import Chroma
 
 vectorstore = Chroma(
-    collection_name="medical_dataset_store",
+    collection_name="car_dataset_store",
     embedding_function=embed_model,
     persist_directory="./",
 )
@@ -44,7 +44,7 @@ retriever = vectorstore.as_retriever()
 
 from langchain_core.prompts import PromptTemplate
 
-template = ("""You are a medical expert.
+template = ("""You are a car expert.
     Use the provided context to answer the question.
     If you don't know the answer, say so. Explain your answer in detail.
     Do not discuss the context in your response; just provide the answer directly.
@@ -75,12 +75,12 @@ def rag_memory_stream(text):
         partial_text += new_text
         yield partial_text
 
-examples = ['I feel dizzy', 'what is the possible sickness for fatigue']
+examples = ['I need a car', 'what is the make and fuel type of a car?']
 
 
 
 
-title = "Real-time AI App with Groq API and LangChain to Answer medical questions"
+title = "Real-time AI App with Groq API and LangChain to Answer car questions"
 demo = gr.Interface(
     title=title,
     fn=rag_memory_stream,