Update app.py

app.py

@@ -3,44 +3,38 @@ from langchain.llms import HuggingFaceHub
 from langchain.chains import LLMChain
 from langchain.prompts import PromptTemplate
 
-#Function to return the response 
+# Function to return the response
 def generate_answer(query):
     llm = HuggingFaceHub(
-        repo_id = "google/flan-t5-xxl", 
-        model_kwargs={"temperature": 0.7, "max_length": 64,"max_new_tokens":512}
+        repo_id="google/flan-t5-xxl",
+        model_kwargs={"temperature": 0.7, "max_length": 64, "max_new_tokens": 512}
     )
-    
-    template = """Question: {query}
 
-                Answer: Let's think step by step.
-                """
+    template = """Patient's Question: {query}
+
+    Doctor's Answer: Let's consider your symptoms. Can you provide more details about your symptoms and how long you've been experiencing them?
+    """
     
-    prompt= PromptTemplate(template=template, input_variables=["query"])
+    prompt = PromptTemplate(template=template, input_variables=["query"])
     llm_chain = LLMChain(prompt=prompt, llm=llm)
     result = llm_chain.run(query)
     return result
-    
-
-#App UI starts here 
-st.set_page_config(page_title = "LangChain Demo", page_icon = ":robot:")
-st.header("LangChain Demo")
 
+# App UI starts here
+st.set_page_config(page_title="Doctor Assistant Demo", page_icon=":robot:")
+st.header("Doctor Assistant Demo")
 
-#Gets User Input 
+# Gets User Input
 def get_text():
     input_text = st.text_input("You: ", key="input")
     return input_text
 
-
 user_input = get_text()
 response = generate_answer(user_input)
 
 submit = st.button("Generate")
 
-#If the button clicked
+# If the button clicked
 if submit:
-    st.subheader("Answer: ")
-    st.write(response)
-
-
-    
+    st.subheader("Doctor's Response:")
+    st.write(response)