Update app.py

app.py

@@ -5,10 +5,8 @@ import numpy as np
 import requests
 
 from langchain_groq import ChatGroq
-from langchain.agents import initialize_agent
 from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
-from langchain.tools import StructuredTool
 
 
 model_path = "unet_model.h5"
@@ -43,31 +41,11 @@ def rishigpt_handler(image_input, groq_api_key):
 
     mask = classify_image(image_input)
 
-    # The LLM tool just reports a dummy text here for now
-    def segment_brain_tool():
-        return "A brain tumor mask was generated."
-
-    tool = StructuredTool.from_function(
-        segment_brain_tool,
-        name="segment_brain",
-        description="Segment brain MRI for tumor detection."
-    )
-
     llm = ChatGroq(
         model="meta-llama/llama-4-scout-17b-16e-instruct",
         temperature=0.3
     )
 
-    agent = initialize_agent(
-        tools=[tool],
-        llm=llm,
-        agent="zero-shot-react-description",
-        verbose=True
-    )
-
-    user_query = "I uploaded a brain MRI. What does the segmentation say?"
-    classification = agent.run(user_query)
-
     prompt = PromptTemplate(
         input_variables=["result"],
         template="You are a medical imaging expert. Based on the result: {result}, explain what this means for diagnosis."
@@ -78,6 +56,7 @@ def rishigpt_handler(image_input, groq_api_key):
         prompt=prompt
     )
 
+    classification = "The brain tumor mask has been generated and segmentation is complete."
     description = llm_chain.run({"result": classification})
 
     return mask, description