Update app.py

app.py

@@ -47,36 +47,37 @@ st.markdown("""
 # Image Upload
 uploaded_file = st.file_uploader("📤 Upload Prescription Image (JPG/PNG)", type=["jpg", "jpeg", "png"])
 
-# Columns for layout
-col1, col2 = st.columns([1, 2])
-
-    dilated_path = orig_path.replace(".png", "_dilated.png")
-    cv2.imwrite(dilated_path, dilated)
-
-    # Load and extract text
-    loader = UnstructuredImageLoader(dilated_path)
-    documents = loader.load()
-    extracted_text = "\n".join([doc.page_content for doc in documents])
-
-    # Define prompt
-    template = """
-    You are a helpful assistant. Here is a prescription text extracted from an image:
-
-    {prescription_text}
-
-    Please summarize the key medicine names and instructions in bullet points.
-    """
-    prompt = PromptTemplate(input_variables=["prescription_text"], template=template)
+ 
+dilated_path = orig_path.replace(".png", "_dilated.png")
+cv2.imwrite(dilated_path, dilated)
+
+# Load and extract text
+loader = UnstructuredImageLoader(dilated_path)
+documents = loader.load()
+extracted_text = "\n".join([doc.page_content for doc in documents])
+
+# Define prompt
+template = """
+You are a helpful assistant. Here is a prescription text extracted from an image:
+
+{prescription_text}
+
+Please summarize the key medicine names and instructions in bullet points.
+"""
+prompt = PromptTemplate(input_variables=["prescription_text"], template=template)
+
+model = HuggingFaceEndpoint(
+    repo_id="mistralai/Mistral-7B-Instruct-v0.3",
+    provider="novita",
+    temperature=0.6,
+    max_new_tokens=300,
+    task="conversational"
+)
 
-    model = HuggingFaceEndpoint(
-        repo_id="mistralai/Mistral-7B-Instruct-v0.3",
-        provider="novita",
-        temperature=0.6,
-        max_new_tokens=300,
-        task="conversational"
-    )
+chain = LLMChain(llm=model, prompt=prompt)
 
-    chain = LLMChain(llm=model, prompt=prompt)
+# Columns for layout
+col1, col2 = st.columns([1, 2])
 
     with col1:
         st.image(dilated, caption="Preprocessed Prescription", channels="GRAY", use_container_width=True)