Update app.py

app.py

@@ -76,19 +76,19 @@ def set_background(image_file):
     )
 
 # Split large response into smaller chunks (for translation)
-def split_text_into_chunks(text, max_length=450):
-    lines = text.split('\n')
-    chunks = []
-    current = ""
-    for line in lines:
-        if len(current) + len(line) + 1 <= max_length:
-            current += line + '\n'
-        else:
-            chunks.append(current.strip())
-            current = line + '\n'
-    if current:
-        chunks.append(current.strip())
-    return chunks
+# def split_text_into_chunks(text, max_length=450):
+#     lines = text.split('\n')
+#     chunks = []
+#     current = ""
+#     for line in lines:
+#         if len(current) + len(line) + 1 <= max_length:
+#             current += line + '\n'
+#         else:
+#             chunks.append(current.strip())
+#             current = line + '\n'
+#     if current:
+#         chunks.append(current.strip())
+#     return chunks
 
 
 def save_text_as_image(text, file_path):
@@ -209,8 +209,8 @@ if uploaded_file:
     prompt = PromptTemplate(input_variables=["prescription_text"], template=template)
 
     llm_model = HuggingFaceEndpoint(
-        repo_id="deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
-        provider="novita",
+        repo_id="Qwen/Qwen3-235B-A22B",
+        provider="nebius",
         temperature=0.6,
         max_new_tokens=300,
         task="conversational"
@@ -218,8 +218,8 @@ if uploaded_file:
     
     llm = ChatHuggingFace(
         llm=llm_model,
-        repo_id="deepseek-ai/DeepSeek-R1-0528-Qwen3-8B",
-        provider="novita",
+        repo_id="Qwen/Qwen3-235B-A22B",
+        provider="nebius",
         temperature=0.6,
         max_new_tokens=300,
         task="conversational"
@@ -234,7 +234,7 @@ if uploaded_file:
         with st.spinner("Analyzing with LLM..."):
             response = chain.run(prescription_text=text)
         st.markdown("#### 💡 AI-based Medicine Analysis")
-        st.text_area("LLM Output", response, height=600)
+        st.text_area("LLM Output", response, height=300)
 
         # Save txt and image
         txt_path = "medicine_analysis.txt"
@@ -252,31 +252,31 @@ if uploaded_file:
             with open(img_path, "rb") as img_file:
                 st.download_button("🖼️ English Image", data=img_file, file_name="medicine_analysis.png", mime="image/png")\
                 
-    if response and st.button("🌐 Translate to Hindi"):
-        with st.spinner("Translating to Hindi..."):
-            chunks = split_text_into_chunks(response, max_length=100)
-            hindi_chunks = []
-            for chunk in chunks:
-                try:
-                    translated = GoogleTranslator(source='auto', target='hi').translate(chunk)
-                    hindi_chunks.append(translated)
-                except Exception as e:
-                    hindi_chunks.append("[Error translating chunk]")
-            hindi_text = "\n\n".join(hindi_chunks)
+    # if response and st.button("🌐 Translate to Hindi"):
+    #     with st.spinner("Translating to Hindi..."):
+    #         chunks = split_text_into_chunks(response, max_length=100)
+    #         hindi_chunks = []
+    #         for chunk in chunks:
+    #             try:
+    #                 translated = GoogleTranslator(source='auto', target='hi').translate(chunk)
+    #                 hindi_chunks.append(translated)
+    #             except Exception as e:
+    #                 hindi_chunks.append("[Error translating chunk]")
+    #         hindi_text = "\n\n".join(hindi_chunks)
     
-        st.markdown("#### 🌐 Hindi Translation")
-        st.text_area("Translated Output (Hindi)", hindi_text, height=600)
+    #     st.markdown("#### 🌐 Hindi Translation")
+    #     st.text_area("Translated Output (Hindi)", hindi_text, height=600)
     
-        hindi_img_path = "hindi_output.png"
-        save_text_as_image(hindi_text, hindi_img_path)
+    #     hindi_img_path = "hindi_output.png"
+    #     save_text_as_image(hindi_text, hindi_img_path)
     
-        st.markdown("#### 📥 Download (Hindi)")
-        col3, col4 = st.columns(2)
-        with col3:
-            st.download_button("⬇️ Hindi TXT", data=hindi_text.encode(), file_name="hindi_medicine_analysis.txt")
-        with col4:
-            with open(hindi_img_path, "rb") as img_file:
-                st.download_button("🖼️ Hindi Image", data=img_file, file_name="hindi_medicine_analysis.png", mime="image/png")
+    #     st.markdown("#### 📥 Download (Hindi)")
+    #     col3, col4 = st.columns(2)
+    #     with col3:
+    #         st.download_button("⬇️ Hindi TXT", data=hindi_text.encode(), file_name="hindi_medicine_analysis.txt")
+    #     with col4:
+    #         with open(hindi_img_path, "rb") as img_file:
+    #             st.download_button("🖼️ Hindi Image", data=img_file, file_name="hindi_medicine_analysis.png", mime="image/png")
 
     try:
         os.remove(orig_path)