Update app.py

app.py

@@ -10,7 +10,7 @@ llm = HuggingFaceEndpoint(
     repo_id="mistralai/Mistral-7B-Instruct-v0.3",
     task="text-generation",
     max_new_tokens=128,
-    temperature=0.4,
+    temperature=0.7,
     do_sample=False,
 )
 
@@ -35,6 +35,7 @@ Example:
 {{"Answer":["General"]}}
 '''
 
+"""
 template_json = '''
 Your task is to read the following text, convert it to json format using 'Answer' as key and return it.
 <text>
@@ -45,6 +46,7 @@ Your final response MUST contain only the response, no other text.
 Example:
 {{"Answer":["General"]}}
 '''
+"""
 
 json_output_parser = JsonOutputParser()
 
@@ -61,7 +63,10 @@ def classify_text(text):
                     "es": "spanish",
                     "it": "italian",
                     }
-    lang = language_map[lang]
+    try:
+        lang = language_map[lang]
+    except:
+        lang = "en"
 
     prompt_classify = PromptTemplate(
         template=template_classify,
@@ -80,7 +85,6 @@ def classify_text(text):
     #formatted_prompt = template_json.format(RESPONSE=classify)
     #response = llm.invoke(formatted_prompt)
 
-    
     parsed_output = json_output_parser.parse(classify)
     end = time.time()
     duration = end - start
@@ -94,9 +98,9 @@ def gradio_app(text):
 def create_gradio_interface():
     with gr.Blocks() as iface:
         text_input = gr.Textbox(label="Text")
-        output_text = gr.Textbox(label="Topics")
+        output_text = gr.Textbox(label="Detected Topics")
         time_taken = gr.Textbox(label="Time Taken (seconds)")
-        submit_btn = gr.Button("Classify")
+        submit_btn = gr.Button("Detect topic")
 
         submit_btn.click(fn=classify_text, inputs=text_input, outputs=[output_text, time_taken])