Update app.py

app.py

@@ -39,7 +39,7 @@ def calculate_readability(text: str) -> float:
     return 206.835 - 1.015 * average_words_per_sentence
 
 # Function to run inference and analysis
-def run_inference_and_analysis(task, system_prompt, input_text, temperature, top_p, max_tokens, min_tokens, stop, random_seed, safe_prompt):
+def run_inference_and_analysis(task, system_prompt, input_text, temperature, top_p, max_tokens, min_tokens, random_seed, safe_prompt):
     # Initialize Pixeltable
     pxt.drop_table('mistral_prompts', ignore_errors=True)
     t = pxt.create_table('mistral_prompts', {
@@ -49,8 +49,7 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
         'timestamp': pxt.Timestamp,
         'temperature': pxt.Float,
         'top_p': pxt.Float,
-        'max_tokens': pxt.Int,
-        'stop': pxt.String,
+        'max_tokens': pxt.Int
         'random_seed': pxt.Int,
         'safe_prompt': pxt.Bool
     })
@@ -64,7 +63,6 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
         'temperature': temperature,
         'top_p': top_p,
         'max_tokens': max_tokens,
-        'stop': stop,
         'random_seed': random_seed,
         'safe_prompt': safe_prompt
     }])
@@ -80,7 +78,6 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
         'temperature': temperature,
         'top_p': top_p,
         'max_tokens': max_tokens if max_tokens is not None else 300,
-        'stop': stop.split(',') if stop else None,
         'random_seed': random_seed,
         'safe_prompt': safe_prompt
     }
@@ -125,7 +122,6 @@ def run_inference_and_analysis(task, system_prompt, input_text, temperature, top
         t.temperature,
         t.top_p,
         t.max_tokens,
-        t.stop,
         t.random_seed,
         t.safe_prompt
     ).order_by(t.timestamp, asc=False).collect().to_pandas()
@@ -202,7 +198,6 @@ def gradio_interface():
                     temperature = gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Temperature")
                     top_p = gr.Slider(minimum=0, maximum=1, value=0.9, step=0.1, label="Top P")
                     max_tokens = gr.Number(label="Max Tokens", value=300)
-                    stop = gr.Textbox(label="Stop Sequences (comma-separated)")
                     random_seed = gr.Number(label="Random Seed", value=None)
                     safe_prompt = gr.Checkbox(label="Safe Prompt", value=False)
 
@@ -243,7 +238,6 @@ def gradio_interface():
                                 "Top P",
                                 "Max Tokens",
                                 "Min Tokens",
-                                "Stop Sequences",
                                 "Random Seed",
                                 "Safe Prompt"
                             ],
@@ -283,7 +277,7 @@ def gradio_interface():
                     
         gr.Examples(
             examples=examples,
-            inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, stop, random_seed, safe_prompt],
+            inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, random_seed, safe_prompt],
             outputs=[omn_response, ml_response, large_sentiment, open_sentiment, large_keywords, open_keywords, large_readability, open_readability],
             fn=run_inference_and_analysis,
             cache_examples=True,
@@ -297,7 +291,7 @@ def gradio_interface():
         
         submit_btn.click(
             run_inference_and_analysis,
-            inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, stop, random_seed, safe_prompt],
+            inputs=[task, system_prompt, input_text, temperature, top_p, max_tokens, random_seed, safe_prompt],
             outputs=[omn_response, ml_response, large_sentiment, open_sentiment, large_keywords, open_keywords, large_readability, open_readability, history, responses, analysis, params]
         )