Update app.py

app.py

@@ -2,26 +2,33 @@ import gradio as gr
 from transformers import pipeline
 
 models = {
-    "MagicPrompt": "pszemraj/distilgpt2-magicprompt-SD",
     "DistilGPT2 SD": "FredZhang7/distilgpt2-stable-diffusion",
-    "Llama-SmolTalk-3.2-1B": "prithivMLmods/Llama-SmolTalk-3.2-1B-Instruct"
+    "Llama-SmolTalk-3.2-1B": "prithivMLmods/Llama-SmolTalk-3.2-1B-Instruct",
+    "Dolphin-Phi 3 2.9.2": "cognitivecomputations/dolphin-2.9.2-Phi-3-Medium",
+    "EXAONE 3.5 2.4B": "LGAI-EXAONE/EXAONE-3.5-2.4B-Instruct",
+    "Granite 3.3 2B": "ibm-granite/granite-3.3-2b-instruct"
 }
-pipelines = {}
-
-for key, value in models.items():
-    pipelines[value] = pipeline("text-generation", model=value)
 
 def respond(
     message,
     _: list[tuple[str, str]],
+    system_prompt: str,
     model: str,
     max_new_tokens: int,
     temperature: float,
     top_p: float,
     top_k: int
 ):
-    yield pipelines[model](
-        message,
+    pipe = pipeline("text-generation", model=value, trust_remote_code=True)
+
+    yield pipe(
+        [
+            *message,
+            {
+                "role": "system",
+                "content": system_prompt
+            }
+        ],
         max_new_tokens=max_new_tokens,
         do_sample=True,
         temperature=temperature,
@@ -38,7 +45,8 @@ demo = gr.ChatInterface(
     title="Prompt Enhancer Test",
     type="messages",
     additional_inputs=[
-        gr.Radio(list(models.items()), value="pszemraj/distilgpt2-magicprompt-SD", type="value", label="Model"),
+        gr.Textbox(value="When the user provides two sentences, return a longer sentence that fuses the two together with a natural motion in between.", lines=5, show_label=True, label="System prompt"),
+        gr.Radio(list(models.items()), value="FredZhang7/distilgpt2-stable-diffusion", type="value", label="Model"),
         # gr.Textbox(value="Enhance the provided text so that it is more vibrant and detailed.", label="System prompt"),
         gr.Slider(minimum=8, maximum=128, value=64, step=8, label="Max new tokens"),
         gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),