Update app.py

app.py

@@ -17,12 +17,12 @@ def get_client(space_id: str) -> Client:
 
 
 @mcp.tool()
-async def generate_image(prompt: str, space_id: str = "ysharma/SanaSprint") -> str:
+async def generate_image(prompt: str, space_id: str = "inoculatemedia/FramePack-F1") -> str:
     """Generate an image using Flux.
     
     Args:
         prompt: Text prompt describing the image to generate
-        space_id: HuggingFace Space ID to use 
+        space_id: inoculatemedia/FramePack-F1
     """
     client = get_client(space_id)
     result = client.predict(
@@ -37,92 +37,3 @@ async def generate_image(prompt: str, space_id: str = "ysharma/SanaSprint") -> s
             api_name="/infer"
     )
     return result
-
-
-@mcp.tool()
-async def run_dia_tts(prompt: str, space_id: str = "ysharma/Dia-1.6B") -> str:
-    """Text-to-Speech Synthesis.
-    
-    Args:
-        prompt: Text prompt describing the conversation between speakers S1, S2
-        space_id: HuggingFace Space ID to use 
-    """
-    client = get_client(space_id)
-    result = client.predict(
-            text_input=f"""{prompt}""",
-            audio_prompt_input=None, 
-            max_new_tokens=3072,
-            cfg_scale=3,
-            temperature=1.3,
-            top_p=0.95,
-            cfg_filter_top_k=30,
-            speed_factor=0.94,
-            api_name="/generate_audio"
-    )
-    return result
-
-
-
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    import sys
-    import io
-    sys.stdout = io.TextIOWrapper(sys.stdout.buffer, encoding='utf-8')
-    
-    mcp.run(transport='stdio')
-    demo.launch()