Update app.py

app.py

@@ -1,36 +1,18 @@
-import gradio as gr
-from transformers import pipeline, set_seed
+from diffusers import DiffusionPipeline
+import tempfile
 
-# Define available models
-AVAILABLE_MODELS = {
-    "GPT-2 (small, fast)": "gpt2",
-    "Falcon (TII UAE)": "tiiuae/falcon-7b-instruct",
-    "Mistral (OpenAccess)": "mistralai/Mistral-7B-v0.1"
-}
+# Load video generation model (you can switch to others)
+video_pipeline = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b", torch_dtype=torch.float16)
+video_pipeline = video_pipeline.to("cuda")
 
-set_seed(42)
-
-# Cache models
-text_model_cache = {}
-image_generator = pipeline("text-to-image", model="CompVis/stable-diffusion-v1-4")
-
-# Session memory
-chat_memory = {}
-
-def load_text_model(model_name):
-    if model_name not in text_model_cache:
-        text_model_cache[model_name] = pipeline("text-generation", model=AVAILABLE_MODELS[model_name])
-    return text_model_cache[model_name]
-
-def codette_terminal(prompt, model_name, generate_image, session_id):
+def codette_terminal(prompt, model_name, generate_image, generate_video, session_id):
     if session_id not in chat_memory:
         chat_memory[session_id] = []
 
     if prompt.lower() in ["exit", "quit"]:
         chat_memory[session_id] = []
-        return "🧠 Codette signing off... Session reset.", None
+        return "🧠 Codette signing off... Session reset.", None, None
 
-    # Text generation
     generator = load_text_model(model_name)
     response = generator(prompt, max_length=100, num_return_sequences=1, do_sample=True)[0]['generated_text'].strip()
 
@@ -38,31 +20,35 @@ def codette_terminal(prompt, model_name, generate_image, session_id):
     chat_memory[session_id].append(f"🧠 Codette > {response}")
     chat_log = "\n".join(chat_memory[session_id][-10:])
 
-    # Optional image generation
-    img = None
+    image = None
+    video = None
+
     if generate_image:
-        img = image_generator(prompt)[0]['image']
-
-    return chat_log, img
-
-# Build Gradio UI
-with gr.Blocks(title="Codette Terminal: Text + Image AI") as demo:
-    gr.Markdown("## 🧬 Codette Terminal (Text + Image, Hugging Face Edition)")
-    gr.Markdown("Choose your model, enter a prompt. Enable image generation if desired. Type `'exit'` to reset.")
-
-    session_id = gr.Textbox(value="session_default", visible=False)
-    model_dropdown = gr.Dropdown(choices=list(AVAILABLE_MODELS.keys()), value="GPT-2 (small, fast)", label="Choose Language Model")
-    generate_image_toggle = gr.Checkbox(label="Also generate image?", value=False)
-    user_input = gr.Textbox(label="Your Prompt", placeholder="e.g. a castle on Mars, explained by an AI philosopher", lines=1)
-    output_text = gr.Textbox(label="Terminal Output", lines=15, interactive=False)
-    output_image = gr.Image(label="AI-Generated Image")
-
-    user_input.submit(
-        fn=codette_terminal,
-        inputs=[user_input, model_dropdown, generate_image_toggle, session_id],
-        outputs=[output_text, output_image]
-    )
-
-# Launch on Spaces
-if __name__ == "__main__":
-    demo.launch()
+        image = image_generator(prompt)[0]['image']
+
+    if generate_video:
+        # Generate video from prompt
+        video_frames = video_pipeline(prompt, num_inference_steps=50).frames
+        # Save frames as video
+        temp_video_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
+        import imageio
+        imageio.mimsave(temp_video_path, video_frames, fps=8)
+        video = temp_video_path
+
+    return chat_log, image, video
+
+
+
+    generate_video_toggle = gr.Checkbox(label="Also generate video?", value=False)
+output_video = gr.Video(label="AI-Generated Video")
+
+user_input.submit(
+    fn=codette_terminal,
+    inputs=[user_input, model_dropdown, generate_image_toggle, generate_video_toggle, session_id],
+    outputs=[output_text, output_image, output_video]
+)
+
+
+
+
+