Delete app.py

app.py

@@ -1,98 +0,0 @@
-import gradio as gr
-import torch
-from transformers import pipeline, set_seed
-from diffusers import DiffusionPipeline
-import tempfile
-import imageio
-
-# ---------- Setup ----------
-AVAILABLE_MODELS = {
-    "GPT-2 (small, fast)": "gpt2",
-    "Falcon (TII UAE)": "tiiuae/falcon-7b-instruct",
-    "Mistral (OpenAccess)": "mistralai/Mistral-7B-v0.1"
-}
-
-set_seed(42)
-text_model_cache = {}
-
-# Load text-to-image model using diffusers (correct API)
-try:
-    image_generator = DiffusionPipeline.from_pretrained("runwayml/stable-diffusion-v1-5")
-    image_generator.to("cpu")
-    image_enabled = True
-except Exception as e:
-    image_generator = None
-    image_enabled = False
-    print(f"[Image model error]: {e}")
-
-# Load text-to-video model
-try:
-    video_pipeline = DiffusionPipeline.from_pretrained("damo-vilab/text-to-video-ms-1.7b")
-    video_pipeline.to("cpu")
-    video_enabled = True
-except Exception as e:
-    video_pipeline = None
-    video_enabled = False
-    print(f"[Video model error]: {e}")
-
-chat_memory = {}
-
-# ---------- Core Function ----------
-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, None
-
-    if model_name not in text_model_cache:
-        text_model_cache[model_name] = pipeline("text-generation", model=AVAILABLE_MODELS[model_name])
-    generator = text_model_cache[model_name]
-    response = generator(prompt, max_length=100, num_return_sequences=1, do_sample=True)[0]['generated_text'].strip()
-
-    chat_memory[session_id].append(f"🖋️ You > {prompt}")
-    chat_memory[session_id].append(f"🧠 Codette > {response}")
-    chat_log = "\n".join(chat_memory[session_id][-10:])
-
-    img = None
-    if generate_image and image_enabled:
-        try:
-            img = image_generator(prompt).images[0]
-        except Exception as e:
-            chat_log += f"\n[Image error]: {e}"
-
-    vid = None
-    if generate_video and video_enabled:
-        try:
-            video_frames = video_pipeline(prompt, num_inference_steps=50).frames
-            temp_video_path = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False).name
-            imageio.mimsave(temp_video_path, video_frames, fps=8)
-            vid = temp_video_path
-        except Exception as e:
-            chat_log += f"\n[Video error]: {e}"
-
-    return chat_log, img, vid
-
-# ---------- Gradio UI ----------
-with gr.Blocks(title="Codette Terminal – Text + Image + Video") as demo:
-    gr.Markdown("## 🧬 Codette Terminal (Text + Image + Video, CPU-Friendly)")
-    gr.Markdown("Type a prompt and select your model. Optionally generate images or videos. Type `'exit'` to reset session.")
-
-    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, interactive=image_enabled)
-    generate_video_toggle = gr.Checkbox(label="Also generate video?", value=False, interactive=video_enabled)
-    user_input = gr.Textbox(label="Your Prompt", placeholder="e.g. A robot dreaming on Mars", lines=1)
-    output_text = gr.Textbox(label="Codette Output", lines=15, interactive=False)
-    output_image = gr.Image(label="Generated Image")
-    output_video = gr.Video(label="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]
-    )
-
-if __name__ == "__main__":
-    demo.launch()