Update app.py from anycoder

app.py

@@ -1,217 +1,136 @@
 import gradio as gr
-import os
-import cv2
-import numpy as np
-from moviepy.editor import *
-
-from diffusers import StableDiffusionInstructPix2PixPipeline
-import torch
-from PIL import Image, ImageOps
-import time
-import psutil
-import math
 import random
-
-# Initialize the pipeline
-pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained("timbrooks/instruct-pix2pix", torch_dtype=torch.float16, safety_checker=None)
-
-device = "GPU 🔥" if torch.cuda.is_available() else "CPU 🥶"
-
-if torch.cuda.is_available():
-    pipe = pipe.to("cuda")
-
-def pix2pix(
-        input_image: Image.Image,
-        instruction: str,
-        steps: int,
-        seed: int,
-        text_cfg_scale: float,
-        image_cfg_scale: float,
-    ):
-
-        width, height = input_image.size
-        factor = 512 / max(width, height)
-        factor = math.ceil(min(width, height) * factor / 64) * 64 / min(width, height)
-        width = int((width * factor) // 64) * 64
-        height = int((height * factor) // 64) * 64
-        input_image = ImageOps.fit(input_image, (width, height), method=Image.Resampling.LANCZOS)
-
-        if instruction == "":
-            return [input_image, seed]
-
-        generator = torch.manual_seed(seed)
-        edited_image = pipe(
-            instruction, image=input_image,
-            guidance_scale=text_cfg_scale, image_guidance_scale=image_cfg_scale,
-            num_inference_steps=steps, generator=generator,
-        ).images[0]
-        print(f"EDITED: {edited_image}")
-        return edited_image
-
-def get_frames(video_in):
-    frames = []
-    #resize the video
-    clip = VideoFileClip(video_in)
-
-    #check fps
-    if clip.fps > 30:
-        print("vide rate is over 30, resetting to 30")
-        clip_resized = clip.resize(height=512)
-        clip_resized.write_videofile("video_resized.mp4", fps=30)
-    else:
-        print("video rate is OK")
-        clip_resized = clip.resize(height=512)
-        clip_resized.write_videofile("video_resized.mp4", fps=clip.fps)
-
-    print("video resized to 512 height")
-
-    # Opens the Video file with CV2
-    cap= cv2.VideoCapture("video_resized.mp4")
-
-    fps = cap.get(cv2.CAP_PROP_FPS)
-    print("video fps: " + str(fps))
-    i=0
-    while(cap.isOpened()):
-        ret, frame = cap.read()
-        if ret == False:
-            break
-        cv2.imwrite('kang'+str(i)+'.jpg',frame)
-        frames.append('kang'+str(i)+'.jpg')
-        i+=1
-
-    cap.release()
-    cv2.destroyAllWindows()
-    print("broke the video into frames")
-
-    return frames, fps
-
-def create_video(frames, fps):
-    print("building video result")
-    clip = ImageSequenceClip(frames, fps=fps)
-    clip.write_videofile("movie.mp4", fps=fps)
-
-    return 'movie.mp4'
-
-def infer(prompt,video_in, seed_in, trim_value):
-    print(prompt)
-    break_vid = get_frames(video_in)
-
-    frames_list= break_vid[0]
-    fps = break_vid[1]
-    n_frame = int(trim_value*fps)
-
-    if n_frame >= len(frames_list):
-        print("video is shorter than the cut value")
-        n_frame = len(frames_list)
-
-    result_frames = []
-    print("set stop frames to: " + str(n_frame))
-
-    for i in frames_list[0:int(n_frame)]:
-        pil_i = Image.open(i).convert("RGB")
-
-        pix2pix_img = pix2pix(pil_i, prompt, 50, seed_in, 7.5, 1.5)
-        #print(pix2pix_img)
-        #image = Image.open(pix2pix_img)
-        #rgb_im = image.convert("RGB")
-
-        # exporting the image
-        pix2pix_img.save(f"result_img-{i}.jpg")
-        result_frames.append(f"result_img-{i}.jpg")
-        print("frame " + i + "/" + str(n_frame) + ": done;")
-
-    final_vid = create_video(result_frames, fps)
-    print("finished !")
-
-    return final_vid
-
-title = """
-    <div style="text-align: center; max-width: 700px; margin: 0 auto;">
-        <div
-        style="
-            display: inline-flex;
-            align-items: center;
-            gap: 0.8rem;
-            font-size: 1.75rem;
-        "
-        >
-        <h1 style="font-weight: 900; margin-bottom: 7px; margin-top: 5px;">
-            Pix2Pix Video
-        </h1>
-        </div>
-        <p style="margin-bottom: 10px; font-size: 94%">
-        Apply Instruct Pix2Pix Diffusion to a video
-        </p>
-    </div>
-"""
-
-article = """
-
-    <div class="footer">
-        <p>
-        Examples by <a href="https://twitter.com/CitizenPlain" target="_blank">Nathan Shipley</a> •&nbsp;
-        Follow <a href="https://twitter.com/fffiloni" target="_blank">Sylvain Filoni</a> for future updates 🤗
-        </p>
-    </div>
-    <div id="may-like-container" style="display: flex;justify-content: center;flex-direction: column;align-items: center;margin-bottom: 30px;">
-        <p>You may also like: </p>
-        <div id="may-like-content" style="display:flex;flex-wrap: wrap;align-items:center;height:20px;">
-
-            <svg height="20" width="162" style="margin-left:4px;margin-bottom: 6px;">
-                 <a href="https://huggingface.co/spaces/timbrooks/instruct-pix2pix" target="_blank">
-                    <image href="https://img.shields.io/badge/🤗 Spaces-Instruct_Pix2Pix-blue" src="https://img.shields.io/badge/🤗 Spaces-Instruct_Pix2Pix-blue.png" height="20"/>
-                 </a>
-            </svg>
-
-        </div>
-
-    </div>
-
-"""
-
-# Create the Gradio 6 interface
+import time
+from datetime import datetime
+
+# Simple AI Chatbot Model
+class SimpleChatbot:
+    def __init__(self):
+        self.responses = {
+            "greetings": ["Hello!", "Hi there!", "Greetings!", "Nice to meet you!"],
+            "farewells": ["Goodbye!", "See you later!", "Take care!", "Farewell!"],
+            "thanks": ["You're welcome!", "No problem!", "Happy to help!", "Anytime!"],
+            "questions": ["That's an interesting question!", "Let me think about that...", "I'll get back to you on that!"],
+            "default": ["I see.", "Interesting!", "Tell me more.", "Go on...", "I'm listening."]
+        }
+
+    def respond(self, message, history):
+        message = message.lower()
+
+        # Simple intent detection
+        if any(word in message for word in ["hi", "hello", "hey", "greetings"]):
+            response = random.choice(self.responses["greetings"])
+        elif any(word in message for word in ["bye", "goodbye", "farewell", "see you"]):
+            response = random.choice(self.responses["farewells"])
+        elif any(word in message for word in ["thank", "thanks", "appreciate"]):
+            response = random.choice(self.responses["thanks"])
+        elif "?" in message:
+            response = random.choice(self.responses["questions"])
+        else:
+            response = random.choice(self.responses["default"])
+
+        # Add timestamp to response
+        timestamp = datetime.now().strftime("%H:%M:%S")
+        full_response = f"[{timestamp}] AI: {response}"
+
+        return full_response
+
+# Create chatbot instance
+chatbot = SimpleChatbot()
+
+# Custom theme for modern look
+custom_theme = gr.themes.Soft(
+    primary_hue="blue",
+    secondary_hue="indigo",
+    neutral_hue="slate",
+    font=gr.themes.GoogleFont("Inter"),
+    text_size="lg",
+    spacing_size="lg",
+    radius_size="md"
+).set(
+    button_primary_background_fill="*primary_600",
+    button_primary_background_fill_hover="*primary_700",
+    block_title_text_weight="600",
+)
+
+# Create Gradio interface
 with gr.Blocks() as demo:
-    with gr.Column(elem_id="col-container"):
-        gr.HTML(title)
-        with gr.Row():
-            with gr.Column():
-                video_inp = gr.Video(label="Video source", sources=["upload"], elem_id="input-vid")
-                prompt = gr.Textbox(label="Prompt", placeholder="enter prompt", show_label=False, elem_id="prompt-in")
-                with gr.Row():
-                    seed_inp = gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1, value=123456)
-                    trim_in = gr.Slider(label="Cut video at (s)", minimum=1, maximum=5, step=1, value=1)
-            with gr.Column():
-                video_out = gr.Video(label="Pix2pix video result", elem_id="video-output")
-                gr.HTML("""
-                <a style="display:inline-block" href="https://huggingface.co/spaces/fffiloni/Pix2Pix-Video?duplicate=true"><img src="https://img.shields.io/badge/-Duplicate%20Space-blue?labelColor=white&style=flat&logo=data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAABAAAAAQCAYAAAAf8/9hAAAAAXNSR0IArs4c6QAAAP5JREFUOE+lk7FqAkEURY+ltunEgFXS2sZGIbXfEPdLlnxJyDdYB62sbbUKpLbVNhyYFzbrrA74YJlh9r079973psed0cvUD4A+4HoCjsA85X0Dfn/RBLBgBDxnQPfAEJgBY+A9gALA4tcbamSzS4xq4FOQAJgCDwV2CPKV8tZAJcAjMMkUe1vX+U+SMhfAJEHasQIWmXNN3abzDwHUrgcRGmYcgKe0bxrblHEB4E/pndMazNpSZGcsZdBlYJcEL9Afo75molJyM2FxmPgmgPqlWNLGfwZGG6UiyEvLzHYDmoPkDDiNm9JR9uboiONcBXrpY1qmgs21x1QwyZcpvxt9NS09PlsPAAAAAElFTkSuQmCC&logoWidth=14" alt="Duplicate Space"></a>
-                work with longer videos / skip the queue:
-                """, elem_id="duplicate-container")
-                submit_btn = gr.Button("Generate Pix2Pix video")
-
-        inputs = [prompt,video_inp,seed_inp, trim_in]
-        outputs = [video_out]
-
-        ex = gr.Examples(
-            [
-                ["Make it a marble sculpture", "./examples/pexels-jill-burrow-7665249_512x512.mp4", 422112651, 4],
-                ["Make it molten lava", "./examples/Ocean_Pexels_ 8953474_512x512.mp4", 43571876, 4]
-            ],
-            inputs=inputs,
-        )
-
-        gr.HTML(article)
-
-    submit_btn.click(infer, inputs=inputs, outputs=outputs)
-
-# Launch with Gradio 6 syntax - all parameters in launch()
-demo.queue(max_size=12).launch(
-    theme=gr.themes.Soft(
-        primary_hue="pink",
-        secondary_hue="purple",
-        font=gr.themes.GoogleFont("IBM Plex Sans")
-    ),
-    css_paths=["style.css"],
+    gr.Markdown("# 🤖 AI Chatbot")
+    gr.Markdown("Built with anycoder - A simple AI chatbot for conversation")
+
+    with gr.Row():
+        with gr.Column(scale=3):
+            chatbot_interface = gr.Chatbot(
+                label="Chat with AI",
+                height=500,
+                avatar_images=(
+                    "https://gradio-builds.s3.amazonaws.com/assets/user-avatar.png",
+                    "https://gradio-builds.s3.amazonaws.com/assets/bot-avatar.png"
+                ),
+                show_label=False
+            )
+            message_input = gr.Textbox(
+                label="Your Message",
+                placeholder="Type your message here...",
+                lines=2,
+                show_label=False
+            )
+
+        with gr.Column(scale=1):
+            gr.Markdown("## Features")
+            gr.Markdown("""
+            - ✅ Simple AI responses
+            - ✅ Conversation history
+            - ✅ Timestamped messages
+            - ✅ User-friendly interface
+            """)
+
+            gr.Markdown("## How to Use")
+            gr.Markdown("""
+            1. Type your message in the input box
+            2. Press Enter or click Send
+            3. The AI will respond automatically
+            4. Continue the conversation naturally
+            """)
+
+            clear_btn = gr.Button("🔄 Clear Chat", variant="secondary")
+
+    # Chatbot logic
+    def user_message(user_msg, history):
+        return "", history + [[user_msg, None]]
+
+    def bot_response(history):
+        user_msg = history[-1][0]
+        bot_msg = chatbot.respond(user_msg, history)
+        history[-1][1] = bot_msg
+        return history
+
+    # Event listeners
+    message_input.submit(
+        user_message,
+        [message_input, chatbot_interface],
+        [message_input, chatbot_interface],
+        queue=False
+    ).then(
+        bot_response,
+        [chatbot_interface],
+        [chatbot_interface]
+    )
+
+    clear_btn.click(
+        lambda: None,
+        None,
+        chatbot_interface,
+        queue=False
+    )
+
+# Launch with custom theme and footer
+demo.launch(
+    theme=custom_theme,
     footer_links=[
-        {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"}
-    ]
+        {"label": "Built with anycoder", "url": "https://huggingface.co/spaces/akhaliq/anycoder"},
+        {"label": "Gradio Docs", "url": "https://gradio.app/docs"}
+    ],
+    title="AI Chatbot",
+    description="A simple AI chatbot for conversation using Gradio"
 )