initial commit

app.py

@@ -0,0 +1,122 @@
+import os
+import re
+import pickle
+import base64
+import requests
+import argparse
+import numpy as np
+import gradio as gr
+
+from functools import partial
+from PIL import Image
+
+SERVER_URL = os.getenv('SERVER_URL')
+
+
+def get_images(state):
+    history = ''
+    for i in range(len(state)):
+        for j in range(len(state[i])):
+            history += state[i][j] + '\n'
+    for image_path in re.findall('image/[0-9,a-z]+\.png', history):
+        if os.path.exists(image_path):
+            continue
+        data = {'method': 'get_image', 'args': [image_path], 'kwargs': {}}
+        data = base64.b64encode(pickle.dumps(data)).decode('utf-8')
+        response = requests.post(SERVER_URL, json=data)
+        image = pickle.loads(base64.b64decode(response.json().encode('utf-8')))
+        image.save(image_path)
+
+
+def bot_request(method, *args, **kwargs):
+    data = {'method': method, 'args': args, 'kwargs': kwargs}
+    data = base64.b64encode(pickle.dumps(data)).decode('utf-8')
+    response = requests.post(SERVER_URL, json=data)
+    response = pickle.loads(base64.b64decode(response.json().encode('utf-8')))
+    if response is not None:
+        state = response[0]
+        get_images(state)
+    return response
+
+
+if __name__ == '__main__':
+    parser = argparse.ArgumentParser()
+    parser.add_argument('--temperature', type=float, default=0.0, help='temperature for the llm model')
+    parser.add_argument('--max_new_tokens', type=int, default=128, help='max number of new tokens to generate')
+    parser.add_argument('--top_p', type=float, default=1.0, help='top_p for the llm model')
+    parser.add_argument('--top_k', type=int, default=40, help='top_k for the llm model')
+    parser.add_argument('--num_beams', type=int, default=4, help='num_beams for the llm model')
+    parser.add_argument('--keep_last_n_paragraphs', type=int, default=1, help='keep last n paragraphs in the memory')
+    args = parser.parse_args()
+
+    examples = [
+        ['images/example-1.jpg', 'What is unusual about this image?'],
+        ['images/example-2.jpg', 'Make the image look like a cartoon.'],
+        ['images/example-3.jpg', 'Segment the tie in the image.'],
+        ['images/example-4.jpg', 'Generate a man watching a sea based on the pose of the woman.'],
+        ['images/example-5.jpg', 'Replace the dog with a cat.'],
+    ]
+
+    if not os.path.exists('image'):
+        os.makedirs('image')
+
+    with gr.Blocks() as demo:
+        with gr.Row():
+            with gr.Column(scale=0.3):
+                with gr.Row():
+                    image = gr.Image(type="pil", label="input image")
+                with gr.Row():
+                    txt = gr.Textbox(lines=7, show_label=False, elem_id="textbox",
+                                     placeholder="Enter text and press submit, or upload an image").style(container=False)
+                with gr.Row():
+                    submit = gr.Button("Submit")
+                with gr.Row():
+                    clear = gr.Button("Clear")
+                with gr.Row():
+                    keep_last_n_paragraphs = gr.Slider(
+                        minimum=0,
+                        maximum=3,
+                        value=args.keep_last_n_paragraphs,
+                        step=1,
+                        interactive=True,
+                        label="Remember Last N Paragraphs")
+                    max_new_token = gr.Slider(
+                        minimum=128,
+                        maximum=1024,
+                        value=args.max_new_tokens,
+                        step=64,
+                        interactive=True,
+                        label="Max New Tokens")
+                    temperature = gr.Slider(
+                        minimum=0.0,
+                        maximum=1.0,
+                        value=args.temperature,
+                        step=0.1,
+                        interactive=True,
+                        label="Temperature")
+                    top_p = gr.Slider(
+                        minimum=0.0,
+                        maximum=1.0,
+                        value=args.top_p,
+                        step=0.1,
+                        interactive=True,
+                        label="Top P")
+            with gr.Column(scale=0.7):
+                chatbot = gr.Chatbot(elem_id="chatbot", label="🦙 GPT4Tools").style(height=690)
+                state = gr.State([])
+
+            txt.submit(partial(bot_request, 'run_text'), [txt, state], [chatbot, state])
+            txt.submit(lambda: "", None, txt)
+            image.upload(lambda: "", None, txt)
+            submit.click(partial(bot_request, 'run_image'), [image, state, txt], [chatbot, state, txt]).then(
+                partial(bot_request, 'run_text'), [txt, state, temperature, top_p, max_new_token, keep_last_n_paragraphs], [chatbot, state, txt]).then(
+                    lambda: None, None, image)
+            clear.click(partial(bot_request, 'clear'))
+            clear.click(lambda: [], None, chatbot)
+            clear.click(lambda: [], None, state)
+        with gr.Row():
+            gr.Examples(
+                examples=examples,
+                inputs=[image, txt],
+            )
+        demo.launch()

requirements.txt

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+requests
+base64
+numpy
+gradio
+pillow
+functools