Create app.py

app.py

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+import torch
+import gradio as gr
+from fastapi import FastAPI
+
+
+import os
+from PIL import Image
+
+import tempfile
+from transformers import TextStreamer
+from utils import title_markdown
+from utils import block_css
+from utils import tos_markdown
+from utils import learn_more_markdown
+
+#app = FastAPI()
+
+textbox = gr.Textbox(
+    show_label = False, placeholder = "Enter text and press ENTER", container = False
+)
+
+with gr.Blocks(title = '' ) as demo:
+    gr.Markdown(title_markdown)
+
+with gr.Blocks(title='MoE-LLaVA🚀')) as demo:
+    gr.Markdown(title_markdown)
+    state = gr.State()
+    state_ = gr.State()
+    first_run = gr.State()
+    images_tensor = gr.State()
+
+    with gr.Row():
+        with gr.Column(scale=3):
+            image1 = gr.Image(label="Input Document", type="filepath")
+
+            cur_dir = os.path.dirname(os.path.abspath(__file__))
+            print(cur_dir)
+            gr.Examples(
+                examples=[
+                    [
+                        f"demo.jfif",
+                        "What is unusual about this image?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "What are the things I should be cautious about when I visit here?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "If there are factual errors in the questions, point it out; if not, proceed answering the question. What’s happening in the desert?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "What is the title of this book?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "What type of food is the girl holding?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "What color is the train?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "What is the girl looking at?",
+                    ],
+                    [
+                        f"demo.jfif",
+                        "What might be the reason for the dog's aggressive behavior?",
+                    ],
+                ],
+                inputs=[image1, textbox],
+            )
+
+        # with gr.Column(scale=7):
+        #     #chatbot = gr.Chatbot(label="MoE-LLaVA", bubble_full_width=True).style(height=750)
+        #     with gr.Row():
+        #         with gr.Column(scale=8):
+        #             textbox.render()
+        #         with gr.Column(scale=1, min_width=50):
+        #             submit_btn = gr.Button(
+        #                 value="Send", variant="primary", interactive=True
+        #             )
+        #     with gr.Row(elem_id="buttons") as button_row:
+        #         upvote_btn = gr.Button(value="👍  Upvote", interactive=True)
+        #         downvote_btn = gr.Button(value="👎  Downvote", interactive=True)
+        #         flag_btn = gr.Button(value="⚠️  Flag", interactive=True)
+        #         # stop_btn = gr.Button(value="⏹️  Stop Generation", interactive=False)
+        #         regenerate_btn = gr.Button(value="🔄  Regenerate", interactive=True)
+        #         clear_btn = gr.Button(value="🗑️  Clear history", interactive=True)
+
+#    gr.Markdown(tos_markdown)
+#    gr.Markdown(learn_more_markdown)
+
+    # submit_btn.click(generate, [image1, textbox, first_run, state, state_, images_tensor],
+    #                  [state, state_, chatbot, first_run, textbox, images_tensor, image1])
+
+    # regenerate_btn.click(regenerate, [state, state_], [state, state_, chatbot, first_run]).then(
+    #     generate, [image1, textbox, first_run, state, state_, images_tensor],
+    #     [state, state_, chatbot, first_run, textbox, images_tensor, image1])
+
+    # clear_btn.click(clear_history, [state, state_],
+    #                 [image1, textbox, first_run, state, state_, chatbot, images_tensor])
+
+# app = gr.mount_gradio_app(app, demo, path="/")
+demo.launch()