Update app.py

app.py

@@ -1,63 +1,147 @@
 import gradio as gr
-from huggingface_hub import InferenceClient
-
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("Groq/Llama-3-Groq-8B-Tool-Use")
-
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
-
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+# import os
+# import sys
+# from pathlib import Path
+import time
+
+models =[
+    "mann-e/Mann-E_Dreams",
+    "Yntec/ChickFlick",
+    "John6666/ultimate-realistic-mix-v2-sdxl",
+    "Yntec/CrystalReality",
+    "John6666/9527-detail-realistic-xl-v55mix-sdxl",
+    "John6666/epicrealism-xl-v8kiss-sdxl",
+    "John6666/wai-real-mix-v8-sdxl",
+    "John6666/real-vis-xl-v40-sdxl",
+    "Yntec/DegreesOfFreedom",
+
+]
+    
+
+model_functions = {}
+model_idx = 1
+for model_path in models:
+    try:
+        model_functions[model_idx] = gr.Interface.load(f"models/{model_path}", live=False, preprocess=True, postprocess=False)
+    except Exception as error:
+        def the_fn(txt):
+            
+            return None
+        model_functions[model_idx] = gr.Interface(fn=the_fn, inputs=["text"], outputs=["image"])
+        
+    model_idx+=1
+    
+
+def send_it_idx(idx):
+    def send_it_fn(prompt):
+        output = (model_functions.get(str(idx)) or model_functions.get(str(1)))(prompt)
+        return output
+    return send_it_fn
+
+def get_prompts(prompt_text):
+
+    return prompt_text
+
+def clear_it(val):
+    if int(val) != 0:
+        val = 0
+    else:
+        val = 0
+        pass
+    return val
+
+def all_task_end(cnt,t_stamp):
+    to = t_stamp + 360
+    et = time.time()
+    if et > to and t_stamp != 0:
+        d = gr.update(value=0)
+        tog = gr.update(value=1)
+        #print(f'to: {to}  et: {et}')
+    else:
+        if cnt != 0:
+            d = gr.update(value=et)
+        else:
+            d = gr.update(value=0)
+        tog = gr.update(value=0)
+        #print (f'passing:  to: {to}  et: {et}')
+        pass
+    return d, tog
+
+def all_task_start():
+    print("\n\n\n\n\n\n\n")
+    t = time.gmtime()
+    t_stamp = time.time()
+    current_time = time.strftime("%H:%M:%S", t)
+    return gr.update(value=t_stamp), gr.update(value=t_stamp), gr.update(value=0)
+
+def clear_fn():
+    nn = len(models)
+    return tuple([None, *[None for _ in range(nn)]])
+
+
+with gr.Blocks(title="SD Models") as my_interface:
+    with gr.Column(scale=12):
+        # with gr.Row():
+        #     gr.Markdown("""- Primary prompt: 你想画的内容(英文单词，如 a cat, 加英文逗号效果更好；点 Improve 按钮进行完善)\n- Real prompt: 完善后的提示词，出现后再点右边的 Run 按钮开始运行""")
+        with gr.Row():
+            with gr.Row(scale=6):
+                primary_prompt=gr.Textbox(label="Prompt", value="")
+                # real_prompt=gr.Textbox(label="Real prompt")
+            with gr.Row(scale=6):
+                # improve_prompts_btn=gr.Button("Improve")
+                with gr.Row():
+                    run=gr.Button("Run",variant="primary")
+                    clear_btn=gr.Button("Clear")
+        with gr.Row():
+            sd_outputs = {}
+            model_idx = 1
+            for model_path in models:
+                with gr.Column(scale=3, min_width=320):
+                    with gr.Box():
+                        sd_outputs[model_idx] = gr.Image(label=model_path)
+                    pass
+                model_idx += 1
+                pass
+            pass
+
+        with gr.Row(visible=False):
+            start_box=gr.Number(interactive=False)
+            end_box=gr.Number(interactive=False)
+            tog_box=gr.Textbox(value=0,interactive=False)
+
+        start_box.change(
+            all_task_end,
+            [start_box, end_box],
+            [start_box, tog_box],
+            every=1,
+            show_progress=True)
+
+        primary_prompt.submit(all_task_start, None, [start_box, end_box, tog_box])
+        run.click(all_task_start, None, [start_box, end_box, tog_box])
+        runs_dict = {}
+        model_idx = 1
+        for model_path in models:
+            runs_dict[model_idx] = run.click(model_functions[model_idx], inputs=[primary_prompt], outputs=[sd_outputs[model_idx]])
+            model_idx += 1
+            pass
+        pass
+
+        # improve_prompts_btn_clicked=improve_prompts_btn.click(
+        #     get_prompts,
+        #     inputs=[primary_prompt],
+        #     outputs=[primary_prompt],
+        #     cancels=list(runs_dict.values()))
+        clear_btn.click(
+            clear_fn,
+            None,
+            [primary_prompt, *list(sd_outputs.values())],
+            cancels=[*list(runs_dict.values())])
+        tog_box.change(
+            clear_it,
+            tog_box,
+            tog_box,
+            cancels=[*list(runs_dict.values())])
+text_gen1=gr.Interface.load("spaces/phenomenon1981/MagicPrompt-Stable-Diffusion")
+
+my_interface.queue(concurrency_count=600, status_update_rate=1)
+my_interface.launch(inline=True, show_api=True)