xixi

app.py

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+import gradio as gr
+
+from tabs.audit import audit_tab
+from tabs.ocr import ocr_tab
+from tabs.helloworld import hello_world_tab
+from tabs.chatbot import chatbot_tab
+from tabs.openai import openai_tab
+
+gr.close_all()
+
+css_string = """
+#ddd1233 .user {
+    min-width: 100px;
+    max-width: 500px;
+    width: auto;
+}
+#ddd1233 .bot {
+    min-width: 100px;
+    max-width: 500px;
+    width: auto;
+}
+"""
+
+with gr.Blocks(css=css_string) as demo:
+    gr.Markdown("""
+        # gradio分享呀
+    """)
+    hello_world_tab()
+    audit_tab()
+    ocr_tab()
+    chatbot_tab()
+    openai_tab()
+
+demo.launch()

tabs/audit.py

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+import gradio as gr
+import requests
+
+
+def audit_text(text, url):
+    data = {
+        "text": text,
+        "source": "ALIYUN",
+        "model": "ALIYUN_TEXT_AUDIT"
+    }
+    res = requests.post(url, json=data)
+    data = res.json()
+
+    is_pass = data.get('data', {}).get('pass')
+    if is_pass:
+        return data, f'合规'
+    return data, '不合规'
+
+
+def audit_tab():
+    with gr.Tab("关键词审核"):
+        with gr.Row():
+            url_input = gr.Textbox(label='接口链接')
+            text_input = gr.Textbox(label="待审核的关键词", lines=10)
+        gr.Examples(['你是傻逼吧', '你是天才'], inputs=text_input)
+        with gr.Row():
+            text_output = gr.Json(label="结果", lines=10)
+            label_output = gr.Label()
+        text_button = gr.Button('检测')
+
+    text_button.click(audit_text, inputs=[text_input, url_input], outputs=[text_output, label_output])

tabs/chatbot.py

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+import time
+
+import gradio as gr
+
+
+def chatbot_tab():
+    with gr.Tab("chat bot"):
+        chatbot = gr.Chatbot(label='对话框', elem_id='ddd1233')
+        msg = gr.Textbox()
+        clear = gr.Button("Clear")
+
+        def user(user_message, history):
+            return "", history + [[user_message, None]]
+
+        def bot(history):
+            history[-1][1] = f"你说: {history[-1][0]}"
+            time.sleep(1)
+            return history
+
+        msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
+            bot, chatbot, chatbot
+        )
+        clear.click(lambda: None, None, chatbot, queue=False)

tabs/helloworld.py

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+import gradio as gr
+
+
+def hello_world(name, request: gr.Request):
+    return f'Hello {name}!'
+
+
+def hello_world_tab():
+    with gr.Tab("hello world!"):
+        with gr.Row():
+            text_input = gr.Textbox(label='姓名', placeholder='请输入你的姓名')
+            text_output = gr.Textbox(label="结果", lines=10)
+        text_button = gr.Button('hello world')
+
+    text_button.click(hello_world, inputs=text_input, outputs=text_output)

tabs/ocr.py

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+import gradio as gr
+import requests
+
+
+request_method_map = {
+    '同步': 'sync',
+    '异步': 'async',
+}
+
+tasks_map = {
+    '关键词提取': 'keywords',
+    'ocr': 'ocr',
+    '表格': 'ocr_table',
+}
+
+subtask_map = {
+    '身份证': 'id_card',
+    '信息表': 'inform_table',
+    '营业执照': 'bus_lic',
+    '银行卡信息': 'bank_info',
+    '用户信息采集表': 'user_info_collect',
+}
+
+
+def ocr_task(request_method, tasks, subtask, file, url):
+    """
+
+    :param request_method:
+    :param tasks:
+    :param subtask:
+    :param file:
+    :param url:
+    :return:
+    """
+    res = requests.post(url, data={
+        'file': file,
+        'request_method': request_method_map.get(request_method),
+        'tasks': tasks_map.get(tasks),
+        'subtask': subtask_map.get(subtask),
+        'angle': 0,
+    })
+    return str(res.json())
+
+
+def ocr_tab():
+    with gr.Tab("ocr 识别"):
+        gr.Markdown('ocr 工具')
+        with gr.Accordion("说明", open=False):
+            gr.Markdown("""
+            # Hello World!
+            嘤嘤嘤
+            嘻嘻嘻
+            """)
+
+        with gr.Row():
+            url_input = gr.Textbox(label='接口链接')
+            request_method = gr.Dropdown(choices=list(request_method_map.keys()), label='运行方式')
+            tasks = gr.Dropdown(choices=list(tasks_map.keys()), label='模式')
+            subtask = gr.Dropdown(choices=list(subtask_map.keys()), label='文件类型')
+            file = gr.File(type='file')
+        text_output = gr.Textbox(label="结果", lines=10)
+        text_button = gr.Button('识别')
+
+    text_button.click(ocr_task, inputs=[request_method, tasks, subtask, file, url_input], outputs=text_output)

tabs/openai.py

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+import gradio as gr
+import openai
+
+
+def generate_image(prompt, api_key):
+    # api_key = os.environ.get('OPENAI_API_KEY')
+    if not api_key:
+        raise gr.Error("缺少OPENAI_API_KEY")
+
+    response = openai.Image.create(
+        prompt=prompt,
+        n=1,
+        size="1024x1024",
+        api_key=api_key
+    )
+    image_url = response['data'][0]['url']
+    return image_url
+
+
+def audio(file, api_key):
+    if not api_key:
+        raise gr.Error("缺少OPENAI_API_KEY")
+
+    with open(file, 'rb') as f:
+        transcript = openai.Audio.transcribe(model="whisper-1", file=f,
+                                             api_key=api_key)
+        return transcript['text']
+
+
+def openai_tab():
+    with gr.Tab("openai"):
+        gr.Markdown('### 文字生成图片')
+        api_key_input = gr.Textbox(label='OPENAI_API_KEY', placeholder='请输入你的OPENAI_API_KEY', type='password')
+
+        with gr.Row():
+            text_input = gr.Textbox(label='请输入你的创意', placeholder='请输入你的创意')
+            text_output = gr.Image(label="图片")
+        text_button = gr.Button('生成创意')
+        text_button.click(generate_image, inputs=[text_input, api_key_input], outputs=text_output)
+
+        gr.Markdown('### 音频识别')
+        with gr.Row():
+            file_input = gr.Audio(label='音频文件', type='filepath')
+            text_output = gr.Text()
+        text_button = gr.Button('音频识别')
+        text_button.click(audio, inputs=[file_input, api_key_input], outputs=text_output)
+
+
+