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README.md

@@ -1,12 +1,12 @@
+
 ---
-title: Chatbot Retry Undo Like
-emoji: 🦀
-colorFrom: red
+title: chatbot_retry_undo_like 
+emoji: 🔥
+colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 4.44.1
-app_file: app.py
+sdk_version: 5.0.0
+app_file: run.py
 pinned: false
+hf_oauth: true
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

@@ -0,0 +1 @@
+huggingface_hub

run.ipynb

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+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: chatbot_retry_undo_like"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio huggingface_hub "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["from huggingface_hub import InferenceClient\n", "import gradio as gr\n", "\n", "client = InferenceClient()\n", "\n", "def respond(\n", "    prompt: str,\n", "    history,\n", "):\n", "    if not history:\n", "        history = [{\"role\": \"system\", \"content\": \"You are a friendly chatbot\"}]\n", "    history.append({\"role\": \"user\", \"content\": prompt})\n", "\n", "    yield history\n", "\n", "    response = {\"role\": \"assistant\", \"content\": \"\"}\n", "    for message in client.chat_completion( # type: ignore\n", "        history,\n", "        temperature=0.95,\n", "        top_p=0.9,\n", "        max_tokens=512,\n", "        stream=True,\n", "        model=\"HuggingFaceH4/zephyr-7b-beta\"\n", "    ):\n", "        response[\"content\"] += message.choices[0].delta.content or \"\"\n", "        yield history + [response]\n", "\n", "\n", "def handle_undo(history, undo_data: gr.UndoData):\n", "    return history[:undo_data.index], history[undo_data.index]['content']\n", "\n", "def handle_retry(history, retry_data: gr.RetryData):\n", "    new_history = history[:retry_data.index]\n", "    previous_prompt = history[retry_data.index]['content']\n", "    yield from respond(previous_prompt, new_history)\n", "\n", "\n", "def handle_like(data: gr.LikeData):\n", "    if data.liked:\n", "        print(\"You upvoted this response: \", data.value)\n", "    else:\n", "        print(\"You downvoted this response: \", data.value)\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    gr.Markdown(\"# Chat with Hugging Face Zephyr 7b \ud83e\udd17\")\n", "    chatbot = gr.Chatbot(\n", "        label=\"Agent\",\n", "        type=\"messages\",\n", "        avatar_images=(\n", "            None,\n", "            \"https://em-content.zobj.net/source/twitter/376/hugging-face_1f917.png\",\n", "        ),\n", "    )\n", "    prompt = gr.Textbox(max_lines=1, label=\"Chat Message\")\n", "    prompt.submit(respond, [prompt, chatbot], [chatbot])\n", "    prompt.submit(lambda: \"\", None, [prompt])\n", "    chatbot.undo(handle_undo, chatbot, [chatbot, prompt])\n", "    chatbot.retry(handle_retry, chatbot, [chatbot])\n", "    chatbot.like(handle_like, None, None)\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

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+from huggingface_hub import InferenceClient
+import gradio as gr
+
+client = InferenceClient()
+
+def respond(
+    prompt: str,
+    history,
+):
+    if not history:
+        history = [{"role": "system", "content": "You are a friendly chatbot"}]
+    history.append({"role": "user", "content": prompt})
+
+    yield history
+
+    response = {"role": "assistant", "content": ""}
+    for message in client.chat_completion( # type: ignore
+        history,
+        temperature=0.95,
+        top_p=0.9,
+        max_tokens=512,
+        stream=True,
+        model="HuggingFaceH4/zephyr-7b-beta"
+    ):
+        response["content"] += message.choices[0].delta.content or ""
+        yield history + [response]
+
+
+def handle_undo(history, undo_data: gr.UndoData):
+    return history[:undo_data.index], history[undo_data.index]['content']
+
+def handle_retry(history, retry_data: gr.RetryData):
+    new_history = history[:retry_data.index]
+    previous_prompt = history[retry_data.index]['content']
+    yield from respond(previous_prompt, new_history)
+
+
+def handle_like(data: gr.LikeData):
+    if data.liked:
+        print("You upvoted this response: ", data.value)
+    else:
+        print("You downvoted this response: ", data.value)
+
+
+with gr.Blocks() as demo:
+    gr.Markdown("# Chat with Hugging Face Zephyr 7b 🤗")
+    chatbot = gr.Chatbot(
+        label="Agent",
+        type="messages",
+        avatar_images=(
+            None,
+            "https://em-content.zobj.net/source/twitter/376/hugging-face_1f917.png",
+        ),
+    )
+    prompt = gr.Textbox(max_lines=1, label="Chat Message")
+    prompt.submit(respond, [prompt, chatbot], [chatbot])
+    prompt.submit(lambda: "", None, [prompt])
+    chatbot.undo(handle_undo, chatbot, [chatbot, prompt])
+    chatbot.retry(handle_retry, chatbot, [chatbot])
+    chatbot.like(handle_like, None, None)
+
+
+if __name__ == "__main__":
+    demo.launch()