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README.md

@@ -5,7 +5,7 @@ emoji: 🔥
 colorFrom: indigo
 colorTo: indigo
 sdk: gradio
-sdk_version: 5.49.1
+sdk_version: 6.0.0
 app_file: run.py
 pinned: false
 hf_oauth: true

requirements.txt

@@ -1,3 +1,3 @@
-gradio-client @ git+https://github.com/gradio-app/gradio@e05eb8df38a4ca20993e94ca4e209cf8110bb677#subdirectory=client/python
-https://gradio-pypi-previews.s3.amazonaws.com/e05eb8df38a4ca20993e94ca4e209cf8110bb677/gradio-5.49.1-py3-none-any.whl
+gradio-client @ git+https://github.com/gradio-app/gradio@d007e6cf617baba5c62e49ec2b7ce278aa863a79#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/d007e6cf617baba5c62e49ec2b7ce278aa863a79/gradio-6.0.0-py3-none-any.whl
 transformers>=4.47.0

run.ipynb

@@ -1 +1 @@
-{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: agent_chatbot"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio transformers>=4.47.0"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from dataclasses import asdict\n", "from transformers import Tool, ReactCodeAgent  # type: ignore\n", "from transformers.agents import stream_to_gradio, HfApiEngine  # type: ignore\n", "\n", "# Import tool from Hub\n", "image_generation_tool = Tool.from_space(  # type: ignore\n", "    space_id=\"black-forest-labs/FLUX.1-schnell\",\n", "    name=\"image_generator\",\n", "    description=\"Generates an image following your prompt. Returns a PIL Image.\",\n", "    api_name=\"/infer\",\n", ")\n", "\n", "llm_engine = HfApiEngine(\"Qwen/Qwen2.5-Coder-32B-Instruct\")\n", "# Initialize the agent with both tools and engine\n", "agent = ReactCodeAgent(tools=[image_generation_tool], llm_engine=llm_engine)\n", "\n", "\n", "def interact_with_agent(prompt, history):\n", "    messages = []\n", "    yield messages\n", "    for msg in stream_to_gradio(agent, prompt):\n", "        messages.append(asdict(msg))  # type: ignore\n", "        yield messages\n", "    yield messages\n", "\n", "\n", "demo = gr.ChatInterface(\n", "    interact_with_agent,\n", "    chatbot= gr.Chatbot(\n", "        label=\"Agent\",\n", "        type=\"messages\",\n", "        avatar_images=(\n", "            None,\n", "            \"https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png\",\n", "        ),\n", "    ),\n", "    examples=[\n", "        [\"Generate an image of an astronaut riding an alligator\"],\n", "        [\"I am writing a children's book for my daughter. Can you help me with some illustrations?\"],\n", "    ],\n", "    type=\"messages\",\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}
+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: agent_chatbot"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio transformers>=4.47.0"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from dataclasses import asdict\n", "from transformers import Tool, ReactCodeAgent  # type: ignore\n", "from transformers.agents import stream_to_gradio, HfApiEngine  # type: ignore\n", "\n", "# Import tool from Hub\n", "image_generation_tool = Tool.from_space(  # type: ignore\n", "    space_id=\"black-forest-labs/FLUX.1-schnell\",\n", "    name=\"image_generator\",\n", "    description=\"Generates an image following your prompt. Returns a PIL Image.\",\n", "    api_name=\"/infer\",\n", ")\n", "\n", "llm_engine = HfApiEngine(\"Qwen/Qwen2.5-Coder-32B-Instruct\")\n", "# Initialize the agent with both tools and engine\n", "agent = ReactCodeAgent(tools=[image_generation_tool], llm_engine=llm_engine)\n", "\n", "\n", "def interact_with_agent(prompt, history):\n", "    messages = []\n", "    yield messages\n", "    for msg in stream_to_gradio(agent, prompt):\n", "        messages.append(asdict(msg))  # type: ignore\n", "        yield messages\n", "    yield messages\n", "\n", "\n", "demo = gr.ChatInterface(\n", "    interact_with_agent,\n", "    chatbot= gr.Chatbot(\n", "        label=\"Agent\",\n", "        avatar_images=(\n", "            None,\n", "            \"https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png\",\n", "        ),\n", "    ),\n", "    examples=[\n", "        [\"Generate an image of an astronaut riding an alligator\"],\n", "        [\"I am writing a children's book for my daughter. Can you help me with some illustrations?\"],\n", "    ],\n", ")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -29,7 +29,6 @@ demo = gr.ChatInterface(
     interact_with_agent,
     chatbot= gr.Chatbot(
         label="Agent",
-        type="messages",
         avatar_images=(
             None,
             "https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png",
@@ -39,7 +38,6 @@ demo = gr.ChatInterface(
         ["Generate an image of an astronaut riding an alligator"],
         ["I am writing a children's book for my daughter. Can you help me with some illustrations?"],
     ],
-    type="messages",
 )
 
 if __name__ == "__main__":