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Declare exports in __all__ for type checking (#10238)
* Declare exports * add changeset * type fixes * more type fixes * add changeset * notebooks * changes --------- Co-authored-by: gradio-pr-bot <[email protected]> Co-authored-by: Freddy Boulton <[email protected]> Co-authored-by: Abubakar Abid <[email protected]>
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fix:Declare exports in __all__ for type checking |
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{"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(\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))\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", " 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} |
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