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README.md

@@ -1,13 +1,12 @@
+
 ---
-title: Agent Chatbot
-emoji: 🌖
+title: agent_chatbot 
+emoji: 🔥
 colorFrom: indigo
-colorTo: red
+colorTo: indigo
 sdk: gradio
-sdk_version: 4.37.2
-app_file: app.py
+sdk_version: 4.38.0
+app_file: run.py
 pinned: false
-license: apache-2.0
+hf_oauth: true
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

@@ -1,2 +1 @@
-git+https://github.com/huggingface/transformers.git#egg=transformers[agents]
-https://gradio-builds.s3.amazonaws.com/542458a3d3185124a44c7400ebfb48012a508772/gradio-4.37.2-py3-none-any.whl
+git+https://github.com/huggingface/transformers.git#egg=transformers[agents]

run.ipynb

@@ -0,0 +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 git+https://github.com/huggingface/transformers.git#egg=transformers[agents]"]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# Downloading files from the demo repo\n", "import os\n", "!wget -q https://github.com/gradio-app/gradio/raw/main/demo/agent_chatbot/utils.py"]}, {"cell_type": "code", "execution_count": null, "id": "44380577570523278879349135829904343037", "metadata": {}, "outputs": [], "source": ["import gradio as gr\n", "from gradio import ChatMessage\n", "from transformers import load_tool, ReactCodeAgent, HfEngine\n", "from utils import stream_from_transformers_agent\n", "\n", "# Import tool from Hub\n", "image_generation_tool = load_tool(\"m-ric/text-to-image\")\n", "\n", "\n", "llm_engine = HfEngine(\"meta-llama/Meta-Llama-3-70B-Instruct\")\n", "# Initialize the agent with both tools\n", "agent = ReactCodeAgent(tools=[image_generation_tool], llm_engine=llm_engine)\n", "\n", "\n", "def interact_with_agent(prompt, messages):\n", "    messages.append(ChatMessage(role=\"user\", content=prompt))\n", "    yield messages\n", "    for msg in stream_from_transformers_agent(agent, prompt):\n", "        messages.append(msg)\n", "        yield messages\n", "    yield messages\n", "\n", "\n", "with gr.Blocks() as demo:\n", "    stored_message = gr.State([])\n", "    chatbot = gr.Chatbot(label=\"Agent\",\n", "                         type=\"messages\",\n", "                         avatar_images=(None, \"https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png\"))\n", "    text_input = gr.Textbox(lines=1, label=\"Chat Message\")\n", "    text_input.submit(lambda s: (s, \"\"), [text_input], [stored_message, text_input]).then(interact_with_agent, [stored_message, chatbot], [chatbot])\n", "\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

@@ -0,0 +1,34 @@
+import gradio as gr
+from gradio import ChatMessage
+from transformers import load_tool, ReactCodeAgent, HfEngine
+from utils import stream_from_transformers_agent
+
+# Import tool from Hub
+image_generation_tool = load_tool("m-ric/text-to-image")
+
+
+llm_engine = HfEngine("meta-llama/Meta-Llama-3-70B-Instruct")
+# Initialize the agent with both tools
+agent = ReactCodeAgent(tools=[image_generation_tool], llm_engine=llm_engine)
+
+
+def interact_with_agent(prompt, messages):
+    messages.append(ChatMessage(role="user", content=prompt))
+    yield messages
+    for msg in stream_from_transformers_agent(agent, prompt):
+        messages.append(msg)
+        yield messages
+    yield messages
+
+
+with gr.Blocks() as demo:
+    stored_message = gr.State([])
+    chatbot = gr.Chatbot(label="Agent",
+                         type="messages",
+                         avatar_images=(None, "https://em-content.zobj.net/source/twitter/53/robot-face_1f916.png"))
+    text_input = gr.Textbox(lines=1, label="Chat Message")
+    text_input.submit(lambda s: (s, ""), [text_input], [stored_message, text_input]).then(interact_with_agent, [stored_message, chatbot], [chatbot])
+
+
+if __name__ == "__main__":
+    demo.launch()