{ "cells": [ { "cell_type": "code", "execution_count": 1, "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "Running on local URL: http://127.0.0.1:7863\n", "Running on public URL: https://cf43e4871c9bab7308.gradio.live\n", "\n", "This share link expires in 72 hours. For free permanent hosting and GPU upgrades, run `gradio deploy` from Terminal to deploy to Spaces (https://huggingface.co./spaces)\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [] }, "execution_count": 1, "metadata": {}, "output_type": "execute_result" } ], "source": [ "import os\n", "import gradio as gr\n", "from dotenv import load_dotenv, find_dotenv\n", "_ = load_dotenv(find_dotenv())\n", "\n", "from langchain.chains import ConversationChain\n", "from langchain.chat_models import ChatOpenAI\n", "from langchain.memory import ConversationBufferMemory\n", "\n", "llm = ChatOpenAI(temperature=0.0)\n", "memory = ConversationBufferMemory()\n", "conversion = ConversationChain(\n", " llm=llm,\n", " memory=memory,\n", " verbose=False\n", ")\n", "\n", "def takeinput(name):\n", " output_str = conversion.predict(input=name)\n", " return output_str\n", "\n", "demo = gr.Interface(\n", " fn=takeinput,\n", " inputs=[\"text\"],\n", " outputs=[\"text\"]\n", ")\n", "\n", "demo.launch(share=True)\n" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.11.4" } }, "nbformat": 4, "nbformat_minor": 4 }