{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "%load_ext autoreload\n", "%autoreload 2" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "GOOGLE_KEY = \"KEY::PROJECT_ID\"" ] }, { "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ "## Use GoogleVertexAPI" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from manifest import Manifest\n", "from manifest.connections.client_pool import ClientConnection\n", "\n", "google_bison = ClientConnection(\n", " client_name=\"google\",\n", " client_connection=GOOGLE_KEY\n", ")\n", "\n", "manifest = Manifest(client_pool=[google_bison])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "# Simple question\n", "print(manifest.run(\"What is your name\", max_tokens=40))" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "from manifest import Manifest\n", "from manifest.connections.client_pool import ClientConnection\n", "\n", "google_bison = ClientConnection(\n", " client_name=\"googlechat\",\n", " client_connection=GOOGLE_KEY\n", ")\n", "\n", "manifest = Manifest(client_pool=[google_bison])" ] }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ "chat_dict = [\n", " # {\"author\": \"bot\", \"content\": \"You are a helpful assistant.\"},\n", " {\"author\": \"user\", \"content\": \"Who won the world series in 2020?\"},\n", " {\"author\": \"bot\", \"content\": \"The Los Angeles Dodgers won the World Series in 2020.\"},\n", " {\"author\": \"user\", \"content\": \"Where was it played?\"}\n", "]\n", "print(manifest.run(chat_dict, max_tokens=8))" ] } ], "metadata": { "kernelspec": { "display_name": "manifest", "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": "3.10.4" }, "orig_nbformat": 4, "vscode": { "interpreter": { "hash": "fddffe4ac3b9f00470127629076101c1b5f38ecb1e7358b567d19305425e9491" } } }, "nbformat": 4, "nbformat_minor": 2 }