diff --git a/week2/community-contributions/tool_integration_gradio_using_anthropic_api.ipynb b/week2/community-contributions/tool_integration_gradio_using_anthropic_api.ipynb new file mode 100644 index 0000000..2964939 --- /dev/null +++ b/week2/community-contributions/tool_integration_gradio_using_anthropic_api.ipynb @@ -0,0 +1,290 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "3f9b483c-f410-4ad3-8f3a-e33527f30f8a", + "metadata": { + "panel-layout": { + "height": 68.2639, + "visible": true, + "width": 100 + } + }, + "source": [ + "# Project - Laptops Assistant\n", + "\n", + "A simple inventory tool integrated with Anthropic API" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cfaff08d-f6e5-4d2d-bfb8-76c154836f3d", + "metadata": {}, + "outputs": [], + "source": [ + "# imports\n", + "\n", + "import os\n", + "import json\n", + "from dotenv import load_dotenv\n", + "import anthropic\n", + "import gradio as gr" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "a04047ea-d01b-469b-93ce-ab4f4e36ca1e", + "metadata": {}, + "outputs": [], + "source": [ + "# Load environment variables in a file called .env\n", + "# Print the key prefixes to help with any debugging\n", + "\n", + "load_dotenv(override=True)\n", + "anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n", + "\n", + "if anthropic_api_key:\n", + " print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n", + "else:\n", + " print(\"Anthropic API Key not set\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "f5e00ced-f47b-4713-8174-7901e1a69881", + "metadata": {}, + "outputs": [], + "source": [ + "# Connect to OpenAI, Anthropic and Google; comment out the Claude or Google lines if you're not using them\n", + "\n", + "claude = anthropic.Anthropic()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3c715efd-cebf-4dc2-8c99-798f3179dd21", + "metadata": {}, + "outputs": [], + "source": [ + "MODEL = \"claude-3-haiku-20240307\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "2b029d1d-9199-483a-94b7-893680af8ad1", + "metadata": {}, + "outputs": [], + "source": [ + "system_message = \"You are a helpful assistant for an Inventory Sales called InvAI. \"\n", + "system_message += \"Give short, courteous answers, no more than 1 sentence. \"\n", + "system_message += \"Always be accurate. If you don't know the answer, say so.\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "8ca1197c-e6a1-4579-96c6-24e8e305cc72", + "metadata": {}, + "outputs": [], + "source": [ + "laptop_items = [\n", + " {\n", + " \"model\": \"Aspire 3 A315-59-570Z OPI Pure Silver\", \n", + " \"brand\": \"Acer\",\n", + " \"price\": \"$595.96\"\n", + " },\n", + " {\n", + " \"model\": \"Aspire Lite 14 AL14-31P-36BE Pure Silver\", \n", + " \"brand\": \"Acer\",\n", + " \"price\": \"$463.52\"\n", + " },\n", + " {\n", + " \"model\": \"Raider 18 HX\",\n", + " \"brand\": \"MSI\",\n", + " \"price\": \"$235.25\"\n", + " }\n", + "]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "1d2bc76b-c1d0-4b3d-a299-9972f7687e4c", + "metadata": {}, + "outputs": [], + "source": [ + "def get_laptop_price(model):\n", + " print(f\"Tool get_laptop_price called for laptop model {model}\")\n", + " laptop_model = model.lower()\n", + " for item in laptop_items:\n", + " if laptop_model in item.get(\"model\").lower():\n", + " return item\n", + " return \"Unknown\"" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "afc9b4a3-3a6f-4839-bebc-89bd598394fd", + "metadata": {}, + "outputs": [], + "source": [ + "\n", + "# get_laptop_price(\"Lite 14 AL14-31P-36BE Pure SilveR\")\n", + "\n", + "get_laptop_price(\"Aspire Lite 14\")" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "12190074-fad8-43f6-8be1-f96a08c16b59", + "metadata": {}, + "outputs": [], + "source": [ + "# There's a particular dictionary structure that's required to describe our function:\n", + "\n", + "price_function = {\n", + " \"name\": \"get_laptop_price\",\n", + " \"description\": (\n", + " \"Returns the laptop's price, brand, and exact model from a given query.\"\n", + " \"Use when the user asks about a laptop's price, e.g.,\"\n", + " \"'How much is this laptop?' → 'The Acer Aspire Lite 14 AL14-31P-36BE Pure Silver is priced at $463.52.'\"\n", + " ),\n", + " \"input_schema\": {\n", + " \"type\": \"object\",\n", + " \"properties\": {\n", + " \"model\": {\n", + " \"type\": \"string\",\n", + " \"description\": \"The model name of the laptop the customer is asking about.\"\n", + " }\n", + " },\n", + " \"required\": [\"model\"]\n", + " }\n", + "}" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "475195e1-dd78-45ba-af6d-16d7cf5c85ae", + "metadata": {}, + "outputs": [], + "source": [ + "# And this is included in a list of tools:\n", + "\n", + "tools = [price_function]" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "3834314d-fd37-4e27-9511-bd519389b31b", + "metadata": {}, + "outputs": [], + "source": [ + "def chat(message, history):\n", + " print(history)\n", + " messages = [{\"role\": \"user\", \"content\": message}]\n", + "\n", + " for history_message in history:\n", + " if history_message[\"role\"] == \"user\":\n", + " messages.append({\"role\": \"user\", \"content\": history_message[\"content\"]})\n", + " \n", + " response = claude.messages.create(model=MODEL, messages=messages, tools=tools, max_tokens=500)\n", + "\n", + " if len(response.content) > 1:\n", + " assistant, user, laptop_model = handle_tool_call(response)\n", + " messages.append(assistant)\n", + " messages.append(user)\n", + " response = claude.messages.create(model=MODEL, messages=messages, tools=tools, max_tokens=500)\n", + "\n", + "\n", + " return response.content[0].text" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "745a9bf8-6ceb-4c1c-bfbf-b0d1f3d5d6fc", + "metadata": {}, + "outputs": [], + "source": [ + "# We have to write that function handle_tool_call:\n", + "\n", + "def handle_tool_call(message):\n", + " # laptop_model = message\n", + " laptop_model = message.content[1].input.get(\"model\")\n", + " laptop_item = get_laptop_price(laptop_model)\n", + " assistant = {\n", + " \"role\": \"assistant\",\n", + " \"content\": [\n", + " {\n", + " \"type\": \"text\",\n", + " \"text\": message.content[0].text\n", + " },\n", + " {\n", + " \"type\": \"tool_use\",\n", + " \"id\": message.content[1].id,\n", + " \"name\": message.content[1].name,\n", + " \"input\": message.content[1].input\n", + " }\n", + " ]\n", + " }\n", + " user = {\n", + " \"role\": \"user\",\n", + " \"content\": [\n", + " {\n", + " \"type\": \"tool_result\",\n", + " \"tool_use_id\": message.content[1].id,\n", + " # \"content\": laptop_item.get(\"price\")\n", + " \"content\": json.dumps(laptop_item)\n", + " }\n", + " ]\n", + " }\n", + " \n", + "\n", + " return assistant, user, laptop_model" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "9408eeb4-d07b-4193-92cd-197610ed942e", + "metadata": {}, + "outputs": [], + "source": [ + "gr.ChatInterface(fn=chat, type=\"messages\").launch()" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python [conda env:base] *", + "language": "python", + "name": "conda-base-py" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.7" + }, + "panel-cell-order": [ + "3f9b483c-f410-4ad3-8f3a-e33527f30f8a" + ] + }, + "nbformat": 4, + "nbformat_minor": 5 +}