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feat(week 2): integration of anthropic api to gradio

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2025-04-08 11:36:47 +08:00
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{
"cells": [
{
"cell_type": "markdown",
"id": "3f9b483c-f410-4ad3-8f3a-e33527f30f8a",
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},
"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",
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"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",
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"id": "a04047ea-d01b-469b-93ce-ab4f4e36ca1e",
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"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()"
]
}
],
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