314 lines
9.2 KiB
Plaintext
314 lines
9.2 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "db8736a7-ed94-441c-9556-831fa57b5a10",
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"metadata": {},
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"source": [
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"# The Product Pricer Continued...\n",
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"\n",
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"## Testing Gemini-1.5-pro model"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "681c717b-4c24-4ac3-a5f3-3c5881d6e70a",
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"metadata": {},
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"outputs": [],
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"source": [
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"import os\n",
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"import re\n",
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"from dotenv import load_dotenv\n",
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"import matplotlib.pyplot as plt\n",
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"import pickle\n",
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"import google.generativeai as google_genai\n",
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"import time"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "21a3833e-4093-43b0-8f7b-839c50b911ea",
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"metadata": {},
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"outputs": [],
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"source": [
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"from items import Item\n",
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"from testing import Tester "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "36d05bdc-0155-4c72-a7ee-aa4e614ffd3c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# environment\n",
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"load_dotenv()\n",
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"os.environ['GOOGLE_API_KEY'] = os.getenv('GOOGLE_API_KEY', 'your-key-if-not-using-env')"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b0a6fb86-74a4-403c-ab25-6db2d74e9d2b",
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"metadata": {},
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"outputs": [],
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"source": [
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"google_genai.configure()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "c830ed3e-24ee-4af6-a07b-a1bfdcd39278",
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"metadata": {},
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"outputs": [],
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"source": [
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"%matplotlib inline"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "5c9b05f4-c9eb-462c-8d86-de9140a2d985",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Load in the pickle files that are located in the `pickled_dataset` folder\n",
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"with open('train.pkl', 'rb') as file:\n",
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" train = pickle.load(file)\n",
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"\n",
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"with open('test.pkl', 'rb') as file:\n",
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" test = pickle.load(file)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "fc5c807b-c14c-458e-8cca-32bc0cc5b7c3",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Function to create the messages format required for Gemini 1.5 Pro\n",
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"# This function prepares the system and user messages in the format expected by Gemini models.\n",
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"def gemini_messages_for(item):\n",
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" system_message = \"You estimate prices of items. Reply only with the price, no explanation\"\n",
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" \n",
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" # Modify the test prompt by removing \"to the nearest dollar\" and \"Price is $\"\n",
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" # This ensures that the model receives a cleaner, simpler prompt.\n",
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" user_prompt = item.test_prompt().replace(\" to the nearest dollar\", \"\").replace(\"\\n\\nPrice is $\", \"\")\n",
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"\n",
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" # Reformat messages to Gemini’s expected format: messages = [{'role':'user', 'parts': ['hello']}]\n",
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" return [\n",
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" {\"role\": \"system\", \"parts\": [system_message]}, # System-level instruction\n",
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" {\"role\": \"user\", \"parts\": [user_prompt]}, # User's query\n",
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" {\"role\": \"model\", \"parts\": [\"Price is $\"]} # Assistant's expected prefix for response\n",
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" ]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d6da66bb-bc4b-49ad-9224-a388470ef20b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Example usage of the gemini_messages_for function\n",
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"gemini_messages_for(test[0]) # Generate message structure for the first test item"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "b1af1888-f94a-4106-b0d8-8a70939eec4e",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Utility function to extract the numerical price from a given string\n",
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"# This function removes currency symbols and commas, then extracts the first number found.\n",
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"def get_price(s):\n",
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" s = s.replace('$', '').replace(',', '') # Remove currency symbols and formatting\n",
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" match = re.search(r\"[-+]?\\d*\\.\\d+|\\d+\", s) # Regular expression to find a number\n",
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" return float(match.group()) if match else 0 # Convert matched value to float, return 0 if no match"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a053c1a9-f86e-427c-a6be-ed8ec7bd63a5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Example usage of get_price function\n",
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"get_price(\"The price is roughly $99.99 because blah blah\") # Expected output: 99.99"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "34a88e34-1719-4d08-adbe-adb69dfe5e83",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Function to get the estimated price using Gemini 1.5 Pro\n",
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"def gemini_1_point_5_pro(item):\n",
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" messages = gemini_messages_for(item) # Generate messages for the model\n",
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" system_message = messages[0]['parts'][0] # Extract system-level instruction\n",
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" user_messages = messages[1:] # Remove system message from messages list\n",
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" \n",
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" # Initialize Gemini 1.5 Pro model with system instruction\n",
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" gemini = google_genai.GenerativeModel(\n",
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" model_name=\"gemini-1.5-pro\",\n",
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" system_instruction=system_message\n",
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" )\n",
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"\n",
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" # Generate response using Gemini API\n",
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" response = gemini.generate_content(\n",
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" contents=user_messages,\n",
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" generation_config=google_genai.GenerationConfig(max_output_tokens=5)\n",
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" )\n",
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"\n",
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" # Extract text response and convert to numerical price\n",
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" return get_price(response.text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "d89b10bb-8ebb-42ef-9146-f6e64e6849f9",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Example usage:\n",
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"gemini_1_point_5_pro(test[0])"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "89ad07e6-a28a-4625-b61e-d2ce12d440fc",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Retrieve the actual price of the test item (for comparison)\n",
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"test[0].price # Output: 374.41"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "384f28e5-e51f-4cd3-8d74-30a8275530db",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Test the function for gemini-1.5 pro using the Tester framework\n",
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"Tester.test(gemini_1_point_5_pro, test)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "9b627291-b02e-48dd-9130-703498135ddf",
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"metadata": {},
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"source": [
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"## Five, Gemini-2.0-flash"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "0ee393a9-7afd-404f-92f2-a64bb4d5fb8b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Function to get the estimated price using Gemini-2.0-flash-exp\n",
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"def gemini_2_point_0_flash_exp(item):\n",
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" messages = gemini_messages_for(item) # Generate messages for the model\n",
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" system_message = messages[0]['parts'][0] # Extract system-level instruction\n",
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" user_messages = messages[1:] # Remove system message from messages list\n",
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" \n",
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" # Initialize Gemini-2.0-flash-exp model with system instruction\n",
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" gemini = google_genai.GenerativeModel(\n",
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" model_name=\"gemini-2.0-flash-exp\",\n",
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" system_instruction=system_message\n",
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" )\n",
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"\n",
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" # Adding a delay to avoid hitting the API rate limit and getting a \"ResourceExhausted: 429\" error\n",
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" time.sleep(5)\n",
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" \n",
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" # Generate response using Gemini API\n",
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" response = gemini.generate_content(\n",
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" contents=user_messages,\n",
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" generation_config=google_genai.GenerationConfig(max_output_tokens=5)\n",
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" )\n",
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"\n",
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" # Extract text response and convert to numerical price\n",
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" return get_price(response.text)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "203dc6f1-309e-46eb-9957-e06eed803cc8",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Example usage:\n",
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"gemini_2_point_0_flash_exp(test[0]) "
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "a844df09-d347-40b9-bb79-006ec4160aab",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Retrieve the actual price of the test item (for comparison)\n",
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"test[0].price # Output: 374.41"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "500b45c7-e5c1-44f2-95c9-1c3c06365339",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Test the function for gemini-2.0-flash-exp using the Tester framework\n",
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"Tester.test(gemini_2_point_0_flash_exp, test)"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "746b2d12-ba92-48e2-9065-c9a108d1593b",
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"metadata": {},
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"outputs": [],
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"source": []
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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