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{
"cells": [
{
"cell_type": "markdown",
"id": "5e6b6966-8689-4e2c-8607-a1c5d948296c",
"metadata": {},
"source": [
"### With this interface you can ask a question and get an answer from the GPT, Claude and Gemini"
]
},
{
"cell_type": "code",
"execution_count": 49,
"id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330",
"metadata": {},
"outputs": [],
"source": [
"# imports\n",
"\n",
"import os\n",
"import requests\n",
"from bs4 import BeautifulSoup\n",
"from typing import List\n",
"from dotenv import load_dotenv\n",
"from openai import OpenAI\n",
"import google.generativeai\n",
"import anthropic\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "d1715421-cead-400b-99af-986388a97aff",
"metadata": {},
"outputs": [],
"source": [
"import gradio as gr # oh yeah!"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"OpenAI API Key exists and begins sk-proj-\n",
"Anthropic API Key exists and begins sk-ant-\n",
"Google API Key exists and begins AIzaSyAJ\n"
]
}
],
"source": [
"# Load environment variables in a file called .env\n",
"# Print the key prefixes to help with any debugging\n",
"\n",
"load_dotenv()\n",
"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
"anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n",
"google_api_key = os.getenv('GOOGLE_API_KEY')\n",
"\n",
"if openai_api_key:\n",
" print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
"else:\n",
" print(\"OpenAI API Key not set\")\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\")\n",
"\n",
"if google_api_key:\n",
" print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n",
"else:\n",
" print(\"Google API Key not set\")"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "22586021-1795-4929-8079-63f5bb4edd4c",
"metadata": {},
"outputs": [],
"source": [
"# Connect to OpenAI, Anthropic and Google; comment out the Claude or Google lines if you're not using them\n",
"\n",
"openai = OpenAI()\n",
"\n",
"claude = anthropic.Anthropic()\n",
"\n",
"google.generativeai.configure()"
]
},
{
"cell_type": "code",
"execution_count": 5,
"id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5",
"metadata": {},
"outputs": [],
"source": [
"# A generic system message - no more snarky adversarial AIs!\n",
"\n",
"system_message = \"You are a helpful assistant\""
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "88c04ebf-0671-4fea-95c9-bc1565d4bb4f",
"metadata": {},
"outputs": [],
"source": [
"# Let's create a call that streams back results\n",
"# If you'd like a refresher on Generators (the \"yield\" keyword),\n",
"# Please take a look at the Intermediate Python notebook in week1 folder.\n",
"\n",
"def stream_gpt(prompt):\n",
" messages = [\n",
" {\"role\": \"system\", \"content\": system_message},\n",
" {\"role\": \"user\", \"content\": prompt}\n",
" ]\n",
" stream = openai.chat.completions.create(\n",
" model='gpt-4o-mini',\n",
" messages=messages,\n",
" stream=True\n",
" )\n",
" result = \"\"\n",
" for chunk in stream:\n",
" result += chunk.choices[0].delta.content or \"\"\n",
" yield result"
]
},
{
"cell_type": "code",
"execution_count": 7,
"id": "bbc8e930-ba2a-4194-8f7c-044659150626",
"metadata": {},
"outputs": [],
"source": [
"def stream_claude(prompt):\n",
" result = claude.messages.stream(\n",
" model=\"claude-3-haiku-20240307\",\n",
" max_tokens=1000,\n",
" temperature=0.7,\n",
" system=system_message,\n",
" messages=[\n",
" {\"role\": \"user\", \"content\": prompt},\n",
" ],\n",
" )\n",
" response = \"\"\n",
" with result as stream:\n",
" for text in stream.text_stream:\n",
" response += text or \"\"\n",
" yield response"
]
},
{
"cell_type": "code",
"execution_count": 8,
"id": "5e228aff-16d5-4141-bd04-ed9940ef7b3b",
"metadata": {},
"outputs": [],
"source": [
"def stream_gemini(prompt):\n",
" gemini = google.generativeai.GenerativeModel(\n",
" model_name='gemini-2.0-flash-exp',\n",
" system_instruction=system_message\n",
" )\n",
" result = \"\"\n",
" for response in gemini.generate_content(prompt, stream=True):\n",
" result += response.text or \"\"\n",
" yield result"
]
},
{
"cell_type": "code",
"execution_count": 92,
"id": "db99aaf1-fe0a-4e79-9057-8599d1ca0149",
"metadata": {},
"outputs": [],
"source": [
"def stream_models(prompt):\n",
" response_gpt = \"\"\n",
" response_claude = \"\"\n",
" response_gemini = \"\"\n",
" for gpt in stream_gpt(prompt):\n",
" response_gpt = gpt\n",
" yield response_gpt, response_claude, response_gemini\n",
" for claude in stream_claude(prompt):\n",
" response_claude = claude\n",
" yield response_gpt, response_claude, response_gemini\n",
" for gemini in stream_gemini(prompt):\n",
" response_gemini = gemini\n",
" yield response_gpt, response_claude, response_gemini"
]
},
{
"cell_type": "code",
"execution_count": 113,
"id": "3377f2fb-55f8-45cb-b713-d99d44748dad",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* Running on local URL: http://127.0.0.1:7919\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7919/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
],
"text/plain": [
"<IPython.core.display.HTML object>"
]
},
"metadata": {},
"output_type": "display_data"
},
{
"data": {
"text/plain": []
},
"execution_count": 113,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Gradio interface\n",
"with gr.Blocks() as view:\n",
" user_input = gr.Textbox(label=\"What models can help with?\", placeholder=\"Type your question here\")\n",
" ask_button = gr.Button(\"Ask\")\n",
" with gr.Row():\n",
" with gr.Column():\n",
" gr.HTML(value=\"<b>GPT response:</b>\") \n",
" gcp_stream = gr.Markdown()\n",
" with gr.Column():\n",
" gr.HTML(value=\"<b>Claude response:</b>\") \n",
" claude_stream = gr.Markdown()\n",
" with gr.Column():\n",
" gr.HTML(value=\"<b>Gemine response:</b>\") \n",
" gemini_stream = gr.Markdown()\n",
"\n",
" ask_button.click(\n",
" fn=stream_models, # Function that yields multiple outputs\n",
" inputs=user_input,\n",
" outputs=[gcp_stream, claude_stream, gemini_stream] # Connect to multiple outputs\n",
" )\n",
"\n",
"view.launch()"
]
}
],
"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": "3.11.11"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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