select specific versions of models from GPT or Claude
This commit is contained in:
ptonpay
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{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 27,
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"id": "c44c5494-950d-4d2f-8d4f-b87b57c5b330",
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"metadata": {},
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"outputs": [],
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"source": [
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"# imports\n",
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"\n",
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"import os\n",
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"import requests\n",
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"from bs4 import BeautifulSoup\n",
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"from typing import List\n",
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"from dotenv import load_dotenv\n",
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"from openai import OpenAI\n",
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"import google.generativeai\n",
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"import anthropic"
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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": 28,
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"id": "d1715421-cead-400b-99af-986388a97aff",
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"metadata": {},
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"outputs": [],
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"source": [
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"import gradio as gr # oh yeah!"
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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": 29,
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"id": "337d5dfc-0181-4e3b-8ab9-e78e0c3f657b",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"OpenAI API Key exists and begins sk-proj-\n",
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"Anthropic API Key exists and begins sk-ant-\n"
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]
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}
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],
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"source": [
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"# Load environment variables in a file called .env\n",
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"# Print the key prefixes to help with any debugging\n",
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"\n",
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"load_dotenv(override=True)\n",
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"openai_api_key = os.getenv('OPENAI_API_KEY')\n",
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"anthropic_api_key = os.getenv('ANTHROPIC_API_KEY')\n",
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"google_api_key = os.getenv('GOOGLE_API_KEY')\n",
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"\n",
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"if openai_api_key:\n",
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" print(f\"OpenAI API Key exists and begins {openai_api_key[:8]}\")\n",
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"else:\n",
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" print(\"OpenAI API Key not set\")\n",
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" \n",
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"if anthropic_api_key:\n",
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" print(f\"Anthropic API Key exists and begins {anthropic_api_key[:7]}\")\n",
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"else:\n",
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" print(\"Anthropic API Key not set\")"
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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": 30,
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"id": "22586021-1795-4929-8079-63f5bb4edd4c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Connect to OpenAI, Anthropic and Google; comment out the Claude or Google lines if you're not using them\n",
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"\n",
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"openai = OpenAI()\n",
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"claude = anthropic.Anthropic()"
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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": 31,
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"id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5",
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"metadata": {},
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"outputs": [],
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"source": [
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"# A generic system message - no more snarky adversarial AIs!\n",
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"system_message = \"You are a helpful assistant\""
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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": 32,
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"id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1",
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"metadata": {},
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"outputs": [],
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"source": [
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"\n",
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"def stream_gpt(prompt, model_version):\n",
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" messages = [\n",
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" {\"role\": \"system\", \"content\": system_message},\n",
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" {\"role\": \"user\", \"content\": prompt}\n",
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" ]\n",
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" stream = openai.chat.completions.create(\n",
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" model=model_version,\n",
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" messages=messages,\n",
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" stream=True\n",
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" )\n",
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" result = \"\"\n",
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" for chunk in stream:\n",
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" result += chunk.choices[0].delta.content or \"\"\n",
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" yield result"
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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": 33,
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"id": "41e98d2d-e7d3-4753-8908-185b208b4044",
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"metadata": {},
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"outputs": [],
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"source": [
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"def stream_claude(prompt, model_version):\n",
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" result = claude.messages.stream(\n",
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" model=model_version,\n",
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" max_tokens=1000,\n",
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" temperature=0.7,\n",
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" system=system_message,\n",
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" messages=[\n",
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" {\"role\": \"user\", \"content\": prompt},\n",
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" ],\n",
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" )\n",
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" response = \"\"\n",
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" with result as stream:\n",
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" for text in stream.text_stream:\n",
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" response += text or \"\"\n",
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" yield response"
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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": 34,
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"id": "5786802b-5ed8-4098-9d80-9bdcf4f7685b",
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"metadata": {},
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"outputs": [],
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"source": [
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"# function using both dropdown values\n",
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"def stream_model(message, model_family, model_version):\n",
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" if model_family == 'GPT':\n",
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" result = stream_gpt(message, model_version)\n",
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" elif model_family == 'Claude':\n",
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" result = stream_claude ( message, model_version)\n",
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" yield from result"
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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": 35,
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"id": "0d30be74-149c-41f8-9eef-1628eb31d74d",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"* Running on local URL: http://127.0.0.1:7891\n",
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"* To create a public link, set `share=True` in `launch()`.\n"
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]
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},
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{
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"data": {
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"text/html": [
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"<div><iframe src=\"http://127.0.0.1:7891/\" width=\"100%\" height=\"500\" allow=\"autoplay; camera; microphone; clipboard-read; clipboard-write;\" frameborder=\"0\" allowfullscreen></iframe></div>"
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],
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"text/plain": [
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"<IPython.core.display.HTML object>"
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]
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},
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"metadata": {},
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"output_type": "display_data"
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},
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{
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"data": {
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"text/plain": []
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},
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"execution_count": 35,
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"metadata": {},
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"output_type": "execute_result"
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},
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{
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"name": "stderr",
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"output_type": "stream",
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"text": [
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"/var/folders/sh/yytd3s6n3wd6952jnw97_v940000gn/T/ipykernel_7803/4165844704.py:7: DeprecationWarning: The model 'claude-3-opus-20240229' is deprecated and will reach end-of-life on January 5th, 2026.\n",
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"Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.\n",
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" yield from result\n",
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"Traceback (most recent call last):\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/queueing.py\", line 626, in process_events\n",
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" response = await route_utils.call_process_api(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/route_utils.py\", line 322, in call_process_api\n",
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" output = await app.get_blocks().process_api(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/blocks.py\", line 2220, in process_api\n",
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" result = await self.call_function(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/blocks.py\", line 1743, in call_function\n",
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" prediction = await utils.async_iteration(iterator)\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 785, in async_iteration\n",
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" return await anext(iterator)\n",
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" ^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 776, in __anext__\n",
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" return await anyio.to_thread.run_sync(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anyio/to_thread.py\", line 56, in run_sync\n",
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" return await get_async_backend().run_sync_in_worker_thread(\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anyio/_backends/_asyncio.py\", line 2470, in run_sync_in_worker_thread\n",
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" return await future\n",
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" ^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anyio/_backends/_asyncio.py\", line 967, in run\n",
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" result = context.run(func, *args)\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 759, in run_sync_iterator_async\n",
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" return next(iterator)\n",
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" ^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 923, in gen_wrapper\n",
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" response = next(iterator)\n",
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" ^^^^^^^^^^^^^^\n",
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" File \"/var/folders/sh/yytd3s6n3wd6952jnw97_v940000gn/T/ipykernel_7803/4165844704.py\", line 7, in stream_model\n",
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" yield from result\n",
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" File \"/var/folders/sh/yytd3s6n3wd6952jnw97_v940000gn/T/ipykernel_7803/2139010203.py\", line 12, in stream_claude\n",
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" with result as stream:\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anthropic/lib/streaming/_messages.py\", line 154, in __enter__\n",
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" raw_stream = self.__api_request()\n",
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" ^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anthropic/_base_client.py\", line 1314, in post\n",
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" return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n",
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" ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n",
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" File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anthropic/_base_client.py\", line 1102, in request\n",
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" raise self._make_status_error_from_response(err.response) from None\n",
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"anthropic.NotFoundError: Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'model: claude-3-opus-20240229'}}\n"
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]
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}
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],
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"source": [
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"\n",
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"# Define available model versions\n",
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"model_versions = {\n",
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" \"GPT\": [\"gpt-4o-mini\", \"gpt-4.1-mini\", \"gpt-4.1-nano\", \"gpt-4.1\", \"o3-mini\"],\n",
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" \"Claude\": [\"claude-3-haiku-20240307\", \"claude-3-opus-20240229\", \"claude-3-sonnet-20240229\"]\n",
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"}\n",
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"\n",
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"# Update second dropdown options based on first dropdown selection\n",
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"def update_model_versions(selected_model_family):\n",
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" return gr.update(choices=model_versions[selected_model_family], value=model_versions[selected_model_family][0])\n",
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"\n",
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"\n",
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"with gr.Blocks() as demo:\n",
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" model_family_dropdown = gr.Dropdown(\n",
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" label=\"Select Model Family\",\n",
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" choices=[\"GPT\", \"Claude\"],\n",
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" value=\"GPT\"\n",
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" )\n",
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" model_version_dropdown = gr.Dropdown(\n",
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" label=\"Select Model Version\",\n",
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" choices=model_versions[\"GPT\"], # Default choices\n",
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" value=model_versions[\"GPT\"][0]\n",
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" )\n",
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" \n",
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" message_input = gr.Textbox(label=\"Your Message\")\n",
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" output = gr.Markdown(label=\"Response\")\n",
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"\n",
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" # Bind logic to update model version dropdown\n",
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" model_family_dropdown.change(\n",
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" fn=update_model_versions,\n",
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" inputs=model_family_dropdown,\n",
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" outputs=model_version_dropdown\n",
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" )\n",
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"\n",
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" # Launch function on submit\n",
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" submit_btn = gr.Button(\"Submit\")\n",
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" submit_btn.click(\n",
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" fn=stream_model,\n",
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" inputs=[message_input, model_family_dropdown, model_version_dropdown],\n",
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" outputs=output\n",
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" )\n",
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"\n",
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"demo.launch()\n"
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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": "bcd43d91-0e80-4387-86fa-ccd1a89feb7d",
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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": "3.11.13"
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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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