{ "cells": [ { "cell_type": "code", "execution_count": 27, "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" ] }, { "cell_type": "code", "execution_count": 28, "id": "d1715421-cead-400b-99af-986388a97aff", "metadata": {}, "outputs": [], "source": [ "import gradio as gr # oh yeah!" ] }, { "cell_type": "code", "execution_count": 29, "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" ] } ], "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", "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\")" ] }, { "cell_type": "code", "execution_count": 30, "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", "claude = anthropic.Anthropic()" ] }, { "cell_type": "code", "execution_count": 31, "id": "b16e6021-6dc4-4397-985a-6679d6c8ffd5", "metadata": {}, "outputs": [], "source": [ "# A generic system message - no more snarky adversarial AIs!\n", "system_message = \"You are a helpful assistant\"" ] }, { "cell_type": "code", "execution_count": 32, "id": "02ef9b69-ef31-427d-86d0-b8c799e1c1b1", "metadata": {}, "outputs": [], "source": [ "\n", "def stream_gpt(prompt, model_version):\n", " messages = [\n", " {\"role\": \"system\", \"content\": system_message},\n", " {\"role\": \"user\", \"content\": prompt}\n", " ]\n", " stream = openai.chat.completions.create(\n", " model=model_version,\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": 33, "id": "41e98d2d-e7d3-4753-8908-185b208b4044", "metadata": {}, "outputs": [], "source": [ "def stream_claude(prompt, model_version):\n", " result = claude.messages.stream(\n", " model=model_version,\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": 34, "id": "5786802b-5ed8-4098-9d80-9bdcf4f7685b", "metadata": {}, "outputs": [], "source": [ "# function using both dropdown values\n", "def stream_model(message, model_family, model_version):\n", " if model_family == 'GPT':\n", " result = stream_gpt(message, model_version)\n", " elif model_family == 'Claude':\n", " result = stream_claude ( message, model_version)\n", " yield from result" ] }, { "cell_type": "code", "execution_count": 35, "id": "0d30be74-149c-41f8-9eef-1628eb31d74d", "metadata": {}, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "* Running on local URL: http://127.0.0.1:7891\n", "* To create a public link, set `share=True` in `launch()`.\n" ] }, { "data": { "text/html": [ "
" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/plain": [] }, "execution_count": 35, "metadata": {}, "output_type": "execute_result" }, { "name": "stderr", "output_type": "stream", "text": [ "/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", "Please migrate to a newer model. Visit https://docs.anthropic.com/en/docs/resources/model-deprecations for more information.\n", " yield from result\n", "Traceback (most recent call last):\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/queueing.py\", line 626, in process_events\n", " response = await route_utils.call_process_api(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/route_utils.py\", line 322, in call_process_api\n", " output = await app.get_blocks().process_api(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/blocks.py\", line 2220, in process_api\n", " result = await self.call_function(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/blocks.py\", line 1743, in call_function\n", " prediction = await utils.async_iteration(iterator)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 785, in async_iteration\n", " return await anext(iterator)\n", " ^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 776, in __anext__\n", " return await anyio.to_thread.run_sync(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anyio/to_thread.py\", line 56, in run_sync\n", " return await get_async_backend().run_sync_in_worker_thread(\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anyio/_backends/_asyncio.py\", line 2470, in run_sync_in_worker_thread\n", " return await future\n", " ^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anyio/_backends/_asyncio.py\", line 967, in run\n", " result = context.run(func, *args)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 759, in run_sync_iterator_async\n", " return next(iterator)\n", " ^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/gradio/utils.py\", line 923, in gen_wrapper\n", " response = next(iterator)\n", " ^^^^^^^^^^^^^^\n", " File \"/var/folders/sh/yytd3s6n3wd6952jnw97_v940000gn/T/ipykernel_7803/4165844704.py\", line 7, in stream_model\n", " yield from result\n", " File \"/var/folders/sh/yytd3s6n3wd6952jnw97_v940000gn/T/ipykernel_7803/2139010203.py\", line 12, in stream_claude\n", " with result as stream:\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anthropic/lib/streaming/_messages.py\", line 154, in __enter__\n", " raw_stream = self.__api_request()\n", " ^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anthropic/_base_client.py\", line 1314, in post\n", " return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", " File \"/opt/anaconda3/envs/llms/lib/python3.11/site-packages/anthropic/_base_client.py\", line 1102, in request\n", " raise self._make_status_error_from_response(err.response) from None\n", "anthropic.NotFoundError: Error code: 404 - {'type': 'error', 'error': {'type': 'not_found_error', 'message': 'model: claude-3-opus-20240229'}}\n" ] } ], "source": [ "\n", "# Define available model versions\n", "model_versions = {\n", " \"GPT\": [\"gpt-4o-mini\", \"gpt-4.1-mini\", \"gpt-4.1-nano\", \"gpt-4.1\", \"o3-mini\"],\n", " \"Claude\": [\"claude-3-haiku-20240307\", \"claude-3-opus-20240229\", \"claude-3-sonnet-20240229\"]\n", "}\n", "\n", "# Update second dropdown options based on first dropdown selection\n", "def update_model_versions(selected_model_family):\n", " return gr.update(choices=model_versions[selected_model_family], value=model_versions[selected_model_family][0])\n", "\n", "\n", "with gr.Blocks() as demo:\n", " model_family_dropdown = gr.Dropdown(\n", " label=\"Select Model Family\",\n", " choices=[\"GPT\", \"Claude\"],\n", " value=\"GPT\"\n", " )\n", " model_version_dropdown = gr.Dropdown(\n", " label=\"Select Model Version\",\n", " choices=model_versions[\"GPT\"], # Default choices\n", " value=model_versions[\"GPT\"][0]\n", " )\n", " \n", " message_input = gr.Textbox(label=\"Your Message\")\n", " output = gr.Markdown(label=\"Response\")\n", "\n", " # Bind logic to update model version dropdown\n", " model_family_dropdown.change(\n", " fn=update_model_versions,\n", " inputs=model_family_dropdown,\n", " outputs=model_version_dropdown\n", " )\n", "\n", " # Launch function on submit\n", " submit_btn = gr.Button(\"Submit\")\n", " submit_btn.click(\n", " fn=stream_model,\n", " inputs=[message_input, model_family_dropdown, model_version_dropdown],\n", " outputs=output\n", " )\n", "\n", "demo.launch()\n" ] }, { "cell_type": "code", "execution_count": null, "id": "bcd43d91-0e80-4387-86fa-ccd1a89feb7d", "metadata": {}, "outputs": [], "source": [] } ], "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": "3.11.13" } }, "nbformat": 4, "nbformat_minor": 5 }