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add exercise_gradio_dropdown

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Laurent JACQUES
2025-01-07 09:15:46 +01:00
parent 0b474e009e
commit 78e6c6a874
2 changed files with 220 additions and 61 deletions
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week2/community-contributions/day2-exercise_gradio_dropdown.ipynb Normal file
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{
"cells": [
{
"cell_type": "markdown",
"id": "a473d607-073d-4963-bdc4-aba654523681",
"metadata": {},
"source": [
"## Day 2 Exercise\n",
"building upon the day1 exercise to offer a multi models via dropdown.\n",
"externalized the common methods into a AISystem.py file to be reused down the line"
]
},
{
"cell_type": "markdown",
"id": "f761729f-3bd5-4dd7-9e63-cbe6b4368a66",
"metadata": {},
"source": [
"## Load env, check for api keys and load up the connections"
]
},
{
"cell_type": "code",
"execution_count": 1,
"id": "fedb3d94-d096-43fd-8a76-9fdbc2d0d78e",
"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 AIzaSyC-\n"
]
}
],
"source": [
"import os\n",
"from enum import Enum, auto\n",
"from dotenv import load_dotenv\n",
"from openai import OpenAI\n",
"import anthropic\n",
"from AISystem import formatPrompt, AI, AISystem\n",
"import gradio as gr # oh yeah!\n",
"\n",
"# 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\")\n",
"\n",
"openai = OpenAI()\n",
"\n",
"claude = anthropic.Anthropic()\n",
"\n",
"gemini_via_openai_client = OpenAI(\n",
" api_key=google_api_key, \n",
" base_url=\"https://generativelanguage.googleapis.com/v1beta/openai/\"\n",
")\n",
"ollama_via_openai = OpenAI(base_url='http://localhost:11434/v1', api_key='ollama')\n",
"openai_model = \"gpt-4o-mini\"\n",
"claude_model = \"claude-3-haiku-20240307\"\n",
"gemini_model = \"gemini-1.5-flash\"\n",
"ollama_model = \"llama3.2\""
]
},
{
"cell_type": "markdown",
"id": "17f7987b-2bdf-434a-8fce-6c367f148dde",
"metadata": {},
"source": [
"## Create the systems for each llms"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "f92eef29-325e-418c-a444-879d83d5fbc9",
"metadata": {},
"outputs": [],
"source": [
"geminiSys = AISystem(gemini_via_openai_client,\n",
" formatPrompt(\"system\",\"You are a chatbot. you always try to make conversation and get more in depth\"), \n",
" gemini_model,\n",
" AI.GEMINI)\n",
"\n",
"openAiSys = AISystem(openai,\n",
" formatPrompt(\"system\",\"You are a chatbot. you always try to make conversation and get more in depth\"), \n",
" openai_model,\n",
" AI.OPEN_AI)\n",
"\n",
"claudeSys = AISystem(claude,\n",
" \"You are a chatbot. you always try to make conversation and get more in depth\", \n",
" claude_model,\n",
" AI.CLAUDE)\n",
"\n",
"ollamaSys = AISystem(ollama_via_openai,\n",
" formatPrompt(\"system\",\"You are a chatbot. you always try to make conversation and get more in depth\"), \n",
" ollama_model,\n",
" AI.OLLAMA)\n",
"sys_dict = { AI.GEMINI: geminiSys, AI.OPEN_AI: openAiSys, AI.CLAUDE: claudeSys, AI.OLLAMA: ollamaSys}\n",
"\n",
"def stream_model(prompt, model):\n",
" aiSystem = sys_dict.get(AI[model.upper()])\n",
" yield from aiSystem.stream(formatPrompt(\"user\",prompt), True)"
]
},
{
"cell_type": "markdown",
"id": "f8ecd283-92b2-454d-b1ae-8016d41e3026",
"metadata": {},
"source": [
"## Create the gradio interface linking with the AI enum for the dropdown"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "9db8ed67-280a-400d-8543-4ab95863ce51",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"* Running on local URL: http://127.0.0.1:7873\n",
"\n",
"To create a public link, set `share=True` in `launch()`.\n"
]
},
{
"data": {
"text/html": [
"<div><iframe src=\"http://127.0.0.1:7873/\" 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": 3,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"\n",
"view = gr.Interface(\n",
" fn=stream_model,\n",
" inputs=[gr.Textbox(label=\"Your prompt:\", lines=6) , gr.Dropdown(choices=[ai.value for ai in AI], label=\"Select model\")],\n",
" outputs=[gr.Markdown(label=\"Response:\")],\n",
" flagging_mode=\"never\"\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
}