183 lines
5.9 KiB
Plaintext
183 lines
5.9 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "2b57204f-3e19-4d11-8901-c0e153ad9992",
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"metadata": {},
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"source": [
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"## Technical Question Answerer With Gradio\n",
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"- Ask a technical question to a chatbot embued with multimodal capabilities.\n",
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"- Choose between different models (e.g. OpenAI's GPT, Anthropic's Claude)."
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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": "bd8e9bef-87ab-46d6-9393-bb308d7e5bc4",
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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 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\n",
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"\n",
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"import gradio as gr\n",
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"import base64\n",
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"from io import BytesIO\n",
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"from PIL import Image\n",
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"from IPython.display import Audio, display\n",
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"\n",
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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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"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\")\n",
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"\n",
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"if google_api_key:\n",
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" print(f\"Google API Key exists and begins {google_api_key[:8]}\")\n",
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"else:\n",
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" print(\"Google API Key not set\")\n",
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"\n",
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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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"openai = OpenAI()\n",
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"claude = anthropic.Anthropic()\n",
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"# google.generativeai.configure()\n",
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"\n",
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"system_message = \"You are a helpful assistant that explains technical contents and responds in markdown\"\n",
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"\n",
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"def talker(message):\n",
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" response = openai.audio.speech.create(\n",
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" model=\"tts-1\",\n",
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" voice=\"onyx\",\n",
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" input=message)\n",
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"\n",
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" audio_stream = BytesIO(response.content)\n",
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" output_filename = \"output_audio.mp3\"\n",
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" with open(output_filename, \"wb\") as f:\n",
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" f.write(audio_stream.read())\n",
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"\n",
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" display(Audio(output_filename, autoplay=True))\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": "20486a61-5d59-4370-b92c-3b7fec63835c",
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"metadata": {},
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"outputs": [],
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"source": [
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"# --- Chat functions ---\n",
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"def chat_gpt(history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history\n",
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" response = openai.chat.completions.create(\n",
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" model=\"gpt-4o-mini\",\n",
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" messages=messages\n",
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" )\n",
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" reply = response.choices[0].message.content\n",
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" history = history + [{\"role\": \"assistant\", \"content\": reply}]\n",
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" talker(reply) # make it talk\n",
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" return history\n",
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"\n",
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"\n",
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"claude_via_openai_client = OpenAI(\n",
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" api_key=anthropic_api_key, \n",
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" base_url=\"https://api.anthropic.com/v1\"\n",
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")\n",
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"\n",
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"def chat_claude(history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_message}] + history\n",
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" response = claude_via_openai_client.chat.completions.create(\n",
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" model=\"claude-3-haiku-20240307\",\n",
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" messages=messages\n",
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" )\n",
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" reply = response.choices[0].message.content\n",
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" history = history + [{\"role\": \"assistant\", \"content\": reply}]\n",
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" talker(reply) # make it talk\n",
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" return history\n",
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"\n",
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"\n",
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"# --- Gradio UI ---\n",
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"with gr.Blocks() as ui:\n",
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" with gr.Row():\n",
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" chatbot = gr.Chatbot(height=500, type=\"messages\")\n",
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" with gr.Row():\n",
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" the_model = gr.Dropdown([\"GPT\", \"Claude\"], label=\"Select model\", value=\"GPT\")\n",
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" with gr.Row():\n",
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" entry = gr.Textbox(label=\"Chat with our AI Assistant:\")\n",
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" with gr.Row():\n",
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" clear = gr.Button(\"Clear\")\n",
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"\n",
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" def do_entry(message, history, model):\n",
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" # add user turn\n",
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" history = history + [{\"role\": \"user\", \"content\": message}]\n",
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" # call selected model\n",
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" if model == \"GPT\":\n",
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" history = chat_gpt(history)\n",
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" elif model == \"Claude\":\n",
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" history = chat_claude(history)\n",
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" return \"\", history\n",
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"\n",
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" entry.submit(\n",
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" fn=do_entry,\n",
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" inputs=[entry, chatbot, the_model],\n",
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" outputs=[entry, chatbot] # only 2 outputs\n",
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" )\n",
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"\n",
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" clear.click(lambda: [], None, chatbot, queue=False)"
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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": "13974664-2965-46b9-9c56-714c70d3f835",
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"metadata": {},
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"outputs": [],
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"source": [
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"ui.launch(inbrowser=True)\n",
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"\n",
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"# prompt = \"\"\"\n",
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"# Please explain what this code does and why:\n",
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"# yield from {book.get(\"author\") for book in books if book.get(\"author\")}\n",
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"# \"\"\""
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]
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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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