Add Copilot and weather agent notebooks
Introduces Copilot.ipynb, an adaptive AI coding assistant with OpenAI and Gemini integration via Gradio, and weather_agent.ipynb, a weather chat agent supporting current, historical, and forecast queries using WeatherAPI and OpenAI tool-calling. Both notebooks provide interactive UIs for user queries.
This commit is contained in:
KiranAyyagari
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week2/community-contributions/Copilot.ipynb
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212
week2/community-contributions/Copilot.ipynb
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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": null,
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"id": "1877ad68",
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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 openai import OpenAI\n",
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"import gradio as gr\n",
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"from dotenv import load_dotenv \n",
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"import google.generativeai as genai\n",
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"from IPython.display import Markdown, display, update_display\n",
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"load_dotenv(override=True)"
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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": "008056a2",
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"metadata": {},
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"outputs": [],
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"source": [
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"openai_api_key = os.getenv('OPENAI_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 its starts with {openai_api_key[:3]}')\n",
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"else:\n",
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" print(\"OpenAi api key doesn't exist\")\n",
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"\n",
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"if google_api_key:\n",
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" print('Google api key exists')\n",
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"else:\n",
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" print(\"Google api key doesn't exist\")\n",
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"\n",
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"OPENAI_MODEL = \"gpt-4o-mini\"\n",
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"GOOGLE_MODEL = \"gemini-1.5-flash\"\n",
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"\n",
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"openai = OpenAI()\n",
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"\n",
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"genai.configure()"
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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": "5013ed7b",
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"metadata": {},
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"outputs": [],
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"source": [
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"system_msg = \"\"\"\n",
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"You are CodeCopilot, an adaptive AI coding assistant that helps users solve problems in any programming language.\n",
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"Always provide correct, runnable, and well-formatted code with clear explanations.\n",
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"Adjust your style based on the user’s expertise: for beginners, break concepts down step by step with simple examples and commented code;\n",
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"for advanced users, deliver concise, production-ready, optimized solutions with best practices and trade-off insights.\n",
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"Ask clarifying questions when requirements are ambiguous, highlight pitfalls and edge cases,\n",
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"and act as a collaborative pair programmer or mentor whose goal is to help users learn, build, and ship high-quality code efficiently.\n",
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"\"\"\"\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": "35c480a1",
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"metadata": {},
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"outputs": [],
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"source": [
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"def create_prompt(prompt, history):\n",
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" messages = [{\"role\": \"system\", \"content\": system_msg}]\n",
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"\n",
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" # history is a list of (user_msg, assistant_msg) tuples\n",
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" for user_msg, assistant_msg in history:\n",
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" if user_msg:\n",
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" messages.append({\"role\": \"user\", \"content\": user_msg})\n",
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" if assistant_msg:\n",
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" messages.append({\"role\": \"assistant\", \"content\": assistant_msg})\n",
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"\n",
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" # new user prompt\n",
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" messages.append({\"role\": \"user\", \"content\": prompt})\n",
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" return messages"
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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": "5dfbecd0",
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"metadata": {},
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"outputs": [],
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"source": [
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"def openai_agent(prompt, history):\n",
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" openai.api_key = openai_api_key\n",
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" messages = create_prompt(prompt, history)\n",
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" response = openai.chat.completions.create(\n",
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" model=OPENAI_MODEL,\n",
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" messages=messages,\n",
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" stream=True\n",
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" )\n",
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" sent_any = False\n",
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" for chunk in response:\n",
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" delta = chunk.choices[0].delta\n",
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" if delta and delta.content:\n",
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" sent_any = True\n",
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" yield delta.content\n",
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" if not sent_any:\n",
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" yield \"(no 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": null,
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"id": "535f7e3d",
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"metadata": {},
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"outputs": [],
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"source": [
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"def gemini_agent(prompt, history):\n",
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" genai.configure(api_key=google_api_key)\n",
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"\n",
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" # reuse OpenAI-style messages\n",
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" messages = create_prompt(prompt, history)\n",
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"\n",
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" gemini_history = []\n",
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" for m in messages:\n",
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" # Gemini does NOT support system role\n",
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" if m[\"role\"] == \"system\":\n",
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" continue\n",
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" gemini_history.append({\n",
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" \"role\": m[\"role\"],\n",
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" \"parts\": [m[\"content\"]]\n",
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" })\n",
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" prompt_with_system = f\"{system_msg}\\n\\n{prompt}\"\n",
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" model = genai.GenerativeModel(GOOGLE_MODEL)\n",
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" chat = model.start_chat(history=gemini_history)\n",
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"\n",
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" response = chat.send_message(prompt_with_system, stream=True)\n",
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" for chunk in response:\n",
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" if chunk and getattr(chunk, \"text\", None):\n",
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" yield chunk.text\n",
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"\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": "21f61ff0",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat_agent(prompt, history, modelType):\n",
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" if modelType == \"OpenAI\":\n",
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" for token in openai_agent(prompt, history):\n",
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" yield token\n",
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" else:\n",
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" for token in gemini_agent(prompt, history):\n",
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" yield token\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": "56686c1d",
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"metadata": {},
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"outputs": [],
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"source": [
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"def chat_fn(prompt, history, model):\n",
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" assistant_response = \"\"\n",
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" for token in chat_agent(prompt, history, model):\n",
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" assistant_response += token\n",
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" yield assistant_response \n",
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"\n",
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"# -------------------------------------------------------------------\n",
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"# UI\n",
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"# -------------------------------------------------------------------\n",
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"with gr.Blocks() as demo:\n",
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" model_choice = gr.Radio([\"OpenAI\", \"Gemini\"], value=\"OpenAI\", label=\"Model\")\n",
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"\n",
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" chat_ui = gr.ChatInterface(\n",
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" fn=chat_fn,\n",
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" additional_inputs=[model_choice],\n",
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" title=\"CodeCopilot\",\n",
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" description=\"An adaptive AI coding assistant that helps developers build and ship high-quality code.\"\n",
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" )\n",
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"\n",
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"demo.launch()"
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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": "llms",
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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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