updated llm project

pages/_notebooks/JeykLLM-create.ipynb

@@ -0,0 +1,300 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": []
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "---\n",
+    "title: \"Chat GPT Text Generation\"\n",
+    "description: \"This notebook demonstrates how to use the Chat GPT model for text generation.\"\n",
+    "tags: [\"NLP\", \"GPT\", \"Text Generation\"]\n",
+    "---"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Pre-requisites\n",
+    "!pip show openai || pip install openai\n",
+    "!pip show python-dotenv || pip install python-dotenv"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "try:\n",
+    "    %load_ext dotenv\n",
+    "    print(\"dotenv extension loaded successfully.\")\n",
+    "except Exception as e:\n",
+    "    print(\"Failed to load dotenv extension.\")\n",
+    "    print(\"Error: \", str(e))\n",
+    "\n",
+    "try:\n",
+    "    %dotenv\n",
+    "    print(\"Environment variables loaded successfully.\")\n",
+    "except Exception as e:\n",
+    "    print(\"Failed to load environment variables.\")\n",
+    "    print(\"Error: \", str(e))\n",
+    "\n",
+    "try:\n",
+    "    %reload_ext dotenv\n",
+    "    print(\"dotenv extension reloaded successfully.\")\n",
+    "except Exception as e:\n",
+    "    print(\"Failed to reload dotenv extension.\")\n",
+    "    print(\"Error: \", str(e))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from dotenv import load_dotenv\n",
+    "import os\n",
+    "\n",
+    "# Load environment variables from .env file\n",
+    "if load_dotenv():\n",
+    "    print(\"Environment variables loaded successfully.\")\n",
+    "else:\n",
+    "    print(\"Failed to load environment variables.\")\n",
+    "\n",
+    "# Get API key from environment variables\n",
+    "api_key = os.getenv('OPENAI_API_KEY')\n",
+    "if api_key:\n",
+    "    print(\"OPENAI_API_KEY loaded successfully.\")\n",
+    "else:\n",
+    "    print(\"Failed to load OPENAI_API_KEY.\")\n",
+    "\n",
+    "# Get project ID from environment variables\n",
+    "project_id = os.getenv('PROJECT_ID')\n",
+    "if project_id:\n",
+    "    print(\"PROJECT_ID loaded successfully.\")\n",
+    "else:\n",
+    "    print(\"Failed to load PROJECT_ID.\")\n",
+    "\n",
+    "# Get organization ID from environment variables\n",
+    "org_id = os.getenv('ORG_ID')\n",
+    "if org_id:\n",
+    "    print(\"ORG_ID loaded successfully.\")\n",
+    "else:\n",
+    "    print(\"Failed to load ORG_ID.\")\n",
+    "\n",
+    "# Print the loaded values\n",
+    "print(\"OPENAI_API_KEY: \", api_key)\n",
+    "print(\"PROJECT_ID: \", project_id)\n",
+    "print(\"ORG_ID: \", org_id)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from openai import OpenAI\n",
+    "import yaml\n",
+    "from datetime import datetime\n",
+    "\n",
+    "client = OpenAI(\n",
+    "  organization='org-sKWn6Hj2qqyP19zHfpXM1j1N',\n",
+    "  project=os.getenv('PROJECT_ID'),\n",
+    "  api_key = os.getenv('OPENAI_API_KEY')\n",
+    ")\n",
+    "\n",
+    "chat_completion = client.chat.completions.create(\n",
+    "    messages=[\n",
+    "        {\n",
+    "            \"role\": \"user\",\n",
+    "            \"content\": \"Say this is a test\",\n",
+    "        }\n",
+    "    ],\n",
+    "    model=\"gpt-3.5-turbo\",\n",
+    ")\n",
+    "\n",
+    "print(chat_completion.choices[0].message.content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def generate_content(prompt):\n",
+    "    response = client.chat.completions.create(\n",
+    "        model=\"gpt-3.5-turbo\",\n",
+    "        messages=[\n",
+    "            {\n",
+    "                \"role\": \"system\",\n",
+    "                \"content\": prompt,\n",
+    "            },\n",
+    "        ],\n",
+    "    )\n",
+    "    # Get the content of the last message in the response\n",
+    "    return response.choices[0].message.content.strip()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_assistant(client):\n",
+    "    name = input(\"Enter the name of the assistant: \")\n",
+    "    instructions = input(\"Enter the instructions for the assistant: \")\n",
+    "    assistant = client.beta.assistants.create(\n",
+    "        name=name,\n",
+    "        instructions=instructions,\n",
+    "        model=\"gpt-4o\",\n",
+    "    )\n",
+    "    return assistant\n",
+    "\n",
+    "# Call the function and store the result\n",
+    "assistant = create_assistant(client)\n",
+    "print(assistant.id)\n",
+    "# Your job is to take content and output a 4-word title that summarizes the content in a thought provoking manner. The title should be intriguing and attention getting for a reader. In other words, try to make it a worth while title for someone to be interested in."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_message(content):\n",
+    "    thread = client.beta.threads.create()\n",
+    "    message = client.beta.threads.messages.create(\n",
+    "        thread_id=thread.id,\n",
+    "        role=\"user\",\n",
+    "        content=content\n",
+    "    )\n",
+    "    return message\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "\n",
+    "prompt = input(\"Please enter your prompt for the GPT: \")\n",
+    "# Tell me a story about a cat named Nubi who smoked dubi's all day by the bay\n",
+    "# Tell me a story about a dog named Fido who loved to play fetch in the park\n",
+    "content = generate_content(prompt)\n",
+    "message = create_message(content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "print(message.thread_id)\n",
+    "print(content)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_and_poll_run(thread_id, assistant_id):\n",
+    "  run = client.beta.threads.runs.create_and_poll(\n",
+    "    thread_id=thread_id,\n",
+    "    assistant_id=assistant_id,\n",
+    "  )\n",
+    "  return run\n",
+    "\n",
+    "thread_id = message.thread_id\n",
+    "assistant_id = assistant.id\n",
+    "run = create_and_poll_run(thread_id, assistant_id)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if run.status == 'completed': \n",
+    "  messages = client.beta.threads.messages.list(\n",
+    "    thread_id=message.thread_id\n",
+    "  )\n",
+    "  text_message = messages.data[0].content[0].text.value\n",
+    "  title = text_message\n",
+    "  print(title)\n",
+    "else:\n",
+    "  print(run.status)\n",
+    "  "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def create_jekyll_post(title, content):\n",
+    "    front_matter = {\n",
+    "        'title': title,\n",
+    "        'layout': 'journals',\n",
+    "        'date': datetime.now().strftime('%Y-%m-%d %H:%M:%S'),\n",
+    "        'categories': 'gpt',\n",
+    "    }\n",
+    "    post_content = f\"---\\n{yaml.dump(front_matter)}---\\n{content}\"\n",
+    "    filename = f\"../_posts/{datetime.now().strftime('%Y-%m-%d')}-{title.lower().replace(' ', '-')}.md\"\n",
+    "    os.makedirs(os.path.dirname(filename), exist_ok=True)\n",
+    "    with open(filename, 'w') as file:\n",
+    "        file.write(post_content)\n",
+    "    return filename"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "file_path = create_jekyll_post(title, content)\n",
+    "print(f\"The new file is created at: {file_path}\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.9.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}