add litellm example (OpenAI-Compatible Endpoint)

examples/Gemini_Pro_LiteLLM_(OpenAI_Compatible_Endpoint).ipynb

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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# OpenAI-Compatible Endpoint\n",
+ "\n",
+ "Use [LiteLLM](https://github.com/BerriAI/litellm) to call Gemini in the OpenAI format. "
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "H--pem7MsUXl"
+ },
+ "outputs": [],
+ "source": [
+ "!pip install litellm"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "xqKTu2-6scyt"
+ },
+ "source": [
+ "# Usage"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "eu3T_V3csZUo"
+ },
+ "outputs": [],
+ "source": [
+ "from litellm import completion\n",
+ "import os\n",
+ "\n",
+ "os.environ['GEMINI_API_KEY'] = \"\"\n",
+ "response = completion(\n",
+ " model=\"gemini/gemini-pro\",\n",
+ " messages=[{\"role\": \"user\", \"content\": \"write code for saying hi from LiteLLM\"}]\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "id": "fO1R-hDCsdsd"
+ },
+ "source": [
+ "# Vision"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {
+ "id": "-ZpcBIknsgyh"
+ },
+ "outputs": [],
+ "source": [
+ "import os\n",
+ "import litellm\n",
+ "from dotenv import load_dotenv\n",
+ "\n",
+ "# Load the environment variables from .env file\n",
+ "load_dotenv()\n",
+ "os.environ[\"GEMINI_API_KEY\"] = os.getenv('GEMINI_API_KEY')\n",
+ "\n",
+ "prompt = 'Describe the image in a few sentences.'\n",
+ "# Note: You can pass here the URL or Path of image directly.\n",
+ "image_url = 'https://storage.googleapis.com/github-repo/img/gemini/intro/landmark3.jpg'\n",
+ "\n",
+ "# Create the messages payload according to the documentation\n",
+ "messages = [\n",
+ " {\n",
+ " \"role\": \"user\",\n",
+ " \"content\": [\n",
+ " {\n",
+ " \"type\": \"text\",\n",
+ " \"text\": prompt\n",
+ " },\n",
+ " {\n",
+ " \"type\": \"image_url\",\n",
+ " \"image_url\": {\"url\": image_url}\n",
+ " }\n",
+ " ]\n",
+ " }\n",
+ "]\n",
+ "\n",
+ "# Make the API call to Gemini model\n",
+ "response = litellm.completion(\n",
+ " model=\"gemini/gemini-pro-vision\",\n",
+ " messages=messages,\n",
+ ")\n",
+ "\n",
+ "# Extract the response content\n",
+ "content = response.get('choices', [{}])[0].get('message', {}).get('content')\n",
+ "\n",
+ "# Print the result\n",
+ "print(content)"
+ ]
+ }
+ ],
+ "metadata": {
+ "colab": {
+ "provenance": []
+ },
+ "kernelspec": {
+ "display_name": "Python 3",
+ "name": "python3"
+ },
+ "language_info": {
+ "name": "python"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}