Unlocking The Power Of Google Gemini Ai: Create Your Own Ai Tool Using The Api With Python.

Understanding Google Gemini AI

Google Gemini AI stands out as a sophisticated machine learning platform crafted by Google, with the primary goal of empowering developers to craft intelligent applications. It harnesses state-of-the-art algorithms and extensive datasets to offer a wide array of AI-driven functionalities, including natural language processing (NLP), image recognition, and sentiment analysis.

Representing a collaborative effort between various Google teams, such as Google Research and Google DeepMind, Gemini AI epitomizes an advanced artificial intelligence model. Engineered to be multimodal, it possesses the capability to comprehend and analyze diverse data types, spanning text, code, audio, images, and videos.

Driven by Google DeepMind's enduring commitment to leveraging artificial intelligence for the collective advancement of humanity, Gemini AI embodies significant strides in the evolution of AI models. Rooted in the aspiration to replicate human perception and interaction with the world, Gemini AI pioneers a new frontier in artificial intelligence research and application development.

Introduction to Google Gemini API

The Google Gemini API serves as a bridge between developers and the powerful capabilities of Gemini AI. Through the API, developers can access various services offered by Gemini, including text analysis, image recognition, and language translation. This allows developers to integrate AI capabilities into their own applications, enhancing their functionality and user experience.

Getting Started with Google Gemini API and Python

To begin using the Google Gemini API with Python, you'll need to follow these steps:

STEP 1 :  Create a Account in https://ai.google.dev/ and generate project key.

STEP 2:  Following modules should be installed in your python project

STEP 3: Create a file called AI.py and paste below code

# !pip install -q -U google-generativeai
import pathlib
import textwrap
import google.generativeai as genai
from IPython.display import display
from IPython.display import Markdown

class GEMINIAiClass():
  def to_markdown(self, text):
     text = text.replace('•', '  *')
     return Markdown(textwrap.indent(text, '> ', predicate=lambda _: True))

  def get_ans(self,ques):
       genai.configure(api_key='your project key')
       model = genai.GenerativeModel('gemini-pro')
       response = model.generate_content(ques)
       return response.text



a1=GEMINIAiClass()
ans=a1.get_ans("How to solve sum of two numbers in c language")
print(ans)