GEMINI API Implementation

Author: Tanzeel

This project demonstrates how to interact with the Google Gemini API for generative AI tasks. Below is a step-by-step breakdown of the Jupyter Notebook (.ipynb) cells and their functionalities.

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Table of Contents

1. Setup & Installation
2. API Key Configuration
3. Initializing the Gemini Model
4. Generating Text Responses
5. Handling Multimodal Inputs
6. Error Handling
7. License

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1. Setup & Installation

Dependencies:

• Python 3.x
• google-generativeai library
• Jupyter Notebook (for interactive execution)

Installation:

!pip install google-generativeai

This cell installs the official Google Gemini API Python SDK.

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2. API Key Configuration

import google.generativeai as genai
genai.configure(api_key="YOUR_API_KEY")

• Functionality: Configures the Gemini API with your unique API key.
• Note: Replace YOUR_API_KEY with an actual key from Google AI Studio.

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3. Initializing the Gemini Model

model = genai.GenerativeModel('gemini-pro')

• Purpose: Initializes the Gemini-Pro model for text-based tasks.
• Variants:
  • gemini-pro: Text-only model.
  • gemini-pro-vision: Multimodal (text + images).

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4. Generating Text Responses

response = model.generate_content("Explain quantum computing in simple terms.")
print(response.text)

• Workflow:
  1. Sends a prompt to the Gemini API.
  2. Returns and prints the generated response.

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5. Handling Multimodal Inputs

vision_model = genai.GenerativeModel('gemini-pro-vision')
response = vision_model.generate_content(["Describe this image:", uploaded_image])

• Use Case: Processes image inputs (e.g., uploaded files or URLs) alongside text prompts.

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6. Error Handling

try:
    response = model.generate_content("Unclear prompt")
except Exception as e:
    print(f"Error: {e}")

• Goal: Catches and displays API errors (e.g., invalid prompts, rate limits).

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7. License

This project is licensed under the MIT License.

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Author: Tanzeel
Repository: GEMINI_API_01

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How to Use

1. Clone the repo:

   git clone https://github.com/CodewithTanzeel/GEMINI_API_01.git

2. Open the notebook in Jupyter/Colab.
3. Replace YOUR_API_KEY with a valid key.
4. Run cells sequentially.

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Notes

• For advanced usage, refer to the official Gemini API docs.
• Avoid hardcoding API keys in shared notebooks. Use environment variables instead.