How to Use Gemini 2.5 for Coding or Debugging Tasks?

Praveen Kumar
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How to Use Gemini 2.5 for Coding or Debugging Tasks

🚀 Introduction

We’ve all hit roadblocks while writing code or debugging late into the night. With the release of Gemini 2.5, Google has made it easier to code, fix, and refactor faster—almost like having a senior engineer sitting next to you 24/7.

Let’s explore how to use Gemini 2.5 for real-world development tasks, with working code examples.

🧠 What Is Gemini 2.5?

Gemini 2.5 is Google’s AI-powered coding assistant that integrates with your IDE and cloud tools. It goes beyond autocomplete by offering:

Context-aware code suggestions
Inline debugging help
Auto-refactoring
Code generation from plain English prompts

👨‍💻 Setting Up Gemini 2.5

Gemini Code Assist can be used inside:

VS Code (via extension)
Android Studio (built-in)
JetBrains IDEs (via plugin)

Once installed:

# Login with your Google account linked to Google Cloud
gcloud auth login

Make sure your project has Gemini enabled under Vertex AI APIs.

⚙️ Using Gemini 2.5 for Coding Tasks

🔧 1. Generating a REST API in Flask

Prompt to Gemini:

“Create a Flask API with CRUD for managing tasks using SQLAlchemy.”

Gemini Output:

from flask import Flask, request, jsonify
from flask_sqlalchemy import SQLAlchemy

app = Flask(__name__)
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite:///tasks.db'
db = SQLAlchemy(app)

class Task(db.Model):
    id = db.Column(db.Integer, primary_key=True)
    title = db.Column(db.String(80), nullable=False)

@app.route('/tasks', methods=['POST'])
def create_task():
    data = request.get_json()
    new_task = Task(title=data['title'])
    db.session.add(new_task)
    db.session.commit()
    return jsonify({'id': new_task.id}), 201

@app.route('/tasks/<int:id>', methods=['GET'])
def get_task(id):
    task = Task.query.get_or_404(id)
    return jsonify({'id': task.id, 'title': task.title})

if __name__ == '__main__':
    app.run(debug=True)

🧠 2. Explaining Code Logic

Prompt to Gemini:

“Explain what this function does and if there’s a performance issue.”

def find_duplicates(nums):
    result = []
    for i in range(len(nums)):
        for j in range(i + 1, len(nums)):
            if nums[i] == nums[j] and nums[i] not in result:
                result.append(nums[i])
    return result

Gemini Output (explanation):

“This function finds duplicate numbers in a list, but it uses a nested loop, which results in O(n²) time complexity. It can be optimized using a set for better performance.”

Suggested Optimization:

def find_duplicates(nums):
    seen = set()
    duplicates = set()
    for num in nums:
        if num in seen:
            duplicates.add(num)
        else:
            seen.add(num)
    return list(duplicates)

🐛 Using Gemini 2.5 for Debugging Tasks

🕵️ 1. Debugging a Null Error

Code Example:

function greetUser(user) {
    console.log("Hello, " + user.name.toUpperCase());
}

Prompt to Gemini:

“Why is this throwing ‘Cannot read property of undefined’?”

Gemini Output:

“The error occurs if user is undefined or user.name is null. Add a null check before accessing name.”

Suggested Fix:

function greetUser(user) {
    if (user && user.name) {
        console.log("Hello, " + user.name.toUpperCase());
    } else {
        console.log("Hello, guest!");
    }
}

🔄 2. Refactoring Code

Prompt to Gemini:

“Refactor this code to use list comprehension and remove duplicates.”

result = []
for item in items:
    if item not in result:
        result.append(item)

Gemini Output:

result = list({item for item in items})

This version removes duplicates using a set and returns a list.

🔍 Bonus: Debugging with Context

You can also paste entire error logs or tracebacks, and Gemini will help interpret them.

Example Prompt:

“Help me fix this ValueError: too many values to unpack.”

Gemini Response:

“It likely means the code expected 2 variables but received more. Check for functions returning multiple values or improperly structured tuples.”

🧪 Real-World Use Case: Fixing a Race Condition in Go

Problem Code:

var count int

func increment() {
    for i := 0; i < 1000; i++ {
        count++
    }
}

Prompt to Gemini:

“Fix this race condition in Go.”

Gemini Output:

import "sync"

var count int
var mu sync.Mutex

func increment() {
    for i := 0; i < 1000; i++ {
        mu.Lock()
        count++
        mu.Unlock()
    }
}

To use the Gemini API (part of Google’s Vertex AI), you’ll interact with it via REST or client libraries (Python, Node.js, etc.) to access Gemini 1.5 / 2.5 models for tasks like code generation, debugging, chat, and multi-turn conversations.

How to use Gemini API in your code

Here’s a simple and complete guide to use Gemini API in your code, especially in Python using the official Google SDK.

✅ Prerequisites

Google Cloud Project with:
- Vertex AI API enabled
- Billing enabled
Service account key with proper permissions
Python 3.8+
Install Vertex AI SDK:

pip install google-cloud-aiplatform

⚙️ Step-by-Step: Using Gemini API in Python

🔐 Step 1: Authenticate

# Set your service account JSON key
export GOOGLE_APPLICATION_CREDENTIALS="path/to/your/service_account.json"

🧠 Step 2: Initialize Vertex AI

from vertexai.preview.language_models import ChatModel, CodeChatModel

# Optionally set your region
import vertexai
vertexai.init(project="your-project-id", location="us-central1")

💬 Step 3: Load Gemini 1.5/2.5 (Code Model)

model = CodeChatModel.from_pretrained("codechat-bison@001")  # for Gemini 1.5
chat = model.start_chat()

🧪 Step 4: Send a Coding Prompt

response = chat.send_message("Write a Python function to detect prime numbers.")
print(response.text)

💡 This will return a full function with docstring and explanation.

🐛 Example: Ask Gemini to Fix a Bug

buggy_code = """
def divide(a, b):
    return a / b

print(divide(5, 0))
"""

response = chat.send_message(f"Fix the following code to handle division by zero:\n\n{buggy_code}")
print(response.text)

🎯 Alternative: Use Gemini Text Model for General Chat

from vertexai.preview.language_models import ChatModel

model = ChatModel.from_pretrained("chat-bison@002")
chat = model.start_chat()
response = chat.send_message("Explain how recursion works in Python.")
print(response.text)

📁 Full Sample Output (for code generation)

Prompt:

Write a function to sort an array using bubble sort.

Response:

def bubble_sort(arr):
    n = len(arr)
    for i in range(n):
        for j in range(0, n - i - 1):
            if arr[j] > arr[j + 1]:
                arr[j], arr[j + 1] = arr[j + 1], arr[j]
    return arr

🚨 Notes:

Model names like codechat-bison@001, gemini-1.5-pro-preview-0409 can change. Check Vertex AI Model Garden for updates.
Gemini API also supports streaming, multimodal (image+text), and tool use (via functions) in advanced configurations.

💸 Is Gemini 2.5 Pro free?

✅ Free Access Options

Google AI Studio (aka ai.dev or AI Studio) grants free, unrestricted access to Gemini 2.5 Pro for experimentation—even via API calls. No payment or subscription required.
Gemini CLI, Google’s open‑source terminal tool, also provides free access: up to 60 requests per minute and 1,000 requests per day with Gemini 2.5 Pro model. Developer use only, no billing.
Gemini for Education extends significantly higher free limits to students and educators as part of a LearnLM initiative.

🧾 Paid Tiers & Subscription Plans

If you’re using Gemini through the Gemini app (chat interface) rather than AI Studio or API:

Google AI Pro plan (~$19.99 USD/month) unlocks consistent access to Gemini 2.5 Pro, Deep Research, search grounding, video tools, higher usage limits, and integration with Gmail, Docs, Chrome, etc.
Google AI Ultra at ~$249.99 USD/month provides the highest limits plus access to Deep Think mode and premium tools like Project Mariner and Veo video generation.

🧮 API Billing: Token-Based Pricing

When calling Gemini 2.5 Pro via Vertex AI API, even outside of free access environments like AI Studio, pricing is metered per token:

Token Range	Input Cost	Output Cost
≤ 200K tokens/million	$1.25	$10
> 200K tokens	$2.50	$15

These represent rates per million tokens. Think of input as your prompt + context, and output includes Gemini’s reasoning.

🧪 Example Scenarios

Experimenting in AI Studio: You get free access with no billing surprises. Ideal for rapid prototyping.
Coding via terminal using Gemini CLI: Free with limits (~60req/min, 1,000req/day). Great for lightweight scripting and debugging.
Student usage: Under Gemini for Education, students and educators may access Gemini 2.5 Pro freely with lifted limits.
Production-grade use on Vertex AI: You’re charged token-by-token as per table above, beyond any free-tier quota.

🔍 Summary Table

Access Method	Gemini 2.5 Pro Access	Cost / Limit Details
AI Studio (ai.dev)	✅ Free	No billing; ideal for prototypes
Gemini CLI (terminal tool)	✅ Free	60 req/min, 1,000 req/day
Gemini for Education (students)	✅ Free	Enhanced limits for academic users
API via Vertex AI (production)*	❌ Not free	Billed per token ($1.25 in / $10 out per million)
Gemini App with AI Pro plan	✅ Paid access	~$19.99/month for full access and higher limits
Gemini App with AI Ultra plan	✅ Paid access	~$249.99/month includes Deep Think and max limits

* Production usage context outside of free tiers.

🔗 Helpful Links:

✅ Final Thoughts

Gemini 2.5 is a productivity boost, not a replacement. From autocompleting CRUD operations to explaining time complexity, it acts like a real-time coding mentor and debugger.

And with features like:

Contextual refactoring
Prompt-based generation
Inline code comments and suggestions

it’s quickly becoming one of the most valuable tools in a developer’s arsenal.

How to Use Gemini 2.5 for Coding or Debugging Tasks?

🚀 Introduction

🧠 What Is Gemini 2.5?

👨‍💻 Setting Up Gemini 2.5

⚙️ Using Gemini 2.5 for Coding Tasks

🔧 1. Generating a REST API in Flask

🧠 2. Explaining Code Logic

🐛 Using Gemini 2.5 for Debugging Tasks

🕵️ 1. Debugging a Null Error

🔄 2. Refactoring Code

🔍 Bonus: Debugging with Context

🧪 Real-World Use Case: Fixing a Race Condition in Go

How to use Gemini API in your code

✅ Prerequisites

⚙️ Step-by-Step: Using Gemini API in Python

🎯 Alternative: Use Gemini Text Model for General Chat

📁 Full Sample Output (for code generation)

🚨 Notes:

💸 Is Gemini 2.5 Pro free?

✅ Free Access Options

🧾 Paid Tiers & Subscription Plans

🧮 API Billing: Token-Based Pricing

🧪 Example Scenarios

🔍 Summary Table

🔗 Helpful Links:

✅ Final Thoughts

💸 Is Gemini 2.5 Pro free?