Why Build Your Own Grammar Checker?

Grammarly costs $12/month. QuillBot locks features behind $8.33/month. And all of them mangle your code—turning array.map() into "array dot map."

In this tutorial, you will build a grammar checker that:

• Corrects grammar, spelling, and punctuation using DeepSeek AI
• Preserves code blocks and technical terms (the secret is in the prompt)
• Shows a visual diff with red/green highlighting
• Works with 3 clicks, no signup required
• Costs under $0.001 per check

All in one afternoon. Let's build it.

What You Need

Before we start, grab these:

1. DeepSeek API key — get one from AiCredits ($3 for 5M tokens) or DeepSeek directly
2. Python 3.10+ with pip
3. Flask installed: pip install flask openai
4. A text editor

That is it. No database, no React, no Docker — just Python and HTML.

Step 1: The DeepSeek Prompt (The Secret Sauce)

The entire magic of a code-aware grammar checker is in the system prompt. Here is the one we use:

system_prompt = """You are a grammar checker. Fix grammar, spelling, and punctuation errors in the user's English text.

IMPORTANT RULES:
1. NEVER change code blocks, variable names, or technical terms
2. NEVER modify things like: npm install, git rebase, array.map(), useEffect
3. Only fix natural language text, leave code as-is
4. Return ONLY the corrected text, no explanations
5. Preserve the original formatting and line breaks"""

The key is rules 1-3: explicitly telling the model what NOT to touch. Without this, DeepSeek (or any LLM) will try to "fix" your code into proper English.

Step 2: The Flask Backend (30 lines)

Our backend is minimal—one endpoint that accepts text, sends it to DeepSeek, and returns the corrected version:

from flask import Flask, request, jsonify
from openai import OpenAI
import time

app = Flask(__name__)

client = OpenAI(
    api_key="YOUR_DEEPSEEK_API_KEY",
    base_url="https://api.aicreditsapi.com/v1"
)

@app.route("/check", methods=["POST"])
def check_grammar():
    text = request.json.get("text", "")
    if not text.strip():
        return jsonify({"error": "No text provided"}), 400
    
    start = time.time()
    response = client.chat.completions.create(
        model="deepseek-chat",
        messages=[
            {"role": "system", "content": system_prompt},
            {"role": "user", "content": text}
        ],
        temperature=0.1  # Low temp for consistency
    )
    elapsed = time.time() - start
    
    corrected = response.choices[0].message.content
    input_tokens = response.usage.prompt_tokens
    output_tokens = response.usage.completion_tokens
    cost = (input_tokens * 0.27 + output_tokens * 1.10) / 1_000_000  # DeepSeek pricing
    
    return jsonify({
        "original": text,
        "corrected": corrected,
        "tokens": input_tokens + output_tokens,
        "cost": round(cost, 6),
        "time": round(elapsed, 2)
    })

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

That is the entire backend — 30 lines. The temperature=0.1 keeps the output deterministic (no creative rewrites), and we track cost per request so you know exactly what you are spending.

Step 3: The Frontend — Visual Diff Engine

The most satisfying part of any grammar checker is seeing your mistakes turn into corrections in real time.

We use a simple word-by-word diff algorithm. Here is the core:

function computeDiff(original, corrected) {
    const origWords = original.split(/(\s+)/);
    const corrWords = corrected.split(/(\s+)/);
    let result = '';
    let i = 0, j = 0;
    
    while (i < origWords.length || j < corrWords.length) {
        if (origWords[i] === corrWords[j]) {
            result += origWords[i];
            i++; j++;
        } else {
            // Mark removed word in red
            if (i < origWords.length) {
                result += `${origWords[i]}`;
                i++;
            }
            // Mark added word in green
            if (j < corrWords.length) {
                result += `${corrWords[j]}`;
                j++;
            }
        }
    }
    return result;
}

CSS for the highlights:

.diff-del { background: #FCEBEB; color: #A32D2D; text-decoration: line-through; }
.diff-ins { background: #EAF3DE; color: #3B6D11; }

Step 4: Putting It Together — Full HTML Page

Here is a complete single-file version. Copy it, replace YOUR_API_KEY, and you are live:

  
Grammar Checker
  

    

      
Input
      
      Check Grammar
    
    

      
Result
      

        Corrected text will appear here.
      
    
  

Save this as templates/index.html in your Flask project, and you are done. One file, fully functional.

Step 5: Cost Analysis — How Cheap Is This Really?

Let's do the math. A typical grammar check on a 500-word document:

$0.001 per check. With the $3 Starter plan (5M tokens), you can run about 3,000 grammar checks. That is less than a tenth of Grammarly's monthly subscription — for potentially months of usage.

Going Further: Production-Ready Features

What you built is functional. Here is what you can add to make it production-ready:

1. Mode selector — Standard / Strict / Technical docs modes with different system prompts
2. Error stats — Show how many errors were found and fixed (count diff-ins and diff-dels)
3. Rate limiting — Add a daily free quota (3 checks) with registration for more
4. Multi-key failover — If one API key hits a rate limit, automatically switch to a backup key
5. Email the result — Let users send the corrected text to their email

All of these features are implemented in the free Lint Grammar Checker — check the source for reference.

Why DeepSeek for This?

You could build this with OpenAI's GPT-4o or Anthropic Claude. But DeepSeek has three advantages:

1. Price: 10-20x cheaper than GPT-4o for the same quality of grammar checking
2. Context window: 1M tokens — you can grammar-check an entire book in one API call
3. Speed: Sub-second response times for typical documents on the DeepSeek V4-Flash model

For a grammar checker — where you need cheap, fast, high-volume processing — DeepSeek is the clear winner.

Ready to build? Get your DeepSeek API key from $3 →