# Prompt Engineering for Grok Code Fast 1
`grok-code-fast-1` is a lightweight agentic model designed to excel as your pair-programmer inside most common coding tools.
## Overview
Grok Code Fast 1 is optimized for:
- Code generation
- Code completion
- Code explanation
- Debugging assistance
- Refactoring suggestions
### Specifications
| Feature | Value |
|---------|-------|
| Context Length | 256K tokens |
| Optimized For | Coding tasks |
| Speed | Fast inference |
## Best Practices
### 1. Be Specific About Language and Framework
**Good**:
```
Write a Python function using FastAPI that creates a REST endpoint
for user registration with email validation using Pydantic.
```
**Less Effective**:
```
Write a function for user registration.
```
### 2. Provide Context
Include relevant context like:
- Existing code structure
- Dependencies being used
- Coding standards to follow
```
Given this existing User model:
```python
class User(BaseModel):
id: int
email: str
name: str
```
Write a function to validate and create a new user.
```
### 3. Specify Output Format
```
Write a TypeScript function that:
1. Takes an array of numbers
2. Returns the sum
3. Include JSDoc comments
4. Add error handling for invalid inputs
```
### 4. Use Step-by-Step Instructions
For complex tasks, break them down:
```
Create a database connection module:
1. Use SQLAlchemy for PostgreSQL
2. Include connection pooling
3. Add retry logic for connection failures
4. Export a session factory function
5. Include proper type hints
```
### 5. Request Explanations When Needed
```
Explain this regex pattern and then write a function that uses it:
^(?=.*[A-Za-z])(?=.*\d)[A-Za-z\d]{8,}$
```
## Example Prompts
### Code Generation
```
Write a Python class for a binary search tree with:
- insert method
- search method
- delete method
- in-order traversal
Include type hints and docstrings.
```
### Debugging
```
This code throws "IndexError: list index out of range":
```python
def process_items(items):
for i in range(len(items) + 1):
print(items[i])
```
Find and fix the bug, then explain what was wrong.
```
### Refactoring
```
Refactor this code to use list comprehension and be more Pythonic:
```python
result = []
for item in items:
if item > 0:
result.append(item * 2)
```
```
### Code Review
```
Review this function for:
1. Potential bugs
2. Performance issues
3. Security concerns
4. Code style improvements
```python
def get_user(user_id):
query = f"SELECT * FROM users WHERE id = {user_id}"
return db.execute(query)
```
```
### Test Generation
```
Write unit tests for this function using pytest:
```python
def calculate_discount(price: float, discount_percent: float) -> float:
if discount_percent < 0 or discount_percent > 100:
raise ValueError("Discount must be between 0 and 100")
return price * (1 - discount_percent / 100)
```
Include tests for:
- Normal cases
- Edge cases
- Error cases
```
## API Usage
```python
from openai import OpenAI
client = OpenAI(
api_key=os.environ.get("XAI_API_KEY"),
base_url="https://api.x.ai/v1"
)
response = client.chat.completions.create(
model="grok-code-fast-1",
messages=[
{
"role": "system",
"content": "You are an expert Python developer. Write clean, well-documented code."
},
{
"role": "user",
"content": "Write a function to merge two sorted lists into one sorted list."
}
]
)
print(response.choices[0].message.content)
```
## IDE Integration Tips
When using Grok Code in IDEs:
1. **Provide file context**: Include surrounding code
2. **Specify cursor position**: Indicate where code should be inserted
3. **Include imports**: Show what's already imported
4. **Mention project type**: Framework, language version, etc.
## Limitations
- May not have knowledge of very recent library updates
- Complex architectural decisions may need human review
- Generated code should always be tested
- Security-critical code needs additional review
