Examples Hub

March 30, 2026 · View on GitHub

Last updated: 2026-01-24
Type: Code Examples
Purpose: Real-world usage patterns

Welcome to Examples

This section contains practical, production-ready code examples organized by use case. Each example is self-contained and can be used as a starting point for your own projects.

📚 Example Categories

Chat & Conversation

Learn how to use Webscout for AI chat interactions:

Basic Chat — Simple question-answer examples
Streaming Responses — Real-time response generation

Search & Information Retrieval

Integrate web search into your applications:

Search — DuckDuckGo, Bing, Brave, Yahoo, and other search engines
Search Integration — Combine search results with AI analysis

Media Generation

Create images and other media programmatically:

Text-to-Image — Generate images from descriptions
Text-to-Speech — Convert text to audio

Reliability & Resilience

Handle errors and failures gracefully:

Failover Patterns — Automatic provider switching
Error Handling — Robust error management
Retry & Timeout — Resilient API calls

Advanced Patterns

For experienced developers:

Custom Providers — Build your own provider
Batch Processing — Process multiple requests efficiently
Conversation Management — Multi-turn dialogues
Tool Calling — Function invocation with AI

Integration Patterns

Connect Webscout with other systems:

FastAPI Integration — Build web APIs
CLI Applications — Command-line tools
Scheduled Tasks — Recurring operations

🚀 Quick Start Examples

Simplest Chat Example

from webscout import Meta

# Initialize (no API key needed)
ai = Meta()

# Ask a question
response = ai.chat("What is Python?")
print(response)

With API Key

from webscout import GROQ

# Initialize with your API key
client = GROQ(api_key="your-groq-api-key")

# Get a response
response = client.chat("Explain quantum computing")
print(response)

With Streaming

from webscout import GROQ

client = GROQ(api_key="your-groq-api-key")

# Stream response in chunks
for chunk in client.chat("Write a haiku", stream=True):
    print(chunk, end="", flush=True)

📖 Learning Path

New to Webscout? Follow this sequence:

Basic Chat — Learn the fundamentals
Streaming Responses — Handle long responses
Search — Add web search capability
Failover Patterns — Make it production-ready
FastAPI Integration — Build a web app

🔍 Find Examples By Use Case

"I want to..."

Goal	Example
Ask simple questions	Basic Chat
Generate long text	Streaming Responses
Search the web	Search
Create images	Text-to-Image
Generate audio	Text-to-Speech
Handle errors	Failover Patterns
Process batches	Batch Processing
Build a web API	FastAPI Integration
Make CLI tools	CLI Applications
Schedule jobs	Scheduled Tasks

💡 Code Quality

All examples:

✅ Run without errors
✅ Include error handling
✅ Have comments explaining steps
✅ Show expected output
✅ Follow best practices
✅ Use type hints

🐍 Python Version Compatibility

Minimum required: Python 3.8+

Tested on:

Python 3.8
Python 3.9
Python 3.10
Python 3.11
Python 3.12

📝 Using These Examples

Copy & Modify

# 1. Copy the example code
# 2. Replace placeholder values:

# BEFORE (from example)
client = GROQ(api_key="your-groq-api-key")

# AFTER (your code)
import os
client = GROQ(api_key=os.getenv("GROQ_API_KEY"))

# 3. Run
python your_script.py

In Jupyter Notebooks

# Install in notebook (if needed)
!pip install webscout

# Import and use
from webscout import GROQ

client = GROQ(api_key="your-key")
response = client.chat("Hello")
print(response)

As a Module

# save_as: my_chat_module.py
from webscout import Meta

def ask_question(question: str) -> str:
    ai = Meta()
    return ai.chat(question)

if __name__ == "__main__":
    result = ask_question("What is AI?")
    print(result)

# Run
python my_chat_module.py

API Reference — Complete API documentation
Getting Started — Quick start guide
Troubleshooting — Solutions to problems
Provider Development — Create custom providers

📌 Common Patterns

Pattern 1: Simple Request-Response

from webscout import Meta

question = "What is machine learning?"
ai = Meta()
answer = ai.chat(question)
print(f"Q: {question}\nA: {answer}")

Pattern 2: Error Handling

from webscout import GROQ
from webscout.exceptions import AIProviderError

try:
    client = GROQ(api_key="key")
    response = client.chat("Hello")
except AIProviderError as e:
    print(f"Provider error: {e}")
except Exception as e:
    print(f"Error: {e}")

Pattern 3: Streaming with Progress

from webscout import GROQ

client = GROQ(api_key="key")
print("Generating response...")

for chunk in client.chat("Your prompt", stream=True):
    print(chunk, end="", flush=True)
print()  # Newline at end

Pattern 4: Batch Processing

from webscout import GROQ

client = GROQ(api_key="key")
questions = ["Q1?", "Q2?", "Q3?"]

for question in questions:
    response = client.chat(question)
    print(f"{question} → {response[:50]}...")