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Quick Start Guide

Get up and running with AdMesh in under 5 minutes! This guide will walk you through making your first recommendation request using any of our SDKs.

Prerequisites​

  • ✅ AdMesh account (sign up here)
  • ✅ API key (get yours here)
  • ✅ Development environment (Python 3.8+, Node.js 18+, or React app)

Choose Your Adventure​

Select the SDK that matches your technology stack:

1. Install the Python SDK​

pip install admesh-python

2. Set up your environment​

# Create a .env file
echo "ADMESH_API_KEY=your_api_key_here" > .env

3. Make your first request​

import os
from admesh import Admesh

# Initialize the client
client = Admesh(api_key=os.environ.get("ADMESH_API_KEY"))

# Get recommendations
response = client.recommend.get_recommendations(
    query="Best CRM for remote teams",
    format="auto"
)

# Print results
print(f"Recommendation ID: {response.recommendation_id}")
print(f"Found {len(response.response.recommendations)} recommendations:")

for rec in response.response.recommendations:
    print(f"\n🎯 {rec.title}")
    print(f"   Reason: {rec.reason}")
    print(f"   Match Score: {rec.intent_match_score:.2f}")
    print(f"   Link: {rec.admesh_link}")

4. Run your code​

python your_script.py

Expected Output​

When you run any of the examples above, you should see output similar to:

Recommendation ID: rec_abc123xyz
Found 2 recommendations:

🎯 HubSpot CRM
   Reason: Perfect for remote teams with excellent collaboration features
   Match Score: 0.92
   Link: https://useadmesh.com/track?ad_id=hubspot-123

🎯 Salesforce
   Reason: Enterprise-grade CRM with powerful automation
   Match Score: 0.88
   Link: https://useadmesh.com/track?ad_id=salesforce-456

Understanding the Response​

Each recommendation includes:

  • title - Product name
  • reason - AI-generated explanation for why it's recommended
  • intent_match_score - How well it matches the query (0-1)
  • admesh_link - Tracked link for analytics and monetization
  • ad_id - Unique identifier for the advertisement
  • product_id - Unique identifier for the product

Next Steps​

🔧 Customize Your Integration​

For AI Applications: Check out our Ad Units Guide for chatbots and AI assistants.

For Web Applications: Explore our UI SDK Installation for rich recommendation displays.

For Backend Services: Learn about Python SDK and TypeScript SDK.

Calculate Your Earnings​

Ready to see your revenue potential? Use our earnings calculator to estimate how much you can earn with AdMesh recommendations based on your platform's traffic and engagement.

📚 Explore More Features​

  • Ad Units - Citation-based recommendations for AI assistants
  • API Reference - Complete API documentation
  • Examples - Implementation examples
  • UI SDK - Frontend component integration

🛠 Advanced Configuration​

Error Handling​

import admesh

try:
    response = client.recommend.get_recommendations(
        query="Best CRM for remote teams",
        format="auto"
    )
except admesh.NoRecommendationsError:
    print("No recommendations found for this query")
except admesh.RateLimitError:
    print("Rate limit exceeded, please try again later")
except admesh.APIError as e:
    print(f"API error: {e}")

Custom Parameters​

response = client.recommend.get_recommendations(
    query="Best CRM for remote teams",
    format="auto",
    max_recommendations=5,
    include_free_tier=True,
    min_trust_score=0.8
)

Troubleshooting​

Common Issues​

Authentication Error​

Error: Invalid API key

Solution: Double-check your API key and ensure it's set correctly in your environment variables.

No Recommendations​

NoRecommendationsError: No recommendations available

Solution: Try a different query or set raise_on_empty_recommendations=False to handle empty results gracefully.

Rate Limit​

RateLimitError: Rate limit exceeded

Solution: Implement exponential backoff or upgrade your plan for higher limits.

Getting Help​

🎉 Congratulations! You've successfully made your first AdMesh API call. Ready to build something amazing? Explore our detailed SDK guides and examples to learn more!