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AFFORAI API Integration With Make.com + Semantic Scholar -Perplexity API Alternative?

Science & Technology

Introduction

In this article, we will explore the integration of the AFFORAI API with Make.com, highlighting why this combination is a compelling alternative to the Perplexity API. For those unfamiliar with AFFORAI, it is a research tool designed to provide factual content by querying a range of sources, making it a suitable choice when you seek reliable answers.

Why Choose AFFORAI Over Perplexity API?

Users dissatisfied with Perplexity's performance may find AFFORAI to be a better alternative. The AFFORAI API offers a free service for up to 20 queries per day, utilizing advanced models such as GPT-4 Mini and HQ, with affordable plans starting at just $ 4 or $ 8 monthly—much more convenient compared to Perplexity's $ 20 monthly plan.

Key Features of AFFORAI API

  1. Document Uploading: Users can upload documents and directly query them.
  2. Semantic Scholar Access: It includes access to over 200 million peer-reviewed research papers.
  3. Real-Time Google Search: For the most current and accurate results, AFFORAI's integration with Google Search stands out as a significant advantage.

Working with AI Models

AFFORAI provides several AI models, including Omni, GPT-4, GPT-4 Mini, and Sonet. Users can connect with Open Router to utilize their preferred AI model, providing flexibility in data retrieval and response generation.

Getting Started with AFFORAI API

To start using the AFFORAI API, you first need an API key:

  1. Navigate to the API documentation accessible via the interface.
  2. Here you will find the API code and the corresponding costs for different API calls.

The basic API call allows users to select an AI model, such as GPT-3.5, and submit a query. For example, without selecting any tools, the model may simply return a default response.

Utilizing Document Retrieval

To use document retrieval, input the file ID from documents uploaded to your AFFORAI account. This feature enables querying specific files for precise information.

When looking for the latest information (such as Bitcoin prices), select the Google Search tool and specify the desired timeframe. This ensures the AI query gathers current data from Google.

Advanced Querying with Semantic Scholar

Using the Semantic Scholar tool, users can generate in-depth research articles on various topics by selecting specific fields of study and publication types. This feature is particularly useful for academic or research-oriented inquiries.

Example Queries

For instance, when querying about different breeds of cats, the model will aggregate findings from peer-reviewed papers, ensuring the information provided is accurate and comprehensive.

Conclusion

The integration of the AFFORAI API with Make.com presents a powerful tool for retrieving reliable information. With its unique features, AFFORAI is positioned as a strong alternative to Perplexity API for users seeking factual content and detailed insights.

Keywords

AFFORAI API, Make.com, Perplexity API, Semantic Scholar, AI models, document retrieval, Google Search, factual content

FAQ

What is AFFORAI API?
AFFORAI API is a research tool that allows users to retrieve accurate and factual information from various sources, including peer-reviewed papers and real-time searches.

How does AFFORAI compare to Perplexity API?
AFFORAI offers a free tier with up to 20 queries per day, lower pricing plans, and additional tools like document uploading and Google Search integration, making it a competitive alternative.

What AI models are available with AFFORAI?
AFFORAI provides access to multiple AI models including Omni, GPT-4, GPT-4 Mini, and Sonet, allowing users flexibility in their queries.

Can I run real-time searches with AFFORAI?
Yes, the AFFORAI API includes a real-time Google Search tool, enabling users to obtain the latest information available online.

What is Semantic Scholar access in AFFORAI?
Semantic Scholar access allows users to gather data from a vast database of peer-reviewed research papers to ensure the information is reliable and well-researched.