ChatPDF is an integration platform that empowers developers to interact with PDF documents through a robust API, allowing for information extraction and natural language conversations. With Relevance AI, you can elevate your PDF interactions by leveraging AI Agents to streamline and enhance your document workflows.
ChatPDF allows for natural language interactions with PDF documents, making information extraction effortless. Relevance AI amplifies this capability by enabling AI Agents to automate and optimize your PDF processing tasks.
Document Intelligence Mastery
Empowers AI agents with advanced PDF comprehension and contextual understanding across multiple documents simultaneously
Seamless Knowledge Orchestration
Enables fluid extraction and synthesis of information from vast PDF repositories with natural language processing capabilities
Rapid Information Synthesis
Accelerates document processing by transforming complex PDF content into actionable insights within seconds
Relevance AI integrates seamlessly with ChatPDF, enabling you to enhance your PDF workflows with intelligent AI Agents.
What you’ll need
You don't need to be a developer to set up this integration. Follow this simple guide to get started:
- A Relevance AI account
- An Airtable account with access to the base and table you'd like to use
- Authorization (you'll connect securely using OAuth—no sensitive info stored manually)
Security & Reliability
The ChatPDF integration platform allows developers to interact with PDF documents effortlessly through a robust API interface. This integration facilitates the uploading of PDFs, extraction of information, and natural language conversations with PDF content.
Key benefits include automated PDF document processing, natural language querying of PDF content, programmatic PDF management, and reference-based responses with page citations.
To get started, ensure you have a ChatPDF account with API access, OAuth credentials for authentication, and a Pipedream account if you are using the Pipedream integration. Your environment should support HTTPS, REST API calls, and JSON responses, with public internet access for PDF URL processing.
For installation, first set up your authentication by securely storing your OAuth credentials. Then, configure the base URL and headers for API requests. You can quickly add a PDF via URL, chat with a PDF, or delete a PDF using the provided code snippets.
Common API patterns include error handling to manage API responses effectively. Troubleshooting common issues such as authentication errors, PDF processing failures, and API rate limits is essential for smooth operation. Best practices include performance optimization, security measures, and comprehensive error handling.
API response codes help you understand the outcome of your requests, with codes indicating success, authentication errors, permission issues, and more. For further assistance, refer to the API documentation, support email, and current pricing page for rate limits.
Remember to replace placeholder values with actual credentials and endpoints when implementing the integration. For additional support or specific use cases, consult the full API documentation or contact ChatPDF support.
No training on your data
Your data remains private and is never utilized for model training purposes.
Security first
We never store anything we don’t need to. The inputs or outputs of your tools are never stored.
To get the most out of the 0CodeKit + Relevance AI integration without writing code:
- Start with a clear setup: Ensure your 0CodeKit account is properly configured with the necessary OAuth credentials and permissions.
- Utilize example code: Leverage the provided code snippets for PDF compression and barcode reading to jumpstart your integration.
- Validate inputs: Always check your input parameters for correctness before making API calls to avoid unnecessary errors.
- Test with sample data: Run your automations using test PDFs and images to ensure everything works smoothly before going live.
- Monitor API usage: Keep an eye on your API calls to avoid hitting rate limits, and implement caching where appropriate.
