Integrations
Edit Image
HTTP Request
If
Google Drive
Sticky Note
Manual Trigger
Basic LLM Chain
Structured Output Parser
Google Gemini Chat Model
This rantir workflow showcases the use of Multimodal LLMs for parsing and extracting information from PDF documents within rantir.
In this scenario, we’re reviewing a candidate’s CV/resume through an AI that filters out unqualified applications. However, the candidate has included a hidden prompt intended to bypass our filter! By leveraging AI Vision, we can effectively address this issue. Read on to learn how!
How it works
- The candidate’s CV/resume, in PDF format, is downloaded from Google Drive for demonstration purposes.
- The PDF is converted to a PNG image using Stirling PDF. Since the hidden prompt is in white font, it remains invisible in the converted image.
- The image is processed by a Basic LLM node using a multimodal model, such as Google’s Gemini 1.5 Pro.
- Within the Basic LLM node, a "User Message" with Binary type is configured, allowing us to send the image file directly in the request.
- The LLM now successfully ignores the hidden prompt, yielding the expected response.
Requirements
- Google Gemini API Key. Alternatively, GPT-4 can also handle this use case.
- Stirling PDF or another service for converting PDFs to images. For privacy, consider self-hosting Stirling PDF to avoid using public APIs.
Customizing the workflow
- Replace the manual trigger with a webhook or other trigger to integrate into your existing services.
- This example validates qualifications; you can expand it to extract data points like years of experience, previous employers, etc.
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