GROQ LLAVA V1.5 7B
For GROQ LLAVA V1.5 7B, automate image analysis by sending images via Telegram. This workflow converts images to base64, queries the GROQ API for detailed descriptions, and returns results directly in your chat. Enhance communication and streamline image processing effortlessly.
View Large Image
Workflow Overview
For GROQ LLAVA V1.5 7B, automate image analysis by sending images via Telegram. This workflow converts images to base64, queries the GROQ API for detailed descriptions, and returns results directly in your chat. Enhance communication and streamline image processing effortlessly.
Target Audience
- Developers: Those who want to automate interactions with Telegram bots.
- Businesses: Companies looking to integrate image processing capabilities into their customer service or marketing strategies.
- Content Creators: Individuals who need to generate descriptions for images quickly and efficiently.
- Data Analysts: Professionals who require automated workflows to process and analyze image data.
Problem Solved
This workflow addresses the challenge of obtaining detailed descriptions of images sent via Telegram. It allows users to automate the process of receiving an image, converting it to base64, and sending it to the GROQ API for analysis, thereby saving time and effort in manual descriptions.
Workflow Steps
- Telegram Trigger: The workflow begins when a user sends an image to the Telegram bot.
- Receive the File: The bot retrieves the image file sent by the user.
- Convert the Image File to Base64: The image is converted to base64 format, which is required for the next step.
- HTTP Request to GROQ LLAVA: The base64 image is sent to the GROQ API along with a request for a detailed description of the image.
- Get Only the Text: The response from the GROQ API is processed to extract the description text.
- Telegram Send the Text: Finally, the description is sent back to the user in the Telegram chat.