Tagged: Code

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Embedding models for Kannada

Table of Contents1 Open Weight Models1.1 nomic-embed-text-v2-moe1.2 paraphrase-multilingual1.3 bge-m31.4 snowflake-arctic-embed22 OpenAI Model2.1 text-embedding-3-large Embedding models transform words, sentences, documents, or digital items into vectors of numbers (usually floats) so that machines can understand and compare them semantically1. A good embedding model has enough information to capture the meaning and relationships in dense vector...

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Simple IMD Alerts

Table of Contents1 What I want2 IMD WMS Layer3 My plan4 Example pages5 Future improvements6 Note IMD (Indian Meteorological Department) has a district-level alert system. They give rain alerts for today and the next four days. They also have something called NowCast that shows the same alert level for now. Alerts are basically...

Year 2023 in Weekly Pictures 1

Year 2023 in Weekly Pictures

Below is the gallery of featured images from my 2023 weekly notes. It represents the year pictorially. It’s an exciting way to look at the year. At some point, I want to make a yearly flip book using these pictures, with locations and characters involved. It will be a good yearbook. Also, I...

KoboToolbox to CouchDB 1

Connecting KoboToolbox to CouchDB for Real Time Data

I have recommended KoboToolbox (and KoboCollect) for nonprofits, and we also use it at DataMeet to collect all kinds of data, including IDVC. For IDVC, I pull the data from KoboToolbox, do some massaging, and then upload it to CouchDB. It works very well. But what if I want to make this whole process real-time? 

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Creating Dynamic PDF reports using Jinja and Gotenberg

I use Jinja2 in a variety of ways. Sometimes to create SVGs and other times to create reports. Recently there was a requirement to create PDF reports as part of a service. Since the app already uses Python and Jinja2, we used that to generate PDF reports. Using data and Jinja2, we created...

Web-Powered Workflows: Fetching and Running Digdag Workflows with Callbacks 0

Web-Powered Workflows: Fetching and Running Digdag Workflows with Callbacks

In Digdag, workflows are typically defined in YAML files with a “.dig” extension. Developers usually write these workflows, which consist of tasks to be executed. However, tasks can also be added dynamically using the Digdag Python API or by downloading a “.dig” file from a remote HTTP server and incorporating it as a subtask. This approach is useful when a web service or app generates customized workflow files based on web app conditions, allowing the workflow logic to be managed externally. You can add webhooks to make it reactive.