In this video, we demonstrate how to use Streamlit to query the Mistral LLM locally with the help of Ollama. We’ll show you how to…
Continue reading → Evaluating AI-Generated Text: Semantic Similarity with Sentence Embeddings
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In this video, we demonstrate how to use Streamlit to query the Mistral LLM locally with the help of Ollama. We’ll show you how to…
Continue reading → Evaluating AI-Generated Text: Semantic Similarity with Sentence Embeddings
An article exploring the process for testing the output of Large Language Models (LLMs) using a tool called “promptfoo.” This tool allows developers to evaluate…
Continue reading → Promptfoo: The Ultimate Tool for Ensuring LLM Quality and Reliability (Part 2)
An article exploring the process for testing the output of Large Language Models (LLMs) using a tool called “promptfoo.” This tool allows developers to evaluate…
Continue reading → Promptfoo: The Ultimate Tool for Ensuring LLM Quality and Reliability (Part 1)
This video is part of a post “Building a Vue.js SPA (Single Page Application) Frontend with FastAPI Backend for AI Integration” QUICK DESCRIPTION Transitioning from…
Continue reading → Video #4 Connect FastAPI Backend to Vue.js Frontend: Full Guide
This video is part of a post “Building a Vue.js SPA (Single Page Application) Frontend with FastAPI Backend for AI Integration” QUICK DESCRIPTION Transitioning from…
Continue reading → Video #1 Scaffold Your First Vitejs App: Comprehensive Beginner’s Guide
This video is part of a post “Empower Your Workflow: Harnessing the Power of LM Studio and Ollama for Seamless Local LLM Execution” POST: https://wp.me/p3Vuhl-3iX…
This video is part of a post “Empower Your Workflow: Harnessing the Power of LM Studio and Ollama for Seamless Local LLM Execution” POST: https://wp.me/p3Vuhl-3iX…
This video is part of a post “Crafting Fluent Translation API: A quick Journey into Text Translation with NLLB, HuggingFace, and FastAPI, Plus a small…
This video is part of a post “Crafting Fluent Translation API: A quick Journey into Text Translation with NLLB, HuggingFace, and FastAPI, Plus a small…
This video is part of a post “Crafting Fluent Translation API: A quick Journey into Text Translation with NLLB, HuggingFace, and FastAPI, Plus a small…
This video is part of a post “Unlocking Speech-to-Text: Harnessing the Power of the OpenAI Whisper API with FastAPI Integration.” This file “009_openai_whisper_fastapi.py” is POC…
Continue reading → Using #whisper & #fastapi : Creating a #multilingual Audio #api with #whisper
This video is part of a post “Unlocking Speech-to-Text: Harnessing the Power of the OpenAI Whisper API with FastAPI Integration.” This file “011_faster_whisper.py” enables quick…
A simple combination with Streamlit, FastAPI and Spacy to expose “features” like: NER (entities), Summary (summary), Tags extraction (keywords) for text in French, Spanish, English…
POC from “005_fastapi_tiangolo_tutorial_sql_databases”: The example given by the official documentation of FastAPI with SQLAlchemy. POC “007_sql_databases_peewee”: The example given by the official documentation of FastAPI…
POC from 008_fastapi_mysql_restapi: Using Docker to create a MYSQL database and a PhpMyAdmin instance connected to FastAPI POC. This video is part of the post…
I already mention this POC. The files are a mix between logical code written by ChatGPT (I have given the prompt in the main.py) and…
A quite simple, educational and hybrid project that demonstrate how-to create an API with FastAPI (backend) that will be the backend a web app made…
Continue reading → #2 How-to create an API with FastAPI, backend for a web app made with Streamlit
I only grab the API and the test (pytest) from this project. In reality, it is a bit more extended project, made by Microsoft’s people…
Continue reading → #3 How-to create an API with FastAPI and start testing it with pytest
This video is part of the post “The importance of the Labeling process or annotating inside an ML pipeline plus an example on how-to train…
This video is part of the post “The importance of the Labeling process or annotating inside an ML pipeline plus an example on how-to train…