Ashish Talati's starred repositories
AzureOpenAILogProbs
Examples of how-to use Azure OpenAI Log Probabilities (LogProbs) feature to enhance Generative AI - Q&A grounding.
tree-of-thoughts
Plug in and Play Implementation of Tree of Thoughts: Deliberate Problem Solving with Large Language Models that Elevates Model Reasoning by atleast 70%
activate-genai
Activate GenAI with Azure
azure-ai-search-lab
A web app that lets you play around with various AI-related search approaches
vector-search-azure-cosmos-db-postgresql
This sample shows how to build vector similarity search on Azure Cosmos DB for PostgreSQL using the pgvector extension and the multi-modal embeddings APIs of Azure AI Vision.
document-intelligence-user-feedback-processor
An experiment to provide the capabilities of Azure AI Document Intelligence Studio template training for feedback loop
kernel-memory
RAG architecture: index and query any data using LLM and natural language, track sources, show citations, asynchronous memory patterns.
enterprise-azureai
Unleash the power of Azure AI to your application developers in a secure & manageable way with Azure API Management and Azure Developer CLI.
counterfit
a CLI that provides a generic automation layer for assessing the security of ML models
azure-openai-rag-workshop
Create your own ChatGPT with Retrieval-Augmented-Generation workshop
llmops-workshop
Learn how to build solutions with Large Language Models.
LangChain-Udemy-Course
This Repo contains the code for the Udemy Course LangChain Full Course - Master LLM Powered Applications
rag-experiment-accelerator
The RAG Experiment Accelerator is a versatile tool designed to expedite and facilitate the process of conducting experiments and evaluations using Azure Cognitive Search and RAG pattern.
finops-toolkit
Tools and resources to help you adopt and implement FinOps capabilities that automate and extend the Microsoft Cloud.
llmops-promptflow-template
LLMOps with Prompt Flow is a "LLMOps template and guidance" to help you build LLM-infused apps using Prompt Flow. It offers a range of features including Centralized Code Hosting, Lifecycle Management, Variant and Hyperparameter Experimentation, A/B Deployment, reporting for all runs and experiments and so on.