Akash Talole's repositories
ai-chat-app-protocol
A description of the HTTP protocol used by multiple Azure AI chat solutions.
akashtalole
Config files for my GitHub profile.
amazon-sagemaker-examples
Example 📓 Jupyter notebooks that demonstrate how to build, train, and deploy machine learning models using 🧠 Amazon SageMaker.
azure-openai-benchmark
Azure OpenAI benchmarking tool
Azure-OpenAI-demos
Azure OpenAI (demos, documentation, accelerators).
azurechat
🤖 💼 Azure Chat Solution Accelerator powered by Azure Open AI Service
conversational-ai-assistant-multi-route-chain
This GitHub repository guides you through building an advanced Conversational AI assistant using AWS services and Anthropic's Claude V2 model. It features intelligent routing to relevant functions, database querying, semantic searches, Lambda function executions, and specialized interactions.
dspy
DSPy: The framework for programming—not prompting—foundation models
FinRobot
FinRobot: An Open-Source AI Agent Platform for Financial Applications using LLMs 🚀 🚀 🚀
genai-quickstart-pocs
This repository contains sample code demonstrating various use cases leveraging Amazon Bedrock and Generative AI. Each sample is a separate project with its own directory, and includes a basic Streamlit frontend to help users quickly set up a proof of concept.
generative-ai-for-semiconductor-design
Generative AI for Semiconductor Design: Engineering Assistant built with Bedrock, Knowledge Bases and Langchain
GenerativeAIExamples
Generative AI reference workflows optimized for accelerated infrastructure and microservice architecture.
GPT-RAG
Sharing the learning along the way we been gathering to enable Azure OpenAI at enterprise scale in a secure manner. GPT-RAG core is a Retrieval-Augmented Generation pattern running in Azure, using Azure Cognitive Search for retrieval and Azure OpenAI large language models to power ChatGPT-style and Q&A experiences.
guardrails
Adding guardrails to large language models.
instructor
structured outputs for llms
NeMo-Guardrails
NeMo Guardrails is an open-source toolkit for easily adding programmable guardrails to LLM-based conversational systems.
qnabot-on-aws
AWS QnABot is a multi-channel, multi-language conversational interface (chatbot) that responds to your customer's questions, answers, and feedback. The solution allows you to deploy a fully functional chatbot across multiple channels including chat, voice, SMS and Amazon Alexa.
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.
ragapp
The easiest way to use Agentic RAG in any enterprise
ragas
Evaluation framework for your Retrieval Augmented Generation (RAG) pipelines
sec-insights
A real world full-stack application using LlamaIndex