⚙️ Tools & Platforms in Gen AI

⚙️ Tools & Platforms in Gen AI

Here's a breakdown of key ⚙️ Tools & Platforms in Generative AI (Gen AI)—covering everything from model development to deployment and integration.


🚀 1. Foundation Models & APIs

These provide the core generative capabilities (text, image, audio, code, etc.).


Tool / Platform Description

OpenAI (GPT, DALL·E) Powerful APIs for text (ChatGPT), image (DALL·E), and code generation

Anthropic (Claude) Safety-focused large language models

Google Gemini Multimodal AI from Google DeepMind

Meta LLaMA Open-source language models for research & deployment

Mistral AI Lightweight and efficient open-source models

Cohere Language models optimized for retrieval-augmented generation (RAG)


🧠 2. Model Training & Fine-Tuning Platforms

Used to train or customize Gen AI models for specific use cases.


Tool Description

Hugging Face Transformers Open-source hub for pre-trained models & datasets

Vertex AI (Google Cloud) Managed Gen AI model training and serving

Amazon Bedrock / SageMaker Access to foundation models & fine-tuning capabilities

Azure OpenAI / ML Studio Managed access to OpenAI models & custom training tools

Weights & Biases Experiment tracking, model training analytics

LoRA / PEFT / QLoRA Efficient fine-tuning techniques for large models


🧪 3. Testing & Evaluation Tools

Used to benchmark performance, safety, and output quality.


Tool Description

Promptbench / Promptfoo Tools for comparing prompt outputs from multiple models

Helicone / LangSmith Logging, monitoring, and evaluation for LLMs

OpenPromptEval / RAGAS Open-source tools for prompt or RAG system evaluation

TruLens Evaluate LLM performance with metrics like helpfulness, honesty


🧰 4. Frameworks & Toolkits

Used for building Gen AI apps (especially LLM-based).


Tool / Framework Description

LangChain Framework for building LLM-powered apps with memory, chains, and tools

LlamaIndex Tools for building retrieval-augmented generation (RAG) apps

Haystack (deepset) Python framework for building LLM pipelines

Flowise Low-code visual builder for Gen AI workflows

AutoGen (Microsoft) Build multi-agent systems using LLMs

DSPy A framework for declarative LLM optimization and pipelines


💻 5. Deployment & Serving Platforms

Used to host models or Gen AI apps.


Tool / Platform Description

Replicate Deploy and run ML models with simple APIs

Modal / Baseten Model serving and hosting infrastructure

Hugging Face Inference Endpoints Easily deploy models in the cloud

Vercel / Netlify Host frontends that interact with Gen AI backends

LangServe / BentoML Serve LangChain or custom Gen AI pipelines as APIs


🔐 6. Responsible AI & Governance

Focus on safety, fairness, compliance, and auditability.


Tool Description

Guardrails AI Add safety and validation to LLM outputs

Azure Content Moderation Flag unsafe or biased content

OpenAI Moderation API Filter harmful content from LLM output

IBM AI Governance End-to-end oversight for AI lifecycle

AI Fairness 360 / Explainability 360 IBM open-source tools for model fairness & explainability


🧠 7. Popular Use Cases Enabled by Gen AI

Use Case Example Tools

Chatbots & Assistants ChatGPT, Claude, LangChain, Rasa

Code Generation GitHub Copilot, CodeWhisperer, Replit

Image & Video Generation DALL·E, Midjourney, RunwayML, Sora

Text Summarization / Q&A LlamaIndex, Cohere, Gemini Pro

Document Intelligence / RAG LangChain, Haystack, Azure AI Search


📌 Summary

Area Examples

Model Providers OpenAI, Anthropic, Google, Meta

Frameworks LangChain, LlamaIndex, DSPy

Deployment Hugging Face, Replicate, Modal

Safety Guardrails AI, Moderation APIs

Evaluation Promptbench, LangSmith, RAGAS


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