# LLM and GenAI applications
URL: https://docs.datarobot.com/en/docs/api/dev-learning/accelerators/llm-and-genai-apps/index.html

> LLM and GenAI applications that you can add to your experiment workflow.

# LLM and GenAI applications

| Topic | Description |
| --- | --- |
| Adaptive agent | Showcases an agent's ability to adapt its reasoning behavior based on conversation dynamics. |
| Direct Preference Optimization for reinforcement learning | Automates the process of fine-tuning an LLM using Direct Preference Optimization (DPO) and then deploying that model to DataRobot. |
| Product feedback automation | Use Predictive AI models in tandem with Generative AI models to overcome the limitation of guardrails around automating the summarization and segmentation of sentiment text. |
| Teams/Slack chatbots | Build collaborative app plug-ins, such as bots for Teams and Slack. |
| AI cluster labeling | Use cluster insights provided by DataRobot with ChatGPT to provide business- or domain-specific labels to the clusters using OpenAI and DataRobot APIs. |
| Customer communication AI | How generative AI models, like GPT-3, can be used to augment predictions and provide customer-friendly subject matter expert responses. |
| Support workflow optimization | Use generative AI models to cater to level-one requests, allowing support teams to focus on more pressing and high-visibility requests. |
| Data annotator app | Leverage the data annotator app to both label new data and label predicted data within an active learning situation after training a model with DataRobot. |
| AI data prep assistant | Use the AI data preparation assistant to streamline and automate the data preparation process. |
| JITR bot responses | Create a deployment to provide context-aware answers 'on the fly' using "Just In Time Retrieval" (JITR). |
| PDF RAG with LLM | Use an LLM as an OCR tool to extract all the text, table, and graph data from a PDF, then build a RAG and playground chat on DataRobot. |
| Healthcare conversation agent | Use Retrieval Augmented Generation to build a conversational agent for Healthcare professionals. |
| Teams GenAI integration | With DataRobot's Generative AI offerings, organizations can deploy chatbots without the need for an additional front-end or consumption layers. |
| Vector chunk visualization | Implement a Streamlit application to gain insights from a vector database of chunks. |
| XoT implementation | Implement and evaluate Everything of Thoughts (XoT) in DataRobot, an approach to make generative AI "think like humans." |
| Zero-shot error analysis | Use zero-shot text classification with large language models (LLMs), focusing on its application in error analysis of supervised text classification models. |
| Compliance agent | Automatically compare your active governance policies against pre-uploaded industry standards or internal benchmarks to identify inconsistencies. |

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