Скачать или смотреть Mistral AI Agents | Full Walkthrough

Mistral AI is one of the big AI labs providing various models including SotA LLM and embedding models, making them an ideal sole provider for retrieval tasks (such as RAG) that require both generation via LLMs and retrieval via embedding models.

The Aurelio Platform provides several utility services to help AI engineers build RAG and GenAI applications faster.

In this example we're going to use both of these together to create a "chat-with-video" AI pipeline. We'll see how to:

1. Take any YouTube video and transcribe it to text using Aurelio's video-to-text endpoint.
2. Use Mistral LLMs to chat with our transcribed video content.
3. Add chat history to make our AI conversational.
4. Integrate async and streaming for a better UX and improved scalability.
5. See how we can optimize response latency and costs by reducing overall token count using semantic similarity, using Aurelio's chunking endpoint and Mistral's embedding models.

📌 Code:
https://github.com/aurelio-labs/cookb...

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00:00 Mistral AI Agent
00:47 Python Setup
01:44 Video Transcription
03:25 Agent Overview
07:03 Using Mistral
09:26 Adding Agent Chat History
11:23 Async and Streaming
17:53 Agent Token Usage
19:17 Building a Retrieval Agent
25:52 Creating a Tool for Mistral
33:40 Tool Execution Logic