Tasking AI - How to build your AI application efficiently
AI Summary
Summary: Introduction to Tasking AI
- Background:
- OpenAI Playground users may feel limited by not being able to use new models like Claude3 and Mistral Large.
- Tasking AI is a new tool that allows switching between different AI models.
- Tasking AI Overview:
- Described as a swiss army knife for creating assistants.
- Cloud-based, open-source, and supports local deployment via Docker.
- No extensive coding experience required.
- Creating Assistants with Tasking AI:
- Assistant 1: Converts news articles into Twitter threads.
- Uses OpenAI models and a web reader plugin.
- Assistant 2: Retrieves current movies playing in theaters.
- Requires an action to access movie API since GPT 3.5 Turbo is offline.
- Assistant 3: Answers questions about YouTube video transcripts.
- Utilizes two Mistral models for chat completion and embedding.
- Tasking AI Features:
- Easy model selection and API key encryption.
- Tools for fetching content and interacting with APIs.
- Supports plugins and actions for task simplification.
- Allows for document retrieval and answering questions based on context.
- Using Tasking AI:
- Register and create a new project on tasking.ai.
- Add models, tools, and assistants through the Tasking AI console.
- Integrate with APIs for real-time data retrieval.
- Additional Capabilities:
- Python client SDK for running assistants programmatically.
- API keys management for secure access.
- Content Creation:
- Demonstrates creating assistants for specific tasks.
- Highlights the ease of use and versatility of Tasking AI.
- Conclusion:
- Tasking AI offers a flexible and user-friendly platform for creating AI assistants.
- Encourages viewers to subscribe for more content and offers to delve deeper into Tasking AI usage in future videos.