10+ Tools to Use AI in the Terminal
In this video, we dive deep into various tools and techniques that allow you to leverage large language models directly in your command line interface. Like & Subscribe! :)
📚 Chapters:
00:00 - Introduction to Using AI in the Terminal
01:00 - Setting Up LLMCLI by Simon Willison
02:00 - Exploring Models and Configurations with LLMCLI
03:00 - Running Local Models with Olamma
04:00 - Managing Model Memory and Performance
05:00 - Working with Local Databases Using Data Set CLI
06:00 - Accessing and Filtering Interaction Logs
07:00 - Utilizing Embeddings with LLMCLI
08:00 - Creati…
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Chapters (32)
Introduction to Using AI in the Terminal
1:00
Setting Up LLMCLI by Simon Willison
2:00
Exploring Models and Configurations with LLMCLI
3:00
Running Local Models with Olamma
4:00
Managing Model Memory and Performance
5:00
Working with Local Databases Using Data Set CLI
6:00
Accessing and Filtering Interaction Logs
7:00
Utilizing Embeddings with LLMCLI
8:00
Creating Embeddings and Searching for Similarities
9:00
Converting Notes to Embeddings and Database Queries
10:00
Understanding Embedding Scores and Context
11:00
Generating Screenshots with Shot Scraper
12:00
Piping Data in the Terminal for Enhanced Productivity
13:00
Managing and Cleaning Terminal Output with Aliases
14:00
Using Bash and Python Scripts in Coordination with LLMs
15:00
Building Customized Aliases for LLM Interactions
16:00
Incorporating Piped Output into Advanced Scripts
17:00
Integration with Clipboard for Fast Workflow
18:00
Capture and Manipulate Output from LLMs
19:00
Chaining Prompts for Tiered Information Processing
20:00
Exploiting PDF to Text for Document Insights
21:00
Introduces git ingest and Reminders of Token Cost
22:00
Utilize r.jina.ai for Webpage to Markdown Conversion
23:00
Tools like Repo Mix and Files to Prompt for Efficient File Management
24:00
Agentic Use Cases with Autogen and Magenta CLI
25:00
Claude's Generative Capabilities in Project Building
26:00
Exploring Python Scripts with UV for Smooth Execution
27:00
Utilizing Inline Metadata for Efficient Packaging
28:00
Demonstrating UV-Run Python Scripts Step-by-Step
29:00
Using Python for LLM Output Navigation and Automation
30:00
Setting Up Claude Projects for Script Creation
31:00
Using Jinja Templates
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