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81 lines
2.7 KiB
81 lines
2.7 KiB
9 months ago
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# The `fabric` client
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This is the primary `fabric` client, which has multiple modes of operation.
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## Client modes
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You can use the client in three different modes:
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1. **Local Only:** You can use the client without a server, and it will use patterns it's downloaded from this repository, or ones that you specify.
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2. **Local Server:** You can run your own version of a Fabric Mill locally (on a private IP), which you can then connect to and use.
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3. **Remote Server:** You can specify a remote server that your client commands will then be calling.
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## Client features
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1. Standalone Mode: Run without needing a server.
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2. Clipboard Integration: Copy responses to the clipboard.
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3. File Output: Save responses to files for later reference.
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4. Pattern Module: Utilize specific patterns for different types of analysis.
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5. Server Mode: Operate the tool in server mode to control your own patterns and let your other apps access it.
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## Installation
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1. If you have this repository downloaded, you already have the client.
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`git clone git@github.com:danielmiessler/fabric.git`
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2. Navigate to the client's directory:
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`cd client`
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3. Set up a virtual environment:
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`python3 -m venv .venv`
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`source .venv/bin/activate`
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4. Install the required packages:
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`pip install -r requirements.txt`
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5. Copy to path:
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`echo export PATH=$PATH:$(pwd)` >> .bashrc` # or .zshrc
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6. Copy your OpenAI API key to the `.env` file in your `nvim ~/.config/fabric/` directory (or create that file and put it in)
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`OPENAI_API_KEY=[Your_API_Key]`
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## Usage
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To use `fabric`, call it with your desired options:
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python fabric.py [options]
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Options include:
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--pattern, -p: Select the module for analysis.
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--stream, -s: Stream output to another application.
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--output, -o: Save the response to a file.
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--copy, -c: Copy the response to the clipboard.
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Example:
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```bash
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# Pasting in an article about LLMs
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pbpaste | fabric --pattern extract_wisdom --output wisdom.txt | fabric --pattern summarize --stream
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```
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```markdown
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ONE SENTENCE SUMMARY:
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- The content covered the basics of LLMs and how they are used in everyday practice.
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MAIN POINTS:
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1. LLMs are large language models, and typically use the transformer architecture.
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2. LLMs used to be used for story generation, but they're now used for many AI applications.
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3. They are vulnerable to hallucination if not configured correctly, so be careful.
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TAKEAWAYS:
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1. It's possible to use LLMs for multiple AI use cases.
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2. It's important to validate that the results you're receiving are correct.
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3. The field of AI is moving faster than ever as a result of GenAI breakthroughs.
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```
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## Contributing
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We welcome contributions to Fabric, including improvements and feature additions to this client.
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## Credits
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The `fabric` client was created by Jonathan Dunn and Daniel Meissler.
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