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sigoden edited this page Oct 24, 2024 · 5 revisions

Usage

Usage: aichat [OPTIONS] [TEXT]...

Arguments:
  [TEXT]...  Input text

Options:
  -m, --model <MODEL>        Select a LLM model
      --prompt <PROMPT>      Use the system prompt
  -r, --role <ROLE>          Select a role
  -s, --session [<SESSION>]  Start or join a session
      --empty-session        Ensure the session is empty
      --save-session         Force the session to be saved
  -a, --agent <AGENT>        Start a agent
  -R, --rag <RAG>            Start a RAG
      --serve [<ADDRESS>]    Serve the LLM API and WebAPP
  -e, --execute              Execute commands in natural language
  -c, --code                 Output code only
  -f, --file <FILE>          Include files with the message
  -S, --no-stream            Turn off stream mode
      --dry-run              Display the message without sending it
      --info                 Display information
      --list-models          List all available chat models
      --list-roles           List all roles
      --list-sessions        List all sessions
      --list-agents          List all agents
      --list-rags            List all RAGs
  -h, --help                 Print help
  -V, --version              Print version

Examples

aichat                                          # Enter REPL
aichat Tell a joke                              # Generate response

aichat -e install nvim                          # Execute command
aichat -c fibonacci in js                       # Generate code

aichat --serve                                  # Run server

aichat -m openai:gpt-4o                         # Select LLM

aichat -r role1                                 # Use role 'role1'
aichat -s                                       # Begin a temp session
aichat -s session1                              # Use session 'session1'
aichat -a agent1                                # Use agent 'agent1'
aichat -R rag1                                  # Use RAG 'rag1'

aichat --info                                   # View system info
aichat -r role1 --info                          # View role info
aichat -s session1 --info                       # View session info
aichat -a agent1 --info                         # View agent info
aichat -R rag1 --info                           # View RAG info

cat data.toml | aichat -c to json > data.json   # Pipe Input/Output
output=$(aichat -S $input)                      # Run in the script

aichat -f a.png -f b.png diff images            # Use files

Shell Assistant

Simply input what you want to do in natural language, and aichat will prompt and run the command that achieves your intent.

aichat-execute

AIChat is aware of OS and shell you are using, it will provide shell command for specific system you have.

Shell Integration

This is a very handy feature, which allows you to use aichat intelligent completions directly in your terminal.

aichat-integration

AIChat offers shell integration scripts for for bash, zsh, PowerShell, fish, and nushell. You can find them on GitHub at https://github.com/sigoden/aichat/tree/main/scripts/shell-integration.

Shell Autocompletion

The shell autocompletion suggests commands, options, and filenames as you type, enabling you to type less, work faster, and avoid typos.

aichat-autocompletions

AIChat offers shell completion scripts for bash, zsh, PowerShell, fish, and nushell. You can find them on GitHub at https://github.com/sigoden/aichat/tree/main/scripts/completions.

Generate Code

By using the --code or -c parameter, you can specifically request pure code output.

aichat-code

The -c/--code with pipe ensures the extraction of code from Markdown.

Use Files & Urls

The -f/--file can be used to send files to LLMs.

# Use local file
aichat -f data.txt
# Use image file
aichat -f image.png ocr
# Use multi files
aichat -f file1 -f file2 explain
# Use local dirs
aichat -f dir/ summarize
# Use remote URLs
aichat -f https://example.com/page summarize

Run Server

AIChat comes with a built-in lightweight http server.

$ aichat --serve
Chat Completions API: http://127.0.0.1:8000/v1/chat/completions
Embeddings API:       http://127.0.0.1:8000/v1/embeddings
LLM Playground:       http://127.0.0.1:8000/playground
LLM Arena:            http://127.0.0.1:8000/arena?num=2

Change the listening address:

$ aichat --serve 0.0.0.0
$ aichat --serve 8080
$ aichat --serve 0.0.0.0:8080
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