Take chatGPT into command line.
- clone this repo
- pip3 install -U -r requirements.txt
- copy
demo_config.json
toconfig.json
- get your OPENAI_API_KEY and put it in
config.json
$ ./gptcli.py -h
usage: gptcli.py [-h] [-c CONFIG]
options:
-h, --help show this help message and exit
-c CONFIG path to your config.json (default: config.json)
Sample config.json
:
{
"api_key": "sk-xxx",
"api_base": "https://chat.pppan.net/v1",
"model": "gpt-3.5-turbo",
"context": 2,
"stream": true,
"stream_render": true,
"showtokens": false,
"proxy": "socks5://localhost:1080",
"prompt": [
{ "role": "system", "content": "If your response contains code, show with syntax highlight, for example ```js\ncode\n```" }
]
}
- (required) api_key: OpenAI's api key. will read from OPENAI_API_KEY envronment variable if not set
- (optional) api_base: OpenAI's api base url. Can set to a server reverse proxy, for example Azure OpenAI Service or chatgptProxyAPI. By default it's from OPENAI_API_BASE or just https://api.openai.com/v1;
- (optional) api_type: OpenAI's api type, read from env OPENAI_API_TYPE by default;
- (optional) api_version: OpenAI's api version, read from env OPENAI_API_VERSION by default;
- (optional) api_organization: OpenAI's organization info, read from env OPENAI_ORGANIZATION by default;
- (optional) model: OpenAI's chat model, by default it's
gpt-3.5-turbo
; choices are:- gpt-3.5-turbo
- gpt-4
- gpt-4-32k
- (optional) context: Chat session context, choices are:
- 0: no context provided for every chat request, cost least tokens, but AI don't kown what you said before;
- 1: only use previous user questions as context;
- 2: use both previous questions and answers as context, would cost more tokens;
- (optional) stream: Output in stream mode;
- (optional) stream_render: Render markdown in stream mode, you can disable it to avoid some UI bugs;
- (optional) showtokens: Print used tokens after every chat;
- (optional) proxy: Use http/https/socks4a/socks5 proxy for requests to
api_base
; - (optional) prompt: Customize your prompt. This will appear in every chat request;
Console help (with tab-complete):
gptcli> .help -v
gptcli commands (use '.help -v' for verbose/'.help <topic>' for details):
======================================================================================================
.edit Run a text editor and optionally open a file with it
.help List available commands or provide detailed help for a specific command
.load Load conversation from Markdown/JSON file
.multiline input multiple lines, end with ctrl-d(Linux/macOS) or ctrl-z(Windows). Cancel
with ctrl-c
.prompt Load different prompts
.quit Exit this application
.reset Reset session, i.e. clear chat history
.save Save current conversation to Markdown/JSON file
.set Set a settable parameter or show current settings of parameters
.usage Tokens usage of current session / last N days, or print detail billing info
Run in Docker:
# build
$ docker build -t gptcli:latest .
# run
$ docker run -it --rm -v $PWD/.key:/gptcli/.key gptcli:latest -h
# for host proxy access:
$ docker run --rm -it -v $PWD/config.json:/gptcli/config.json --network host gptcli:latest -c /gptcli/config.json
- Single Python script
- Session based
- Markdown support with code syntax highlight
- Stream output support
- Proxy support (HTTP/HTTPS/SOCKS4A/SOCKS5)
- Multiline input support (via
.multiline
command) - Save and load session from file (Markdown/JSON) (via
.save
and.load
command) - Print tokens usage in realtime, and tokens usage for last N days, and billing details
- Integrate with
llama_index
to support chatting with documents