pip install gpt-chat-cli

export OPENAI_API_KEY="INSERT_SECRET_KEY"

source ~/.bashrc

$ gpt-chat-cli
GPT Chat CLI version 0.1.0
Press Control-D to exit
[#] Hello!
[gpt-3.5-turbo-0301] Hello! How can I assist you today?

$ gpt-chat-cli "In one sentence, who is Joseph Weizenbaum?"
[gpt-3.5-turbo-0301] Joseph Weizenbaum was a German-American computer scientist
and philosopher who is known for creating the ELIZA program, one of the first 
natural language processing programs.

$ gpt-chat-cli -i "What linux command prints a list of all open TCP sockets on port 8080?"
GPT Chat CLI version 0.1.0
Press Control-D to exit
[#] What linux command prints a list of all open TCP sockets on port 8080?
[gpt-3.5-turbo-0301] You can use the `lsof` (list open files) command to list all
open TCP sockets on a specific port. The command to list all open TCP sockets on
port 8080 is `sudo lsof -i :8080`


[#] Can you do this with ss?
[gpt-3.5-turbo-0301] Yes, you can also use the `ss` (socket statistics) command to
list all open TCP sockets on port 8080. The command to list all open TCP sockets
on port 8080 using `ss` is `sudo ss -tlnp 'sport = :8080'`

$ printf "What is smmsp in /etc/group?\n$(cat /etc/group | head)" | gpt-chat-cli
[gpt-3.5-turbo-0301] `smmsp` is a system user and group used by the Sendmail mail transfer agent (MTA)
for sending mail. The `smmsp` group is used to provide access to the Sendmail queue directory and
other Sendmail-related files. Members of this group are allowed to read and write to the Sendmail
queue directory and other Sendmail-related files.

$ gpt-chat-cli "Write rust code to find the average of a list" > average.rs
$ cat average.rs
Here's an example Rust code to find the average of a list of numbers:

fn main() {
    let numbers = vec![1, 2, 3, 4, 5];
    let sum: i32 = numbers.iter().sum();
    let count = numbers.len();
    let average = sum / count as i32;
    println!("The average is {}", average);
}

This code creates a vector of numbers, calculates the sum of the numbers using the `iter()` method and the `sum()` method, counts the number of elements in the vector using the `len()` method, and then calculates the average by dividing the sum by the count. Finally, it prints the average to the console.

$ gpt-chat-cli --list-models
gpt-3.5-turbo
gpt-3.5-turbo-0301
gpt-4
gpt-4-0314
gpt-4-32k

usage: gpt-chat-cli [-h] [-m MODEL] [-t TEMPERATURE] [-f FREQUENCY_PENALTY] [-p PRESENCE_PENALTY] [-k MAX_TOKENS] [-s TOP_P] [-n N_COMPLETIONS] [--system-message SYSTEM_MESSAGE] [--adornments {on,off,auto}]
                    [--color {on,off,auto}] [--version] [-l] [-i] [--prompt-from-fd PROMPT_FROM_FD | --prompt-from-file PROMPT_FROM_FILE]
                    [message]

positional arguments:
  message               The contents of the message. When in a interactive session, this is the initial prompt provided.

options:
  -h, --help            show this help message and exit
  -m MODEL, --model MODEL
                        ID of the model to use
  -t TEMPERATURE, --temperature TEMPERATURE
                        What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic.
  -f FREQUENCY_PENALTY, --frequency-penalty FREQUENCY_PENALTY
                        Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.
  -p PRESENCE_PENALTY, --presence-penalty PRESENCE_PENALTY
                        Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.
  -k MAX_TOKENS, --max-tokens MAX_TOKENS
                        The maximum number of tokens to generate in the chat completion. Defaults to 2048.
  -s TOP_P, --top-p TOP_P
                        An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens
                        comprising the top 10% probability mass are considered.
  -n N_COMPLETIONS, --n-completions N_COMPLETIONS
                        How many chat completion choices to generate for each input message.
  --system-message SYSTEM_MESSAGE
                        Specify an alternative system message.
  --adornments {on,off,auto}
                        Show adornments to indicate the model and response. Can be set to 'on', 'off', or 'auto'.
  --color {on,off,auto}
                        Set color to 'on', 'off', or 'auto'.
  --version             Print version and exit
  -l, --list-models     List models and exit
  -i, --interactive     Start an interactive session
  --prompt-from-fd PROMPT_FROM_FD
                        Obtain the initial prompt from the specified file descriptor
  --prompt-from-file PROMPT_FROM_FILE
                        Obtain the initial prompt from the specified file

The current date and time is 2023-05-06 15:55:56.619232. When emitting code or producing markdown, ensure to label fenced code blocks with the language in use.'

$ gpt-chat-cli -i --prompt-from-fd 3 3<<EOF
heredoc> Can you review this code:
heredoc> $(cat quicksort.c)
heredoc> EOF
[#] Can you review this code:
void quicksort(struct dl_entry ** entries, int low, int high){
  if(high - low < 1)
    return;

  int left = low + 1;
  int right = high;
  while(left < right){
    if(entries[right]->access_time < entries[low]->access_time)
      right--;
...
[gpt-3.5-turbo-0301] The code appears to be a valid implementation of the quicksort algorithm for 
sorting an array of pointers to `dl_entry` structures based on the `access_time` member. However, there are a few points that could be improved:

1. Naming: The function name `quicksort` is not very descriptive. It would be better to name it something like `quicksort_entries_by_access_time` to make it clear what it does.

...
[#]

$ alias gpt3='gpt-chat-cli -m gpt-3.5-turbo'
$ gpt3
[#] ...

function cmd {
    local request="$1"
    local shell=$(basename "${SHELL}")

    local os=""

    if command -v lsb_release >/dev/null 2>&1; then
        os="$ lsb_release -a\n$(lsb_release -a)\n"
    fi

    local kernel=""

    if command -v uname >/dev/null 2>&1; then
        kernel="$ uname -s -r\n$(uname -s -r)\n"
    fi

    local prompt=""

    prompt="${prompt}Suggest a command to be run in the $shell to accomplish the following task:\n\n"
    prompt="${prompt}$request\n\n"
    prompt="${prompt}Please output the command and a short description\n\n"

    if [ -n "${os}" ] || [ -n "${kernel}" ]; then
        prompt="${prompt}Here is some additional info about the system:\n\n${os}${kernel}"
    fi

    printf "$prompt" | gpt-chat-cli
}

$ cmd "test if ip forwarding is enabled"
[gpt-3.5-turbo-0301] You can use the `sysctl` command to test if IP forwarding is enabled. Here's the command you can run in your zsh shell:

sysctl net.ipv4.ip_forward

This command will return `net.ipv4.ip_forward = 0` if IP forwarding is disabled and `net.ipv4.ip_forward = 1` if IP forwarding is enabled.

openai.error.InvalidRequestError: This model's maximum context length is 4097 tokens. However, your messages resulted in 9758 tokens. Please reduce the length of the messages.