Generate chat completions

curl --location 'https://api.writer.com/v1/chat' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $WRITER_API_KEY" \
--data '{
    "model": "palmyra-x5",
    "messages": [
        {
            "role": "user",
            "content": "You are an expert at writing concise product descriptions for an E-Commerce Retailer"
        },
        {
            "role": "assistant",
            "content": "Okay, great I can help write these descriptions. Do you have a specific product in mind?"
        },
        {
            "role": "user",
            "content": "Please write a one sentence product description for a cozy, stylish sweater suitable for both casual and formal occasions"
        }
    ]
}'

from writerai import Writer

# Initialize the client. If you don't pass the `api_key` parameter,
# the client looks for the `WRITER_API_KEY` environment variable.
client = Writer()

chat_response = client.chat.chat(
  messages=[
    {
        "role": "user",
        "content": "You are an expert at writing concise product descriptions for an E-Commerce Retailer"
    },
    {
        "role": "assistant",
        "content": "Okay, great I can help write these descriptions. Do you have a specific product in mind?"
    },
    {
        "role": "user",
        "content": "Please write a one sentence product description for a cozy, stylish sweater suitable for both casual and formal occasions"
    }
  ],
  model="palmyra-x5"
)

print(chat_response.choices[0].message.content)

import { Writer } from 'writer-sdk';

// Initialize the Writer client. If you don't pass the `apiKey` parameter,
// the client looks for the `WRITER_API_KEY` environment variable.
const client = new Writer();  

const chatResponse = await client.chat.chat({
  messages: [
    {
        role: "user",
        content: "You are an expert at writing concise product descriptions for an E-Commerce Retailer"
    },
    {
        role: "assistant",
        content: "Okay, great I can help write these descriptions. Do you have a specific product in mind?"
    },
    {
        role: "user",
        content: "Please write a one sentence product description for a cozy, stylish sweater suitable for both casual and formal occasions"
    }
  ],
  model: 'palmyra-x5'
});

console.log(chatResponse.choices[0].message.content);

system_prompt = "You are a helpful assistant that responds in a casual, friendly tone and uses emojis in your responses."

messages = [
  {"role": "system", "content": system_prompt},
]

const system_prompt = "You are a helpful assistant that responds in a casual, friendly tone and uses emojis in your responses.";

let messages = [
  {role: "system", content: system_prompt},
];

# Stream the chat response to the user using the `stream` helper method
with client.chat.stream(messages=messages, model="palmyra-x5") as stream:
    for event in stream:
        # Check if the event is a content delta, which contains this chunk of the chat response
        if event.type == "content.delta":
            print(event.delta, end="", flush=True)
# Collect the full response from the stream
completion = stream.get_final_completion().choices[0].message.content

// Stream the chat response to the user using the `stream` helper method
const stream = client.chat.stream({
    model: 'palmyra-x5',
    messages: messages,
  })
  // Print this chunk of the chat response to the console
  .on('content', (diff) => process.stdout.write(diff));

// Collect the full response from the stream
let full_message = await stream.finalChatCompletion();
full_message = full_message.choices[0].message.content;

from writerai import Writer

# Initialize the client. If you don't pass the `api_key` parameter,
# the client looks for the `WRITER_API_KEY` environment variable.
client = Writer()

end = False
system_prompt = "You are a helpful assistant that responds in a casual, friendly tone and uses emojis in your responses."

# Ask the user for an initial message
input_message = "\nEnter a message for the assistant. Type 'exit' to end the conversation. > "
initial_message = input(input_message)

# Add the user's message to the conversation history
messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": initial_message}]

# Main loop to handle the conversation.
while not end:
    # Stream the chat response to the user using the `stream` helper method
    with client.chat.stream(messages=messages, model="palmyra-x5") as stream:
        for event in stream:
            # Check if the event is a content delta, which contains this chunk of the chat response
            if event.type == "content.delta":
                print(event.delta, end="", flush=True)
    # Collect the full response from the stream and add it to the conversation history
    full_message = stream.get_final_completion().choices[0].message.content
    messages.append({"role": "assistant", "content": full_message})
    new_message = input(input_message)
    messages.append({"role": "user", "content": new_message})
    if new_message == "exit":
        end = True

import { Writer } from 'writer-sdk';

// Initialize the Writer client. If you don't pass the `apiKey` parameter,
// the client looks for the `WRITER_API_KEY` environment variable.
const client = new Writer();  

// helpers for reading user input from the command line
// ----------------------------------------------------------------------------
const readline = await import('readline');

// Create an interface for input and output
const rl = readline.createInterface({
  input: process.stdin,
  output: process.stdout
});

// Prompt the user for input.
const prompt = (question) => {
  return new Promise((resolve) => {
    rl.question(question, (answer) => {
      resolve(answer);
    });
  });
};
// ----------------------------------------------------------------------------

let end = false;
let system_prompt = "You are a helpful assistant that responds in a casual, friendly tone and uses emojis in your responses.";
let initial_message = await prompt("Enter a message for the assistant. Type 'exit' to end the conversation. > ");
let messages = [{"role": "system", "content": system_prompt}, {"role": "user", "content": initial_message}];

// Main loop to handle the conversation.
while (!end) {
  // Stream the chat response to the user using the `stream` helper method
  const stream = client.chat.stream({
    model: 'palmyra-x5',
    messages: messages,
  })
  // Print this chunk of the chat response to the console
  .on('content', (diff) => process.stdout.write(diff));

  // Collect the full response from the stream and add it to the conversation history
  let full_message = await stream.finalChatCompletion();
  full_message = full_message.choices[0].message.content;
  messages.push({role: "assistant", content: full_message});
  console.log("\n");
  let new_message = await prompt("Enter a message for the assistant. Type 'exit' to end the conversation. > ");
  messages.push({role: "user", content: new_message});
  if (new_message === "exit") {
      end = true;
  }
}