Generate text from a prompt - Writer AI Studio

Text generation endpoint

You can use the text generation endpoint to generate text with an LLM.

You need an API key to access the Writer API. Get an API key by following the steps in the API quickstart. We recommend setting the API key as an environment variable in a .env file with the name WRITER_API_KEY.

Text generation vs. chat completion

The text generation endpoint is appropriate when you need to generate a single text response based on a given prompt, or when you want to ask a specific LLM a question. The chat completion endpoint can generate single messages, or create more complex conversations between a user and a general-purpose LLM. Additionally, the chat completion endpoint offers tool calling, which you can use to access other LLMs, Knowledge Graphs, and custom functions.

Endpoint overview

URL: POST https://api.writer.com/v1/completions

Using the /completions endpoint results in charges for model usage. See the pricing page for more information.

cURL

curl --location 'https://api.writer.com/v1/completions' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $WRITER_API_KEY" \
--data '{
  "model": "palmyra-x5",
  "prompt": "Tell me a story",
  "max_tokens": 1000,
  "temperature": 0.7,
  "stream": true
}'

Python

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()

text_generation = client.completions.create(
  model="palmyra-x5",
  prompt="Tell me a story",
  max_tokens=1000,
  temperature=0.7,
  stream=True
)

for chunk in text_generation:
    print(chunk.value, end="", flush=True)

JavaScript

import { Writer } from 'writer-sdk';

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

const text_generation = await client.completions.create({
  model: 'palmyra-x5',
  prompt: 'Tell me a story',
  max_tokens: 1000,
  temperature: 0.7,
  stream: true
});

for await (const chunk of text_generation) {
    process.stdout.write(chunk.value);
}

Request body

Below are the required and commonly used optional parameters for the text generation endpoint.

Parameter Type Description
model string Required. The ID of the model to use for text generation.
prompt string Required. The prompt to generate text from.
max_tokens int The maximum number of tokens to generate for the response. Defaults to 100.
temperature float Temperature influences the randomness in generated text. Defaults to 1. Increase the value for more creative responses, and decrease the value for more predictable responses.
stream Boolean A Boolean value that indicates whether to stream the response. Defaults to false.

See the full list of available parameters in the text generation endpoint reference.

Response parameters

Non-streaming response

If you set the stream parameter to false, the response is a single JSON object with the following parameters:

Parameter Type Description
model string The ID of the model used to generate the response.
choices array An array of choices objects.
choices[0].text string The generated text.
choices[0].log_probs object The log probabilities of the tokens in the generated text.
{
  "choices": [
    {
      "text": "Camping Gear: The Ultimate Guide\n\nCamping is a great way to get outdoors and enjoy nature",
      "log_probs": null
    }
  ],
  "model": "palmyra-x5"
}

Streaming response

If you set the stream parameter to true, the response is delivered as server-sent events with the following parameters:

Parameter Description
value The content of the chunk.
data: {"value":"Camping Gear: The Ultimate Guide\n\nCamping is a great way to get outdoors and enjoy nature"}

Generate streaming and non-streaming responses

The examples below generate a single message from the palmyra-x5 model, using the prompt “How can I treat a cold?”

Streaming response

The text generation endpoint supports streaming responses. The response comes in chunks until the entire response finishes. Streaming responses are useful when you want to display the generated text in real-time, or when you want to stream the response to a client, rather than waiting for the entire response to finish.

Example requests

cURL

curl --location 'https://api.writer.com/v1/completions' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $WRITER_API_KEY" \
--data '{
  "model": "palmyra-x5",
  "prompt": "How can I treat a cold?",
  "stream": true
}'

Python

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()

text_generation = client.completions.create(
  model="palmyra-x5",
  prompt="How can I treat a cold?",
  stream=True
)

for chunk in text_generation:
    print(chunk.value, end="", flush=True)

JavaScript

import { Writer } from 'writer-sdk';

const text_generation = await client.completions.create({
  model: 'palmyra-x5',
  prompt: 'How can I treat a cold?',
  stream: true
});

for await (const chunk of text_generation) {
    process.stdout.write(chunk.value);
}

Non-streaming response

For non-streaming responses, the response returns as a single JSON object after the entire response is complete. The text is in the choices[0].text field.

Example requests

cURL

curl --location 'https://api.writer.com/v1/completions' \
--header 'Content-Type: application/json' \
--header "Authorization: Bearer $WRITER_API_KEY" \
--data '{
  "model": "palmyra-x5",
  "prompt": "How can I treat a cold?",
  "stream": false
}'

Python

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()

text_generation = client.completions.create(
  model="palmyra-x5",
  prompt="How can I treat a cold?",
  stream=False
)

print(text_generation.choices[0].text)

JavaScript

import { Writer } from 'writer-sdk';

const text_generation = await client.completions.create({
  model: 'palmyra-x5',
  prompt: 'How can I treat a cold?',
  stream: false
});

console.log(text_generation.choices[0].text);