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# Update Prompt

PUT /apis/models/v2/workspaces/{workspace}/prompts/{name}
Content-Type: application/json

Update an existing prompt (full replacement of mutable fields).

Reference: https://docs.nvidia.com/nemo-platform/nemo-platform/v0.3.0/documentation/reference/api-reference/prompts/update-prompt-apis-models-v-2-workspaces-workspace-prompts-name-put

## Request

### Path parameters

- `workspace` (string, required)
- `name` (string, required)

### Body (application/json)

- `project` (string, optional) — The URN of the project associated with this prompt.
- `description` (string, optional)
- `messages` (list of object, optional)
  - `role` (enum, required) — The role of the message author.
    - Allowed values: `system`, `developer`, `user`, `assistant`
  - `content` (string, required) — Templated message content. May contain template variables.
- `input_variables` (list of string, optional)
- `tools` (list of object, optional)
  - `type` ("function", required) — The type of the tool. Currently only 'function' is supported.
  - `function` (object, required) — The function definition for this tool.
    - `name` (string, required) — The name of the function to be called.
    - `description` (string, optional) — A description of what the function does, used by the model to decide when and how to call it.
    - `parameters` (map from string to any, optional) — The parameters the function accepts, described as a JSON Schema object.
    - `strict` (boolean, optional) — Whether to enforce strict schema adherence when generating the function call.
- `tool_choice` (string or map from string to any, optional)
- `response_format` (map from string to any, optional)
- `inference_params` (object, optional) — Parameters for model inference. Extra fields can be supplied for additional options applied to the inference request directly. Fields not supported by the model may cause inference errors during evaluation.
  - `model` (string, optional) — Model identifier
  - `temperature` (double, optional) — Float value between 0 and 1. temp of 0 indicates greedy decoding, where the token with highest prob is chosen. Temperature can't be set to 0.0 currently
  - `max_tokens` (integer, optional) — Max tokens to generate
  - `max_completion_tokens` (integer, optional) — Max tokens to generate
  - `top_p` (double, optional) — Float value between 0 and 1; limits to the top tokens within a certain probability. top_p=0 means the model will only consider the single most likely token for the next prediction
  - `stop` (list of string, optional)
- `tags` (list of string, optional)

## Response

### 200

Update an existing prompt

- `name` (string, required) — Name of the entity. Name/workspace combo must be unique across all entities. Name must start with a lowercase letter, be 2-63 characters, and use lowercase letters, digits, hyphens, and dots (no consecutive hyphens, cannot end with a hyphen).
- `workspace` (string, required) — The workspace of the entity. Allowed characters: letters (a-z, A-Z), digits (0-9), underscores, hyphens, and dots.
- `created_at` (datetime, required) — The timestamp of model entity creation
- `updated_at` (datetime, required) — The timestamp of the last model entity update
- `id` (string, optional) — Unique identifier for the prompt.
- `project` (string, optional) — The URN of the project associated with this entity.
- `description` (string, optional) — Optional description of the prompt.
- `messages` (list of object, optional) — Ordered list of chat messages that make up the prompt.
  - `role` (enum, required) — The role of the message author.
    - Allowed values: `system`, `developer`, `user`, `assistant`
  - `content` (string, required) — Templated message content. May contain template variables.
- `input_variables` (list of string, optional) — Names of the Jinja2 template variables the prompt expects.
- `tools` (list of object, optional) — Optional OpenAI-compatible tool definitions to send with the prompt.
  - `type` ("function", required) — The type of the tool. Currently only 'function' is supported.
  - `function` (object, required) — The function definition for this tool.
    - `name` (string, required) — The name of the function to be called.
    - `description` (string, optional) — A description of what the function does, used by the model to decide when and how to call it.
    - `parameters` (map from string to any, optional) — The parameters the function accepts, described as a JSON Schema object.
    - `strict` (boolean, optional) — Whether to enforce strict schema adherence when generating the function call.
- `tool_choice` (string or map from string to any, optional) — Controls which (if any) tool is called: 'none', 'auto', 'required', or a named-tool object.
- `response_format` (map from string to any, optional) — Optional OpenAI-compatible response_format, e.g. a json_schema structured-output spec.
- `inference_params` (object, optional) — Optional default model and sampling parameters (temperature, top_p, max_tokens, ...).
  - `model` (string, optional) — Model identifier
  - `temperature` (double, optional) — Float value between 0 and 1. temp of 0 indicates greedy decoding, where the token with highest prob is chosen. Temperature can't be set to 0.0 currently
  - `max_tokens` (integer, optional) — Max tokens to generate
  - `max_completion_tokens` (integer, optional) — Max tokens to generate
  - `top_p` (double, optional) — Float value between 0 and 1; limits to the top tokens within a certain probability. top_p=0 means the model will only consider the single most likely token for the next prediction
  - `stop` (list of string, optional)
- `tags` (list of string, optional) — Optional free-form tags for organizing prompts.

## Examples

**Request**

```json
{}
```

**Response**

```json
{
  "name": "llama-3.1-8b",
  "workspace": "string",
  "created_at": "2024-01-15T09:30:00Z",
  "updated_at": "2024-01-15T09:30:00Z",
  "id": "string",
  "project": "string",
  "description": "string",
  "messages": [
    {
      "role": "system",
      "content": "string"
    }
  ],
  "input_variables": [
    "string"
  ],
  "tools": [
    {
      "type": "string",
      "function": {
        "name": "string",
        "description": "string",
        "parameters": {},
        "strict": true
      }
    }
  ],
  "tool_choice": {},
  "response_format": {},
  "inference_params": {
    "model": "string",
    "temperature": 1.1,
    "max_tokens": 1,
    "max_completion_tokens": 1,
    "top_p": 0.5,
    "stop": [
      "string"
    ]
  },
  "tags": [
    "string"
  ]
}
```

**SDK Code**

```python
import requests

url = "https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name"

payload = {}
headers = {"Content-Type": "application/json"}

response = requests.put(url, json=payload, headers=headers)

print(response.json())
```

```javascript
const url = 'https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name';
const options = {method: 'PUT', headers: {'Content-Type': 'application/json'}, body: '{}'};

try {
  const response = await fetch(url, options);
  const data = await response.json();
  console.log(data);
} catch (error) {
  console.error(error);
}
```

```go
package main

import (
	"fmt"
	"strings"
	"net/http"
	"io"
)

func main() {

	url := "https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name"

	payload := strings.NewReader("{}")

	req, _ := http.NewRequest("PUT", url, payload)

	req.Header.Add("Content-Type", "application/json")

	res, _ := http.DefaultClient.Do(req)

	defer res.Body.Close()
	body, _ := io.ReadAll(res.Body)

	fmt.Println(res)
	fmt.Println(string(body))

}
```

```ruby
require 'uri'
require 'net/http'

url = URI("https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name")

http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true

request = Net::HTTP::Put.new(url)
request["Content-Type"] = 'application/json'
request.body = "{}"

response = http.request(request)
puts response.read_body
```

```java
import com.mashape.unirest.http.HttpResponse;
import com.mashape.unirest.http.Unirest;

HttpResponse<String> response = Unirest.put("https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name")
  .header("Content-Type", "application/json")
  .body("{}")
  .asString();
```

```php
<?php
require_once('vendor/autoload.php');

$client = new \GuzzleHttp\Client();

$response = $client->request('PUT', 'https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name', [
  'body' => '{}',
  'headers' => [
    'Content-Type' => 'application/json',
  ],
]);

echo $response->getBody();
```

```csharp
using RestSharp;

var client = new RestClient("https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name");
var request = new RestRequest(Method.PUT);
request.AddHeader("Content-Type", "application/json");
request.AddParameter("application/json", "{}", ParameterType.RequestBody);
IRestResponse response = client.Execute(request);
```

```swift
import Foundation

let headers = ["Content-Type": "application/json"]
let parameters = [] as [String : Any]

let postData = JSONSerialization.data(withJSONObject: parameters, options: [])

let request = NSMutableURLRequest(url: NSURL(string: "https://api.example.com/apis/models/v2/workspaces/workspace/prompts/name")! as URL,
                                        cachePolicy: .useProtocolCachePolicy,
                                    timeoutInterval: 10.0)
request.httpMethod = "PUT"
request.allHTTPHeaderFields = headers
request.httpBody = postData as Data

let session = URLSession.shared
let dataTask = session.dataTask(with: request as URLRequest, completionHandler: { (data, response, error) -> Void in
  if (error != nil) {
    print(error as Any)
  } else {
    let httpResponse = response as? HTTPURLResponse
    print(httpResponse)
  }
})

dataTask.resume()
```