Custom Prompter Model
Integrate a prompter model into an LLM workflow
A prompter model is a type of language model specifically designed to craft instructions that guide the output of large language models (LLMs). It helps in prompt engineering, focusing on optimizing the responses of LLMs to prompts.
Let's demonstrate how you can create your own prompter model and connect it to an LLM in a workflow.
info
The initialization code used in the following examples is outlined in detail on the client installation page.
Create a Prompter Model
- Python
- JavaScript (REST)
- NodeJS
- Java
- PHP
- cURL
##########################################################################################
# In this section, we set the user authentication, app ID, model ID, and model type ID.
# Change these strings to run your own example.
#########################################################################################
USER_ID = 'YOUR_USER_ID_HERE'
# Your PAT (Personal Access Token) can be found in the Account's Security section
PAT = 'YOUR_PAT_HERE'
APP_ID = 'YOUR_APP_ID_HERE'
# Change these to create your own model
MODEL_ID = 'my-prompter-model'
MODEL_TYPE_ID = 'prompter'
##########################################################################
# YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
##########################################################################
from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
from clarifai_grpc.grpc.api.status import status_code_pb2
channel = ClarifaiChannel.get_grpc_channel()
stub = service_pb2_grpc.V2Stub(channel)
metadata = (('authorization', 'Key ' + PAT),)
userDataObject = resources_pb2.UserAppIDSet(user_id=USER_ID, app_id=APP_ID)
post_models_response = stub.PostModels(
service_pb2.PostModelsRequest(
user_app_id=userDataObject,
models=[
resources_pb2.Model(
id=MODEL_ID,
model_type_id=MODEL_TYPE_ID
)
]
),
metadata=metadata
)
if post_models_response.status.code != status_code_pb2.SUCCESS:
print(post_models_response.status)
raise Exception("Post models failed, status: " + post_models_response.status.description)
<!--index.html file-->
<script>
///////////////////////////////////////////////////////////////////////////////////////////
// In this section, we set the user authentication, app ID, model ID, and model type ID.
// Change these strings to run your own example.
//////////////////////////////////////////////////////////////////////////////////////////
const USER_ID = 'YOUR_USER_ID_HERE';
// Your PAT (Personal Access Token) can be found in the Account's Security section
const PAT = 'YOUR_PAT_HERE';
const APP_ID = 'YOUR_APP_ID_HERE';
// Change these to create your own model
const MODEL_ID = 'my-prompter-model';
const MODEL_TYPE_ID = 'prompter';
///////////////////////////////////////////////////////////////////////////////////
// YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
///////////////////////////////////////////////////////////////////////////////////
const raw = JSON.stringify({
"user_app_id": {
"user_id": USER_ID,
"app_id": APP_ID
},
"model": {
"id": MODEL_ID,
"model_type_id": MODEL_TYPE_ID
}
});
const requestOptions = {
method: 'POST',
headers: {
'Accept': 'application/json',
'Authorization': 'Key ' + PAT
},
body: raw
};
fetch("https://api.clarifai.com/v2/models", requestOptions)
.then(response => response.text())
.then(result => console.log(result))
.catch(error => console.log('error', error));
</script>
//index.js file
////////////////////////////////////////////////////////////////////////////////////////////
// In this section, we set the user authentication, app ID, model ID, and model type ID.
// Change these strings to run your own example.
///////////////////////////////////////////////////////////////////////////////////////////
const USER_ID = 'YOUR_USER_ID_HERE';
// Your PAT (Personal Access Token) can be found in the Account's Security section
const PAT = 'YOUR_PAT_HERE';
const APP_ID = 'YOUR_APP_ID_HERE';
// Change these to create your own model
const MODEL_ID = 'my-prompter-model';
const MODEL_TYPE_ID = 'prompter';
/////////////////////////////////////////////////////////////////////////////
// YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
/////////////////////////////////////////////////////////////////////////////
const { ClarifaiStub, grpc } = require("clarifai-nodejs-grpc");
const stub = ClarifaiStub.grpc();
// This will be used by every Clarifai endpoint call
const metadata = new grpc.Metadata();
metadata.set("authorization", "Key " + PAT);
stub.PostModels(
{
user_app_id: {
"user_id": USER_ID,
"app_id": APP_ID
},
models: [
{
id: MODEL_ID,
model_type_id: MODEL_TYPE_ID
}
]
},
metadata,
(err, response) => {
if (err) {
throw new Error(err);
}
if (response.status.code !== 10000) {
throw new Error("Post models failed, status: " + response.status.description);
}
}
);
package com.clarifai.example;
import com.clarifai.grpc.api.*;
import com.clarifai.channel.ClarifaiChannel;
import com.clarifai.credentials.ClarifaiCallCredentials;
import com.clarifai.grpc.api.status.StatusCode;
public class ClarifaiExample {
////////////////////////////////////////////////////////////////////////////////////////////
// In this section, we set the user authentication, app ID, model ID, and model type ID.
// Change these strings to run your own example.
///////////////////////////////////////////////////////////////////////////////////////////
static final String USER_ID = "YOUR_USER_ID_HERE";
//Your PAT (Personal Access Token) can be found in the portal under Authentication
static final String PAT = "YOUR_PAT_HERE";
static final String APP_ID = "YOUR_APP_ID_HERE";
// Change these to create your own model
static final String MODEL_ID = "my-prompter-model";
static final String MODEL_TYPE_ID = "prompter";
///////////////////////////////////////////////////////////////////////////////////
// YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
///////////////////////////////////////////////////////////////////////////////////
public static void main(String[] args) {
V2Grpc.V2BlockingStub stub = V2Grpc.newBlockingStub(ClarifaiChannel.INSTANCE.getGrpcChannel())
.withCallCredentials(new ClarifaiCallCredentials(PAT));
SingleModelResponse postModelsResponse = stub.postModels(
PostModelsRequest.newBuilder()
.setUserAppId(UserAppIDSet.newBuilder().setUserId(USER_ID).setAppId(APP_ID))
.addModels(
Model.newBuilder()
.setId(MODEL_ID)
.setModelTypeId(MODEL_TYPE_ID)
).build()
);
if (postModelsResponse.getStatus().getCode() != StatusCode.SUCCESS) {
throw new RuntimeException("Post models failed, status: " + postModelsResponse.getStatus());
}
}
}
<?php
require __DIR__ . "/vendor/autoload.php";
/////////////////////////////////////////////////////////////////////////////////////////////////
// In this section, we set the user authentication, app ID, model ID, and model type ID.
// Change these strings to run your own example.
/////////////////////////////////////////////////////////////////////////////////////////////////
$USER_ID = "YOUR_USER_ID_HERE";
// Your PAT (Personal Access Token) can be found in the Account's Security section
$PAT = "YOUR_PAT_HERE";
$APP_ID = "YOUR_APP_ID_HERE";
// Change these to create your own model
$MODEL_ID = "my-prompter-model";
$MODEL_TYPE_ID = "prompter";
///////////////////////////////////////////////////////////////////////////////////
// YOU DO NOT NEED TO CHANGE ANYTHING BELOW THIS LINE TO RUN THIS EXAMPLE
///////////////////////////////////////////////////////////////////////////////////
use Clarifai\ClarifaiClient;
use Clarifai\Api\Model;
use Clarifai\Api\PostModelsRequest;
use Clarifai\Api\Status\StatusCode;
use Clarifai\Api\UserAppIDSet;
$client = ClarifaiClient::grpc();
$metadata = ["Authorization" => ["Key " . $PAT]];
$userDataObject = new UserAppIDSet([
"user_id" => $USER_ID,
"app_id" => $APP_ID,
]);
// Let's make a RPC call to the Clarifai platform. It uses the opened gRPC client channel to communicate a
// request and then wait for the response
[$response, $status] = $client->PostModels(
// The request object carries the request along with the request status and other metadata related to the request itself
new PostModelsRequest([
"user_app_id" => $userDataObject,
"models" => [
new Model([
"id" => $MODEL_ID,
"model_type_id" => $MODEL_TYPE_ID,
]),
],
]),
$metadata
)->wait();
// A response is returned and the first thing we do is check the status of it
// A successful response will have a status code of 0; otherwise, there is some error
if ($status->code !== 0) {
throw new Exception("Error: {$status->details}");
}
// In addition to the RPC response status, there is a Clarifai API status that reports if the operation was a success or failure
// (not just that the communication was successful)
if ($response->getStatus()->getCode() != StatusCode::SUCCESS) {
throw new Exception("Failure response: " . $response->getStatus()->getDescription() . " " . $response->getStatus()->getDetails());
}
?>
curl -X POST "https://api.clarifai.com/v2/users/YOUR_USER_ID_HERE/apps/YOUR_APP_ID_HERE/models" \
-H "Authorization: Key YOUR_PAT_HERE" \
-H "Content-Type: application/json" \
-d '{
"model": {
"id": "my-prompter-model",
"model_type_id": "prompter"
}
}'
Text Output Example
Predicted output for the model: `my-prompter-model`
Classify whether the sentiment of the given text is positive or negative I love your product very much
Predicted output for the model: `GPT-4`
The sentiment of the given text is positive.