Fine-tune

Upload a file

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Upload a file for fine-tuning
file = portkey.files.create(
    file=open("dataset.jsonl", "rb"),
    purpose="fine-tune"
)

print(file)

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Upload a file for fine-tuning
file = portkey.files.create(
    file=open("dataset.jsonl", "rb"),
    purpose="fine-tune"
)

print(file)

import { Portkey } from "portkey-ai";
import * as fs from 'fs';

// Initialize the Portkey client
const portkey = Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

(async () => {
    // Upload a file for fine-tuning
    const file = await portkey.files.create({
        file: fs.createReadStream("dataset.jsonl"),
        purpose: "fine-tune"
    });

    console.log(file);
})();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        virtual_key="VIRTUAL_KEY",
        api_key="PORTKEY_API_KEY"
    )
)

# Upload a file for fine-tuning
file = openai.files.create(
    file=open("dataset.jsonl", "rb"),
    purpose="fine-tune"
)

print(file)

import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai';
import * as fs from 'fs';

const openai = new OpenAI({
    apiKey: 'OPENAI_API_KEY',
    baseURL: PORTKEY_GATEWAY_URL,
    defaultHeaders: createHeaders({
        virtualKey: "VIRTUAL_KEY",
        apiKey: "PORTKEY_API_KEY"
    })
});

(async () => {
    // Upload a file for fine-tuning
    const file = await openai.files.create({
        file: fs.createReadStream("dataset.jsonl"),
        purpose: "fine-tune"
    });

    console.log(file);
})();

curl -X POST --header 'x-portkey-api-key: <portkey_api_key>' \
 --header 'x-portkey-virtual-key: <virtual_key>' \
 --form '[email protected]' \
 --form 'purpose=fine-tune' \
 'https://api.portkey.ai/v1/files'

Create a fine-tuning job

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Create a fine-tuning job
fine_tune_job = portkey.fine_tuning.jobs.create(
    model="gpt-3.5-turbo", # Base model to fine-tune
    training_file="file_id", # ID of the uploaded training file
    validation_file="file_id", # Optional: ID of the uploaded validation file
    suffix="finetune_name", # Custom suffix for the fine-tuned model name
    hyperparameters={
        "n_epochs": 1
    }
)

print(fine_tune_job)

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Create a fine-tuning job
fine_tune_job = portkey.fine_tuning.jobs.create(
    model="gpt-3.5-turbo", # Base model to fine-tune
    training_file="file_id", # ID of the uploaded training file
    validation_file="file_id", # Optional: ID of the uploaded validation file
    suffix="finetune_name", # Custom suffix for the fine-tuned model name
    hyperparameters={
        "n_epochs": 1
    }
)

print(fine_tune_job)

import { Portkey } from "portkey-ai";

// Initialize the Portkey client
const portkey = Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

(async () => {
    // Create a fine-tuning job
    const fineTuneJob = await portkey.fineTuning.jobs.create({
        model: "gpt-3.5-turbo", // Base model to fine-tune
        training_file: "file_id", // ID of the uploaded training file
        validation_file: "file_id", // Optional: ID of the uploaded validation file
        suffix: "finetune_name", // Custom suffix for the fine-tuned model name
        hyperparameters: {
            n_epochs: 1
        }
    });

    console.log(fineTuneJob);
})();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        virtual_key="VIRTUAL_KEY",
        api_key="PORTKEY_API_KEY"
    )
)

# Create a fine-tuning job
fine_tune_job = openai.fine_tuning.jobs.create(
    model="gpt-3.5-turbo", # Base model to fine-tune
    training_file="file_id", # ID of the uploaded training file
    validation_file="file_id", # Optional: ID of the uploaded validation file
    suffix="finetune_name", # Custom suffix for the fine-tuned model name
    hyperparameters={
        "n_epochs": 1
    }
)

print(fine_tune_job)

import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai';

const openai = new OpenAI({
    apiKey: 'OPENAI_API_KEY',
    baseURL: PORTKEY_GATEWAY_URL,
    defaultHeaders: createHeaders({
        virtualKey: "VIRTUAL_KEY",
        apiKey: "PORTKEY_API_KEY"
    })
});

(async () => {
    // Create a fine-tuning job
    const fineTuneJob = await openai.fineTuning.jobs.create({
        model: "gpt-3.5-turbo", // Base model to fine-tune
        training_file: "file_id", // ID of the uploaded training file
        validation_file: "file_id", // Optional: ID of the uploaded validation file
        suffix: "finetune_name", // Custom suffix for the fine-tuned model name
        hyperparameters: {
            n_epochs: 1
        }
    });

    console.log(fineTuneJob);
})();

curl -X POST --header 'Content-Type: application/json' \
 --header 'x-portkey-api-key: <portkey_api_key>' \
 --header 'x-portkey-virtual-key: <virtual_key>' \
 --data \
 $'{"model": "<base_model>", "suffix": "<finetune_name>", "training_file": "<file_id>", "validation_file": "<file_id>", "method": {"type": "supervised", "supervised": {"hyperparameters": {"n_epochs": 1}}}}\n' \
'https://api.portkey.ai/v1/fine_tuning/jobs'

List fine-tuning jobs

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# List all fine-tuning jobs
jobs = portkey.fine_tuning.jobs.list(
    limit=10  # Optional: Number of jobs to retrieve (default: 20)
)

print(jobs)

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# List all fine-tuning jobs
jobs = portkey.fine_tuning.jobs.list(
    limit=10  # Optional: Number of jobs to retrieve (default: 20)
)

print(jobs)

import { Portkey } from "portkey-ai";

// Initialize the Portkey client
const portkey = Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

(async () => {
    // List all fine-tuning jobs
    const jobs = await portkey.fineTuning.jobs.list({
        limit: 10  // Optional: Number of jobs to retrieve (default: 20)
    });

    console.log(jobs);
})();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        virtual_key="VIRTUAL_KEY",
        api_key="PORTKEY_API_KEY"
    )
)

# List all fine-tuning jobs
jobs = openai.fine_tuning.jobs.list(
    limit=10  # Optional: Number of jobs to retrieve (default: 20)
)

print(jobs)

import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai';

const openai = new OpenAI({
    apiKey: 'OPENAI_API_KEY',
    baseURL: PORTKEY_GATEWAY_URL,
    defaultHeaders: createHeaders({
        virtualKey: "VIRTUAL_KEY",
        apiKey: "PORTKEY_API_KEY"
    })
});

(async () => {
    // List all fine-tuning jobs
    const jobs = await openai.fineTuning.jobs.list({
        limit: 10  // Optional: Number of jobs to retrieve (default: 20)
    });

    console.log(jobs);
})();

curl -X GET --header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-virtual-key: <virtual_key>' \
'https://api.portkey.ai/v1/fine_tuning/jobs'

Get a fine-tuning job

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Retrieve a specific fine-tuning job
job = portkey.fine_tuning.jobs.retrieve(
    "job_id"  # The ID of the fine-tuning job to retrieve
)

print(job)

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Retrieve a specific fine-tuning job
job = portkey.fine_tuning.jobs.retrieve(
    "job_id"  # The ID of the fine-tuning job to retrieve
)

print(job)

import { Portkey } from "portkey-ai";

// Initialize the Portkey client
const portkey = Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

(async () => {
    // Retrieve a specific fine-tuning job
    const job = await portkey.fineTuning.jobs.retrieve(
        "job_id"  // The ID of the fine-tuning job to retrieve
    );

    console.log(job);
})();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        virtual_key="VIRTUAL_KEY",
        api_key="PORTKEY_API_KEY"
    )
)

# Retrieve a specific fine-tuning job
job = openai.fine_tuning.jobs.retrieve(
    fine_tuning_job_id="job_id"  # The ID of the fine-tuning job to retrieve
)

print(job)

import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai';

const openai = new OpenAI({
    apiKey: 'OPENAI_API_KEY',
    baseURL: PORTKEY_GATEWAY_URL,
    defaultHeaders: createHeaders({
        virtualKey: "VIRTUAL_KEY",
        apiKey: "PORTKEY_API_KEY"
    })
});

(async () => {
    // Retrieve a specific fine-tuning job
    const job = await openai.fineTuning.jobs.retrieve(
        "job_id"  // The ID of the fine-tuning job to retrieve
    );

    console.log(job);
})();

curl -X GET --header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-virtual-key: <virtual_key>' \
'https://api.portkey.ai/v1/fine_tuning/jobs/<job_id>'

Cancel a fine-tuning job

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Cancel a fine-tuning job
cancelled_job = portkey.fine_tuning.jobs.cancel(
    "job_id"  # The ID of the fine-tuning job to cancel
)

print(cancelled_job)

from portkey_ai import Portkey

# Initialize the Portkey client
portkey = Portkey(
    api_key="PORTKEY_API_KEY", # Replace with your Portkey API key
    virtual_key="VIRTUAL_KEY" # Add your provider's virtual key
)

# Cancel a fine-tuning job
cancelled_job = portkey.fine_tuning.jobs.cancel(
    "job_id"  # The ID of the fine-tuning job to cancel
)

print(cancelled_job)

import { Portkey } from "portkey-ai";

// Initialize the Portkey client
const portkey = Portkey({
    apiKey: "PORTKEY_API_KEY",  // Replace with your Portkey API key
    virtualKey: "VIRTUAL_KEY"   // Add your provider's virtual key
});

(async () => {
    // Cancel a fine-tuning job
    const cancelledJob = await portkey.fineTuning.jobs.cancel(
        "job_id"  // The ID of the fine-tuning job to cancel
    );

    console.log(cancelledJob);
})();

from openai import OpenAI
from portkey_ai import PORTKEY_GATEWAY_URL, createHeaders

openai = OpenAI(
    api_key='OPENAI_API_KEY',
    base_url=PORTKEY_GATEWAY_URL,
    default_headers=createHeaders(
        virtual_key="VIRTUAL_KEY",
        api_key="PORTKEY_API_KEY"
    )
)

# Cancel a fine-tuning job
cancelled_job = openai.fine_tuning.jobs.cancel(
    "job_id"  # The ID of the fine-tuning job to cancel
)

print(cancelled_job)

import OpenAI from 'openai';
import { PORTKEY_GATEWAY_URL, createHeaders } from 'portkey-ai';

const openai = new OpenAI({
    apiKey: 'OPENAI_API_KEY',
    baseURL: PORTKEY_GATEWAY_URL,
    defaultHeaders: createHeaders({
        virtualKey: "VIRTUAL_KEY",
        apiKey: "PORTKEY_API_KEY"
    })
});

(async () => {
    // Cancel a fine-tuning job
    const cancelledJob = await openai.fineTuning.jobs.cancel(
        "job_id"  // The ID of the fine-tuning job to cancel
    );

    console.log(cancelledJob);
})();

curl -X POST --header 'x-portkey-api-key: <portkey_api_key>' \
--header 'x-portkey-virtual-key: <virtual_key>' \
'https://api.portkey.ai/v1/fine_tuning/jobs/<job_id>/cancel'

Refer to OpenAI’s fine-tuning documentation for more information on the parameters and options available.

Ecosystem

LLMs

Vector Databases

Agents

Libraries

Upload a file

Create a fine-tuning job

List fine-tuning jobs

Get a fine-tuning job

Cancel a fine-tuning job

Ecosystem

LLMs

Vector Databases

Agents

Libraries

​Upload a file

​Create a fine-tuning job

​List fine-tuning jobs

​Get a fine-tuning job

​Cancel a fine-tuning job

Upload a file

Create a fine-tuning job

List fine-tuning jobs

Get a fine-tuning job

Cancel a fine-tuning job