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Add more modules
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‎openai-engine.el

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;;; openai-engine.el --- Control moderations with OpenAI API -*- lexical-binding: t; -*-
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;;; openai-engine.el --- Control engines with OpenAI API -*- lexical-binding: t; -*-
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;; Copyright (C) 2023 Shen, Jen-Chieh
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;;
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;; [DEPRECATED]
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;;
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;; Given a input text, outputs if the model classifies it as violating OpenAI's
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;; content policy.
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;; These endpoints describe and provide access to the various engines available
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;; in the API.
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;;
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;; See https://platform.openai.com/docs/api-reference/engines
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;;
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The argument ENGINE-ID is the engine to use for this request.
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The argument CALLBACK is execuated after request is made."
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(openai-request "https://api.openai.com/v1/engines/"
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(openai-request (format "https://api.openai.com/v1/engines/%s" engine-id)
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:type "GET"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:data (json-encode
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`(("engine_id" . ,engine-id)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)

‎openai-fine-tune.el

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;;; openai-fine-tune.el --- Control fine-tunes with OpenAI API -*- lexical-binding: t; -*-
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;; Copyright (C) 2023 Shen, Jen-Chieh
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;; This file is not part of GNU Emacs.
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;; This program is free software: you can redistribute it and/or modify
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;; it under the terms of the GNU General Public License as published by
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;; the Free Software Foundation, either version 3 of the License, or
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;; (at your option) any later version.
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;; This program is distributed in the hope that it will be useful,
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;; but WITHOUT ANY WARRANTY; without even the implied warranty of
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;; MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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;; GNU General Public License for more details.
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;; You should have received a copy of the GNU General Public License
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;; along with this program. If not, see <https://www.gnu.org/licenses/>.
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;;; Commentary:
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;;
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;; Manage fine-tuning jobs to tailor a model to your specific training data.
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;;
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;; See https://platform.openai.com/docs/api-reference/fine-tunes
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;;
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;;; Code:
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(require 'openai)
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(defcustom openai-fine-tune-model "curie"
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"The name of the base model to fine-tune.
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You can select one of \"ada\", \"babbage\", \"curie\", \"davinci\", or a
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fine-tuned model created after 2022-04-21. To learn more about these models,
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see the Models documentation."
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:type 'string
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:group 'openai)
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(defcustom openai-fine-tune-validation-file ""
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"The ID of an uploaded file that contains validation data."
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:type 'string
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:group 'openai)
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(defcustom openai-fine-tune-n-epochs 4
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"The number of epochs to train the model for.
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An epoch refers to one full cycle through the training dataset."
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:type 'integer
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:group 'openai)
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(defcustom openai-fine-tune-batch-size nil
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"The batch size to use for training.
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The batch size is the number of training examples used to train a single forward
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and backward pass.
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By default, the batch size will be dynamically configured to be ~0.2% of the
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number of examples in the training set, capped at 256 - in general, we've found
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that larger batch sizes tend to work better for larger datasets."
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:type 'integer
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:group 'openai)
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(defcustom openai-fine-tune-learning-rate-multiplier nil
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"The learning rate multiplier to use for training.
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The fine-tuning learning rate is the original learning rate used for pretraining
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multiplied by this value.
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By default, the learning rate multiplier is the 0.05, 0.1, or 0.2 depending on
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final `batch_size' (larger learning rates tend to perform better with larger
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batch sizes). We recommend experimenting with values in the range 0.02 to 0.2 to
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see what produces the best results."
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:type 'integer
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:group 'openai)
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(defcustom openai-fine-tune-prompt-loss-weight 0.01
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"The weight to use for loss on the prompt tokens. This controls how much the
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model tries to learn to generate the prompt (as compared to the completion which
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always has a weight of 1.0), and can add a stabilizing effect to training when
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completions are short.
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If prompts are extremely long (relative to completions), it may make sense to
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reduce this weight so as to avoid over-prioritizing learning the prompt."
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:type 'number
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:group 'openai)
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(defcustom openai-fine-tune-compute-classification-metrics 0.01
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"If set, we calculate classification-specific metrics such as accuracy and F-1
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score using the validation set at the end of every epoch.
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In order to compute classification metrics, you must provide a `validation_file'.
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Additionally, you must specify `classification_n_classes' for multiclass
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classification or `classification_positive_class' for binary classification."
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:type 'boolean
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:group 'openai)
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(defcustom openai-fine-tune-classification-n-classes nil
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"The number of classes in a classification task.
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This parameter is required for multiclass classification."
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:type 'integer
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:group 'openai)
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(defcustom openai-fine-tune-classification-positive-class nil
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"The positive class in binary classification.
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This parameter is needed to generate precision, recall, and F1 metrics when
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doing binary classification."
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:type 'string
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:group 'openai)
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(defcustom openai-fine-tune-classification-betas nil
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"If this is provided, we calculate F-beta scores at the specified beta values.
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The F-beta score is a generalization of F-1 score. This is only used for binary
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classification.
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With a beta of 1 (i.e. the F-1 score), precision and recall are given the same
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weight. A larger beta score puts more weight on recall and less on precision.
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A smaller beta score puts more weight on precision and less on recall."
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:type 'list
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:group 'openai)
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(defcustom openai-fine-tune-suffix nil
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"A string of up to 40 characters that will be added to your fine-tuned model
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name.
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For example, a suffix of \"custom-model-name\" would produce a model name like
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`ada:ft-your-org:custom-model-name-2022-02-15-04-21-04'."
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:type 'string
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:group 'openai)
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;;
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;;; API
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(defun openai-fine-tune-create (training-file callback)
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"Creates a job that fine-tunes a specified model from a given dataset.
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Response includes details of the enqueued job including job status and the name
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of the fine-tuned models once complete.
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The argument TRAINING-FILE is the ID of an uploaded file that contains training
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data.
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The argument CALLBACK is execuated after request is made."
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(openai-request "https://api.openai.com/v1/fine-tunes"
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:type "POST"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:data (json-encode
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`(("model" . ,openai-fine-tune-model)
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("training_file" . ,training-file)
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("validation_file" . ,openai-fine-tune-validation-file)
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("n_epochs" . ,openai-fine-tune-n-epochs)
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("batch_size" . ,openai-fine-tune-batch-size)
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("learning_rate_multiplier" . ,openai-fine-tune-learning-rate-multiplier)
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("prompt_loss_weight" . ,openai-fine-tune-prompt-loss-weight)
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("compute_classification_metrics" . ,openai-fine-tune-compute-classification-metrics)
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("classification_n_classes" . ,openai-fine-tune-classification-n-classes)
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("classification_positive_class" . ,openai-fine-tune-classification-positive-class)
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("classification_betas" . ,openai-fine-tune-classification-betas)
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("suffix" . ,openai-fine-tune-suffix)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)
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(funcall callback data)))))
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(defun openai-fine-tune-list (callback)
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"List your organization's fine-tuning jobs.
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The argument CALLBACK is execuated after request is made."
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(openai-request "https://api.openai.com/v1/fine-tunes"
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:type "GET"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)
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(funcall callback data)))))
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(defun openai-fine-tune-retrieve (fine-tune-id callback)
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"Gets info about the fine-tune job.
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The FINE-TUNE-ID of the fine-tune job.
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The argument CALLBACK is execuated after request is made."
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(openai-request (format "https://api.openai.com/v1/fine-tunes/%s" fine-tune-id)
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:type "GET"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)
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(funcall callback data)))))
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(defun openai-fine-tune-cancel (fine-tune-id callback)
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"Immediately cancel a fine-tune job.
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The FINE-TUNE-ID of the fine-tune job to cancel.
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The argument CALLBACK is execuated after request is made."
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(openai-request (format "https://api.openai.com/v1/fine-tunes/%s/cancel" fine-tune-id)
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:type "POST"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)
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(funcall callback data)))))
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(defun openai-fine-tune-list-events (fine-tune-id callback)
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"Get fine-grained status updates for a fine-tune job.
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The FINE-TUNE-ID of the fine-tune job to get events for.
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The argument CALLBACK is execuated after request is made."
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(openai-request (format "https://api.openai.com/v1/fine-tunes/%s/events" fine-tune-id)
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:type "GET"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)
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(funcall callback data)))))
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(defun openai-fine-tune-list-events (model callback)
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"Delete a fine-tuned model. You must have the Owner role in your organization.
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The MODEL to delete.
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The argument CALLBACK is execuated after request is made."
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(openai-request (format "https://api.openai.com/v1/models/%s" model)
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:type "DELETE"
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:headers `(("Content-Type" . "application/json")
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("Authorization" . ,(concat "Bearer " openai-key)))
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:parser 'json-read
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:success (cl-function
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(lambda (&key data &allow-other-keys)
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(funcall callback data)))))
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;;
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;;; Application
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(defvar openai-fine-tune-entries nil
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"Async files entries.")
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(tblui-define
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openai-fine-tune
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(lambda () openai-fine-tune-entries)
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[("ID" 15 nil)
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("Object" 30 nil)
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("Model" 6 nil)
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("Created at" 10 nil)
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("fine_tuned_model" 10 nil)
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("hyperparams" 40 nil)
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("organization_id" 40 nil)
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("status" 10 nil)
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("validation_files" 10 nil)
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("training_files" 10 nil)
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("Updated at" 10 nil)]
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nil)
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;;;###autoload
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(defun openai-list-fine-tunes ()
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"List fine-tuning jobs."
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(interactive)
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(setq openai-fine-tune-entries nil) ; reset
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(openai-file-list (lambda (data)
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(let ((id 0))
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(let-alist data
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(mapc (lambda (fine-tune)
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(let-alist fine-tune
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(push (list (number-to-string id)
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(vector .id
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.object
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.model
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.created_at
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.fine_tuned_model
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.hyperparams
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.organization_id
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.result_files
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.status
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.validation_files
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.training_files
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.updated_at))
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openai-fine-tune-entries))
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(cl-incf id))
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.data)))
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(openai-fine-tune-goto-ui))))
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(provide 'openai-fine-tune)
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;;; openai-fine-tune.el ends here

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