Dblade is a command line program for linux. The default setup is for Azure OpenAI APi batch processing, however this code could be used for any JSON HTTPS/REST type API that takes POST requests with a JSON body.
The secrets for the API to send data to are in a .env file. This file is encrypted via forge utility. See https://github.com/jpegleg/dwarven-toolbox for more information.
Once the .env file is created and encrypted with forge, then a user can execute dblade to decrypt, load, and re-encrypt the .env and process files as declared in evaluate.txt.
Example evaluate.txt:
[process]
workspace/drafts/inputs_1.txt
workspace/drafts/inputs_2.txt
tmp/enforcement.txt
data_task_alpha.txt
more_files.md
Each file after the process stanza will be read. The logic on reading files for dblade is to read 20 lines, then keep reading after 20 until an empty line is encountered or we run out of data.
The amount read is a "chunk" which is sent as a prompt to Azure OpenAI JSON API.
Each run of dblade gets a transaction ID which is a UUIDv4. This transaction id is logged to STDOUT and used to name the output files from the Azure OpenAI API.
When dblade is run, we expect a user to supply the decryption password for .env interactively, then supply a password to encrypt .env with. This can be the same password or a new password.
Here is an example of running dblade:
$ dblade
[2023-08-11 01:09:44.590076121 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Running dblade, reading password for .env decryption...
Password:
[2023-08-11 01:09:46.466283283 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Env decrypted for usage: .env
Password:
[2023-08-11 01:09:48.355480695 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Env loaded, reading password for re-encrypting .env...
[2023-08-11 01:09:48.355480695 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Env encrypted for storage: .env
[2023-08-11 01:09:48.355617159 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Opening evaluate.txt for files to process...
[2023-08-11 01:09:48.355638867 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - File to process: 1.txt
[2023-08-11 01:09:48.355645160 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - File to process: 2.txt
[2023-08-11 01:09:48.355710758 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Calling AI API for chunk: {"prompt":"List types of squirrels in north america.","max_tokens":500} ...
[2023-08-11 01:10:02.617199647 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Saved output from AI API to "review__1.txt_34e78380-9170-486f-a293-4833d411c0de"
[2023-08-11 01:10:02.617467124 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Calling AI API for chunk: {"prompt":"List types of bats in north america.","max_tokens":500} ...
[2023-08-11 01:10:18.288379001 UTC INFO] 34e78380-9170-486f-a293-4833d411c0de - Saved output from AI API to "review__2.txt_34e78380-9170-486f-a293-4833d411c0de"
$
The value for max_tokens is hard-coded to 500 by default. This can be adjusted to also be read from .env or hard-coded to another value.
While the dblade program is designed to use Azure OpenAI, any API that takes a JSON POST can work, just adjust the code to match the need.
The interactive password prompt can easily be replaced with reading the password or key from another mechanism if a version of dblade needs to run in a fully automated way, etc.