cog-safe-push

Safely push a Cog model version by making sure it works and is backwards-compatible with previous versions.

Prerequisites

1. Set the ANTHROPIC_API_KEY and REPLICATE_API_TOKEN environment variables.
2. Install Cog and cog login
3. If you're running this from a cloned source, pip install . in the cog-safe-push directory.

Installation

This package is not on PyPI yet, but you can install it directly from GitHub using pip:

pip install git+https://github.com/replicate/cog-safe-push.git

Usage

To safely push a model to Replicate, run this inside your Cog directory:

$ cog-safe-push --test-hardware=<hardware> <username>/<model-name>

This will:

1. Lint the predict file with ruff
2. Create a private test model on Replicate, named <username>/<model-name>-test running <hardware>
3. Push the local Cog model to the test model on Replicate
4. Lint the model schema (making sure all inputs have descriptions, etc.)
5. If there is an existing version on the upstream <username>/<model-name> model, it will
   1. Make sure that the schema in the test version is backwards compatible with the existing upstream version
   2. Run predictions against both upstream and test versions and make sure the same inputs produce the same (or equivalent) outputs
6. Fuzz the test model for five minutes by throwing a bunch of different inputs at it and make sure it doesn't throw any errors

Both the creation of model inputs and comparison of model outputs is handled by Claude.

Full help text

usage: cog-safe-push [-h] [--config CONFIG] [--help-config]
                     [--test-model TEST_MODEL] [--no-push]
                     [--test-hardware TEST_HARDWARE] [--no-compare-outputs]
                     [--predict-timeout PREDICT_TIMEOUT] [--test-case TEST_CASES]
                     [--fuzz-fixed-inputs FUZZ_FIXED_INPUTS]
                     [--fuzz-disabled-inputs FUZZ_DISABLED_INPUTS]
                     [--fuzz-iterations FUZZ_ITERATIONS] [--parallel PARALLEL]
                     [-v]
                     [model]

Safely push a Cog model, with tests

positional arguments:
  model                 Model in the format <owner>/<model-name>

options:
  -h, --help            show this help message and exit
  --config CONFIG       Path to the YAML config file. If --config is not passed,
                        ./cog-safe-push.yaml will be used, if it exists. Any
                        arguments you pass in will override fields on the predict
                        configuration stanza.
  --help-config         Print a default cog-safe-push.yaml config to stdout.
  --test-model TEST_MODEL
                        Replicate model to test on, in the format
                        <username>/<model-name>. If omitted, <model>-test will be
                        used. The test model is created automatically if it
                        doesn't exist already
  --no-push             Only test the model, don't push it to <model>
  --test-hardware TEST_HARDWARE
                        Hardware to run the test model on. Only used when
                        creating the test model, if it doesn't already exist.
  --no-compare-outputs  Don't make predictions to compare that prediction outputs
                        match the current version
  --predict-timeout PREDICT_TIMEOUT
                        Timeout (in seconds) for predictions. Default: 300
  --test-case TEST_CASES
                        Inputs and expected output that will be used for testing,
                        you can provide multiple --test-case options for multiple
                        test cases. The first test case will be used when
                        comparing outputs to the current version. Each --test-
                        case is semicolon-separated key-value pairs in the format
                        '<key1>=<value1>;<key2=value2>[<output-checker>]'.
                        <output-checker> can either be '==<exact-string-or-url>'
                        or '~=<ai-prompt>'. If you use '==<exact-string-or-url>'
                        then the output of the model must match exactly the
                        string or url you specify. If you use '~=<ai-prompt>'
                        then the AI will verify your output based on <ai-prompt>.
                        If you omit <output-checker>, it will just verify that
                        the prediction doesn't throw an error.
  --fuzz-fixed-inputs FUZZ_FIXED_INPUTS
                        Inputs that should have fixed values during fuzzing. All
                        other non-disabled input values will be generated by AI.
                        If no test cases are specified, these will also be used
                        when comparing outputs to the current version. Semicolon-
                        separated key-value pairs in the format
                        '<key1>=<value1>;<key2=value2>' (etc.)
  --fuzz-disabled-inputs FUZZ_DISABLED_INPUTS
                        Don't pass values for these inputs during fuzzing.
                        Semicolon-separated keys in the format '<key1>;<key2>'
                        (etc.). If no test cases are specified, these will also
                        be disabled when comparing outputs to the current
                        version.
  --fuzz-iterations FUZZ_ITERATIONS
                        Maximum number of iterations to run fuzzing.
  --parallel PARALLEL   Number of parallel prediction threads.
  -v, --verbose         Increase verbosity level (max 3)```

### Using a configuration file

You can use a configuration file instead of passing all arguments on the command line. If you create a file called `cog-safe-push.yaml` in your Cog directory, it will be used. Any command line arguments you pass will override the values in the config file.

```yaml
# cog-safe-push --help-config
model: <model>
parallel: 4
predict:
  compare_outputs: true
  fuzz:
    disabled_inputs: []
    iterations: 10
    fixed_inputs: {}
  predict_timeout: 300
  test_cases:
  - exact_string: <exact string match>
    inputs:
      <input1>: <value1>
  - inputs:
      <input2>: <value2>
    match_url: <match output image against url>
  - inputs:
      <input3>: <value3>
    match_prompt: <match output using AI prompt, e.g. 'an image of a cat'>
test_hardware: <hardware, e.g. cpu>
test_model: <test model, or empty to append '-test' to model>
train:
  destination: <generated prediction model, e.g. andreasjansson/test-predict. leave
    blank to append '-dest' to the test model>
  destination_hardware: <hardware for the created prediction model, e.g. cpu>
  fuzz:
    disabled_inputs: []
    iterations: 10
    fixed_inputs: {}
  test_cases:
  - exact_string: <exact string match>
    inputs:
      <input1>: <value1>
  - inputs:
      <input2>: <value2>
    match_url: <match output image against url>
  - inputs:
      <input3>: <value3>
    match_prompt: <match output using AI prompt, e.g. 'an image of a cat'>
  train_timeout: 300

# values between < and > should be edited

Nota bene

• This is alpha software. If you find a bug, please open an issue!