diff --git a/.github/workflows/onpush.yml b/.github/workflows/onpush.yml index 98c41c5..f8ac0ad 100644 --- a/.github/workflows/onpush.yml +++ b/.github/workflows/onpush.yml @@ -27,10 +27,10 @@ jobs: poetry install --all-extras - name: Lint with ruff run: | - poetry run ruff giza_actions + poetry run ruff giza - name: Pre-commit check run: | poetry run pre-commit run --all-files - name: Testing run: | - poetry run pytest --cov=giza_actions --cov-report term-missing + poetry run pytest --cov=giza.agents --cov-report term-missing diff --git a/.github/workflows/onrelease.yml b/.github/workflows/onrelease.yml index c6c5401..363c980 100644 --- a/.github/workflows/onrelease.yml +++ b/.github/workflows/onrelease.yml @@ -30,7 +30,7 @@ jobs: poetry install - name: Lint with ruff run: | - poetry run ruff giza_actions + poetry run ruff giza - name: Build dist run: poetry build - name: Publish a Python distribution to PyPI diff --git a/README.md b/README.md index 89bdd1f..ed260c9 100644 --- a/README.md +++ b/README.md @@ -7,7 +7,7 @@ The extensible nature of Giza Agents allows developers to enshrine custom strate ## Where to start? -Check out our extensive [documentation]([https://actions.gizatech.xyz/welcome/giza-actions-sdk](https://docs.gizatech.xyz/products/ai-agents)) to understand the concepts and follow how-to-guides. +Check out our extensive [documentation]([docs.gizatech.xyz/products/ai-agents) to understand the concepts and follow how-to-guides. ## Installation @@ -23,10 +23,10 @@ $ source .env/bin/activate $ .env/Scripts/activate ``` -Now you’re ready to install ⚡Actions with the following command: +Now you’re ready to install ⚡Agents with the following command: ```bash -$ pip install giza-actions +$ pip install giza-agents ``` ## Setup @@ -49,12 +49,6 @@ Optional: you can create an API Key for your user in order to not regenerate you $ giza users create-api-key ``` -To create Actions Runs you will need a Giza Workspace, create it by executing the following command in your terminal: - -```bash -$ giza workspaces create -``` - ## Usage ### Creating Agents @@ -112,7 +106,7 @@ $ export _PASSPHRASE= ``` ```python -from giza_actions.agent import Agent +from giza.agents import Agent # Here we check for the passphrase in the environment agent = Agent.from_id(id=1, contracts={"my_contract": "0x1234567890"}) @@ -131,7 +125,7 @@ with agent.execute() as contracts: ## Examples -Examples of how to use the Actions SDK can be found in the `examples` directory. Each example includes a README or a Notebook with detailed instructions on how to run the example. +Examples of how to use the Agents can be found in the `examples` directory. Each example includes a README or a Notebook with detailed instructions on how to run the example. ## Contributing diff --git a/examples/agents/action_agent.py b/examples/agents/action_agent.py index 764e286..5fc5644 100644 --- a/examples/agents/action_agent.py +++ b/examples/agents/action_agent.py @@ -1,14 +1,11 @@ +import logging import pprint import numpy as np from PIL import Image -from giza_actions.action import action -from giza_actions.agent import GizaAgent -from giza_actions.task import task +from giza.agents import GizaAgent -from prefect import get_run_logger # Process the image -@task def process_image(img): img = np.resize(img, (28,28)) img = img.reshape(1,1,28,28) @@ -19,17 +16,15 @@ def process_image(img): return tensor # Get the image -@task def get_image(path): with Image.open(path) as img: img = img.convert('L') img = np.array(img) return img -# Create the Action -@action(log_prints=True) +# Create the execution function def transmission(): - logger = get_run_logger() + logger = logging.getLogger(__name__) img_path = 'seven.png' img = get_image(img_path) img = process_image(img) diff --git a/examples/agents/mnist_agent_tutorial.ipynb b/examples/agents/mnist_agent_tutorial.ipynb index ee29761..332bb1d 100644 --- a/examples/agents/mnist_agent_tutorial.ipynb +++ b/examples/agents/mnist_agent_tutorial.ipynb @@ -12,15 +12,15 @@ "\n", "In this notebook, we will create an AI Agent to mint an MNIST NFT. Using an existing MNIST endpoint, we will perform a prediction on the MNIST dataset and mint an NFT based on the prediction.\n", "\n", - "This tutorial can be thought of as the continuation of the previous tutorial [Build a Verifiable Neural Network with Giza Actions](https://actions.gizatech.xyz/tutorials/build-a-verifiable-neural-network-with-giza-actions) where we created a verifiable MNIST model ([notebook](https://github.com/gizatechxyz/actions-sdk/blob/main/examples/verifiable_mnist/verifiable_mnist.ipynb)).\n", + "This tutorial can be thought of as the continuation of the previous tutorial [Verifiable MNIST Neural Network](https://docs.gizatech.xyz/tutorials/zkml/verifiable-mnist-neural-network) where we created a verifiable MNIST model ([notebook](https://github.com/gizatechxyz/giza-agents/blob/main/examples/verifiable_mnist/verifiable_mnist.ipynb)).\n", "\n", "## Before you begin\n", "\n", "1. Python 3.11 or later must be installed on your machine\n", "2. Giza CLI must be installed on your machine. You can install it by running `pip install giza-cli`\n", - "3. Actions-SDK should be installed with the extra `agents`. You can install it by running `pip install giza-actions[agents]`\n", + "3. giza-agents should be installed. You can install it by running `pip install giza-agents`\n", "4. You must have an active Giza account. If you don't have one, you can create one [here](https://cli.gizatech.xyz/examples/basic).\n", - "5. You must have an MNIST model deployed on Giza. You can follow the tutorial [Build a Verifiable Neural Network with Giza Actions](https://actions.gizatech.xyz/tutorials/build-a-verifiable-neural-network-with-giza-actions) to deploy an MNIST model on Giza.\n", + "5. You must have an MNIST model deployed on Giza. You can follow the tutorial [Build a Verifiable Neural Network](https://docs.gizatech.xyz/tutorials/zkml/verifiable-mnist-neural-network) to deploy an MNIST model on Giza.\n", "6. During the tutorial, you will need to interact with the Giza CLI, and Ape's framework, and provide multiple inputs, like `model-id`, `version-id`, `account name`, etc.\n", "7. You must be logged in to the Giza CLI or have an API KEY.\n", "\n", @@ -29,10 +29,10 @@ "Let's start by installing the required libraries.\n", "\n", "```bash\n", - "pip install giza-actions[agents]\n", + "pip install giza-agents\n", "```\n", "\n", - "This will install the `giza-actions` library along with the `agents` extra, which contains the necessary tools to create an AI Agent.\n", + "This will install the `giza-agents` library, which contains the necessary tools to create an AI Agent.\n", "\n", "## Creating an account\n", "\n", @@ -108,7 +108,7 @@ "\n", "## How to use the AI Agent\n", "\n", - "Now that the agent is created we can start using it through the `giza-actions` library. As we will be using the agent to mint an MNIST NFT, we will need to provide the MNIST image to the agent and preprocess it before sending it to the model." + "Now that the agent is created we can start using it through the `giza-agents` library. As we will be using the agent to mint an MNIST NFT, we will need to provide the MNIST image to the agent and preprocess it before sending it to the model." ] }, { @@ -121,9 +121,7 @@ "import numpy as np\n", "from PIL import Image\n", "\n", - "from giza_actions.agent import GizaAgent, AgentResult\n", - "from giza_actions.action import action\n", - "from giza_actions.task import task\n", + "from giza.agents import GizaAgent, AgentResult\n", "\n", "# Make sure to fill these in\n", "MODEL_ID = ...\n", @@ -146,7 +144,7 @@ "* Access the prediction result\n", "* Mint an NFT based on the prediction result\n", "\n", - "To load and preprocess the image, we can use the function that we already created in the previous tutorial [Build a Verifiable Neural Network with Giza Actions](https://actions.gizatech.xyz/tutorials/build-a-verifiable-neural-network-with-giza-actions)." + "To load and preprocess the image, we can use the function that we already created in the previous tutorial [Build a Verifiable Neural Network](https://docs.gizatech.xyz/tutorials/zkml/verifiable-mnist-neural-network)." ] }, { @@ -156,7 +154,6 @@ "outputs": [], "source": [ "# This function is for the previous MNIST tutorial\n", - "@task(name=\"Preprocess an image for the MNIST model.\")\n", "def preprocess_image(image_path: str):\n", " \"\"\"\n", " Preprocess an image for the MNIST model.\n", @@ -197,7 +194,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=\"Create a Giza agent for the MNIST model\")\n", "def create_agent(model_id: int, version_id: int, chain: str, contract: str):\n", " \"\"\"\n", " Create a Giza agent for the MNIST model with MNIST \n", @@ -225,7 +221,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=\"Predict the digit in an image.\")\n", "def predict(agent: GizaAgent, image: np.ndarray):\n", " \"\"\"\n", " Predict the digit in an image.\n", @@ -259,7 +254,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=\"Get the digit from the prediction.\")\n", "def get_digit(prediction: AgentResult):\n", " \"\"\"\n", " Get the digit from the prediction.\n", @@ -300,7 +294,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=\"Execute the MNIST to mint a new NFT.\")\n", "def execute_contract(agent: GizaAgent, digit: int):\n", " \"\"\"\n", " Execute the MNIST contract with the predicted digit to mint a new NFT.\n", @@ -330,7 +323,6 @@ "metadata": {}, "outputs": [], "source": [ - "@action(name=\"Mint an NFT with a prediction.\", log_prints=True)\n", "def mint_nft_with_prediction():\n", " # Preprocess the image\n", " image = preprocess_image(\"seven.png\")\n", diff --git a/examples/agents/read_contracts.py b/examples/agents/read_contracts.py index 4ca61fd..335a4fe 100644 --- a/examples/agents/read_contracts.py +++ b/examples/agents/read_contracts.py @@ -17,7 +17,7 @@ In this example, we call the `name` method of the contracts, which is a method that returns the name of the contract, and then we print the result. But we could execute any function of a contract in the same way. """ -from giza_actions.agent import GizaAgent +from giza.agents import GizaAgent MODEL_ID = ... VERSION_ID = ... diff --git a/examples/agents/using_arbitrum.ipynb b/examples/agents/using_arbitrum.ipynb index 269f84d..c1e5c08 100644 --- a/examples/agents/using_arbitrum.ipynb +++ b/examples/agents/using_arbitrum.ipynb @@ -16,10 +16,10 @@ "\n", "1. Python 3.11 or later must be installed on your machine\n", "2. Giza CLI must be installed on your machine. You can install it by running `pip install giza-cli`\n", - "3. Actions-SDK should be installed with the extra `agents`. You can install it by running `pip install giza-actions[agents]`\n", + "3. giza-agents should be installed. You can install it by running `pip install giza-agents`\n", "4. You must have an active Giza account. If you don't have one, you can create one [here](https://cli.gizatech.xyz/examples/basic).\n", - "5. You must have a model deployed on Giza. You can follow the tutorial [Build a Verifiable Neural Network with Giza Actions](https://actions.gizatech.xyz/tutorials/build-a-verifiable-neural-network-with-giza-actions) to deploy an MNIST model on Giza.\n", - "6. During the tutorial, you will need to interact with the Giza CLI, Ape's framework, and provide multiple inputs, like `model-id`, `version-id`, `account name`, etc.\n", + "5. You must have an MNIST model deployed on Giza. You can follow the tutorial [Build a Verifiable Neural Network](https://docs.gizatech.xyz/tutorials/zkml/verifiable-mnist-neural-network) to deploy an MNIST model on Giza.\n", + "6. During the tutorial, you will need to interact with the Giza CLI, and Ape's framework, and provide multiple inputs, like `model-id`, `version-id`, `account name`, etc.\n", "7. You must be logged in to the Giza CLI or have an API KEY.\n", "\n", "## Installing the required libraries\n", @@ -27,10 +27,10 @@ "Let's start by installing the required libraries.\n", "\n", "```bash\n", - "pip install giza-actions[agents]\n", + "pip install giza-agents\n", "```\n", "\n", - "This will install the `giza-actions` library along with the `agents` extra, which contains the necessary tools to create an AI Agent.\n", + "This will install the `giza-agents` library along with the `agents` extra, which contains the necessary tools to create an AI Agent.\n", "\n", "## Creating an account\n", "\n", @@ -174,13 +174,13 @@ "export _PASSPHRASE=your-passphrase\n", "```\n", "\n", - "If you are using it from a notebook, you will need to launch the notebook instance from an environment with the passphrase variable or set it in the code before importing `giza_actions`:\n", + "If you are using it from a notebook, you will need to launch the notebook instance from an environment with the passphrase variable or set it in the code before importing `giza.agents`:\n", "\n", "```python\n", "import os\n", "os.environ[\"_PASSPHRASE\"] = \"your-passphrase\"\n", "\n", - "from giza_actions.agent import GizaAgent\n", + "from giza.agents import GizaAgent\n", "...\n", "```\n", "\n", @@ -197,7 +197,7 @@ "os.environ[\"_PASSPHRASE\"] = ...\n", "\n", "\n", - "from giza_actions.agent import GizaAgent\n", + "from giza.agents import GizaAgent\n", "\n", "MODEL_ID = ...\n", "VERSION_ID = ...\n", diff --git a/examples/agents/using_polygon.ipynb b/examples/agents/using_polygon.ipynb index b14d873..931aca6 100644 --- a/examples/agents/using_polygon.ipynb +++ b/examples/agents/using_polygon.ipynb @@ -16,9 +16,9 @@ "\n", "1. Python 3.11 or later must be installed on your machine\n", "2. Giza CLI must be installed on your machine. You can install it by running `pip install giza-cli`\n", - "3. Actions-SDK should be installed. You can install it by running `pip install giza-actions`\n", + "3. giza-agents should be installed. You can install it by running `pip install giza-agents`\n", "4. You must have an active Giza account. If you don't have one, you can create one [here](https://cli.gizatech.xyz/examples/basic).\n", - "5. You must have a model deployed on Giza. You can follow the tutorial [Build a Verifiable Neural Network with Giza Actions](https://actions.gizatech.xyz/tutorials/build-a-verifiable-neural-network-with-giza-actions) to deploy an MNIST model on Giza.\n", + "5. You must have a model deployed on Giza. You can follow the tutorial [Build a Verifiable Neural Network](https://docs.gizatech.xyz/tutorials/zkml/verifiable-mnist-neural-network) to deploy an MNIST model on Giza.\n", "6. During the tutorial, you will need to interact with the Giza CLI, Ape's framework, and provide multiple inputs, like `model-id`, `version-id`, `account name`, etc.\n", "7. You must be logged in to the Giza CLI or have an API KEY.\n", "\n", @@ -27,10 +27,10 @@ "Let's start by installing the required libraries.\n", "\n", "```bash\n", - "pip install giza-actions\n", + "pip install giza-agents\n", "```\n", "\n", - "This will install the `giza-actions` library, which contains the necessary tools to create an AI Agent.\n", + "This will install the `giza-agents` library, which contains the necessary tools to create an AI Agent.\n", "\n", "## Creating an account\n", "\n", @@ -169,13 +169,13 @@ "export _PASSPHRASE=your-passphrase\n", "```\n", "\n", - "If you are using it from a notebook, you will need to launch the notebook instance from an environment with the passphrase variable or set it in the code before importing `giza_actions`:\n", + "If you are using it from a notebook, you will need to launch the notebook instance from an environment with the passphrase variable or set it in the code before importing `giza.agents`:\n", "\n", "```python\n", "import os\n", "os.environ[\"_PASSPHRASE\"] = \"your-passphrase\"\n", "\n", - "from giza_actions.agent import GizaAgent\n", + "from giza.agents import GizaAgent\n", "...\n", "```\n", "\n", @@ -192,7 +192,7 @@ "os.environ[\"_PASSPHRASE\"] = ...\n", "\n", "\n", - "from giza_actions.agent import GizaAgent\n", + "from giza.agents import GizaAgent\n", "\n", "MODEL_ID = ...\n", "VERSION_ID = ...\n", diff --git a/examples/ezkl/linear_regression/predict_action.py b/examples/ezkl/linear_regression/predict_action.py index 66a7817..ffd05a7 100644 --- a/examples/ezkl/linear_regression/predict_action.py +++ b/examples/ezkl/linear_regression/predict_action.py @@ -1,12 +1,10 @@ import time import requests -from giza import API_HOST -from giza.client import DeploymentsClient +from giza.cli import API_HOST +from giza.cli.client import DeploymentsClient -from giza_actions.action import Action, action -from giza_actions.model import GizaModel -from giza_actions.task import task +from giza.agents.model import GizaModel MODEL_ID = ... # The ID of the model VERSION = ... # The version of the model @@ -23,7 +21,6 @@ def get_deployment_id(): return client.list(MODEL_ID, VERSION).__root__[0].id -@task def predict(): """ Predict using the model and version for a linear regression model. @@ -39,7 +36,6 @@ def predict(): return result, request_id -@task def wait_for_proof(request_id): """ Wait for the proof associated with the request ID. For 240 seconds, it will attempt to retrieve the proof every 5 seconds. @@ -65,12 +61,9 @@ def wait_for_proof(request_id): time.sleep(5) -@action(log_prints=True) def inference(): result, request_id = predict() wait_for_proof(request_id) -if __name__ == "__main__": - action_deploy = Action(entrypoint=inference, name="ezkl-linear-regression") - action_deploy.serve(name="ezkl-linear-regression") +inference() diff --git a/examples/ezkl/linear_regression/train_linear_regression.py b/examples/ezkl/linear_regression/train_linear_regression.py index cef862f..d349394 100644 --- a/examples/ezkl/linear_regression/train_linear_regression.py +++ b/examples/ezkl/linear_regression/train_linear_regression.py @@ -5,11 +5,7 @@ from hummingbird.ml import convert from sklearn.linear_model import LinearRegression -from giza_actions.action import Action, action -from giza_actions.task import task - -@task def train(): X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]]) @@ -19,12 +15,10 @@ def train(): return reg -@task def convert_to_torch(linear_regression, sample): return convert(linear_regression, "torch", sample).model -@task def convert_to_onnx(model, sample): # Input to the model shape = sample.shape @@ -44,7 +38,6 @@ def convert_to_onnx(model, sample): ) -@task def create_input_file(sample: np.ndarray): with open("input.json", "w") as f: f.write( @@ -57,7 +50,6 @@ def create_input_file(sample: np.ndarray): ) -@action(log_prints=True) def model_to_onnx(): lr = train() sample = np.array([7, 2]) @@ -66,6 +58,4 @@ def model_to_onnx(): create_input_file(sample) -if __name__ == "__main__": - action_deploy = Action(entrypoint=model_to_onnx, name="linear-regression-to-onnx") - action_deploy.serve(name="linear-regression-to-onnx") +model_to_onnx() diff --git a/examples/imagenet/inference.py b/examples/imagenet/inference.py index 8c05334..a862b7f 100644 --- a/examples/imagenet/inference.py +++ b/examples/imagenet/inference.py @@ -3,45 +3,37 @@ import cv2 from PIL import Image -from giza_actions.action import Action, action -from giza_actions.model import GizaModel -from giza_actions.task import task +from giza.agents.model import GizaModel -@task def download_image(): image_url = 'https://s3.amazonaws.com/model-server/inputs/kitten.jpg' image_data = requests.get(image_url).content with open('kitten.jpg', 'wb') as handler: handler.write(image_data) -@task def download_labels(): labels_url = 'https://s3.amazonaws.com/onnx-model-zoo/synset.txt' labels_data = requests.get(labels_url).content with open('synset.txt', 'wb') as handler: handler.write(labels_data) -@task def download_model(): model_url = 'https://github.com/onnx/models/raw/main/vision/classification/resnet/model/resnet50-v1-12.onnx' model_data = requests.get(model_url).content with open('resnet50-v1-12.onnx', 'wb') as handler: handler.write(model_data) -@task def read_labels(): with open('synset.txt') as f: labels = [l.rstrip() for l in f] return labels -@task def get_image(path): with Image.open(path) as img: img = np.array(img.convert('RGB')) return img -@task def preprocess(img): img = img / 255. img = cv2.resize(img, (256, 256)) @@ -55,7 +47,6 @@ def preprocess(img): img = np.expand_dims(img, axis=0) return img -@task def predict(model, labels, img, verifiable: bool = False): ort_inputs = {model.session.get_inputs()[0].name: img} preds = model.predict(ort_inputs, verifiable=verifiable) @@ -63,7 +54,6 @@ def predict(model, labels, img, verifiable: bool = False): a = np.argsort(preds)[::-1] print('class=%s ; probability=%f' %(labels[a[0]],preds[a[0]])) -@action(log_prints=True) def execution(): model_path = 'resnet50-v1-12.onnx' img_path = 'kitten.jpg' @@ -78,6 +68,4 @@ def execution(): img = preprocess(img) predict(model, labels, img, verifiable=verifiable) -if __name__ == '__main__': - action_deploy = Action(entrypoint=execution, name="inference-local-action") - action_deploy.serve(name="imagenet-local-action") \ No newline at end of file +execution() diff --git a/examples/simple/example.py b/examples/simple/example.py deleted file mode 100644 index e3b703f..0000000 --- a/examples/simple/example.py +++ /dev/null @@ -1,22 +0,0 @@ -from giza_actions.action import Action, action -from giza_actions.model import GizaModel -from giza_actions.task import task - -@task -def preprocess(): - print(f"Preprocessing...") - - -@task -def transform(): - print(f"Transforming...") - - -@action(log_prints=True) -def inference(): - preprocess() - transform() - -if __name__ == '__main__': - action_deploy = Action(entrypoint=inference, name="inference-local-action") - action_deploy.serve(name="inference-local-action") diff --git a/examples/simple/example_cron.py b/examples/simple/example_cron.py deleted file mode 100644 index 68ad9ae..0000000 --- a/examples/simple/example_cron.py +++ /dev/null @@ -1,22 +0,0 @@ -from giza_actions.action import Action, action -from giza_actions.model import GizaModel -from giza_actions.task import task - -@task -def preprocess(): - print(f"Preprocessing...") - - -@task -def transform(): - print(f"Transforming...") - - -@action(log_prints=True) -def inference(): - preprocess() - transform() - -if __name__ == '__main__': - action_deploy = Action(entrypoint=inference, name="inference-local-action") - action_deploy.serve(name="inference-local-action", cron="* * * * *") diff --git a/examples/simple/example_interval.py b/examples/simple/example_interval.py deleted file mode 100644 index fd588c7..0000000 --- a/examples/simple/example_interval.py +++ /dev/null @@ -1,22 +0,0 @@ -from giza_actions.action import Action, action -from giza_actions.model import GizaModel -from giza_actions.task import task - -@task -def preprocess(): - print(f"Preprocessing...") - - -@task -def transform(): - print(f"Transforming...") - - -@action(log_prints=True) -def inference(): - preprocess() - transform() - -if __name__ == '__main__': - action_deploy = Action(entrypoint=inference, name="inference-local-action") - action_deploy.serve(name="inference-local-action", interval=10) diff --git a/examples/simple/example_parameters.py b/examples/simple/example_parameters.py deleted file mode 100644 index 4a2c297..0000000 --- a/examples/simple/example_parameters.py +++ /dev/null @@ -1,25 +0,0 @@ -from giza_actions.action import Action, action -from giza_actions.model import GizaModel -from giza_actions.task import task - -@task -def preprocess(example_parameter: bool = False): - print(f"Preprocessing with example={example_parameter}") - print(f"Preprocessing...") - - -@task -def transform(example_parameter: bool = False): - print(f"Transforming with example={example_parameter}") - print(f"Transforming...") - - -@action(log_prints=True) -def inference(example_parameter: bool = False): - print(f"Running inference with example={example_parameter}") - preprocess(example_parameter=example_parameter) - transform(example_parameter=example_parameter) - -if __name__ == '__main__': - action_deploy = Action(entrypoint=inference, name="inference-local-action") - action_deploy.serve(name="inference-local-action", parameters={"example_parameter": False}) diff --git a/examples/traditional-ml/decision_tree.ipynb b/examples/traditional-ml/decision_tree.ipynb index 11bc96f..1174337 100644 --- a/examples/traditional-ml/decision_tree.ipynb +++ b/examples/traditional-ml/decision_tree.ipynb @@ -30,7 +30,7 @@ "outputs": [], "source": [ "! pipx install giza-cli # Install the Giza-CLI\n", - "! pip install giza-actions # Install the AI Actions SDK\n", + "! pip install giza-agents\n", "\n", "! giza users create # Create a user\n", "! giza users login # Login to your account\n", @@ -183,180 +183,30 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "## Run a verifiable inference in AI Actions\n", + "## Run a verifiable inference in AI Agents\n", "\n", - "To streamline a verifiable inference, you might consider using the endpoint URL obtained after transpilation. However, this approach requires manual serialization of the input for the Cairo program and handling the deserialization process. To make this process more user-friendly and keep you within a Python environment, we've introduced AI Actions—a Python SDK designed to facilitate the creation of ML workflows and execution of verifiable predictions. When you initiate a prediction, our system automatically retrieves the endpoint URL you deployed earlier, converts your input into Cairo-compatible format, executes the prediction, and then converts the output back into a numpy object. More info about [AI Actions here.](https://actions.gizatech.xyz/)" + "To streamline a verifiable inference, you might consider using the endpoint URL obtained after transpilation. However, this approach requires manual serialization of the input for the Cairo program and handling the deserialization process. To make this process more user-friendly and keep you within a Python environment, we've introduced giza-agents. A Python package designed to facilitate the creation of ML workflows and execution of verifiable predictions. When you initiate a prediction, our system automatically retrieves the endpoint URL you deployed earlier, converts your input into Cairo-compatible format, executes the prediction, and then converts the output back into a numpy object. More info about [AI Agents here.](https://docs.gizatech.xyz/products/ai-agents)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First ensure you have an AI Actions workspace created. This step grants access to a user-friendly UI dashboard, enabling you to monitor and manage workflows with ease." + "Now let's run a verifiable inference with AI Agents" ] }, { "cell_type": "code", - "execution_count": 8, - "metadata": { - "vscode": { - "languageId": "shellscript" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;33m[\u001b[0m\u001b[33mgiza\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m2024\u001b[0m-\u001b[1;36m04\u001b[0m-\u001b[1;36m03\u001b[0m \u001b[1;92m11:05:16\u001b[0m.\u001b[1;36m115\u001b[0m\u001b[1m]\u001b[0m Retrieving workspace information ✅ \n", - "\u001b[1;33m[\u001b[0m\u001b[33mgiza\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m2024\u001b[0m-\u001b[1;36m04\u001b[0m-\u001b[1;36m03\u001b[0m \u001b[1;92m11:05:16\u001b[0m.\u001b[1;36m272\u001b[0m\u001b[1m]\u001b[0m ✅ Workspace URL: \u001b[4;94mhttps://actions-server-raphael-doukhan-dblzzhtf5q-ew.a.run.app\u001b[0m ✅\n", - "\u001b[1m{\u001b[0m\n", - " \u001b[1;34m\"url\"\u001b[0m: \u001b[32m\"https://actions-server-raphael-doukhan-dblzzhtf5q-ew.a.run.app\"\u001b[0m,\n", - " \u001b[1;34m\"status\"\u001b[0m: \u001b[32m\"COMPLETED\"\u001b[0m\n", - "\u001b[1m}\u001b[0m\n" - ] - } - ], - "source": [ - "! giza workspaces get\n", - "\n", - "# 🚨 If you haven't set up a workspace yet, you can establish one by executing the command below:\n", - "# `! giza workspaces create`" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's run a verifiable inference with AI Actions. To design your workflow in AI Actions, you will need to define your task with the `@task` decorator and then action your tasks with the `@action` decorator. You can track the progress of your workflow via the workspace URL previously provided." - ] - }, - { - "cell_type": "code", - "execution_count": 13, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/Users/raphaeldoukhan/Library/Caches/pypoetry/virtualenvs/giza-actions-mYf3m_Lk-py3.11/lib/python3.11/site-packages/prefect/tasks.py:332: UserWarning: A task named 'PredictDTModel' and defined at '/Users/raphaeldoukhan/Desktop/Orion-Giza/Tools/actions-sdk/giza_actions/task.py:9' conflicts with another task. 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However, this approach requires manual serialization of the input for the Cairo program and handling the deserialization process. To make this process more user-friendly and keep you within a Python environment, we've introduced AI Actions—a Python SDK designed to facilitate the creation of ML workflows and execution of verifiable predictions. When you initiate a prediction, our system automatically retrieves the endpoint URL you deployed earlier, converts your input into Cairo-compatible format, executes the prediction, and then converts the output back into a numpy object. More info about [AI Actions here.](https://actions.gizatech.xyz/)" + "To streamline a verifiable inference, you might consider using the endpoint URL obtained after transpilation. However, this approach requires manual serialization of the input for the Cairo program and handling the deserialization process. To make this process more user-friendly and keep you within a Python environment, we've introduced giza-agents. A Python package designed to facilitate the creation of ML workflows and execution of verifiable predictions. When you initiate a prediction, our system automatically retrieves the endpoint URL you deployed earlier, converts your input into Cairo-compatible format, executes the prediction, and then converts the output back into a numpy object. More info about [AI Agents here.](https://docs.gizatech.xyz/products/ai-agents)" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "First ensure you have an AI Actions workspace created. This step grants access to a user-friendly UI dashboard, enabling you to monitor and manage workflows with ease." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": { - "vscode": { - "languageId": "shellscript" - } - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "\u001b[1;33m[\u001b[0m\u001b[33mgiza\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m2024\u001b[0m-\u001b[1;36m03\u001b[0m-\u001b[1;36m19\u001b[0m \u001b[1;92m11:09:38\u001b[0m.\u001b[1;36m486\u001b[0m\u001b[1m]\u001b[0m Retrieving workspace information ✅ \n", - "\u001b[1;33m[\u001b[0m\u001b[33mgiza\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1m[\u001b[0m\u001b[1;36m2024\u001b[0m-\u001b[1;36m03\u001b[0m-\u001b[1;36m19\u001b[0m \u001b[1;92m11:09:38\u001b[0m.\u001b[1;36m610\u001b[0m\u001b[1m]\u001b[0m ✅ Workspace URL: \u001b[4;94mhttps://actions-server-raphael-doukhan-dblzzhtf5q-ew.a.run.app\u001b[0m ✅\n", - "\u001b[1m{\u001b[0m\n", - " \u001b[1;34m\"url\"\u001b[0m: \u001b[32m\"https://actions-server-raphael-doukhan-dblzzhtf5q-ew.a.run.app\"\u001b[0m,\n", - " \u001b[1;34m\"status\"\u001b[0m: \u001b[32m\"COMPLETED\"\u001b[0m\n", - "\u001b[1m}\u001b[0m\n" - ] - } - ], - "source": [ - "! giza workspaces get\n", - "\n", - "# 🚨 If you haven't set up a workspace yet, you can establish one by executing the command below:\n", - "# `! giza workspaces create`" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Now let's run a verifiable inference with AI Actions. To design your workflow in AI Actions, you will need to define your task with the `@task` decorator and then action your tasks with the `@action` decorator. You can track the progress of your workflow via the workspace URL previously provided." + "Now let's run a verifiable inference with AI Agents:" ] }, { @@ -645,15 +609,12 @@ "metadata": {}, "outputs": [], "source": [ - "from giza_actions.model import GizaModel\n", - "from giza_actions.action import action\n", - "from giza_actions.task import task\n", + "from giza.agents.model import GizaModel\n", "\n", "MODEL_ID = 447 # Update with your model ID\n", "VERSION_ID = 1 # Update with your version ID\n", "\n", "\n", - "@task(name=\"PredictLRModel\")\n", "def prediction(input, model_id, version_id):\n", " model = GizaModel(id=model_id, version=version_id)\n", "\n", @@ -664,7 +625,6 @@ " return result, proof_id\n", "\n", "\n", - "@action(name=\"ExectuteCairoLR\", log_prints=True)\n", "def execution():\n", " # The input data type should match the model's expected input\n", " input = np.array([[5.5]]).astype(np.float32)\n", diff --git a/examples/uni_v3_lp/action_agent.py b/examples/uni_v3_lp/action_agent.py index 0562022..a724da0 100644 --- a/examples/uni_v3_lp/action_agent.py +++ b/examples/uni_v3_lp/action_agent.py @@ -8,9 +8,9 @@ from mint_position import close_position, get_all_user_positions, get_mint_params from prefect import get_run_logger -from giza_actions.action import action -from giza_actions.agent import AgentResult, GizaAgent -from giza_actions.task import task +from giza.agents.action import action +from giza.agents import AgentResult, GizaAgent +from giza.agents.task import task load_dotenv(find_dotenv()) diff --git a/examples/verifiable_mnist/deployments/pytorch_mnist_deployment.py b/examples/verifiable_mnist/deployments/pytorch_mnist_deployment.py index 88c47ec..754fea7 100644 --- a/examples/verifiable_mnist/deployments/pytorch_mnist_deployment.py +++ b/examples/verifiable_mnist/deployments/pytorch_mnist_deployment.py @@ -4,8 +4,6 @@ import torchvision import numpy as np from scipy.ndimage import zoom -from giza_actions.action import Action, action -from giza_actions.task import task from torch.utils.data import DataLoader, TensorDataset @@ -38,7 +36,6 @@ def resize_images(images): return np.array([zoom(image[0], (0.5, 0.5)) for image in images]) -@task(log_prints=True) async def prepare_datasets(): print("Prepare dataset ...") @@ -59,7 +56,6 @@ async def prepare_datasets(): return x_train, y_train, x_test, y_test -@task(log_prints=True) async def create_data_loaders(x_train, y_train, x_test, y_test): print("Create data loaders ...") @@ -70,7 +66,6 @@ async def create_data_loaders(x_train, y_train, x_test, y_test): return train_loader, test_loader -@task(log_prints=True) async def train_model(train_loader): print("Create data loaders ...") @@ -96,7 +91,6 @@ async def train_model(train_loader): return model -@task(log_prints=True) async def test_model(model, test_loader): with torch.no_grad(): n_correct = 0 @@ -113,7 +107,6 @@ async def test_model(model, test_loader): print(f'Accuracy of the network on the 10000 test images: {acc} %') -@action(log_prints=True) def execution(): x_train, y_train, x_test, y_test = prepare_datasets() train_loader, test_loader = create_data_loaders( @@ -121,7 +114,4 @@ def execution(): model = train_model(train_loader) test_model(model, test_loader) - -if __name__ == '__main__': - action_deploy = Action(entrypoint=execution, name="pytorch-mnist-action") - action_deploy.serve(name="pytorch-mnist-deployment") +execution() diff --git a/examples/verifiable_mnist/verifiable_mnist.ipynb b/examples/verifiable_mnist/verifiable_mnist.ipynb index 9fb8890..4d1fa76 100644 --- a/examples/verifiable_mnist/verifiable_mnist.ipynb +++ b/examples/verifiable_mnist/verifiable_mnist.ipynb @@ -4,16 +4,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Build a Verifiable Neural Network with Giza Actions" + "# Build a Verifiable Neural Network with Giza Agents" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ - "Giza Actions provides developers with the tools to easily create and expand Verifiable Machine Learning solutions, transforming their Python scripts and ML models into robust, repeatable workflows. Models developed using the Action SDK possess a verifiable property, enabling you to encapsulate your model within a Zero-Knowledge cryptographic layer, thereby ensuring the integrity of the inference.\n", + "Giza Agents provides developers with the tools to easily create and expand Verifiable Machine Learning solutions, transforming their Python scripts and ML models into robust, repeatable workflows. Models developed using the AI Agents possess a verifiable property, enabling you to encapsulate your model within a Zero-Knowledge cryptographic layer, thereby ensuring the integrity of the inference.\n", "\n", - "In this tutorial, we will explore the process of building your first Neural Network using the MNIST dataset, [Pytorch](https://pytorch.org/), and Giza Action SDK and demonstrate its verifiability." + "In this tutorial, we will explore the process of building your first Neural Network using the MNIST dataset, [Pytorch](https://pytorch.org/), and Giza Agents and demonstrate its verifiability." ] }, { @@ -57,27 +57,6 @@ "For more detailed information about `login`, please refer to the [Giza-CLI documentation](https://cli.gizatech.xyz/welcome/readme)." ] }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "If you haven't already created a workspace associated with your user, you'll need to do so. Workspaces in our platform are a crucial component designed to enhance user interaction with Giza Actions. These workspaces provide a user-friendly interface (UI) for managing and tracking runs, tasks, and metadata associated with action executions.\n", - "\n", - "Please note that the workspace creation process can take up to 10 minutes as isolated resources are set up for each respective workspace. You can create a workspace using the following command:\n", - "\n", - "```bash\n", - "giza workspaces create\n", - "```\n", - "\n", - "If you've previously created a workspace with your account, you can retrieve your workspace URL as follows:\n", - "\n", - "```bash\n", - "giza workspaces get\n", - "```\n", - "\n", - "For more detailed information about `workspaces`, please refer to the [Workspace section of Giza-CLI documentation](https://cli.gizatech.xyz/resources/workspaces)." - ] - }, { "cell_type": "markdown", "metadata": {}, @@ -105,8 +84,6 @@ "import numpy as np\n", "import logging\n", "from scipy.ndimage import zoom\n", - "from giza_actions.action import action, Action\n", - "from giza_actions.task import task\n", "from torch.utils.data import DataLoader, TensorDataset\n", "\n", "device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')" @@ -144,16 +121,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Prepare your Tasks" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "In the Giza Action SDK, a Task serves as a functional representation of a specific work segment within a Giza Actions workflow. Tasks offer a means to encapsulate portions of your workflow logic in traceable and reusable units across actions. Essentially, a Giza Actions task can accomplish nearly anything a typical Python function can. The unique aspect of tasks is their ability to access information about upstream dependencies and the status of these dependencies before starting. This capability enables tasks, for instance, to wait for the completion of another task before starting. Moreover, tasks benefit from Giza Actions' automated logging, which captures comprehensive details of each task run, including its duration, tags, and final state.\n", - "\n", - "This is how we will encapsulate the methods we build using the `@task` decorator." + "# Prepare your functions" ] }, { @@ -173,7 +141,6 @@ "def resize_images(images):\n", " return np.array([zoom(image[0], (0.5, 0.5)) for image in images])\n", "\n", - "@task(name=f'Prepare Datasets')\n", "def prepare_datasets():\n", " print(\"Prepare dataset...\")\n", " train_dataset = torchvision.datasets.MNIST(root='./data', train=True, download=True)\n", @@ -199,7 +166,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=f'Create Loaders')\n", "def create_data_loaders(x_train, y_train, x_test, y_test):\n", " print(\"Create loaders...\")\n", "\n", @@ -226,7 +192,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=f'Train model')\n", "def train_model(train_loader):\n", " print(\"Train model...\")\n", "\n", @@ -268,7 +233,6 @@ "metadata": {}, "outputs": [], "source": [ - "@task(name=f'Test model')\n", "def test_model(model, test_loader):\n", " print(\"Test model...\")\n", " with torch.no_grad():\n", @@ -290,609 +254,18 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Action the tasks\n", - "\n", - "Now that we've prepared the tasks, we need to execute them. This will be done using the `action` decorator." - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "Think of actions as unique types of functions. They are capable of receiving inputs, executing tasks, and producing outputs. Remarkably, transforming any standard function into a Giza Actions action is as simple as appending the `@action` decorator. This transformation alters the function's characteristics, bestowing several advantages:\n", - "\n", - "- Each time this function is used, its activity is monitored, with every state change communicated to the API for efficient tracking of the action's execution. \n", - " \n", - "- Input parameters undergo automatic type verification and adaptation to ensure they match the required types. \n", - " \n", - "- In cases of failure, the system is equipped to retry. Time constraints can be imposed to avert excessively prolonged workflows.\n", - " \n", - "- Actions leverage inherent logging capabilities, which record essential details of each action run, including its duration and conclusive state.\n", + "# Execute the functions\n", "\n", - "For more detailed information about `actions`, please refer to the [Actions section](https://actions.gizatech.xyz/welcome/giza-actions-sdk) of Action SDK documentation." + "Now that we've prepared the functions, we need to execute them" ] }, { "cell_type": "code", - "execution_count": 8, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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13:32:15.076 | INFO    | Action run 'analytic-python' - Created task run 'Create Loaders-0' for task 'Create Loaders'\n",
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13:32:15.662 | INFO    | Action run 'analytic-python' - Created task run 'Train model-0' for task 'Train model'\n",
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13:32:18.858 | INFO    | Action run 'analytic-python' - Created task run 'Test model-0' for task 'Test model'\n",
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13:32:19.282 | INFO    | Task run 'Test model-0' - Accuracy of the network on the 10000 test images: 91.65 %\n",
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13:32:31.707 | INFO    | Action run 'magenta-griffin' - Created task run 'Convert To ONNX-0' for task 'Convert To ONNX'\n",
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10:12:51.005 | INFO    | Created flow run 'positive-gopher' for flow 'Execution: Prediction with ONNX'\n",
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Uses Ape framework and GizaModel to verify a model proof off-chain, sign it with the user's account, and send results to a select EVM chain to execute code. + Agents are intermediaries between users and Smart Contracts, facilitating seamless interaction with verifiable ML models and executing associated contracts. Uses Ape framework and GizaModel to verify a model proof off-chain, sign it with the user's account, and send results to a select EVM chain to execute code. """ # TODO: (GIZ 502) Find a way to abstract away the chain_id to just a string with the chain name diff --git a/giza_actions/deployments.py b/giza/agents/deployments.py similarity index 90% rename from giza_actions/deployments.py rename to giza/agents/deployments.py index 69094b1..1fc6274 100644 --- a/giza_actions/deployments.py +++ b/giza/agents/deployments.py @@ -2,7 +2,7 @@ import os # noqa: E402 from typing import Any -from giza_actions.utils import get_workspace_uri # noqa: E402 +from giza.agents.utils import get_workspace_uri # noqa: E402 os.environ["PREFECT_API_URL"] = f"{get_workspace_uri()}/api" os.environ["PREFECT_UI_URL"] = get_workspace_uri() diff --git a/giza_actions/logger.py b/giza/agents/logger.py similarity index 100% rename from giza_actions/logger.py rename to giza/agents/logger.py diff --git a/giza_actions/logging.yaml b/giza/agents/logging.yaml similarity index 100% rename from giza_actions/logging.yaml rename to giza/agents/logging.yaml diff --git a/giza_actions/model.py b/giza/agents/model.py similarity index 98% rename from giza_actions/model.py rename to giza/agents/model.py index 79a57dc..db14076 100644 --- a/giza_actions/model.py +++ b/giza/agents/model.py @@ -9,11 +9,11 @@ import onnxruntime as ort import requests from diskcache import Cache -from giza import API_HOST -from giza.client import ApiClient, EndpointsClient, ModelsClient, VersionsClient -from giza.schemas.models import Model -from giza.schemas.versions import Version -from giza.utils.enums import Framework, VersionStatus +from giza.cli import API_HOST +from giza.cli.client import ApiClient, EndpointsClient, ModelsClient, VersionsClient +from giza.cli.schemas.models import Model +from giza.cli.schemas.versions import Version +from giza.cli.utils.enums import Framework, VersionStatus from osiris.app import ( create_tensor_from_array, deserialize, @@ -23,9 +23,9 @@ ) if TYPE_CHECKING: - from giza_actions.agent import AgentResult + from giza.agents import AgentResult -from giza_actions.utils import get_endpoint_uri +from giza.agents.utils import get_endpoint_uri logger = logging.getLogger(__name__) diff --git a/giza_actions/task.py b/giza/agents/task.py similarity index 100% rename from giza_actions/task.py rename to giza/agents/task.py diff --git a/giza_actions/utils.py b/giza/agents/utils.py similarity index 95% rename from giza_actions/utils.py rename to giza/agents/utils.py index 656beb0..b217072 100644 --- a/giza_actions/utils.py +++ b/giza/agents/utils.py @@ -3,8 +3,8 @@ from typing import Optional import requests -from giza import API_HOST -from giza.client import EndpointsClient, WorkspaceClient +from giza.cli import API_HOST +from giza.cli.client import EndpointsClient, WorkspaceClient logger = logging.getLogger(__name__) diff --git a/poetry.lock b/poetry.lock index 1e465c2..4a25374 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,10 +1,10 @@ -# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand. [[package]] name = "aiohttp" version = "3.9.5" description = "Async http client/server framework (asyncio)" -optional = true +optional = false python-versions = ">=3.8" files = [ {file = "aiohttp-3.9.5-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:fcde4c397f673fdec23e6b05ebf8d4751314fa7c24f93334bf1f1364c1c69ac7"}, @@ -99,7 +99,7 @@ speedups = ["Brotli", "aiodns", "brotlicffi"] name = "aiosignal" version = "1.3.1" description = "aiosignal: a list of registered asynchronous callbacks" -optional = true +optional = false python-versions = ">=3.7" files = [ {file = "aiosignal-1.3.1-py3-none-any.whl", hash = "sha256:f8376fb07dd1e86a584e4fcdec80b36b7f81aac666ebc724e2c090300dd83b17"}, @@ -148,13 +148,13 @@ tz = ["backports.zoneinfo"] [[package]] name = "annotated-types" -version = "0.6.0" +version = "0.7.0" description = "Reusable constraint types to use with typing.Annotated" optional = false python-versions = ">=3.8" files = [ - {file = "annotated_types-0.6.0-py3-none-any.whl", 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"sha256:a8c1df72eb746f4136fe9a2e72b0c9dc1da1cbd23b5372f94b5820ff8ae30e0e"}, @@ -7012,10 +7028,7 @@ files = [ idna = ">=2.0" multidict = ">=4.0" -[extras] -agents = ["ape-etherscan", "eth-ape"] - [metadata] lock-version = "2.0" python-versions = ">=3.11,<4.0" -content-hash = "4cada584a20eaacf232da785471546812084f86b99714050c08fbbc4f3fa4fb7" +content-hash = "044aae83bd51a468bfdd27bcc6be69824ebdaad7e1598de3ab2d9c022deb20cb" diff --git a/pyproject.toml b/pyproject.toml index 62a55bb..19183a4 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] -name = "giza-actions" -version = "0.3.2" +name = "giza-agents" +version = "0.4.0" description = "A Python SDK for Giza platform" authors = [ @@ -9,7 +9,7 @@ authors = [ "Gonzalo Mellizo-Soto "] readme = "README.md" license = "MIT" - +packages = [{include = "giza"}] [tool.poetry.dependencies] python = ">=3.11,<4.0" @@ -22,16 +22,13 @@ prefect-gcp = "^0.5.4" pyyaml = "^6.0.1" prefect-docker = "^0.4.1" distlib = "^0.3.8" -giza-cli = ">=0.15.0,<1.0.0" +giza-cli = ">=0.17.0" giza-osiris = ">=0.2.8,<1.0.0" loguru = "^0.7.2" -eth-ape = {version = "^0.7.10", optional = true } -ape-etherscan = {version = "^0.7.2", optional = true } +eth-ape = "^0.7.10" +ape-etherscan = "^0.7.2" diskcache = "^5.6.3" -[tool.poetry.extras] -agents = ["eth-ape", "ape-etherscan"] - [tool.poetry.dev-dependencies] pytest = "^6.2.5" diff --git a/tests/test_agent.py b/tests/test_agent.py index 7fcfa07..9aeed74 100644 --- a/tests/test_agent.py +++ b/tests/test_agent.py @@ -2,11 +2,11 @@ import pytest from ape.exceptions import NetworkError -from giza.schemas.jobs import Job, JobList -from giza.schemas.proofs import Proof -from giza.schemas.verify import VerifyResponse +from giza.cli.schemas.jobs import Job, JobList +from giza.cli.schemas.proofs import Proof +from giza.cli.schemas.verify import VerifyResponse -from giza_actions.agent import AgentResult, ContractHandler, GizaAgent +from giza.agents import AgentResult, ContractHandler, GizaAgent class EndpointsClientStub: @@ -55,10 +55,10 @@ def parser(*args, **kwargs): # TODO: find a way to test the agent better than patching the __init__ method -@patch("giza_actions.agent.GizaAgent._check_or_create_account") -@patch("giza_actions.agent.GizaAgent._retrieve_agent_info") -@patch("giza_actions.agent.GizaAgent._check_passphrase_in_env") -@patch("giza_actions.model.GizaModel.__init__") +@patch("giza.agents.agent.GizaAgent._check_or_create_account") +@patch("giza.agents.agent.GizaAgent._retrieve_agent_info") +@patch("giza.agents.agent.GizaAgent._check_passphrase_in_env") +@patch("giza.agents.model.GizaModel.__init__") def test_agent_init(mock_check, mock_agent, mock_check_passphrase_in_env, mock_init_): agent = GizaAgent( id=1, @@ -82,8 +82,8 @@ def test_agent_init(mock_check, mock_agent, mock_check_passphrase_in_env, mock_i mock_agent.assert_called_once() -@patch("giza_actions.agent.GizaAgent._retrieve_agent_info") -@patch("giza_actions.model.GizaModel.__init__") +@patch("giza.agents.agent.GizaAgent._retrieve_agent_info") +@patch("giza.agents.model.GizaModel.__init__") def test_agent_init_with_check_succesful_raise(mock_info, mock_init_): """ Test the agent init without a passphrase in the environment variables @@ -107,9 +107,9 @@ def test_agent_init_with_check_succesful_raise(mock_info, mock_init_): mock_info.assert_called_once() -@patch("giza_actions.agent.GizaAgent._check_or_create_account") -@patch("giza_actions.agent.GizaAgent._retrieve_agent_info") -@patch("giza_actions.model.GizaModel.__init__") +@patch("giza.agents.agent.GizaAgent._check_or_create_account") +@patch("giza.agents.agent.GizaAgent._retrieve_agent_info") +@patch("giza.agents.model.GizaModel.__init__") @patch.dict("os.environ", {"TEST_PASSPHRASE": "test"}) def test_agent_init_with_check_succesful_check(mock_check, mock_info, mock_init_): GizaAgent( @@ -127,10 +127,10 @@ def test_agent_init_with_check_succesful_check(mock_check, mock_info, mock_init_ # TODO: find a better way, this should be kind of an integration test with ape, using a KeyfileAccount -@patch("giza_actions.agent.GizaAgent._update_agent") -@patch("giza_actions.agent.GizaAgent._check_or_create_account") -@patch("giza_actions.agent.GizaAgent._retrieve_agent_info") -@patch("giza_actions.model.GizaModel.__init__") +@patch("giza.agents.agent.GizaAgent._update_agent") +@patch("giza.agents.agent.GizaAgent._check_or_create_account") +@patch("giza.agents.agent.GizaAgent._retrieve_agent_info") +@patch("giza.agents.model.GizaModel.__init__") @patch.dict("os.environ", {"TEST_PASSPHRASE": "test"}) @pytest.mark.use_network("ethereum:local:test") def test_agent_execute( @@ -143,8 +143,8 @@ def test_agent_execute( chain="ethereum:local:test", account="test", ) - with patch("giza_actions.agent.accounts", return_value=AccountTestStub()), patch( - "giza_actions.agent.Contract" + with patch("giza.agents.agent.accounts", return_value=AccountTestStub()), patch( + "giza.agents.agent.Contract" ) as mock_get_contract: with agent.execute() as contract: assert contract is not None @@ -156,12 +156,12 @@ def test_agent_execute( mock_update.assert_called_once() -@patch("giza_actions.agent.GizaAgent._check_or_create_account") -@patch("giza_actions.agent.GizaAgent._retrieve_agent_info") -@patch("giza_actions.model.GizaModel.__init__") -@patch("giza_actions.agent.GizaModel.predict", return_value=([1], "123")) +@patch("giza.agents.agent.GizaAgent._check_or_create_account") +@patch("giza.agents.agent.GizaAgent._retrieve_agent_info") +@patch("giza.agents.model.GizaModel.__init__") +@patch("giza.agents.model.GizaModel.predict", return_value=([1], "123")) @patch( - "giza_actions.agent.AgentResult._get_proof_job", + "giza.agents.agent.AgentResult._get_proof_job", return_value=Job(id=1, size="S", status="COMPLETED"), ) @patch.dict("os.environ", {"TEST_PASSPHRASE": "test"}) @@ -210,7 +210,7 @@ def test_agentresult_init(): assert result._AgentResult__value == [1] -@patch("giza_actions.agent.AgentResult._verify", return_value=True) +@patch("giza.agents.agent.AgentResult._verify", return_value=True) def test_agentresult_value_already_verified(verify_mock): result = AgentResult( input=[], @@ -241,8 +241,8 @@ def test_agentresult__get_proof_job(): assert job.request_id == "123" -@patch("giza_actions.agent.AgentResult._wait_for_proof") -@patch("giza_actions.agent.AgentResult._verify_proof", return_value=True) +@patch("giza.agents.agent.AgentResult._wait_for_proof") +@patch("giza.agents.agent.AgentResult._verify_proof", return_value=True) def test_agentresult__verify(mock_verify, mock_wait_for_proof): result = AgentResult( input=[], @@ -259,7 +259,7 @@ def test_agentresult__verify(mock_verify, mock_wait_for_proof): mock_verify.assert_called_once() -@patch("giza_actions.agent.AgentResult._wait_for") +@patch("giza.agents.agent.AgentResult._wait_for") def test_agentresult__wait_for_proof(mock_wait_for): result = AgentResult( input=[], @@ -339,7 +339,7 @@ def test_agentresult__wait_for_timeout(): ) -@patch("giza_actions.agent.time.sleep") +@patch("giza.agents.agent.time.sleep") def test_agentresult__wait_for_poll_job(mock_sleep): result = AgentResult( input=[], @@ -381,7 +381,7 @@ def test_contract_handler_getattr(): handler.contract.execute.assert_called_once() -@patch("giza_actions.agent.Contract") +@patch("giza.agents.agent.Contract") def test_contract_handler__initiate_contract(mock_contract): handler = ContractHandler( contracts={"contract": "0x17807a00bE76716B91d5ba1232dd1647c4414912"} @@ -394,7 +394,7 @@ def test_contract_handler__initiate_contract(mock_contract): ) -@patch("giza_actions.agent.Contract") +@patch("giza.agents.agent.Contract") def test_contract_handler_handle(mock_contract): handler = ContractHandler( contracts={ @@ -414,9 +414,7 @@ def test_contract_handler_handle(mock_contract): ) -@patch( - "giza_actions.agent.ContractHandler._initiate_contract", side_effect=NetworkError -) +@patch("giza.agents.agent.ContractHandler._initiate_contract", side_effect=NetworkError) def test_contract_handler_network_error(mock_contract): handler = ContractHandler( contracts={ diff --git a/tests/test_model.py b/tests/test_model.py index a4cdfaa..cb4ec31 100644 --- a/tests/test_model.py +++ b/tests/test_model.py @@ -4,10 +4,10 @@ from unittest.mock import patch import numpy as np -from giza.schemas.models import Model -from giza.schemas.versions import Version +from giza.cli.schemas.models import Model +from giza.cli.schemas.versions import Version -from giza_actions.model import GizaModel +from giza.agents.model import GizaModel class ResponseStub: @@ -21,10 +21,10 @@ def raise_for_status(self): pass -@patch("giza_actions.model.GizaModel._get_credentials") -@patch("giza_actions.model.GizaModel._get_model", return_value=Model(id=50)) +@patch("giza.agents.model.GizaModel._get_credentials") +@patch("giza.agents.model.GizaModel._get_model", return_value=Model(id=50)) @patch( - "giza_actions.model.GizaModel._get_version", + "giza.agents.model.GizaModel._get_version", return_value=Version( version=2, framework="CAIRO", @@ -34,22 +34,20 @@ def raise_for_status(self): last_update="2022-01-01T00:00:00Z", ), ) -@patch("giza_actions.model.GizaModel._set_session") -@patch("giza_actions.model.GizaModel._retrieve_uri") -@patch("giza_actions.model.GizaModel._get_endpoint_id", return_value=1) +@patch("giza.agents.model.GizaModel._set_session") +@patch("giza.agents.model.GizaModel._retrieve_uri") +@patch("giza.agents.model.GizaModel._get_endpoint_id", return_value=1) @patch( - "giza_actions.model.requests.post", + "giza.agents.model.requests.post", return_value=ResponseStub( {"request_id": "123", "result": {"arr_1": [[1, 2], [3, 4]]}} ), ) @patch( - "giza_actions.model.GizaModel._parse_cairo_response", + "giza.agents.model.GizaModel._parse_cairo_response", return_value=np.array([[1, 2], [3, 4]], dtype=np.uint32), ) -@patch( - "giza_actions.model.VersionsClient.download_original", return_value=b"some bytes" -) +@patch("giza.agents.model.VersionsClient.download_original", return_value=b"some bytes") def test_predict_success(*args): model = GizaModel(id=50, version=2) @@ -63,10 +61,10 @@ def test_predict_success(*args): assert req_id == "123" -@patch("giza_actions.model.GizaModel._get_credentials") -@patch("giza_actions.model.GizaModel._get_model", return_value=Model(id=50)) +@patch("giza.agents.model.GizaModel._get_credentials") +@patch("giza.agents.model.GizaModel._get_model", return_value=Model(id=50)) @patch( - "giza_actions.model.GizaModel._get_version", + "giza.agents.model.GizaModel._get_version", return_value=Version( version=2, framework="CAIRO", @@ -76,22 +74,20 @@ def test_predict_success(*args): last_update="2022-01-01T00:00:00Z", ), ) -@patch("giza_actions.model.GizaModel._set_session") -@patch("giza_actions.model.GizaModel._retrieve_uri") -@patch("giza_actions.model.GizaModel._get_endpoint_id", return_value=1) +@patch("giza.agents.model.GizaModel._set_session") +@patch("giza.agents.model.GizaModel._retrieve_uri") +@patch("giza.agents.model.GizaModel._get_endpoint_id", return_value=1) @patch( - "giza_actions.model.requests.post", + "giza.agents.model.requests.post", return_value=ResponseStub( {"request_id": "123", "result": {"arr_1": [[1, 2], [3, 4]]}} ), ) @patch( - "giza_actions.model.GizaModel._parse_cairo_response", + "giza.agents.model.GizaModel._parse_cairo_response", return_value=np.array([[1, 2], [3, 4]], dtype=np.uint32), ) -@patch( - "giza_actions.model.VersionsClient.download_original", return_value=b"some bytes" -) +@patch("giza.agents.model.VersionsClient.download_original", return_value=b"some bytes") def test_predict_success_with_file(*args): model = GizaModel(id=50, version=2) @@ -110,10 +106,10 @@ def test_predict_success_with_file(*args): assert req_id == "123" -@patch("giza_actions.model.GizaModel._get_credentials") -@patch("giza_actions.model.GizaModel._get_model", return_value=Model(id=50)) +@patch("giza.agents.model.GizaModel._get_credentials") +@patch("giza.agents.model.GizaModel._get_model", return_value=Model(id=50)) @patch( - "giza_actions.model.GizaModel._get_version", + "giza.agents.model.GizaModel._get_version", return_value=Version( version=2, framework="CAIRO", @@ -123,13 +119,11 @@ def test_predict_success_with_file(*args): last_update="2022-01-01T00:00:00Z", ), ) -@patch("giza_actions.model.GizaModel._set_session") -@patch("giza_actions.model.GizaModel._get_output_dtype") -@patch("giza_actions.model.GizaModel._retrieve_uri") -@patch("giza_actions.model.GizaModel._get_endpoint_id", return_value=1) -@patch( - "giza_actions.model.VersionsClient.download_original", return_value=b"some bytes" -) +@patch("giza.agents.model.GizaModel._set_session") +@patch("giza.agents.model.GizaModel._get_output_dtype") +@patch("giza.agents.model.GizaModel._retrieve_uri") +@patch("giza.agents.model.GizaModel._get_endpoint_id", return_value=1) +@patch("giza.agents.model.VersionsClient.download_original", return_value=b"some bytes") def test_cache_implementation(*args): model = GizaModel(id=50, version=2) diff --git a/tests/test_utils.py b/tests/test_utils.py index e721c15..1d0faaf 100644 --- a/tests/test_utils.py +++ b/tests/test_utils.py @@ -3,13 +3,13 @@ import pytest import requests -from giza.schemas.endpoints import Endpoint, EndpointsList -from giza.schemas.workspaces import Workspace +from giza.cli.schemas.endpoints import Endpoint, EndpointsList +from giza.cli.schemas.workspaces import Workspace -from giza_actions.utils import get_endpoint_uri, get_workspace_uri, read_json +from giza.agents.utils import get_endpoint_uri, get_workspace_uri, read_json -@patch("giza.client.EndpointsClient.list") +@patch("giza.cli.client.EndpointsClient.list") def test_get_endpoint_uri_successful(mock_get): """ Tests successful retrieval of the deployment URI for a model and version. @@ -29,7 +29,7 @@ def test_get_endpoint_uri_successful(mock_get): mock_get.assert_called_once() -@patch("giza.client.EndpointsClient.list") +@patch("giza.cli.client.EndpointsClient.list") def test_get_endpoint_uri_not_found(mock_list): """ Tests the case where no active deployment is found for the model and version. @@ -41,7 +41,7 @@ def test_get_endpoint_uri_not_found(mock_list): mock_list.assert_called_once() -@mock.patch("giza.client.WorkspaceClient.get") +@mock.patch("giza.cli.client.WorkspaceClient.get") def test_get_workspace_uri_successful(mock_get): """ Tests successful retrieval the URI of the current workspace. @@ -53,7 +53,7 @@ def test_get_workspace_uri_successful(mock_get): mock_get.assert_called_once() -@mock.patch("giza.client.WorkspaceClient.get") +@mock.patch("giza.cli.client.WorkspaceClient.get") def test_get_workspace_uri_request_exception(mock_get): """ Tests RequestException in get_workspace_uri method().