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docs/opengradient/client/index.md

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- **[model_hub](./model_hub)** -- Model repository management: create, version, and upload ML models
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- **[alpha](./alpha)** -- Alpha Testnet features: on-chain ONNX model inference (VANILLA, TEE, ZKML modes), workflow deployment, and scheduled ML model execution (OpenGradient testnet gas tokens)
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- **[twins](./twins)** -- Digital twins chat via OpenGradient verifiable inference
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- **`opengradient.client.opg_token`** -- OPG token Permit2 approval utilities for x402 payments
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- **`opengradient.client.tee_registry`** -- TEE registry client for verified endpoints and TLS certificates
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## Usage
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docs/opengradient/client/llm.md

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)
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```
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**Arguments**
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* **`private_key (str)`**: Ethereum private key for signing x402 payments.
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* **`rpc_url (str)`**: RPC URL for the OpenGradient network. Used to fetch the
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active TEE endpoint from the on-chain registry when ``llm_server_url``
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is not provided.
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* **`tee_registry_address (str)`**: Address of the on-chain TEE registry contract.
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* **`llm_server_url (str, optional)`**: Bypass the registry and connect directly
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to this TEE endpoint URL (e.g. ``"https://1.2.3.4"``). When set,
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TLS certificate verification is disabled automatically because
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self-hosted TEE servers typically use self-signed certificates.
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.. warning::
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Using ``llm_server_url`` disables TLS certificate verification,
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which removes protection against man-in-the-middle attacks.
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Only connect to servers you trust and over secure network paths.
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#### Methods
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docs/opengradient/index.md

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# Package opengradient
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**Version: 0.8.0**
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**Version: 0.9.0**
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OpenGradient Python SDK for decentralized AI inference with end-to-end verification.
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pyproject.toml

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[tool.ruff.mccabe]
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max-complexity = 10
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[dependency-groups]
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dev = [
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"setuptools>=82.0.1",
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]

uv.lock

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