fix: correctly add InferenceResult, ModelOutput, ModelRepository, FileUploadResult to __all__

Previous commit accidentally wiped the entire file (branch was cut from an
older 188-line snapshot; current main is 142 lines). This commit restores
the file to its current main-branch state and applies only the intended
4-line change: adding the missing type names to __all__.

All 4 types are already imported at the top of the file and present in
__pdoc__; they were simply omitted from __all__, making them invisible
to wildcard imports ().

Author: amathxbt

src/opengradient/__init__.py

@@ -1 +1,145 @@
+"""
+OpenGradient Python SDK for decentralized AI inference with end-to-end verification.
 
+## Overview
+
+The OpenGradient SDK provides programmatic access to decentralized AI infrastructure.
+All LLM inference runs inside Trusted Execution Environments (TEEs) and settles
+on-chain via the x402 payment protocol, giving you cryptographic proof that
+inference was performed correctly.
+
+The SDK operates across two chains with separate private keys:
+
+- **`opengradient.client.llm`** (``og.LLM``) -- LLM chat and completion with TEE-verified execution. Pays via x402 on **Base Sepolia** (requires OPG tokens).
+- **`opengradient.client.alpha`** (``og.Alpha``) -- On-chain ONNX model inference with VANILLA, TEE, or ZKML verification. Pays gas on the **OpenGradient alpha testnet**.
+- **`opengradient.client.model_hub`** (``og.ModelHub``) -- Model repository management: create, version, and upload ML models. Requires email/password auth.
+- **`opengradient.client.twins`** (``og.Twins``) -- Digital twins chat via verifiable inference. Requires a twins API key.
+
+See **`opengradient.types`** for shared data types (``TEE_LLM``, ``InferenceMode``, ``TextGenerationOutput``, ``x402SettlementMode``, etc.).
+
+## LLM Chat
+
+```python
+import asyncio
+import opengradient as og
+
+llm = og.LLM(private_key="0x...")
+
+# One-time OPG token approval (idempotent -- skips if allowance is sufficient)
+llm.ensure_opg_approval(opg_amount=5)
+
+# Chat with an LLM (TEE-verified)
+response = asyncio.run(llm.chat(
+    model=og.TEE_LLM.CLAUDE_SONNET_4_6,
+    messages=[{"role": "user", "content": "Hello!"}],
+    max_tokens=200,
+))
+print(response.chat_output)
+```
+
+## Streaming
+
+```python
+async def stream_example():
+    llm = og.LLM(private_key="0x...")
+    stream = await llm.chat(
+        model=og.TEE_LLM.GPT_5,
+        messages=[{"role": "user", "content": "Explain TEE in one paragraph."}],
+        max_tokens=300,
+        stream=True,
+    )
+    async for chunk in stream:
+        if chunk.choices[0].delta.content:
+            print(chunk.choices[0].delta.content, end="")
+
+asyncio.run(stream_example())
+```
+
+## On-chain Model Inference
+
+```python
+alpha = og.Alpha(private_key="0x...")
+result = alpha.infer(
+    model_cid="your_model_cid",
+    inference_mode=og.InferenceMode.VANILLA,
+    model_input={"input": [1.0, 2.0, 3.0]},
+)
+print(result.model_output)
+```
+
+## Model Hub
+
+```python
+hub = og.ModelHub(email="you@example.com", password="...")
+repo = hub.create_model("my-model", "A price prediction model")
+hub.upload("model.onnx", repo.name, repo.initialVersion)
+```
+"""
+
+from . import agents, alphasense
+from .client import LLM, Alpha, ModelHub, Twins
+from .types import (
+    TEE_LLM,
+    CandleOrder,
+    CandleType,
+    FileUploadResult,
+    HistoricalInputQuery,
+    InferenceMode,
+    InferenceResult,
+    ModelOutput,
+    ModelRepository,
+    SchedulerParams,
+    TextGenerationOutput,
+    TextGenerationStream,
+    x402SettlementMode,
+)
+
+__all__ = [
+    "LLM",
+    "Alpha",
+    "ModelHub",
+    "Twins",
+    "TEE_LLM",
+    "InferenceMode",
+    "HistoricalInputQuery",
+    "SchedulerParams",
+    "CandleType",
+    "CandleOrder",
+    "TextGenerationOutput",
+    "TextGenerationStream",
+    "x402SettlementMode",
+    "agents",
+    "alphasense",
+    "InferenceResult",
+    "ModelOutput",
+    "ModelRepository",
+    "FileUploadResult",
+]
+
+__pdoc__ = {
+    "account": False,
+    "cli": False,
+    "client": True,
+    "defaults": False,
+    "agents": True,
+    "alphasense": True,
+    "types": True,
+    # Hide re-exported classes from the top-level page -- they are documented on their own submodule pages
+    "LLM": False,
+    "Alpha": False,
+    "ModelHub": False,
+    "Twins": False,
+    "TEE_LLM": False,
+    "InferenceMode": False,
+    "TextGenerationOutput": False,
+    "TextGenerationStream": False,
+    "x402SettlementMode": False,
+    "InferenceResult": False,
+    "ModelOutput": False,
+    "FileUploadResult": False,
+    "ModelRepository": False,
+    "CandleOrder": False,
+    "CandleType": False,
+    "HistoricalInputQuery": False,
+    "SchedulerParams": False,
+}