Refactor Client API

README.md

@@ -51,18 +51,18 @@ opengradient config init
 import os
 import opengradient as og
 
-og_client = og.new_client(
+client = og.init(
+    private_key=os.environ.get("OG_PRIVATE_KEY"),
     email=None,  # Optional: only needed for model uploads
     password=None,
-    private_key=os.environ.get("OG_PRIVATE_KEY"),
 )
 ```
 
 ### 3. Basic Usage
 
 #### LLM Chat
 ```python
-completion = og_client.llm_chat(
+completion = client.llm.chat(
     model=og.TEE_LLM.GPT_4O,
     messages=[{"role": "user", "content": "Hello!"}],
 )
@@ -73,7 +73,7 @@ print(f"Tx hash: {completion.transaction_hash}")
 #### Custom Model Inference
 Browse models on our [Model Hub](https://hub.opengradient.ai/) or upload your own:
 ```python
-result = og_client.infer(
+result = client.inference.infer(
     model_cid="your-model-cid",
     model_input={"input": [1.0, 2.0, 3.0]},
     inference_mode=og.InferenceMode.VANILLA,
@@ -86,7 +86,7 @@ print(f"Output: {result.model_output}")
 OpenGradient supports secure, verifiable inference through TEE for leading LLM providers. Access models from OpenAI, Anthropic, Google, and xAI with cryptographic attestation:
 ```python
 # Use TEE mode for verifiable AI execution
-completion = og_client.llm_chat(
+completion = client.llm.chat(
     model=og.TEE_LLM.CLAUDE_3_7_SONNET,
     messages=[{"role": "user", "content": "Your message here"}],
 )
@@ -112,10 +112,10 @@ The Alpha Testnet provides access to experimental features, including **workflow
 ```python
 import opengradient as og
 
-og.init(
+client = og.init(
+    private_key="your-private-key",
     email="your-email",
     password="your-password",
-    private_key="your-private-key",
 )
 
 # Define input query for historical price data
@@ -129,7 +129,7 @@ input_query = og.HistoricalInputQuery(
 )
 
 # Deploy a workflow (optionally with scheduling)
-contract_address = og.alpha.new_workflow(
+contract_address = client.alpha.new_workflow(
     model_cid="your-model-cid",
     input_query=input_query,
     input_tensor_name="input",
@@ -141,14 +141,14 @@ print(f"Workflow deployed at: {contract_address}")
 #### Execute and Read Results
 ```python
 # Manually trigger workflow execution
-result = og.alpha.run_workflow(contract_address)
+result = client.alpha.run_workflow(contract_address)
 print(f"Inference output: {result}")
 
 # Read the latest result
-latest = og.alpha.read_workflow_result(contract_address)
+latest = client.alpha.read_workflow_result(contract_address)
 
 # Get historical results
-history = og.alpha.read_workflow_history(contract_address, num_results=5)
+history = client.alpha.read_workflow_history(contract_address, num_results=5)
 ```
 
 ### 6. Examples

docs/opengradient/llm/index.md → docs/opengradient/agents/index.md

@@ -4,7 +4,7 @@ outline: [2,3]
 
 
 
-# Package opengradient.llm
+# Package opengradient.agents
 
 OpenGradient LLM Adapters
 
@@ -19,7 +19,7 @@ into existing applications and agent frameworks.
 ### Langchain adapter 
 
 ```python
-def langchain_adapter(private_key: str, model_cid: opengradient.types.LLM, max_tokens: int = 300) ‑> opengradient.llm.og_langchain.OpenGradientChatModel
+def langchain_adapter(private_key: str, model_cid: opengradient.types.LLM, max_tokens: int = 300) ‑> opengradient.agents.og_langchain.OpenGradientChatModel
 ```
 
 
@@ -34,7 +34,7 @@ and can be plugged into LangChain agents.
 ### Openai adapter 
 
 ```python
-def openai_adapter(private_key: str) ‑> opengradient.llm.og_openai.OpenGradientOpenAIClient
+def openai_adapter(private_key: str) ‑> opengradient.agents.og_openai.OpenGradientOpenAIClient
 ```
 
 

docs/opengradient/alphasense/index.md

@@ -15,7 +15,7 @@ OpenGradient AlphaSense Tools
 ### Create read workflow tool 
 
 ```python
-def create_read_workflow_tool(tool_type: opengradient.alphasense.types.ToolType, workflow_contract_address: str, tool_name: str, tool_description: str, output_formatter: Callable[..., str] = <function <lambda>>) ‑> Union[langchain_core.tools.base.BaseTool, Callable]
+def create_read_workflow_tool(tool_type: opengradient.alphasense.types.ToolType, workflow_contract_address: str, tool_name: str, tool_description: str, alpha: Optional[opengradient.client.alpha.Alpha] = None, output_formatter: Callable[..., str] = <function <lambda>>) ‑> Union[langchain_core.tools.base.BaseTool, Callable]
 ```
 
 
@@ -44,7 +44,7 @@ Callable: For ToolType.SWARM, returns a decorated function with appropriate meta
 ### Create run model tool 
 
 ```python
-def create_run_model_tool(tool_type: opengradient.alphasense.types.ToolType, model_cid: str, tool_name: str, model_input_provider: Callable[..., Dict[str, Union[str, int, float, List, numpy.ndarray]]], model_output_formatter: Callable[[opengradient.types.InferenceResult], str], tool_input_schema: Optional[Type[pydantic.main.BaseModel]] = None, tool_description: str = 'Executes the given ML model', inference_mode: opengradient.types.InferenceMode = InferenceMode.VANILLA) ‑> Union[langchain_core.tools.base.BaseTool, Callable]
+def create_run_model_tool(tool_type: opengradient.alphasense.types.ToolType, model_cid: str, tool_name: str, model_input_provider: Callable[..., Dict[str, Union[str, int, float, List, numpy.ndarray]]], model_output_formatter: Callable[[opengradient.types.InferenceResult], str], inference: Optional[opengradient.client.onchain_inference.Inference] = None, tool_input_schema: Optional[Type[pydantic.main.BaseModel]] = None, tool_description: str = 'Executes the given ML model', inference_mode: opengradient.types.InferenceMode = InferenceMode.VANILLA) ‑> Union[langchain_core.tools.base.BaseTool, Callable]
 ```
 
 

docs/opengradient/alpha.md → docs/opengradient/client/alpha.md

@@ -4,7 +4,7 @@ outline: [2,3]
 
 
 
-# Package opengradient.alpha
+# Package opengradient.client.alpha
 
 Alpha Testnet features for OpenGradient SDK.
 
@@ -16,7 +16,7 @@ including workflow management and ML model execution.
 
 ###  Alpha
 
-<code>class <b>Alpha</b>(client: Client)</code>
+<code>class <b>Alpha</b>(blockchain: [Web3](docs/main.md#Web3), wallet_account: [local](docs/signers.md#local))</code>
 
 
 

docs/opengradient/client/client.md

@@ -0,0 +1,53 @@
+---
+outline: [2,3]
+---
+
+
+
+# Package opengradient.client.client
+
+## Classes
+
+
+###  Client
+
+<code>class <b>Client</b>(private_key: str, email: Optional[str] = None, password: Optional[str] = None, rpc_url: str = 'https://ogevmdevnet.opengradient.ai', api_url: str = 'https://sdk-devnet.opengradient.ai', contract_address: str = '0x8383C9bD7462F12Eb996DD02F78234C0421A6FaE', og_llm_server_url: Optional[str] = 'https://llmogevm.opengradient.ai', og_llm_streaming_server_url: Optional[str] = 'https://llmogevm.opengradient.ai')</code>
+
+
+
+
+Initialize the OpenGradient client.
+
+
+**Arguments**
+
+* **`private_key`**: Private key for OpenGradient transactions.
+* **`email`**: Email for Model Hub authentication. Optional.
+* **`password`**: Password for Model Hub authentication. Optional.
+* **`rpc_url`**: RPC URL for the blockchain network.
+* **`api_url`**: API URL for the OpenGradient API.
+* **`contract_address`**: Inference contract address.
+* **`og_llm_server_url`**: OpenGradient LLM server URL.
+* **`og_llm_streaming_server_url`**: OpenGradient LLM streaming server URL.
+
+
+#### Variables
+
+
+
+* static `inference  : opengradient.client.onchain_inference.Inference` - The type of the None singleton.
+
+* static `llm  : opengradient.client.llm.LLM` - The type of the None singleton.
+
+* static `model_hub  : opengradient.client.model_hub.ModelHub` - The type of the None singleton.
+
+
+
+* `alpha` - Access Alpha Testnet features.
+
+  Returns:
+    Alpha: Alpha namespace with workflow and ML model execution methods.
+
+  Example:
+    client = og.Client(...)
+    result = client.alpha.new_workflow(model_cid, input_query, input_tensor_name)

docs/opengradient/client/exceptions.md

@@ -0,0 +1,188 @@
+---
+outline: [2,3]
+---
+
+
+
+# Package opengradient.client.exceptions
+
+## Classes
+
+
+###  AuthenticationError
+
+<code>class <b>AuthenticationError</b>(message='Authentication failed', **kwargs)</code>
+
+
+
+
+Raised when there's an authentication error
+
+
+
+
+
+###  FileNotFoundError
+
+<code>class <b>FileNotFoundError</b>(file_path)</code>
+
+
+
+
+Raised when a file is not found
+
+
+
+
+
+###  InferenceError
+
+<code>class <b>InferenceError</b>(message, model_cid=None, **kwargs)</code>
+
+
+
+
+Raised when there's an error during inference
+
+
+
+
+
+###  InsufficientCreditsError
+
+<code>class <b>InsufficientCreditsError</b>(message='Insufficient credits', required_credits=None, available_credits=None, **kwargs)</code>
+
+
+
+
+Raised when the user has insufficient credits for the operation
+
+
+
+
+
+###  InvalidInputError
+
+<code>class <b>InvalidInputError</b>(message, invalid_fields=None, **kwargs)</code>
+
+
+
+
+Raised when invalid input is provided
+
+
+
+
+
+###  NetworkError
+
+<code>class <b>NetworkError</b>(message, status_code=None, response=None)</code>
+
+
+
+
+Raised when a network error occurs
+
+
+
+
+
+###  OpenGradientError
+
+<code>class <b>OpenGradientError</b>(message, status_code=None, response=None)</code>
+
+
+
+
+Base exception for OpenGradient SDK
+
+
+#### Subclasses
+  * `AuthenticationError`
+  * `FileNotFoundError`
+  * `InferenceError`
+  * `InsufficientCreditsError`
+  * `InvalidInputError`
+  * `NetworkError`
+  * `RateLimitError`
+  * `ResultRetrievalError`
+  * `ServerError`
+  * `TimeoutError`
+  * `UnsupportedModelError`
+  * `UploadError`
+
+
+
+###  RateLimitError
+
+<code>class <b>RateLimitError</b>(message='Rate limit exceeded', retry_after=None, **kwargs)</code>
+
+
+
+
+Raised when API rate limit is exceeded
+
+
+
+
+
+###  ResultRetrievalError
+
+<code>class <b>ResultRetrievalError</b>(message, inference_cid=None, **kwargs)</code>
+
+
+
+
+Raised when there's an error retrieving results
+
+
+
+
+
+###  ServerError
+
+<code>class <b>ServerError</b>(message, status_code=None, response=None)</code>
+
+
+
+
+Raised when a server error occurs
+
+
+
+
+
+###  TimeoutError
+
+<code>class <b>TimeoutError</b>(message='Request timed out', timeout=None, **kwargs)</code>
+
+
+
+
+Raised when a request times out
+
+
+
+
+
+###  UnsupportedModelError
+
+<code>class <b>UnsupportedModelError</b>(model_type)</code>
+
+
+
+
+Raised when an unsupported model type is used
+
+
+
+
+
+###  UploadError
+
+<code>class <b>UploadError</b>(message, file_path=None, **kwargs)</code>
+
+
+
+
+Raised when there's an error during file upload