Merge pull request #137 from djwu563/develop/v0.2.1

Update the device docs to include ProgrammaticClient

docs/concepts/clients/devices/app.md

@@ -0,0 +1,18 @@
+# AppClient
+
+## Introduction
+`AppClient` is a client tool designed for user interaction within applications.
+
+## Initialization Parameters
+- `interactor`: Optional parameter, workflow used for interaction
+- `processor`: Optional parameter, workflow used for image processing
+- `config_path`: Optional parameter, path to the worker configuration file
+- `workers`: Optional parameter, list of Worker instances
+
+Note:
+1. Either `interactor` or `processor` must be provided
+2. At least one of `config_path` or `workers` must be provided, or both can be used
+
+## Input and Output
+- Input: Uses `AppInput`
+- Output: Uses `AppCallback`

docs/concepts/clients/devices/cli.md

@@ -0,0 +1,22 @@
+# DefaultClient
+
+## Introduction
+`DefaultClient` is the default client used for interacting with users via the command line.
+
+## Initialization Parameters
+- `interactor`: Optional parameter, workflow used for interaction
+- `processor`: Optional parameter, workflow used for image processing
+- `config_path`: Optional parameter, path to the worker configuration file
+- `workers`: Optional parameter, list of Worker instances
+- `input_prompt`: Optional parameter, prompt message for user input (defaults to None)
+
+Note:
+1. Either `interactor` or `processor` must be provided
+2. At least one of `config_path` or `workers` must be provided, or both can be used
+3. If you need a prompt message after startup, you can either:
+   - Pass it through the `input_prompt` parameter
+   - Set it in the `self.input.read_input()` method of your first worker node
+
+## Input and Output
+- Input: Uses `AppInput`
+- Output: Uses `DefaultCallback`

docs/concepts/clients/devices/programmatic.md

@@ -0,0 +1,75 @@
+# ProgrammaticClient
+
+## Introduction
+`ProgrammaticClient` is a client tool designed for executing batch tasks.
+
+## Initialization Parameters
+- `processor`: Required parameter, the processor for handling tasks
+- `config_path`: Optional parameter, path to the worker configuration file
+- `workers`: Optional parameter, list of Worker instances
+
+Note: Either `config_path` or `workers` must be provided.
+
+## Execution Methods
+ProgrammaticClient provides two methods for executing batch tasks:
+
+### 1. start_batch_processor
+Parallel processing of multiple tasks:
+```python
+# Usage example
+workflow_input_list = []
+for i in range(3):
+    workflow_input_list.append({
+        "id": str(i), 
+        "file_path": f"/path/to/test{i}.png"
+    })
+programmatic_client.start_batch_processor(workflow_input_list=workflow_input_list)
+programmatic_client.stop_processor()
+```
+
+Features:
+- Supports multi-process parallel execution
+- Default of 5 processes per worker
+- Process count can be adjusted via the `concurrency` parameter in the worker configuration file
+
+### 2. start_processor_with_input
+Serial processing of individual tasks:
+```python
+# Usage example
+for i in range(3):
+    programmatic_client.start_processor_with_input(
+        workflow_input={"id": str(i), "file_path": f"/path/to/test{i}.png"}
+    )
+programmatic_client.stop_processor()
+```
+
+Features:
+- Executes one task at a time
+- Waits for the current task to complete before executing the next one
+
+## Parameter Passing
+To pass parameters during execution, you need to:
+1. Define the corresponding parameters in the worker's `_run` method
+2. Specify parameter sources when defining the task
+
+Example code:
+```python
+@registry.register_worker()
+class SimpleTest(BaseWorker):
+    def _run(self, id: str, file_path: str):
+        print("id:", id)
+        print("file_path:", file_path)
+        # do something
+
+# Define task
+task1 = simple_task(
+    task_def_name="SimpleTest",
+    task_reference_name="simple_test",
+    inputs={
+        "id": workflow.input("id"),
+        "file_path": workflow.input("file_path")
+    }
+)
+
+workflow >> task1
+```

docs/concepts/clients/devices/webpage.md

@@ -0,0 +1,24 @@
+# WebpageClient
+
+## Introduction
+`WebpageClient` is a web-based chat interface implemented with Gradio, designed for interactive communication.
+
+## Initialization Parameters
+- `interactor`: Optional parameter, workflow used for interaction
+- `processor`: Optional parameter, workflow used for image processing
+- `config_path`: Optional parameter, path to the worker configuration file
+- `workers`: Optional parameter, list of Worker instances
+
+Note:
+1. Either `interactor` or `processor` must be provided
+2. At least one of `config_path` or `workers` must be provided, or both can be used
+3. When using `interactor`:
+   - Default port: **7860**
+   - Access URL: `http://127.0.0.1:7860`
+4. When using `processor`:
+   - Default port: **7861**
+   - Access URL: `http://127.0.0.1:7861`
+
+## Input and Output
+- Input: Uses `AppInput`
+- Output: Uses `AppCallback`

docs/concepts/clients/client.md → docs/concepts/clients/input_and_callback.md

@@ -1,27 +1,4 @@
-# Client
-
-Currently, there are three clients: `DefaultClient`, `AppClient`, and `WebpageClient`.
-
-`DefaultClient` is the default client used for interacting with users via the command line. 
-- The parameters of `DefaultClient` include `interactor`, `processor`, `config_path`, `workers`, and `input_prompt`.
-- Among them, either `interactor` or `processor` must be chosen to be passed in. `interactor` is the workflow used for interaction, and `processor` is the workflow used for image processing.
-- At least one of `config_path` and `workers` must be passed in, or both can be passed. `config_path` is the path to the worker configuration file, and `workers` is a list of `Worker` instances.
-- `input_prompt` is the prompt message for user input, which defaults to None. If you need to provide a prompt message after startup, you need to pass it in. Alternatively, you can set `input_prompt` in the `self.input.read_input()` method of your first worker node.
-
-`AppClient` is used for interacting with users within an app.
-- The parameters of `AppClient` include `interactor`, `processor`, `config_path`, and `workers`.
-- Among them, either `interactor` or `processor` must be chosen to be passed in. `interactor` is the workflow used for interaction, and `processor` is the workflow used for image processing.
-- At least one of `config_path` and `workers` must be passed in, or both can be passed. `config_path` is the path to the worker configuration file, and `workers` is a list of `Worker` instances.
-
-`WebpageClient` is a web page chat window implemented with gradio, which can be used for interaction.
-- The parameters of `WebpageClient` include `interactor`, `processor`, `config_path`, and `workers`.
-- Among them, either `interactor` or `processor` must be chosen to be passed in.
-- `interactor` is the workflow used for interaction, with a default port of **7860** after startup, and the access address is `http://127.0.0.1:7860`.
-- `processor` is the workflow used for image processing, with a default port of **7861** after startup, and the access address is `http://127.0.0.1:7861`.
-- At least one of `config_path` and `workers` must be passed in, or both can be passed. `config_path` is the path to the worker configuration file, and `workers` is a list of `Worker` instances.
-
-
-The input for `DefaultClient` uses `AppInput`, and the output uses `DefaultCallback`. The input for `AppClient` uses `AppInput`, and the output uses `AppCallback`. The input for `WebpageClient` uses `AppInput`, and the output uses `AppCallback`.
+# Input and Callback
 
 When writing an agent worker, you don't need to worry about which one to use. Simply call `self.input.read_input()` and `self.callback.send_xxx()`. Depending on whether `DefaultClient` or `AppClient` or `WebpageClient` is instantiated, different input and output logic will be followed.
 

omagent-core/src/omagent_core/clients/devices/programmatic/client.py

@@ -70,7 +70,6 @@ def _process_workflow(self, workflow:ConductorWorkflow, workflow_input:dict):
             workflow_instance_id = workflow.start_workflow_with_input(workflow_input=workflow_input)
             while True:
                 status = workflow.get_workflow(workflow_id=workflow_instance_id).status
-                print("status:", status)
                 if status in terminal_status:
                     break
                 sleep(1)