update production demo with endpoints

Author: aboutphilippe

production_demo/README.md

@@ -1,6 +1,6 @@
 # Restack AI - Production Example
 
-This repository contains a simple example project to help you scale with the Restack AI.
+This repository contains a simple example project to help you scale with Restack AI.
 It demonstrates how to scale reliably to millions of workflows on a local machine with a local LLM provider.
 
 ## Walkthrough video
@@ -60,85 +60,93 @@ And for each child workflow, for each step you can see how long the function sta
 
 ## Prerequisites
 
-- Python 3.8 or higher
+- Python 3.10 or higher
 - Poetry (for dependency management)
 - Docker (for running the Restack services)
 - Local LLM provider (we use LMStudio and a Meta Llama 3.1 8B Instruct 4bit model in this example)
 
-## Usage
+## Start LM stduio for local LLM provider
 
-0. Start LM Studio and start local server with Meta Llama 3.1 8B Instruct 4bit model
+Start local server with Meta Llama 3.1 8B Instruct 4bit model
 
 https://lmstudio.ai
 
-1. Run Restack local engine with Docker:
+## Prerequisites
 
-   ```bash
-   docker run -d --pull always --name restack -p 5233:5233 -p 6233:6233 -p 7233:7233 ghcr.io/restackio/restack:main
-   ```
+- Docker (for running Restack)
+- Python 3.10 or higher
 
-2. Open the web UI to see the workflows:
+## Start Restack
 
-   ```bash
-   http://localhost:5233
-   ```
+To start the Restack, use the following Docker command:
 
-3. Clone this repository:
+```bash
+docker run -d --pull always --name restack -p 5233:5233 -p 6233:6233 -p 7233:7233 ghcr.io/restackio/restack:main
+```
 
-   ```bash
-   git clone https://github.com/restackio/examples-python
-   cd examples-python/examples/production_demo
-   ```
+## Start python shell
 
-4. Install dependencies using Poetry:
+```bash
+poetry env use 3.10 && poetry shell
+```
 
-   ```bash
-   poetry env use 3.12
-   ```
+## Install dependencies
+
+```bash
+poetry install
+```
+
+```bash
+poetry env info # Optional: copy the interpreter path to use in your IDE (e.g. Cursor, VSCode, etc.)
+```
+
+```bash
+poetry run dev
+```
 
-   ```bash
-   poetry shell
-   ```
+## Run workflows
 
-   ```bash
-   poetry install
-   ```
+### from UI
 
-   ```bash
-   poetry env info # Optional: copy the interpreter path to use in your IDE (e.g. Cursor, VSCode, etc.)
-   ```
+You can run workflows from the UI by clicking the "Run" button.
 
-5. Run the services:
+![Run workflows from UI](./ui-endpoints.png)
 
-   ```bash
-   poetry run dev
-   ```
+### from API
 
-   This will start the Restack service with the defined workflows and functions.
+You can run one workflow from the API by using the generated endpoint:
 
-6. In a new terminal, schedule the workflow:
+`POST http://localhost:6233/api/workflows/ChildWorkflow`
 
-   ```bash
-   poetry shell
-   ```
+or multiple workflows by using the generated endpoint:
 
-   ```bash
-   poetry run workflow
-   ```
+`POST http://localhost:6233/api/workflows/ExampleWorkflow`
 
-   This will schedule the ExampleWorkflow` and print the result.
+### from any client
 
-7. Optionally, schedule the workflow to run on a interval:
+You can run workflows with any client connected to Restack, for example:
+
+```bash
+poetry run schedule
+```
+
+executes `schedule_workflow.py` which will connect to Restack and execute the `ChildWorkflow` workflow.
+
+```bash
+poetry run scale
+```
+
+executes `schedule_scale.py` which will connect to Restack and execute the `ExampleWorkflow` workflow.
+
+```bash
+poetry run interval
+```
 
-   ```bash
-   poetry run interval
-   ```
+executes `schedule_interval.py` which will connect to Restack and execute the `ChildWorkflow` workflow every second.
 
-8. Optionally, schedule a parent workflow to run 50 child workflows all at once:
+## Deploy on Restack Cloud
 
-   ```bash
-   poetry run scale
-   ```
+To deploy the application on Restack, you can create an account at [https://console.restack.io](https://console.restack.io)
 
 ## Project Structure
 
@@ -149,7 +157,7 @@ https://lmstudio.ai
   - `services.py`: Sets up and runs the Restack services
 - `schedule_workflow.py`: Example script to schedule and run a workflow
 - `schedule_interval.py`: Example script to schedule and a workflow every second
-- `schedule_scale.py`: Example script to schedule and run 100 workflows at once
+- `schedule_scale.py`: Example script to schedule and run 50 workflows at once
 
 # Deployment
 

production_demo/pyproject.toml

@@ -11,9 +11,10 @@ packages = [{include = "src"}]
 
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
-restack-ai = "^0.0.48"
+restack-ai = "^0.0.52"
 watchfiles = "^1.0.0"
 openai = "^1.57.2"
+pydantic = "^2.10.5"
 
 [tool.poetry.dev-dependencies]
 pytest = "6.2"  # Optional: Add if you want to include tests in your example

production_demo/schedule_scale.py

@@ -2,6 +2,8 @@
 import time
 from restack_ai import Restack
 
+from src.workflows.workflow import ExampleWorkflowInput
+
 async def main():
 
     client = Restack()
@@ -10,6 +12,7 @@ async def main():
     await client.schedule_workflow(
         workflow_name="ExampleWorkflow",
         workflow_id=workflow_id,
+        input=ExampleWorkflowInput(amount=50)
     )
 
     exit(0)

production_demo/src/functions/evaluate.py

@@ -1,8 +1,12 @@
 from restack_ai.function import function, FunctionFailure, log
 from openai import OpenAI
+from pydantic import BaseModel
+
+class EvaluateInput(BaseModel):
+    generated_text: str
 
 @function.defn()
-async def llm_evaluate(generated_text: str) -> str:
+async def llm_evaluate(input: EvaluateInput) -> str:
     try:
         client = OpenAI(base_url="http://192.168.4.142:1234/v1/",api_key="llmstudio")
     except Exception as e:
@@ -12,7 +16,7 @@ async def llm_evaluate(generated_text: str) -> str:
     prompt = (
         f"Evaluate the following joke for humor, creativity, and originality. "
         f"Provide a score out of 10 for each category for your score.\n\n"
-        f"Joke: {generated_text}\n\n"
+        f"Joke: {input.generated_text}\n\n"
         f"Response format:\n"
         f"Humor: [score]/10"
         f"Creativity: [score]/10"

production_demo/src/functions/function.py

@@ -2,8 +2,13 @@
 
 tries = 0
 
+from pydantic import BaseModel
+
+class ExampleFunctionInput(BaseModel):
+    name: str
+
 @function.defn()
-async def example_function(input: str) -> str:
+async def example_function(input: ExampleFunctionInput) -> str:
     try:
         global tries
 
@@ -12,7 +17,7 @@ async def example_function(input: str) -> str:
             raise FunctionFailure(message="Simulated failure", non_retryable=False)
 
         log.info("example function started", input=input)
-        return f"Hello, {input}!"
+        return f"Hello, {input.name}!"
     except Exception as e:
         log.error("example function failed", error=e)
         raise e

production_demo/src/functions/generate.py

@@ -1,8 +1,13 @@
 from restack_ai.function import function, FunctionFailure, log
 from openai import OpenAI
 
+from pydantic import BaseModel
+
+class GenerateInput(BaseModel):
+    prompt: str
+
 @function.defn()
-async def llm_generate(prompt: str) -> str:
+async def llm_generate(input: GenerateInput) -> str:
 
     try:
         client = OpenAI(base_url="http://192.168.4.142:1234/v1/",api_key="llmstudio")
@@ -16,7 +21,7 @@ async def llm_generate(prompt: str) -> str:
             messages=[
                 {
                     "role": "user",
-                    "content": prompt
+                    "content": input.prompt
                 }
             ],
             temperature=0.5,

production_demo/src/services.py

@@ -10,7 +10,7 @@
 from src.functions.evaluate import llm_evaluate
 
 from src.workflows.workflow import ExampleWorkflow, ChildWorkflow
-
+import webbrowser
 
 
 async def main():
@@ -43,5 +43,6 @@ def run_services():
 def watch_services():
     watch_path = os.getcwd()
     print(f"Watching {watch_path} and its subdirectories for changes...")
+    webbrowser.open("http://localhost:5233")
     run_process(watch_path, recursive=True, target=run_services)
 

production_demo/src/workflows/child.py

@@ -1,18 +1,21 @@
 from datetime import timedelta
-
+from pydantic import BaseModel, Field
 from restack_ai.workflow import workflow, import_functions, log
 
 with import_functions():
     from src.functions.function import example_function
     from src.functions.generate import llm_generate
     from src.functions.evaluate import llm_evaluate
 
+class ChildWorkflowInput(BaseModel):
+    name: str = Field(default='John Doe')
+
 @workflow.defn()
 class ChildWorkflow:
     @workflow.run
-    async def run(self):
+    async def run(self, input: ChildWorkflowInput):
         log.info("ChildWorkflow started")
-        await workflow.step(example_function, input="first", start_to_close_timeout=timedelta(minutes=2))
+        await workflow.step(example_function, input=input, start_to_close_timeout=timedelta(minutes=2))
 
         await workflow.sleep(1)
 

production_demo/src/workflows/workflow.py

@@ -1,25 +1,29 @@
 import asyncio
 from datetime import timedelta
-
+from pydantic import BaseModel, Field
 from restack_ai.workflow import workflow, log, workflow_info, import_functions
-from .child import ChildWorkflow
+from .child import ChildWorkflow, ChildWorkflowInput
 
 with import_functions():
-    from src.functions.generate import llm_generate
+    from src.functions.generate import llm_generate 
+
+class ExampleWorkflowInput(BaseModel):
+    amount: int = Field(default=50)
 
 @workflow.defn()
 class ExampleWorkflow:
     @workflow.run
-    async def run(self):
+    async def run(self, input: ExampleWorkflowInput):
         # use the parent run id to create child workflow ids
         parent_workflow_id = workflow_info().workflow_id
 
         tasks = []
-        for i in range(50):
+        for i in range(input.amount):
             log.info(f"Queue ChildWorkflow {i+1} for execution")
             task = workflow.child_execute(
                 ChildWorkflow, 
-                workflow_id=f"{parent_workflow_id}-child-execute-{i+1}"
+                workflow_id=f"{parent_workflow_id}-child-execute-{i+1}",
+                input=ChildWorkflowInput(name=f"child workflow {i+1}")
             )
             tasks.append(task)