[FEAT][CLI] [DOCS][CLI]

cache.txt

@@ -0,0 +1 @@
+logged_in

docs/mkdocs.yml

@@ -141,6 +141,7 @@ nav:
     - Onboarding: 
       - Installation: "swarms/install/install.md"
       - Quickstart: "swarms/install/quickstart.md"
+      - Swarms CLI: "swarms/cli/main.md"
     - Agents:
       # - Overview: "swarms/structs/index.md"
       # - Build Custom Agents: "swarms/structs/diy_your_own_agent.md"

docs/swarms/cli/main.md

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+# Swarms CLI Documentation
+
+The Swarms Command Line Interface (CLI) allows you to easily manage and run your Swarms of agents from the command line. This page will guide you through the installation process and provide a breakdown of the available commands.
+
+## Installation
+
+You can install the `swarms` package using `pip` or `poetry`.
+
+### Using pip
+
+```bash
+pip3 install -U swarms
+```
+
+### Using poetry
+
+```bash
+poetry add swarms
+```
+
+Once installed, you can run the Swarms CLI with the following command:
+
+```bash
+poetry run swarms help
+```
+
+## Swarms CLI - Help
+
+When running `swarms help`, you'll see the following output:
+
+```
+  _________                                     
+ /   _____/_  _  _______ _______  _____   ______
+ \_____  \ \/ \/ /\__  \_  __ \/     \ /  ___/
+ /        \     /  / __ \|  | \/  Y Y  \___ \ 
+/_______  / \/\_/  (____  /__|  |__|_|  /____  >
+        \/              \/            \/     \/ 
+
+
+
+    Swarms CLI - Help
+
+    Commands:
+    onboarding    : Starts the onboarding process
+    help          : Shows this help message
+    get-api-key   : Retrieves your API key from the platform
+    check-login   : Checks if you're logged in and starts the cache
+    read-docs     : Redirects you to swarms cloud documentation!
+    run-agents    : Run your Agents from your agents.yaml
+
+    For more details, visit: https://docs.swarms.world
+```
+
+### CLI Commands
+
+Below is a detailed explanation of the available commands:
+
+- **onboarding**  
+  Starts the onboarding process to help you set up your environment and configure your agents.
+
+  Usage:
+  ```bash
+  swarms onboarding
+  ```
+
+- **help**  
+  Displays the help message, including a list of available commands.
+
+  Usage:
+  ```bash
+  swarms help
+  ```
+
+- **get-api-key**  
+  Retrieves your API key from the platform, allowing your agents to communicate with the Swarms platform.
+
+  Usage:
+  ```bash
+  swarms get-api-key
+  ```
+
+- **check-login**  
+  Verifies if you are logged into the platform and starts the cache for storing your login session.
+
+  Usage:
+  ```bash
+  swarms check-login
+  ```
+
+- **read-docs**  
+  Redirects you to the official Swarms documentation on the web for further reading.
+
+  Usage:
+  ```bash
+  swarms read-docs
+  ```
+
+- **run-agents**  
+  Executes your agents from the `agents.yaml` configuration file, which defines the structure and behavior of your agents.
+
+  Usage:
+  ```bash
+  swarms run-agents
+  ```

examples/distributed/exec_on_cpu.py

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+import logging
+import os
+
+from clusterops import (
+    execute_with_cpu_cores,
+    list_available_cpus,
+)
+from swarm_models import OpenAIChat
+
+from swarms import Agent
+
+# Configure logging
+logging.basicConfig(level=logging.INFO)
+
+api_key = os.getenv("OPENAI_API_KEY")
+
+# Create an instance of the OpenAIChat class
+model = OpenAIChat(
+    openai_api_key=api_key,
+    model_name="gpt-4o-mini",
+    temperature=0.1,
+    max_tokens=2000,
+)
+
+
+# Function for the director agent
+def director_task(task: str):
+    logging.info(f"Running Director agent for task: {task}")
+    director = Agent(
+        agent_name="Director",
+        system_prompt="Directs the tasks for the workers",
+        llm=model,
+        max_loops=1,
+        dashboard=False,
+        streaming_on=True,
+        verbose=True,
+        stopping_token="<DONE>",
+        state_save_file_type="json",
+        saved_state_path="director.json",
+    )
+    return director.run(task)
+
+
+# Function for worker 1
+def worker1_task(task: str):
+    logging.info(f"Running Worker1 agent for task: {task}")
+    worker1 = Agent(
+        agent_name="Worker1",
+        system_prompt="Generates a transcript for a youtube video on what swarms are",
+        llm=model,
+        max_loops=1,
+        dashboard=False,
+        streaming_on=True,
+        verbose=True,
+        stopping_token="<DONE>",
+        state_save_file_type="json",
+        saved_state_path="worker1.json",
+    )
+    return worker1.run(task)
+
+
+# Function for worker 2
+def worker2_task(task: str):
+    logging.info(f"Running Worker2 agent for task: {task}")
+    worker2 = Agent(
+        agent_name="Worker2",
+        system_prompt="Summarizes the transcript generated by Worker1",
+        llm=model,
+        max_loops=1,
+        dashboard=False,
+        streaming_on=True,
+        verbose=True,
+        stopping_token="<DONE>",
+        state_save_file_type="json",
+        saved_state_path="worker2.json",
+    )
+    return worker2.run(task)
+
+
+# CPU Core Assignment Example
+def assign_tasks_to_cpus():
+    # List available CPUs
+    cpus = list_available_cpus()
+    logging.info(f"Available CPUs: {cpus}")
+
+    # Example: Assign Director task to 1 CPU core
+    logging.info("Executing Director task using 1 CPU core")
+    execute_with_cpu_cores(
+        1, director_task, "Direct the creation of swarm video format"
+    )
+
+    # Example: Assign Worker1 task to 2 CPU cores
+    logging.info("Executing Worker1 task using 2 CPU cores")
+    execute_with_cpu_cores(
+        2,
+        worker1_task,
+        "Generate transcript for youtube video on swarms",
+    )
+
+    # Example: Assign Worker2 task to 2 CPU cores
+    logging.info("Executing Worker2 task using 2 CPU cores")
+    execute_with_cpu_cores(
+        2,
+        worker2_task,
+        "Summarize the transcript generated by Worker1",
+    )
+
+    print("finished")
+
+
+if __name__ == "__main__":
+    logging.info(
+        "Starting the CPU-based task assignment for agents..."
+    )
+    assign_tasks_to_cpus()