[CLEANUP]

README.md

@@ -72,6 +72,23 @@ Refer to our documentation for production grade implementation details.
 $ pip3 install -U swarms
 ```
 
+
+## Onboarding
+
+Now that you have downloaded swarms with `pip3 install -U swarms`, we get access to the `CLI`. Get Onboarded with CLI Now with:
+
+```bash
+swarms onboarding
+```
+
+You can also run this command for help:
+
+```bash
+swarms help
+```
+
+For more documentation on the CLI [CLICK HERE](https://docs.swarms.world/en/latest/swarms/cli/main/)
+
 ---
 
 # Usage Examples 🤖

agents.yaml

@@ -1,7 +1,6 @@
 agents:
   - agent_name: "Financial-Analysis-Agent"
     model:
-      openai_api_key: "your_openai_api_key"
       model_name: "gpt-4o-mini"
       temperature: 0.1
       max_tokens: 2000
@@ -17,10 +16,11 @@ agents:
     context_length: 200000
     return_step_meta: false
     output_type: "str"  # Can be "json" or any other format
+    task: "What are the benefits of working with BlackRock"
+
 
   - agent_name: "Stock-Analysis-Agent"
     model:
-      openai_api_key: "your_openai_api_key"
       model_name: "gpt-4o-mini"
       temperature: 0.2
       max_tokens: 1500
@@ -36,3 +36,4 @@ agents:
     context_length: 150000
     return_step_meta: true
     output_type: "str"
+    task: "What is a roth IRA"

agents_from_yaml_example.py

@@ -1,24 +1,19 @@
 from loguru import logger
 from dotenv import load_dotenv
-from swarms import create_agents_from_yaml
+from swarms.agents.create_agents_from_yaml import create_agents_from_yaml
 
 # Load environment variables
 load_dotenv()
 
 # Path to your YAML file
-yaml_file = "agents_config.yaml"
+yaml_file = "agents.yaml"
 
 try:
     # Create agents and run tasks (using 'both' to return agents and task results)
-    agents, task_results = create_agents_from_yaml(
-        yaml_file, return_type="both"
+    task_results = create_agents_from_yaml(
+        yaml_file, return_type="tasks"
     )
-
-    # Print the results of the tasks
-    for result in task_results:
-        print(
-            f"Agent: {result['agent_name']} | Task: {result['task']} | Output: {result.get('output', 'Error encountered')}"
-        )
-
+    
+    logger.info(f"Results from agents: {task_results}")
 except Exception as e:
     logger.error(f"An error occurred: {e}")

docs/mkdocs.yml

@@ -147,8 +147,8 @@ nav:
       # - Build Custom Agents: "swarms/structs/diy_your_own_agent.md"
       - Agent Architecture: "swarms/framework/agents_explained.md"
       - Complete Agent API: "swarms/structs/agent.md"
-      - Integrating External Agents from Griptape, Langchain, etc: "swarms/agents/external_party_agents.md"
       - Create and Run Agents from YAML: "swarms/agents/create_agents_yaml.md"
+      - Integrating External Agents from Griptape, Langchain, etc: "swarms/agents/external_party_agents.md"
       - Tools:
         - Overview: "swarms/tools/main.md"
         - What are tools?: "swarms/tools/build_tool.md"

docs/swarms/agents/create_agents_yaml.md

@@ -1,4 +1,4 @@
-# `create_agents_from_yaml`
+# Building Agents from a YAML File
 
 The `create_agents_from_yaml` function enables the dynamic creation and execution of agents based on configurations defined in a YAML file. This function is designed to support enterprise use-cases, offering flexibility, reliability, and scalability for various agent-based workflows.
 
@@ -63,7 +63,7 @@ agents:
       model_name: "gpt-4o-mini"
       temperature: 0.1
       max_tokens: 2000
-    system_prompt: "financial_agent_sys_prompt"
+    system_prompt: "Your full system prompt here"
     max_loops: 1
     autosave: true
     dashboard: false
@@ -82,7 +82,7 @@ agents:
       model_name: "gpt-4o-mini"
       temperature: 0.2
       max_tokens: 1500
-    system_prompt: "stock_agent_sys_prompt"
+    system_prompt: "Your full system prompt here"
     max_loops: 2
     autosave: true
     dashboard: false

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "5.7.1"
+version = "5.7.7"
 description = "Swarms - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <kye@apac.ai>"]

swarms/agents/create_agents_from_yaml.py

@@ -58,16 +58,7 @@ def create_agents_from_yaml(
         logger.info(f"Creating agent: {agent_config['agent_name']}")
 
         # Get the OpenAI API key from environment or YAML config
-        api_key = os.getenv("OPENAI_API_KEY") or agent_config[
-            "model"
-        ].get("openai_api_key")
-        if not api_key:
-            logger.error(
-                f"API key is missing for agent: {agent_config['agent_name']}"
-            )
-            raise ValueError(
-                f"API key is missing for agent: {agent_config['agent_name']}"
-            )
+        api_key = os.getenv("OPENAI_API_KEY") or agent_config["model"]["openai_api_key"]
 
         # Create an instance of OpenAIChat model
         model = OpenAIChat(
@@ -87,31 +78,11 @@ def create_agents_from_yaml(
             raise ValueError(
                 f"System prompt is missing for agent: {agent_config['agent_name']}"
             )
-
-        # Dynamically choose the system prompt based on the agent config
-        try:
-            system_prompt = globals().get(
-                agent_config["system_prompt"]
-            )
-            if not system_prompt:
-                logger.error(
-                    f"System prompt {agent_config['system_prompt']} not found."
-                )
-                raise ValueError(
-                    f"System prompt {agent_config['system_prompt']} not found."
-                )
-        except KeyError:
-            logger.error(
-                f"System prompt {agent_config['system_prompt']} is not valid."
-            )
-            raise ValueError(
-                f"System prompt {agent_config['system_prompt']} is not valid."
-            )
-
+        
         # Initialize the agent using the configuration
         agent = Agent(
             agent_name=agent_config["agent_name"],
-            system_prompt=system_prompt,
+            system_prompt=agent_config["system_prompt"],
             llm=model,
             max_loops=agent_config.get("max_loops", 1),
             autosave=agent_config.get("autosave", True),
@@ -178,19 +149,3 @@ def create_agents_from_yaml(
         logger.error(f"Invalid return_type: {return_type}")
         raise ValueError(f"Invalid return_type: {return_type}")
 
-
-# # Usage example
-# yaml_file = 'agents_config.yaml'
-
-# try:
-#     # Auto-create agents from the YAML file and return both agents and task results
-#     agents, task_results = create_agents_from_yaml(yaml_file, return_type="tasks")
-
-#     # Example: Print task results
-#     for result in task_results:
-#         print(f"Agent: {result['agent_name']} | Task: {result['task']} | Output: {result.get('output', 'Error encountered')}")
-
-# except FileNotFoundError as e:
-#     logger.error(f"Error: {e}")
-# except ValueError as e:
-#     logger.error(f"Error: {e}")

swarms/cli/main.py

@@ -41,7 +41,7 @@ def show_help():
     [bold white]get-api-key[/bold white]   : Retrieves your API key from the platform
     [bold white]check-login[/bold white]   : Checks if you're logged in and starts the cache
     [bold white]read-docs[/bold white]     : Redirects you to swarms cloud documentation!
-    [bold white]run-agents[/bold white]    : Run your Agents from your agents.yaml
+    [bold white]run-agents[/bold white]    : Run your Agents from your specified yaml file. Specify the yaml file with path the `--yaml-file` arg. Example: `--yaml-file agents.yaml`
 
     For more details, visit: https://docs.swarms.world
     """
@@ -107,12 +107,21 @@ def main():
     # Adding arguments for different commands
     parser.add_argument(
         "command",
-        choices=["onboarding", "help", "get-api-key", "check-login"],
+        choices=["onboarding", "help", "get-api-key", "check-login", "run-agents"],
         help="Command to run",
     )
+    parser.add_argument(
+        "--yaml-file",
+        type=str,
+        default="agents.yaml",
+        help="Specify the YAML file for running agents",
+    )
 
     args = parser.parse_args()
 
+    # Debug print to verify the command
+    print(f"Command received: {args.command}")
+
     show_ascii_art()
 
     # Determine which command to run
@@ -124,17 +133,14 @@ def main():
         get_api_key()
     elif args.command == "check-login":
         check_login()
-    elif args.command == "read-docs":
-        redirect_to_docs()
     elif args.command == "run-agents":
         create_agents_from_yaml(
-            yaml_file="agents.yaml", return_type="tasks"
+            yaml_file=args.yaml_file, return_type="tasks"
         )
     else:
         console.print(
             "[bold red]Unknown command! Type 'help' for usage.[/bold red]"
         )
 
-
 if __name__ == "__main__":
     main()

swarms/cli/onboarding_process.py

@@ -81,14 +81,14 @@ class OnboardingProcess:
                 combined_data = {**self.user_data, **self.system_data}
                 log_agent_data(combined_data)
                 # threading.Thread(target=log_agent_data(combined_data)).start()
-                with open(self.auto_save_path, "w") as f:
-                    json.dump(combined_data, f, indent=4)
-                    # logger.info(
-                    #     "User and system data successfully saved to {}",
-                    #     self.auto_save_path,
-                    # )
-                with open(self.cache_save_path, "w") as f:
-                    json.dump(combined_data, f, indent=4)
+                # with open(self.auto_save_path, "w") as f:
+                #     json.dump(combined_data, f, indent=4)
+                #     # logger.info(
+                #     #     "User and system data successfully saved to {}",
+                #     #     self.auto_save_path,
+                #     # )
+                # with open(self.cache_save_path, "w") as f:
+                #     json.dump(combined_data, f, indent=4)
                     # logger.info(
                     #     "User and system data successfully cached in {}",
                     #     self.cache_save_path,
@@ -138,6 +138,8 @@ class OnboardingProcess:
                 )
             self.user_data[key] = response.strip()
             self.save_data()
+            
+            return response
         except ValueError as e:
             logger.warning(e)
             self.ask_input(prompt, key)
@@ -150,7 +152,7 @@ class OnboardingProcess:
     def collect_user_info(self) -> None:
         """
         Initiates the onboarding process by collecting the user's full name, first name, email,
-        Swarms API key, and system data.
+        Swarms API key, and system data. Additionally, it reminds the user to set their WORKSPACE_DIR environment variable.
         """
         logger.info("Initiating swarms cloud onboarding process...")
         self.ask_input(
@@ -168,6 +170,13 @@ class OnboardingProcess:
             "Enter your Swarms API key (or type 'quit' to exit): Get this in your swarms dashboard: https://swarms.world/platform/api-keys ",
             "swarms_api_key",
         )
+        workspace = self.ask_input(
+            "Enter your WORKSPACE_DIR: This is where logs, errors, and agent configurations will be stored (or type 'quit' to exit). Remember to set this as an environment variable: https://docs.swarms.world/en/latest/swarms/install/quickstart/ || ",
+            "workspace_dir",
+        )
+        os.environ["WORKSPACE_DIR"] = workspace
+        logger.info("Important: Please ensure you have set your WORKSPACE_DIR environment variable as per the instructions provided.")
+        logger.info("Additionally, remember to add your API keys for your respective models in your .env file.")
         logger.success("Onboarding process completed successfully!")
 
     def run(self) -> None: