[PLAYRGROUNDFIX]

docs/mkdocs.yml

@@ -131,8 +131,6 @@ nav:
     - Swarm Ecosystem: "swarms/ecosystem.md"
   - Framework:
     - Overview: "swarms/framework/index.md"
-    - Contributing: 
-      - Tests: "swarms/framework/test.md"
     - Models:
       - Overview: "swarms/models/index.md"
       - How to Create A Custom Language Model: "swarms/models/custom_model.md"
@@ -148,6 +146,8 @@ nav:
       - Overview: "swarms/structs/multi_agent_orchestration.md"
       - Swarm Architectures: "swarms/concept/swarm_architectures.md"
       - Workflows: "swarms/structs/workflows.md"
+    - Contributing: 
+      - Tests: "swarms/framework/test.md"
   - Reference:
     - Overview: "swarms/structs/index.md"
     - Models:

playground/agents/mm_agent_example.py

@@ -1,17 +0,0 @@
-from swarms.agents import MultiModalAgent
-
-load_dict = {"ImageCaptioning": "cuda"}
-
-node = MultiModalAgent(load_dict)
-
-text = node.run_text("What is your name? Generate a picture of yourself")
-
-img = node.run_img("/image1", "What is this image about?")
-
-chat = node.chat(
-    (
-        "What is your name? Generate a picture of yourself. What is"
-        " this image about?"
-    ),
-    streaming=True,
-)

playground/agents/worker_example.py

@@ -1,32 +0,0 @@
-# Importing necessary modules
-import os
-
-from dotenv import load_dotenv
-
-from swarms import OpenAIChat
-from swarms.agents.worker_agent import Worker
-
-# Loading environment variables from .env file
-load_dotenv()
-
-# Retrieving the OpenAI API key from environment variables
-api_key = os.getenv("OPENAI_API_KEY")
-
-# Creating a Worker instance
-worker = Worker(
-    name="My Worker",
-    role="Worker",
-    human_in_the_loop=False,
-    tools=[],
-    temperature=0.5,
-    llm=OpenAIChat(openai_api_key=api_key),
-    verbose=True,
-)
-
-# Running the worker with a prompt
-out = worker.run(
-    "Hello, how are you? Create an image of how your are doing!"
-)
-
-# Printing the output
-print(out)

tests/structs/test_multi_agent_collab.py

@@ -57,6 +57,7 @@ worker2 = Agent(
 # Create a list of agents
 agents = [director, worker1, worker2]
 
+
 @pytest.fixture
 def collaboration():
     return MultiAgentCollaboration(agents)