schemq

neo_sapiens/hass_schema.py

@@ -0,0 +1,63 @@
+from pydantic import BaseModel, Field
+from typing import List
+from swarms.utils.json_utils import base_model_to_json
+
+class AgentSchema(BaseModel):
+    name: str = Field(
+        ...,
+        title="Name of the agent",
+    )
+    system_prompt: str = Field(
+        ...,
+        title = "System prompt for the agent",
+    )
+
+
+class HassSchema(BaseModel):
+    plan: List[str] = Field(
+        ...,
+        title="Plan to solve the input problem",
+    )
+    number_of_agents: int = Field(
+        ...,
+        title="Number of agents to use for the problem",
+    )
+
+    agents: List[AgentSchema] = Field(
+        ...,
+        title="List of agents to use for the problem",
+    )
+
+
+
+json = HassSchema.model_json_schema()
+json = base_model_to_json(HassSchema)
+# print(json)
+
+
+
+def parse_hass_schema(data: str) -> tuple:
+    parsed_data = eval(data)
+    hass_schema = HassSchema(**parsed_data)
+    return hass_schema.plan, hass_schema.number_of_agents, hass_schema.agents
+
+# Example usage
+data = '''
+{
+    "plan": ["Step 1", "Step 2", "Step 3"],
+    "number_of_agents": 5,
+    "agents": [
+        {
+            "name": "Agent 1",
+            "system_prompt": "Prompt 1"
+        },
+        {
+            "name": "Agent 2",
+            "system_prompt": "Prompt 2"
+        }
+    ]
+}
+'''
+
+parsed_schema = parse_hass_schema(data)
+print(parsed_schema)

neo_sapiens/main.py

@@ -1 +1,101 @@
+from swarms import Agent, Anthropic, tool, OpenAIChat
+import subprocess
 
+# Model
+llm = OpenAIChat()
+
+# Tools
+@tool
+def terminal(
+    code: str,
+):
+    """
+    Run code in the terminal.
+
+    Args:
+        code (str): The code to run in the terminal.
+
+    Returns:
+        str: The output of the code.
+    """
+    out = subprocess.run(
+        code, shell=True, capture_output=True, text=True
+    ).stdout
+    return str(out)
+
+
+@tool
+def browser(query: str):
+    """
+    Search the query in the browser with the `browser` tool.
+
+    Args:
+        query (str): The query to search in the browser.
+
+    Returns:
+        str: The search results.
+    """
+    import webbrowser
+
+    url = f"https://www.google.com/search?q={query}"
+    webbrowser.open(url)
+    return f"Searching for {query} in the browser."
+
+@tool
+def create_file(file_path: str, content: str):
+    """
+    Create a file using the file editor tool.
+
+    Args:
+        file_path (str): The path to the file.
+        content (str): The content to write to the file.
+
+    Returns:
+        str: The result of the file creation operation.
+    """
+    with open(file_path, "w") as file:
+        file.write(content)
+    return f"File {file_path} created successfully."
+
+@tool
+def file_editor(file_path: str, mode: str, content: str):
+    """
+    Edit a file using the file editor tool.
+
+    Args:
+        file_path (str): The path to the file.
+        mode (str): The mode to open the file in.
+        content (str): The content to write to the file.
+
+    Returns:
+        str: The result of the file editing operation.
+    """
+    with open(file_path, mode) as file:
+        file.write(content)
+    return f"File {file_path} edited successfully."
+
+
+# Agent
+agent = Agent(
+    agent_name="Neo Sapien orchestrator",
+    system_prompt=(
+        "Autonomous agent that can interact with humans and other"
+        " agents. Be Helpful and Kind. Use the tools provided to"
+        " assist the user. Return all code in markdown format."
+    ),
+    llm=llm,
+    max_loops="auto",
+    autosave=True,
+    dashboard=False,
+    streaming_on=True,
+    verbose=True,
+    stopping_token="<DONE>",
+    interactive=True,
+    tools=[terminal, browser, file_editor, create_file],
+    code_interpreter=True,
+    # streaming=True,
+)
+
+# Run the agent
+out = agent("Create a new file for a plan to take over the world.")
+print(out)