[FEAT][AgentRearrange][CLEANUP]

.github/workflows/cron_job_tests.yml

@@ -0,0 +1,27 @@
+name: Run pytest
+
+on:
+  schedule:
+    # This will run the job every day at a random minute past the hour
+    - cron:  '0 0 * * *'
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+    steps:
+    - name: Check out code
+      uses: actions/checkout@v4
+
+    - name: Set up Python
+      uses: actions/setup-python@v4
+      with:
+        python-version: '3.9'
+
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        pip install pytest
+        pip install swarms
+
+    - name: Run tests
+      run: pytest

.gitignore

@@ -12,6 +12,7 @@ static/generated
 runs
 chroma
 Unit Testing Agent_state.json
+Devin_state.json
 swarms/__pycache__
 artifacts
 venv

devin.py

@@ -0,0 +1,77 @@
+"""
+Plan -> act in a loop until observation is met
+
+
+# Tools
+- Terminal
+- Text Editor
+- Browser
+"""
+from swarms import Agent, OpenAIChat, tool
+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.
+
+    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."
+
+
+# Agent
+agent = Agent(
+    agent_name="Devin",
+    system_prompt=(
+        "Autonomous agent that can interact with humans and other"
+        " agents. Be Helpful and Kind. Use the tools provided to"
+        " assist the user."
+    ),
+    llm=llm,
+    max_loops=4,
+    autosave=True,
+    dashboard=False,
+    streaming_on=True,
+    verbose=True,
+    stopping_token="<DONE>",
+    interactive=True,
+    tools=[terminal, browser],
+    # streaming=True,
+)
+
+# Run the agent
+out = agent("What is the weather today in palo alto?")
+print(out)

pyproject.toml

@@ -5,7 +5,7 @@ build-backend = "poetry.core.masonry.api"
 
 [tool.poetry]
 name = "swarms"
-version = "4.7.1"
+version = "4.7.3"
 description = "Swarms - Pytorch"
 license = "MIT"
 authors = ["Kye Gomez <[email protected]>"]

swarms/__init__.py

@@ -1,10 +1,6 @@
-import os
-
 from swarms.telemetry.bootup import bootup  # noqa: E402, F403
 from swarms.telemetry.sentry_active import activate_sentry
 
-os.environ["WANDB_SILENT"] = "true"
-
 bootup()
 activate_sentry()
 

swarms/models/__init__.py

@@ -34,7 +34,6 @@
 )
 from swarms.models.qwen import QwenVLMultiModal  # noqa: E402
 
-from swarms.models.sam_supervision import SegmentAnythingMarkGenerator
 from swarms.models.sampling_params import SamplingParams, SamplingType
 from swarms.models.together import TogetherLLM  # noqa: E402
 from swarms.models.types import (  # noqa: E402
@@ -74,7 +73,6 @@
     "Replicate",
     "SamplingParams",
     "SamplingType",
-    "SegmentAnythingMarkGenerator",
     "TextModality",
     "TogetherLLM",
     "Vilt",

swarms/structs/__init__.py

@@ -78,6 +78,7 @@
     find_token_in_text,
     parse_tasks,
 )
+from swarms.structs.agent_rearrange import AgentRearrange
 
 
 __all__ = [
@@ -147,4 +148,5 @@
     "find_agent_by_id",
     "find_token_in_text",
     "parse_tasks",
+    "AgentRearrange",
 ]

rearrange_agent_example.py → swarms/structs/agent_rearrange.py

@@ -1,9 +1,10 @@
 import logging
 from collections import defaultdict
 from typing import Callable, Sequence
-from swarms import Agent, Anthropic
+from swarms.structs.agent import Agent
 from swarms.structs.base_swarm import BaseSwarm
 
+
 # Assuming the existence of an appropriate Agent class and logger setup
 class AgentRearrange(BaseSwarm):
     def __init__(
@@ -12,6 +13,8 @@ def __init__(
         verbose: bool = False,
         custom_prompt: str = None,
         callbacks: Sequence[Callable] = None,
+        *args,
+        **kwargs,
     ):
         super().__init__()
         if not all(isinstance(agent, Agent) for agent in agents):
@@ -159,76 +162,76 @@ def __call__(
         return results
 
 
-## Initialize the workflow
-agent = Agent(
-    agent_name="t",
-    agent_description=(
-        "Generate a transcript for a youtube video on what swarms"
-        " are!"
-    ),
-    system_prompt=(
-        "Generate a transcript for a youtube video on what swarms"
-        " are!"
-    ),
-    llm=Anthropic(),
-    max_loops=1,
-    autosave=True,
-    dashboard=False,
-    streaming_on=True,
-    verbose=True,
-    stopping_token="<DONE>",
-)
-
-agent2 = Agent(
-    agent_name="t1",
-    agent_description=(
-        "Generate a transcript for a youtube video on what swarms"
-        " are!"
-    ),
-    llm=Anthropic(),
-    max_loops=1,
-    system_prompt="Summarize the transcript",
-    autosave=True,
-    dashboard=False,
-    streaming_on=True,
-    verbose=True,
-    stopping_token="<DONE>",
-)
-
-agent3 = Agent(
-    agent_name="t2",
-    agent_description=(
-        "Generate a transcript for a youtube video on what swarms"
-        " are!"
-    ),
-    llm=Anthropic(),
-    max_loops=1,
-    system_prompt="Finalize the transcript",
-    autosave=True,
-    dashboard=False,
-    streaming_on=True,
-    verbose=True,
-    stopping_token="<DONE>",
-)
-
-
-# Rearrange the agents
-rearrange = AgentRearrange(
-    agents=[agent, agent2, agent3],
-    verbose=True,
-    # custom_prompt="Summarize the transcript",
-)
-
-# Run the workflow on a task
-results = rearrange(
-    # pattern="t -> t1, t2 -> t2",
-    pattern="t -> t1 -> t2",
-    default_task=(
-        "Generate a transcript for a YouTube video on what swarms"
-        " are!"
-    ),
-    t="Generate a transcript for a YouTube video on what swarms are!",
-    # t2="Summarize the transcript",
-    # t3="Finalize the transcript",
-)
-# print(results)
+# ## Initialize the workflow
+# agent = Agent(
+#     agent_name="t",
+#     agent_description=(
+#         "Generate a transcript for a youtube video on what swarms"
+#         " are!"
+#     ),
+#     system_prompt=(
+#         "Generate a transcript for a youtube video on what swarms"
+#         " are!"
+#     ),
+#     llm=Anthropic(),
+#     max_loops=1,
+#     autosave=True,
+#     dashboard=False,
+#     streaming_on=True,
+#     verbose=True,
+#     stopping_token="<DONE>",
+# )
+
+# agent2 = Agent(
+#     agent_name="t1",
+#     agent_description=(
+#         "Generate a transcript for a youtube video on what swarms"
+#         " are!"
+#     ),
+#     llm=Anthropic(),
+#     max_loops=1,
+#     system_prompt="Summarize the transcript",
+#     autosave=True,
+#     dashboard=False,
+#     streaming_on=True,
+#     verbose=True,
+#     stopping_token="<DONE>",
+# )
+
+# agent3 = Agent(
+#     agent_name="t2",
+#     agent_description=(
+#         "Generate a transcript for a youtube video on what swarms"
+#         " are!"
+#     ),
+#     llm=Anthropic(),
+#     max_loops=1,
+#     system_prompt="Finalize the transcript",
+#     autosave=True,
+#     dashboard=False,
+#     streaming_on=True,
+#     verbose=True,
+#     stopping_token="<DONE>",
+# )
+
+
+# # Rearrange the agents
+# rearrange = AgentRearrange(
+#     agents=[agent, agent2, agent3],
+#     verbose=True,
+#     # custom_prompt="Summarize the transcript",
+# )
+
+# # Run the workflow on a task
+# results = rearrange(
+#     # pattern="t -> t1, t2 -> t2",
+#     pattern="t -> t1 -> t2",
+#     default_task=(
+#         "Generate a transcript for a YouTube video on what swarms"
+#         " are!"
+#     ),
+#     t="Generate a transcript for a YouTube video on what swarms are!",
+#     # t2="Summarize the transcript",
+#     # t3="Finalize the transcript",
+# )
+# # print(results)

swarms/telemetry/bootup.py

@@ -1,3 +1,4 @@
+import os
 import logging
 import warnings
 
@@ -9,5 +10,6 @@ def bootup():
     """Bootup swarms"""
     disable_logging()
     logging.disable(logging.CRITICAL)
+    os.environ["WANDB_SILENT"] = "true"
     warnings.filterwarnings("ignore", category=DeprecationWarning)
     auto_update()