[BUFG][TypeError: descriptor 'append' for 'list' objects doesn't apply to a 'Task' object

]

playground/structs/concurrent_workflow.py

@@ -0,0 +1,26 @@
+import os 
+from dotenv import load_dotenv 
+from swarms import OpenAIChat, Task, ConcurrentWorkflow, Agent
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Load environment variables
+llm = OpenAIChat(openai_api_key=os.getenv("OPENAI_API_KEY"))
+agent = Agent(llm=llm, max_loops=1)
+
+# Create a workflow
+workflow = ConcurrentWorkflow(max_workers=5)
+
+# Create tasks
+task1 = Task(agent, "What's the weather in miami")
+task2 = Task(agent, "What's the weather in new york")
+task3 = Task(agent, "What's the weather in london")
+
+# Add tasks to the workflow
+workflow.add(task1)
+workflow.add(task2)
+workflow.add(task3)
+
+# Run the workflow
+workflow.run()

scripts/auto_tests_docs/auto_docs_omni.py

@@ -5,36 +5,13 @@ import threading
 from dotenv import load_dotenv
 from scripts.auto_tests_docs.docs import DOCUMENTATION_WRITER_SOP
 from swarms import OpenAIChat
-from swarms.structs.agent import Agent
-from swarms.structs.autoscaler import AutoScaler
-from swarms.structs.base import BaseStructure
-from swarms.structs.base_swarm import AbstractSwarm
-from swarms.structs.base_workflow import BaseWorkflow
-from swarms.structs.concurrent_workflow import ConcurrentWorkflow
-from swarms.structs.conversation import Conversation
-from swarms.structs.groupchat import GroupChat, GroupChatManager
-from swarms.structs.model_parallizer import ModelParallelizer
-from swarms.structs.multi_agent_collab import MultiAgentCollaboration
-from swarms.structs.nonlinear_workflow import NonlinearWorkflow
-from swarms.structs.recursive_workflow import RecursiveWorkflow
-from swarms.structs.schemas import (
-    Artifact,
-    ArtifactUpload,
-    StepInput,
-    TaskInput,
-)
-from swarms.structs.sequential_workflow import SequentialWorkflow
-from swarms.structs.swarm_net import SwarmNetwork
-from swarms.structs.utils import (
-    distribute_tasks,
-    extract_key_from_json,
-    extract_tokens_from_text,
-    find_agent_by_id,
-    find_token_in_text,
-    parse_tasks,
-)
 
 
+###########
+
+
+###############
+
 load_dotenv()
 
 api_key = os.getenv("OPENAI_API_KEY")
@@ -86,33 +63,7 @@ def process_documentation(
 
 
 def main(module: str = "docs/swarms/structs"):
-    items = [
-        Agent,
-        SequentialWorkflow,
-        AutoScaler,
-        Conversation,
-        TaskInput,
-        Artifact,
-        ArtifactUpload,
-        StepInput,
-        SwarmNetwork,
-        ModelParallelizer,
-        MultiAgentCollaboration,
-        AbstractSwarm,
-        GroupChat,
-        GroupChatManager,
-        parse_tasks,
-        find_agent_by_id,
-        distribute_tasks,
-        find_token_in_text,
-        extract_key_from_json,
-        extract_tokens_from_text,
-        ConcurrentWorkflow,
-        RecursiveWorkflow,
-        NonlinearWorkflow,
-        BaseWorkflow,
-        BaseStructure,
-    ]
+    items = []
 
     threads = []
     for item in items:

swarms/memory/__init__.py

@@ -2,10 +2,12 @@ from swarms.memory.base_vectordb import VectorDatabase
 from swarms.memory.short_term_memory import ShortTermMemory
 from swarms.memory.sqlite import SQLiteDB
 from swarms.memory.weaviate_db import WeaviateDB
+from swarms.memory.visual_memory import VisualShortTermMemory
 
 __all__ = [
     "VectorDatabase",
     "ShortTermMemory",
     "SQLiteDB",
     "WeaviateDB",
+    "VisualShortTermMemory",
 ]

swarms/memory/visual_memory.py

@@ -0,0 +1,118 @@
+from typing import List
+from datetime import datetime
+
+
+class VisualShortTermMemory:
+    """
+    A class representing visual short-term memory.
+
+    Attributes:
+        memory (list): A list to store images and their descriptions.
+
+    Examples:
+        example = VisualShortTermMemory()
+        example.add(
+            images=["image1.jpg", "image2.jpg"],
+            description=["description1", "description2"],
+            timestamps=[1.0, 2.0],
+            locations=["location1", "location2"],
+        )
+        print(example.return_as_string())
+        # print(example.get_images())
+    """
+
+    def __init__(self):
+        self.memory = []
+
+    def add(
+        self,
+        images: List[str] = None,
+        description: List[str] = None,
+        timestamps: List[float] = None,
+        locations: List[str] = None,
+    ):
+        """
+        Add images and their descriptions to the memory.
+
+        Args:
+            images (list): A list of image paths.
+            description (list): A list of corresponding descriptions.
+            timestamps (list): A list of timestamps for each image.
+            locations (list): A list of locations where the images were captured.
+        """
+        current_time = datetime.now()
+
+        # Create a dictionary of each image and description
+        # and append it to the memory
+        for image, description, timestamp, location in zip(
+            images, description, timestamps, locations
+        ):
+            self.memory.append(
+                {
+                    "image": image,
+                    "description": description,
+                    "timestamp": timestamp,
+                    "location": location,
+                    "added_at": current_time,
+                }
+            )
+
+    def get_images(self):
+        """
+        Get a list of all images in the memory.
+
+        Returns:
+            list: A list of image paths.
+        """
+        return [item["image"] for item in self.memory]
+
+    def get_descriptions(self):
+        """
+        Get a list of all descriptions in the memory.
+
+        Returns:
+            list: A list of descriptions.
+        """
+        return [item["description"] for item in self.memory]
+
+    def search_by_location(self, location: str):
+        """
+        Search for images captured at a specific location.
+
+        Args:
+            location (str): The location to search for.
+
+        Returns:
+            list: A list of images captured at the specified location.
+        """
+        return [
+            item["image"]
+            for item in self.memory
+            if item["location"] == location
+        ]
+
+    def search_by_timestamp(self, start_time: float, end_time: float):
+        """
+        Search for images captured within a specific time range.
+
+        Args:
+            start_time (float): The start time of the range.
+            end_time (float): The end time of the range.
+
+        Returns:
+            list: A list of images captured within the specified time range.
+        """
+        return [
+            item["image"]
+            for item in self.memory
+            if start_time <= item["timestamp"] <= end_time
+        ]
+
+    def return_as_string(self):
+        """
+        Return the memory as a string.
+
+        Returns:
+            str: A string representation of the memory.
+        """
+        return str(self.memory)

swarms/structs/concurrent_workflow.py

@@ -91,11 +91,13 @@ class ConcurrentWorkflow(BaseStructure):
                 try:
                     result = future.result()
                     if self.print_results:
-                        print(f"Task {task}: {result}")
+                        logger.info(f"Task {task}: {result}")
                     if self.return_results:
                         results.append(result)
                 except Exception as e:
-                    print(f"Task {task} generated an exception: {e}")
+                    logger.error(
+                        f"Task {task} generated an exception: {e}"
+                    )
 
         return results if self.return_results else None
 

swarms/structs/recursive_workflow.py

@@ -33,13 +33,13 @@ class RecursiveWorkflow(BaseStructure):
 
     def __init__(self, stop_token: str = "<DONE>"):
         self.stop_token = stop_token
-        self.task_pool = List[Task]
+        self.task_pool = []
 
         assert (
             self.stop_token is not None
         ), "stop_token cannot be None"
 
-    def add(self, task: Task, tasks: List[Task] = None):
+    def add(self, task: Task = None, tasks: List[Task] = None):
         """Adds a task to the workflow.
 
         Args:
@@ -49,12 +49,13 @@ class RecursiveWorkflow(BaseStructure):
         try:
             if tasks:
                 for task in tasks:
+                    if isinstance(task, Task):
                         self.task_pool.append(task)
                         logger.info(
                             "[INFO][RecursiveWorkflow] Added task"
                             f" {task} to workflow"
                         )
-            else:
+            elif isinstance(task, Task):
                 self.task_pool.append(task)
                 logger.info(
                     f"[INFO][RecursiveWorkflow] Added task {task} to"
@@ -74,8 +75,8 @@ class RecursiveWorkflow(BaseStructure):
         try:
             for task in self.task_pool:
                 while True:
-                    result = task.execute()
-                    if self.stop_token in result:
+                    result = task.run()
+                    if result is not None and self.stop_token in result:
                         break
                     logger.info(f"{result}")
         except Exception as error:

swarms/structs/task.py

@@ -54,9 +54,8 @@ class Task:
     >>> task.result
 
     """
-
-    description: str
     agent: Union[Callable, Agent]
+    description: str
     args: List[Any] = field(default_factory=list)
     kwargs: Dict[str, Any] = field(default_factory=dict)
     result: Any = None