feat: Add dynamic mulit modal

swarms/structs/flow.py

@@ -9,12 +9,15 @@ TODO:
 
 import json
 import logging
+import re
 import time
 from typing import Any, Callable, Dict, List, Optional, Tuple, Generator
 from termcolor import colored
 import inspect
 import random
 
+from swarms.models.openai_models import OpenAIChat
+
 
 # Constants
 FLOW_SYSTEM_PROMPT = """
@@ -95,8 +98,13 @@ class Flow:
         dynamic_temperature: bool = False,
         **kwargs: Any,
     ):
-        self.llm = llm
         # self.template = template
+        self.processors = {
+            'text': self.process_text,
+            'image': self.process_image,
+            'audio': self.process_audio,
+        }
+        self.llm = llm
         self.max_loops = max_loops
         self.stopping_condition = stopping_condition
         self.loop_interval = loop_interval
@@ -110,6 +118,43 @@ class Flow:
         self.dashboard = dashboard
         self.dynamic_temperature = dynamic_temperature
 
+    def __call__(self, task, **kwargs):
+        """Invoke the flow by providing a template and its variables."""
+        subtasks = self.break_down_task(task)
+        responses = []
+        for subtask in subtasks:
+            mode = self.determine_mode(subtask)
+            processor = self.processors.get(mode)
+            if processor:
+                refined_prompt = self.text_model(f"Define the task '{subtask}' as it relates to the original task '{task}'.")
+                response = processor(refined_prompt, task)
+                responses.append(response)
+            else:
+                    raise ValueError(f'Invalid mode: {mode}')
+            return responses
+
+    def break_down_task(self, task):
+        # Break down the task into subtasks
+        subtasks = re.split(r' with | and ', task)
+        return subtasks
+
+    def determine_mode(self, subtask):
+        result = self.classifier(subtask, candidate_labels=['text', 'image', 'audio', 'video'])
+        return result['labels'][0]
+
+    def process_image(self, image_description):
+        response = self.image_model(image_description)
+        return response
+
+    def process_audio(self, audio_description):
+        response = self.audio_model(audio_description)
+        return response
+
+    def process_video(self, video_description):
+        response = self.video_model(video_description)
+        return response
+        
+        return "Video generated from description: " + video_description
     def provide_feedback(self, feedback: str) -> None:
         """Allow users to provide feedback on the responses."""
         self.feedback.append(feedback)
@@ -121,11 +166,6 @@ class Flow:
             return self.stopping_condition(response)
         return False
 
-    def __call__(self, prompt, **kwargs) -> str:
-        """Invoke the flow by providing a template and its variables."""
-        response = self.llm(prompt, **kwargs)
-        return response
-
     def dynamic_temperature(self):
         """
         1. Check the self.llm object for the temperature