flow class AI: preprended to responses

Former-commit-id: 5c7157a916

docs/swarms/structs/flow.md

@@ -57,7 +57,7 @@ from swarms.structs import Flow
 flow = Flow(llm=my_language_model, max_loops=5)
 
 # Define a starting task or message
-initial_task = "Hello, can you provide me with some information?"
+initial_task = "Generate a 10,000 word blog on health and wellness."
 
 # Run the conversation loop
 final_response = flow.run(initial_task)
@@ -68,7 +68,7 @@ final_response = flow.run(initial_task)
 You can collect feedback during the conversation using the `provide_feedback` method:
 
 ```python
-flow.provide_feedback("The response was not accurate.")
+flow.provide_feedback("Generate an SOP for new sales employees on the best cold sales practices")
 ```
 
 ### Stopping Condition
@@ -112,7 +112,7 @@ from swarms.structs import Flow
 flow = Flow(llm=my_language_model, max_loops=5)
 
 # Define a starting task or message
-initial_task = "Hello, can you provide me with some information?"
+initial_task = "Generate an long form analysis on the transformer model architecture."
 
 # Run the conversation loop
 final_response = flow.run(initial_task)
@@ -137,7 +137,7 @@ from swarms.structs import Flow
 flow = Flow(llm=my_language_model, max_loops=5, interactive=True)
 
 # Provide initial task
-initial_task = "Hello, can you tell me a joke?"
+initial_task = "Rank and prioritize the following financial documents and cut out 30% of our expenses"
 
 # Run the conversation loop
 final_response = flow.run(initial_task)

flow.py

@@ -1,7 +1,7 @@
 from swarms.models import OpenAIChat
 from swarms.structs import Flow
 
-api_key = "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"
+api_key = ""
 
 
 # Initialize the language model,
@@ -16,4 +16,5 @@ llm = OpenAIChat(
 flow = Flow(llm=llm, max_loops=5, dashboard=True)
 
 out = flow.run("Generate a 10,000 word blog on health and wellness.")
+
 print(out)

positive_med.py

@@ -281,7 +281,7 @@ def social_media_prompt(article: str, goal: str = "Clicks and engagement"):
 
 # Agent that generates topics
 topic_selection_task = (
-    "Generate 10 topics on gaining mental clarity using ancient Taosim practices"
+    "Generate 10 topics on gaining mental clarity using ancient practices"
 )
 topics = llm(
     f"Your System Instructions: {TOPIC_GENERATOR}, Your current task: {topic_selection_task}"

swarms/structs/flow.py

@@ -212,7 +212,7 @@ class Flow:
 
         """
         response = task
-        history = [task]
+        history = [f"Human: {task}"]
 
         # If dashboard = True then print the dashboard
         if self.dashboard:
@@ -232,7 +232,18 @@ class Flow:
             while attempt < self.retry_attempts:
                 try:
                     response = self.llm(response)
-                    print(f"Next query: {response}")
+                    # print(f"Next query: {response}")
+                    # break
+
+                    if self.interactive:
+                        print(f"AI: {response}")
+                        history.append(f"AI: {response}")
+                        response = input("You: ")
+                        history.append(f"Human: {response}")
+                    else:
+                        print(f"AI: {response}")
+                        history.append(f"AI: {response}")
+                        print(response)
                     break
                 except Exception as e:
                     logging.error(f"Error generating response: {e}")