pavanjava · pavanjava · Oct 4, 2025 · Oct 4, 2025
diff --git a/devops_agent/cli.py b/devops_agent/cli.py
@@ -85,13 +85,16 @@ def run_interactive_mode(provider: str, output: str = None, format: str = 'text'
 
             # Process the query
             console.print(Panel.fit(
-                "[bold cyan]DevOps Agent[/bold cyan] [dim]Thinking...[/dim]",
+                "[bold cyan]DevOps Team[/bold cyan] [dim]Thinking...[/dim]",
                 border_style="cyan"
             ))
 
             try:
                 response = execute_master_agent(provider=provider, user_query=user_input)
-                console.print(f"\n[bold cyan]Assistant:[/bold cyan]\n{response}")
+                console.print(Panel.fit(
+                    f"[bold yellow]Assistant:[/bold yellow] [dim]{response}[/dim]",
+                    border_style="yellow"
+                ))
 
                 # Save to output file if specified
                 if output:
@@ -119,7 +122,10 @@ def process_query(provider: str, query: str, output: str = None, format: str = '
 
     try:
         response = execute_master_agent(provider=provider, user_query=query)
-        console.print(f"\n[bold cyan]Assistant:[/bold cyan]\n{response}")
+        console.print(Panel.fit(
+            f"[bold yellow]Assistant:[/bold yellow] [dim]{response}[/dim]",
+            border_style="yellow"
+        ))
 
         if output:
             save_to_file(output, query, response, format)

diff --git a/devops_agent/core/devops_agent.py b/devops_agent/core/devops_agent.py
@@ -32,7 +32,7 @@
 
 def execute_devops_agent(provider: str, user_query: str = None) -> Agent:
     console.print(Panel.fit(
-        "[bold cyan]DevOps Agent Executing...[/bold cyan]",
+        "[bold cyan]DevOps Agent Invoking...[/bold cyan]",
         border_style="cyan"
     ))
     llm_provider = provider.lower().strip()
@@ -51,7 +51,7 @@ def execute_devops_agent(provider: str, user_query: str = None) -> Agent:
         description="You help answer questions about the devops domain.",
         instructions=devops_prompt,
         # knowledge=knowledge,
-        # stream_intermediate_steps=True,
+        stream_intermediate_steps=True,
         # add_knowledge_to_context=True,
         # add_datetime_to_context=True,
         # add_session_summary_to_context=True,

diff --git a/devops_agent/core/kubernetes_agent.py b/devops_agent/core/kubernetes_agent.py
@@ -34,7 +34,7 @@
 def execute_k8s_agent(provider: str, user_query: str = None) -> Agent:
 
     console.print(Panel.fit(
-        "[bold cyan]Kubernetes Agent Executing...[/bold cyan]",
+        "[bold cyan]Kubernetes Agent Invoking...[/bold cyan]",
         border_style="cyan"
     ))
 
@@ -54,7 +54,7 @@ def execute_k8s_agent(provider: str, user_query: str = None) -> Agent:
         description="You help answer questions about the kubernetes domain of any infrastructure like Azure(AKS), AWS(EKS), and GCP(GKS)",
         instructions=k8s_prompt,
         # knowledge=knowledge,
-        # stream_intermediate_steps=True,
+        stream_intermediate_steps=True,
         # add_knowledge_to_context=True,
         # add_datetime_to_context=True,
         # add_session_summary_to_context=True,

diff --git a/devops_agent/core/master_agent.py b/devops_agent/core/master_agent.py
@@ -1,19 +1,34 @@
 import asyncio
 import os
+from typing import Any
 
 from agno.knowledge import Knowledge
 from agno.models.openai import OpenAIChat
 from agno.models.anthropic import Claude
 from agno.models.google.gemini import Gemini
 from agno.team import Team
+from agno.tools.reasoning import ReasoningTools
 from agno.vectordb.qdrant import Qdrant
+from agno.db.in_memory import InMemoryDb
 from agno.knowledge.embedder.fastembed import FastEmbedEmbedder
 from qdrant_client import QdrantClient
 from qdrant_client.http.models import VectorParams, Distance
 
 from devops_agent.core.devops_agent import execute_devops_agent
 from devops_agent.core.kubernetes_agent import execute_k8s_agent
 
+from rich.console import Console
+from rich.panel import Panel
+from rich.live import Live
+from rich.markdown import Markdown
+from rich.console import Group
+
+from dotenv import load_dotenv, find_dotenv
+
+load_dotenv(find_dotenv())
+
+console = Console()
+
 qclient = QdrantClient(url=os.environ.get('QDRANT_URL'), api_key=os.environ.get('QDRANT_API_KEY'))
 if not qclient.collection_exists("devops-memory"):
     qclient.create_collection(collection_name="devops-memory",
@@ -41,34 +56,41 @@ def execute_master_agent(provider: str, user_query: str) -> str:
     devops_team = Team(
         name="Multi Cloud and Devops Team",
         model=model,
-        respond_directly=True,
         members=[
             execute_devops_agent(provider=provider),
             execute_k8s_agent(provider=provider),
         ],
-        markdown=True,
         instructions=[
             "You are a intelligent router that directs questions to the appropriate agent.",
             "If the user asks in a non devops or k8s question whose agent is not a team member, respond in English with:",
             "'I can only answer in the following technologies: Devops & Kubernetes Architecture on Multiple clouds. Please ask your question in one of these technologies.'",
             "Always check the technology or domain of the user's input before routing to an agent.",
             "For unsupported technologies like coding, flowcharts, analytics etc respond in English with the above message.",
         ],
+        tools=[ReasoningTools()],  # Enable reasoning capabilities
         knowledge=knowledge,
-        determine_input_for_members=True,
+        db=InMemoryDb(),
+        respond_directly=False, # if set to true the member response if directly given to user
+        determine_input_for_members=False,
+        delegate_task_to_all_members=False,
         stream_intermediate_steps=True,
         add_knowledge_to_context=True,
         add_datetime_to_context=True,
         add_session_summary_to_context=True,
         show_members_responses=True,
+        share_member_interactions=True,
+        enable_agentic_memory=True,
+        markdown=True
     )
 
     response = devops_team.run(user_query, stream_intermediate_steps=True, retry=3)
 
     # saved the response to knowledge in async mode
     asyncio.run(
         knowledge.add_content_async(text_content=f"question: {user_query}, Assistant: {response.content}",
-                                    metadata={"agent_id": response.team_id, "session_id": response.session_id})
+                                    skip_if_exists=False,
+                                    metadata={"agent_id": response.team_id, "session_id": response.session_id,
+                                              "run_id": response.run_id})
     )
 
     return response.content
diff --git a/devops_agent/playground.py b/devops_agent/playground.py
@@ -0,0 +1,7 @@
+from devops_agent.core.master_agent import execute_master_agent
+from dotenv import load_dotenv, find_dotenv
+
+load_dotenv(find_dotenv())
+
+if __name__ == '__main__':
+    execute_master_agent(provider="openai", user_query="Analyze distributed tracing data to identify performance bottleneck in microservices architecture")
diff --git a/pyproject.toml b/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "devops-agent"
-version = "0.1.0"
+version = "0.0.1"
 description = "AI-powered DevOps CLI assistant"
 readme = "README.md"
 requires-python = ">=3.8"