Added Modular Structure and Stock Analyser usecase application

.github/workflows/main.yaml

@@ -0,0 +1,25 @@
+name: Sync to Hugging Face Space
+on:
+  push:
+    branches: [main]
+
+  # to run this workflow manually from the Actions tab 
+  workflow_dispatch:
+
+jobs:
+  sync-to-hub:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v3
+        with:
+          fetch-depth: 0
+          lfs: false
+          
+      - name: Ignore large files
+        run : git filter-branch --index-filter 'git rm -rf --cached --ignore-unmatch "Rag_Documents/layout-parser-paper.pdf"' HEAD
+
+      - name: Push to hub
+        env:
+          HF_TOKEN: ${{ secrets.HF_TOKEN }}
+        run: git push --force https://sanket03:[email protected]/spaces/sanket03/AgnoAIAgents main
+        

README.md

@@ -1,2 +1,16 @@
-# agno-ai-agents
-Examples of Agents build with Agno AI Framework
+---
+title: AgnoAgenticAI
+emoji: 🐨
+colorFrom: blue
+colorTo: red
+sdk: streamlit
+sdk_version: 1.42.0
+app_file: app.py
+pinned: false
+license: apache-2.0
+short_description: Refined AgnoAgenticAI
+---
+
+### End To End Agentic AI Projects
+
+

app.py

@@ -0,0 +1,5 @@
+from src.agnoai.main import load_agno_agenticai_app
+
+
+if __name__=="__main__":
+    load_agno_agenticai_app()

requirements.txt

@@ -13,4 +13,6 @@ duckduckgo-search
 yfinance 
 sqlalchemy 
 fastapi[standard]
+groq
+langchain_core
 

src/agnoai/LLMs/groqllm.py

@@ -0,0 +1,20 @@
+import os
+import streamlit as st
+from agno.models.groq import Groq
+
+class GroqLLM:
+    def __init__(self,user_controls_input):
+        self.user_controls_input=user_controls_input
+
+    def get_llm_model(self):
+        try:
+            groq_api_key=self.user_controls_input['GROQ_API_KEY']
+            selected_groq_model=self.user_controls_input['selected_groq_model']
+            if groq_api_key=='' and os.environ["GROQ_API_KEY"] =='':
+                st.error("Please Enter the Groq API KEY")
+
+            llm = Groq(api_key=groq_api_key, id=selected_groq_model)
+
+        except Exception as e:
+            raise ValueError(f"Error Occurred with Exception : {e}")
+        return llm

src/agnoai/LLMs/openaillm.py

@@ -0,0 +1,20 @@
+import os
+import streamlit as st
+from agno.models.openai import OpenAIChat
+
+class OpenAILLM:
+    def __init__(self,user_controls_input):
+        self.user_controls_input=user_controls_input
+
+    def get_llm_model(self):
+        try:
+            openai_api_key=self.user_controls_input['OPENAI_API_KEY']
+            selected_openai_model=self.user_controls_input['selected_openai_model']
+            if openai_api_key=='' and os.environ["OPENAI_API_KEY"] =='':
+                st.error("Please Enter the OpenAI API KEY")
+
+            llm = OpenAIChat(api_key=openai_api_key, id=selected_openai_model)
+
+        except Exception as e:
+            raise ValueError(f"Error Occurred with Exception : {e}")
+        return llm

src/agnoai/aiagents/agents.py

@@ -0,0 +1,50 @@
+from agno.agent import Agent
+from agno.models.openai import OpenAIChat
+from agno.embedder.openai import OpenAIEmbedder
+from agno.tools.duckduckgo import DuckDuckGoTools
+from agno.tools.yfinance import YFinanceTools
+
+class Agents:
+    def __init__(self, user_controls_input, model):
+        self.user_controls_input=user_controls_input
+        self.model = model
+    
+    def web_agent(self):
+        web_aiagent = Agent(
+            name="Web Agent",
+            role="Search the web for information",
+            # model=self.user_controls_input["selected_llm"],
+            model=self.model,
+            tools=[DuckDuckGoTools()],
+            instructions="Always include sources",
+            show_tool_calls=True,
+            markdown=True,
+        )
+        return web_aiagent
+
+    def finance_agent(self):
+        finance_aiagent = Agent(
+            name="Finance Agent",
+            role="Get Financial Data",
+            # model=self.user_controls_input["selected_llm"],
+            model=self.model,
+            tools=[YFinanceTools(stock_price=True, analyst_recommendations=True,stock_fundamentals=True,company_info=True)],
+            instructions="Use tables to display data",
+            show_tool_calls=True,
+            markdown=True,
+        )
+        return finance_aiagent
+    
+    def agent_team(self):
+        agent_aiteam = Agent(
+        team = [self.web_agent(), self.finance_agent()],
+        # model = self.user_controls_input["selected_llm"],
+        model=self.model,
+        instructions=["Always include sources", "Use tables to display data"],
+        show_tool_calls=True,
+        markdown=True,
+        )
+        return agent_aiteam
+    
+    
+

src/agnoai/aiagents/multiagents.py

@@ -0,0 +1,9 @@
+# from agents import Agents
+# from agno.agent import Agent
+
+
+# class MultiAgents:
+#     def __init__(self, Agents, user_controls_input):
+#         self.Agents = Agents()
+
+#     def agent_team(self):

src/agnoai/main.py

@@ -0,0 +1,50 @@
+import streamlit as st
+import json
+from src.agnoai.ui.streamlitui.loadui import LoadStreamlitUI
+from src.agnoai.LLMs.groqllm import GroqLLM
+from src.agnoai.LLMs.openaillm import OpenAILLM
+from src.agnoai.aiagents.agents import Agents
+from src.agnoai.ui.streamlitui.display_result import DisplayResultStreamlit
+
+# Main Function 
+def load_agno_agenticai_app():
+
+    # Load UI
+    ui = LoadStreamlitUI()
+    user_input = ui.load_streamlit_ui()
+
+    if not user_input:
+        st.error("Error: Failed to load user input from the UI.")
+        return
+    
+    # Text input for user message
+    if st.session_state.IsFetchButtonClicked:
+        user_message = st.session_state.timeframe 
+    else :
+        user_message = st.chat_input("Enter your message:")
+
+    if user_message:
+        try:
+            if user_input['selected_llm']=='Groq':
+                obj_llm_config = GroqLLM(user_controls_input=user_input)
+                model = obj_llm_config.get_llm_model()
+
+                if not model:
+                    st.error("Error: LLM model could not be initialized.")
+                    return
+            elif user_input['selected_llm']=='OpenAI':
+                obj_llm_config = OpenAILLM(user_controls_input=user_input)
+                model = obj_llm_config.get_llm_model()
+
+                if not model:
+                    st.error("Error: LLM model could not be initialized.")
+                    return
+            
+            ### Agents
+            agents = Agents(user_input, model)
+            agent_team = agents.agent_team()
+            DisplayResultStreamlit(agent_team, user_message).display_result_on_ui()
+            
+        
+        except Exception as e:
+                 raise ValueError(f"Error Occurred with Exception : {e}")  

src/agnoai/ui/streamlitui/display_result.py

@@ -0,0 +1,33 @@
+import streamlit as st
+from langchain_core.messages import HumanMessage,AIMessage,ToolMessage
+import json
+
+class DisplayResultStreamlit:
+    def __init__(self,agent_team,user_message):
+        self.agent_team = agent_team
+        self.user_message = user_message
+
+
+    def display_result_on_ui(self):
+        agent_team = self.agent_team
+        user_message = self.user_message
+
+        #  # Streamlit Interface
+        # st.title("📈 Stock Analysis Expert")
+        # # Description of the application
+        # st.write("""
+        # Welcome to the Stock Analysis Expert dashboard! This interactive app helps you analyze stock performance using key technical indicators. 
+        # You can explore historical stock data, visualize trends, and make informed investment decisions.
+        # """)
+
+        # # User Input
+        # user_input = st.text_input("Enter your question:")
+        # print(user_input)
+
+        # Display Response
+        if user_message:
+            with st.spinner("Thinking..."):
+                response = agent_team.run(user_message)
+                st.markdown(response.get_content_as_string())
+
+    

src/agnoai/ui/streamlitui/loadui.py

@@ -0,0 +1,69 @@
+import streamlit as st
+import os
+from datetime import date
+
+# from langchain_core.messages import AIMessage,HumanMessage
+from src.agnoai.ui.uiconfigfile import Config
+
+class LoadStreamlitUI:
+    def __init__(self):
+        self.config =  Config() 
+        self.user_controls = {}
+
+    def initialize_session(self):
+        return {
+        "current_step": "requirements",
+        "requirements": "",
+        "user_stories": "",
+        "po_feedback": "",
+        "generated_code": "",
+        "review_feedback": "",
+        "decision": None
+    }
+
+    def load_streamlit_ui(self):
+        st.set_page_config(page_title= "🤖 " + self.config.get_page_title(), layout="wide")
+        st.header("🤖 " + self.config.get_page_title())
+        st.session_state.timeframe = ''
+        st.session_state.IsFetchButtonClicked = False
+        st.session_state.IsSDLC = False
+
+        with st.sidebar:
+            # Get options from config
+            llm_options = self.config.get_llm_options()
+            usecase_options = self.config.get_usecase_options()
+
+            # LLM selection
+            self.user_controls["selected_llm"] = st.selectbox("Select LLM", llm_options)
+
+            if self.user_controls["selected_llm"] == 'Groq':
+                # Model selection
+                model_options = self.config.get_groq_model_options()
+                self.user_controls["selected_groq_model"] = st.selectbox("Select Model", model_options)
+                # API key input
+                self.user_controls["GROQ_API_KEY"] = st.session_state["GROQ_API_KEY"] = st.text_input("API Key",
+                                                                                                      type="password")
+                # Validate API key
+                if not self.user_controls["GROQ_API_KEY"]:
+                    st.warning("⚠️ Please enter your GROQ API key to proceed. Don't have? refer : https://console.groq.com/keys ")
+
+            elif self.user_controls["selected_llm"] == 'OpenAI':
+                # Model selection
+                model_options = self.config.get_openai_model_options()
+                self.user_controls["selected_openai_model"] = st.selectbox("Select Model", model_options)
+                # API key input
+                self.user_controls["OPENAI_API_KEY"] = st.session_state["OPENAI_API_KEY"] = st.text_input("API Key",
+                                                                                                      type="password")
+                # Validate API key
+                if not self.user_controls["OPENAI_API_KEY"]:
+                    st.warning("⚠️ Please enter your OpenAI API key to proceed. Don't have? refer : https://platform.openai.com/api-keys ")
+
+            # Use case selection
+            self.user_controls["selected_usecase"] = st.selectbox("Select Usecases", usecase_options)
+
+            if "state" not in st.session_state:
+                st.session_state.state = self.initialize_session()
+
+        
+
+        return self.user_controls

src/agnoai/ui/uiconfigfile.ini

@@ -0,0 +1,6 @@
+[DEFAULT]
+PAGE_TITLE = AGNO : Quickly Build AI Agents
+LLM_OPTIONS = Groq, OpenAI
+USECASE_OPTIONS = Stock Analyser
+GROQ_MODEL_OPTIONS = llama-3.3-70b-versatile, llama-3.1-8b-instant, mixtral-8x7b-32768, gemma2-9b-it, qwen-2.5-32b, deepseek-r1-distill-qwen-32b, deepseek-r1-distill-llama-70b-specdec, deepseek-r1-distill-llama-70b
+OPENAI_MODEL_OPTIONS = gpt-4o, gpt-4o-mini

src/agnoai/ui/uiconfigfile.py

@@ -0,0 +1,21 @@
+from configparser import ConfigParser
+
+class Config:
+    def __init__(self, config_file = "./src/agnoai/ui/uiconfigfile.ini"):
+        self.config = ConfigParser()
+        self.config.read(config_file)
+        
+    def get_llm_options(self):
+        return self.config["DEFAULT"].get("LLM_OPTIONS").split(", ")
+
+    def get_usecase_options(self):
+        return self.config["DEFAULT"].get("USECASE_OPTIONS").split(", ")
+
+    def get_groq_model_options(self):
+        return self.config["DEFAULT"].get("GROQ_MODEL_OPTIONS").split(", ")
+    
+    def get_openai_model_options(self):
+        return self.config["DEFAULT"].get("OPENAI_MODEL_OPTIONS")
+
+    def get_page_title(self):
+        return self.config["DEFAULT"].get("PAGE_TITLE")