ai news completed

.gitignore

@@ -1,2 +1,4 @@
 *.pyc
 /.chroma_db
+/AINews
+*.ipynb

README.md

@@ -173,6 +173,11 @@ To stop the Streamlit app, press `Ctrl+C` in the terminal where the app is runni
 ![tp flow](screenshots/tp_flow.png)  
 ![Travel planner](screenshots/travel_planner.png)  
 
+### 6. Travel Planner 
+**Reference**:  
+![ai news flow](screenshots/ai_news_flow.png)  
+![ai news](screenshots/ai_news.png)  
+
 ---
 
 ## 📚 Templates & Community  

src/langgraphagenticai/graph/graph_builder.py

@@ -3,6 +3,7 @@ from langgraph.prebuilt import tools_condition,ToolNode
 from langchain_core.prompts import ChatPromptTemplate
 import datetime
 #module import
+from src.langgraphagenticai.node.ai_news_node import AINewsNode
 from src.langgraphagenticai.node import travel_planner_node
 from src.langgraphagenticai.node.customer_support_chatbot import Customer_Support_Bot
 from src.langgraphagenticai.tools.customtool import book_appointment, cancel_appointment, get_next_available_appointment
@@ -80,7 +81,7 @@ class GraphBuilder:
         # Define the edge to end the graph after the Travel Planner completes
         self.graph_builder.add_edge("travel_planner", END)
     
-    # Helper methods          
+    # Helper methods -  START       
     # Nodes
     def call_caller_model(self,state: MessagesState):
         state["current_time"] = datetime.datetime.now().strftime("%Y-%m-%d %H:%M")
@@ -95,7 +96,9 @@ class GraphBuilder:
             return "end"
         else:
             return "continue"
-            
+        
+    
+    # Helper method - END     
     def appointment_receptionist_bot_build_graph(self):
         caller_tools = [book_appointment, get_next_available_appointment, cancel_appointment]
         tool_node = ToolNode(caller_tools)
@@ -132,6 +135,19 @@ class GraphBuilder:
     def customer_support_build_graph(self):
         obj_cs_bot = Customer_Support_Bot(llm=self.llm)
         self.graph_builder = obj_cs_bot.chat_bot()
+        
+    def ai_news_build_graph(self):
+        # Initialize the AINewsNode
+        ai_news_node = AINewsNode(self.llm)
+
+        self.graph_builder.add_node("fetch_news", ai_news_node.fetch_news)
+        self.graph_builder.add_node("summarize_news", ai_news_node.summarize_news)
+        self.graph_builder.add_node("save_result", ai_news_node.save_result)
+
+        self.graph_builder.set_entry_point("fetch_news")
+        self.graph_builder.add_edge("fetch_news", "summarize_news")
+        self.graph_builder.add_edge("summarize_news", "save_result")
+        self.graph_builder.add_edge("save_result", END)
 
     def setup_graph(self, usecase: str):
         """
@@ -147,6 +163,8 @@ class GraphBuilder:
             self.appointment_receptionist_bot_build_graph()
         elif usecase =="Customer Support":
             self.customer_support_build_graph()
+        elif usecase =="AI News":
+            self.ai_news_build_graph()
         else:
             raise ValueError("Invalid use case selected.")
         return self.graph_builder.compile()

src/langgraphagenticai/main.py

@@ -26,7 +26,10 @@ def load_langgraph_agenticai_app():
             return
 
         # Text input for user message
-        user_message = st.chat_input("Enter your 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:
                 # Configure LLM

src/langgraphagenticai/node/ai_news_node.py

@@ -0,0 +1,84 @@
+from tavily import TavilyClient
+from langchain_openai import ChatOpenAI
+from langchain_core.prompts import ChatPromptTemplate
+
+class AINewsNode:
+    def __init__(self,llm):
+        """
+        Initialize the AINewsNode with API keys for Tavily and OpenAI.
+        """
+        self.tavily = TavilyClient()
+        self.llm = llm
+        # this is used to capture various steps in this file so that later can be use for steps shown
+        self.state = {}
+
+    def fetch_news(self, state: dict) -> dict:
+        """
+        Fetch AI news based on the specified frequency.
+        
+        Args:
+            state (dict): The state dictionary containing 'frequency'.
+        
+        Returns:
+            dict: Updated state with 'news_data' key containing fetched news.
+        """
+        frequency = state['messages'][0].content.lower()
+        self.state['frequency'] = frequency
+        time_range_map = {'daily': 'd', 'weekly': 'w', 'monthly': 'm', 'year': 'y'}
+        days_map = {'daily': 1, 'weekly': 7, 'monthly': 30, 'year': 366}
+        
+        response = self.tavily.search(
+            query="Top Artificial Intelligence (AI) technology news India and globally",
+            topic="news",
+            time_range=time_range_map[frequency],
+            include_answer="advanced",
+            max_results=15,
+            days=days_map[frequency],
+            # include_domains=["techcrunch.com", "venturebeat.com/ai", ...]  # Uncomment and add domains if needed
+        )
+        state['news_data'] = response.get('results', [])
+        self.state['news_data'] = state['news_data']
+        return state
+
+    def summarize_news(self, state: dict) -> dict:
+        """
+        Summarize the fetched news using an LLM.
+        
+        Args:
+            state (dict): The state dictionary containing 'news_data'.
+        
+        Returns:
+            dict: Updated state with 'summary' key containing the summarized news.
+        """
+        news_items = self.state['news_data']
+        prompt_template = ChatPromptTemplate.from_messages([
+            ("system", """Summarize AI news articles into markdown format. For each item include:
+- Date in **YYYY-MM-DD** format in IST timezone
+- Concise sentences summary from latest news
+- Sort news by date wise (latest first)
+- Source URL as link
+Use format:
+### [Date]
+- [Summary](URL)"""),
+            ("user", "Articles:\n{articles}")
+        ])
+        
+        articles_str = "\n\n".join([
+            f"Content: {item.get('content', '')}\nURL: {item.get('url', '')}\nDate: {item.get('published_date', '')}"
+            for item in news_items
+        ])
+        
+        response = self.llm.invoke(prompt_template.format(articles=articles_str))
+        state['summary'] = response.content
+        self.state['summary'] = state['summary']
+        return self.state
+    
+    def save_result(self,state):
+        frequency = self.state['frequency']
+        summary = self.state['summary']
+        filename = f"./AINews/{frequency}_summary.md"
+        with open(filename, 'w') as f:
+            f.write(f"# {frequency.capitalize()} AI News Summary\n\n")
+            f.write(summary)
+        self.state['filename'] = filename
+        return self.state

src/langgraphagenticai/ui/streamlitui/display_result.py

@@ -88,6 +88,32 @@ class DisplayResultStreamlit:
                 st.title('data protection checks')
                 st.write(data_protection_checks) 
         
+        elif usecase == "AI News":
+            frequency = self.user_message
+            result = graph.invoke({"messages": frequency})
+            try:
+                # Read the markdown file
+                AI_NEWS_PATH = f"./AINews/{frequency.lower()}_summary.md"
+                with open(AI_NEWS_PATH, "r") as file:
+                    markdown_content = file.read()
+
+                # Display the markdown content in Streamlit
+                st.markdown(markdown_content, unsafe_allow_html=True)
+            except FileNotFoundError:
+                st.error(f"News Not Generated or File not found: {AI_NEWS_PATH}")
+            except Exception as e:
+                st.error(f"An error occurred: {str(e)}")
+                
+            
+            with open(AI_NEWS_PATH, 'r') as f:
+                st.download_button(
+                    "💾 Download Summary",
+                    f.read(),
+                    file_name=AI_NEWS_PATH,
+                    mime="text/markdown"
+                )
+            st.success(f"✅ Summary saved to {AI_NEWS_PATH}")
+            
         # display graph
         if graph:
             st.write('state graph - workflow')

src/langgraphagenticai/ui/streamlitui/loadui.py

@@ -11,9 +11,14 @@ class LoadStreamlitUI:
         self.config =  Config() # config
         self.user_controls = {}
 
+
     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
+        
+        
 
         with st.sidebar:
             # Get options from config
@@ -38,7 +43,7 @@ class LoadStreamlitUI:
             # Use case selection
             self.user_controls["selected_usecase"] = st.selectbox("Select Usecases", usecase_options)
             
-            if self.user_controls["selected_usecase"] =="Chatbot with Tool":
+            if self.user_controls["selected_usecase"] =="Chatbot with Tool" or self.user_controls["selected_usecase"] =="AI News" :
             # API key input
                 os.environ["TAVILY_API_KEY"] = self.user_controls["TAVILY_API_KEY"] = st.session_state["TAVILY_API_KEY"] = st.text_input("TAVILY API KEY",
                                                                                                       type="password")
@@ -93,6 +98,21 @@ class LoadStreamlitUI:
                 "start_date": start_date,
                 "end_date": end_date,
             })
+          
+        elif self.user_controls['selected_usecase']=="AI News":
+            st.subheader("📰 AI News Explorer ")
             
-
+            with st.sidebar:
+                time_frame = st.selectbox(
+                    "📅 Select Time Frame",
+                    ["Daily", "Weekly", "Monthly"],
+                    index=0
+                )
+            
+            if st.button("🔍 Fetch Latest AI News", use_container_width=True):
+                st.session_state.IsFetchButtonClicked = True
+                st.session_state.timeframe = time_frame
+            else :
+                st.session_state.IsFetchButtonClicked = False
+                    
         return self.user_controls

src/langgraphagenticai/ui/uiconfigfile.ini

@@ -1,6 +1,6 @@
 [DEFAULT]
 PAGE_TITLE = LangGraph: Build Stateful Agentic AI graph
 LLM_OPTIONS = Groq
-USECASE_OPTIONS = Basic Chatbot, Chatbot with Tool, Travel Planner, Appointment Receptionist, Customer Support
+USECASE_OPTIONS = Basic Chatbot, Chatbot with Tool, Travel Planner, AI News, Appointment Receptionist, Customer Support
 GROQ_MODEL_OPTIONS = mixtral-8x7b-32768, llama3-8b-8192, llama3-70b-8192, gemma-7b-i