Integrate weather tools with current and alert weather tools

.env.example

@@ -0,0 +1,3 @@
+SERPER_API_KEY=
+OPENAI_API_KEY=
+TAVILY_API_KEY=t

.gitignore

@@ -1,3 +1,16 @@
-*.pyc
+# ---------------------------
+# Python
+# ---------------------------
 __pycache__/
+*.py[cod]
+*.pyo
+*.pyd
+*.so
+*.egg
+*.egg-info/
+dist/
+build/
+.eggs/
+
 .env
+

main.py

@@ -0,0 +1,53 @@
+import streamlit as st
+from streamlit_option_menu import option_menu
+
+# ---- CONFIG ----
+st.set_page_config(page_title="Card Navigation App", layout="wide")
+
+# ---- SIDEBAR MENU ----
+with st.sidebar:
+    selected = option_menu(
+        "Navigation",
+        ["Home", "Page 1", "Page 2", "Page 3", "Page 4"],
+        icons=["house", "1-circle", "2-circle", "3-circle", "4-circle"],
+        menu_icon="list",
+        default_index=0,
+    )
+
+# ---- MAIN CONTENT ----
+if selected == "Home":
+    st.markdown(
+        "<h2 style='text-align:center;'>Choose a Page</h2>", unsafe_allow_html=True
+    )
+
+    cols = st.columns(4, gap="large")
+
+    # Four cards in center
+    with cols[0]:
+        if st.button("Page 1", use_container_width=True):
+            st.session_state["selected"] = "Page 1"
+    with cols[1]:
+        if st.button("Page 2", use_container_width=True):
+            st.session_state["selected"] = "Page 2"
+    with cols[2]:
+        if st.button("Page 3", use_container_width=True):
+            st.session_state["selected"] = "Page 3"
+    with cols[3]:
+        if st.button("Page 4", use_container_width=True):
+            st.session_state["selected"] = "Page 4"
+
+elif selected == "Page 1":
+    st.title("📘 Page 1")
+    st.write("Welcome to Page 1 content")
+
+elif selected == "Page 2":
+    st.title("📙 Page 2")
+    st.write("Welcome to Page 2 content")
+
+elif selected == "Page 3":
+    st.title("📗 Page 3")
+    st.write("Welcome to Page 3 content")
+
+elif selected == "Page 4":
+    st.title("📕 Page 4")
+    st.write("Welcome to Page 4 content")

pyproject.toml

@@ -12,13 +12,19 @@ authors = [
 
 dependencies = [
     "black>=25.1.0",
+    "ddgs>=9.5.2",
+    "duckduckgo-search>=8.1.1",
     "langchain>=0.3.26",
+    "langchain-community>=0.3.27",
     "langchain-ollama>=0.3.3",
+    "langchain-tavily>=0.2.11",
+    "langgraph>=0.6.4",
     "pytest>=8.4.1",
     "pytest-mock>=3.14.1",
     "python-dotenv>=1.1.0",
     "ruff>=0.12.0",
     "streamlit>=1.46.0",
+    "streamlit-option-menu>=0.4.0",
 ]
 
 classifiers = [
@@ -37,3 +43,7 @@ addopts = "-ra -q"
 testpaths = ["tests"]
 pythonpath = [".", "src"]
 
+
+[tool.ruff.lint]
+extend-ignore = ["F401"]
+per-file-ignores = { "__init__.py" = ["F401"] }

src/agents/__init__.py

@@ -0,0 +1,2 @@
+from src.agents.weather_assistant import weather_assistant_agen_config
+from src.agents.agent import Agent

src/agents/agent.py

@@ -0,0 +1,14 @@
+from langchain_core.tools.base import BaseTool
+from typing import List
+
+
+class Agent:
+    def __init__(
+        self,
+        prompt: str,
+        name: str = None,
+        tools: list[BaseTool] = [],
+    ):
+        self.system_prompt: str = prompt
+        self.tools: List[BaseTool] = tools
+        self.name: str = name

src/agents/weather_assistant.py

@@ -0,0 +1,13 @@
+from src.agents.agent import Agent
+from src.tools import current_weather_tool, weather_alerts_tool
+
+
+weather_assistant_agen_config = Agent(
+    name="Weather_Assistant_Agent",
+    tools=[current_weather_tool, weather_alerts_tool],
+    prompt="""You are a helpful weather assistant. 
+        You should identify for which countries weather information is needed from the user messages {messages}. 
+        Use only the country name or postal code if there is any in user message, for tool calling.
+        lways call the weather tool when you detect a location query. Do not stop after reasoning; fetch and return the weather in the same response.
+        Also fetch if there is any weather alerts.""",
+)

src/components/__init__.py

@@ -0,0 +1,4 @@
+from src.components.sidebar import sidebar
+
+
+__all__ = ["sidebar"]

src/components/sidebar.py

@@ -0,0 +1,13 @@
+import streamlit as st
+
+
+def sidebar(get_ollama_names, update_model):
+    with st.sidebar:
+        with st.expander("⚙️ Model Settings", expanded=True):
+            st.selectbox(
+                "Select LLM model",
+                get_ollama_names(),
+                key="selected_model",
+                on_change=update_model,
+            )
+            st.divider()

src/constants/__init__.py

@@ -0,0 +1 @@
+from src.constants.variables import WEATHER_API_KEY, WEATHER_BASE_URL, OPENAI_KEY

src/constants/variables.py

@@ -0,0 +1,9 @@
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+WEATHER_API_KEY: str = os.getenv("WEATHER_API_KEY", "")
+WEATHER_BASE_URL: str = os.getenv("WEATHER_BASE_URL")
+
+OPENAI_KEY: str = os.getenv("OPENAI_KEY", "")

src/llm/__init__.py

@@ -3,3 +3,5 @@
 contact: joshanjohn2003@gmail.com
 subjected to copyright@2025
 """
+
+from src.llm.llm import LLM

src/llm/llm.py

@@ -5,21 +5,26 @@
 """
 
 from langchain_ollama import ChatOllama
+from src.utils import logger
 
 
 class LLM:
     def __init__(self, model: str) -> None:
         self.model: str = model
-        self.llm: ChatOllama = self.load_model()
 
-    def load_model(self) -> ChatOllama:
+    def get_llm_model(self) -> ChatOllama:
         if not self.model:
+            logger.error("Model name is required to load ChatOllama.")
             raise ValueError("Model name is required to load ChatOllama.")
+        logger.info(f"LLM = {self.model}")
         return ChatOllama(model=self.model)
 
-    def run(self, msg: str) -> str:
+    def __call__(self, msg: str) -> str:
         if not msg:
-            return "Failed to generate LLM response"
+            _error = "Failed to generate LLM response"
+            logger.error(_error)
+            return _error
 
-        print(self.llm.get_name())  # if get_name() is a method
-        return self.llm.invoke(msg).content
+        llm = self.get_llm_model()
+        logger.debug(f"Model {llm.get_name()} loaded ... ")
+        return llm.invoke(msg).content

src/main.py

@@ -6,20 +6,38 @@
 
 import streamlit as st
 from utils.get_models import get_ollama_names
-from src.workflows.workflow import WorkFlow
+from src.workflows import Workflow
+from src.components import sidebar
+from dotenv import load_dotenv
+
+load_dotenv()
 
 
 def update_model():
     st.session_state.model = st.session_state.selected_model
+    st.session_state.workflow = init_workflow(st.session_state.model)
 
 
 def init_workflow(llm_model: str):
-    return WorkFlow(llm=llm_model)
+    return Workflow(llm_model)
 
 
-def main():
-    col1, col2 = st.columns([3, 1])
+def run_workflow(workflow: Workflow, query: str, messages: list) -> str:
+    """Run compiled workflow on user query and return assistant response."""
+    compiled = workflow.get_workflow()
 
+    # Convert chat history into AgentState
+    # Run graph with user query
+    result_state = compiled.invoke({"messages": messages})
+
+    # Extract AI response from updated state
+    last_message = (
+        result_state["messages"][-1].content if result_state["messages"] else ""
+    )
+    return last_message
+
+
+def init_session_states():
     # Initialize model and dropdown selection
     if "model" not in st.session_state:
         default_model = get_ollama_names()[0]
@@ -28,73 +46,80 @@ def main():
     if "selected_model" not in st.session_state:
         st.session_state.selected_model = st.session_state.model
 
+    # Initialize workflow
+    if "workflow" not in st.session_state:
+        st.session_state.workflow = init_workflow(st.session_state.model)
+
     # Initialize chat history
     if "messages" not in st.session_state:
         st.session_state.messages = []
 
-    # UI - Left: Title + Model info
-    with col1:
-        st.title("Cllama")
-        st.write(f"Current model: `{st.session_state.model}`")
-
-    # UI - Right: Model selector
-    with col2:
-        st.selectbox(
-            "Select LLM model",
-            get_ollama_names(),
-            key="selected_model",
-            on_change=update_model,
-        )
 
-    # Display chat history
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    # Chat input
-    prompt = st.chat_input("Ask me...")
-
-    if prompt:
-        # Show user input
-        with st.chat_message("user"):
-            st.markdown(prompt)
-        st.session_state.messages.append({"role": "user", "content": prompt})
-
-        # Process AI response
-        with st.spinner("AI is typing..."):
-            workflow = init_workflow(st.session_state.model)
-            response = workflow.invoke(prompt)
-
-        # Show assistant response
-        with st.chat_message("assistant"):
-            st.markdown(response)
-        st.session_state.messages.append({"role": "assistant", "content": response})
-
-    # Author credit footer at bottom-right
-    st.markdown(
-        """
-        <style>
-        .footer-credit {
-            position: fixed;
-            bottom: 8px;
-            right: 16px;
-            font-size: 12px;
-            color: gray;
-            z-index: 9999;
-        }
-        .footer-credit a {
-            color: yellow;
-            text-decoration: none;
-            font-size: 14px;
-        }
-        </style>
-        <div class="footer-credit">
-            Author <a href="https://github.com/joshanjohn" target="_blank">Joshan John</a>
-        </div>
-        """,
-        unsafe_allow_html=True,
+def main():
+
+    init_session_states()
+
+    sidebar(
+        get_ollama_names=get_ollama_names,
+        update_model=update_model,
     )
 
+    st.title("Cllama")
+    st.write(f"Current model: `{st.session_state.model}`")
+
+    with st.container():
+        # Chat input
+        prompt = st.chat_input("Ask me...")
+
+        # Display chat history
+        for message in st.session_state.messages:
+            with st.chat_message(message["role"]):
+                st.markdown(message["content"])
+
+        if prompt:
+            # Show user input
+            with st.chat_message("user"):
+                st.markdown(prompt)
+            st.session_state.messages.append({"role": "user", "content": prompt})
+
+            # Process AI response
+            with st.spinner("AI is typing..."):
+                response = run_workflow(
+                    st.session_state.workflow,
+                    prompt,
+                    st.session_state.messages,
+                )
+
+            # Show assistant response
+            with st.chat_message("assistant"):
+                st.markdown(response)
+            st.session_state.messages.append({"role": "assistant", "content": response})
+
+        # Author credit footer at bottom-right
+        st.markdown(
+            """
+            <style>
+            .footer-credit {
+                position: fixed;
+                bottom: 8px;
+                right: 16px;
+                font-size: 12px;
+                color: gray;
+                z-index: 9999;
+            }
+            .footer-credit a {
+                color: green;
+                text-decoration: none;
+                font-size: 14px;
+            }
+            </style>
+            <div class="footer-credit">
+                Author <a href="https://github.com/joshanjohn" target="_blank">Joshan John</a>
+            </div>
+            """,
+            unsafe_allow_html=True,
+        )
+
 
 if __name__ == "__main__":
     main()

src/states/__init__.py

@@ -0,0 +1 @@
+from src.states.agent_state import AgentState