Create app.py

app.py

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+import streamlit as st
+import uuid
+import os
+import re
+from pydantic import BaseModel, Field
+
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.messages import BaseMessage
+from langchain_core.runnables.history import RunnableWithMessageHistory
+from langchain_core.runnables import ConfigurableFieldSpec
+from langchain_core.chat_history import BaseChatMessageHistory
+from langchain_groq import ChatGroq
+
+# --- Load environment variables from .env ---
+groq_api_key = os.environ["GROQ_API_KEY"]
+
+
+# --- In-memory session-based history ---
+class InMemoryHistory(BaseChatMessageHistory, BaseModel):
+    messages: list[BaseMessage] = Field(default_factory=list)
+
+    def add_messages(self, messages: list[BaseMessage]) -> None:
+        self.messages.extend(messages)
+
+    def clear(self) -> None:
+        self.messages = []
+
+store = {}
+def get_by_session_id(session_id: str) -> BaseChatMessageHistory:
+    if session_id not in store:
+        store[session_id] = InMemoryHistory()
+    return store[session_id]
+
+# --- Prompt Template ---
+prompt = ChatPromptTemplate.from_messages([
+    ("system", "You are an intelligent AI bot which assists in counselling people of all domains. Answer in a friendly, age-appropriate tone. Try your best to solve the user's problem. Never talk about killing or dying."),
+    ("system", "Person Name: {person_name}\nAge: {age}\nTalk responsibly according to the user's age. Refrain from bad language or harsh topics."),
+    ("system", "If user asks about your work say you are an AI counseller to colunsl them"),
+    ("system", "If user asks about who made you: you were made by Mercy AI tech team"),
+    MessagesPlaceholder(variable_name="history"),
+    ("human", "{question}")
+])
+
+model = ChatGroq(
+    groq_api_key=groq_api_key,
+    model_name="llama3-8b-8192"
+)
+
+chain = prompt | model
+
+# --- Chain with History Management ---
+chain_with_history = RunnableWithMessageHistory(
+    chain,
+    get_session_history=get_by_session_id,
+    input_messages_key="question",
+    history_messages_key="history",
+    history_factory_config=[
+        ConfigurableFieldSpec(
+            id="session_id",
+            annotation=str,
+            name="Session ID",
+            description="Conversation session ID.",
+            default="default-session",
+            is_shared=True,
+        )
+    ]
+)
+
+# --- Streamlit UI ---
+st.set_page_config(page_title="Mercy AI", layout="centered")
+st.title("🤖 Mercy AI — Your AI Companion")
+st.subheader("Your journey matters. I'm here to listen, support, and guide you.")
+
+session_id = str(uuid.uuid4())  # You can also use a static ID if preferred.
+
+with st.sidebar:
+    st.header("Info")
+    person_name = st.text_input("Name")
+    age = st.text_input("Age")
+    st.session_state['session_id'] = session_id  
+
+# --- Input Validation ---
+def is_valid_name(name):
+    return bool(re.fullmatch(r"[A-Za-z\s]{2,50}", name.strip()))
+
+def is_valid_age(age_str):
+    return age_str.isdigit() and 5 <= int(age_str) <= 100
+
+if not person_name or not age:
+    st.warning("Please enter your name and age to start.")
+    st.stop()
+
+if not is_valid_name(person_name):
+    st.error("Invalid name. Use only letters and spaces (2-50 characters).")
+    st.stop()
+
+if not is_valid_age(age):
+    st.error("Invalid age. Enter a number between 5 and 120.")
+    st.stop()
+
+# --- Chat History Setup ---
+if "chat_history" not in st.session_state:
+    st.session_state.chat_history = []
+
+st.markdown("Type your question below:")
+
+user_input = st.chat_input("Ask something...")
+
+if user_input:
+    with st.spinner("Processing... Please wait."):
+        response = chain_with_history.invoke(
+            {
+                "person_name": person_name.strip(),
+                "age": age,
+                "question": user_input
+            },
+            config={"configurable": {"session_id": session_id}}
+        )
+        st.session_state.chat_history.append(("user", user_input))
+        st.session_state.chat_history.append(("bot", response.content))
+
+# --- Display chat messages ---
+for role, msg in st.session_state.chat_history:
+    with st.chat_message("user" if role == "user" else "assistant"):
+        st.markdown(msg)