MyChatbot / src /streamlit_app.py
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import streamlit as st
from chat_langraph import system, workflow, HumanMessage, AIMessage, get_all_chat_ids, ToolMessage
import uuid
import os
import base64
st.set_page_config(layout="wide")
st.title("College Chatbot")
TEMP_DIR = "/tmp"
os.makedirs(TEMP_DIR, exist_ok=True)
# --- Helpers ---
def set_title(messages):
if messages:
title = "New Chat"
st.session_state.chat_dict[st.session_state.current_chat_id] = title
def set_config():
return {"configurable": {"thread_id": st.session_state.current_chat_id}}
def load_session_state():
if "chats" not in st.session_state:
st.session_state.chats = get_all_chat_ids()
if "current_chat_id" not in st.session_state:
if len(st.session_state.chats) > 0:
st.session_state.current_chat_id = st.session_state.chats[-1]
else:
new_id = str(uuid.uuid4())
st.session_state.chats.append(new_id)
st.session_state.current_chat_id = new_id
if "chat_dict" not in st.session_state:
st.session_state.chat_dict = {}
def render_sidebar():
with st.sidebar:
st.title("Chats")
if st.button("➕ New Chat"):
new_id = str(uuid.uuid4())
st.session_state.chats.append(new_id)
st.session_state.current_chat_id = new_id
config = {"configurable": {"thread_id": new_id}}
workflow.update_state(config, {"messages": [system]})
st.session_state.chat_dict[new_id] = "New Chat"
for chat_id in st.session_state.chats:
if st.button(st.session_state.chat_dict.get(chat_id, "New Chat"), key=chat_id):
st.session_state.current_chat_id = chat_id
def create_download_link(file_path: str, label: str = None) -> str:
"""Generate HTML download link for a file."""
if not os.path.exists(file_path):
return ""
try:
with open(file_path, "rb") as f:
data = f.read()
b64 = base64.b64encode(data).decode()
label = label or f"📥 Download {os.path.basename(file_path)}"
href = f'<a href="data:file/octet-stream;base64,{b64}" download="{os.path.basename(file_path)}">{label}</a>'
return href
except Exception as e:
return f"Error creating download link: {e}"
def show_file(file_path: str):
"""Show file inline + download link."""
if not os.path.exists(file_path):
return
ext = os.path.splitext(file_path)[1].lower()
if ext in [".png", ".jpg", ".jpeg"]:
st.image(file_path, caption=os.path.basename(file_path))
elif ext in [".txt", ".py", ".java", ".cpp", ".md"]:
with open(file_path, "r", encoding="utf-8", errors="ignore") as f:
st.code(f.read(), language=ext.lstrip("."))
st.markdown(create_download_link(file_path), unsafe_allow_html=True)
def render_tool_message(tool_message: ToolMessage):
"""Render tool execution based on tool name instead of message content."""
file_related_keywords = ["read", "write", "file", "save", "export", "create"]
with st.chat_message("assistant"):
tool_name = getattr(tool_message, "name", "").lower()
st.info(f"🧰 Tool used: {tool_name or 'Unknown Tool'}")
# Check if this is a file-related tool
if any(k in tool_name for k in file_related_keywords):
# Find all files in TEMP_DIR (freshly modified ones)
created_files = sorted(
[os.path.join(TEMP_DIR, f) for f in os.listdir(TEMP_DIR)],
key=lambda x: os.path.getmtime(x),
reverse=True,
)
if created_files:
st.success("📄 File(s) created by tool:")
for file_path in created_files[:3]: # show up to 3 recent
show_file(file_path)
else:
st.warning("No new file detected in /tmp.")
def loadchats():
if "current_chat_id" not in st.session_state:
return []
config = {"configurable": {"thread_id": st.session_state.current_chat_id}}
state = workflow.get_state(config)
messages = state.values.get("messages", [])
for message in messages:
if isinstance(message, HumanMessage):
with st.chat_message("human"):
st.write(message.content)
elif isinstance(message, AIMessage):
with st.chat_message("assistant"):
st.write(message.content)
elif isinstance(message, ToolMessage):
render_tool_message(message)
return messages
# --- Main Chat Flow ---
load_session_state()
render_sidebar()
if "current_chat_id" in st.session_state:
loadchats()
if user_input := st.chat_input("Your message:"):
with st.chat_message("human"):
st.write(user_input)
with st.chat_message("assistant"):
response_placeholder = st.empty()
full_response = ""
for message, metadata in workflow.stream(
{"messages": [system, HumanMessage(user_input)]},
config={"configurable": {"thread_id": st.session_state.current_chat_id}},
stream_mode="messages",
):
if isinstance(message, AIMessage):
full_response += message.content or ""
elif isinstance(message, ToolMessage):
render_tool_message(message)
response_placeholder.markdown(full_response)