Spaces:
Running
Running
File size: 1,282 Bytes
b31069e b3efaf6 f1342ba b31069e bc557f4 f1342ba 6237635 f1342ba c2f2340 f1342ba 4a49352 42117bb f1342ba e1bcbc6 f1342ba e1bcbc6 b31069e f1342ba |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 |
import streamlit as st
import dotenv
import os
def main():
dotenv.load_dotenv(dotenv_path=os.path.join('.streamlit', '.env'))
st.set_page_config(page_title="RAG Agent", page_icon="🤖", layout="wide")
audit_page = st.Page("audit_page/audit.py", title="Audit", icon="📋", default=True)
dialog_page = st.Page("audit_page/dialogue_doc.py", title="Dialoguer avec le document", icon="💬")
kg_page = st.Page("audit_page/knowledge_graph.py", title="Graphe de connaissance", icon="🧠")
agents_page = st.Page("agents_page/catalogue.py", title="Catalogue des agents", icon="📇")
compte_rendu = st.Page("audit_page/compte_rendu.py", title="Compte rendu", icon="📝")
recommended_agents = st.Page("agents_page/recommended_agent.py", title="Agents recommandés", icon="⭐")
chatbot = st.Page("chatbot_page/chatbot.py", title="Chatbot", icon="💬")
documentation = st.Page("doc_page/documentation.py", title="Documentation", icon="📚")
pg = st.navigation(
{
"Audit de contenus": [audit_page,dialog_page],
"Equipe d'agents IA": [recommended_agents],
"Chatbot": [chatbot],
"Documentation": [documentation]
}
)
pg.run()
if __name__ == "__main__":
main() |