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3dbf4e8 | 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 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 | import streamlit as st
import datetime
import requests
from streamlit_extras.add_vertical_space import add_vertical_space
from streamlit_lottie import st_lottie
import streamlit.components.v1 as components
# Senin lokal servislerini doğrudan içeri aktarıyoruz (FastAPI veya Render'a gerek yok!)
from app.services.nlp_triplet import extract_triplets_from_text
from app.services.memory_engine import group_by_author, count_predicates, most_common_subjects
from app.services.graph_builder import build_graph_from_triplets
from app.services.graph_visualizer import visualize_graph
st.set_page_config(page_title="AI Memory Graph", layout="wide", page_icon="🧠")
# Lottie Animasyonu Yükleme
def load_lottieurl(url: str):
r = requests.get(url)
if r.status_code != 200: return None
return r.json()
lottie_ai = load_lottieurl("https://assets9.lottiefiles.com/packages/lf20_touohxv0.json")
col1, col2 = st.columns([4, 1])
with col1:
st.title("🧠 AI Memory Graph")
st.markdown("A visual way to extract and understand multi-user chat memories using NLP + Graphs.")
with col2:
if lottie_ai:
st_lottie(lottie_ai, height=100, key="ai")
add_vertical_space(1)
# Session State Tanımlamaları
if "messages" not in st.session_state:
st.session_state["messages"] = []
if "triplets" not in st.session_state:
st.session_state["triplets"] = []
# --- SOHBET GİRİŞ ALANI ---
st.subheader("💬 Add Chat Messages")
with st.form("message_form", clear_on_submit=True):
col_sender, col_msg = st.columns([1, 3])
with col_sender:
sender = st.text_input("Sender", placeholder="e.g. Erdem")
with col_msg:
text = st.text_input("Message", placeholder="e.g. I recommend using FastAPI for the backend.")
submitted = st.form_submit_button("➕ Add Message")
if submitted and sender and text:
st.session_state["messages"].append({
"sender": sender,
"text": text,
"timestamp": datetime.datetime.utcnow().isoformat()
})
st.success(f"Message added for {sender}!")
# Eklenen mesajları göster
if st.session_state["messages"]:
with st.expander("📑 View Current Messages", expanded=False):
st.json(st.session_state["messages"])
add_vertical_space(1)
# --- İŞLEM BUTONLARI ---
c1, c2, c3 = st.columns(3)
# 1. Triplet Çıkarma İşlemi
with c1:
if st.button("🔍 Extract Triplets", use_container_width=True):
with st.spinner("Analyzing text with SpaCy Transformer..."):
all_triplets = []
for msg in st.session_state["messages"]:
extracted = extract_triplets_from_text(msg["text"])
for triplet in extracted:
triplet["timestamp"] = msg["timestamp"]
triplet["author"] = msg["sender"]
all_triplets.append(triplet)
st.session_state["triplets"] = all_triplets
st.success(f"Extracted {len(all_triplets)} triplets!")
st.json(all_triplets)
# 2. Hafıza Özeti İşlemi
with c2:
if st.button("📝 Memory Summary", use_container_width=True):
if not st.session_state["triplets"]:
st.warning("Please extract triplets first!")
else:
summary = {
"total_triplets": len(st.session_state["triplets"]),
"by_user": group_by_author(st.session_state["triplets"]),
"predicate_counts": count_predicates(st.session_state["triplets"]),
"common_subjects": most_common_subjects(st.session_state["triplets"])
}
st.write("### 📊 Stats")
st.json(summary)
# 3. Grafik Çizdirme İşlemi
with c3:
if st.button("🌐 Show Knowledge Graph", use_container_width=True):
if not st.session_state["triplets"]:
st.warning("Please extract triplets first!")
else:
with st.spinner("Building and rendering graph..."):
# Grafiği oluştur
G = build_graph_from_triplets(st.session_state["triplets"])
# HTML olarak kaydet (webbrowser.open KESİNLİKLE KAPALI OLMALI)
visualize_graph(G, output_path="memory_graph.html")
# Kaydedilen HTML'i Streamlit içine göm
try:
with open("memory_graph.html", "r", encoding="utf-8") as f:
html_content = f.read()
st.write("### 🕸️ Graph Visualization")
components.html(html_content, height=600, scrolling=True)
except FileNotFoundError:
st.error("Graph HTML file could not be generated.")
# Footer
add_vertical_space(3)
st.markdown("---")
st.caption("Developed by Erdem Yavuz Hacisoftaoglu | Powered by SpaCy, NetworkX & Streamlit") |