WP10 #6
|
|
@ -2,22 +2,17 @@ import streamlit as st
|
|||
import requests
|
||||
import uuid
|
||||
import os
|
||||
import json
|
||||
from datetime import datetime
|
||||
import time
|
||||
from dotenv import load_dotenv
|
||||
|
||||
# --- CONFIGURATION ---
|
||||
# Load .env file explicitly to get timeouts and URLs
|
||||
load_dotenv()
|
||||
|
||||
API_BASE_URL = os.getenv("MINDNET_API_URL", "http://localhost:8002")
|
||||
CHAT_ENDPOINT = f"{API_BASE_URL}/chat"
|
||||
FEEDBACK_ENDPOINT = f"{API_BASE_URL}/feedback"
|
||||
|
||||
# Timeout strategy:
|
||||
# 1. Try MINDNET_API_TIMEOUT (specific for frontend)
|
||||
# 2. Try MINDNET_LLM_TIMEOUT (backend setting)
|
||||
# 3. Default to 300 seconds (5 minutes) for local inference safety
|
||||
# Timeout-Strategie
|
||||
timeout_setting = os.getenv("MINDNET_API_TIMEOUT") or os.getenv("MINDNET_LLM_TIMEOUT")
|
||||
API_TIMEOUT = float(timeout_setting) if timeout_setting else 300.0
|
||||
|
||||
|
|
@ -28,16 +23,10 @@ st.set_page_config(
|
|||
layout="centered"
|
||||
)
|
||||
|
||||
# Custom CSS for cleaner look
|
||||
st.markdown("""
|
||||
<style>
|
||||
.reportview-container { margin-top: -2em; }
|
||||
.stDeployButton {display:none;}
|
||||
.stMainMenu {visibility: hidden;}
|
||||
div[data-testid="stExpander"] div[role="button"] p {
|
||||
font-size: 0.9rem;
|
||||
font-weight: 600;
|
||||
}
|
||||
.intent-badge {
|
||||
background-color: #f0f2f6;
|
||||
border-radius: 5px;
|
||||
|
|
@ -48,202 +37,202 @@ st.markdown("""
|
|||
display: inline-block;
|
||||
border: 1px solid #e0e0e0;
|
||||
}
|
||||
.source-feedback {
|
||||
font-size: 0.8em;
|
||||
color: #888;
|
||||
}
|
||||
</style>
|
||||
""", unsafe_allow_html=True)
|
||||
|
||||
# --- SESSION STATE INITIALIZATION ---
|
||||
# --- SESSION STATE ---
|
||||
if "messages" not in st.session_state:
|
||||
st.session_state.messages = []
|
||||
if "user_id" not in st.session_state:
|
||||
st.session_state.user_id = str(uuid.uuid4())
|
||||
|
||||
# --- API CLIENT FUNCTIONS ---
|
||||
# --- API FUNCTIONS ---
|
||||
|
||||
def send_chat_message(message: str, top_k: int, explain: bool):
|
||||
"""Sends the user message to the FastAPI backend."""
|
||||
payload = {
|
||||
"message": message,
|
||||
"top_k": top_k,
|
||||
"explain": explain
|
||||
}
|
||||
payload = {"message": message, "top_k": top_k, "explain": explain}
|
||||
try:
|
||||
# Use the configured timeout from .env
|
||||
response = requests.post(CHAT_ENDPOINT, json=payload, timeout=API_TIMEOUT)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
except requests.exceptions.ReadTimeout:
|
||||
return {"error": f"Timeout: Das Backend hat nicht innerhalb von {int(API_TIMEOUT)} Sekunden geantwortet. (Local LLM is busy)."}
|
||||
except requests.exceptions.ConnectionError:
|
||||
return {"error": f"Backend nicht erreichbar unter {API_BASE_URL}. Läuft der Server?"}
|
||||
return {"error": f"Timeout ({int(API_TIMEOUT)}s). Das lokale LLM rechnet noch."}
|
||||
except Exception as e:
|
||||
return {"error": str(e)}
|
||||
|
||||
def send_feedback(query_id: str, score: int):
|
||||
"""Sends feedback to the backend."""
|
||||
# Note: We rate the overall answer. API expects node_id.
|
||||
# We use 'generated_answer' as a convention for the full response.
|
||||
def submit_feedback(query_id: str, node_id: str, score: int, comment: str = None):
|
||||
"""Sendet Feedback asynchron."""
|
||||
payload = {
|
||||
"query_id": query_id,
|
||||
"node_id": "generated_answer",
|
||||
"node_id": node_id,
|
||||
"score": score,
|
||||
"comment": "User feedback via Streamlit UI"
|
||||
"comment": comment
|
||||
}
|
||||
try:
|
||||
requests.post(FEEDBACK_ENDPOINT, json=payload, timeout=5)
|
||||
return True
|
||||
except:
|
||||
return False
|
||||
# Wir nutzen st.toast für dezentes Feedback ohne Rerun
|
||||
target = "Antwort" if node_id == "generated_answer" else "Quelle"
|
||||
st.toast(f"Feedback für {target} gespeichert! (Score: {score})")
|
||||
except Exception as e:
|
||||
st.error(f"Feedback-Fehler: {e}")
|
||||
|
||||
# --- UI COMPONENTS ---
|
||||
|
||||
def render_sidebar():
|
||||
with st.sidebar:
|
||||
st.header("⚙️ Konfiguration")
|
||||
st.markdown(f"**Backend:** `{API_BASE_URL}`")
|
||||
st.caption(f"⏱️ Timeout: {int(API_TIMEOUT)}s")
|
||||
st.caption(f"Backend: `{API_BASE_URL}`")
|
||||
|
||||
st.markdown("---")
|
||||
st.subheader("Retrieval Settings")
|
||||
top_k = st.slider("Quellen (Top-K)", min_value=1, max_value=10, value=5)
|
||||
explain_mode = st.checkbox("Explanation Layer", value=True, help="Zeigt an, warum Quellen gewählt wurden.")
|
||||
st.subheader("Retrieval")
|
||||
top_k = st.slider("Quellen Anzahl", 1, 10, 5)
|
||||
explain_mode = st.toggle("Explanation Layer", value=True)
|
||||
|
||||
st.markdown("---")
|
||||
st.markdown("### 🧠 System Status")
|
||||
st.info(f"**Version:** v2.3.1\n\n**Modules:**\n- Decision Engine: ✅\n- Hybrid Router: ✅\n- Feedback Loop: ✅")
|
||||
|
||||
if st.button("Clear Chat History"):
|
||||
st.divider()
|
||||
st.info("WP-10: Advanced Feedback Loop Active")
|
||||
if st.button("Reset Chat"):
|
||||
st.session_state.messages = []
|
||||
st.rerun()
|
||||
|
||||
return top_k, explain_mode
|
||||
|
||||
def render_intent_badge(intent, source):
|
||||
"""Visualizes the Decision Engine state."""
|
||||
icon = "🧠"
|
||||
if intent == "EMPATHY": icon = "❤️"
|
||||
elif intent == "DECISION": icon = "⚖️"
|
||||
elif intent == "CODING": icon = "💻"
|
||||
elif intent == "FACT": icon = "📚"
|
||||
return f"""<div class="intent-badge">{icon} <b>Intent:</b> {intent} <span style="color:#999">({source})</span></div>"""
|
||||
|
||||
return f"""
|
||||
<div class="intent-badge">
|
||||
{icon} <b>Intent:</b> {intent} <span style="color:#999">({source})</span>
|
||||
</div>
|
||||
def render_sources(sources, query_id):
|
||||
"""
|
||||
Rendert Quellen inklusive granularem Feedback-Mechanismus.
|
||||
"""
|
||||
|
||||
def render_sources(sources):
|
||||
"""Renders the retrieved sources in expandable cards."""
|
||||
if not sources:
|
||||
return
|
||||
|
||||
st.markdown("#### 📚 Verwendete Quellen")
|
||||
|
||||
for idx, hit in enumerate(sources):
|
||||
score = hit.get('total_score', 0)
|
||||
node_id = hit.get('node_id')
|
||||
title = hit.get('note_id', 'Unbekannt')
|
||||
payload = hit.get('payload', {})
|
||||
note_type = payload.get('type', 'unknown')
|
||||
title = hit.get('note_id', 'Unbekannt')
|
||||
|
||||
# Determine Header Color/Icon based on score
|
||||
# Icon basierend auf Score
|
||||
score_icon = "🟢" if score > 0.8 else "🟡" if score > 0.5 else "⚪"
|
||||
expander_title = f"{score_icon} {title} (Typ: {note_type}, Score: {score:.2f})"
|
||||
|
||||
with st.expander(f"{score_icon} {title} (Typ: {note_type}, Score: {score:.2f})"):
|
||||
# Content
|
||||
content = hit.get('source', {}).get('text', 'Kein Text verfügbar.')
|
||||
st.markdown(f"_{content[:300]}..._")
|
||||
with st.expander(expander_title):
|
||||
# 1. Inhalt
|
||||
text = hit.get('source', {}).get('text', 'Kein Text')
|
||||
st.markdown(f"_{text[:300]}..._")
|
||||
|
||||
# Explanation (WP-04b)
|
||||
explanation = hit.get('explanation')
|
||||
if explanation:
|
||||
st.markdown("---")
|
||||
st.caption("**Warum wurde das gefunden?**")
|
||||
reasons = explanation.get('reasons', [])
|
||||
for r in reasons:
|
||||
# 2. Explanation (Why-Layer)
|
||||
if 'explanation' in hit and hit['explanation']:
|
||||
st.caption("**Warum gefunden?**")
|
||||
for r in hit['explanation'].get('reasons', []):
|
||||
st.caption(f"- {r.get('message')}")
|
||||
|
||||
# --- MAIN APP LOGIC ---
|
||||
# 3. Granulares Feedback (Source Level)
|
||||
st.markdown("---")
|
||||
c1, c2 = st.columns([3, 1])
|
||||
with c1:
|
||||
st.caption("War diese Quelle hilfreich für die Antwort?")
|
||||
with c2:
|
||||
# Callback Wrapper für Source-Feedback
|
||||
def on_source_fb(qid=query_id, nid=node_id, k=f"fb_src_{node_id}"):
|
||||
val = st.session_state.get(k)
|
||||
# Mapping: Thumbs Up (1) -> Score 5, Thumbs Down (0) -> Score 1
|
||||
mapped_score = 5 if val == 1 else 1
|
||||
submit_feedback(qid, nid, mapped_score, comment="Source Feedback via UI")
|
||||
|
||||
top_k_setting, explain_setting = render_sidebar()
|
||||
st.feedback(
|
||||
"thumbs",
|
||||
key=f"fb_src_{query_id}_{node_id}", # Unique Key pro Query/Node
|
||||
on_change=on_source_fb,
|
||||
kwargs={"qid": query_id, "nid": node_id, "k": f"fb_src_{query_id}_{node_id}"}
|
||||
)
|
||||
|
||||
# --- MAIN APP ---
|
||||
|
||||
top_k, show_explain = render_sidebar()
|
||||
st.title("mindnet v2.3.1")
|
||||
st.caption("Lead Frontend Architect Edition | WP-10 Chat Interface")
|
||||
|
||||
# 1. Render History
|
||||
# 1. Chat History Rendern
|
||||
for msg in st.session_state.messages:
|
||||
with st.chat_message(msg["role"]):
|
||||
if msg["role"] == "assistant":
|
||||
# Render Meta-Data first
|
||||
# Meta-Daten
|
||||
if "intent" in msg:
|
||||
st.markdown(render_intent_badge(msg["intent"], msg.get("intent_source", "?")), unsafe_allow_html=True)
|
||||
|
||||
# Antwort-Text
|
||||
st.markdown(msg["content"])
|
||||
|
||||
# Render Sources
|
||||
# Quellen (mit Feedback-Option, aber Status ist readonly für alte Nachrichten in Streamlit oft schwierig,
|
||||
# daher rendern wir Feedback-Controls idealerweise nur für die letzte Nachricht oder speichern Status)
|
||||
# In dieser Version rendern wir sie immer, Streamlit State managed das.
|
||||
if "sources" in msg:
|
||||
render_sources(msg["sources"])
|
||||
render_sources(msg["sources"], msg["query_id"])
|
||||
|
||||
# Render Latency info
|
||||
if "latency_ms" in msg:
|
||||
st.caption(f"⏱️ Antwortzeit: {msg['latency_ms']}ms | Query-ID: `{msg.get('query_id')}`")
|
||||
# Globales Feedback (Sterne)
|
||||
qid = msg["query_id"]
|
||||
|
||||
def on_global_fb(q=qid, k=f"fb_glob_{qid}"):
|
||||
val = st.session_state.get(k) # Liefert 0-4
|
||||
if val is not None:
|
||||
submit_feedback(q, "generated_answer", val + 1, comment="Global Star Rating")
|
||||
|
||||
st.caption("Wie gut war diese Antwort?")
|
||||
st.feedback(
|
||||
"stars",
|
||||
key=f"fb_glob_{qid}",
|
||||
on_change=on_global_fb
|
||||
)
|
||||
|
||||
else:
|
||||
st.markdown(msg["content"])
|
||||
|
||||
# 2. Handle User Input
|
||||
if prompt := st.chat_input("Was beschäftigt dich?"):
|
||||
# Add User Message
|
||||
# 2. User Input
|
||||
if prompt := st.chat_input("Deine Frage an das System..."):
|
||||
# User Message anzeigen
|
||||
st.session_state.messages.append({"role": "user", "content": prompt})
|
||||
with st.chat_message("user"):
|
||||
st.markdown(prompt)
|
||||
|
||||
# Generate Response
|
||||
# API Call
|
||||
with st.chat_message("assistant"):
|
||||
message_placeholder = st.empty()
|
||||
status_placeholder = st.empty()
|
||||
with st.spinner("Thinking..."):
|
||||
resp = send_chat_message(prompt, top_k, show_explain)
|
||||
|
||||
with st.spinner("Thinking... (Decision Engine Active)"):
|
||||
api_response = send_chat_message(prompt, top_k_setting, explain_setting)
|
||||
|
||||
if "error" in api_response:
|
||||
st.error(api_response["error"])
|
||||
if "error" in resp:
|
||||
st.error(resp["error"])
|
||||
else:
|
||||
# Extract data
|
||||
answer = api_response.get("answer", "")
|
||||
intent = api_response.get("intent", "FACT")
|
||||
source = api_response.get("intent_source", "Unknown")
|
||||
query_id = api_response.get("query_id")
|
||||
hits = api_response.get("sources", [])
|
||||
latency = api_response.get("latency_ms", 0)
|
||||
# Daten extrahieren
|
||||
answer = resp.get("answer", "")
|
||||
intent = resp.get("intent", "FACT")
|
||||
source = resp.get("intent_source", "Unknown")
|
||||
query_id = resp.get("query_id")
|
||||
hits = resp.get("sources", [])
|
||||
|
||||
# 1. Show Intent
|
||||
status_placeholder.markdown(render_intent_badge(intent, source), unsafe_allow_html=True)
|
||||
# Sofort rendern (damit User nicht auf Rerun warten muss)
|
||||
st.markdown(render_intent_badge(intent, source), unsafe_allow_html=True)
|
||||
st.markdown(answer)
|
||||
render_sources(hits, query_id)
|
||||
|
||||
# 2. Show Answer
|
||||
message_placeholder.markdown(answer)
|
||||
# Feedback Slot für die NEUE Nachricht vorbereiten
|
||||
st.caption("Wie gut war diese Antwort?")
|
||||
st.feedback("stars", key=f"fb_glob_{query_id}", on_change=lambda: submit_feedback(query_id, "generated_answer", st.session_state[f"fb_glob_{query_id}"] + 1))
|
||||
|
||||
# 3. Show Sources
|
||||
render_sources(hits)
|
||||
|
||||
# 4. Show Latency & Feedback UI
|
||||
st.caption(f"⏱️ {latency}ms | ID: `{query_id}`")
|
||||
|
||||
# Feedback Buttons
|
||||
col1, col2, col3, col4 = st.columns([1,1,1,4])
|
||||
with col1:
|
||||
if st.button("👍", key=f"up_{query_id}"):
|
||||
send_feedback(query_id, 5)
|
||||
st.toast("Feedback gesendet: Positiv!")
|
||||
with col2:
|
||||
if st.button("👎", key=f"down_{query_id}"):
|
||||
send_feedback(query_id, 1)
|
||||
st.toast("Feedback gesendet: Negativ.")
|
||||
|
||||
# Save to history
|
||||
# In History speichern
|
||||
st.session_state.messages.append({
|
||||
"role": "assistant",
|
||||
"content": answer,
|
||||
"intent": intent,
|
||||
"intent_source": source,
|
||||
"sources": hits,
|
||||
"query_id": query_id,
|
||||
"latency_ms": latency
|
||||
"query_id": query_id
|
||||
})
|
||||
|
|
@ -6,7 +6,7 @@ Zweck:
|
|||
WP-06 Update: Intent & Intent-Source in ChatResponse.
|
||||
|
||||
Version:
|
||||
0.6.1 (WP-06: Decision Engine Transparency)
|
||||
0.6.2 (WP-06: Decision Engine Transparency, Erweiterung des Feeback Request)
|
||||
Stand:
|
||||
2025-12-09
|
||||
"""
|
||||
|
|
@ -64,11 +64,14 @@ class QueryRequest(BaseModel):
|
|||
|
||||
class FeedbackRequest(BaseModel):
|
||||
"""
|
||||
User-Feedback zu einem spezifischen Treffer.
|
||||
User-Feedback zu einem spezifischen Treffer oder der Gesamtantwort.
|
||||
"""
|
||||
query_id: str = Field(..., description="ID der ursprünglichen Suche")
|
||||
node_id: str = Field(..., description="ID des bewerteten Treffers")
|
||||
score: int = Field(..., ge=0, le=1, description="1 (Positiv) oder 0 (Negativ/Irrelevant)")
|
||||
# node_id ist optional: Wenn leer oder "generated_answer", gilt es für die Antwort.
|
||||
# Wenn eine echte Chunk-ID, gilt es für die Quelle.
|
||||
node_id: str = Field(..., description="ID des bewerteten Treffers oder 'generated_answer'")
|
||||
# Update: Range auf 1-5 erweitert für differenziertes Tuning
|
||||
score: int = Field(..., ge=1, le=5, description="1 (Irrelevant/Falsch) bis 5 (Perfekt)")
|
||||
comment: Optional[str] = None
|
||||
|
||||
|
||||
|
|
@ -153,3 +156,5 @@ class ChatResponse(BaseModel):
|
|||
latency_ms: int
|
||||
intent: Optional[str] = Field("FACT", description="WP-06: Erkannter Intent (FACT/DECISION)")
|
||||
intent_source: Optional[str] = Field("Unknown", description="WP-06: Quelle der Intent-Erkennung (Keyword vs. LLM)")
|
||||
|
||||
|
||||
Loading…
Reference in New Issue
Block a user