Update app.py
Browse files
app.py
CHANGED
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## 1. FastAPI λ°±μλ (backend.py)
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```python
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from fastapi import FastAPI, HTTPException
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from fastapi.middleware.cors import CORSMiddleware
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from pydantic import BaseModel
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from typing import List, Optional, Dict, Any
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import os
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import httpx
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import asyncio
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import json
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from datetime import datetime
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import logging
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# λ‘κΉ
μ€μ
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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app = FastAPI(title="Collaborative LLM System")
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# CORS μ€μ
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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# νκ²½ λ³μμμ ν ν° κ°μ Έμ€κΈ°
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FRIENDLI_TOKEN = os.getenv("FRIENDLI_TOKEN")
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if not FRIENDLI_TOKEN:
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raise ValueError("FRIENDLI_TOKEN νκ²½ λ³μκ° μ€μ λμ§ μμμ΅λλ€.")
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API_URL = "https://api.friendli.ai/dedicated/v1/chat/completions"
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MODEL_ID = "dep89a2fld32mcm"
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#
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role: str
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content: str
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class
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user_query: str
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max_iterations: int = 3
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role: str
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timestamp: str
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- μ 체μ μΈ λ°©ν₯κ³Ό νλ μμν¬λ₯Ό μ μν©λλ€.
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- μ€νμ AIμ λ΅λ³μ κ²ν νκ³ κ°μ μ μ μ μν©λλ€.
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- ꡬ쑰μ μ΄κ³ 체κ³μ μΈ μ κ·Όμ μΆκ΅¬ν©λλ€.""",
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"executor": """λΉμ μ μΈλΆμ μΈ λ΄μ©μ ꡬννλ μ€νμ AIμ
λλ€.
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- κ°λ
μ AIμ μ§μΉ¨μ λ°λΌ ꡬ체μ μΈ λ΄μ©μ μμ±ν©λλ€.
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- μ€μ©μ μ΄κ³ μ€ν κ°λ₯ν μΈλΆ μ¬νμ μ§μ€ν©λλ€.
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- νμμ κ°λ
μμκ² μΆκ° μ§μΉ¨μ μμ²ν©λλ€."""
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}
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# λ©μμ§ κ΅¬μ±
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full_messages = [
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{"role": "system", "content": system_prompts.get(role, "")},
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*messages
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]
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headers = {
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"Authorization": f"Bearer {FRIENDLI_TOKEN}",
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"Content-Type": "application/json"
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}
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"
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try:
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data = response.json()
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return data["choices"][0]["message"]["content"]
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except Exception as e:
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logger.error(f"LLM
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# API μλν¬μΈνΈ
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@app.post("/api/llm/single")
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async def single_llm_call(request: LLMRequest):
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"""λ¨μΌ LLM νΈμΆ"""
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messages = [{"role": msg.role, "content": msg.content} for msg in request.messages]
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if request.stream:
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async def generate():
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async for chunk in call_llm(messages, request.role, stream=True):
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yield chunk
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return generate()
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else:
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content = await call_llm(messages, request.role, stream=False)
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return LLMResponse(
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content=content,
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role=request.role,
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timestamp=datetime.now().isoformat()
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)
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@app.post("/api/llm/collaborate")
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async def collaborative_process(request: CollaborativeRequest):
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"""νλ ₯μ LLM μ²λ¦¬"""
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user_query = request.user_query
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conversation_log = []
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μ΄ μ§λ¬Έμ λν μ 체μ μΈ μ κ·Ό λ°©ν₯κ³Ό νλ μμν¬λ₯Ό μ μν΄μ£ΌμΈμ.
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ν΅μ¬ μμμ κ³ λ €μ¬νμ ꡬ쑰ννμ¬ μ€λͺ
ν΄μ£ΌμΈμ."""
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supervisor_response = ""
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async for chunk in call_llm([{"role": "user", "content": supervisor_prompt}], "supervisor"):
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supervisor_response += chunk
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conversation_log.append({
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"role": "supervisor",
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"stage": "initial_analysis",
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"content": supervisor_response,
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"timestamp": datetime.now().isoformat()
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})
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executor_response = ""
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async for chunk in call_llm([{"role": "user", "content": executor_prompt}], "executor"):
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executor_response += chunk
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# 3λ¨κ³: κ°λ
μ AIμ κ²ν λ° νΌλλ°±
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review_prompt = f"""μ¬μ©μ μ§λ¬Έ: {user_query}
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μ€νμ AIμ λ΅λ³:
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{executor_response}
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μ΄ λ΅λ³μ κ²ν νκ³ κ°μ μ κ³Ό μΆκ° κ³ λ €μ¬νμ μ μν΄μ£ΌμΈμ."""
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review_response = ""
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async for chunk in call_llm([{"role": "user", "content": review_prompt}], "supervisor"):
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review_response += chunk
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###
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{user_query}
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### π κ±°μμ λΆμ (κ°λ
μ AI)
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---
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*μ΄ λ΅λ³μ κ±°μμ κ΄μ κ³Ό λ―Έμμ μΈλΆμ¬νμ μ’
ν©νμ¬ μμ±λμμ΅λλ€.*"""
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return {
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"final_result": final_summary,
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"conversation_log": conversation_log,
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"timestamp": datetime.now().isoformat()
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}
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except Exception as e:
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logger.error(f"νλ ₯ μ²λ¦¬ μ€λ₯: {str(e)}")
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raise HTTPException(status_code=500, detail=str(e))
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@app.get("/health")
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async def health_check():
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return {"status": "healthy", "timestamp": datetime.now().isoformat()}
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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```
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## 2. Streamlit νλ‘ νΈμλ (streamlit_app.py)
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```python
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import streamlit as st
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import requests
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import json
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from datetime import datetime
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import time
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import os
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# νμ΄μ§ μ€μ
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st.set_page_config(
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page_title="νλ ₯μ LLM μμ€ν
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page_icon="π€",
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layout="wide",
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initial_sidebar_state="expanded"
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)
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# μ€νμΌ μ€μ
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st.markdown("""
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<style>
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.main-header {
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text-align: center;
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background: linear-gradient(90deg, #667eea 0%, #764ba2 100%);
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-webkit-background-clip: text;
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-webkit-text-fill-color: transparent;
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font-size: 3rem;
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font-weight: bold;
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margin-bottom: 2rem;
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}
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.llm-box {
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background-color: #f0f2f6;
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border-radius: 10px;
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padding: 1rem;
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margin-bottom: 1rem;
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border-left: 4px solid;
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}
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.supervisor-box {
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border-left-color: #667eea;
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}
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.executor-box {
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border-left-color: #764ba2;
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}
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.timestamp {
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font-size: 0.8rem;
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color: #666;
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}
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</style>
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""", unsafe_allow_html=True)
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# λ°±μλ URL
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BACKEND_URL = os.getenv("BACKEND_URL", "http://localhost:8000")
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# μΈμ
μν μ΄κΈ°ν
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if "conversation_history" not in st.session_state:
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st.session_state.conversation_history = []
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if "current_conversation" not in st.session_state:
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st.session_state.current_conversation = None
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# ν€λ
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st.markdown('<h1 class="main-header">π€ νλ ₯μ LLM μμ€ν
</h1>', unsafe_allow_html=True)
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st.markdown("κ±°μμ κ°λ
μ AIμ λ―Έμμ μ€νμ AIκ° νλ ₯νμ¬ μ΅μμ λ΅λ³μ λ§λ€μ΄λ
λλ€.")
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# μ¬μ΄λλ°
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with st.sidebar:
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st.header("βοΈ μ€μ ")
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# λ°±μλ μν νμΈ
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try:
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response = requests.get(f"{BACKEND_URL}/health")
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if response.status_code == 200:
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st.success("β
λ°±μλ μ°κ²°λ¨")
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else:
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st.error("β λ°±μλ μ°κ²° μ€ν¨")
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except:
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st.error("β λ°±μλ μλ²λ₯Ό μμν΄μ£ΌμΈμ")
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st.divider()
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# λν κΈ°λ‘
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st.header("π λν κΈ°λ‘")
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if st.session_state.conversation_history:
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for idx, conv in enumerate(reversed(st.session_state.conversation_history)):
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if st.button(f"π¬ {conv['query'][:30]}...", key=f"hist_{idx}"):
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st.session_state.current_conversation = conv
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else:
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st.info("λν κΈ°λ‘μ΄ μμ΅λλ€.")
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if st.button("ποΈ κΈ°λ‘ μ΄κΈ°ν"):
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st.session_state.conversation_history = []
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st.session_state.current_conversation = None
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st.rerun()
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# λ©μΈ 컨ν
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main_container = st.container()
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# μ§λ¬Έ μ
λ ₯
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with main_container:
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col1, col2 = st.columns([5, 1])
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with col1:
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user_query = st.text_input(
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"μ§λ¬Έμ μ
λ ₯νμΈμ:",
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placeholder="μ: κΈ°κ³νμ΅ λͺ¨λΈμ μ±λ₯μ ν₯μμν€λ λ°©λ²μ?",
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key="user_input"
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)
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with col2:
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process_button = st.button("π λΆμ μμ", type="primary", use_container_width=True)
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# μ²λ¦¬ λ‘μ§
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if process_button and user_query:
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with st.spinner("AIλ€μ΄ νλ ₯νμ¬ λ΅λ³μ μμ±νκ³ μμ΅λλ€..."):
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try:
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# λ°±μλμ μμ²
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response = requests.post(
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f"{BACKEND_URL}/api/llm/collaborate",
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json={"user_query": user_query, "max_iterations": 3}
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)
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"timestamp": datetime.now().isoformat()
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}
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st.session_state.conversation_history.append(conversation)
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st.session_state.current_conversation = conversation
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st.success("β
λΆμ μλ£!")
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else:
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st.error(f"μ€λ₯ λ°μ: {response.status_code}")
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except Exception as e:
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st.markdown("### π μ΅μ’
μ’
ν© κ²°κ³Ό")
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with st.expander("νΌμΉκΈ°", expanded=True):
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st.markdown(conv["result"]["final_result"])
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# λν κ³Όμ
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st.markdown("### π AI νλ ₯ κ³Όμ ")
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# λ κ°μ 컬λΌμΌλ‘ λΆν
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col1, col2 = st.columns(2)
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supervisor_logs = [log for log in conv["result"]["conversation_log"] if log["role"] == "supervisor"]
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executor_logs = [log for log in conv["result"]["conversation_log"] if log["role"] == "executor"]
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with col1:
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st.markdown("#### π§ κ°λ
μ AI (κ±°μμ λΆμ)")
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for log in supervisor_logs:
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with st.container():
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st.markdown(f'<div class="llm-box supervisor-box">', unsafe_allow_html=True)
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st.markdown(f"**{log['stage']}**")
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st.text(log["content"][:500] + "..." if len(log["content"]) > 500 else log["content"])
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st.markdown(f'<span class="timestamp">{log["timestamp"]}</span>', unsafe_allow_html=True)
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st.markdown('</div>', unsafe_allow_html=True)
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with col2:
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st.markdown("#### ποΈ μ€νμ AI (λ―Έμμ ꡬν)")
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for log in executor_logs:
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with st.container():
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st.markdown(f'<div class="llm-box executor-box">', unsafe_allow_html=True)
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st.markdown(f"**{log['stage']}**")
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st.text(log["content"][:500] + "..." if len(log["content"]) > 500 else log["content"])
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st.markdown(f'<span class="timestamp">{log["timestamp"]}</span>', unsafe_allow_html=True)
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st.markdown('</div>', unsafe_allow_html=True)
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# νλ¨ μ 보
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st.divider()
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421 |
-
st.markdown("""
|
422 |
-
<div style="text-align: center; color: #666;">
|
423 |
-
π‘ μ΄ μμ€ν
μ λ AIκ° μλ‘ λ€λ₯Έ κ΄μ μμ μ κ·Όνμ¬ λ λμ λ΅λ³μ λ§λ€μ΄λ
λλ€.<br>
|
424 |
-
κ°λ
μ AIλ μ 체μ μΈ λ°©ν₯μ, μ€νμ AIλ ꡬ체μ μΈ μΈλΆμ¬νμ λ΄λΉν©λλ€.
|
425 |
-
</div>
|
426 |
-
""", unsafe_allow_html=True)
|
427 |
-
```
|
428 |
|
429 |
-
|
430 |
-
|
431 |
-
```python
|
432 |
-
import gradio as gr
|
433 |
-
import requests
|
434 |
-
import json
|
435 |
-
from datetime import datetime
|
436 |
-
import os
|
437 |
-
import asyncio
|
438 |
-
|
439 |
-
# λ°±μλ URL
|
440 |
-
BACKEND_URL = os.getenv("BACKEND_URL", "http://localhost:8000")
|
441 |
-
|
442 |
-
# κΈλ‘λ² λ³μ
|
443 |
-
conversation_history = []
|
444 |
-
|
445 |
-
def check_backend_status():
|
446 |
-
"""λ°±μλ μν νμΈ"""
|
447 |
-
try:
|
448 |
-
response = requests.get(f"{BACKEND_URL}/health")
|
449 |
-
return response.status_code == 200
|
450 |
-
except:
|
451 |
-
return False
|
452 |
|
453 |
def process_query(user_query, history):
|
454 |
-
"""
|
455 |
if not user_query:
|
456 |
-
return history, "", "", "", "μ§λ¬Έμ μ
λ ₯ν΄μ£ΌμΈμ."
|
|
|
|
|
|
|
457 |
|
458 |
try:
|
459 |
-
#
|
460 |
-
|
461 |
-
|
462 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
463 |
)
|
464 |
|
465 |
-
if response.status_code == 200:
|
466 |
-
result = response.json()
|
467 |
-
|
468 |
-
# λν λ‘κ·Έ νμ±
|
469 |
-
supervisor_text = ""
|
470 |
-
executor_text = ""
|
471 |
-
|
472 |
-
for log in result["conversation_log"]:
|
473 |
-
if log["role"] == "supervisor":
|
474 |
-
supervisor_text += f"[{log['stage']}]\n{log['content']}\n\n"
|
475 |
-
else:
|
476 |
-
executor_text += f"[{log['stage']}]\n{log['content']}\n\n"
|
477 |
-
|
478 |
-
# νμ€ν 리 μ
λ°μ΄νΈ
|
479 |
-
new_history = history + [(user_query, result["final_result"])]
|
480 |
-
|
481 |
-
return (
|
482 |
-
new_history,
|
483 |
-
supervisor_text,
|
484 |
-
executor_text,
|
485 |
-
result["final_result"],
|
486 |
-
"β
λΆμ μλ£!"
|
487 |
-
)
|
488 |
-
else:
|
489 |
-
return history, "", "", "", f"β μ€λ₯ λ°μ: {response.status_code}"
|
490 |
-
|
491 |
except Exception as e:
|
492 |
-
|
|
|
493 |
|
494 |
def clear_all():
|
495 |
"""λͺ¨λ λ΄μ© μ΄κΈ°ν"""
|
496 |
-
return [], "", "", "", ""
|
497 |
-
|
498 |
-
# Gradio μΈν°νμ΄μ€
|
499 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
500 |
gr.Markdown(
|
501 |
"""
|
502 |
# π€ νλ ₯μ LLM μμ€ν
|
503 |
|
504 |
-
κ±°μμ κ°λ
μ AIμ λ―Έμμ μ€νμ AIκ° νλ ₯νμ¬ μ΅μμ λ΅λ³μ λ§λ€μ΄λ
λλ€.
|
|
|
|
|
|
|
|
|
|
|
505 |
"""
|
506 |
)
|
507 |
|
508 |
-
# λ°±μλ μν νμ
|
509 |
-
with gr.Row():
|
510 |
-
backend_status = gr.Markdown(
|
511 |
-
"π’ λ°±μλ μ°κ²°λ¨" if check_backend_status() else "π΄ λ°±μλ μ°κ²° μλ¨"
|
512 |
-
)
|
513 |
-
|
514 |
with gr.Row():
|
515 |
# μΌμͺ½: μ
λ ₯ λ° μ±ν
κΈ°λ‘
|
516 |
with gr.Column(scale=1):
|
517 |
chatbot = gr.Chatbot(
|
518 |
label="π¬ λν κΈ°λ‘",
|
519 |
-
height=
|
520 |
-
show_copy_button=True
|
|
|
521 |
)
|
522 |
|
523 |
user_input = gr.Textbox(
|
524 |
label="μ§λ¬Έ μ
λ ₯",
|
525 |
placeholder="μ: κΈ°κ³νμ΅ λͺ¨λΈμ μ±λ₯μ ν₯μμν€λ λ°©λ²μ?",
|
526 |
-
lines=
|
527 |
)
|
528 |
|
529 |
with gr.Row():
|
530 |
-
submit_btn = gr.Button("π λΆμ μμ", variant="primary")
|
531 |
-
clear_btn = gr.Button("ποΈ μ΄κΈ°ν")
|
532 |
|
533 |
status_text = gr.Textbox(
|
534 |
label="μν",
|
535 |
interactive=False,
|
536 |
-
value="λκΈ° μ€..."
|
|
|
537 |
)
|
538 |
|
539 |
# μ€λ₯Έμͺ½: AI μΆλ ₯
|
540 |
with gr.Column(scale=2):
|
541 |
# μ΅μ’
κ²°κ³Ό
|
542 |
-
|
543 |
-
|
544 |
-
|
545 |
-
|
546 |
|
547 |
with gr.Row():
|
548 |
# κ°λ
μ AI μΆλ ₯
|
549 |
with gr.Column():
|
|
|
550 |
supervisor_output = gr.Textbox(
|
551 |
-
label="
|
552 |
lines=15,
|
553 |
max_lines=20,
|
554 |
-
interactive=False
|
|
|
555 |
)
|
556 |
|
557 |
# μ€νμ AI μΆλ ₯
|
558 |
with gr.Column():
|
|
|
559 |
executor_output = gr.Textbox(
|
560 |
-
label="
|
561 |
lines=15,
|
562 |
max_lines=20,
|
563 |
-
interactive=False
|
|
|
564 |
)
|
565 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
566 |
# μ΄λ²€νΈ νΈλ€λ¬
|
567 |
submit_btn.click(
|
568 |
fn=process_query,
|
@@ -587,24 +354,17 @@ with gr.Blocks(title="νλ ₯μ LLM μμ€ν
", theme=gr.themes.Soft()) as app:
|
|
587 |
outputs=[chatbot, supervisor_output, executor_output, final_output, status_text]
|
588 |
)
|
589 |
|
590 |
-
# μμ
|
591 |
-
gr.Examples(
|
592 |
-
examples=[
|
593 |
-
"κΈ°κ³νμ΅ λͺ¨λΈμ μ±λ₯μ ν₯μμν€λ λ°©λ²μ?",
|
594 |
-
"ν¨κ³Όμ μΈ νλ‘μ νΈ κ΄λ¦¬ μ λ΅μ μ립νλ λ°©λ²μ?",
|
595 |
-
"μ§μ κ°λ₯ν λΉμ¦λμ€ λͺ¨λΈμ ꡬμΆνλ λ°©λ²μ?",
|
596 |
-
"볡μ‘ν λ°μ΄ν°λ₯Ό μκ°ννλ μ΅μ μ λ°©λ²μ?"
|
597 |
-
],
|
598 |
-
inputs=user_input
|
599 |
-
)
|
600 |
-
|
601 |
gr.Markdown(
|
602 |
"""
|
603 |
---
|
604 |
-
|
605 |
-
|
606 |
-
|
607 |
-
|
|
|
|
|
|
|
|
|
608 |
"""
|
609 |
)
|
610 |
|
@@ -612,6 +372,6 @@ if __name__ == "__main__":
|
|
612 |
app.launch(
|
613 |
server_name="0.0.0.0",
|
614 |
server_port=7860,
|
615 |
-
share=
|
616 |
show_error=True
|
617 |
-
)
|
|
|
1 |
+
import gradio as gr
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
2 |
import os
|
|
|
|
|
3 |
import json
|
4 |
+
import requests
|
5 |
from datetime import datetime
|
6 |
+
import asyncio
|
7 |
+
import aiohttp
|
8 |
+
from typing import List, Dict, Any
|
9 |
import logging
|
10 |
|
11 |
# λ‘κΉ
μ€μ
|
12 |
logging.basicConfig(level=logging.INFO)
|
13 |
logger = logging.getLogger(__name__)
|
14 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
15 |
# νκ²½ λ³μμμ ν ν° κ°μ Έμ€κΈ°
|
16 |
+
FRIENDLI_TOKEN = os.getenv("FRIENDLI_TOKEN", "YOUR_FRIENDLI_TOKEN")
|
|
|
|
|
|
|
17 |
API_URL = "https://api.friendli.ai/dedicated/v1/chat/completions"
|
18 |
MODEL_ID = "dep89a2fld32mcm"
|
19 |
|
20 |
+
# μ μ λ³μ
|
21 |
+
conversation_history = []
|
|
|
|
|
22 |
|
23 |
+
class LLMCollaborativeSystem:
|
24 |
+
def __init__(self):
|
25 |
+
self.token = FRIENDLI_TOKEN
|
26 |
+
self.api_url = API_URL
|
27 |
+
self.model_id = MODEL_ID
|
28 |
+
|
29 |
+
def create_headers(self):
|
30 |
+
"""API ν€λ μμ±"""
|
31 |
+
return {
|
32 |
+
"Authorization": f"Bearer {self.token}",
|
33 |
+
"Content-Type": "application/json"
|
34 |
+
}
|
35 |
+
|
36 |
+
def create_supervisor_prompt(self, user_query: str, executor_response: str = None) -> str:
|
37 |
+
"""κ°λ
μ AI ν둬ννΈ μμ±"""
|
38 |
+
if executor_response:
|
39 |
+
return f"""λΉμ μ κ±°μμ κ΄μ μμ λΆμνκ³ μ§λνλ κ°λ
μ AIμ
λλ€.
|
40 |
|
41 |
+
μ¬μ©μ μ§λ¬Έ: {user_query}
|
|
|
|
|
42 |
|
43 |
+
μ€νμ AIμ λ΅λ³:
|
44 |
+
{executor_response}
|
|
|
|
|
45 |
|
46 |
+
μ΄ λ΅λ³μ κ²ν νκ³ κ°μ μ κ³Ό μΆκ° κ³ λ €μ¬νμ μ μν΄μ£ΌμΈμ. ꡬ쑰μ μ΄κ³ 체κ³μ μΈ νΌλλ°±μ μ 곡νμΈμ."""
|
47 |
+
else:
|
48 |
+
return f"""λΉμ μ κ±°μμ κ΄μ μμ λΆμνκ³ μ§λνλ κ°λ
μ AIμ
λλ€.
|
49 |
+
|
50 |
+
μ¬μ©μ μ§λ¬Έ: {user_query}
|
51 |
+
|
52 |
+
μ΄ μ§λ¬Έμ λν μ 체μ μΈ μ κ·Ό λ°©ν₯κ³Ό νλ μμν¬λ₯Ό μ μν΄μ£ΌμΈμ. ν΅μ¬ μμμ κ³ λ €μ¬νμ ꡬ쑰ννμ¬ μ€λͺ
ν΄μ£ΌμΈμ."""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
53 |
|
54 |
+
def create_executor_prompt(self, user_query: str, supervisor_guidance: str) -> str:
|
55 |
+
"""μ€νμ AI ν둬ννΈ μμ±"""
|
56 |
+
return f"""λΉμ μ μΈλΆμ μΈ λ΄μ©μ ꡬννλ μ€νμ AIμ
λλ€.
|
57 |
+
|
58 |
+
κ°λ
μ AIμ μ§μΉ¨:
|
59 |
+
{supervisor_guidance}
|
60 |
+
|
61 |
+
μ¬μ©μ μ§λ¬Έ: {user_query}
|
62 |
+
|
63 |
+
μ μ§μΉ¨μ λ°νμΌλ‘ ꡬ체μ μ΄κ³ μ€ν κ°λ₯ν μΈλΆ λ΄μ©μ μμ±ν΄μ£ΌμΈμ. μ€μ©μ μ΄κ³ ꡬν κ°λ₯ν ν΄κ²°μ±
μ μ§μ€νμΈμ."""
|
64 |
|
65 |
+
def call_llm_sync(self, messages: List[Dict[str, str]], role: str) -> str:
|
66 |
+
"""λκΈ°μ LLM API νΈμΆ"""
|
67 |
try:
|
68 |
+
# μν μ λ°λ₯Έ μμ€ν
ν둬ννΈ
|
69 |
+
system_prompts = {
|
70 |
+
"supervisor": "λΉμ μ κ±°μμ κ΄μ μμ λΆμνκ³ μ§λνλ κ°λ
μ AIμ
λλ€.",
|
71 |
+
"executor": "λΉμ μ μΈλΆμ μΈ λ΄μ©μ ꡬννλ μ€νμ AIμ
λλ€."
|
72 |
+
}
|
73 |
+
|
74 |
+
# λ©μμ§ κ΅¬μ±
|
75 |
+
full_messages = [
|
76 |
+
{"role": "system", "content": system_prompts.get(role, "")},
|
77 |
+
*messages
|
78 |
+
]
|
79 |
+
|
80 |
+
payload = {
|
81 |
+
"model": self.model_id,
|
82 |
+
"messages": full_messages,
|
83 |
+
"max_tokens": 2048,
|
84 |
+
"temperature": 0.7,
|
85 |
+
"top_p": 0.8,
|
86 |
+
"stream": False
|
87 |
+
}
|
88 |
+
|
89 |
+
response = requests.post(
|
90 |
+
self.api_url,
|
91 |
+
headers=self.create_headers(),
|
92 |
+
json=payload,
|
93 |
+
timeout=60
|
94 |
+
)
|
95 |
+
|
96 |
+
if response.status_code == 200:
|
97 |
data = response.json()
|
98 |
return data["choices"][0]["message"]["content"]
|
99 |
+
else:
|
100 |
+
logger.error(f"API μ€λ₯: {response.status_code}")
|
101 |
+
return f"API νΈμΆ μ€λ₯: {response.status_code}"
|
102 |
|
103 |
except Exception as e:
|
104 |
+
logger.error(f"LLM νΈμΆ μ€ μ€λ₯: {str(e)}")
|
105 |
+
return f"μ€λ₯ λ°μ: {str(e)}"
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
106 |
|
107 |
+
def process_collaborative(self, user_query: str) -> Dict[str, Any]:
|
108 |
+
"""νλ ₯μ μ²λ¦¬ νλ‘μΈμ€"""
|
109 |
+
conversation_log = []
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
110 |
|
111 |
+
try:
|
112 |
+
# 1λ¨κ³: κ°λ
μ AIμ μ΄κΈ° λΆμ
|
113 |
+
supervisor_prompt = self.create_supervisor_prompt(user_query)
|
114 |
+
supervisor_response = self.call_llm_sync(
|
115 |
+
[{"role": "user", "content": supervisor_prompt}],
|
116 |
+
"supervisor"
|
117 |
+
)
|
|
|
|
|
|
|
|
|
118 |
|
119 |
+
conversation_log.append({
|
120 |
+
"role": "supervisor",
|
121 |
+
"stage": "μ΄κΈ° λΆμ",
|
122 |
+
"content": supervisor_response,
|
123 |
+
"timestamp": datetime.now().strftime("%H:%M:%S")
|
124 |
+
})
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
125 |
|
126 |
+
# 2λ¨κ³: μ€νμ AIμ μΈλΆ ꡬν
|
127 |
+
executor_prompt = self.create_executor_prompt(user_query, supervisor_response)
|
128 |
+
executor_response = self.call_llm_sync(
|
129 |
+
[{"role": "user", "content": executor_prompt}],
|
130 |
+
"executor"
|
131 |
+
)
|
132 |
+
|
133 |
+
conversation_log.append({
|
134 |
+
"role": "executor",
|
135 |
+
"stage": "μΈλΆ ꡬν",
|
136 |
+
"content": executor_response,
|
137 |
+
"timestamp": datetime.now().strftime("%H:%M:%S")
|
138 |
+
})
|
139 |
+
|
140 |
+
# 3λ¨κ³: κ°λ
μ AIμ κ²ν λ° νΌλλ°±
|
141 |
+
review_prompt = self.create_supervisor_prompt(user_query, executor_response)
|
142 |
+
review_response = self.call_llm_sync(
|
143 |
+
[{"role": "user", "content": review_prompt}],
|
144 |
+
"supervisor"
|
145 |
+
)
|
146 |
+
|
147 |
+
conversation_log.append({
|
148 |
+
"role": "supervisor",
|
149 |
+
"stage": "κ²ν λ° νΌλλ°±",
|
150 |
+
"content": review_response,
|
151 |
+
"timestamp": datetime.now().strftime("%H:%M:%S")
|
152 |
+
})
|
153 |
+
|
154 |
+
# 4λ¨κ³: μ΅μ’
μ’
ν©
|
155 |
+
final_summary = f"""## π€ νλ ₯μ AI μμ€ν
μ’
ν© λ΅λ³
|
156 |
|
157 |
+
### π μ¬μ©μ μ§λ¬Έ
|
158 |
{user_query}
|
159 |
|
160 |
### π κ±°μμ λΆμ (κ°λ
μ AI)
|
|
|
168 |
|
169 |
---
|
170 |
*μ΄ λ΅λ³μ κ±°μμ κ΄μ κ³Ό λ―Έμμ μΈλΆμ¬νμ μ’
ν©νμ¬ μμ±λμμ΅λλ€.*"""
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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|
171 |
|
172 |
+
return {
|
173 |
+
"final_result": final_summary,
|
174 |
+
"conversation_log": conversation_log,
|
175 |
+
"supervisor_texts": [log["content"] for log in conversation_log if log["role"] == "supervisor"],
|
176 |
+
"executor_texts": [log["content"] for log in conversation_log if log["role"] == "executor"]
|
177 |
+
}
|
178 |
+
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|
179 |
except Exception as e:
|
180 |
+
logger.error(f"νλ ₯ μ²λ¦¬ μ€λ₯: {str(e)}")
|
181 |
+
return {
|
182 |
+
"final_result": f"μ²λ¦¬ μ€ μ€λ₯κ° λ°μνμ΅λλ€: {str(e)}",
|
183 |
+
"conversation_log": [],
|
184 |
+
"supervisor_texts": [],
|
185 |
+
"executor_texts": []
|
186 |
+
}
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|
187 |
|
188 |
+
# μμ€ν
μΈμ€ν΄μ€ μμ±
|
189 |
+
llm_system = LLMCollaborativeSystem()
|
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|
190 |
|
191 |
def process_query(user_query, history):
|
192 |
+
"""Gradio μΈν°νμ΄μ€λ₯Ό μν 쿼리 μ²λ¦¬ ν¨μ"""
|
193 |
if not user_query:
|
194 |
+
return history, "", "", "", "β μ§λ¬Έμ μ
λ ₯ν΄μ£ΌμΈμ."
|
195 |
+
|
196 |
+
# μ²λ¦¬ μμ
|
197 |
+
status = "π AIλ€μ΄ νλ ₯νμ¬ λ΅λ³μ μμ±νκ³ μμ΅λλ€..."
|
198 |
|
199 |
try:
|
200 |
+
# νλ ₯μ μ²λ¦¬
|
201 |
+
result = llm_system.process_collaborative(user_query)
|
202 |
+
|
203 |
+
# κ°λ
μμ μ€νμ ν
μ€νΈ ν¬λ§·ν
|
204 |
+
supervisor_text = "\n\n---\n\n".join([
|
205 |
+
f"[{log['stage']}] - {log['timestamp']}\n{log['content']}"
|
206 |
+
for log in result["conversation_log"] if log["role"] == "supervisor"
|
207 |
+
])
|
208 |
+
|
209 |
+
executor_text = "\n\n---\n\n".join([
|
210 |
+
f"[{log['stage']}] - {log['timestamp']}\n{log['content']}"
|
211 |
+
for log in result["conversation_log"] if log["role"] == "executor"
|
212 |
+
])
|
213 |
+
|
214 |
+
# νμ€ν 리 μ
λ°μ΄νΈ
|
215 |
+
new_history = history + [(user_query, result["final_result"])]
|
216 |
+
|
217 |
+
return (
|
218 |
+
new_history,
|
219 |
+
supervisor_text,
|
220 |
+
executor_text,
|
221 |
+
result["final_result"],
|
222 |
+
"β
λΆμ μλ£!"
|
223 |
)
|
224 |
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|
225 |
except Exception as e:
|
226 |
+
error_msg = f"β μ²λ¦¬ μ€ μ€λ₯: {str(e)}"
|
227 |
+
return history, "", "", error_msg, error_msg
|
228 |
|
229 |
def clear_all():
|
230 |
"""λͺ¨λ λ΄μ© μ΄κΈ°ν"""
|
231 |
+
return [], "", "", "", "π μ΄κΈ°νλμμ΅λλ€."
|
232 |
+
|
233 |
+
# Gradio μΈν°νμ΄μ€
|
234 |
+
css = """
|
235 |
+
.gradio-container {
|
236 |
+
font-family: 'Arial', sans-serif;
|
237 |
+
}
|
238 |
+
.supervisor-box {
|
239 |
+
border-left: 4px solid #667eea;
|
240 |
+
padding-left: 10px;
|
241 |
+
}
|
242 |
+
.executor-box {
|
243 |
+
border-left: 4px solid #764ba2;
|
244 |
+
padding-left: 10px;
|
245 |
+
}
|
246 |
+
"""
|
247 |
+
|
248 |
+
with gr.Blocks(title="νλ ₯μ LLM μμ€ν
", theme=gr.themes.Soft(), css=css) as app:
|
249 |
gr.Markdown(
|
250 |
"""
|
251 |
# π€ νλ ₯μ LLM μμ€ν
|
252 |
|
253 |
+
> κ±°μμ κ°λ
μ AIμ λ―Έμμ μ€νμ AIκ° νλ ₯νμ¬ μ΅μμ λ΅λ³μ λ§λ€μ΄λ
λλ€.
|
254 |
+
|
255 |
+
**μμ€ν
ꡬ쑰:**
|
256 |
+
- π§ **κ°λ
μ AI**: μ 체μ μΈ λ°©ν₯κ³Ό νλ μμν¬λ₯Ό μ μ
|
257 |
+
- ποΈ **μ€νμ AI**: ꡬ체μ μ΄κ³ μ€ν κ°λ₯ν μΈλΆμ¬νμ μμ±
|
258 |
+
- π **νλ ₯ νλ‘μΈμ€**: μνΈ νΌλλ°±μ ν΅ν λ΅λ³ κ°μ
|
259 |
"""
|
260 |
)
|
261 |
|
|
|
|
|
|
|
|
|
|
|
|
|
262 |
with gr.Row():
|
263 |
# μΌμͺ½: μ
λ ₯ λ° μ±ν
κΈ°λ‘
|
264 |
with gr.Column(scale=1):
|
265 |
chatbot = gr.Chatbot(
|
266 |
label="π¬ λν κΈ°λ‘",
|
267 |
+
height=500,
|
268 |
+
show_copy_button=True,
|
269 |
+
bubble_full_width=False
|
270 |
)
|
271 |
|
272 |
user_input = gr.Textbox(
|
273 |
label="μ§λ¬Έ μ
λ ₯",
|
274 |
placeholder="μ: κΈ°κ³νμ΅ λͺ¨λΈμ μ±λ₯μ ν₯μμν€λ λ°©λ²μ?",
|
275 |
+
lines=3
|
276 |
)
|
277 |
|
278 |
with gr.Row():
|
279 |
+
submit_btn = gr.Button("π λΆμ μμ", variant="primary", scale=2)
|
280 |
+
clear_btn = gr.Button("ποΈ μ΄κΈ°ν", scale=1)
|
281 |
|
282 |
status_text = gr.Textbox(
|
283 |
label="μν",
|
284 |
interactive=False,
|
285 |
+
value="λκΈ° μ€...",
|
286 |
+
max_lines=1
|
287 |
)
|
288 |
|
289 |
# μ€λ₯Έμͺ½: AI μΆλ ₯
|
290 |
with gr.Column(scale=2):
|
291 |
# μ΅μ’
κ²°κ³Ό
|
292 |
+
with gr.Accordion("π μ΅μ’
μ’
ν© κ²°κ³Ό", open=True):
|
293 |
+
final_output = gr.Markdown(
|
294 |
+
value="*μ§λ¬Έμ μ
λ ₯νλ©΄ κ²°κ³Όκ° μ¬κΈ°μ νμλ©λλ€.*"
|
295 |
+
)
|
296 |
|
297 |
with gr.Row():
|
298 |
# κ°λ
μ AI μΆλ ₯
|
299 |
with gr.Column():
|
300 |
+
gr.Markdown("### π§ κ°λ
μ AI (κ±°μμ λΆμ)")
|
301 |
supervisor_output = gr.Textbox(
|
302 |
+
label="",
|
303 |
lines=15,
|
304 |
max_lines=20,
|
305 |
+
interactive=False,
|
306 |
+
elem_classes=["supervisor-box"]
|
307 |
)
|
308 |
|
309 |
# μ€νμ AI μΆλ ₯
|
310 |
with gr.Column():
|
311 |
+
gr.Markdown("### ποΈ μ€νμ AI (λ―Έμμ ꡬν)")
|
312 |
executor_output = gr.Textbox(
|
313 |
+
label="",
|
314 |
lines=15,
|
315 |
max_lines=20,
|
316 |
+
interactive=False,
|
317 |
+
elem_classes=["executor-box"]
|
318 |
)
|
319 |
|
320 |
+
# μμ
|
321 |
+
gr.Examples(
|
322 |
+
examples=[
|
323 |
+
"κΈ°κ³νμ΅ λͺ¨λΈμ μ±λ₯μ ν₯μμν€λ λ°©λ²μ?",
|
324 |
+
"ν¨κ³Όμ μΈ νλ‘μ νΈ κ΄λ¦¬ μ λ΅μ μ립νλ λ°©λ²μ?",
|
325 |
+
"μ§μ κ°λ₯ν λΉμ¦λμ€ λͺ¨λΈμ ꡬμΆνλ λ°©λ²μ?",
|
326 |
+
"볡μ‘ν λ°μ΄ν°λ₯Ό μκ°ννλ μ΅μ μ λ°©λ²μ?",
|
327 |
+
"νμ μμ°μ±μ λμ΄λ λ°©λ²μ?"
|
328 |
+
],
|
329 |
+
inputs=user_input,
|
330 |
+
label="π‘ μμ μ§λ¬Έ"
|
331 |
+
)
|
332 |
+
|
333 |
# μ΄λ²€νΈ νΈλ€λ¬
|
334 |
submit_btn.click(
|
335 |
fn=process_query,
|
|
|
354 |
outputs=[chatbot, supervisor_output, executor_output, final_output, status_text]
|
355 |
)
|
356 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
357 |
gr.Markdown(
|
358 |
"""
|
359 |
---
|
360 |
+
### π μ¬μ© λ°©λ²
|
361 |
+
1. μ§λ¬Έμ μ
λ ₯νκ³ Enter λλ 'λΆμ μμ' λ²νΌμ ν΄λ¦νμΈμ.
|
362 |
+
2. λ AIκ° νλ ₯νμ¬ λ΅λ³μ μμ±νλ κ³Όμ μ μ€μκ°μΌλ‘ νμΈν μ μμ΅λλ€.
|
363 |
+
3. μ΅μ’
μ’
ν© κ²°κ³Όλ μλ¨μ νμλ©λλ€.
|
364 |
+
|
365 |
+
### βοΈ νκ²½ μ€μ
|
366 |
+
- `FRIENDLI_TOKEN` νκ²½ λ³μλ₯Ό μ€μ νμΈμ: `export FRIENDLI_TOKEN="your_token"`
|
367 |
+
- λλ μ½λμ `FRIENDLI_TOKEN` λ³μλ₯Ό μ§μ μμ νμΈμ.
|
368 |
"""
|
369 |
)
|
370 |
|
|
|
372 |
app.launch(
|
373 |
server_name="0.0.0.0",
|
374 |
server_port=7860,
|
375 |
+
share=True,
|
376 |
show_error=True
|
377 |
+
)
|