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ciyidogan commited on May 25

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4eb71c8

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1 Parent(s): 1f8b14f

Delete inference_test.py

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inference_test.py +0 -133

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@@ -1,133 +0,0 @@
-import os, threading, uvicorn, time, traceback, random, json, asyncio, uuid
-from fastapi import FastAPI, Request
-from fastapi.responses import HTMLResponse, JSONResponse
-from transformers import AutoTokenizer, AutoModelForSequenceClassification
-import intent_test_runner
-from service_config import ServiceConfig
-import intent, intent, llm_model
-from log import log
-from chat_handler_debug import handle_chat
-from llm_model import get_model, get_tokenizer
-s_config = ServiceConfig()
-s_config.setup_environment()
-# === FastAPI
-app = FastAPI()
-chat_history = []
-@app.get("/")
-def health():
-    return {"status": "ok"}
-import uuid  # yukarıda zaten eklendiğini varsayıyoruz
-@app.post("/run_tests", status_code=202)
-def run_tests():
-    log("🚦 /run_tests çağrıldı. Testler başlatılıyor...")
-    threading.Thread(target=intent_test_runner.run_all_tests, daemon=True).start()
-    return {"status": "running", "message": "Test süreci başlatıldı."}
-@app.get("/start", response_class=HTMLResponse)
-def root():
-    # Yeni session ID üret
-    session_id = str(uuid.uuid4())
-    session_info = {
-        "session_id": session_id,
-        "variables": {},
-        "auth_tokens": {},
-        "last_intent": None,
-        "awaiting_variable": None
-    }
-    # Session store başlatıldıysa ekle
-    if not hasattr(app.state, "session_store"):
-        app.state.session_store = {}
-    app.state.session_store[session_id] = session_info
-    log(f"🌐 /start ile yeni session başlatıldı: {session_id}")
-    # HTML + session_id gömülü
-    return f"""
-    <html><body>
-        <h2>Turkcell LLM Chat</h2>
-        <textarea id='input' rows='4' cols='60'></textarea><br>
-        <button onclick='send()'>Gönder</button><br><br>
-        <label>Model Cevabı:</label><br>
-        <textarea id='output' rows='10' cols='80' readonly style='white-space: pre-wrap;'></textarea>
-        <script>
-        const sessionId = "{session_id}";
-        localStorage.setItem("session_id", sessionId);
-        async function send() {{
-            const input = document.getElementById("input").value;
-            const res = await fetch('/chat', {{
-                method: 'POST',
-                headers: {{
-                    'Content-Type': 'application/json',
-                    'X-Session-ID': sessionId
-                }},
-                body: JSON.stringify({{ user_input: input }})
-            }});
-            const data = await res.json();
-            document.getElementById('output').value = data.reply || data.response || data.error || 'Hata oluştu.';
-        }}
-        </script>
-    </body></html>
-    """
-@app.post("/start_chat")
-def start_chat():
-    if get_model() is None or get_tokenizer() is None:
-        return {"error": "Model yüklenmedi."}
-    if not hasattr(app.state, "session_store"):
-        app.state.session_store = {}
-    session_id = str(uuid.uuid4())
-    session_info = {
-        "session_id": session_id,
-        "variables": {},
-        "auth_tokens": {},
-        "last_intent": None,
-        "awaiting_variable": None
-    }
-    app.state.session_store[session_id] = session_info
-    log(f"🆕 Yeni session başlatıldı: {session_id}")
-    return {"session_id": session_id}
-@app.post("/train_intents", status_code=202)
-def train_intents(train_input: intent.TrainInput):
-    log("📥 POST /train_intents çağrıldı.")
-    intents = train_input.intents
-    data_formats = getattr(train_input, "data_formats", [])
-    s_config.INTENT_DEFINITIONS = {intent["name"]: intent for intent in intents}
-    s_config.DATA_FORMATS = data_formats  # 🔧 DATA_FORMATS burada set ediliyor
-    threading.Thread(
-        target=lambda: intent.background_training(intents, s_config),
-        daemon=True
-    ).start()
-    return {"status": "accepted", "message": "Intent eğitimi arka planda başlatıldı."}
-@app.post("/load_intent_model")
-def load_intent_model():
-    try:
-        intent.INTENT_TOKENIZER = AutoTokenizer.from_pretrained(s_config.INTENT_MODEL_PATH)
-        intent.INTENT_MODEL = AutoModelForSequenceClassification.from_pretrained(s_config.INTENT_MODEL_PATH)
-        with open(os.path.join(s_config.INTENT_MODEL_PATH, "label2id.json")) as f:
-            intent.LABEL2ID = json.load(f)
-        return {"status": "ok", "message": "Intent modeli yüklendi."}
-    except Exception as e:
-        return JSONResponse(content={"error": str(e)}, status_code=500)
-@app.post("/chat")
-async def chat(msg: llm_model.Message, request: Request):
-    return await handle_chat(msg, request, app, s_config)
-threading.Thread(target=llm_model.setup_model, kwargs={"s_config": s_config}, daemon=True).start()
-threading.Thread(target=lambda: uvicorn.run(app, host="0.0.0.0", port=7860), daemon=True).start()
-while True:
-    time.sleep(60)