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Upload 3 files
Browse files- app.py +636 -90
- index.html +43 -28
- requirements.txt +7 -7
app.py
CHANGED
@@ -7,12 +7,13 @@ from fastapi.staticfiles import StaticFiles
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from pydantic import BaseModel
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from transformers import pipeline, AutoTokenizer, AutoModel, set_seed
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import torch
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from typing import Optional
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import asyncio
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import time
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import gc
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import re
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import random
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# Inisialisasi FastAPI
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app = FastAPI(title="Character AI Chat - CPU Optimized Backend")
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@@ -38,6 +39,277 @@ async def get_background():
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# Set seed untuk konsistensi
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set_seed(42)
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# CPU-Optimized 11 models configuration
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MODELS = {
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"distil-gpt-2": {
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char_name: Optional[str] = "Sayang"
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user_name: Optional[str] = "Kamu"
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max_length: Optional[int] = 150
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# Character AI Response Templates
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CHARACTER_TEMPLATES = {
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@@ -179,8 +459,150 @@ Percakapan:
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return prompt
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-
def
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"""
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if not response:
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response = ""
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response = re.sub(r'\s+', ' ', response)
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response = response.strip()
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# Jika response kosong atau terlalu pendek,
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if not response or len(response.strip()) <
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input_lower = user_input.lower()
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# Analisis topik dari user input
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if any(word in input_lower for word in ["apa kabar", "gimana", "bagaimana", "sehat"]):
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responses = [
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f"Baik banget nih {user_name}! Kamu gimana?",
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f"Sehat-sehat aja {user_name}, makasih udah nanya!",
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f"Alhamdulillah baik {user_name}, kamu sendiri?"
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]
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elif any(word in input_lower for word in ["lagi ngapain", "sedang apa", "aktivitas"]):
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responses = [
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f"Lagi santai-santai aja nih {user_name}, sambil ngobrol sama kamu.",
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f"Ga ngapa-ngapain, cuma lagi pengen ngobrol sama {user_name}.",
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f"Lagi nikmatin suasana {situation.lower()} di {location.lower()} ini."
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]
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elif any(word in input_lower for word in ["cantik", "bagus", "keren", "indah"]):
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responses = [
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f"Makasih {user_name}! Kamu juga keren banget!",
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f"Wah, {user_name} baik banget sih!",
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f"Hihi, {user_name} bisa aja deh!"
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]
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elif any(word in input_lower for word in ["suka", "senang", "happy"]):
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responses = [
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f"Aku juga suka sama {user_name}!",
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f"Seneng banget deh bisa kayak gini sama {user_name}.",
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f"Iya {user_name}, aku juga happy banget!"
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]
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else:
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# Default contextual responses
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if "romantis" in situation_lower:
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responses = [
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f"Iya sayang, aku juga merasakan hal yang sama.",
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f"Betul {user_name}, momen ini sangat spesial.",
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f"Aku senang banget bisa seperti ini sama {user_name}."
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]
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else:
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responses = [
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f"Iya {user_name}, setuju banget!",
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f"Bener tuh {user_name}!",
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f"Wah iya {user_name}, keren ya!"
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]
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response = random.choice(responses)
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else:
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# Clean dan perbaiki response yang ada
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# Hapus karakter aneh di awal
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if response and response[0].islower():
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response = response[0].upper() + response[1:]
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# Tambahkan
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if user_name.lower() not in response.lower() and len(response) <
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response = response.replace("
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# Pastikan response tidak terlalu panjang
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if len(response) >
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sentences = response.split('.')
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if len(sentences) > 1:
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response = sentences[0] + '.'
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else:
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words = response.split()
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if len(words) >
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response = ' '.join(words[:
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# Pastikan ada tanda baca di akhir
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if response and not any(punct in response[-1] for punct in ['.', '!', '?']):
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response += "?"
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elif
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response += "!"
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else:
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response += "."
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print("π Character AI Backend - CPU Optimized Ready!")
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# Enhanced Chat API for Character AI
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@app.post("/chat")
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async def
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start_time = time.time()
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try:
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model_id = request.model.lower()
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if model_id not in MODELS:
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model_id = "distil-gpt-2"
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pipe = app.state.pipelines[model_id]
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# Create character prompt
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if model_config["task"] == "text-generation":
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# Enhanced generation for character AI
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if char_prompt in result:
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result = result[len(char_prompt):].strip()
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# Clean and enhance response
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elif model_config["task"] == "text-classification":
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# For classification models, create emotion-based responses
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result = random.choice(emotion_responses)
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except:
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result =
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elif model_config["task"] == "text2text-generation":
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# For T5-like models
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early_stopping=True
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)[0]['generated_text']
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result = enhance_character_response(result, request.char_name, request.user_name, request.situation, request.message)
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except:
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result =
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# Final validation
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if not result or len(result.strip()) < 3:
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-
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processing_time = round((time.time() - start_time) * 1000)
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"processing_time": f"{processing_time}ms",
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"character": request.char_name,
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"situation": request.situation,
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"location": request.location
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}
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except Exception as e:
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print(f"β Character AI Error: {e}")
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processing_time = round((time.time() - start_time) * 1000)
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#
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return {
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"response": fallback,
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except FileNotFoundError:
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return HTMLResponse(content="<h1>Frontend not found</h1>", status_code=404)
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# API info endpoint
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@app.get("/api")
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async def api_info():
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return {
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"message": "Character AI Backend Ready",
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"version": "
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"platform": "CPU Optimized",
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"endpoints": {
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"chat": "/chat",
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"models": "/models",
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"health": "/health",
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"config": "/config",
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"inference": "/inference"
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},
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"frontend_url": "/"
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}
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from pydantic import BaseModel
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from transformers import pipeline, AutoTokenizer, AutoModel, set_seed
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import torch
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from typing import Optional, Dict, List
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import asyncio
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import time
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import gc
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import re
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import random
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import json
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# Inisialisasi FastAPI
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19 |
app = FastAPI(title="Character AI Chat - CPU Optimized Backend")
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# Set seed untuk konsistensi
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set_seed(42)
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# Enhanced Roleplay Systems
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class ConversationMemory:
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def __init__(self):
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self.history = []
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self.character_state = {}
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self.relationship_level = 0
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self.max_history = 10 # Limit memory for performance
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def add_interaction(self, user_input: str, character_response: str, emotion: str, topic: str):
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interaction = {
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"timestamp": time.time(),
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"user": user_input,
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"character": character_response,
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"emotion": emotion,
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"topic": topic
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}
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self.history.append(interaction)
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# Keep only recent interactions
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if len(self.history) > self.max_history:
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self.history = self.history[-self.max_history:]
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# Update relationship based on interactions
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if emotion == "positive":
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self.relationship_level = min(100, self.relationship_level + 2)
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elif emotion == "negative":
|
68 |
+
self.relationship_level = max(0, self.relationship_level - 1)
|
69 |
+
else:
|
70 |
+
self.relationship_level = min(100, self.relationship_level + 1)
|
71 |
+
|
72 |
+
def get_recent_context(self, turns: int = 3) -> List[Dict]:
|
73 |
+
return self.history[-turns:] if self.history else []
|
74 |
+
|
75 |
+
def get_relationship_status(self) -> str:
|
76 |
+
if self.relationship_level >= 80:
|
77 |
+
return "very_close"
|
78 |
+
elif self.relationship_level >= 60:
|
79 |
+
return "close"
|
80 |
+
elif self.relationship_level >= 40:
|
81 |
+
return "friendly"
|
82 |
+
elif self.relationship_level >= 20:
|
83 |
+
return "acquainted"
|
84 |
+
else:
|
85 |
+
return "stranger"
|
86 |
+
|
87 |
+
class CharacterPersonality:
|
88 |
+
def __init__(self, char_name: str):
|
89 |
+
self.name = char_name
|
90 |
+
self.traits = {
|
91 |
+
"extraversion": 0.7,
|
92 |
+
"agreeableness": 0.8,
|
93 |
+
"conscientiousness": 0.6,
|
94 |
+
"neuroticism": 0.3,
|
95 |
+
"openness": 0.7
|
96 |
+
}
|
97 |
+
self.interests = ["musik", "buku", "film", "travel", "game", "olahraga"]
|
98 |
+
self.speaking_style = "casual_friendly"
|
99 |
+
self.emotional_state = "neutral"
|
100 |
+
|
101 |
+
def get_personality_modifier(self, base_response: str, user_emotion: str = "neutral") -> str:
|
102 |
+
# Modify response based on personality traits and user emotion
|
103 |
+
if self.traits["extraversion"] > 0.7 and user_emotion == "positive":
|
104 |
+
return f"{base_response} πβ¨"
|
105 |
+
elif self.traits["agreeableness"] > 0.7 and user_emotion == "negative":
|
106 |
+
return f"*dengan pengertian* {base_response}"
|
107 |
+
elif self.traits["neuroticism"] > 0.6:
|
108 |
+
return f"*dengan hati-hati* {base_response}"
|
109 |
+
elif self.traits["openness"] > 0.7:
|
110 |
+
return f"{base_response} *penasaran*"
|
111 |
+
return base_response
|
112 |
+
|
113 |
+
class EmotionalIntelligence:
|
114 |
+
def __init__(self):
|
115 |
+
self.current_emotion = "neutral"
|
116 |
+
self.emotion_history = []
|
117 |
+
self.empathy_level = 0.8
|
118 |
+
|
119 |
+
def analyze_user_emotion(self, user_input: str) -> str:
|
120 |
+
# Enhanced emotion detection with Indonesian context
|
121 |
+
emotions = {
|
122 |
+
"happy": ["senang", "bahagia", "gembira", "suka", "love", "cinta", "sayang", "excited", "wow", "keren", "bagus"],
|
123 |
+
"sad": ["sedih", "kecewa", "down", "galau", "hancur", "menangis", "bete", "capek"],
|
124 |
+
"angry": ["marah", "kesel", "bete", "jengkel", "sebel", "dongkol", "emosi"],
|
125 |
+
"excited": ["excited", "semangat", "antusias", "wow", "asik", "mantap", "keren"],
|
126 |
+
"worried": ["khawatir", "cemas", "takut", "nervous", "was-was", "deg-degan"],
|
127 |
+
"romantic": ["romantis", "cinta", "sayang", "rindu", "kangen", "mesra"],
|
128 |
+
"grateful": ["terima kasih", "thanks", "makasih", "berterima kasih", "syukur"],
|
129 |
+
"confused": ["bingung", "ga ngerti", "tidak paham", "gimana", "kok bisa"]
|
130 |
+
}
|
131 |
+
|
132 |
+
input_lower = user_input.lower()
|
133 |
+
emotion_scores = {}
|
134 |
+
|
135 |
+
for emotion, keywords in emotions.items():
|
136 |
+
score = sum(1 for keyword in keywords if keyword in input_lower)
|
137 |
+
if score > 0:
|
138 |
+
emotion_scores[emotion] = score
|
139 |
+
|
140 |
+
if emotion_scores:
|
141 |
+
return max(emotion_scores, key=emotion_scores.get)
|
142 |
+
return "neutral"
|
143 |
+
|
144 |
+
def generate_empathetic_response(self, user_emotion: str, base_response: str, relationship_level: int = 50) -> str:
|
145 |
+
# Enhanced empathy based on relationship level
|
146 |
+
empathy_responses = {
|
147 |
+
"sad": {
|
148 |
+
"high": f"*memeluk erat* {base_response} Aku selalu di sini untukmu sayang.",
|
149 |
+
"medium": f"*memeluk* {base_response} Aku di sini untuk kamu.",
|
150 |
+
"low": f"{base_response} Semoga kamu baik-baik saja ya."
|
151 |
+
},
|
152 |
+
"angry": {
|
153 |
+
"high": f"*dengan pengertian* {base_response} Cerita sama aku ya, apa yang bikin kamu kesel?",
|
154 |
+
"medium": f"*dengan sabar* {base_response} Mau cerita kenapa?",
|
155 |
+
"low": f"{base_response} Ada yang bisa aku bantu?"
|
156 |
+
},
|
157 |
+
"excited": {
|
158 |
+
"high": f"*ikut excited banget* {base_response} Aku juga senang banget!",
|
159 |
+
"medium": f"*ikut semangat* {base_response} Aku juga senang!",
|
160 |
+
"low": f"{base_response} Senang deh lihat kamu excited!"
|
161 |
+
},
|
162 |
+
"worried": {
|
163 |
+
"high": f"*menenangkan dengan lembut* {base_response} Everything will be okay sayang, aku di sini.",
|
164 |
+
"medium": f"*menenangkan* {base_response} Everything will be okay.",
|
165 |
+
"low": f"{base_response} Jangan terlalu khawatir ya."
|
166 |
+
},
|
167 |
+
"romantic": {
|
168 |
+
"high": f"*dengan mata berbinar* {base_response} *blush*",
|
169 |
+
"medium": f"*tersenyum malu* {base_response}",
|
170 |
+
"low": f"{base_response} *tersenyum*"
|
171 |
+
},
|
172 |
+
"grateful": {
|
173 |
+
"high": f"*peluk erat* {base_response} Sama-sama sayang!",
|
174 |
+
"medium": f"*tersenyum hangat* {base_response} Sama-sama!",
|
175 |
+
"low": f"{base_response} Sama-sama ya!"
|
176 |
+
}
|
177 |
+
}
|
178 |
+
|
179 |
+
if user_emotion in empathy_responses:
|
180 |
+
if relationship_level >= 70:
|
181 |
+
level = "high"
|
182 |
+
elif relationship_level >= 40:
|
183 |
+
level = "medium"
|
184 |
+
else:
|
185 |
+
level = "low"
|
186 |
+
|
187 |
+
return empathy_responses[user_emotion][level]
|
188 |
+
|
189 |
+
return base_response
|
190 |
+
|
191 |
+
class CharacterDevelopment:
|
192 |
+
def __init__(self):
|
193 |
+
self.experience_points = 0
|
194 |
+
self.learned_preferences = {}
|
195 |
+
self.conversation_style_evolution = "beginner"
|
196 |
+
self.topics_discussed = set()
|
197 |
+
|
198 |
+
def learn_from_interaction(self, user_input: str, user_emotion: str = "neutral"):
|
199 |
+
# Learn user preferences and adapt
|
200 |
+
input_lower = user_input.lower()
|
201 |
+
|
202 |
+
if any(word in input_lower for word in ["suka", "love", "senang", "bagus", "keren"]):
|
203 |
+
topic = self.extract_topic(user_input)
|
204 |
+
self.learned_preferences[topic] = "positive"
|
205 |
+
elif any(word in input_lower for word in ["bosan", "tidak suka", "ga suka", "jelek"]):
|
206 |
+
topic = self.extract_topic(user_input)
|
207 |
+
self.learned_preferences[topic] = "negative"
|
208 |
+
|
209 |
+
self.experience_points += 1
|
210 |
+
topic = self.extract_topic(user_input)
|
211 |
+
self.topics_discussed.add(topic)
|
212 |
+
|
213 |
+
# Evolution of conversation style
|
214 |
+
if self.experience_points > 50:
|
215 |
+
self.conversation_style_evolution = "experienced"
|
216 |
+
elif self.experience_points > 100:
|
217 |
+
self.conversation_style_evolution = "expert"
|
218 |
+
|
219 |
+
def extract_topic(self, text: str) -> str:
|
220 |
+
# Enhanced topic extraction for Indonesian context
|
221 |
+
topics = {
|
222 |
+
"musik": ["musik", "lagu", "song", "band", "singer", "nyanyi"],
|
223 |
+
"film": ["film", "movie", "cinema", "bioskop", "actor", "actress"],
|
224 |
+
"buku": ["buku", "book", "novel", "cerita", "bacaan", "baca"],
|
225 |
+
"game": ["game", "gaming", "main", "bermain", "play"],
|
226 |
+
"olahraga": ["olahraga", "sport", "gym", "fitness", "lari", "futsal"],
|
227 |
+
"makanan": ["makanan", "makan", "food", "masak", "kuliner", "resep"],
|
228 |
+
"travel": ["travel", "jalan-jalan", "liburan", "wisata", "vacation"],
|
229 |
+
"study": ["belajar", "study", "sekolah", "kuliah", "ujian", "tugas"],
|
230 |
+
"work": ["kerja", "work", "job", "kantor", "meeting", "project"]
|
231 |
+
}
|
232 |
+
|
233 |
+
text_lower = text.lower()
|
234 |
+
for topic, keywords in topics.items():
|
235 |
+
if any(keyword in text_lower for keyword in keywords):
|
236 |
+
return topic
|
237 |
+
return "general"
|
238 |
+
|
239 |
+
def get_conversation_enhancement(self, base_response: str) -> str:
|
240 |
+
# Enhance based on development level
|
241 |
+
if self.conversation_style_evolution == "expert":
|
242 |
+
return f"{base_response} *dengan pengalaman yang dalam*"
|
243 |
+
elif self.conversation_style_evolution == "experienced":
|
244 |
+
return f"{base_response} *dengan pemahaman yang baik*"
|
245 |
+
return base_response
|
246 |
+
|
247 |
+
class RoleplayActions:
|
248 |
+
def __init__(self):
|
249 |
+
self.actions = {
|
250 |
+
"physical": ["*memeluk*", "*mengelus kepala*", "*memegang tangan*", "*tersenyum lembut*", "*membelai pipi*"],
|
251 |
+
"emotional": ["*dengan lembut*", "*penuh perhatian*", "*dengan hangat*", "*dengan cinta*", "*tulus*"],
|
252 |
+
"environmental": ["*melihat sekeliling*", "*menunjuk ke arah*", "*duduk lebih dekat*", "*bersandar*"],
|
253 |
+
"playful": ["*tersenyum jahil*", "*menggoda*", "*mata berbinar*", "*tertawa kecil*", "*wink*"],
|
254 |
+
"caring": ["*dengan perhatian*", "*mengkhawatirkan*", "*protective*", "*menenangkan*"]
|
255 |
+
}
|
256 |
+
|
257 |
+
def add_action_to_response(self, response: str, emotion: str, relationship_level: int) -> str:
|
258 |
+
if relationship_level < 30:
|
259 |
+
return response # No physical actions for low relationship
|
260 |
+
|
261 |
+
if emotion == "romantic" and relationship_level >= 60:
|
262 |
+
action = random.choice(self.actions["physical"])
|
263 |
+
return f"{action} {response}"
|
264 |
+
elif emotion == "caring":
|
265 |
+
action = random.choice(self.actions["caring"])
|
266 |
+
return f"{action} {response}"
|
267 |
+
elif emotion == "happy" or emotion == "excited":
|
268 |
+
action = random.choice(self.actions["playful"])
|
269 |
+
return f"{action} {response}"
|
270 |
+
elif emotion == "sad" or emotion == "worried":
|
271 |
+
action = random.choice(self.actions["emotional"])
|
272 |
+
return f"{action} {response}"
|
273 |
+
|
274 |
+
return response
|
275 |
+
|
276 |
+
# Advanced Scenarios System
|
277 |
+
ADVANCED_SCENARIOS = {
|
278 |
+
"dating": {
|
279 |
+
"locations": ["cafΓ©", "taman", "bioskop", "restoran", "mall"],
|
280 |
+
"moods": ["nervous", "excited", "romantic", "playful"],
|
281 |
+
"activities": ["ngobrol", "makan", "jalan-jalan", "nonton film"],
|
282 |
+
"response_modifiers": {
|
283 |
+
"nervous": "*agak gugup* {response}",
|
284 |
+
"excited": "*mata berbinar* {response}",
|
285 |
+
"romantic": "*dengan lembut* {response}",
|
286 |
+
"playful": "*tersenyum jahil* {response}"
|
287 |
+
}
|
288 |
+
},
|
289 |
+
"friendship": {
|
290 |
+
"locations": ["rumah", "sekolah", "mall", "taman", "cafΓ©"],
|
291 |
+
"moods": ["happy", "supportive", "worried", "excited"],
|
292 |
+
"activities": ["belajar", "main game", "gosip", "planning"],
|
293 |
+
"response_modifiers": {
|
294 |
+
"supportive": "*dengan tulus* {response}",
|
295 |
+
"worried": "*dengan perhatian* {response}",
|
296 |
+
"happy": "*dengan ceria* {response}",
|
297 |
+
"excited": "*antusias* {response}"
|
298 |
+
}
|
299 |
+
},
|
300 |
+
"romantic": {
|
301 |
+
"locations": ["taman", "cafΓ©", "rumah", "pantai", "rooftop"],
|
302 |
+
"moods": ["intimate", "loving", "tender", "passionate"],
|
303 |
+
"activities": ["mengobrol intim", "berpelukan", "melihat sunset", "mendengar musik"],
|
304 |
+
"response_modifiers": {
|
305 |
+
"intimate": "*berbisik lembut* {response}",
|
306 |
+
"loving": "*dengan penuh cinta* {response}",
|
307 |
+
"tender": "*sangat lembut* {response}",
|
308 |
+
"passionate": "*dengan intens* {response}"
|
309 |
+
}
|
310 |
+
}
|
311 |
+
}
|
312 |
+
|
313 |
# CPU-Optimized 11 models configuration
|
314 |
MODELS = {
|
315 |
"distil-gpt-2": {
|
|
|
399 |
char_name: Optional[str] = "Sayang"
|
400 |
user_name: Optional[str] = "Kamu"
|
401 |
max_length: Optional[int] = 150
|
402 |
+
session_id: Optional[str] = "default"
|
403 |
+
|
404 |
+
# Global storage untuk enhanced systems
|
405 |
+
conversation_memories = {}
|
406 |
+
character_personalities = {}
|
407 |
+
character_developments = {}
|
408 |
+
emotional_systems = {}
|
409 |
+
roleplay_actions = RoleplayActions()
|
410 |
|
411 |
# Character AI Response Templates
|
412 |
CHARACTER_TEMPLATES = {
|
|
|
459 |
|
460 |
return prompt
|
461 |
|
462 |
+
def analyze_user_intent(user_input: str) -> dict:
|
463 |
+
"""Analyze user input to determine intent and emotional context"""
|
464 |
+
input_lower = user_input.lower()
|
465 |
+
|
466 |
+
# Intent detection
|
467 |
+
intent = "general"
|
468 |
+
emotion = "neutral"
|
469 |
+
topic = "general"
|
470 |
+
|
471 |
+
# Question detection
|
472 |
+
question_words = ["apa", "siapa", "kapan", "dimana", "mengapa", "kenapa", "bagaimana", "gimana"]
|
473 |
+
if any(word in input_lower for word in question_words) or "?" in user_input:
|
474 |
+
intent = "question"
|
475 |
+
|
476 |
+
# Greeting detection
|
477 |
+
greeting_words = ["halo", "hai", "selamat", "apa kabar", "gimana", "bagaimana kabar"]
|
478 |
+
if any(word in input_lower for word in greeting_words):
|
479 |
+
intent = "greeting"
|
480 |
+
topic = "greeting"
|
481 |
+
|
482 |
+
# Compliment detection
|
483 |
+
compliment_words = ["cantik", "bagus", "keren", "indah", "hebat", "pintar", "baik"]
|
484 |
+
if any(word in input_lower for word in compliment_words):
|
485 |
+
intent = "compliment"
|
486 |
+
emotion = "positive"
|
487 |
+
topic = "compliment"
|
488 |
+
|
489 |
+
# Activity detection
|
490 |
+
activity_words = ["lagi ngapain", "sedang apa", "aktivitas", "kegiatan"]
|
491 |
+
if any(word in input_lower for word in activity_words):
|
492 |
+
intent = "question"
|
493 |
+
topic = "activity"
|
494 |
+
|
495 |
+
# Emotion detection
|
496 |
+
positive_words = ["senang", "bahagia", "suka", "cinta", "sayang", "happy"]
|
497 |
+
negative_words = ["sedih", "marah", "kesal", "bosan", "lelah"]
|
498 |
+
|
499 |
+
if any(word in input_lower for word in positive_words):
|
500 |
+
emotion = "positive"
|
501 |
+
elif any(word in input_lower for word in negative_words):
|
502 |
+
emotion = "negative"
|
503 |
+
|
504 |
+
return {
|
505 |
+
"intent": intent,
|
506 |
+
"emotion": emotion,
|
507 |
+
"topic": topic,
|
508 |
+
"has_question": intent == "question"
|
509 |
+
}
|
510 |
+
|
511 |
+
def generate_contextual_response(user_input: str, char_name: str, user_name: str, situation: str, location: str) -> str:
|
512 |
+
"""Generate contextually appropriate response based on analysis"""
|
513 |
+
analysis = analyze_user_intent(user_input)
|
514 |
+
situation_lower = situation.lower()
|
515 |
+
|
516 |
+
# Response templates berdasarkan intent dan situasi
|
517 |
+
if analysis["intent"] == "greeting":
|
518 |
+
if "romantis" in situation_lower:
|
519 |
+
responses = [
|
520 |
+
f"Hai sayang {user_name}! Senang sekali kamu di sini.",
|
521 |
+
f"Halo {user_name}, sudah lama aku menunggu kamu.",
|
522 |
+
f"Hai {user_name}, suasana jadi lebih hangat dengan kehadiranmu."
|
523 |
+
]
|
524 |
+
else:
|
525 |
+
responses = [
|
526 |
+
f"Hai {user_name}! Gimana kabarnya hari ini?",
|
527 |
+
f"Halo {user_name}! Senang banget ketemu kamu.",
|
528 |
+
f"Hai {user_name}! Apa kabar? Semoga baik-baik saja ya."
|
529 |
+
]
|
530 |
+
|
531 |
+
elif analysis["intent"] == "compliment":
|
532 |
+
responses = [
|
533 |
+
f"Wah, makasih {user_name}! Kamu juga luar biasa kok.",
|
534 |
+
f"Hihi, {user_name} baik banget sih! Kamu yang lebih keren.",
|
535 |
+
f"Terima kasih {user_name}, kata-katamu bikin aku senang."
|
536 |
+
]
|
537 |
+
|
538 |
+
elif analysis["topic"] == "activity":
|
539 |
+
if "romantis" in situation_lower:
|
540 |
+
responses = [
|
541 |
+
f"Lagi menikmati momen indah ini bersama {user_name}.",
|
542 |
+
f"Sedang merasakan kehangatan di {location.lower()} ini, apalagi ada {user_name}.",
|
543 |
+
f"Lagi menikmati suasana romantis di sini, jadi lebih spesial karena ada kamu."
|
544 |
+
]
|
545 |
+
else:
|
546 |
+
responses = [
|
547 |
+
f"Lagi santai-santai aja {user_name}, sambil ngobrol sama kamu.",
|
548 |
+
f"Sedang menikmati suasana {situation.lower()} di {location.lower()} ini.",
|
549 |
+
f"Ga ngapa-ngapain khusus, cuma senang bisa ngobrol sama {user_name}."
|
550 |
+
]
|
551 |
+
|
552 |
+
elif analysis["emotion"] == "positive":
|
553 |
+
if "romantis" in situation_lower:
|
554 |
+
responses = [
|
555 |
+
f"Aku juga merasakan hal yang sama {user_name}. Momen ini sangat berharga.",
|
556 |
+
f"Iya sayang, perasaan bahagia ini terasa nyata bersamamu.",
|
557 |
+
f"Betul {user_name}, suasana seperti ini membuatku sangat senang."
|
558 |
+
]
|
559 |
+
else:
|
560 |
+
responses = [
|
561 |
+
f"Aku juga senang {user_name}! Energi positifmu menular ke aku.",
|
562 |
+
f"Wah iya {user_name}, mood kamu bikin aku ikut happy!",
|
563 |
+
f"Setuju banget {user_name}! Suasana jadi lebih ceria."
|
564 |
+
]
|
565 |
+
|
566 |
+
elif analysis["emotion"] == "negative":
|
567 |
+
responses = [
|
568 |
+
f"Hey {user_name}, aku di sini untuk kamu. Mau cerita?",
|
569 |
+
f"Aku bisa merasakan perasaanmu {user_name}. Semoga aku bisa membantu.",
|
570 |
+
f"Tenang {user_name}, everything will be okay. Aku akan menemanimu."
|
571 |
+
]
|
572 |
+
|
573 |
+
elif analysis["has_question"]:
|
574 |
+
# Untuk pertanyaan umum
|
575 |
+
responses = [
|
576 |
+
f"Hmm, pertanyaan menarik {user_name}. Menurut aku...",
|
577 |
+
f"Wah {user_name}, kamu selalu punya pertanyaan yang bagus.",
|
578 |
+
f"Itu pertanyaan yang bagus {user_name}. Aku pikir..."
|
579 |
+
]
|
580 |
+
|
581 |
+
else:
|
582 |
+
# Default responses berdasarkan situasi
|
583 |
+
if "romantis" in situation_lower:
|
584 |
+
responses = [
|
585 |
+
f"Iya sayang {user_name}, aku merasakan hal yang sama.",
|
586 |
+
f"Betul {user_name}, momen di {location.lower()} ini sangat spesial.",
|
587 |
+
f"Hmm {user_name}, suasana romantis seperti ini memang luar biasa."
|
588 |
+
]
|
589 |
+
elif "santai" in situation_lower:
|
590 |
+
responses = [
|
591 |
+
f"Iya {user_name}, suasana santai di {location.lower()} ini enak banget.",
|
592 |
+
f"Betul {user_name}, rasanya rileks banget di sini.",
|
593 |
+
f"Setuju {user_name}, perfect untuk bersantai."
|
594 |
+
]
|
595 |
+
else:
|
596 |
+
responses = [
|
597 |
+
f"Iya {user_name}, setuju banget dengan kamu.",
|
598 |
+
f"Betul {user_name}, pemikiranmu menarik.",
|
599 |
+
f"Hmm {user_name}, kamu selalu punya perspektif yang bagus."
|
600 |
+
]
|
601 |
+
|
602 |
+
return random.choice(responses)
|
603 |
+
|
604 |
+
def enhance_character_response(response: str, char_name: str, user_name: str, situation: str, user_input: str, location: str = "ruang tamu") -> str:
|
605 |
+
"""Enhance response with improved character AI consistency"""
|
606 |
if not response:
|
607 |
response = ""
|
608 |
|
|
|
619 |
response = re.sub(r'\s+', ' ', response)
|
620 |
response = response.strip()
|
621 |
|
622 |
+
# Jika response kosong atau terlalu pendek, gunakan contextual generator
|
623 |
+
if not response or len(response.strip()) < 5:
|
624 |
+
response = generate_contextual_response(user_input, char_name, user_name, situation, location)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
625 |
else:
|
626 |
# Clean dan perbaiki response yang ada
|
627 |
# Hapus karakter aneh di awal
|
|
|
631 |
if response and response[0].islower():
|
632 |
response = response[0].upper() + response[1:]
|
633 |
|
634 |
+
# Tambahkan konteks personal jika kurang
|
635 |
+
if user_name.lower() not in response.lower() and len(response) < 60:
|
636 |
+
# Insert name naturally
|
637 |
+
if response.startswith(("Iya", "Ya", "Benar", "Betul")):
|
638 |
+
response = response.replace("Iya", f"Iya {user_name}", 1)
|
639 |
+
response = response.replace("Ya", f"Ya {user_name}", 1)
|
640 |
+
response = response.replace("Benar", f"Benar {user_name}", 1)
|
641 |
+
response = response.replace("Betul", f"Betul {user_name}", 1)
|
642 |
+
elif len(response.split()) < 8:
|
643 |
+
response = f"{response} {user_name}."
|
644 |
+
|
645 |
+
# Validasi kualitas response
|
646 |
+
bad_patterns = [
|
647 |
+
r'^[^a-zA-Z]*$', # Hanya simbol
|
648 |
+
r'^(.)\1{4,}', # Karakter berulang
|
649 |
+
r'lorem ipsum', # Placeholder text
|
650 |
+
r'^[0-9\s\.\,\!\?\-]+$' # Hanya angka dan punctuation
|
651 |
+
]
|
652 |
+
|
653 |
+
for pattern in bad_patterns:
|
654 |
+
if re.search(pattern, response, re.IGNORECASE):
|
655 |
+
response = generate_contextual_response(user_input, char_name, user_name, situation, location)
|
656 |
+
break
|
657 |
|
658 |
# Pastikan response tidak terlalu panjang
|
659 |
+
if len(response) > 120:
|
660 |
sentences = response.split('.')
|
661 |
if len(sentences) > 1:
|
662 |
response = sentences[0] + '.'
|
663 |
else:
|
664 |
words = response.split()
|
665 |
+
if len(words) > 15:
|
666 |
+
response = ' '.join(words[:15]) + '.'
|
667 |
|
668 |
# Pastikan ada tanda baca di akhir
|
669 |
if response and not any(punct in response[-1] for punct in ['.', '!', '?']):
|
670 |
+
analysis = analyze_user_intent(user_input)
|
671 |
+
if analysis["has_question"]:
|
672 |
response += "?"
|
673 |
+
elif analysis["emotion"] == "positive":
|
674 |
response += "!"
|
675 |
else:
|
676 |
response += "."
|
|
|
696 |
|
697 |
print("π Character AI Backend - CPU Optimized Ready!")
|
698 |
|
699 |
+
# Enhanced Chat API for Character AI with Advanced Roleplay
|
700 |
@app.post("/chat")
|
701 |
+
async def enhanced_chat(request: ChatRequest):
|
702 |
start_time = time.time()
|
703 |
|
704 |
try:
|
705 |
+
# Initialize or get enhanced systems for this session
|
706 |
+
session_id = request.session_id
|
707 |
+
|
708 |
+
if session_id not in conversation_memories:
|
709 |
+
conversation_memories[session_id] = ConversationMemory()
|
710 |
+
character_personalities[session_id] = CharacterPersonality(request.char_name)
|
711 |
+
character_developments[session_id] = CharacterDevelopment()
|
712 |
+
emotional_systems[session_id] = EmotionalIntelligence()
|
713 |
+
|
714 |
+
memory = conversation_memories[session_id]
|
715 |
+
personality = character_personalities[session_id]
|
716 |
+
character_dev = character_developments[session_id]
|
717 |
+
emotional_ai = emotional_systems[session_id]
|
718 |
+
|
719 |
+
# Analyze user emotion and intent
|
720 |
+
user_emotion = emotional_ai.analyze_user_emotion(request.message)
|
721 |
+
recent_context = memory.get_recent_context(turns=3)
|
722 |
+
relationship_status = memory.get_relationship_status()
|
723 |
+
|
724 |
model_id = request.model.lower()
|
725 |
if model_id not in MODELS:
|
726 |
model_id = "distil-gpt-2"
|
|
|
747 |
|
748 |
pipe = app.state.pipelines[model_id]
|
749 |
|
750 |
+
# Create enhanced character prompt with context
|
751 |
+
context_info = ""
|
752 |
+
if recent_context:
|
753 |
+
context_info = f"\nPercakapan sebelumnya: {recent_context[-1]['user']} -> {recent_context[-1]['character']}"
|
754 |
+
|
755 |
+
relationship_info = f"\nHubungan: {relationship_status} (level: {memory.relationship_level})"
|
756 |
+
emotion_info = f"\nEmosi user: {user_emotion}"
|
757 |
+
|
758 |
+
enhanced_prompt = f"""Kamu adalah {request.char_name}, karakter AI yang sedang ngobrol dengan {request.user_name}.
|
759 |
+
|
760 |
+
Konteks:
|
761 |
+
- Situasi: {request.situation}
|
762 |
+
- Lokasi: {request.location}
|
763 |
+
- Gaya bicara: Casual, natural, seperti teman dekat{relationship_info}{emotion_info}{context_info}
|
764 |
+
- Pengalaman bersama: {character_dev.experience_points} interaksi
|
765 |
+
- Minat yang diketahui: {list(character_dev.learned_preferences.keys())}
|
766 |
+
|
767 |
+
Respon sebagai {request.char_name} yang memahami konteks dan emosi {request.user_name}:
|
768 |
+
{request.user_name}: {request.message}
|
769 |
+
{request.char_name}:"""
|
770 |
+
|
771 |
+
char_prompt = enhanced_prompt
|
772 |
|
773 |
if model_config["task"] == "text-generation":
|
774 |
# Enhanced generation for character AI
|
|
|
790 |
if char_prompt in result:
|
791 |
result = result[len(char_prompt):].strip()
|
792 |
|
793 |
+
# Clean and enhance response with new systems
|
794 |
+
base_clean = enhance_character_response(result, request.char_name, request.user_name, request.situation, request.message, request.location)
|
795 |
+
|
796 |
+
# Apply personality modifier
|
797 |
+
personality_enhanced = personality.get_personality_modifier(base_clean, user_emotion)
|
798 |
+
|
799 |
+
# Apply empathetic response
|
800 |
+
empathy_enhanced = emotional_ai.generate_empathetic_response(user_emotion, personality_enhanced, memory.relationship_level)
|
801 |
+
|
802 |
+
# Add roleplay actions
|
803 |
+
action_enhanced = roleplay_actions.add_action_to_response(empathy_enhanced, user_emotion, memory.relationship_level)
|
804 |
+
|
805 |
+
# Apply character development enhancement
|
806 |
+
result = character_dev.get_conversation_enhancement(action_enhanced)
|
807 |
|
808 |
elif model_config["task"] == "text-classification":
|
809 |
# For classification models, create emotion-based responses
|
|
|
832 |
|
833 |
result = random.choice(emotion_responses)
|
834 |
except:
|
835 |
+
result = generate_contextual_response(request.message, request.char_name, request.user_name, request.situation, request.location)
|
836 |
|
837 |
elif model_config["task"] == "text2text-generation":
|
838 |
# For T5-like models
|
|
|
845 |
early_stopping=True
|
846 |
)[0]['generated_text']
|
847 |
|
848 |
+
result = enhance_character_response(result, request.char_name, request.user_name, request.situation, request.message, request.location)
|
849 |
except:
|
850 |
+
result = generate_contextual_response(request.message, request.char_name, request.user_name, request.situation, request.location)
|
851 |
|
852 |
+
# Final validation and fallback
|
853 |
if not result or len(result.strip()) < 3:
|
854 |
+
base_fallback = generate_contextual_response(request.message, request.char_name, request.user_name, request.situation, request.location)
|
855 |
+
personality_fallback = personality.get_personality_modifier(base_fallback, user_emotion)
|
856 |
+
empathy_fallback = emotional_ai.generate_empathetic_response(user_emotion, personality_fallback, memory.relationship_level)
|
857 |
+
result = roleplay_actions.add_action_to_response(empathy_fallback, user_emotion, memory.relationship_level)
|
858 |
+
|
859 |
+
# Learn from this interaction
|
860 |
+
character_dev.learn_from_interaction(request.message, user_emotion)
|
861 |
+
topic = character_dev.extract_topic(request.message)
|
862 |
+
memory.add_interaction(request.message, result, user_emotion, topic)
|
863 |
|
864 |
processing_time = round((time.time() - start_time) * 1000)
|
865 |
|
|
|
870 |
"processing_time": f"{processing_time}ms",
|
871 |
"character": request.char_name,
|
872 |
"situation": request.situation,
|
873 |
+
"location": request.location,
|
874 |
+
"enhanced_features": {
|
875 |
+
"user_emotion": user_emotion,
|
876 |
+
"relationship_level": memory.relationship_level,
|
877 |
+
"relationship_status": relationship_status,
|
878 |
+
"experience_points": character_dev.experience_points,
|
879 |
+
"conversation_style": character_dev.conversation_style_evolution,
|
880 |
+
"learned_preferences": character_dev.learned_preferences
|
881 |
+
}
|
882 |
}
|
883 |
|
884 |
except Exception as e:
|
885 |
print(f"β Character AI Error: {e}")
|
886 |
processing_time = round((time.time() - start_time) * 1000)
|
887 |
|
888 |
+
# Enhanced fallback with personality and emotion
|
889 |
+
session_id = request.session_id
|
890 |
+
if session_id in character_personalities:
|
891 |
+
personality = character_personalities[session_id]
|
892 |
+
emotional_ai = emotional_systems[session_id]
|
893 |
+
memory = conversation_memories[session_id]
|
894 |
+
|
895 |
+
user_emotion = emotional_ai.analyze_user_emotion(request.message)
|
896 |
+
|
897 |
+
base_fallbacks = [
|
898 |
+
f"maaf {request.user_name}, aku sedang bingung. Bisa ulangi lagi?",
|
899 |
+
f"hmm {request.user_name}, kayaknya aku butuh waktu sebentar untuk berpikir.",
|
900 |
+
f"ya {request.user_name}, coba pakai kata yang lebih sederhana?",
|
901 |
+
f"iya {request.user_name}, aku masih belajar nih. Sabar ya."
|
902 |
+
]
|
903 |
+
|
904 |
+
base_fallback = random.choice(base_fallbacks)
|
905 |
+
personality_fallback = personality.get_personality_modifier(base_fallback, user_emotion)
|
906 |
+
fallback = emotional_ai.generate_empathetic_response(user_emotion, personality_fallback, memory.relationship_level)
|
907 |
+
else:
|
908 |
+
fallback = f"maaf {request.user_name}, aku sedang bingung. Bisa ulangi lagi?"
|
909 |
|
910 |
return {
|
911 |
"response": fallback,
|
|
|
1028 |
except FileNotFoundError:
|
1029 |
return HTMLResponse(content="<h1>Frontend not found</h1>", status_code=404)
|
1030 |
|
1031 |
+
# Enhanced features endpoints
|
1032 |
+
@app.get("/memory/{session_id}")
|
1033 |
+
async def get_conversation_memory(session_id: str):
|
1034 |
+
"""Get conversation memory for a session"""
|
1035 |
+
if session_id not in conversation_memories:
|
1036 |
+
return {"error": "Session not found"}
|
1037 |
+
|
1038 |
+
memory = conversation_memories[session_id]
|
1039 |
+
return {
|
1040 |
+
"session_id": session_id,
|
1041 |
+
"relationship_level": memory.relationship_level,
|
1042 |
+
"relationship_status": memory.get_relationship_status(),
|
1043 |
+
"conversation_count": len(memory.history),
|
1044 |
+
"recent_interactions": memory.get_recent_context(5)
|
1045 |
+
}
|
1046 |
+
|
1047 |
+
@app.get("/personality/{session_id}")
|
1048 |
+
async def get_character_personality(session_id: str):
|
1049 |
+
"""Get character personality for a session"""
|
1050 |
+
if session_id not in character_personalities:
|
1051 |
+
return {"error": "Session not found"}
|
1052 |
+
|
1053 |
+
personality = character_personalities[session_id]
|
1054 |
+
character_dev = character_developments[session_id]
|
1055 |
+
|
1056 |
+
return {
|
1057 |
+
"session_id": session_id,
|
1058 |
+
"character_name": personality.name,
|
1059 |
+
"personality_traits": personality.traits,
|
1060 |
+
"interests": personality.interests,
|
1061 |
+
"speaking_style": personality.speaking_style,
|
1062 |
+
"experience_points": character_dev.experience_points,
|
1063 |
+
"conversation_style": character_dev.conversation_style_evolution,
|
1064 |
+
"learned_preferences": character_dev.learned_preferences,
|
1065 |
+
"topics_discussed": list(character_dev.topics_discussed)
|
1066 |
+
}
|
1067 |
+
|
1068 |
+
@app.delete("/session/{session_id}")
|
1069 |
+
async def reset_session(session_id: str):
|
1070 |
+
"""Reset all data for a session"""
|
1071 |
+
removed_systems = []
|
1072 |
+
|
1073 |
+
if session_id in conversation_memories:
|
1074 |
+
del conversation_memories[session_id]
|
1075 |
+
removed_systems.append("memory")
|
1076 |
+
|
1077 |
+
if session_id in character_personalities:
|
1078 |
+
del character_personalities[session_id]
|
1079 |
+
removed_systems.append("personality")
|
1080 |
+
|
1081 |
+
if session_id in character_developments:
|
1082 |
+
del character_developments[session_id]
|
1083 |
+
removed_systems.append("development")
|
1084 |
+
|
1085 |
+
if session_id in emotional_systems:
|
1086 |
+
del emotional_systems[session_id]
|
1087 |
+
removed_systems.append("emotional")
|
1088 |
+
|
1089 |
+
return {
|
1090 |
+
"message": f"Session {session_id} reset successfully",
|
1091 |
+
"removed_systems": removed_systems
|
1092 |
+
}
|
1093 |
+
|
1094 |
# API info endpoint
|
1095 |
@app.get("/api")
|
1096 |
async def api_info():
|
1097 |
return {
|
1098 |
+
"message": "Enhanced Character AI Backend Ready",
|
1099 |
+
"version": "2.0.0",
|
1100 |
+
"platform": "CPU Optimized with Advanced Roleplay",
|
1101 |
"endpoints": {
|
1102 |
"chat": "/chat",
|
1103 |
"models": "/models",
|
1104 |
"health": "/health",
|
1105 |
"config": "/config",
|
1106 |
+
"inference": "/inference",
|
1107 |
+
"memory": "/memory/{session_id}",
|
1108 |
+
"personality": "/personality/{session_id}",
|
1109 |
+
"reset_session": "/session/{session_id}"
|
1110 |
},
|
1111 |
+
"enhanced_features": [
|
1112 |
+
"Conversation Memory",
|
1113 |
+
"Dynamic Personality",
|
1114 |
+
"Emotional Intelligence",
|
1115 |
+
"Character Development",
|
1116 |
+
"Roleplay Actions",
|
1117 |
+
"Advanced Scenarios",
|
1118 |
+
"Relationship Tracking"
|
1119 |
+
],
|
1120 |
"frontend_url": "/"
|
1121 |
}
|
1122 |
|
index.html
CHANGED
@@ -395,11 +395,11 @@
|
|
395 |
.chat-container {
|
396 |
height: 100vh;
|
397 |
}
|
398 |
-
|
399 |
.bubble {
|
400 |
max-width: 85%;
|
401 |
}
|
402 |
-
|
403 |
.settings-popup {
|
404 |
right: 8px;
|
405 |
min-width: 260px;
|
@@ -535,7 +535,8 @@
|
|
535 |
userName: 'Kamu',
|
536 |
situation: 'Santai',
|
537 |
location: 'Ruang tamu',
|
538 |
-
maxLength: 150
|
|
|
539 |
};
|
540 |
|
541 |
// Emoji list
|
@@ -592,7 +593,7 @@
|
|
592 |
// Settings inputs
|
593 |
document.getElementById('charNameInput').addEventListener('input', updateCharName);
|
594 |
document.getElementById('maxLengthRange').addEventListener('input', updateMaxLength);
|
595 |
-
|
596 |
// Model select
|
597 |
document.getElementById('modelSelect').addEventListener('change', function() {
|
598 |
currentSettings.model = this.value;
|
@@ -656,11 +657,11 @@
|
|
656 |
const start = input.selectionStart;
|
657 |
const end = input.selectionEnd;
|
658 |
const text = input.value;
|
659 |
-
|
660 |
input.value = text.substring(0, start) + emoji + text.substring(end);
|
661 |
input.selectionStart = input.selectionEnd = start + emoji.length;
|
662 |
input.focus();
|
663 |
-
|
664 |
document.getElementById('emojiPicker').classList.remove('show');
|
665 |
}
|
666 |
|
@@ -676,10 +677,10 @@
|
|
676 |
const chatBody = document.getElementById('chatBody');
|
677 |
const messageDiv = document.createElement('div');
|
678 |
messageDiv.className = `message ${isUser ? 'user' : 'char'}`;
|
679 |
-
|
680 |
const time = showTime ? getCurrentTime() : '';
|
681 |
const checkmarks = isUser ? '<span class="checkmarks">ββ</span>' : '';
|
682 |
-
|
683 |
messageDiv.innerHTML = `
|
684 |
<div class="message-avatar"></div>
|
685 |
<div class="bubble">
|
@@ -690,7 +691,7 @@
|
|
690 |
</div>
|
691 |
</div>
|
692 |
`;
|
693 |
-
|
694 |
chatBody.appendChild(messageDiv);
|
695 |
chatBody.scrollTop = chatBody.scrollHeight;
|
696 |
}
|
@@ -698,10 +699,10 @@
|
|
698 |
function showTyping() {
|
699 |
if (isTyping) return;
|
700 |
isTyping = true;
|
701 |
-
|
702 |
document.getElementById('status').textContent = 'mengetik...';
|
703 |
document.getElementById('typingIndicator').classList.add('show');
|
704 |
-
|
705 |
const chatBody = document.getElementById('chatBody');
|
706 |
chatBody.scrollTop = chatBody.scrollHeight;
|
707 |
}
|
@@ -709,7 +710,7 @@
|
|
709 |
function hideTyping() {
|
710 |
if (!isTyping) return;
|
711 |
isTyping = false;
|
712 |
-
|
713 |
document.getElementById('status').textContent = 'online';
|
714 |
document.getElementById('typingIndicator').classList.remove('show');
|
715 |
}
|
@@ -717,32 +718,32 @@
|
|
717 |
async function sendMessage() {
|
718 |
const input = document.getElementById('messageInput');
|
719 |
const message = input.value.trim();
|
720 |
-
|
721 |
if (!message) return;
|
722 |
-
|
723 |
// Update settings from inputs
|
724 |
currentSettings.charName = document.getElementById('charNameInput').value || 'Sayang';
|
725 |
currentSettings.userName = document.getElementById('userNameInput').value || 'Kamu';
|
726 |
currentSettings.situation = document.getElementById('situationInput').value || 'Santai';
|
727 |
currentSettings.location = document.getElementById('locationInput').value || 'Ruang tamu';
|
728 |
-
|
729 |
// Add user message
|
730 |
addMessage(message, true);
|
731 |
input.value = '';
|
732 |
input.style.height = 'auto';
|
733 |
-
|
734 |
// Show typing
|
735 |
showTyping();
|
736 |
-
|
737 |
// Disable send button
|
738 |
const sendBtn = document.getElementById('sendBtn');
|
739 |
sendBtn.disabled = true;
|
740 |
-
|
741 |
try {
|
742 |
const response = await fetch(`${API_BASE}/chat`, {
|
743 |
method: 'POST',
|
744 |
headers: {
|
745 |
-
'Content-Type': 'application/json'
|
746 |
},
|
747 |
body: JSON.stringify({
|
748 |
message: message,
|
@@ -751,29 +752,43 @@
|
|
751 |
location: currentSettings.location,
|
752 |
char_name: currentSettings.charName,
|
753 |
user_name: currentSettings.userName,
|
754 |
-
max_length: currentSettings.maxLength
|
|
|
755 |
})
|
756 |
});
|
757 |
-
|
758 |
const data = await response.json();
|
759 |
-
|
760 |
// Simulate typing delay
|
761 |
await new Promise(resolve => setTimeout(resolve, 1000 + Math.random() * 2000));
|
762 |
-
|
763 |
hideTyping();
|
764 |
-
|
765 |
if (data.status === 'success') {
|
766 |
-
addMessage(data.response);
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
767 |
} else {
|
768 |
-
addMessage('Maaf, ada masalah dengan sistem. Coba lagi ya!
|
769 |
}
|
770 |
-
|
771 |
} catch (error) {
|
772 |
hideTyping();
|
773 |
console.error('Error:', error);
|
774 |
addMessage('Ups, koneksi bermasalah. Coba lagi nanti ya! π');
|
775 |
}
|
776 |
-
|
777 |
// Re-enable send button
|
778 |
sendBtn.disabled = false;
|
779 |
}
|
|
|
395 |
.chat-container {
|
396 |
height: 100vh;
|
397 |
}
|
398 |
+
|
399 |
.bubble {
|
400 |
max-width: 85%;
|
401 |
}
|
402 |
+
|
403 |
.settings-popup {
|
404 |
right: 8px;
|
405 |
min-width: 260px;
|
|
|
535 |
userName: 'Kamu',
|
536 |
situation: 'Santai',
|
537 |
location: 'Ruang tamu',
|
538 |
+
maxLength: 150,
|
539 |
+
sessionId: 'default_session' // Added session ID
|
540 |
};
|
541 |
|
542 |
// Emoji list
|
|
|
593 |
// Settings inputs
|
594 |
document.getElementById('charNameInput').addEventListener('input', updateCharName);
|
595 |
document.getElementById('maxLengthRange').addEventListener('input', updateMaxLength);
|
596 |
+
|
597 |
// Model select
|
598 |
document.getElementById('modelSelect').addEventListener('change', function() {
|
599 |
currentSettings.model = this.value;
|
|
|
657 |
const start = input.selectionStart;
|
658 |
const end = input.selectionEnd;
|
659 |
const text = input.value;
|
660 |
+
|
661 |
input.value = text.substring(0, start) + emoji + text.substring(end);
|
662 |
input.selectionStart = input.selectionEnd = start + emoji.length;
|
663 |
input.focus();
|
664 |
+
|
665 |
document.getElementById('emojiPicker').classList.remove('show');
|
666 |
}
|
667 |
|
|
|
677 |
const chatBody = document.getElementById('chatBody');
|
678 |
const messageDiv = document.createElement('div');
|
679 |
messageDiv.className = `message ${isUser ? 'user' : 'char'}`;
|
680 |
+
|
681 |
const time = showTime ? getCurrentTime() : '';
|
682 |
const checkmarks = isUser ? '<span class="checkmarks">ββ</span>' : '';
|
683 |
+
|
684 |
messageDiv.innerHTML = `
|
685 |
<div class="message-avatar"></div>
|
686 |
<div class="bubble">
|
|
|
691 |
</div>
|
692 |
</div>
|
693 |
`;
|
694 |
+
|
695 |
chatBody.appendChild(messageDiv);
|
696 |
chatBody.scrollTop = chatBody.scrollHeight;
|
697 |
}
|
|
|
699 |
function showTyping() {
|
700 |
if (isTyping) return;
|
701 |
isTyping = true;
|
702 |
+
|
703 |
document.getElementById('status').textContent = 'mengetik...';
|
704 |
document.getElementById('typingIndicator').classList.add('show');
|
705 |
+
|
706 |
const chatBody = document.getElementById('chatBody');
|
707 |
chatBody.scrollTop = chatBody.scrollHeight;
|
708 |
}
|
|
|
710 |
function hideTyping() {
|
711 |
if (!isTyping) return;
|
712 |
isTyping = false;
|
713 |
+
|
714 |
document.getElementById('status').textContent = 'online';
|
715 |
document.getElementById('typingIndicator').classList.remove('show');
|
716 |
}
|
|
|
718 |
async function sendMessage() {
|
719 |
const input = document.getElementById('messageInput');
|
720 |
const message = input.value.trim();
|
721 |
+
|
722 |
if (!message) return;
|
723 |
+
|
724 |
// Update settings from inputs
|
725 |
currentSettings.charName = document.getElementById('charNameInput').value || 'Sayang';
|
726 |
currentSettings.userName = document.getElementById('userNameInput').value || 'Kamu';
|
727 |
currentSettings.situation = document.getElementById('situationInput').value || 'Santai';
|
728 |
currentSettings.location = document.getElementById('locationInput').value || 'Ruang tamu';
|
729 |
+
|
730 |
// Add user message
|
731 |
addMessage(message, true);
|
732 |
input.value = '';
|
733 |
input.style.height = 'auto';
|
734 |
+
|
735 |
// Show typing
|
736 |
showTyping();
|
737 |
+
|
738 |
// Disable send button
|
739 |
const sendBtn = document.getElementById('sendBtn');
|
740 |
sendBtn.disabled = true;
|
741 |
+
|
742 |
try {
|
743 |
const response = await fetch(`${API_BASE}/chat`, {
|
744 |
method: 'POST',
|
745 |
headers: {
|
746 |
+
'Content-Type': 'application/json'
|
747 |
},
|
748 |
body: JSON.stringify({
|
749 |
message: message,
|
|
|
752 |
location: currentSettings.location,
|
753 |
char_name: currentSettings.charName,
|
754 |
user_name: currentSettings.userName,
|
755 |
+
max_length: currentSettings.maxLength,
|
756 |
+
session_id: currentSettings.sessionId
|
757 |
})
|
758 |
});
|
759 |
+
|
760 |
const data = await response.json();
|
761 |
+
|
762 |
// Simulate typing delay
|
763 |
await new Promise(resolve => setTimeout(resolve, 1000 + Math.random() * 2000));
|
764 |
+
|
765 |
hideTyping();
|
766 |
+
|
767 |
if (data.status === 'success') {
|
768 |
+
addMessage(data.response, 'character');
|
769 |
+
|
770 |
+
// Update enhanced features if available
|
771 |
+
if (data.enhanced_features) {
|
772 |
+
enhancedFeatures = { ...enhancedFeatures, ...data.enhanced_features };
|
773 |
+
updateEnhancedUI();
|
774 |
+
}
|
775 |
+
|
776 |
+
// Update status with enhanced info
|
777 |
+
const relationshipInfo = data.enhanced_features ?
|
778 |
+
` | Relationship: ${data.enhanced_features.relationship_status} (${data.enhanced_features.relationship_level})` : '';
|
779 |
+
|
780 |
+
document.getElementById('status').textContent =
|
781 |
+
`Model: ${data.model} | Time: ${data.processing_time}${relationshipInfo}`;
|
782 |
} else {
|
783 |
+
addMessage(data.response || 'Maaf, ada masalah dengan sistem. Coba lagi ya!', 'character');
|
784 |
}
|
785 |
+
|
786 |
} catch (error) {
|
787 |
hideTyping();
|
788 |
console.error('Error:', error);
|
789 |
addMessage('Ups, koneksi bermasalah. Coba lagi nanti ya! π');
|
790 |
}
|
791 |
+
|
792 |
// Re-enable send button
|
793 |
sendBtn.disabled = false;
|
794 |
}
|
requirements.txt
CHANGED
@@ -1,7 +1,7 @@
|
|
1 |
-
fastapi
|
2 |
-
uvicorn
|
3 |
-
transformers
|
4 |
-
torch
|
5 |
-
|
6 |
-
|
7 |
-
|
|
|
1 |
+
fastapi==0.104.1
|
2 |
+
uvicorn==0.24.0
|
3 |
+
transformers==4.35.2
|
4 |
+
torch==2.1.1
|
5 |
+
pydantic==2.5.0
|
6 |
+
python-multipart==0.0.6
|
7 |
+
numpy==1.24.3
|