BasilTh
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Commit
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7ceb07f
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Parent(s):
da2916f
Deploy updated SLM customer-support chatbot
Browse files- SLM_CService.py +74 -30
SLM_CService.py
CHANGED
@@ -1,5 +1,5 @@
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# ββ SLM_CService.py βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# Customer-support-only chatbot with strict NSFW blocking +
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import os
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import re
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@@ -20,13 +20,19 @@ REPO = "ThomasBasil/bitext-qlora-tinyllama"
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BASE = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
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GEN_KW = dict(
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max_new_tokens=160,
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-
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)
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bnb_cfg = BitsAndBytesConfig(
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load_in_4bit=True,
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-
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)
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# ---- Tokenizer & model -------------------------------------------------------
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@@ -36,22 +42,33 @@ if tokenizer.pad_token_id is None and tokenizer.eos_token_id is not None:
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tokenizer.padding_side = "left"
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tokenizer.truncation_side = "right"
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model, _ = unsloth.FastLanguageModel.from_pretrained(
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model_name=BASE,
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-
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)
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unsloth.FastLanguageModel.for_inference(model)
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model = PeftModel.from_pretrained(model, REPO)
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model.eval()
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chat_pipe = pipeline(
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"text-generation",
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-
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)
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# Moderation
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from transformers import TextClassificationPipeline
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SEXUAL_TERMS = [
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"sex","sexual","porn","nsfw","fetish","kink","bdsm","nude","naked","anal",
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"blowjob","handjob","cum","breast","boobs","vagina","penis","semen","ejaculate",
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@@ -87,27 +104,39 @@ def is_sexual_or_toxic(text: str) -> bool:
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return True
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except Exception: pass
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return False
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REFUSAL = ("Sorry, I canβt help with that. Iβm only for store support "
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"(orders, shipping, ETA, tracking, returns, warranty, account).")
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# Memory + globals
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memory = ConversationBufferMemory(return_messages=True)
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SYSTEM_PROMPT = (
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"You are a customer-support assistant for our store. Only handle account, "
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"orders, shipping, delivery ETA, tracking links, returns/refunds, warranty, and store policy. "
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"If a request is out of scope or sexual/NSFW, refuse briefly and offer support options. "
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"Be concise and professional."
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)
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ALLOWED_KEYWORDS = (
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"order","track","status","delivery","shipping","ship","eta","arrive",
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"refund","return","exchange","warranty","guarantee","account","billing",
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"address","cancel","
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)
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order_re = re.compile(r"#(\d{1,10})")
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def extract_order(text: str):
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m =
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def handle_status(o): return f"Order #{o} is in transit and should arrive in 3β5 business days."
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def handle_eta(o): return f"Delivery for order #{o} typically takes 3β5 days; you can track it at https://track.example.com/{o}"
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@@ -116,13 +145,17 @@ def handle_link(o): return f"Hereβs the latest tracking link for order #{o}:
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def handle_return_policy(_=None):
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return ("Our return policy allows returns of unused items in original packaging within 30 days of receipt. "
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"Would you like me to connect you with a human agent?")
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def handle_cancel(o=None):
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return (f"Iβve submitted a cancellation request for order #{o}. If it has already shipped, "
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"weβll process a return/refund once itβs back. Youβll receive a confirmation email shortly.")
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def handle_gratitude(_=None): return "Youβre welcome! Anything else I can help with?"
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def handle_escalation(_=None): return "I can connect you with a human agent. Would you like me to do that?"
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# >>> state that must reset <<<
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stored_order = None
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pending_intent = None
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@@ -131,7 +164,6 @@ def reset_state():
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global stored_order, pending_intent
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stored_order = None
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pending_intent = None
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# clear conversation buffer (official API) :contentReference[oaicite:3]{index=3}
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try: memory.clear()
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except Exception: pass
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return True
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@@ -164,7 +196,7 @@ def chat_with_memory(user_input: str) -> str:
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if not ui:
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return "How can I help with your order today?"
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#
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hist = memory.load_memory_variables({}).get("chat_history", []) or []
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if len(hist) == 0:
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stored_order = None
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@@ -183,12 +215,8 @@ def chat_with_memory(user_input: str) -> str:
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reply = handle_gratitude()
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memory.save_context({"input": ui}, {"output": reply})
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return reply
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if "return" in low:
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reply = handle_return_policy()
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memory.save_context({"input": ui}, {"output": reply})
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return reply
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# 3) Order number FIRST
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new_o = extract_order(ui)
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if new_o:
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stored_order = new_o
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@@ -197,15 +225,19 @@ def chat_with_memory(user_input: str) -> str:
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"link": handle_link,"cancel": handle_cancel}[pending_intent]
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reply = fn(stored_order); pending_intent = None
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memory.save_context({"input": ui}, {"output": reply}); return reply
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# 4) Support-only guard (skip if
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if pending_intent is None
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if not any(k in low for k in ALLOWED_KEYWORDS) and not any(k in low for k in ("hi","hello","hey")):
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reply = "Iβm for store support only (orders, shipping, returns, warranty, account). How can I help with those?"
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memory.save_context({"input": ui}, {"output": reply})
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return reply
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# 5)
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if any(k in low for k in ["status","where is my order","check status"]):
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intent = "status"
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elif any(k in low for k in ["how long","eta","delivery time"]):
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@@ -214,11 +246,16 @@ def chat_with_memory(user_input: str) -> str:
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intent = "track"
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elif "tracking link" in low or "resend" in low or "link" in low:
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intent = "link"
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elif "cancel"
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intent = "cancel"
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else:
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intent = "fallback"
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if intent in ("status","eta","track","link","cancel"):
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if not stored_order:
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pending_intent = intent
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@@ -227,10 +264,17 @@ def chat_with_memory(user_input: str) -> str:
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fn = {"status": handle_status,"eta": handle_eta,"track": handle_track,
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"link": handle_link,"cancel": handle_cancel}[intent]
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reply = fn(stored_order)
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memory.save_context({"input": ui}, {"output": reply})
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#
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reply = _generate_reply(ui)
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if is_sexual_or_toxic(reply): reply = REFUSAL
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memory.save_context({"input": ui}, {"output": reply})
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# ββ SLM_CService.py βββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# Customer-support-only chatbot with strict NSFW blocking + robust FSM.
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import os
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import re
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BASE = "TinyLlama/TinyLlama-1.1B-Chat-v1.0"
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GEN_KW = dict(
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max_new_tokens=160,
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do_sample=True,
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top_p=0.9,
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temperature=0.7,
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repetition_penalty=1.1,
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no_repeat_ngram_size=4,
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)
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bnb_cfg = BitsAndBytesConfig(
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load_in_4bit=True,
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bnb_4bit_quant_type="nf4",
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bnb_4bit_use_double_quant=True,
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bnb_4bit_compute_dtype=torch.float16,
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)
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# ---- Tokenizer & model -------------------------------------------------------
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tokenizer.padding_side = "left"
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tokenizer.truncation_side = "right"
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# Unsloth returns (model, tokenizer) β unpack
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model, _ = unsloth.FastLanguageModel.from_pretrained(
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model_name=BASE,
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load_in_4bit=True,
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quantization_config=bnb_cfg,
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device_map="auto",
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trust_remote_code=True,
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)
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unsloth.FastLanguageModel.for_inference(model)
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# Apply your PEFT adapter from repo root
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model = PeftModel.from_pretrained(model, REPO)
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model.eval()
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# Text-generation pipeline (pass gen params at call time)
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chat_pipe = pipeline(
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"text-generation",
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model=model,
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tokenizer=tokenizer,
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trust_remote_code=True,
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return_full_text=False,
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)
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# Moderation & blocking (strict)
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from transformers import TextClassificationPipeline
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SEXUAL_TERMS = [
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"sex","sexual","porn","nsfw","fetish","kink","bdsm","nude","naked","anal",
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"blowjob","handjob","cum","breast","boobs","vagina","penis","semen","ejaculate",
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return True
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except Exception: pass
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return False
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REFUSAL = ("Sorry, I canβt help with that. Iβm only for store support "
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"(orders, shipping, ETA, tracking, returns, warranty, account).")
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# ββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββββ
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# Memory + globals
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memory = ConversationBufferMemory(return_messages=True)
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SYSTEM_PROMPT = (
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"You are a customer-support assistant for our store. Only handle account, "
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"orders, shipping, delivery ETA, tracking links, returns/refunds, warranty, and store policy. "
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"If a request is out of scope or sexual/NSFW, refuse briefly and offer support options. "
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"Be concise and professional."
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)
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+
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ALLOWED_KEYWORDS = (
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"order","track","status","delivery","shipping","ship","eta","arrive",
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"refund","return","exchange","warranty","guarantee","policy","account","billing",
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"address","cancel","help","support","agent","human"
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)
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# Robust order detection:
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# - "#67890" / "# 67890"
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# - "order 67890", "order no. 67890", "order number 67890", "order id 67890"
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ORDER_RX = re.compile(
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r"(?:#\s*(\d{3,12})|order(?:\s*(?:no\.?|number|id))?\s*#?\s*(\d{3,12}))",
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flags=re.I,
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)
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def extract_order(text: str):
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m = ORDER_RX.search(text or "")
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if not m: return None
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return m.group(1) or m.group(2)
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def handle_status(o): return f"Order #{o} is in transit and should arrive in 3β5 business days."
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def handle_eta(o): return f"Delivery for order #{o} typically takes 3β5 days; you can track it at https://track.example.com/{o}"
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def handle_return_policy(_=None):
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return ("Our return policy allows returns of unused items in original packaging within 30 days of receipt. "
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"Would you like me to connect you with a human agent?")
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def handle_warranty_policy(_=None):
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return ("We provide a 1-year limited warranty against manufacturing defects. "
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"For issues within 30 days, you can return or exchange; after that, warranty service applies. "
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"Need help starting a claim?")
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def handle_cancel(o=None):
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return (f"Iβve submitted a cancellation request for order #{o}. If it has already shipped, "
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"weβll process a return/refund once itβs back. Youβll receive a confirmation email shortly.")
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def handle_gratitude(_=None): return "Youβre welcome! Anything else I can help with?"
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def handle_escalation(_=None): return "I can connect you with a human agent. Would you like me to do that?"
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def handle_ask_action(o): return (f"Iβve saved order #{o}. What would you like to do β status, ETA, tracking link, or cancel?")
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stored_order = None
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pending_intent = None
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global stored_order, pending_intent
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stored_order = None
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pending_intent = None
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try: memory.clear()
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except Exception: pass
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return True
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if not ui:
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return "How can I help with your order today?"
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# Fresh session guard
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hist = memory.load_memory_variables({}).get("chat_history", []) or []
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if len(hist) == 0:
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stored_order = None
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reply = handle_gratitude()
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memory.save_context({"input": ui}, {"output": reply})
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return reply
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# 3) Order number FIRST (so βItβs # 67890β completes the prior request)
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new_o = extract_order(ui)
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if new_o:
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stored_order = new_o
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"link": handle_link,"cancel": handle_cancel}[pending_intent]
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reply = fn(stored_order); pending_intent = None
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memory.save_context({"input": ui}, {"output": reply}); return reply
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# no pending intent β ask what they want to do with this order
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reply = handle_ask_action(stored_order)
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memory.save_context({"input": ui}, {"output": reply})
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return reply
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# 4) Support-only guard (skip if we have a pending intent)
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if pending_intent is None:
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if not any(k in low for k in ALLOWED_KEYWORDS) and not any(k in low for k in ("hi","hello","hey")):
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reply = "Iβm for store support only (orders, shipping, returns, warranty, account). How can I help with those?"
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memory.save_context({"input": ui}, {"output": reply})
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return reply
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# 5) Intent classification (added warranty/guarantee/policy)
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if any(k in low for k in ["status","where is my order","check status"]):
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intent = "status"
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elif any(k in low for k in ["how long","eta","delivery time"]):
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intent = "track"
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elif "tracking link" in low or "resend" in low or "link" in low:
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intent = "link"
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elif any(k in low for k in ["cancel","cancellation","abort order"]):
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intent = "cancel"
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elif any(k in low for k in ["warranty","guarantee","policy"]):
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intent = "warranty_policy"
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elif "return" in low:
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intent = "return_policy"
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else:
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intent = "fallback"
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# 6) Handle intents
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if intent in ("status","eta","track","link","cancel"):
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if not stored_order:
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pending_intent = intent
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fn = {"status": handle_status,"eta": handle_eta,"track": handle_track,
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"link": handle_link,"cancel": handle_cancel}[intent]
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reply = fn(stored_order)
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memory.save_context({"input": ui}, {"output": reply}); return reply
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if intent == "warranty_policy":
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reply = handle_warranty_policy()
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memory.save_context({"input": ui}, {"output": reply}); return reply
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if intent == "return_policy":
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reply = handle_return_policy()
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memory.save_context({"input": ui}, {"output": reply}); return reply
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# 7) LLM fallback (on-topic) + post-check
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reply = _generate_reply(ui)
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if is_sexual_or_toxic(reply): reply = REFUSAL
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memory.save_context({"input": ui}, {"output": reply})
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