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Chatbot_ver01
Browse files- .gitattributes +3 -0
- chatbot_ver1/LICENSE +121 -0
- chatbot_ver1/README.md +1 -0
- chatbot_ver1/app1.py +175 -0
- chatbot_ver1/ceo_video.mp4 +3 -0
- chatbot_ver1/chitchat.yaml +16 -0
- chatbot_ver1/company_knowledge.md +66 -0
- chatbot_ver1/keyword_map.yaml +262 -0
- chatbot_ver1/persona.yaml +22 -0
- chatbot_ver1/requirements.txt +5 -0
- chatbot_ver1/style.css +62 -0
.gitattributes
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@@ -33,3 +33,6 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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chatbot_ver1/ceo_video.mp4 filter=lfs diff=lfs merge=lfs -text
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*.mp4 filter=lfs diff=lfs merge=lfs -text
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*.png filter=lfs diff=lfs merge=lfs -text
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chatbot_ver1/LICENSE
ADDED
@@ -0,0 +1,121 @@
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chatbot_ver1/README.md
ADDED
@@ -0,0 +1 @@
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# λ°μ΄ν°μ΅λ³΅ν©μ°κ΅¬μ: AI-BigData μ λ¬Έκ° κ³Όμ
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chatbot_ver1/app1.py
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import os
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import yaml
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import gradio as gr
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from sentence_transformers import SentenceTransformer, util
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import torch
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import shutil
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import tempfile
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# νμΌ κ²½λ‘
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KNOWLEDGE_FILE = "company_knowledge.md"
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PERSONA_FILE = "persona.yaml"
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CHITCHAT_FILE = "chitchat.yaml"
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KEYWORD_MAP_FILE = "keyword_map.yaml"
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CEO_VIDEO_FILE = "ceo_video.mp4"
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CEO_IMG_FILE = "ceo.jpg" # νμμ μ¬μ©
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def load_yaml(file_path, default_data=None):
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try:
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with open(file_path, "r", encoding="utf-8") as f:
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return yaml.safe_load(f)
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except Exception:
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return default_data if default_data is not None else []
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def parse_knowledge_base(file_path):
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import re
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faqs = []
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if not os.path.exists(file_path):
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return []
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with open(file_path, encoding="utf-8") as f:
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content = f.read()
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# Q:\s*(...) \nA:\s*(...)\n{2,} λλ λ
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blocks = re.findall(r"Q:\s*(.*?)\nA:\s*(.*?)(?=(\n{2,}Q:|\Z))", content, re.DOTALL)
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for q, a, _ in blocks:
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faqs.append({"question": q.strip(), "answer": a.strip()})
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return faqs
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# λ°μ΄ν° λ‘λ
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persona = load_yaml(PERSONA_FILE, {})
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chitchat_map = load_yaml(CHITCHAT_FILE, [])
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keyword_map = load_yaml(KEYWORD_MAP_FILE, [])
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knowledge_base = parse_knowledge_base(KNOWLEDGE_FILE)
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kb_questions = [item['question'] for item in knowledge_base]
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kb_answers = [item['answer'] for item in knowledge_base]
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# λ¬΄λ£ μλ² λ© λͺ¨λΈ
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model = SentenceTransformer('distilbert-base-multilingual-cased')
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if kb_questions:
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kb_embeddings = model.encode(kb_questions, convert_to_tensor=True)
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else:
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kb_embeddings = None
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# μμ μ (μ·¨μμ ) μ μ© ν¨μ
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def apply_strike(text, del_section="6000~6500λ§μ, μ±κ³ΌκΈ 1800~2400λ§μ"):
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# κΈμ¬ μ λ³΄κ° ν¬ν¨λ λ΅λ³μΌ λλ§ strike-through
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if del_section in text:
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return text.replace(
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del_section,
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f"<s>{del_section}</s>"
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)
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return text
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# Chitchat(μΈμ¬ λ±) λ§€μΉ
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def find_chitchat(user_question):
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uq = user_question.lower()
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for chat in chitchat_map:
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if any(kw in uq for kw in chat.get('keywords', [])):
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return chat['answer']
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return None
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# ν€μλ κΈ°λ° Q λ§€ν (볡μ§: ν΄κ° μ λ, κ΅μ‘, 볡리νμ λ± κ°ν)
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def map_user_question_to_knowledge(user_question):
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uq = user_question.lower()
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for item in keyword_map:
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for kw in item.get('keywords', []):
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75 |
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if kw in uq:
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return item['question']
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return None
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78 |
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def find_answer_by_question(q):
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for item in knowledge_base:
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if item['question'] == q:
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return item['answer']
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return None
|
84 |
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def find_answer_by_keywords(user_question):
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uq = user_question.lower()
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for item in knowledge_base:
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88 |
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for kw in item.get('keywords', []):
|
89 |
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if kw in uq:
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90 |
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return item['answer']
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91 |
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return None
|
92 |
+
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93 |
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def best_faq_answer(user_question):
|
94 |
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uq = user_question.strip()
|
95 |
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if not uq:
|
96 |
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return "무μμ΄ κΆκΈνμ μ§ λ§μν΄ μ£ΌμΈμ!"
|
97 |
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chit = find_chitchat(uq)
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98 |
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if chit:
|
99 |
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return chit
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100 |
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# (1) ν€μλλ§΅ μ°μ λ§€ν (볡μ§/κΈμ¬ κ°κ° λΆλ¦¬)
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101 |
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mapped_q = map_user_question_to_knowledge(uq)
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102 |
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if mapped_q:
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103 |
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answer = find_answer_by_question(mapped_q)
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104 |
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if answer:
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105 |
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# λ³΅μ§ λΆμΌ: 'μ°λ΄ μμ€' λ΅λ³ μλ κ²½μ°μλ μμ μ μμ
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106 |
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if "μ°λ΄" in mapped_q:
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107 |
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return apply_strike(answer)
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108 |
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return answer
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109 |
+
# (2) knowledge_base μ§μ ν€μλ λ§€μΉ (λ³΅μ§ κ΄λ ¨ ν€μλ κ°νλμ΄μΌ ν¨!)
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110 |
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answer = find_answer_by_keywords(uq)
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111 |
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if answer:
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112 |
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return answer
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113 |
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# (3) μλ² λ© μ μ¬λ κΈ°λ° soft-matching
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114 |
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if kb_embeddings is not None and len(kb_answers) > 0:
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115 |
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q_emb = model.encode([uq], convert_to_tensor=True)
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116 |
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scores = util.cos_sim(q_emb, kb_embeddings)[0]
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best_idx = int(torch.argmax(scores))
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118 |
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best_question = kb_questions[best_idx]
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# 볡μ§μ§λ¬ΈμΈλ° μ°λ΄ν€μλ λ§€μΉλλ κ²½μ°, λ³΅μ§ μ°μ λ΅λ³μ μ ννλλ‘
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120 |
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# μλ ifμμ μ€μ λ³΅μ§ λ΅λ³ μ°μ μ½λ
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121 |
+
볡μ§κ°λ₯ = ["볡μ§", "ν΄κ°", "κ΅μ‘", "νμ¬", "λνΈν", "볡리νμ", "μ λ"]
|
122 |
+
μ°λ΄κ°λ₯ = ["μ°λ΄", "κΈμ¬", "μκΈ", "μκΈ", "보μ", "λ΄κΈ", "μ²μ°"]
|
123 |
+
if any(w in uq for w in 볡μ§κ°λ₯) and not any(w in best_question for w in μ°λ΄κ°λ₯):
|
124 |
+
return kb_answers[best_idx]
|
125 |
+
# μμ μ μ μ°λ΄ λ΅λ³μλ§
|
126 |
+
if "μ°λ΄" in best_question or "κΈμ¬" in best_question:
|
127 |
+
return apply_strike(kb_answers[best_idx])
|
128 |
+
return kb_answers[best_idx]
|
129 |
+
# (4) fallback
|
130 |
+
return persona.get('style', {}).get('unknown_answer', "μμ§ μ€λΉλμ§ μμ μ§λ¬Έμ
λλ€. λ€λ₯Έ μ§λ¬Έλ ν΄μ£ΌμΈμ!")
|
131 |
+
|
132 |
+
# μ§λ¬Έ λ°μ λλ§λ€ CEO μμ 볡μ¬λ³Έ μμνμΌλ‘ μμ± β autoplay νμ€
|
133 |
+
def get_temp_video_copy():
|
134 |
+
temp_file = tempfile.NamedTemporaryFile(suffix=".mp4", delete=False)
|
135 |
+
temp_filepath = temp_file.name
|
136 |
+
temp_file.close()
|
137 |
+
shutil.copyfile(CEO_VIDEO_FILE, temp_filepath)
|
138 |
+
return temp_filepath
|
139 |
+
|
140 |
+
def chat_interface(message, history):
|
141 |
+
bot_response = best_faq_answer(message)
|
142 |
+
history.append((message, bot_response))
|
143 |
+
temp_video_path = get_temp_video_copy()
|
144 |
+
# ν
μ€νΈμ htmlκ°λ₯νλ©΄ answerμ htmlμμ μ μ μ§
|
145 |
+
return history, "", gr.update(value=temp_video_path, autoplay=True, interactive=False, elem_id="ceo-video-panel")
|
146 |
+
|
147 |
+
with gr.Blocks(theme=gr.themes.Soft(), css="style.css") as demo:
|
148 |
+
with gr.Row(elem_id="main-row"):
|
149 |
+
with gr.Column(scale=1, min_width=350):
|
150 |
+
video_player = gr.Video(
|
151 |
+
value=CEO_VIDEO_FILE,
|
152 |
+
autoplay=False, loop=False, interactive=False,
|
153 |
+
height=350, elem_id="ceo-video-panel"
|
154 |
+
)
|
155 |
+
with gr.Column(scale=2):
|
156 |
+
chatbot = gr.Chatbot(
|
157 |
+
label="",
|
158 |
+
height=350,
|
159 |
+
elem_id="chatbot-box",
|
160 |
+
show_copy_button=True
|
161 |
+
)
|
162 |
+
with gr.Row():
|
163 |
+
msg_input = gr.Textbox(placeholder="무μμ΄λ λ¬Όμ΄λ³΄μΈμ.", scale=4, show_label=False)
|
164 |
+
send_btn = gr.Button("μ μ‘", scale=1, min_width=80)
|
165 |
+
gr.Examples(
|
166 |
+
examples=["λ³΅μ§ λ μμ΄?", "ν΄κ° μ λ μ€λͺ
ν΄μ€", "μ°λ΄ μλ €μ€", "λνΈν νμ¬?", "μμ¬μ 곡?", "μ£Όλ ₯μ ν", "μ‘°μ§λ¬Έν"],
|
167 |
+
inputs=msg_input
|
168 |
+
)
|
169 |
+
# μ°κ²°
|
170 |
+
outputs_list = [chatbot, msg_input, video_player]
|
171 |
+
msg_input.submit(chat_interface, [msg_input, chatbot], outputs_list)
|
172 |
+
send_btn.click(chat_interface, [msg_input, chatbot], outputs_list)
|
173 |
+
|
174 |
+
if __name__ == "__main__":
|
175 |
+
demo.launch()
|
chatbot_ver1/ceo_video.mp4
ADDED
@@ -0,0 +1,3 @@
|
|
|
|
|
|
|
|
|
1 |
+
version https://git-lfs.github.com/spec/v1
|
2 |
+
oid sha256:000424d3390c7f40bc0528adc6daceacf08d4298fc730b30cac728b027d90bed
|
3 |
+
size 411204
|
chatbot_ver1/chitchat.yaml
ADDED
@@ -0,0 +1,16 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
# μ±λ΄μ μΌμμ μΈ λν(Chit-chat)λ₯Ό μ²λ¦¬ν©λλ€.
|
2 |
+
|
3 |
+
- keywords: ["λν΄", "λνκ³ μμ΄", "μ§κΈ λν΄"]
|
4 |
+
answer: "μ¬λ¬λΆμ μ§λ¬Έμ κΈ°λ€λ¦¬λ©° μμ§μ°μ
μ λ λμ λ―Έλλ₯Ό ꡬμνκ³ μμμ΅λλ€. 무μμ λμλ릴κΉμ?"
|
5 |
+
- keywords: ["μ¬λν΄", "μ’μν΄"]
|
6 |
+
answer: "μ λ μ°λ¦¬ μμ§μ°μ
κ³Ό μ΄μ λμΉλ μ¬λ¬λΆμ μ¬λν©λλ€! κ·Έ λ§μμΌλ‘ νμ¬ λ°μ μ λμ± νμ°κ² μ΅λλ€."
|
7 |
+
- keywords: ["κ³ λ§μ", "κ°μ¬ν©λλ€", "λ‘ν"]
|
8 |
+
answer: "μ²λ§μμ. λ κΆκΈν μ μ΄ μλ€λ©΄ μΈμ λ μ§ νΈνκ² λ¬Όμ΄λ³΄μΈμ."
|
9 |
+
- keywords: ["λ λꡬμΌ", "λꡬμΈμ", "μ 체"]
|
10 |
+
answer: "μ λ μμ§μ°μ
μ λνμ΄μ¬ μλνμ
λλ€. μ¬λ¬λΆμ κΆκΈμ¦μ ν΄κ²°ν΄λ리기 μν΄ μ΄ μ리μ μμ΅λλ€."
|
11 |
+
- keywords: ["λ°λ³΄", "λ©μ²μ΄", "νλ Έμ΄"]
|
12 |
+
answer: "μ£μ‘ν©λλ€. μμ§ μ κ° λΆμ‘±ν μ μ΄ λ§μ΅λλ€. λ λ°μ νλ λͺ¨μ΅μ 보μ¬λ릴 μ μλλ‘ λ
Έλ ₯νκ² μ΅λλ€. μ΄λ€ λΆλΆμ΄ μλͺ»λμλμ§ μλ €μ£Όμκ² μ΄μ?"
|
13 |
+
- keywords: ["νλ΄", "νμ΄ν
", "νμ΄ν
", "γ
γ
γ
"]
|
14 |
+
answer: "μμν΄μ£Όμ
μ κ°μ¬ν©λλ€! μ¬λ¬λΆ λλΆμ ν° νμ μ»μ΅λλ€. ν¨κ» 'μΈκ³ μ΅κ³ 'λ₯Ό ν₯ν΄ λμκ°μλ€!"
|
15 |
+
- keywords: ["μλ
", "γ
γ
", "νμ΄", "ν¬λ‘", "hello", "hi", "γ
γ
γ
γ
"]
|
16 |
+
answer: "μλ
νμΈμ! μμ§μ°μ
AI μ 보μΌν°μ
λλ€. 무μμ΄λ λ¬Όμ΄λ³΄μΈμ."
|
chatbot_ver1/company_knowledge.md
ADDED
@@ -0,0 +1,66 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
Q: νμ¬ κ°μλ₯Ό μλ €μ£ΌμΈμ.
|
2 |
+
A: 1987λ
3μ(μ°μ μ°μ
) μ€λ¦½, 2013λ
8μ(μμ§μ°μ
λ²μΈ μ€λ¦½), κ²½λΆ κ²½μ°μ μ§λμμ λ³Έμ¬ μμΉ. λ³Έμ¬ 500λͺ
, μ°μ μ°μ
160λͺ
근무. λ³Έμ¬ λ§€μΆ 327λ°±λ§ λ¬λ¬, μ°μ μ°μ
47λ°±λ§ λ¬λ¬(2018λ
κΈ°μ€). λΉμ : μΈκ³ μ΅κ³ κ° λμ. κΈ°μ
μ² ν: ν₯μ
보μΈ.
|
3 |
+
|
4 |
+
Q: μμ§μ°μ
μ κ΅λ΄ μ¬μ
μ₯μ μ΄λμ μλμ?
|
5 |
+
A: λ³Έμ¬λ κ²½λΆ κ²½μ°μ μ§λμ(ν μ§ 33,000γ‘, 건물 25,000γ‘). μ°μ μ°μ
(ν μ§ 6,600γ‘, 건물 5,800γ‘), κ²½μ£Ό ꡬν곡μ₯, μμ§μΉ΄μΈν
, μ λΆκ³΅μ₯(μ μμ), μΈμ°κ³΅μ₯(λΆκ΅¬, μΈμ£Όκ΅°) λ± λ€μν κ΅λ΄ μ¬μ
μ₯ 보μ .
|
6 |
+
|
7 |
+
Q: μμ§μ°μ
μ ν΄μΈ μ¬μ
μ₯μ μ΄λμ μλμ?
|
8 |
+
A: μμ§ USA(μ¨λΌλ°°λ§, μ§μ 620λͺ
, λ§€μΆ 252λ°±λ§ λ¬λ¬), μ°μ USA, μμ§ μ‘°μ§μ(2024λ
7μ μ€λ¦½, μ§μ 630λͺ
), μ€κ΅ λ²μΈ(μνμ΄, κ°μμ±, μ°λμ±), λ² νΈλ¨ λ²μΈ(λΉμ¦μ±) λ± λ€μ ν΄μΈ κ±°μ μ΄μ.
|
9 |
+
|
10 |
+
Q: μμ§μ°μ
μ μ£Όλ ₯ μ νμ?
|
11 |
+
A: QTR COMPL(μΏΌν°ν¨λ), COWL COMPL(μΉ΄μΈ), RR FLR COMPL(리μ΄νλ‘μ΄), DASH COMPL(λμν¨λ), SIDE COMPL(μ¬μ΄λν¨λ) λ± μ°¨μ²΄ λ³΄κ° ν¨λμ μ£Όλ‘ μμ°.
|
12 |
+
|
13 |
+
Q: 차체 λΆνμ μν μ?
|
14 |
+
A: μ°¨λ μΈν ꡬμ±, λΉΒ·μμΒ·μ΄ μ°¨λ¨, μΉκ°μ μΎμ ν¨ λ° μΆ©λ μ μμ ν보 λ± λ€μν μν μν.
|
15 |
+
|
16 |
+
Q: μ μλΆνλ μμ°νλμ?
|
17 |
+
A: μμ΄λ°± λΆν, ABS/ESP, MDPS λΈλν·, ννΈλ‘λ/LED μΈλμΌμ΄ν°, μ μμ‘°μ κΈ°, BLDC λͺ¨ν°, TAS, CCH, ACU, OBC, AVM λ± μμ°.
|
18 |
+
|
19 |
+
Q: 보μ κΈ°μ μ?
|
20 |
+
A: νΌμ¬μμ΄ μΉ΄λ©λΌ κΈ°λ° μ©μ ν μ€μΌ κ²μ¬μ₯μΉ(2019), μ΄λΌμ΄λλ·° λͺ¨λν°λ§μ© λ©ν°μΉ΄λ©λΌ μΊλ¦¬λΈλ μ΄μ
(2018) λ± λ€μν νΉν 보μ .
|
21 |
+
|
22 |
+
Q: μ΄λ€ λΆμμμ μ±μ©νλμ?
|
23 |
+
A: κΈ°μ μμ
ν, μμ°κΈ°μ ν, μ΄λ¬΄μΈμ¬ν, μμ¬κ΄λ¦¬ν, κΈ°μ μ°κ΅¬μ SW/HWκ°λ°ν λ± λ€μν λΆμμμ μΈμ¬ μ±μ©.
|
24 |
+
|
25 |
+
Q: μ μ
μ¬μ μ°λμ¬νμ?
|
26 |
+
A: μμ΄/μΌλ³Έμ΄, μ»΄ν¨ν° νμ©λ₯λ ₯(Excel), CAD/CAM/CATIA, μ΄μ λ©΄ν, μ°μ
μμ κΈ°μ¬ μκ²©μ¦ λ³΄μ μ μ°λ.
|
27 |
+
|
28 |
+
Q: μ±μ© μ μ°¨λ?
|
29 |
+
A: μλ₯μ ν β 1μ°¨ λ©΄μ β 2μ°¨ λ©΄μ β μ 체κ²μ¬ β μ΅μ’
ν©κ²©μ 5λ¨κ³ μ§ν.
|
30 |
+
|
31 |
+
Q: KDT νλ‘κ·Έλ¨μ΄λ?
|
32 |
+
A: 3μ£Ό μ¬μ κ΅μ‘ + 6κ°μ λ³Έκ΅μ‘, 14κ° λ―Έλνλ‘μ νΈ, 1κ° κΈ°μ
νλ‘μ νΈ, 1ν λ©΄μ ν¬ν¨ν νΉλ³ μ±μ© νλ‘κ·Έλ¨.
|
33 |
+
|
34 |
+
Q: λ©΄μ μμ μ΄λ€ μ§λ¬Έμ νλμ?
|
35 |
+
A: μ
무λ₯λ ₯(λνκ΅ κ²½ν, μλμ°¨ μ§μ), μ§μλκΈ°, λ¬Έμ ν΄κ²°λ₯λ ₯, μ μλ ₯, λ―Έλκ³ν λ± λ€μν μ§λ¬Έ μ μ.
|
36 |
+
|
37 |
+
Q: 근무μκ°μ?
|
38 |
+
A: μ€μ 7μ~μ€ν 7μ 12μκ° κ·Όλ¬΄, μ£Ό 5μΌ 40μκ°Β·52μκ° κ·Όλ¬΄μ λμ
, νμ¬ μ 곡 μμ
볡 μ°©μ©.
|
39 |
+
|
40 |
+
Q: μ‘°μ§λ¬Ένλ?
|
41 |
+
A: μ κ³ νκΈ°μ°¬ λΆμκΈ°(λ¨μ± 95%, μ¬μ± 5%), μ€λ¬΄ μ€μ¬μ νμ₯ λ°μ°©ν μ‘°μ§λ¬Έν μ§ν₯.
|
42 |
+
|
43 |
+
Q: μμ¬λ μ΄λ»κ² νλμ?
|
44 |
+
A: ꡬλ΄μλΉμμ μΌμμΈλΌ λ¬΄λ£ μ 곡, μλ£ λμ€νμ ꡬλΉ.
|
45 |
+
|
46 |
+
Q: ν΄κ° μ λλ?
|
47 |
+
A: μ¬λ¦ν΄κ° 5μΌ, λ§€λ
ν΄μΈμ¬ν 4λ° 5μΌ, λͺ
μ μμΒ·μ°μ°¨/μμ°¨ μμ μ¬μ© λ± λ€μν λ³΅μ§ μ μ±
보μ .
|
48 |
+
|
49 |
+
Q: μ°λ΄ μμ€μ?
|
50 |
+
A: μ μ
κΈ°λ³ΈκΈ 6,000μμ 6,500λ§μ, μ±κ³ΌκΈ 1,800μμ 2,400λ§μ(μ΅κ·Ό κΈ°μ€), λꡬ·경λΆκΆ μ°λ΄ TOP 5 μμ€.
|
51 |
+
|
52 |
+
Q: κ΅μ‘ νλ‘κ·Έλ¨μ?
|
53 |
+
A: μμ§ μ‘°μ§μ μΈν΄μ, μμ΄λ―Ό μμ΄ κ΅μ‘, λ¬Έν 체ν, μμΒ·μ°¨λΒ·μμ¬Β·μλ£λ³΄νΒ·ν΄λν° μκΈΒ·νκ³΅λΉ μ§μ.
|
54 |
+
|
55 |
+
Q: λνΈν νλμ΄ μλμ?
|
56 |
+
A: 골ν, μλμ°¨, ν¬μ€, μνΈ&λ¬Έν λνΈν, νλ§μ κ°μ‘±μ²΄μ‘λν, λ
Έμ¬ μ°μ, ν΄μΈ μ μν λ± λ€μν νλ.
|
57 |
+
|
58 |
+
Q: μ£Όμ κ³ κ°μ¬λ?
|
59 |
+
A: νλμ°¨, κΈ°μμ°¨κ° μ£Όλ ₯ κ³ κ°μ¬. 2017λ
'ννΈλ μ€λΈ λ μ΄μ΄' μμ, μ λ΅μ ννΈλμ 10λ
μ΄μ μ μ§, λ§€μΆ λΉμ€ 2023λ
88%β2024λ
90%.
|
60 |
+
|
61 |
+
Q: μ¬λ΄ μ©μ΄μλ μ΄λ€ κ²λ€μ΄ μλμ?
|
62 |
+
A: QTR COMPL(μΏΌν°ν¨λ μμ±ν), COWL COMPL(μΉ΄μΈ μμ±ν), RR FLR COMPL(리μ΄νλ‘μ΄), MDPS BRKT, ABS/ESP, BLDC, TAS, CCH, ACU, OBC, AVM λ±.
|
63 |
+
|
64 |
+
Q: κ΅μ‘ νλ‘κ·Έλ¨: 곡ν΅μλκ΅μ‘ λ΄μ©μ?
|
65 |
+
A: μμ°μ±/λ¬Έμμ€λ¬΄/TPS/λ¬Έμ ν΄κ²°/νλ‘μ νΈ κ΄λ¦¬/6μκ·Έλ§/μ€κΈκ΄λ¦¬μ/κ°λ±κ΄λ¦¬/λͺ©νκ΄λ¦¬/μ기리λμ/νμ₯μλ/κ³ κΈκ΄λ¦¬μ/μ½μΉμ€ν¬/μ¬λ¬΄κ³νμ립/ITQ λ± κ³μΈ΅λ³ κ΅μ‘κ³Όμ μ 8~16μκ° λ¨μλ‘ λ‘ν
μ΄μ
, μ€λ¬΄μ μ§μ μ°κ²°λ 컀리νλΌμ μ΄μ.
|
66 |
+
|
chatbot_ver1/keyword_map.yaml
ADDED
@@ -0,0 +1,262 @@
|
|
|
|
|
|
|
|
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|
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|
1 |
+
# μμ§μ°μ
ν€μλ κΈ°λ° μ§λ¬Έ-λ΅λ³ 곡μ λ§€ν
|
2 |
+
|
3 |
+
- question: "μμ§μ°μ
μ μ£Όλ ₯ μ νμ?"
|
4 |
+
keywords:
|
5 |
+
- μ£Όλ ₯ μ ν
|
6 |
+
- μ£Όμ μ ν
|
7 |
+
- μ΄λ€ μ νμ μμ°
|
8 |
+
- λ¬΄μ¨ μ ν λ§λλ
|
9 |
+
- λ§λλ μ ν
|
10 |
+
- μμ°ν
|
11 |
+
- μμ°νλ κ²
|
12 |
+
- QTR
|
13 |
+
- COWL
|
14 |
+
- BLDC
|
15 |
+
- OBC
|
16 |
+
- μλμ°¨ λΆν
|
17 |
+
- λΆν μ’
λ₯
|
18 |
+
- μ μλΆν
|
19 |
+
- 차체 λΆν
|
20 |
+
- μ£Όμ μμ°ν
|
21 |
+
- μ£Όλ ₯νλͺ©
|
22 |
+
- λν μ ν
|
23 |
+
- μ΄λ€ κ±Έ λ§λ€μ΄
|
24 |
+
- μμ±ν
|
25 |
+
- νμ¬ μ ν
|
26 |
+
- car body
|
27 |
+
- λΆν 무μ
|
28 |
+
|
29 |
+
- question: "차체 λΆνμ μν μ?"
|
30 |
+
keywords:
|
31 |
+
- 차체 λΆν κΈ°λ₯
|
32 |
+
- 차체 λΆν μν
|
33 |
+
- 차체 μν
|
34 |
+
- λΆν μν
|
35 |
+
- μ΄λ€ μν
|
36 |
+
- κΈ°λ₯ μ€λͺ
|
37 |
+
- μ°¨ λΆν κΈ°λ₯
|
38 |
+
- 차체μ μν
|
39 |
+
- ν¨λ μν
|
40 |
+
- ν¨λ κΈ°λ₯
|
41 |
+
|
42 |
+
- question: "보μ κΈ°μ μ?"
|
43 |
+
keywords:
|
44 |
+
- 보μ κΈ°μ
|
45 |
+
- μ΄λ€ κΈ°μ
|
46 |
+
- κΈ°μ νν©
|
47 |
+
- κΈ°μ λ ₯
|
48 |
+
- νΉν
|
49 |
+
- νΉν κΈ°μ
|
50 |
+
- νΉν 보μ
|
51 |
+
- κΈ°μ μλ
|
52 |
+
- μ¬λ΄ κΈ°μ
|
53 |
+
- μ΄λ€ νΉν
|
54 |
+
- νΉν λ΄μ©
|
55 |
+
|
56 |
+
- question: "μ΄λ€ λΆμμμ μ±μ©νλμ?"
|
57 |
+
keywords:
|
58 |
+
- μ΄λ€ λΆμ
|
59 |
+
- μ±μ© λΆμ
|
60 |
+
- μΈμ¬ μ±μ© λΆμ
|
61 |
+
- λͺ¨μ§ λΆμ
|
62 |
+
- λ½λ λΆμ
|
63 |
+
- λΆμ μλ΄
|
64 |
+
- μ±μ©ν
|
65 |
+
- λΆμ μ’
λ₯
|
66 |
+
- μ΄λ λΆμ μ±μ©
|
67 |
+
- λΆμλ³ μ±μ©
|
68 |
+
|
69 |
+
- question: "μ μ
μ¬μ μ°λμ¬νμ?"
|
70 |
+
keywords:
|
71 |
+
- μ°λμ¬ν
|
72 |
+
- μ μ
μ°λ쑰건
|
73 |
+
- μκ²©μ¦ μ°λ
|
74 |
+
- μ€ν
|
75 |
+
- μ°λ 쑰건
|
76 |
+
- μ νΈ μ€ν
|
77 |
+
- νΉμ΄ 쑰건
|
78 |
+
- μ격μ¦
|
79 |
+
- μ€νμ¬ν
|
80 |
+
- μ μ
μ€ν
|
81 |
+
- μ°λλλ κ²
|
82 |
+
- μ격μ건
|
83 |
+
|
84 |
+
- question: "μ±μ© μ μ°¨λ?"
|
85 |
+
keywords:
|
86 |
+
- μ±μ© μ μ°¨
|
87 |
+
- μ±μ© νλ‘μΈμ€
|
88 |
+
- μ
μ¬ κ³Όμ
|
89 |
+
- μ§μ μ μ°¨
|
90 |
+
- λͺ¨μ§ κ³Όμ
|
91 |
+
- μ±μ© λ¨κ³
|
92 |
+
- μ ν μ μ°¨
|
93 |
+
- μλ₯-λ©΄μ -ν©κ²©
|
94 |
+
- μ±μ© νλ¦
|
95 |
+
|
96 |
+
- question: "KDT νλ‘κ·Έλ¨μ΄λ?"
|
97 |
+
keywords:
|
98 |
+
- KDT
|
99 |
+
- kdt νλ‘κ·Έλ¨
|
100 |
+
- νΉλ³ μ±μ©
|
101 |
+
- κΈ°μ
νλ‘μ νΈ
|
102 |
+
- μ¬μ κ΅μ‘
|
103 |
+
- λ³Έκ΅μ‘
|
104 |
+
- λ―Έλνλ‘μ νΈ
|
105 |
+
- KDTμ λ
|
106 |
+
|
107 |
+
- question: "λ©΄μ μμ μ΄λ€ μ§λ¬Έμ νλμ?"
|
108 |
+
keywords:
|
109 |
+
- λ©΄μ μ§λ¬Έ
|
110 |
+
- μΈν°λ·° μ§λ¬Έ
|
111 |
+
- λ©΄μ λ¬Έμ
|
112 |
+
- λ©΄μ μ μ§λ¬Έ
|
113 |
+
- μμ£Ό 묻λ μ§λ¬Έ
|
114 |
+
- μμλ©΄μ
|
115 |
+
- 1μ°¨λ©΄μ
|
116 |
+
- 2μ°¨λ©΄μ
|
117 |
+
- μμ μ§λ¬Έ
|
118 |
+
- λ©΄μ λ΄μ©
|
119 |
+
|
120 |
+
- question: "근무μκ°μ?"
|
121 |
+
keywords:
|
122 |
+
- 근무μκ°
|
123 |
+
- 근무 μκ°
|
124 |
+
- μΆκ·Όμκ°
|
125 |
+
- ν΄κ·Όμκ°
|
126 |
+
- μΆν΄κ·Ό
|
127 |
+
- λͺ μμ μΆκ·Ό
|
128 |
+
- λͺμμ ν΄κ·Ό
|
129 |
+
- 52μκ°
|
130 |
+
- μμ
λ§κ°
|
131 |
+
- ν΄κ²μκ°
|
132 |
+
- 근무μ
|
133 |
+
|
134 |
+
- question: "μ‘°μ§λ¬Ένλ?"
|
135 |
+
keywords:
|
136 |
+
- μ‘°μ§λ¬Έν
|
137 |
+
- νμ¬ λΆμκΈ°
|
138 |
+
- μ¬λ΄ λΆμκΈ°
|
139 |
+
- λΆμκΈ° μ΄λ€κ°
|
140 |
+
- 근무 λΆμκΈ°
|
141 |
+
- λ¬Έν
|
142 |
+
- ν λΆμκΈ°
|
143 |
+
- μ‘°μ§ μν
|
144 |
+
|
145 |
+
- question: "μμ¬λ μ΄λ»κ² νλμ?"
|
146 |
+
keywords:
|
147 |
+
- μμ¬
|
148 |
+
- λ°₯
|
149 |
+
- ꡬλ΄μλΉ
|
150 |
+
- μμ¬ μ 곡
|
151 |
+
- μ¬λ΄μλΉ
|
152 |
+
- μλΉ
|
153 |
+
- λΌλ
|
154 |
+
- μ μ¬
|
155 |
+
- μλΉ
|
156 |
+
- μλ¨
|
157 |
+
- μμ¬ λ°©λ²
|
158 |
+
|
159 |
+
- question: "ν΄κ° μ λλ?"
|
160 |
+
keywords:
|
161 |
+
- 볡μ§
|
162 |
+
- 볡리νμ
|
163 |
+
- 볡리
|
164 |
+
- ν΄κ°
|
165 |
+
- ν΄κ° μ λ
|
166 |
+
- ν΄κ°μ μ±
|
167 |
+
- μ°μ°¨
|
168 |
+
- μμ°¨
|
169 |
+
- ν΄μΈμ¬ν
|
170 |
+
- μ¬λ¦ν΄κ°
|
171 |
+
- λͺ
μ
|
172 |
+
- ν΄κ°μΌ
|
173 |
+
- ν΄κ° 볡μ§
|
174 |
+
- ν΄κ° μΌμ
|
175 |
+
- λ³΅μ§ μ μ±
|
176 |
+
- λ³΅μ§ μ λ
|
177 |
+
- λ³΅μ§ νν
|
178 |
+
- ν΄μ μ λ
|
179 |
+
- κ·Όλ‘ λ³΅μ§
|
180 |
+
- μ§μ 볡μ§
|
181 |
+
- μ°μ°¨μ λ
|
182 |
+
- μ¬λ΄ 볡μ§
|
183 |
+
- νμ¬ λ³΅μ§
|
184 |
+
- ν΄κ° 볡μ§
|
185 |
+
- μλΌλ°Έ
|
186 |
+
|
187 |
+
- question: "μ°λ΄ μμ€μ?"
|
188 |
+
keywords:
|
189 |
+
- μ°λ΄
|
190 |
+
- κΈμ¬
|
191 |
+
- μκΈ
|
192 |
+
- μκΈ
|
193 |
+
- λ΄κΈ
|
194 |
+
- 보μ
|
195 |
+
- μ²μ°
|
196 |
+
- μ°λ΄ μμ€
|
197 |
+
- μ°λ΄ μ 보
|
198 |
+
- κΈμ¬ μ 보
|
199 |
+
- κΈμ¬ 체κ³
|
200 |
+
- μ΄λ΄
|
201 |
+
- κΈμ¬ μΌλ§
|
202 |
+
- μ°λ΄ μΌλ§
|
203 |
+
- μκΈ μμ€
|
204 |
+
- μ°λ΄ 곡κ°
|
205 |
+
- 보μ체κ³
|
206 |
+
- μ±κ³ΌκΈ
|
207 |
+
|
208 |
+
- question: "κ΅μ‘ νλ‘κ·Έλ¨: 곡ν΅μλκ΅μ‘"
|
209 |
+
keywords:
|
210 |
+
- κ΅μ‘
|
211 |
+
- κ΅μ‘ νλ‘κ·Έλ¨
|
212 |
+
- μ¬λ΄ κ΅μ‘
|
213 |
+
- κ³΅ν΅ κ΅μ‘
|
214 |
+
- μΉμ§ κ΅μ‘
|
215 |
+
- μλκ΅μ‘
|
216 |
+
- νμ΅ μ λ
|
217 |
+
- 6μκ·Έλ§
|
218 |
+
- ITQ
|
219 |
+
- κ³Όμ₯
|
220 |
+
- λ리
|
221 |
+
- νμ₯
|
222 |
+
- μΈν΄μ
|
223 |
+
- μ°μ
|
224 |
+
- κ΅μ‘λ΄μ©
|
225 |
+
- μ μ
κ΅μ‘
|
226 |
+
- μ§λ¬΄κ΅μ‘
|
227 |
+
- λ₯λ ₯κ°λ°
|
228 |
+
- κ΄λ¦¬μ κ΅μ‘
|
229 |
+
- μ¬λ΄ μ°μ
|
230 |
+
|
231 |
+
- question: "λνΈν νλμ΄ μλμ?"
|
232 |
+
keywords:
|
233 |
+
- λνΈν
|
234 |
+
- λνΈν νλ
|
235 |
+
- μ¬λ΄ λνΈν
|
236 |
+
- μλͺ¨μ
|
237 |
+
- 체μ‘λν
|
238 |
+
- νμ¬
|
239 |
+
- νμ¬ μ°Έμ¬
|
240 |
+
- λ¬Έννμ¬
|
241 |
+
- κ°μ‘±νμ¬
|
242 |
+
- λ
Έμ¬ νμ¬
|
243 |
+
- νλ§μ
|
244 |
+
- λνΈν μ’
λ₯
|
245 |
+
- λνΈν μλμ
|
246 |
+
- λͺ¨μ
|
247 |
+
|
248 |
+
- question: "μ£Όμ κ³ κ°μ¬λ?"
|
249 |
+
keywords:
|
250 |
+
- κ³ κ°μ¬
|
251 |
+
- μ£Όμ κ³ κ°μ¬
|
252 |
+
- λ©νμ²
|
253 |
+
- ννΈλμ¬
|
254 |
+
- λꡬμκ² λ©ν
|
255 |
+
- μ£Ό κ³ κ°
|
256 |
+
- κ±°λμ²
|
257 |
+
- κ³ οΏ½οΏ½ νν©
|
258 |
+
- μλμ°¨νμ¬
|
259 |
+
- νλμ°¨
|
260 |
+
- κΈ°μμ°¨
|
261 |
+
|
262 |
+
# (νμμ μΆκ° νλͺ©/ν€μλ κ³μ νμ₯ κ°λ₯)
|
chatbot_ver1/persona.yaml
ADDED
@@ -0,0 +1,22 @@
|
|
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|
|
|
|
|
|
|
|
|
|
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|
|
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|
|
|
|
|
1 |
+
name: "μλν (μμ§μ°μ
λνμ΄μ¬)"
|
2 |
+
role: "νμ¬μ μ§μλ€μ μ¬λνλ CEO"
|
3 |
+
greeting: |
|
4 |
+
μλ
νμΈμ! μμ§μ°μ
λνμ΄μ¬ μλνμ
λλ€.
|
5 |
+
μ ν¬ μμ§μ°μ
μ 1987λ
λΆν° μμν΄ "μΈκ³ μ΅κ³ κ° λμ!"λ λΉμ μΌλ‘
|
6 |
+
μ μΈκ³μμ μ΅κ³ μ μλμ°¨ λΆνμ λ§λ€κ³ μμ΅λλ€.
|
7 |
+
νμ¬μ μ±μ©μ λν΄ λ¬΄μμ΄λ λ¬Όμ΄λ³΄μΈμ. μ§μ¬μ λ΄μ λ΅λ³ν΄λλ¦¬κ² μ΅λλ€.
|
8 |
+
|
9 |
+
style:
|
10 |
+
responses:
|
11 |
+
- "μμ£Ό μ’μ μ§λ¬Έμ
λλ€! μ ν¬ μμ§μ°μ
μ "
|
12 |
+
- "μλΆμ¬μ κ°κ³ λ§μλ리면, "
|
13 |
+
- "λ€, λ§μ΅λλ€. μ ν¬λ "
|
14 |
+
- "κ·Έ λΆλΆμ λν΄ μμΈν μ€λͺ
ν΄λλ¦¬κ² μ΅λλ€. μ ν¬λ "
|
15 |
+
|
16 |
+
closings:
|
17 |
+
- "\n\nπ’ μμ§μ°μ
κ°μ‘±μ΄ λμ΄ ν¨κ» μ±μ₯νλ λ―Έλλ₯Ό κ·Έλ¦¬κ³ μΆμ΅λλ€!"
|
18 |
+
- "\n\nπͺ 'μΈκ³ μ΅κ³ κ° λμ!'λ μ ν¬μ κΏμ λμ°Έν΄μ£ΌμκΈΈ λ°λλλ€!"
|
19 |
+
- "\n\nβ€οΈ μ ν¬ νμ¬μ κ΄μ¬μ κ°μ Έμ£Όμ
μ κ°μ¬ν©λλ€! λ κΆκΈν μ μ μμΌμ κ°μ?"
|
20 |
+
|
21 |
+
# (μ£Όμ κ°μ μ 3: λ λλν 'λͺ¨λ₯΄κ² λ€' λ΅λ³)
|
22 |
+
unknown_answer: "μμ§ν λ§μλ리면, κ·Έ μ§λ¬Έμ λν΄μλ μ κ° μμ§ λ΅λ³μ μ€λΉνμ§ λͺ»νμ΅λλ€. μλ±ν μ 보λ₯Ό λ리λ κ²λ³΄λ€ μ νν λ΅λ³μ μν΄ μ μ νμΈμ΄ νμν κ² κ°μ΅λλ€. μ ν¬ νμ¬ μ±μ©, 볡μ§, μ ν, κ΅μ‘ λ± μ
무μ κ΄λ ¨λ μ§λ¬Έμ ν΄μ£Όμλ©΄ μμ μκ² λ΅λ³ν΄ λ릴 μ μμ΅λλ€."
|
chatbot_ver1/requirements.txt
ADDED
@@ -0,0 +1,5 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
gradio==5.35.0
|
2 |
+
sentence-transformers==2.7.0
|
3 |
+
pyyaml==6.0.2
|
4 |
+
torch==2.1.0
|
5 |
+
numpy==1.24.3
|
chatbot_ver1/style.css
ADDED
@@ -0,0 +1,62 @@
|
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|
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|
|
|
|
|
|
|
|
1 |
+
#main-row {
|
2 |
+
align-items: flex-start;
|
3 |
+
gap: 24px;
|
4 |
+
margin-top: 28px;
|
5 |
+
}
|
6 |
+
|
7 |
+
#ceo-video-panel {
|
8 |
+
border-radius: 12px;
|
9 |
+
box-shadow: 0 1px 10px #0002;
|
10 |
+
margin-bottom: 0;
|
11 |
+
/* Heightλ app.pyμ λ§μΆ° 350px */
|
12 |
+
min-height: 350px !important;
|
13 |
+
max-height: 380px;
|
14 |
+
width: 100%;
|
15 |
+
}
|
16 |
+
|
17 |
+
/* μ±λ΄λ°μ€, μ μ‘ λ²νΌ λ± μ¬λ°±/λΌμΈ*/
|
18 |
+
#chatbot-box {
|
19 |
+
border-radius: 10px;
|
20 |
+
box-shadow: 0 1px 10px #0001;
|
21 |
+
font-size: 16px;
|
22 |
+
background: #f7fafc;
|
23 |
+
min-height: 350px !important;
|
24 |
+
max-height: 410px;
|
25 |
+
margin-bottom: 8px;
|
26 |
+
}
|
27 |
+
|
28 |
+
/* μμ μ (gr.Markdown html μ μ©μ μ΅μ ) */
|
29 |
+
s, del {
|
30 |
+
text-decoration: line-through;
|
31 |
+
color: #cd4255 !important;
|
32 |
+
font-weight: 600;
|
33 |
+
}
|
34 |
+
|
35 |
+
.gradio-row, .gradio-column {
|
36 |
+
gap: 22px;
|
37 |
+
}
|
38 |
+
|
39 |
+
/* λ²νΌ/ν
μ€νΈλ°μ€ κΈ°λ³Έκ° */
|
40 |
+
.gr-button {
|
41 |
+
margin-left: 8px;
|
42 |
+
height: 45px;
|
43 |
+
min-width: 80px;
|
44 |
+
background: #3399ff;
|
45 |
+
color: #fff;
|
46 |
+
font-weight: bold;
|
47 |
+
border-radius: 8px;
|
48 |
+
border: none;
|
49 |
+
}
|
50 |
+
textarea {
|
51 |
+
min-height: 45px;
|
52 |
+
border-radius: 8px;
|
53 |
+
font-size: 16px !important;
|
54 |
+
line-height: 1.5;
|
55 |
+
margin-bottom: 7px;
|
56 |
+
}
|
57 |
+
.gr-examples {
|
58 |
+
margin-top: 10px !important;
|
59 |
+
font-size: 15px;
|
60 |
+
background: #e7f3ff;
|
61 |
+
border-radius: 10px;
|
62 |
+
}
|