Upload 3 files
Browse files- app.py +127 -0
- requirements.txt +8 -0
- testchatdata.csv +69 -0
app.py
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import streamlit as st
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from streamlit_chat import message
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import tempfile
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from langchain.document_loaders.csv_loader import CSVLoader
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from langchain.embeddings import HuggingFaceEmbeddings
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from langchain.vectorstores import FAISS
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from langchain.llms import CTransformers
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from langchain.chains import ConversationalRetrievalChain
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from ctransformers import AutoModelForCausalLM
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from langchain_g4f import G4FLLM
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from g4f import Provider, models
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# import spacy
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import requests
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# Define the path for generated embeddings
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DB_FAISS_PATH = 'vectorstore/db_faiss'
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# Load the model of choice
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def load_llm():
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# url = "https://huggingface.co/TheBloke/Llama-2-7B-Chat-GGML/blob/main/llama-2-7b-chat.ggmlv3.q4_K_M.bin" # 2.87G
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# model_loc, file_size = dl_hf_model(url)
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# llm = CTransformers(
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# model=model_loc,
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# temperature=0.2,
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# model_type="llama",
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# top_k=10,
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# top_p=0.9,
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# repetition_penalty=1.0,
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# max_new_tokens=512, # adjust as needed
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# seed=42,
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# reset=True, # reset history (cache)
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# stream=False,
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# # threads=cpu_count,
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# # stop=prompt_prefix[1:2],
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# )
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llm = G4FLLM(
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model=models.gpt_4,
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provider=Provider.ChatBase,
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)
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return llm
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hide_streamlit_style = """
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<style>
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#MainMenu {visibility: hidden;}
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footer {visibility: hidden;}
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</style>
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"""
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st.markdown(hide_streamlit_style, unsafe_allow_html=True)
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# Set the title for the Streamlit app
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st.title("ZendoçŸå¥³ãã£ããããã¯ã¹")
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csv_url = "https://huggingface.co/spaces/uyen13/chatgirl/raw/main/testchatdata.csv"
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# csv_url="https://docs.google.com/uc?export=download&id=1fQ2v2n9zQcoi6JoOU3lCBDHRt3a1PmaE"
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# Define the path where you want to save the downloaded file
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tmp_file_path = "testchatdata.csv"
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# Download the CSV file
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response = requests.get(csv_url)
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if response.status_code == 200:
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with open(tmp_file_path, 'wb') as file:
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file.write(response.content)
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else:
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raise Exception(f"Failed to download the CSV file from {csv_url}")
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# Load CSV data using CSVLoader
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loader = CSVLoader(file_path=tmp_file_path, encoding="utf-8", csv_args={'delimiter': ','})
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data = loader.load()
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# Create embeddings using Sentence Transformers
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embeddings = HuggingFaceEmbeddings(model_name='sentence-transformers/all-MiniLM-L6-v2', model_kwargs={'device': 'cpu'})
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# Create a FAISS vector store and save embeddings
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db = FAISS.from_documents(data, embeddings)
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db.save_local(DB_FAISS_PATH)
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# Load the language model
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llm = load_llm()
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# Create a conversational chain
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chain = ConversationalRetrievalChain.from_llm(llm=llm, retriever=db.as_retriever())
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# Initialize spaCy with the Japanese model
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# nlp = spacy.load("ja_core_news_sm")
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# Function for conversational chat
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def conversational_chat(query):
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result = chain({"question": query, "chat_history": st.session_state['history']})
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st.session_state['history'].append((query, result["answer"]))
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return result["answer"]
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# Initialize chat history
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if 'history' not in st.session_state:
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st.session_state['history'] = []
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# Initialize messages
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if 'generated' not in st.session_state:
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st.session_state['generated'] = ["ããã«ã¡ã¯ïŒzendoçŸå¥³ã§ããäœããæ¢ãã§ããïŒ... ð€"]
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if 'past' not in st.session_state:
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st.session_state['past'] = ["ãã£ããã¯ãããã"]
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# Create containers for chat history and user input
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response_container = st.container()
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container = st.container()
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# User input form
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with container:
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with st.form(key='my_form', clear_on_submit=True):
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user_input = st.text_input("ChatBox", placeholder="質åããèšå
¥ãã ãã... ", key='input')
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submit_button = st.form_submit_button(label='Send')
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if submit_button and user_input:
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output = conversational_chat(user_input)
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st.session_state['past'].append(user_input)
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st.session_state['generated'].append(output)
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# Display chat history
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if st.session_state['generated']:
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with response_container:
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for i in range(len(st.session_state['generated'])):
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message(st.session_state["past"][i], is_user=True, key=str(i) + '_user', avatar_style="big-smile")
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message(st.session_state["generated"][i], key=str(i), avatar_style="thumbs")
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requirements.txt
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langchain==0.0.297
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python-dotenv==1.0.0
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faiss-cpu
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torch
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sentence_transformers
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ctransformers
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streamlit_chat
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git+https://github.com/MIDORIBIN/langchain-gpt4free.git
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testchatdata.csv
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item,content,paylink,rating,recommend
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|
16 |
+
"èªç©ºäŒç€Ÿã®çŸå¥³ãã¡(Fourth Wingç·š)","æ¬æžãèªç©ºäŒç€Ÿã®çŸå¥³ãã¡(Fourth Wingç·š)ãã¯ãã·ãã¯ãªãã¬ã¶ãŒãšã¹ã«ãŒããçãã¢ãŒãã³ãªçŸå¥³ãã¡ãåããåçéã§ããçãè¢ãããã°ãã¹ã«ãŒããããŒããåããã第åã®ç¿Œã§ããããµãŒãã¹ãã€ã³ãããè¡šçŸããŠããŸããèªç©ºäŒç€Ÿã®ãšã¬ã¬ã³ããªã€ã¡ãŒãžã«å ããããäžå±€å¿«é©ãªãã©ã€ããæäŸãããããã§ãã·ã§ãã«ãªå¥³æ§ãã¡ã®å§¿ãã楜ãã¿ãã ããã","https://buy.stripe.com/fZedSu2waaUI4QE3cm",,"賌å
¥ãã¹ã"
|
17 |
+
"çŽæã®å®ã人 (AIçŸå¥³åçé)","ãçŽæã®å®ã人ãã¯ããžã£ã³ããŒã¹ã«ãŒããšã¹ããŒã«ãŒãåãããã¹ããŒãã£ã§ã«ãžã¥ã¢ã«ãªçŸå¥³ãã¡ã®åçéã§ããããã¯ã¬ã¹ããã¢ã¹ããªã¥ãã¯ãµãã¯ããã¬ãŒåžœãªã©ã®å°ç©ã§ãåæ§çã§ãããããªé°å²æ°ãæŒåºããŸããçŽæãå®ãããã«æ¥ã
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åãæŸã£ãŠããŸãã","https://buy.stripe.com/7sIbKmdaOe6UeredR1",,"賌å
¥ãã¹ã"
|
18 |
+
"Fourth Wingã®ã¬ãžã£ãŒã¯ã«ãŒãº(AIçŸå¥³åçé)","æ¬æžãFourth Wingã®ã¬ãžã£ãŒã¯ã«ãŒãºãã§ã¯ãæµ·ã®äžã§æ¥œããçŸå¥³ãã¡ãåããåçéã§ããããããã¯ã³ããŒã¹ããµã³ã°ã©ã¹ããµã³ãã«ãªã©ãå€ãããåºã§ç«ã¡ã§å·¡ãã¯ã«ãŒãºã®é¢šæ¯ãèããŸããFourth Wingã®çŸå¥³ãã¡ããèŒãæµ·ãšãšãã«å€¢ã®ãããªã²ãšãšããæŒåºããŸãã","https://buy.stripe.com/fZe3dQb2G1k8bf24gs",,"賌å
¥ãã¹ã"
|
19 |
+
"çå®ã®çŸãã (AIçŸå¥³åçé)","ãçå®ã®çŸãããã¯ãã¯ã³ããŒã¹ã«ãã³ãã¹ãåããããšã¬ã¬ã³ãã§ãã§ããã³ãªçŸå¥³ãã¡ã®åçéã§ãããžã¥ãšãªãŒãã«ãã¥ãŒã·ã£ããã¬ã¹ã¬ãããªã©ã®å°ç©ããäžåã§è¯ãããªå°è±¡ãäžããŸããçå®ãè¿œæ±ãã女æ§ãã¡ã¯ããã®çŸãããå
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¥ãã¹ã"
|
20 |
+
"ãã£ã€ãçŸå¥³ã®çŽæ
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ãã äžåœçŸå¥³ãã¡ã®çŽçãªé
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|
21 |
+
"ãã£ã€ãçŸå¥³ã®è¯éºãªãè(AIçŸå¥³åçé)","æ¬æžããã£ã€ãçŸå¥³ã®è¯éºãªãèãã¯ããã£ã€ããã¬ã¹ããŸãšã£ãçŸãã女æ§ãã¡ã®åçéã§ãã髪食ããæåãæã¡ãèããããªå§¿ãæ«é²ãã圌女ãã¡ã¯ãçŸãããšè¯éºããå
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¥ãã¹ã"
|
22 |
+
"æ Œéæã€ãã³ãã®çŸå¥³ãã¡","æ¬æžãæ Œéæã€ãã³ãã®çŸå¥³ãã¡ãã¯ãMMAã€ãã³ãã§ã¢ãã«ããã¹ãã¹ãã¢ã·ã¹ã¿ã³ããšããŠåããã¢ã¹ã¬ããã¯ã§ã¹ã¿ã€ãªãã·ã¥ãªå¥³æ§ãã¡ã®åçéã§ãããã¡ãã®å¥³æ§ãã¡ã¯ããã°ãã°ãµãã·ã¥ãæã¡ãç°ãªã髪åãããŠããããã£ããããžã£ã³ãã¹ãŒããççšããŠããŸãã","https://buy.stripe.com/7sIaGi8Uye6U0AofZe",,"賌å
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|
23 |
+
"ãã¯ãããžãŒã®å
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ãã¡(Fourth Wingç·š)","æ¬æžããã¯ãããžãŒã®å
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|
24 |
+
"çŸé£ã®å¥³ç¥ãã¡(Fourth Wingç·š)","æ¬æžãçŸé£ã®å¥³ç¥ãã¡(Fourth Wingç·š)ãã¯ãé£åããèåãé£æåãåãæ±ã£ãåçéã§ããèžè¡çãªçŸãããšå
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|
25 |
+
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|
26 |
+
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|
27 |
+
"æ Œéæã€ãã³ãã®çŸå¥³ãã¡2","æ¬æžãæ Œéæã€ãã³ãã®çŸå¥³ãã¡ãã¯ãMMAã€ãã³ãã§ã¢ãã«ããã¹ãã¹ãã¢ã·ã¹ã¿ã³ããšããŠåããã¢ã¹ã¬ããã¯ã§ã¹ã¿ã€ãªãã·ã¥ãªå¥³æ§ãã¡ã®åçéã§ãããã¡ãã®å¥³æ§ãã¡ã¯ããã°ãã°ãµãã·ã¥ãæã¡ãç°ãªã髪åãããŠããããã£ããããžã£ã³ãã¹ãŒããççšããŠããŸãã","https://buy.stripe.com/3cs01E8Uy0g4bf25kF",,"賌å
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|
28 |
+
"ãã£ã€ãçŸå¥³2","æ¬æžããã£ã€ãçŸå¥³2ãã¯ãè¯ãããªãã£ã€ããã¬ã¹ããã¥ããã¯ã身ã«ãŸãšã£ãçŸããäžåœã®å¥³æ§ãã¡ãåããåçéã§ãã竹垜åãæåãååãæã¡ããã³ããé¯ã®ãŒããšäžç·ã«æ®åœ±ããã圌女ãã¡ã®å§¿ã¯ãæ
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|
29 |
+
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|
30 |
+
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|
31 |
+
"ãããŒã©ã€(IU version)","æ¬æžãNever Lieãã¯ããšã¬ã¬ã³ããªã¯ã³ããŒã¹ãçãAIã¢ãã«ã®åçéã§ããé
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|
32 |
+
"ãããŒã©ã€(Classy version)","æ¬æžãNever Lie( Classy Version )ãã¯ããšã¬ã¬ã³ããªã¯ã³ããŒã¹ã«ãäžåãªããŒã«ããã¯ã¬ã¹ããã³ãã¹ããµã³ã°ã©ã¹ãã·ã§ã«ããŒããã°ãã·ã«ã¯ã¹ã«ãŒãããã¬ã¹ã¬ãããªã©ãåãããããAIã¢ãã«ã®åçéã§ããäžåããšè±ªè¯ããæŒåºããæŽç·Žãããã¹ã¿ã€ã«ã§ãåªé
ã«é
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|
33 |
+
"ãã£ã€ãçŸå¥³ã®äžç2","æ¬æžããã£ã€ãçŸå¥³ã®äžç2ãã¯ãè¯éºãªãã£ã€ããã¬ã¹ã身ã«ãŸãšã£ãçŸå¥³ãã¡ã®åçéã§ããè±æããã¢ã¢ã¯ã»ãµãªãŒãæåãã¹ãªããããªãã³ãªã©ãçµã¿åãããçããªãã¯ã女æ§ããããšåªé
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|
34 |
+
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|
35 |
+
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|
36 |
+
"ã¬ãŒã¹ã¯ã€ãŒã³ã®çŸå¥³ãã¡2","æ¬æžãã¬ãŒã¹ã¯ã€ãŒã³ã®çŸå¥³ãã¡ãã¯ãã¬ãŒã·ã³ã°ã³ã¹ãã¥ãŒã ã身ã«ãŸãšã£ãã¢ãŒãã³ãªçŸå¥³ãã¡ãåããåçéã§ãããã«ã¡ãããããŒã«ããŠãšã¹ãã·ã§ã€ããŒãã¹ãããã³ã°ã®çµã¿åããã¯ãã¢ãŒã¿ãŒã¹ããŒãã象城ãã匷åã§é
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|
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+
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ãã«æºã¡ãäžåã§ãã","https://buy.stripe.com/4gwg0Cc6K2ocbf2dRl",,"賌å
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|
38 |
+
"ã¬ãŒã¹ã¯ã€ãŒã³ JOJO2","æ¬æžãã¬ãŒã¹ã¯ã€ãŒã³ JOJOãã¯ããã§ãã¯æã®ã¹ã«ãŒãããã£ã¹ã±ãããæè¢ãã¡ã¬ããã¿ã³ã¯ããããä¿è·ãã¥ãŒãã身ã«çããJOJOããã®åçéã§ããå¿
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|
39 |
+
"ãããŒã©ã€(Glamour version)","æ¬æžãNever Lie( Glamour Version )ãã¯ãé
æçãã€å®èœçãªãã¬ã¹ã«ãè¯éºãªãžã¥ãšãªãŒãããŒã«ãæè¢ããµã³ã°ã©ã¹ãããã«ããããã¬ã¹ãªã©ã®ã°ã©ãã©ã¹ãªã¢ã¯ã»ãµãªãŒã身ã«ã€ããé
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|
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+
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|
41 |
+
"æŠäŸ ã®çŸå¥³ãã¡","æ¬æžãæŠäŸ ã®çŸå¥³ãã¡ãã¯ã挢æããŸãšã£ãçŸãã女æ§ãã¡ãåããåçéã§ããå£ãæãè®ã®è±ã竹ãæŠè¡ãå§äŸ¶ãªã©ãæŠäŸ å°èª¬ã«ç»å ŽããããªèŠçŽ ãæãããŠããŸããçŸå¥³ãã¡ã¯åæ¢ããšæ°åãåããè¿«åã®ããããŒãºãçŸããåããæ«é²ããŸããæŠäŸ ã®äžçã«èããçŸãããšå匷ããæããäžåã§ãã","https://buy.stripe.com/bIY6q21s68MA4QE7t1",,"賌å
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|
42 |
+
"æ±æŽã®éºããçŸã®èª¿ã¹(AIçŸå¥³åçé)","æ¬æžãæ±æŽã®éºããçŸã®èª¿ã¹ãã¯ããã£ã€ããã¬ã¹ããŸãšã£ãçŸãã女æ§ãã¡ã®åçéã§ãã髪食ããæåãæã¡ãæ±æŽã®éºãããè¡šçŸãã圌女ãã¡ã®å§¿ã¯ãåªé
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|
43 |
+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
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|
49 |
+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
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|
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+
"èª å®ãªç³ (AIçŸå¥³åçé)","ãèª å®ãªç³ãã¯ãå¿åªããçŽ çŽãªçŸå¥³ãã¡ã®åçéã§ããã«ãŒãã£ã¬ã³ãšããã ãã³ãã«ããŒãã¡ãŒãšããã«ãžã¥ã¢ã«ãªã¹ã¿ã€ã«ã«ã¯ãçŒé¡ããã³ãããã°ãã¡ã¬ãã±ãŒã¹ãªã©ã®å°ç©ããããããŠããŸãããããããªç³ããèª å®ããšçŽç²ããäŒããŸãã","https://buy.stripe.com/5kA8ya9YC8MA0Ao9Br",,"賌å
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|
60 |
+
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|
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+
"Fourth Wingã®ãªãã£ã¹ãã¡ãã·ã§ã³(AIçŸå¥³åçé)","æ¬æžãFourth Wingã®ãªãã£ã¹ãã¡ãã·ã§ã³ãã¯ããªãã£ã¹ã§çããªãçŸå¥³ãã¡ãåããåçéã§ããçœè¡£å¢æãã®äžãæŽèœãã¢ã¯ã»ãµãªãŒãããŒãããã°ãã¯ã©ã¹æãããžã£ã±ããã§ãã¡ãã·ã§ã³æ§ãè¿œæ±ããã«ãã¯ã¹ãšç¥æ§ãå
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|
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+
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|
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+
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|
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+
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|
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+
"Fourth Wingã®ãŠã£ã³ã¿ãŒãã¡ãã·ã§ã³(AIçŸå¥³åçé)","æ¬æžãFourth Wingã®ãŠã£ã³ã¿ãŒãã¡ãã·ã§ã³ãã¯ãå¯ãå£ç¯ã«çããªãçŸå¥³ãã¡ãåããåçéã§ããã³ãŒããããã©ãŒãåžœåãã¹ãããã³ã°ãªã©ã现ãããã£ããŒã«ã«ãŸã§ãã ãã£ããã¡ãã·ã§ã³ã¹ã¿ã€ã«ã¯ã圌女ãã¡ã®ã»ã³ã¹ã®è¯ããç©èªã£ãŠããŸããFourth Wingã®å¥³æ§ãã¡ãå¬ã®å£ç¯ã«èº«ã«çãããæŽèœãªã¢ã€ãã ãäžæå
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|
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+
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|
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+
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|
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+
"èª å®ãªååš (AIçŸå¥³åçé)","ãèª å®ãªååšãã¯ãã¿ãŒãã«ããã¯ã»ãŒã¿ãŒãšãã³ã°ã¹ã«ãŒããçãçŽ æŽã§äžåãªçŸå¥³ãã¡ã®åçéã§ããããŒãã£ãã€ã€ãªã³ã°ãã·ã§ã«ããŒããã°ãã¹ããŒã«ãªã©ã®å°ç©ããæãããªé°å²æ°ãæŒåºããŸããèª å®ã§åªããååšæããµãã女æ§ãã¡ããèªç¶ãªçŸãããæŸã£ãŠããŸãã","https://buy.stripe.com/aEU3dQfiWe6U3MA7ts",,"賌å
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|
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+
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