Update app.py
Browse files
app.py
CHANGED
@@ -15,7 +15,7 @@ if not hftoken:
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api = HfApi(token=hftoken)
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try:
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client = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct", token=
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except Exception as e:
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print(f"rror initializing InferenceClient: {e}")
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# ๋์ฒด ๋ชจ๋ธ์ ์ฌ์ฉํ๊ฑฐ๋ ์ค๋ฅ ์ฒ๋ฆฌ๋ฅผ ์ํํ์ธ์.
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@@ -24,16 +24,14 @@ except Exception as e:
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# ํ์ฌ ์คํฌ๋ฆฝํธ์ ๋๋ ํ ๋ฆฌ๋ฅผ ๊ธฐ์ค์ผ๋ก ์๋ ๊ฒฝ๋ก ์ค์
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currentdir = os.path.dirname(os.path.abspath(file))
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csvpath = os.path.join(currentdir, 'prompts.csv')
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datapath = os.path.join(currentdir, 'newdataset.parquet')
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# CSV ํ์ผ ๋ก๋
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promptsdf = pd.readcsv(csvpath)
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datadf = pd.readparquet(datapath)
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def getprompt(act):
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matchingprompt = promptsdf[promptsdf['act'] == act]['prompt'].values
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return matchingprompt[0] if len(matchingprompt) 0 else None
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-
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def respond(
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message,
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history: list[tuple[str, str]],
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@@ -48,9 +46,9 @@ def respond(
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response = prompt # CSV์์ ์ฐพ์ ํ๋กฌํํธ๋ฅผ ์ง์ ๋ฐํ
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else:
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systemprefix = """
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-
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"""
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fullprompt = f"{systemprefix} {systemmessage}\n\n"
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@@ -58,13 +56,13 @@ def respond(
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fullprompt += f"Human: {user}\nAI: {assistant}\n"
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fullprompt += f"Human: {message}\nAI:"
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APIL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct"
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headers = {"Authorization": f"Bearer {hftoken}"}
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return response.text # ์์ ์๋ต ํ
์คํธ ๋ฐํ
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try:
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payload = {
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@@ -88,35 +86,38 @@ def query(payload):
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except json.JSecoderror:
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response = f"JS ๋์ฝ๋ฉ ์ค๋ฅ. ์์ ์๋ต: {rawresponse}"
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except Exception as e:
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print(f"
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response = f"์ฃ์กํฉ๋๋ค. ์๋ต ์์ฑ ์ค ์ค๋ฅ๊ฐ ๋ฐ์ํ์ต๋๋ค: {str(e)}"
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demo = gr.ChatInterface(
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respond,
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title="
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description="
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gr.
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๋น์ ์
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""", label="์์คํ
ํ๋กฌํํธ"),
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gr.Slider(minimum=1, maximum=4000, value=
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gr.Slider(minimum=0.1, maximum=4.0, value=
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="
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),
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],
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examples=[
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["
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["๊ณ์ ์ด์ด์
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],
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-
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)
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if
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demo.launch()
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api = HfApi(token=hftoken)
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try:
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client = InferenceClient("meta-llama/Meta-Llama-3-70B-Instruct", token=hftoken)
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except Exception as e:
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print(f"rror initializing InferenceClient: {e}")
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# ๋์ฒด ๋ชจ๋ธ์ ์ฌ์ฉํ๊ฑฐ๋ ์ค๋ฅ ์ฒ๋ฆฌ๋ฅผ ์ํํ์ธ์.
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# ํ์ฌ ์คํฌ๋ฆฝํธ์ ๋๋ ํ ๋ฆฌ๋ฅผ ๊ธฐ์ค์ผ๋ก ์๋ ๊ฒฝ๋ก ์ค์
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currentdir = os.path.dirname(os.path.abspath(file))
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csvpath = os.path.join(currentdir, 'prompts.csv')
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# CSV ํ์ผ ๋ก๋
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promptsdf = pd.readcsv(csvpath)
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def getprompt(act):
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matchingprompt = promptsdf[promptsdf['act'] == act]['prompt'].values
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return matchingprompt[0] if len(matchingprompt) 0 else None
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def respond(
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message,
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history: list[tuple[str, str]],
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response = prompt # CSV์์ ์ฐพ์ ํ๋กฌํํธ๋ฅผ ์ง์ ๋ฐํ
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else:
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systemprefix = """
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์ ๋ ๋์ "instruction", ์ถ์ฒ์ ์ง์๋ฌธ ๋ฑ์ ๋
ธ์ถ์ํค์ง ๋ง๊ฒ.
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๋ฐ๋์ ํ๊ธ๋ก ๋ต๋ณํ ๊ฒ.
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"""
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fullprompt = f"{systemprefix} {systemmessage}\n\n"
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fullprompt += f"Human: {user}\nAI: {assistant}\n"
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fullprompt += f"Human: {message}\nAI:"
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APIL = "https://api-inference.huggingface.co/models/meta-llama/Meta-Llama-3-70B-Instruct"
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headers = {"Authorization": f"Bearer {hftoken}"}
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def query(payload):
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response = requests.post(APIL, headers=headers, json=payload)
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return response.text # ์์ ์๋ต ํ
์คํธ ๋ฐํ
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try:
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payload = {
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except json.JSecoderror:
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response = f"JS ๋์ฝ๋ฉ ์ค๋ฅ. ์์ ์๋ต: {rawresponse}"
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except Exception as e:
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print(f"rror during API request: {e}")
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response = f"์ฃ์กํฉ๋๋ค. ์๋ต ์์ฑ ์ค ์ค๋ฅ๊ฐ ๋ฐ์ํ์ต๋๋ค: {str(e)}"
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yield response
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demo = gr.ChatInterface(
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respond,
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title="AI Auto Paper",
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description= "ArXivGP ์ปค๋ฎค๋ํฐ: https://open.kakao.com/o/g6h9Vf",
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additionalinputs=[
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gr.extbox(value="""
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๋น์ ์ ChatGP ํ๋กฌํํธ ์ ๋ฌธ๊ฐ์
๋๋ค. ๋ฐ๋์ ํ๊ธ๋ก ๋ต๋ณํ์ธ์.
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์ฃผ์ด์ง CSV ํ์ผ์์ ์ฌ์ฉ์์ ์๊ตฌ์ ๋ง๋ ํ๋กฌํํธ๋ฅผ ์ฐพ์ ์ ๊ณตํ๋ ๊ฒ์ด ์ฃผ์ ์ญํ ์
๋๋ค.
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CSV ํ์ผ์ ์๋ ๋ด์ฉ์ ๋ํด์๋ ์ ์ ํ ๋๋ต์ ์์ฑํด ์ฃผ์ธ์.
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""", label="์์คํ
ํ๋กฌํํธ"),
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gr.Slider(minimum=1, maximum=4000, value=1000, step=1, label="Max new tokens"),
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gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="emperature"),
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gr.Slider(
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minimum=0.1,
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maximum=1.0,
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value=0.95,
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step=0.05,
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label="op-p (nucleus sampling)",
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),
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],
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examples=[
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["ํ๊ธ๋ก ๋ต๋ณํ ๊ฒ"],
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["๊ณ์ ์ด์ด์ ์์ฑํ๋ผ"],
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],
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cacheexamples=alse,
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)
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if name == "main":
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demo.launch()
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