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import os
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from dotenv import load_dotenv
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load_dotenv()
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OPENAI_API_KEY = os.getenv('OPENAI_API_KEY')
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TAVILY_API_KEY = os.getenv('TAVILY_API_KEY')
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from langchain_openai import ChatOpenAI
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from crewai import Agent, Task, Crew, Process
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llm = ChatOpenAI(model='gpt-3.5-turbo', temperature=0, api_key=OPENAI_API_KEY)
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from langchain_community.tools.tavily_search import TavilySearchResults
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search_tool = TavilySearchResults(api_key = TAVILY_API_KEY)
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def rus_crypto_crew(topic):
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researcher = Agent(
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role = 'Market Researcher',
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goal = f'Uncover emerging trend and investment opportunities in the cryptocurrency market in 2024. Focus on topic {topic}',
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backstory = 'Identify groundbreaking trend and actionable insights.',
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verbose = True,
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tools = [search_tool],
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allow_delegation = False,
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llm = llm,
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max_iter = 3,
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max_rpm = 10
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)
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analyst = Agent(
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role = 'investment analyst',
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goal = f'Analyze cryptocurrency market data to extract actionable insights and investment leads. Focus on topic {topic}',
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backstory = 'Draw meaningful conclusion from market data.',
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verbose = True,
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allow_delegation = False,
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llm = llm
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)
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translator = Agent(
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role = 'translator',
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goal = 'Translate report about cryptocurrency market data into korean',
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backstory = 'Translate this sentence into very natural Korean.',
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verbose = True,
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allow_delegation = False,
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llm = llm
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)
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research_task = Task(
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description = 'Explore the internet to pinpoint emerging trends and potential investment opportunities.',
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agent = researcher,
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expected_output='A detailed summary of the reserch results in string format'
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)
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analyze_task = Task(
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description = 'Analyze the provided cryptocurrency market data to extract key insights and compile a concise report.',
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agent = analyst,
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expected_output='A refined finalized version of the report in string format'
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)
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translate_task = Task(
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description = 'Translate documents written by analyst into korean.',
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agent = translator,
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expected_output = 'A translated report written by analyst(english into korean).'
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)
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crypto_crew = Crew(
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agents = [researcher, analyst, translator],
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tasks = [research_task, analyze_task, translate_task],
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process = Process.sequential
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)
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result = crypto_crew.kickoff()
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return result
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import gradio as gr
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def process_query(message, history):
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return rus_crypto_crew(message)
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app = gr.ChatInterface(
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fn = process_query,
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title = 'Crypto Investment Advisor Bot',
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description = '์ํธํํ ๊ด๋ จ ํธ๋ ๋๋ฅผ ํ์
ํ์ฌ ํฌ์ ์ธ์ฌ์ดํธ๋ฅผ ์ ๊ณตํด๋๋ฆฝ๋๋ค.'
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)
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app.launch() |