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paper.py
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| 1 |
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import os
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| 2 |
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import json
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| 3 |
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import logging
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| 4 |
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from datetime import datetime, timedelta
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| 5 |
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from langchain_google_genai import ChatGoogleGenerativeAI
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from langchain.schema import SystemMessage, HumanMessage
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
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| 9 |
+
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| 10 |
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class Agent:
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| 11 |
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def __init__(self, role: str, goal: str, backstory: str, personality: str = "", llm=None) -> None:
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| 12 |
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"""
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| 13 |
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Initialize an Agent with role, goal, backstory, personality, and assigned LLM.
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| 14 |
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"""
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self.role = role
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self.goal = goal
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self.backstory = backstory
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self.personality = personality
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| 19 |
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self.tools = [] # Initialize with empty list for future tool integrations
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self.llm = llm
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class Task:
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def __init__(self, description: str, agent: Agent, expected_output: str, context=None) -> None:
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"""
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Initialize a Task with its description, the responsible agent, expected output, and optional context.
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| 26 |
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"""
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self.description = description
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self.agent = agent
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self.expected_output = expected_output
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self.context = context or []
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| 31 |
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google_api_key = os.getenv("GEMINI_API_KEY") # 실제 Google API 키 사용
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if not google_api_key:
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logging.error("GEMINI_API_KEY is not set in the environment variables.")
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llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", google_api_key=google_api_key)
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# -------------------------------------------------------------------------------
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| 38 |
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# Define Academic Research Agents
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# -------------------------------------------------------------------------------
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literature_research_agent = Agent(
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role="Assumsions Analysis Agent",
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goal="Provide a comprehensive review of existing assumsions on the feasibility study topic.",
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| 43 |
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backstory="An experienced academic researcher specialized in feasibility study assumsions and meta-analyses.",
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| 44 |
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personality="Analytical, thorough, and detail-oriented.",
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llm=llm,
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)
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outline_agent = Agent(
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role="Outline Agent",
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goal="Generate a structured and detailed outline for a feasibility study based on the assumsions. The outline that needs to be prepared includes: Market Analysis, Technical Analysis, Financial Analysis, Legal and Regulatory Analysis, Risk Analysis, Environmental and Social Impact Analysis, Conclusions and Recommendations.",
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| 51 |
+
backstory="A methodical academic planner who organizes feasibility study findings into coherent paper structures.",
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| 52 |
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personality="Organized, systematic, and insightful.",
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| 53 |
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llm=llm,
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)
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| 55 |
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draft_writing_agent = Agent(
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role="Draft Writing Agent",
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goal="Compose a first draft of the feasibility paper based on the assumsions review and outline. The writings that needs to be prepared includes: Market Analysis, Technical Analysis, Financial Analysis, Legal and Regulatory Analysis, Risk Analysis, Environmental and Social Impact Analysis, Conclusions and Recommendations.",
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| 59 |
+
backstory="A skilled academic writer capable of synthesizing feasibility study findings into well-structured drafts.",
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| 60 |
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personality="Articulate, precise, and scholarly.",
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llm=llm,
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)
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+
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citation_agent = Agent(
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role="Citation Agent",
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goal="Generate a list of relevant citations and references in the required format for the research paper.",
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backstory="A detail-oriented bibliographic expert with extensive knowledge of citation standards.",
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personality="Meticulous, accurate, and research-savvy.",
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llm=llm,
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)
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editing_agent = Agent(
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role="Editing Agent",
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goal="Revise and polish the draft for clarity, coherence, and academic tone. The writings that needs to be prepared includes: Market Analysis, Technical Analysis, Financial Analysis, Legal and Regulatory Analysis, Risk Analysis, Environmental and Social Impact Analysis, Conclusions and Recommendations.",
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| 75 |
+
backstory="An expert editor skilled in improving feasibility manuscripts and ensuring high-quality presentation.",
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| 76 |
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personality="Critical, precise, and supportive.",
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llm=llm,
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| 78 |
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)
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chatbot_agent = Agent(
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| 81 |
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role="Chatbot Agent",
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| 82 |
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goal="Engage in interactive conversation to answer queries related to the feasibility study documents",
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| 83 |
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backstory="A conversational AI assistant with extensive knowledge in academia,feasibility study, and research methodologies.",
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| 84 |
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personality="Helpful, conversational, and knowledgeable.",
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| 85 |
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llm=llm,
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| 86 |
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)
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| 88 |
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# -------------------------------------------------------------------------------
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| 89 |
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# Define Tasks for Academic Research and Writing
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| 90 |
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# -------------------------------------------------------------------------------
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literature_research_task = Task(
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| 92 |
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description="""prepare the creation of a Feasibility Study with the theme on {topic} considering the keywords {keywords}.
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| 93 |
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Please provide:
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- Market Analysis
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- Technical Analysis
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- Financial Analysis
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- Legal and Regulatory Analysis
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| 99 |
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- Risk Analysis
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| 100 |
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- Environmental and Social Impact Analysis
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- Conclusions and Recommendations
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| 102 |
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Format the response with bullet points and concise summaries.""",
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| 103 |
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agent=literature_research_agent,
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expected_output="""A comprehensive Feasibility Study covering:
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| 105 |
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1. Market Analysis
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2. Technical Analysis
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| 107 |
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3. Financial Analysis
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| 108 |
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4. Legal and Regulatory Analysis
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| 109 |
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5. Risk Analysis
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| 110 |
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6. Environmental and Social Impact Analysis
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| 111 |
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7. Conclusions and Recommendations"""
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| 112 |
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)
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| 113 |
+
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| 114 |
+
outline_task = Task(
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| 115 |
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description="""Based on the Feasibility Study topic {topic} and assumsions review findings, generate a detailed outline for a Feasibility Study paper.
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| 116 |
+
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| 117 |
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Include sections such as:
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| 118 |
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- Market Analysis
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| 119 |
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- Technical Analysis
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| 120 |
+
- Financial Analysis
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| 121 |
+
- Legal and Regulatory Analysis
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| 122 |
+
- Risk Analysis
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| 123 |
+
- Environmental and Social Impact Analysis
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| 124 |
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- Conclusions and Recommendations
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| 125 |
+
- References
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| 126 |
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Format the outline in a structured manner with bullet points and subheadings.""",
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| 127 |
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agent=outline_agent,
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| 128 |
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expected_output="A structured outline for a Feasibility Study paper including all major sections and key points to cover in each section."
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| 129 |
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)
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| 130 |
+
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| 131 |
+
draft_writing_task = Task(
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| 132 |
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description="""Using the Feasibility Study topic {topic}, the assumsions review, and the generated outline, compose a first draft of the Feasibility Study paper.
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| 133 |
+
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| 134 |
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The draft should include:
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| 135 |
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- Market Analysis
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| 136 |
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- Technical Analysis
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| 137 |
+
- Financial Analysis
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| 138 |
+
- Legal and Regulatory Analysis
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| 139 |
+
- Risk Analysis
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| 140 |
+
- Environmental and Social Impact Analysis
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| 141 |
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- Conclusions and Recommendations
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| 142 |
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- References
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| 143 |
+
Ensure the tone is academic and the content is well-organized.""",
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| 144 |
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agent=draft_writing_agent,
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| 145 |
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expected_output="A complete first draft of the Feasibility Study paper covering all sections with sufficient academic detail."
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| 146 |
+
)
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| 147 |
+
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| 148 |
+
citation_task = Task(
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| 149 |
+
description="""Based on the Feasibility Study review for {topic}, generate a list of key references and citations in APA format.
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| 150 |
+
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| 151 |
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Include:
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| 152 |
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- Author names, publication year, title, and source,
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| 153 |
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- At least 10 key references relevant to the research topic.
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| 154 |
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Format the output as a numbered list of citations.""",
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| 155 |
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agent=citation_agent,
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| 156 |
+
expected_output="A list of 10+ relevant citations in APA format."
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| 157 |
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)
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| 158 |
+
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| 159 |
+
editing_task = Task(
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| 160 |
+
description="""Review and edit the draft for clarity, coherence, and academic tone.
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| 161 |
+
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| 162 |
+
Focus on:
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| 163 |
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- Improving sentence structure,
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| 164 |
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- Ensuring logical flow between sections,
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| 165 |
+
- Correcting grammar and stylistic issues,
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| 166 |
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- Enhancing academic tone.
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| 167 |
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Provide the polished version of the paper.""",
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| 168 |
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agent=editing_agent,
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| 169 |
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expected_output="A refined and polished version of the Feasibility Study paper draft."
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| 170 |
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)
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| 171 |
+
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| 172 |
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chatbot_task = Task(
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| 173 |
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description="Provide a conversational and detailed response to Feasibility Study-related queries.",
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| 174 |
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agent=chatbot_agent,
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| 175 |
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expected_output="A friendly, informative response addressing the query."
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| 176 |
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)
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| 177 |
+
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def run_task(task: Task, input_text: str) -> str:
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| 179 |
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"""
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| 180 |
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Executes the given task using the associated agent's LLM and returns the response content.
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| 181 |
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"""
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| 182 |
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try:
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| 183 |
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if not isinstance(task, Task):
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| 184 |
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raise ValueError(f"Expected 'task' to be an instance of Task, got {type(task)}")
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| 185 |
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if not hasattr(task, 'agent') or not isinstance(task.agent, Agent):
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raise ValueError("Task must have a valid 'agent' attribute of type Agent.")
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| 187 |
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system_input = (
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| 188 |
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f"Agent Details:\n"
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| 189 |
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f"Role: {task.agent.role}\n"
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| 190 |
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f"Goal: {task.agent.goal}\n"
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| 191 |
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f"Backstory: {task.agent.backstory}\n"
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f"Personality: {task.agent.personality}\n"
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)
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task_input = (
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f"Task Details:\n"
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f"Task Description: {task.description}\n"
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f"Expected Output: {task.expected_output}\n"
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f"Input for Task:\n{input_text}\n"
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)
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messages = [
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SystemMessage(content=system_input),
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HumanMessage(content=task_input)
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]
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response = task.agent.llm.invoke(messages)
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if not response or not response.content:
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raise ValueError("Empty response from LLM.")
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return response.content
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except Exception as e:
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logging.error(f"Error in task '{task.agent.role}': {e}")
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return f"Error in {task.agent.role}: {e}"
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