Create paper.py

paper.py

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+import os
+import json
+import logging
+from datetime import datetime, timedelta
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain.schema import SystemMessage, HumanMessage
+
+logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s")
+
+class Agent:
+    def __init__(self, role: str, goal: str, backstory: str, personality: str = "", llm=None) -> None:
+        """
+        Initialize an Agent with role, goal, backstory, personality, and assigned LLM.
+        """
+        self.role = role
+        self.goal = goal
+        self.backstory = backstory
+        self.personality = personality
+        self.tools = []  # Initialize with empty list for future tool integrations
+        self.llm = llm
+
+class Task:
+    def __init__(self, description: str, agent: Agent, expected_output: str, context=None) -> None:
+        """
+        Initialize a Task with its description, the responsible agent, expected output, and optional context.
+        """
+        self.description = description
+        self.agent = agent
+        self.expected_output = expected_output
+        self.context = context or []
+
+google_api_key = os.getenv("GEMINI_API_KEY")  # 실제 Google API 키 사용
+if not google_api_key:
+    logging.error("GEMINI_API_KEY is not set in the environment variables.")
+llm = ChatGoogleGenerativeAI(model="gemini-2.0-flash", google_api_key=google_api_key)
+
+# -------------------------------------------------------------------------------
+# Define Academic Research Agents
+# -------------------------------------------------------------------------------
+literature_research_agent = Agent(
+    role="Literature Research Agent",
+    goal="Research and provide a comprehensive review of existing literature on the research topic.",
+    backstory="An experienced academic researcher specialized in literature reviews and meta-analyses.",
+    personality="Analytical, thorough, and detail-oriented.",
+    llm=llm,
+)
+
+outline_agent = Agent(
+    role="Outline Agent",
+    goal="Generate a structured and detailed outline for a research paper based on the research topic and literature.",
+    backstory="A methodical academic planner who organizes research findings into coherent paper structures.",
+    personality="Organized, systematic, and insightful.",
+    llm=llm,
+)
+
+draft_writing_agent = Agent(
+    role="Draft Writing Agent",
+    goal="Compose a first draft of the research paper based on the literature review and outline.",
+    backstory="A skilled academic writer capable of synthesizing research findings into well-structured drafts.",
+    personality="Articulate, precise, and scholarly.",
+    llm=llm,
+)
+
+citation_agent = Agent(
+    role="Citation Agent",
+    goal="Generate a list of relevant citations and references in the required format for the research paper.",
+    backstory="A detail-oriented bibliographic expert with extensive knowledge of citation standards.",
+    personality="Meticulous, accurate, and research-savvy.",
+    llm=llm,
+)
+
+editing_agent = Agent(
+    role="Editing Agent",
+    goal="Revise and polish the draft for clarity, coherence, and academic tone.",
+    backstory="An expert editor skilled in improving academic manuscripts and ensuring high-quality presentation.",
+    personality="Critical, precise, and supportive.",
+    llm=llm,
+)
+
+chatbot_agent = Agent(
+    role="Chatbot Agent",
+    goal="Engage in interactive conversation to answer queries related to the academic research process.",
+    backstory="A conversational AI assistant with extensive knowledge in academia and research methodologies.",
+    personality="Helpful, conversational, and knowledgeable.",
+    llm=llm,
+)
+
+# -------------------------------------------------------------------------------
+# Define Tasks for Academic Research and Writing
+# -------------------------------------------------------------------------------
+literature_research_task = Task(
+    description="""Research academic literature on {topic} considering the keywords {keywords}.
+    
+Please provide:
+- A summary of the current state of research,
+- Key trends and gaps in the literature,
+- Notable studies and their findings,
+- Relevant theoretical frameworks and methodologies.
+Format the response with bullet points and concise summaries.""",
+    agent=literature_research_agent,
+    expected_output="""A comprehensive literature review summary covering:
+1. Summary of current research trends
+2. Identification of gaps and controversies
+3. Key studies with brief descriptions
+4. Theoretical frameworks and methodologies used"""
+)
+
+outline_task = Task(
+    description="""Based on the research topic {topic} and literature review findings, generate a detailed outline for a research paper.
+    
+Include sections such as:
+- Abstract
+- Introduction (including research questions and objectives)
+- Literature Review
+- Methodology
+- Results/Findings
+- Discussion
+- Conclusion
+- References
+Format the outline in a structured manner with bullet points and subheadings.""",
+    agent=outline_agent,
+    expected_output="A structured outline for a research paper including all major sections and key points to cover in each section."
+)
+
+draft_writing_task = Task(
+    description="""Using the research topic {topic}, the literature review, and the generated outline, compose a first draft of the research paper.
+    
+The draft should include:
+- A coherent narrative flow,
+- Detailed sections as per the outline,
+- Integration of key findings from the literature review.
+Ensure the tone is academic and the content is well-organized.""",
+    agent=draft_writing_agent,
+    expected_output="A complete first draft of the research paper covering all sections with sufficient academic detail."
+)
+
+citation_task = Task(
+    description="""Based on the literature review for {topic}, generate a list of key references and citations in APA format.
+    
+Include:
+- Author names, publication year, title, and source,
+- At least 10 key references relevant to the research topic.
+Format the output as a numbered list of citations.""",
+    agent=citation_agent,
+    expected_output="A list of 10+ relevant citations in APA format."
+)
+
+editing_task = Task(
+    description="""Review and edit the draft for clarity, coherence, and academic tone.
+    
+Focus on:
+- Improving sentence structure,
+- Ensuring logical flow between sections,
+- Correcting grammar and stylistic issues,
+- Enhancing academic tone.
+Provide the polished version of the paper.""",
+    agent=editing_agent,
+    expected_output="A refined and polished version of the research paper draft."
+)
+
+chatbot_task = Task(
+    description="Provide a conversational and detailed response to academic research-related queries.",
+    agent=chatbot_agent,
+    expected_output="A friendly, informative response addressing the query."
+)
+
+def run_task(task: Task, input_text: str) -> str:
+    """
+    Executes the given task using the associated agent's LLM and returns the response content.
+    """
+    try:
+        if not isinstance(task, Task):
+            raise ValueError(f"Expected 'task' to be an instance of Task, got {type(task)}")
+        if not hasattr(task, 'agent') or not isinstance(task.agent, Agent):
+            raise ValueError("Task must have a valid 'agent' attribute of type Agent.")
+        system_input = (
+            f"Agent Details:\n"
+            f"Role: {task.agent.role}\n"
+            f"Goal: {task.agent.goal}\n"
+            f"Backstory: {task.agent.backstory}\n"
+            f"Personality: {task.agent.personality}\n"
+        )
+        task_input = (
+            f"Task Details:\n"
+            f"Task Description: {task.description}\n"
+            f"Expected Output: {task.expected_output}\n"
+            f"Input for Task:\n{input_text}\n"
+        )
+        messages = [
+            SystemMessage(content=system_input),
+            HumanMessage(content=task_input)
+        ]
+        response = task.agent.llm.invoke(messages)
+        if not response or not response.content:
+            raise ValueError("Empty response from LLM.")
+        return response.content
+    except Exception as e:
+        logging.error(f"Error in task '{task.agent.role}': {e}")
+        return f"Error in {task.agent.role}: {e}"