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update and clean the scripts but not finished
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,136 @@ | ||
| from research_town.agents import AgentManager | ||
| from research_town.configs import Config | ||
| from research_town.dbs import LogDB, PaperDB, ProfileDB, ProgressDB | ||
| from research_town.envs import ProposalWritingEnv | ||
| from research_town.utils.paper_collector import get_paper_introduction | ||
| from typing import List, Optional | ||
| import logging | ||
| import os | ||
| from typing import Optional | ||
| from research_town.utils.model_prompting import model_prompting | ||
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| def write_proposal_researchtown( | ||
| authors: List[str], intros: List[str], keyword: str, id: int | ||
| ) -> Optional[str]: | ||
| """ | ||
| Generates a comprehensive research proposal based on the provided authors and existing proposals | ||
| using the ProposalWritingEnv environment. | ||
| Args: | ||
| authors (List[str]): List of author names. | ||
| intros (List[str]): List of existing introduction texts. | ||
| Returns: | ||
| Optional[str]: Generated proposal as a string if successful, else None. | ||
| """ | ||
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| config = Config('../configs') | ||
| if os.path.exists(f'./profile_dbs/profile_{id}'): | ||
| profile_db = ProfileDB(load_file_path=f'./profile_dbs/profile_{id}') | ||
| else: | ||
| profile_db = ProfileDB() | ||
| profile_db.pull_profiles(names=authors, config=config) | ||
| profile_db.save_to_json(f'./profile_dbs/profile_{id}') | ||
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| # Initialize other databases using default instances | ||
| log_db = LogDB() | ||
| progress_db = ProgressDB() | ||
| paper_db = PaperDB() # Assuming existing papers are handled elsewhere | ||
| paper_db.pull_papers(num=3, domain=keyword) | ||
| # Initialize ProposalWritingEnv with the required databases and configuration | ||
| agent_manager = AgentManager(config=config, profile_db=profile_db) | ||
| env = ProposalWritingEnv( | ||
| name='proposal_writing', | ||
| log_db=log_db, | ||
| progress_db=progress_db, | ||
| paper_db=paper_db, | ||
| config=config, | ||
| agent_manager=agent_manager, | ||
| ) | ||
| logger.info('Initialized ProposalWritingEnv.') | ||
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| # Create a leader agent (assuming `create_leader` requires a profile) | ||
| leader_profile = profile_db.get(name=authors[0])[0] | ||
| print('leader_profile', leader_profile) | ||
| leader = agent_manager.create_agent(leader_profile, role='leader') | ||
| if not leader_profile: | ||
| logger.error('No valid leader profile found.') | ||
| return None | ||
| logger.info('Created leader agent for profile') | ||
|
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| # Prepare the context from existing proposals | ||
| # Assuming that the context should be a list of proposal strings | ||
| env.on_enter( | ||
| leader=leader, | ||
| contexts=intros, | ||
| ) | ||
| logger.info('Entered ProposalWritingEnv with provided proposals as context.') | ||
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| # Run the environment to generate the proposal | ||
| run_result = env.run() | ||
| if run_result is not None: | ||
| for progress, agent in run_result: | ||
| # Process progress and agent if needed | ||
| pass | ||
| logger.info('Ran ProposalWritingEnv.') | ||
|
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| # Exit the environment and retrieve the generated proposal | ||
| exit_status, exit_dict = env.on_exit() | ||
| proposal = exit_dict.get('proposal') | ||
| if proposal and proposal.content: | ||
| logger.info('Successfully generated proposal.') | ||
| return str(proposal.content) | ||
| else: | ||
| logger.warning('Proposal generation returned no content.') | ||
| return None | ||
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| def write_proposal_baseline(intro: str, model: str = 'gpt-4o-mini') -> Optional[str]: | ||
| """ | ||
| Generates the five core research questions based on the introduction text using an LLM. | ||
| Args: | ||
| intro (str): Introduction text of the paper. | ||
| Returns: | ||
| Optional[str]: Generated five core questions as a string. | ||
| """ | ||
| try: | ||
| prompt = [ | ||
| { | ||
| 'role': 'user', | ||
| 'content': ( | ||
| 'Here is a high-level summarized insight of a research field Machine Learning.\n\n' | ||
| 'Here are the five core questions:\n\n' | ||
| '[Question 1] - What is the problem?\n\n' | ||
| 'Formulate the specific research question you aim to address. Only output one question and do not include any more information.\n\n' | ||
| '[Question 2] - Why is it interesting and important?\n\n' | ||
| 'Explain the broader implications of solving this problem for the research community.\n' | ||
| 'Discuss how such paper will affect the future research.\n' | ||
| 'Discuss how addressing this question could advance knowledge or lead to practical applications.\n\n' | ||
| '[Question 3] - Why is it hard?\n\n' | ||
| 'Discuss the challenges and complexities involved in solving this problem.\n' | ||
| 'Explain why naive or straightforward approaches may fail.\n' | ||
| 'Identify any technical, theoretical, or practical obstacles that need to be overcome. MAKE IT CLEAR.\n\n' | ||
| "[Question 4] - Why hasn't it been solved before?\n\n" | ||
| 'Identify gaps or limitations in previous research or existing solutions.\n' | ||
| 'Discuss any barriers that have prevented this problem from being solved until now.\n' | ||
| 'Explain how your approach differs from or improves upon prior work. MAKE IT CLEAR.\n\n' | ||
| '[Question 5] - What are the key components of my approach and results?\n\n' | ||
| 'Outline your proposed methodology in detail, including the method, dataset, metric that you plan to use.\n' | ||
| 'Describe the expected outcomes. MAKE IT CLEAR.\n\n' | ||
| f'Introduction:\n{intro}\n\n' | ||
| 'Please provide the five core questions contents based on the above introduction.' | ||
| ), | ||
| } | ||
| ] | ||
| response = model_prompting(model, prompt, mode='TEST') | ||
| if response and len(response) > 0 and len(response[0]) > 0: | ||
| return response[0] | ||
| else: | ||
| print('Received empty response from model_prompting for current_5q.') | ||
| return None | ||
| except Exception as e: | ||
| print(f'Error generating current_5q: {e}') | ||
| return None |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,33 @@ | ||
| import argparse | ||
| from proposal_writing import write_proposal_researchtown | ||
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| def main(args: argparse.Namespace) -> None: | ||
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| return | ||
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| if __name__ == '__main__': | ||
| parser = argparse.ArgumentParser() | ||
| parser.add_argument( | ||
| '--input', type=str, required=True, help='Path to the input JSON file.' | ||
| ) | ||
| parser.add_argument( | ||
| '--output', type=str, required=True, help='Path to the output JSONL file.' | ||
| ) | ||
| parser.add_argument( | ||
| '--intro_log', | ||
| type=str, | ||
| required=False, | ||
| help='Path to the introduction log JSONL file.', | ||
| ) | ||
| parser.add_argument( | ||
| '--model_name', | ||
| type=str, | ||
| required=False, | ||
| default='gpt-40-mini', | ||
| help='Model name for the single agent test.', | ||
| ) | ||
| args = parser.parse_args() | ||
|
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| main(args) |
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