This is page 1 of 2. Use http://codebase.md/tmlr-group/CausalCOAT?lines=false&page={x} to view the full context. # Directory Structure ``` ├── .DS_Store ├── AppleGastronome │ ├── .DS_Store │ ├── Apple_Gastronome_AG7_v20240513_colab_annoation_2024_05_16_1422_hk_Mixtral_GPT-3.5-Turbo_iter1.xlsx │ ├── Apple_Gastronome_AG7_v20240513_colab_annoation_2024_05_16_1422_hk_Mixtral_GPT-3.5-Turbo_iter2.xlsx │ ├── Apple_Gastronome_AG7_v20240513_colab_annoation_2024_05_16_1422_hk_Mixtral_GPT-3.5-Turbo_iter3.xlsx │ ├── Apple_Gastronome_AG7_v20240513.ipynb │ ├── Apple_Gastronome_AG7_v20240513.xlsx │ └── Formal_exp_1 AG7_2024_05_16_1422 GPT-3.5-Turbo release.ipynb ├── assets │ ├── coat_map.pdf │ └── paper.pdf ├── coat_real_world_case │ ├── brain_tumor.png │ └── news_n_stock.png ├── lingam_coat_result │ ├── lingam coat gpt3-5.png │ ├── lingam coat gpt4.png │ ├── lingam coat llama-2-70b.png │ ├── lingam coat mistral-med.png │ └── lingam_coat_table.xlsx ├── Neuropathic │ ├── Formal_exp_1_Neuro_RSI symptom_only release.ipynb │ ├── id_name.txt │ ├── neuro_addition_1000_0126.csv │ ├── neuro_R_shoulder_impingement.xlsx │ ├── Neuropathic_Pain_Diagnosis_v20240119.ipynb │ └── SimulatedData_SampleSize100.csv ├── openai_utils.py ├── README.md └── utils.py ``` # Files -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- ```markdown <h1 align='center'> Discovery of the Hidden World with Large Language Models </h1> <p align='center'> <a href="https://arxiv.org/abs/2402.03941"><img src="https://img.shields.io/badge/arXiv-2402.03941-b31b1b.svg" alt="Paper"></a> <a href="https://neurips.cc/"><img src="https://img.shields.io/badge/Pub-NeurIPS'24-blue" alt="Conf"></a> <a href="https://causalcoat.github.io/"><img src="https://img.shields.io/badge/website-CausalCOAT-D76364" alt="Slides"></a> </p> [NeurIPS 2024] Discovery of the Hidden World with Large Language Models This repository contains the source codes for reproducing the results of NeurIPS'24 paper: [**Discovery of the Hidden World with Large Language Models**](). **Author List**: Chenxi Liu*, Yongqiang Chen*, Tongliang Liu, Mingming Gong, James Cheng, Bo Han, Kun Zhang (* Equal Contribution) ## Prepare to Use API ### Interact with OpenAI 1. Go through [the OpenAI Quickstart Tutorial](https://platform.openai.com/docs/quickstart?context=python) 2. In this project, we `LLM_openai()` to contorl the interaction with OpenAI ```python import sys sys.path.insert(0, '/project/root/path') # set project root path from utils import Logger from openai_utils import LLM_openai # check the conversation log at 'logs/{exp_name}' logger = Logger( root = '/project/root/path', exp_name = 'set_exp_name' ) llm = LLM_openai(logger) response = llm.chat( model="gpt-4-1106-preview", content= "Hello GPT4!", system_instruct = "You are a helpful assistant." ) ``` ### Interact with Poe 1. Go through [the Poe FastAPI Tutorial](https://creator.poe.com/docs/accessing-other-bots-on-poe) 2. In this project, we `chat()` to contorl the interaction with Poe ```python import fastapi_poe as fp import asyncio async def chat(content, bot_name="GPT-3.5-Turbo" ): poe_api_key = "your api key" # set your api key message = fp.ProtocolMessage(role="user", content=content) responce = "" async for partial in fp.get_bot_response(messages=[message], bot_name=bot_name, api_key=poe_api_key): responce = responce + partial.text return responce response = await chat("Hello world!", bot_name="GPT-3.5-Turbo" ) ``` ## The AppleGastronome Benchmark ### Files - **Apple_Gastronome_AG7_v20240513.ipynb** This is the notebook to generate the AppleGastronome Benchmark dataset. "AG7" means there are 7 variables considered in the data-generating process. - **Apple_Gastronome_AG7_v20240513.xlsx** This is the generated AppleGastronome Benchmark dataset. It consists of 8 columns: 7 variables plus one column for the review texts. - **Formal_exp_1 AG7_2024_05_16_1422 GPT-3.5-Turbo release.ipynb** This is the notebook to test COAT method with different Foundation Models. - **Other .xlsx files** Annotations generated by [annotation-2024_05_16_1422_hk_mistralai_GPT-3.5-Turbo release.ipynb](https://colab.research.google.com/drive/1GHUIk631UzD-lI49H_0eTJc9YKJ2lwxe?usp=sharing) Conversation Logs: - **META**: https://poe.com/s/Suv0XqninMg9nQTGFEiy - **COAT+CoT**: https://poe.com/s/x1tha9wV6opPydhym2sQ - **DATA**: First round of COAT. - **COAT**: https://poe.com/s/tYvcQuIyRB54wVpyUZyx ## The Neuropathic Benchmark Source of the causal graph: [here](https://observablehq.com/@turuibo/the-complete-causal-graph-of-neuropathic-pain-diagnosis) ### Files - **SimulatedData_SampleSize100.csv** and **neuro_addition_1000_0126.csv** Generated from [Neuropathic Pain Diagnosis Simulator](https://github.com/TURuibo/Neuropathic-Pain-Diagnosis-Simulator). Simulation of the real-life diagnosis with three levels of variables, including the symptom-level, radiculopathy-level and the pathophysiology-level. - **id_name.txt** From [Neuropathic Pain Diagnosis Simulator](https://github.com/TURuibo/Neuropathic-Pain-Diagnosis-Simulator). It stores variable names. - **Neuropathic_Pain_Diagnosis_v20240119.ipynb** This is the notebook to generate clinical notes from tabular data *SimulatedData_SampleSize100.csv*. *Only symptom-level vairables are used.* - **neuro_R_shoulder_impingement.xlsx** This is the generated clinical notes. - **Formal_exp_1_Neuro_RSI symptom_only release.ipynb** This is the notebook to test COAT method with different Foundation Models. ``` -------------------------------------------------------------------------------- /utils.py: -------------------------------------------------------------------------------- ```python import os class Logger(): def __init__(self, root, exp_name): # Set path self.log_root_path = os.path.join(root, f'logs/{exp_name}') self.category = ['conversation', 'factors', 'causal_graph'] # init log files if not os.path.exists(self.log_root_path): os.makedirs(self.log_root_path) def straight_write(self, cate, content, mode='a'): assert cate in self.category with open(os.path.join(self.log_root_path, cate+'.log'), mode) as file: file.write('\n'+content+'\n') def get_value_from_responce(responce): if responce is None: return 'None' if 'he value is:' not in responce: return '?' last_part = responce.split('The value is:')[-1] if '-1' in last_part: return -1 elif '0' in last_part: return 0 elif '1' in last_part: return 1 ``` -------------------------------------------------------------------------------- /openai_utils.py: -------------------------------------------------------------------------------- ```python from openai import OpenAI import os import time class LLM_openai(): def __init__(self, logger): self.client = OpenAI() self.logger = logger self.thread_id = None def log(self, content): self.logger.straight_write('conversation', content, mode='a') def load_assistant(self, asst_id): self.asst_id = asst_id self.assistant = self.client.beta.assistants.retrieve(asst_id) self.log(f'>> Loaded OpenAI assistant {self.asst_id}') def delete_thread(self): if self.thread_id is None: return response = self.client.beta.threads.delete(self.thread_id) assert response.deleted self.thread_id = None def chat(self, content, system_instruct = None, model="gpt-4-1106-preview", **kwargs): ''' Output: - run_result - responce - files ''' # init self.delete_thread() if system_instruct is None: system_instruct = 'You are an excellently helpful AI assistant for analysis and abstraction on data.' # chat completions = self.client.chat.completions.create( model=model, messages=[ {"role": "system", "content": system_instruct}, {"role": "user", "content": content} ], **kwargs ) print(completions.id) self.log( ('-' * 5) + f'{completions.id}' + ('-' * 10)) self.log('User: \n' + content) # get responce responce = completions.choices[0].message.content self.log('ChatGPT: \n' + responce) return responce def chat_assistant(self, content, args, file_ids = []): ''' Output: - run_result - responce - files ''' # init self.delete_thread() sleep_gap = args['sleep gap'] max_wait = args['max wait'] # new thread thread = self.client.beta.threads.create( messages=[ { "role": "user", "content": content, "file_ids": file_ids } ] ) print(thread.id) self.thread_id = thread.id self.log( ('-' * 5) + f'{self.thread_id}' + ('-' * 10)) self.log('User: \n' + content) # run run_result = None run = self.client.beta.threads.runs.create( thread_id=thread.id, assistant_id=self.assistant.id ) print(run.id) for i in range(max_wait//sleep_gap+1): run = self.client.beta.threads.runs.retrieve( thread_id=thread.id, run_id=run.id ) print(i * sleep_gap, run.status) if not (run.status in ['in_progress', 'queued']): print(run.status) run_result = run.status # == 'completed' break if i >= max_wait//sleep_gap: run = self.client.beta.threads.runs.cancel( thread_id=thread.id, run_id=run.id ) run_result = 'time out' break time.sleep(sleep_gap) if run_result != 'completed': return run_result, None, None # get responce messages = self.client.beta.threads.messages.list( thread_id=thread.id ) num_responce = len(messages.data) responces = [] files = [] for i in range(num_responce-2, -1, -1): this_responce = messages.data[i].content[0].text.value responces.append(this_responce) for annotation in messages.data[i].content[0].text.annotations: if hasattr(annotation, 'file_path'): this_file_id = annotation.file_path.file_id this_file_content = self.client.files.content(this_file_id).read().decode("utf-8") files.append(this_file_content) self.log('ChatGPT: \n' + '\n'.join(responces)) if len(files) > 0: self.log('\n'.join(files)) return run_result, responces, files ``` -------------------------------------------------------------------------------- /Neuropathic/id_name.txt: -------------------------------------------------------------------------------- ``` 0: DLI C1-C2 1: DLI C2-C3 2: DLI C3-C4 3: DLI C4-C5 4: DLI C5-C6 5: DLI C6-C7 6: DLI C7-C8 7: DLI C8-T1 8: DLI L1-L2 9: DLI L2-L3 10: DLI L3-L4 11: DLI L4-L5 12: DLI L5-S1 13: DLI S1-S2 14: DLI T1-T2 15: DLI T10-T11 16: DLI T11-T12 17: DLI T12-L1 18: DLI T2-T3 19: DLI T3-T4 20: DLI T4-T5 21: DLI T5-T6 22: DLI T6-T7 23: DLI T7-T8 24: DLI T8-T9 25: DLI T9-T10 26: Kraniocervikal ledskada 27: L C2 Radiculopathy 28: R C2 Radiculopathy 29: L C3 Radiculopathy 30: R C3 Radiculopathy 31: L C4 Radiculopathy 32: R C4 Radiculopathy 33: L C5 Radiculopathy 34: R C5 Radiculopathy 35: L C6 Radiculopathy 36: R C6 Radiculopathy 37: L C7 Radiculopathy 38: R C7 Radiculopathy 39: L C8 Radiculopathy 40: R C8 Radiculopathy 41: L T1 Radiculopathy 42: R T1 Radiculopathy 43: L T2 Radiculopathy 44: R T2 Radiculopathy 45: L T3 Radiculopathy 46: R T3 Radiculopathy 47: L T4 Radiculopathy 48: R T4 Radiculopathy 49: L T5 Radiculopathy 50: R T5 Radiculopathy 51: L T6 Radiculopathy 52: R T6 Radiculopathy 53: L T7 Radiculopathy 54: R T7 Radiculopathy 55: L T8 Radiculopathy 56: R T8 Radiculopathy 57: L T9 Radiculopathy 58: R T9 Radiculopathy 59: L T10 Radiculopathy 60: R T10 Radiculopathy 61: L T11 Radiculopathy 62: R T11 Radiculopathy 63: L T12 Radiculopathy 64: R T12 Radiculopathy 65: L L1 Radiculopathy 66: R L1 Radiculopathy 67: L L2 Radiculopathy 68: R L2 Radiculopathy 69: L L3 Radiculopathy 70: R L3 Radiculopathy 71: L L4 Radiculopathy 72: R L4 Radiculopathy 73: L L5 Radiculopathy 74: R L5 Radiculopathy 75: L S1 Radiculopathy 76: R S1 Radiculopathy 77: L S2 Radiculopathy 78: R S2 Radiculopathy 79: Ibs 80: L neck problems 81: Neck pain 82: R neck 83: L tinnitus 84: L eye problems 85: L ear problems 86: R tinnitus 87: R eye problems 88: R ear problems 89: Headache 90: L jaw problems 91: L forehead headache 92: Mouth 93: Forehead headache 94: R headache 95: R pta 96: Pharyngeal discomfort 97: R jaw trouble 98: Back headache 99: R back headache pain 100: L collarbone pain 101: R collarbone problems 102: Central chest pain 103: L central chest pain 104: L central chest disorders 105: R front axle problems 106: L shoulder impingement 107: R shoulder impingement 108: L shoulder problems 109: L shoulder trouble 110: R shoulder problems 111: R shoulder trouble 112: L upper arm discomfort 113: L upper elbow pain 114: Intracapular problems 115: L interscapular complaints 116: R intracapular trouble 117: L lateral elbow pain 118: L lateral arm discomfort 119: R lateral elbow pain 120: L elbow problems 121: R elbow trouble 122: L arm 123: L thumbs up 124: R thumbs up 125: L wrist problems 126: R wrist problems 127: L lower arm disorders 128: R lower arm disorders 129: L hand problems 130: R hand problems 131: L bend of arm problems 132: R armband 133: R bend of arm discomfort 134: L medial elbow problems 135: R medial elbow problems 136: L finger trouble 137: R finger trouble 138: L small finger trouble 139: R little finger trouble 140: L groin trouble 141: L medial groin disorders 142: L lateral groin discomfort 143: Central groin disorders 144: R lateral groin discomfort 145: R groin trouble 146: L adductor tendon 147: R adductor tendonitis 148: L hip disorders 149: L backache 150: Backache 151: L lumbago 152: Lumbago 153: R lumbago 154: L front thigh pain 155: R front thigh pain 156: R thigh problems 157: L leg problems 158: L thigh pain 159: R leg problems 160: R medial vadbesvär 161: L pta 162: L hip joint 163: R hip trouble 164: R hip arthritis 165: L medial knee joint disorder 166: L front knee pain 167: R medial knee joint disorder 168: R front knee pain 169: L shin 170: R shin 171: L llower leg problems 172: L knee trouble 173: R knee trouble 174: L tåledbesvär 175: L big toe problems 176: R big toe problems 177: L foot pain 178: L ankle trouble 179: R ankle trouble 180: L footstool trouble 181: R arch 182: R morton trouble 183: R fainting 184: L ischias 185: R ischias 186: L ham 187: L obesity 188: R ham 189: L toe problems 190: R foot pain 191: R tear problems 192: R obesity 193: R dorsal knee joint disorder 194: L dorsal knee joint disorder 195: L lateral knee pain 196: R lateral knee pain 197: L small toe trouble 198: L lateral foot disorders 199: R lateral foot disorders 200: R heel problems 201: Calcaneal pain 202: L heel problems 203: Coccydyni 204: L rear thigh pain 205: R rear thigh pain 206: L achilles problems 207: L achilles tendon 208: L achillodyni 209: R achilles problems 210: R achilles tendency 211: R achillodyni 212: Breast backache 213: Chest discomfort 214: L breast problems 215: R breast problems 216: Toracal dysfunction 217: Upper abdominal discomfort 218: Lateral abdominal discomfort 219: Abdominal discomfort 220: L lower abdominal discomfort 221: Lower abdominal discomfort ``` -------------------------------------------------------------------------------- /Neuropathic/SimulatedData_SampleSize100.csv: -------------------------------------------------------------------------------- ``` 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