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6 changes: 5 additions & 1 deletion commands.sh
Original file line number Diff line number Diff line change
Expand Up @@ -23,6 +23,7 @@ conda activate autog-cpu
# -------------- install other dependencies int autog-cpu environment
pip install codetiming humanfriendly sentence_transformers==3.3.0 nltk==3.9.1 torchdata==0.7 torchtext==0.16.0
pip install transformers==4.44.2
pip install llama-index llama-index-llms-bedrock
# for Graphviz
sudo apt-get install graphviz
# for nltk data
Expand Down Expand Up @@ -70,10 +71,13 @@ bash scripts/download.sh
# - input the overall prompt+new contents into an LLM (e.g., Claud Sonet 3.5+) API or Web console to get answer.
# - copy the answer (in RAW format!!!!!) and save to a file, named type.txt under the mag/ folder.

# 2. run autog, and explanation of these arguments
# 2. Option 1: run autog (manually call LLM), and explanation of these arguments
# mag -> name of the --dataset argument
# /data/datasets -> path of the folder that store data, .e.g, /data/datasets
# autog-s -> the method to run the model
# type.txt -> the name of file to save analysis results from LLM. Since we manually create this, this file is not used.
# venue -> Name of the task to fit the solution
python -m main.autog mag ./data/datasets/mag autog-s type.txt venue

# 2. Option 2: run autog2 (automatically interact with LLM for single or multiple rounds)
python -m main.autog2 mag anthropic.claude-3-sonnet-20240229-v1:0 ./data/datasets autog-s venue
2 changes: 1 addition & 1 deletion main/autog2.py
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
import typer
import numpy as np
from rich import traceback
from models.autog.agent import AutoG_Agent
from models.autog.agent_old import AutoG_Agent
from prompts.task import get_task_description
from utils.misc import seed_everything
from utils.data.rdb import load_dbb_dataset_from_cfg_path_no_name
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2 changes: 1 addition & 1 deletion scripts/download.sh
Original file line number Diff line number Diff line change
@@ -1,6 +1,6 @@
## IEEE-CIS RR Movielens Outbrain MAG AVS diginetica ESCI Stackexchange

dataset_path="/data/datasets"
dataset_path="./data/datasets"

mkdir -p $dataset_path

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