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·
205d5cc
1
Parent(s):
a394efd
fix path in app.py
Browse files- .gitignore +2 -0
- app.py +8 -7
- evaluation_p_metrics.csv +0 -0
- models.csv +6 -2
- models_logo/CHATGPT3_5.png +0 -0
- models_logo/CHATGPT4mini.png +0 -0
- models_logo/CHATGPTo1mini.png +0 -0
- models_logo/DEEPSEEK.jpg +0 -0
- models_logo/LLAMA.jpg +0 -0
- models_logo/QWQ.png +0 -0
- test_prediction.py +5 -2
- utilities.py +9 -1
- utils_get_db_tables_info.py +0 -1
.gitignore
CHANGED
@@ -1,5 +1,7 @@
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__pycache__
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# Byte-compiled / optimized / DLL files
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logs/
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__pycache__
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._*
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# Byte-compiled / optimized / DLL files
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logs/
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app.py
CHANGED
@@ -1,6 +1,9 @@
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import gradio as gr
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import pandas as pd
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import os
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# # https://discuss.huggingface.co/t/issues-with-sadtalker-zerogpu-spaces-inquiry-about-community-grant/110625/10
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# if os.environ.get("SPACES_ZERO_GPU") is not None:
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# import spaces
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@@ -16,20 +19,18 @@ from qatch.connectors.sqlite_connector import SqliteConnector
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from qatch.generate_dataset.orchestrator_generator import OrchestratorGenerator
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from qatch.evaluate_dataset.orchestrator_evaluator import OrchestratorEvaluator
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from prediction import ModelPrediction
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import
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import utilities as us
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import time
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import plotly.express as px
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import plotly.graph_objects as go
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import plotly.colors as pc
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import re
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import csv
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# @spaces.GPU
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# def model_prediction():
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# pass
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pnp_path = os.path.join("data", "evaluation_p_metrics.csv")
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with open('style.css', 'r') as file:
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css = file.read()
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import gradio as gr
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import pandas as pd
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import os
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import re
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import csv
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import time
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# # https://discuss.huggingface.co/t/issues-with-sadtalker-zerogpu-spaces-inquiry-about-community-grant/110625/10
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# if os.environ.get("SPACES_ZERO_GPU") is not None:
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# import spaces
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from qatch.generate_dataset.orchestrator_generator import OrchestratorGenerator
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from qatch.evaluate_dataset.orchestrator_evaluator import OrchestratorEvaluator
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from prediction import ModelPrediction
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from utils_get_db_tables_info import utils_extract_db_schema_as_string
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import utilities as us
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import plotly.express as px
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import plotly.graph_objects as go
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import plotly.colors as pc
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pnp_path = os.path.join("data", "evaluation_p_metrics.csv")
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us.check_and_create_dir('data/data_interface/')
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us.check_and_create_dir('data/data_results/')
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us.check_and_create_dir('data/databases/')
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with open('style.css', 'r') as file:
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css = file.read()
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evaluation_p_metrics.csv
DELETED
The diff for this file is too large to render.
See raw diff
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models.csv
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name,code,price,image_path
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Meta-
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name,code,price,image_path
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Meta LLAMA-8,llama-8,0.0,./models_logo/LLAMA.jpg
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DeepSeek-R1-Distill-Llama-70B,DeepSeek-R1-Distill-Llama-70B,0.0,./models_logo/DEEPSEEK.jpg
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CHAT GPT-3.5,gpt-3.5,0.0,models_logo/CHATGPT3_5.png
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CHAT GPT-4 mini,gpt-4o-mini,0.0,./models_logo/CHATGPT4mini.png
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CHAT GPT-o1-mini,o1-mini,0.0,./models_logo/CHATGPTo1mini.png
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QwQ,QwQ,0.0,./models_logo/QWQ.png
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models_logo/CHATGPT3_5.png
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models_logo/CHATGPT4mini.png
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models_logo/CHATGPTo1mini.png
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models_logo/DEEPSEEK.jpg
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models_logo/LLAMA.jpg
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models_logo/QWQ.png
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test_prediction.py
CHANGED
@@ -1,4 +1,5 @@
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from prediction import ModelPrediction
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def main():
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if __name__ == "__main__":
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main()
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-
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from prediction import ModelPrediction
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import utilities as us
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def main():
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if __name__ == "__main__":
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# main()
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us.check_and_create_dir('data/data_interface/')
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us.check_and_create_dir('data/data_results/')
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us.check_and_create_dir('data/databases/')
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utilities.py
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@@ -129,4 +129,12 @@ def extract_tables_dict(pnp_path):
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if tbl_name not in tables_dict:
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tables_dict[tbl_name] = []
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#tables_dict[tbl_name].append(row)
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return tables_dict
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if tbl_name not in tables_dict:
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tables_dict[tbl_name] = []
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#tables_dict[tbl_name].append(row)
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return tables_dict
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def check_and_create_dir(db_path):
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# Check if the folder exists, and create it if it doesn't
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if not os.path.exists(db_path):
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os.makedirs(db_path)
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print(f"Folder created: {db_path}")
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else:
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print(f"Folder already exists: {db_path}")
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utils_get_db_tables_info.py
CHANGED
@@ -2,7 +2,6 @@ import os
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import sqlite3
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import re
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-
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def utils_extract_db_schema_as_string(
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db_id, base_path, normalize=False, sql: str | None = None
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):
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import sqlite3
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import re
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def utils_extract_db_schema_as_string(
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db_id, base_path, normalize=False, sql: str | None = None
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):
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