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initial commit for prediction
Browse files- app.py +1 -15
- prediction.py +45 -0
- requirements.txt +3 -0
app.py
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@@ -1,21 +1,11 @@
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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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# if os.environ.get("SPACES_ZERO_GPU") is not None:
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# import spaces
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# else:
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# class spaces:
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# @staticmethod
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# def GPU(func):
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# def wrapper(*args, **kwargs):
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# return func(*args, **kwargs)
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# return wrapper
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import sys
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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 predictor.orchestrator_predictor import OrchestratorPredictor
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import utils_get_db_tables_info
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import utilities as us
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import time
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import plotly.graph_objects as go
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import plotly.colors as pc
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# @spaces.GPU
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# def model_prediction():
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# pass
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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 sys
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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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import utils_get_db_tables_info
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import utilities as us
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import time
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import plotly.graph_objects as go
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import plotly.colors as pc
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with open('style.css', 'r') as file:
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css = file.read()
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prediction.py
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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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else:
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class spaces:
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@staticmethod
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def GPU(func):
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def wrapper(*args, **kwargs):
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return func(*args, **kwargs)
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return wrapper
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class ModelPrediction:
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def __init__(self, model_name):
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self.prediction_fun = self._model_prediction(model_name)
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def make_prediction(prompt):
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pass
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def _model_prediction(self, model_name):
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predict_fun = predict_with_api
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if 'gpt-3.5' in model_name:
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model_name = 'openai/gpt-3.5-turbo-0125'
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elif 'gpt-4o-mini' in model_name:
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model_name = 'openai/gpt-4o-mini-2024-07-18'
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elif 'o1-mini' in model_name:
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model_name = 'openai/o1-mini-2024-09-12'
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elif 'QwQ' in model_name:
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model_name = 'together_ai/Qwen/QwQ-32B'
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elif 'DeepSeek-R1-Distill-Llama-70B' in model_name:
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model_name = 'together_ai/deepseek-ai/DeepSeek-R1-Distill-Llama-70B'
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else:
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raise ValueError('Model forbidden')
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return
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def predict_with_api(prompt):
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pass
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@spaces.GPU
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def predict_with_hf(prompt):
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pass
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requirements.txt
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langchain>=0.3.9
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func-timeout>=4.3.5
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eval-type-backport>=0.2.0
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# Conditional dependency for Gradio (requires Python >=3.10)
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gradio>=5.20.1; python_version >= "3.10"
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langchain>=0.3.9
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func-timeout>=4.3.5
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eval-type-backport>=0.2.0
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openai==1.66.3
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litellm==1.63.14
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together==1.4.6
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# Conditional dependency for Gradio (requires Python >=3.10)
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gradio>=5.20.1; python_version >= "3.10"
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