Spaces:
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Sleeping
fixed imports
Browse files
api/service_manager.py
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@@ -1,6 +1,6 @@
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import uvicorn
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from
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def run():
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import uvicorn
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from web_server import app
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def run():
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api/web_server.py
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@@ -2,8 +2,6 @@ import dill
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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# from ..core.search_engine import PromptSearchEngine
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class Query(BaseModel):
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prompt: str
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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class Query(BaseModel):
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prompt: str
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core/__pycache__/search_engine.cpython-39.pyc
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Binary files a/core/__pycache__/search_engine.cpython-39.pyc and b/core/__pycache__/search_engine.cpython-39.pyc differ
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core/__pycache__/vectorizer.cpython-39.pyc
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Binary files a/core/__pycache__/vectorizer.cpython-39.pyc and b/core/__pycache__/vectorizer.cpython-39.pyc differ
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core/data/__pycache__/dataset.cpython-39.pyc
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Binary files a/core/data/__pycache__/dataset.cpython-39.pyc and b/core/data/__pycache__/dataset.cpython-39.pyc differ
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core/data/dataset.py
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from datasets import load_dataset
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from core.search_engine import PromptSearchEngine
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class PromptDataset:
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return [item['Prompt'] for item in self.dataset['test']]
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# if __name__ == "__main__":
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# dataset = PromptDataset("Gustavosta/Stable-Diffusion-Prompts")
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# dataset.load()
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# prompts = dataset.get_prompts()
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# engine = PromptSearchEngine(prompts)
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# result = engine.most_similar("dark")
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# print(result)
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from datasets import load_dataset
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class PromptDataset:
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return [item['Prompt'] for item in self.dataset['test']]
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core/initialization.py
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@@ -1,7 +1,7 @@
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import dill
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from
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def run():
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import dill
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from data.dataset import PromptDataset
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from search_engine import PromptSearchEngine
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def run():
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core/search_engine.py
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@@ -3,7 +3,7 @@ from typing import List, Sequence, Tuple
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import faiss
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import numpy as np
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from
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class PromptSearchEngine:
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import faiss
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import numpy as np
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from vectorizer import Vectorizer
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class PromptSearchEngine:
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