Feat: custom url and with fast api
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18
FindinDB.py
18
FindinDB.py
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@ -21,6 +21,7 @@ from langchain.embeddings import HuggingFaceEmbeddings
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import pandas as pd
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import pandas as pd
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import sqlite3
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import sqlite3
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from sentence_transformers import SentenceTransformer
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from sentence_transformers import SentenceTransformer
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from fastapi import FastAPI
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#from cleantext import clean
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#from cleantext import clean
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import re
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import re
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model_name = 'hiiamsid/sentence_similarity_spanish_es'
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model_name = 'hiiamsid/sentence_similarity_spanish_es'
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@ -32,6 +33,13 @@ hf = HuggingFaceEmbeddings(
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encode_kwargs=encode_kwargs
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encode_kwargs=encode_kwargs
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)
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)
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CUSTOM_PATH = "/angela"
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app = FastAPI()
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@app.get("/")
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def read_main():
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return {"message": "This is your main app"}
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def loadModels():
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def loadModels():
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#model = GPT4All("orca-mini-3b.ggmlv3.q4_0.bin")
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#model = GPT4All("orca-mini-3b.ggmlv3.q4_0.bin")
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@ -124,7 +132,13 @@ with gr.Blocks() as demo:
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# metrica3=gr.Textbox(label="metrica3")
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# metrica3=gr.Textbox(label="metrica3")
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Enviar_btn = gr.Button("Responder")
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Enviar_btn = gr.Button("Responder")
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Enviar_btn.click(fn=QARequest, inputs=[Pregunta,filtred], outputs=[Respuesta,id], api_name="Angela") #
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Enviar_btn.click(fn=QARequest, inputs=[Pregunta,filtred], outputs=[Respuesta,id], api_name="api_angela") #
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demo.launch() #
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#demo.launch(root_path="angela") #
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gradio_app = gr.routes.App.create_app(demo)
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app.mount(CUSTOM_PATH, gradio_app)
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#app = demo.mount_gradio_app(app, io, path=CUSTOM_PATH)
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