TextEmbeddings / main_service.py
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We have modified the implementation to return the dataframe with
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import gradio as gr
from utils_model import ModelFactory
class GradioAppManager():
def __init__(self, model_type):
model_factory_obj = ModelFactory()
self.model = model_factory_obj.create_model(model_type)
def __retrieve_embeddings__(self, input_queries_df):
queries_list = input_queries_df.values
queries_embeddings_list = self.model.retrieve_embeddings_from_texts_list(queries_list)
return queries_embeddings_list
def build(self):
gr_input_dataframe = gr.Dataframe(headers=['queries'], datatype=['str'], row_count=2, col_count=(1, 'fixed'))
app = gr.Interface(fn=self.__retrieve_embeddings__,
inputs=[gr_input_dataframe],
outputs="dataframe")
return app
def run(self, app):
app.launch(server_name='0.0.0.0')
gradio_app_manager_obj = GradioAppManager('sentence_similarity_spanish')
app = gradio_app_manager_obj.build()
gradio_app_manager_obj.run(app)