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| from haystack.nodes import BM25Retriever, FARMReader | |
| from haystack.document_stores import ElasticsearchDocumentStore | |
| from haystack.pipelines import ExtractiveQAPipeline | |
| from abc import ABC, abstractmethod | |
| import certifi | |
| import gradio as gr | |
| ca_certs=certifi.where() | |
| class Config(): | |
| es_host = "ask2democracy.es.us-central1.gcp.cloud.es.io" | |
| es_user = "elastic" | |
| es_password = "siKAHmmk2flwEaKNqQVZwp49" | |
| proposals_index = "petrolfo" | |
| #reader_model_name_or_path = "deepset/roberta-base-squad2" | |
| reader_model_name_or_path = "deepset/xlm-roberta-large-squad2" | |
| use_gpu = True | |
| class DocumentQueries(ABC): | |
| def search_by_query(self, query : str, retriever_top_k: int, reader_top_k: int, es_index: str): | |
| pass | |
| class ExtractiveProposalQueries(DocumentQueries): | |
| def __init__(self, es_host: str, es_index: str, es_user, es_password, reader_name_or_path: str, use_gpu = True) -> None: | |
| reader = FARMReader(model_name_or_path = reader_name_or_path, use_gpu = use_gpu, num_processes=1) | |
| self._initialize_pipeline(es_host, es_index, es_user, es_password, reader = reader) | |
| def _initialize_pipeline(self, es_host, es_index, es_user, es_password, reader = None): | |
| if reader is not None: | |
| self.reader = reader | |
| self.es_host = es_host | |
| self.es_user = es_user | |
| self.es_password = es_password | |
| self.document_store = ElasticsearchDocumentStore(host = es_host, username=es_user, password=es_password, index = es_index, port = 443, scheme='https', verify_certs=True, ca_certs=ca_certs) | |
| self.retriever = BM25Retriever(document_store = self.document_store) | |
| self.pipe = ExtractiveQAPipeline(self.reader, self.retriever) | |
| def search_by_query(self, query : str, retriever_top_k: int, reader_top_k: int, es_index: str = None) : | |
| if es_index is not None: | |
| self._initialize_pipeline(self.es_host, es_index, self.es_user, self.es_password) | |
| params = {"Retriever": {"top_k": retriever_top_k}, "Reader": {"top_k": reader_top_k}} | |
| prediction = self.pipe.run( query = query, params = params) | |
| return prediction["answers"] | |
| query = ExtractiveProposalQueries(es_host = Config.es_host, es_index = Config.proposals_index, | |
| es_user = Config.es_user, es_password = Config.es_password, | |
| reader_name_or_path = Config.reader_model_name_or_path, | |
| use_gpu = Config.use_gpu) | |
| def update(query): | |
| return f"{query}", f"{query}", f"{query}", f"{query}" | |
| def search(question): | |
| p1_result = query.search_by_query(query = question, retriever_top_k = 5, reader_top_k = 1, es_index = "petro") | |
| p2_result = query.search_by_query(query = question, retriever_top_k = 5, reader_top_k = 1, es_index = "rodolfo") | |
| return [p1_result[0].answer, | |
| p1_result[0].context, | |
| p2_result[0].answer, | |
| p2_result[0].context] | |
| demo = gr.Blocks() | |
| def update(query): | |
| return f"{query}", f"{query}", f"{query}", f"{query}" | |
| def search(question): | |
| p1_result = query.search_by_query(query = question, retriever_top_k = 5, reader_top_k = 1, es_index = "petro") | |
| p2_result = query.search_by_query(query = question, retriever_top_k = 5, reader_top_k = 1, es_index = "rodolfo") | |
| return [p1_result[0].answer, | |
| p1_result[0].context, | |
| p2_result[0].answer, | |
| p2_result[0].context] | |
| demo = gr.Blocks() | |
| query = ExtractiveProposalQueries(es_host = Config.es_host, es_index = Config.proposals_index, | |
| es_user = Config.es_user, es_password = Config.es_password, | |
| reader_name_or_path = Config.reader_model_name_or_path, | |
| use_gpu = Config.use_gpu) | |
| def update(query): | |
| return f"{query}", f"{query}", f"{query}", f"{query}" | |
| def search(question): | |
| p1_result = query.search_by_query(query = question, retriever_top_k = 5, reader_top_k = 3, es_index = "petro") | |
| p2_result = query.search_by_query(query = question, retriever_top_k = 5, reader_top_k = 3, es_index = "rodolfo") | |
| return [p1_result[0].answer, | |
| p1_result[0].context, | |
| p2_result[0].answer, | |
| p2_result[0].context] | |
| examples = [ | |
| ['¿Que va a hacer con la deuda del ICETEX?'], | |
| ['¿Como impulsará la creación de startus o emprendimientos creados por jóvenes?'], | |
| ['¿Propuestas de para garantizar la protección de lideres sociales y ambientales?'], | |
| ['¿Cómo promoverá el mercado laboral de los jóvenes?'], | |
| ['¿Cuales medidas tomará para mejorar la remuneración de los jóvenes ?'], | |
| ['¿Cuales aciones propone para aumentar la capacidad del sistema de salud en materia de prevención y atención de enfermedades?'], | |
| ['¿apoyará el proceso de paz con el ELN?'] | |
| ] | |
| description = """ | |
| Ask2Democracy🇨🇴 - Elecciones precidenciales Colombia 2022 | |
| El debate ha sido un ausente en la segunda vuelta por la presidencia de Colombia del 2022. | |
| para ayudar con el conocimiento de las propuestas de los candidatos construí este espacio, | |
| puede hacerle preguntas a la propuestas de los candidatos. | |
| Un pequeño aporte a un fin de semana determinante en la democracia Colombiana [Abajo algunos ejemplos]👇 | |
| <p> | |
| <br>Este espacio hace parte de un proyecto open source que busca ayudar con el conocimiento de la historia Colombiana. <a href= "https://github.com/jorge-henao/ask_to_democracy">repo en github con FastAPI</a></br> | |
| </p> | |
| <p> | |
| Por: Jorge Henao 🇨🇴 <a href="https://twitter.com/jhenaotw" target='_blank'>Twitter</a> <a href="https://www.linkedin.com/in/henaojorge" target='_blank'/>LinkedIn</a> | |
| </p> | |
| """ | |
| iface = gr.Interface(fn=search, | |
| title= "Ask2Democracy🇨🇴", | |
| description = description, | |
| inputs=[ | |
| gr.inputs.Textbox(lines=2, placeholder="hazle una pregunta a los candidatos", label='que va a hacer con la deuda del ICETEX?') | |
| ], | |
| outputs=[ | |
| gr.outputs.Textbox(label="Respuesta de Petro"), | |
| gr.outputs.Textbox(label="Contexto de la propuesta"), | |
| gr.outputs.Textbox(label="Respuesta de Rodolfo Hernandez"), | |
| gr.outputs.Textbox(label="Contexto de la propuesta") | |
| ], | |
| examples = examples, | |
| theme = 'peach' | |
| ) | |
| iface.launch(enable_queue=True) |