gradio app updated

app.py

@@ -1,5 +1,73 @@
 import gradio as gr
 
+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):
+    
+    @abstractmethod
+    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 = False) -> 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"]
+    
+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]
+
+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}"