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app.py

@@ -63,17 +63,17 @@ def clear_file_fn():
     return None, None
 
 
-def retrieve_document_fn(question, document_data, document_index):
+def retrieve_document_fn(question, instruct, document_data, document_index):
     num_retrieval_doc = 3
     if document_index is None or document_data is None:
         gr.Warning("Please upload documents first!")
         return [None for i in range(num_retrieval_doc)]
     
-    question_embedding = model.encode([question])
+    question_embedding = model.encode([instruct + question])
     batch_scores, batch_inxs = document_index.search(question_embedding, k=num_retrieval_doc)
     
     answers = [document_data[i]["text"] for i in batch_inxs[0][:num_retrieval_doc]]
-    return tuple(answers)
+    return answers[0], answers[1], answers[2], document_data, document_index
 
 
 def main(args):
@@ -98,8 +98,8 @@ def main(args):
         retrieval_interface = gr.Interface(
             fn=retrieve_document_fn,
             inputs=["text"],
-            outputs=["text", "text",  "text"],
-            additional_inputs=[document_data, document_index],
+            outputs=["text", "text",  "text", gr.State(), gr.State()],
+            additional_inputs=[gr.Textbox("Instruct: Given a query, retrieve documents that answer the query. \n Query: ", label="Instruct of Query"), document_data, document_index],
             concurrency_limit=1,
         )