Updates to give context as the top 2 relevant document chunks

app.py

@@ -57,7 +57,7 @@ def load_model():
     #     "MBZUAI/LaMini-Flan-T5-783M"
     
     tokenizer = AutoTokenizer.from_pretrained("Xenova/LaMini-Flan-T5-783M")
-    model = ORTModelForSeq2SeqLM.from_pretrained("Xenova/LaMini-Flan-T5-783M", subfolder = "onnx", decoder_file_name="decoder_with_past_model.onnx")
+    model = ORTModelForSeq2SeqLM.from_pretrained("Xenova/LaMini-Flan-T5-783M", subfolder = "onnx")
 
     return tokenizer, model
 
@@ -100,7 +100,9 @@ if user_input:
     else:
         tokenizer, model = load_model()
         docs = db.similarity_search(user_input)
-        output = wrap_text_preserve_newlines(str(docs[0]))
+        output1 = wrap_text_preserve_newlines(str(docs[0]))
+        output2 = wrap_text_preserve_newlines(str(docs[1]))
+        
         if tag in ["welcome", "thanks", "exit"]:
             input = user_input    
         elif tag in ["BibekBOT-introduction"]:
@@ -114,7 +116,7 @@ if user_input:
             end_prompt = "\nPlease make meaningful sentence and try to be descriptive as possible responding with many sentences and ending with proper punctuations. If you think the content doesn't contain good answer to the question, give some polite respones telling them that you do not have specific response to the query and apologize and refer them to contact Bibek directly.\n"  # NoQA"
             short_response_template = "\nIf your response is very short like 1 or 2 sentence, add a followup sentence like 'Let me know if there's anything else I can help you with. or If there's anything else I can assist with, please don't hesitate to ask. I mean something similar in polite way."  # NoQA
 
-            input = task_description_prompt + output + prompt_template + user_input + end_prompt
+            input = task_description_prompt + output1+ "\n" +output2 + prompt_template + user_input + end_prompt
             
         input_ids = tokenizer(
             input,