Upload 3 files

app.py

@@ -70,7 +70,7 @@ with st.sidebar:
     st.subheader("Select Options:")
 
 with st.sidebar:
-    num_results = int(st.number_input("Number of Results to query", 1, 15, value=5))
+    num_results = int(st.number_input("Number of Results to query", 1, 15, value=6))
 
 
 # Choose encoder model
@@ -108,7 +108,7 @@ elif encoder_model == "SGPT":
 
 
 with st.sidebar:
-    window = int(st.number_input("Sentence Window Size", 0, 10, value=3))
+    window = int(st.number_input("Sentence Window Size", 0, 10, value=1))
 
 with st.sidebar:
     threshold = float(

utils.py

@@ -115,19 +115,16 @@ def text_lookup(data, sentence_ids):
 
 
 def generate_prompt(query_text, context_list):
-    context = " \n\n".join(context_list)
-    prompt = f"""Answer the question as truthfully as possible using the provided text. Try to include as many key details as possible and format the answer in points.
-
-    Context: 
-    {context}
-    
-    Q: {query_text} 
-    A:"""
+    context = " ".join(context_list)
+    prompt = f"""Answer the question as accurately as possible using the provided context. Try to include as many key details as possible.
+Context: {context}
+Question: {query_text}
+Answer:"""
     return prompt
 
 
 def generate_prompt_2(query_text, context_list):
-    context = " \n\n".join(context_list)
+    context = " ".join(context_list)
     prompt = f"""
     Context information is below: 
     ---------------------
@@ -144,9 +141,9 @@ def gpt_model(prompt):
         model="text-davinci-003",
         prompt=prompt,
         temperature=0.1,
-        max_tokens=512,
+        max_tokens=1024,
         top_p=1.0,
-        frequency_penalty=0.0,
+        frequency_penalty=0.5,
         presence_penalty=1,
     )
     return response.choices[0].text