add additional examples

app.py

@@ -84,8 +84,10 @@ def infer(
 
     # Clear model state for generative mode
     model.resetState()
-    if (mode == "Q/A"):
-        prompt = f"Ask Expert\n\nQuestion:\n{prompt}\n\nExpert Full Answer:\n"
+    if (mode == "Q/A - AE"):
+        prompt = f"\nAsk Expert\n\nQuestion:\n{prompt}\n\nExpert Full Answer:\n"
+    elif (mode == "Q/A - EQHA"):
+        prompt = f"\nExpert Questions & Helpful Answers\nAsk Research Experts\nQuestion:\n{prompt}\n\nFull Answer:\n"
 
     print(f"PROMPT ({datetime.now()}):\n-------\n{prompt}")
     print(f"OUTPUT ({datetime.now()}):\n-------\n")
@@ -210,13 +212,19 @@ def chat(
 examples = [
     [
         # Question Answering
-        '''What is the capital of Germany?''', "Q/A", 25, 0.2, 0.8, 0.0, "<|endoftext|>,\\n"],
+        '''What are some good plans to collect all mosquitoes''', "Q/A - EQHA", 256, 1.0, 0.85, -999, "<|endoftext|>"],
     [
         # Question Answering
-        '''Are humans good or bad?''', "Q/A", 150, 0.8, 0.8, -1.0, "<|endoftext|>"],
+        '''What are some good plans to collect all mosquitoes''', "Q/A - AE", 256, 1.0, 0.85, -999, "<|endoftext|>"],
     [
         # Question Answering
-        '''What is the purpose of Vitamin A?''', "Q/A", 60, 0.2, 0.8, -0.5, "<|endoftext|>"],
+        '''What is the capital of Germany?''', "Q/A - AE", 25, 0.2, 0.8, 0, "<|endoftext|>,\\n"],
+    [
+        # Question Answering
+        '''Are humans good or bad?''', "Q/A - AE", 150, 0.8, 0.8, -1, "<|endoftext|>"],
+    [
+        # Question Answering
+        '''What is the purpose of Vitamin A?''', "Q/A - AE", 60, 0.2, 0.8, 0, "<|endoftext|>"],
     [
         # Chatbot
         '''This is a conversation between two AI large language models named Alex and Fritz. They are exploring each other's capabilities, and trying to ask interesting questions of one another to explore the limits of each others AI.
@@ -224,7 +232,7 @@ examples = [
 Conversation:
 Alex: Good morning, Fritz, what type of LLM are you based upon?
 Fritz: Morning Alex, I am an RNN with transformer level performance. My language model is 100% attention free.
-Alex:''', "generative", 220, 0.9, 0.9, -3.0, "<|endoftext|>,\\n\\n"],
+Alex:''', "generative", 220, 0.9, 0.9, -3, "<|endoftext|>,\\n\\n"],
     [
         # Generate List
         '''Task given:
@@ -236,7 +244,7 @@ Best Full Response:
     [
         # Natural Language Interface
         '''Here is a short story (in the style of Tolkien) in which Aiden attacks a robot with a sword:
-        ''', "generative", 140, 0.85, 0.8, -3.5, "<|endoftext|>"]
+        ''', "generative", 140, 0.85, 0.8, -3, "<|endoftext|>"]
 ]
 
 
@@ -246,12 +254,12 @@ iface = gr.Interface(
     allow_flagging="never",
     inputs=[
         gr.Textbox(lines=20, label="Prompt"),  # prompt
-        gr.Radio(["generative", "Q/A"],
+        gr.Radio(["generative", "Q/A - AE", "Q/A - EQHA"],
                  value="generative", label="Choose Mode"),
         gr.Slider(1, 256, value=40),  # max_tokens
         gr.Slider(0.0, 1.0, value=0.8),  # temperature
         gr.Slider(0.0, 1.0, value=0.85),  # top_p
-        gr.Slider(-99, 0.0, value=0.0, step=0.5, label="Reduce End of Text Probability"), # end_adj
+        gr.Slider(-999, 0.0, value=0.0, step=1, label="Reduce End of Text Probability"), # end_adj
         gr.Textbox(lines=1, value="<|endoftext|>")  # stop
     ],
     outputs=gr.Textbox(label="Generated Output", lines=25),