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app.py

@@ -4,24 +4,63 @@ import gradio as gr
 import time
 from hay.pipeline import rs_pipeline
 
-with gr.Blocks() as chat:
-    chatbot = gr.Chatbot()
-    msg = gr.Textbox()
-    clear = gr.ClearButton([msg, chatbot])
-
-    def user(user_message, history):
-        return "", history + [[user_message, None]]
-
-    def respond(message, chat_history):
-        question = str(message)
-        answer = rs_pipeline(question)
-        bot_message = answer
-        chat_history.append((message, bot_message))
-        time.sleep(2)
-        return " ", chat_history
-    
+d='data'
+# d='data2'
+
+title = """<h1 align="center">Chat Literature</h1>"""
+description = """<br><br><h3 align="center">This is a literature chat model, which can currently answer questions to regulation/two-sided markets topic in Supply chain mangement.</h3>"""
+
+def user(user_message, history):
+    return "", history + [[user_message, None]]
+
+def respond(message, chat_history):
+    question = str(message)
+    answer = rs_pipeline(question, d)
+    bot_message = answer
+    chat_history.append((message, bot_message))
+    time.sleep(2)
+    return " ", chat_history
+
+with gr.Blocks(theme=gr.themes.Soft(primary_hue="emerald", neutral_hue="slate")) as chat:
+    gr.HTML(title)
+    chatbot = gr.Chatbot().style(height=750)
+    msg = gr.Textbox(label="Send a message", placeholder="Send a message",
+                             show_label=False).style(container=False)
+    # with gr.Row():
+    #     with gr.Column():
+    #         msg = gr.Textbox(label="Send a message", placeholder="Send a message",
+    #                          show_label=False).style(container=False)
+    #     with gr.Column():
+    #         with gr.Row():
+                # submit = gr.Button("Submit")
+                # stop = gr.Button("Stop")
+                # clear = gr.Button("Clear")
+
+
     msg.submit(respond, [msg, chatbot], [msg, chatbot])
 
-# def application():
+
+    if d=='data':
+        gr.Examples([
+            ["How to reduce carbon emissions?"],
+            ["What are the main topics in these papers?"],
+            ["What are the major math models in PI."]
+        ], inputs=msg, label= "Click on any example to copy in the chatbox"
+        )
+    
+    else:
+        gr.Examples([
+            ["Who are the main users (participants) in the two-sided market?"],
+            ["What are the decisions made in the two-sided market? And who makes this decision?"],
+            ["What are the main effects in the two-sided market"]
+        ], inputs=msg, label= "Click on any example to copy in the chatbox"
+        )
+
+    gr.HTML(description)
+
+def application():
+    return None
+
+chat.queue()
 chat.launch()
 

data2/Abhishek etal2020 - ISR2021 - business models peer-to-peer rental.pdf

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data2/Adner etal2022 - MS - frenemies in platform markets.pdf

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data2/Anderson etal2014 - ISR - platform investment.pdf

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data2/Aouad etal2023 - WP - centralized vs. decentralized price control.pdf

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data2/Armstrong2006 - RJE - competition two-sided markets.pdf

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data2/Bakos_Halaburda2020 - MS - platform competition multihoming.pdf

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data2/Benjaafar etal2018 - MS - p2p product sharing.pdf

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data2/Benjaafar etal2021 - MS - sharing economy mobility.pdf

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data2/Benjaafar_Hu2020 - MSOM - sharing economy.pdf

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data2/Bernstein etal2020 - MSOM - competition demand and supply congestion effects.pdf

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data2/Cachon etal2017 - MSOM - surge pricing service platform.pdf

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data2/Chellappa_Mukherjee2020 - MS - role of information.pdf

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data2/Chen etal2019 - MSOM - online platform.pdf

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data2/Chen_Guo2022 - MISQ - advertising and retail platform openness.pdf

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data2/Choi etal2020 - EJOR - optimal pricing platform.pdf

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data2/Chou etal2012 - POM - newsvendor pricing.pdf

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data2/Cohen_Zhang2022 - POM - competition and coopetition.pdf

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data2/Cohen_Zhang2023 - WP - competition and coopetition for two-sided markets.pdf

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data2/Dou etal2016 - IJPR - service investment and pricing.pdf

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data2/Eisenmann etal2006 - HBR - two-sided markets.pdf

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data2/Farajallah etal2019 - IEP - pricing behavior.pdf

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data2/Hagiu_Spulber2013 - MS - coordination two-sided market.pdf

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data2/Hu2020 - POM - view on sharing economy.pdf

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data2/Huang etal2022 - MS - quality regulation.pdf

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data2/Katz_Shapiro1985 - AER - network externalities.pdf

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data2/Kung_Zhong2017 - TRE - pricing strategy.pdf

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data2/Lin etal2011 - JMIS - innovation and price competition.pdf

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data2/Lin etal2020 - EJOR - pricing platform competition.pdf

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data2/Liu etal2019 - EJOR - platform competition.pdf

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data2/Liu etal2019 - TRE - pricing decisions.pdf

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data2/Liu_Serfes2013 - JEMS - price discrimination two-sided market.pdf

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data2/Mantena_Saha2012 - JMIS - co-opetition.pdf

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data2/Rochet_Tirole2004 - overview two-sided markets.pdf

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data2/Rochet_Tirole2006 - RJE - two-sided market.pdf

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data2/Rysman2009 - JEP - economices of two-sided markets.pdf

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data2/Song etal2020 - ISR - spillover effect platform openness.pdf

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data2/Sun etal2020 - EJOR - Inform or Assign drivers.pdf

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data2/Wang etal2019 - IJPE - competition O2O.pdf

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data2/Wei etal2023 - EJOR - CSR.pdf

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data2/Wen_Siqin2019 - IJPE.pdf

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data2/Weyl2010 - AER - price theory platforms.pdf

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data2/Xie etal2021 - IJPE - competition multi-homing.pdf

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data2/Yuan etal2019 - MSOM - coopetition waiting-area.pdf

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data2/Zhang etal2022 - MS - competition.pdf

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data2/Zheng etal2020 - IEEE - CSR price.pdf

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data2/Zhong etal2019 - IJPE - permanent agents and competition.pdf

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main.py

@@ -1,8 +1,9 @@
 import argparse
 from hay.retriever import generate_docs
-from hay.pipeline import rg_pipeline, rs_pipeline
+from hay.pipeline import rg_pipeline, rs_pipeline, rsg_pipeline
 from app import application
 
+d = 'data'
 
 def main():
     parser = argparse.ArgumentParser()
@@ -22,6 +23,11 @@ def main():
         action='store_true'
     )
 
+    parser.add_argument(
+        '--conv', dest='conv',
+        action='store_true'
+    )
+
     parser.add_argument(
         '--gradio', dest='gradio',
         action='store_true'
@@ -33,24 +39,33 @@ def main():
         '''
         Use this argument to generate the docs and store in DOCUMENT format
         '''
-        generate_docs(overlap=10, length=100)
+        generate_docs(overlap=10, length=100, d=d)
 
     if args.rgpipeline:
         '''
         Use this argument to run the base retriever generator pipeline
         '''
         question = "How to reduce emissions?"
-        rg_pipeline(question)
+        rg_pipeline(question, d)
 
     if args.rspipeline:
         '''
         Use this argument to run the retriever summarizer pipeline
         '''
-
-        question = "How to reduce emissions in last mile supply chain?"
-        answer = rs_pipeline(question)     
+        question = "Who are the main users in the two-sided market"
+        # question = "What are the decisions made in the two-sided market? And who makes this decision? "
+        # question = "What are the main effects in the two-sided market?"
+        # question = "What are the main topics in these papers?"
+        answer = rs_pipeline(question, d)     
         print(answer)
 
+    if args.conv:
+        '''
+        Use this argument to run the pipeline using conversational agent class
+        '''
+        op = rsg_pipeline()
+        print(op)
+    
     if args.gradio:
         '''
         Use this argument to run the application