Update app.py

app.py

@@ -17,9 +17,11 @@ import fastapi
 from typing import List, Dict
 import httpx
 import pandas as pd
+import datasets as ds
 
 # -------------------------------------------- For Memory - you will need to set up a dataset and HF_TOKEN ---------
-UseMemory=False
+#UseMemory=False
+UseMemory=True
 
 
 DATASET_REPO_URL="https://huggingface.co/datasets/awacke1/ChatbotMemory.csv"
@@ -54,6 +56,7 @@ def store_message(name: str, message: str):
             writer.writerow(
                 {"time": str(datetime.now()), "message": message.strip(), "name": name.strip()  }
             )
+        #repo.git_pull(rebase=True)
         commit_url = repo.push_to_hub()
 
         # test api retrieval of any dataset that is saved, then return it...
@@ -103,21 +106,50 @@ def chat(message, history):
     history_useful = add_note_to_history(response, history_useful)
     list_history = history_useful[0].split('</s> <s>')
     history.append((list_history[-2], list_history[-1]))  
-    #ret = 
+    
+    df=pd.DataFrame()
     
     if UseMemory: 
         store_message(message, response) # Save to dataset  -- uncomment with code above, create a dataset to store and add your HF_TOKEN from profile to this repo to use.
-    return history, history
+        df = ds.load_dataset("awacke1/ChatbotMemory.csv")
+        df = df["train"].to_pandas()
+        df = df.sort_values(by="time",ascending=False)
+        #df.sort_index(axis=1, ascending=False)
+    return history, df
+    #return df
+    #return history,  df
+
+    
+#gr.Interface(
+#    fn=chat,
+#    theme="huggingface",
+#    css=".footer {display:none !important}",
+#    inputs=["text", "state"],
+#    #outputs=["chatbot", "state", "text"],
+#    outputs=["chatbot", "state", "dataframe"],
+#    title=title,
+#    allow_flagging="never",
+#    description=f"Gradio chatbot backed by memory in a dataset repository.",
+#    article=f"The memory dataset for saves is [{DATASET_REPO_URL}]({DATASET_REPO_URL}) And here: https://huggingface.co/spaces/awacke1/DatasetAnalyzer  Code and datasets on chat are here  hf  tk: https://paperswithcode.com/datasets?q=chat&v=lst&o=newest"
+#    ).launch(debug=True)
+
+
+
+with gr.Blocks() as demo:
+  gr.Markdown("<h1><center>🍰Gradio chatbot backed by memory in a dataset repository.🎨</center></h1>")
+  #gr.Markdown("The memory dataset for saves is [{DATASET_REPO_URL}]({DATASET_REPO_URL}) And here: https://huggingface.co/spaces/awacke1/DatasetAnalyzer  Code and datasets on chat are here  hf  tk: https://paperswithcode.com/datasets?q=chat&v=lst&o=newest")
+  
+  with gr.Row():
+    t1 = gr.Textbox(lines=1, default="", label="Chat Text:")
+    b1 = gr.Button("Send Message")
     
-gr.Interface(
-    fn=chat,
-    theme="huggingface",
-    css=".footer {display:none !important}",
-    inputs=["text", "state"],
-    #outputs=["chatbot", "state", "text"],
-    outputs=["chatbot", "state"],
-    title=title,
-    allow_flagging="never",
-    description=f"Gradio chatbot backed by memory in a dataset repository.",
-    article=f"The memory dataset for saves is [{DATASET_REPO_URL}]({DATASET_REPO_URL}) And here: https://huggingface.co/spaces/awacke1/DatasetAnalyzer  Code and datasets on chat are here  hf  tk: https://paperswithcode.com/datasets?q=chat&v=lst&o=newest"
-    ).launch(debug=True)
+  with gr.Row(): # inputs and buttons
+    s1 = gr.State([])
+    s2 = gr.Markdown()
+  with gr.Row():
+    df1 = gr.Dataframe(wrap=True, max_rows=1000, overflow_row_behaviour= "paginate")
+    #chatoutput = gr.Dataframe(wrap=True, max_rows=1000, overflow_row_behaviour= "paginate", datatype = ["markdown", "markdown"], headers=['url', 'prompt'])
+    
+  b1.click(fn=chat, inputs=[t1, s1], outputs=[s1, df1]) 
+
+demo.launch(debug=True, show_error=True)