Update app.py

app.py

@@ -16,14 +16,12 @@ import pandas as pd
 
 # -------------------------------------------- For Memory - you will need to set up a dataset and HF_TOKEN ---------
 UseMemory=True
-
 if UseMemory:
    DATASET_REPO_URL="https://huggingface.co/datasets/awacke1/ChatbotMemory.csv"
    DATASET_REPO_ID="awacke1/ChatbotMemory.csv"
    DATA_FILENAME="ChatbotMemory.csv"
    DATA_FILE=os.path.join("data", DATA_FILENAME)
    HF_TOKEN=os.environ.get("HF_TOKEN")
-
 if UseMemory: 
    try:
       hf_hub_download(
@@ -38,60 +36,10 @@ if UseMemory:
       local_dir="data", clone_from=DATASET_REPO_URL, use_auth_token=HF_TOKEN
       )
 
-async def get_splits(dataset_name: str) -> Dict[str, List[Dict]]:
-    URL = f"https://datasets-server.huggingface.co/splits?dataset={dataset_name}"
-    async with httpx.AsyncClient() as session:
-        response = await session.get(URL)
-        return response.json()
-
-async def get_valid_datasets() -> Dict[str, List[str]]:
-    URL = f"https://datasets-server.huggingface.co/valid"
-    async with httpx.AsyncClient() as session:
-        response = await session.get(URL)
-        datasets = response.json()["valid"]
-        return gr.Dropdown.update(choices=datasets, value="kelm")
-        # The one to watch: https://huggingface.co/rungalileo
-        # rungalileo/medical_transcription_40
-
-async def get_first_rows(dataset: str, config: str, split: str) -> Dict[str, Dict[str, List[Dict]]]:
-    URL = f"https://datasets-server.huggingface.co/first-rows?dataset={dataset}&config={config}&split={split}"
-    async with httpx.AsyncClient() as session:
-        response = await session.get(URL)
-        print(URL)
-        gr.Markdown(URL)
-        return response.json()
-
-def get_df_from_rows(api_output):
-    return pd.DataFrame([row["row"] for row in api_output["rows"]])
-
-async def update_configs(dataset_name: str):
-    splits = await get_splits(dataset_name)
-    all_configs = sorted(set([s["config"] for s in splits["splits"]]))
-    return (gr.Dropdown.update(choices=all_configs, value=all_configs[0]),
-            splits)
-
-async def update_splits(config_name: str, state: gr.State):
-    splits_for_config = sorted(set([s["split"] for s in state["splits"] if s["config"] == config_name]))
-    dataset_name = state["splits"][0]["dataset"]
-    dataset = await update_dataset(splits_for_config[0], config_name, dataset_name)
-    return (gr.Dropdown.update(choices=splits_for_config, value=splits_for_config[0]), dataset)
-
-async def update_dataset(split_name: str, config_name: str, dataset_name: str):
-    rows = await get_first_rows(dataset_name, config_name, split_name)
-    df = get_df_from_rows(rows)
-    return df
-
-# Guido von Roissum: https://www.youtube.com/watch?v=-DVyjdw4t9I
-async def update_URL(dataset: str, config: str, split: str) -> str:
-    URL = f"https://datasets-server.huggingface.co/first-rows?dataset={dataset}&config={config}&split={split}"
-    URL = f"https://huggingface.co/datasets/{split}"
-    return (URL)
-   
-async def openurl(URL: str) -> str:
-    html = f"<a href={URL} target=_blank>{URL}</a>"
-    return (html)
-
-
+def get_df(name: str):
+    dataset = load_dataset(str, split="train")
+    return dataset
+    
 def store_message(name: str, message: str):
     if name and message:
         with open(DATA_FILE, "a") as csvfile:
@@ -99,15 +47,17 @@ def store_message(name: str, message: str):
             writer.writerow(
                 {"time": str(datetime.now()), "message": message.strip(), "name": name.strip()  }
             )
-# uncomment line below to begin saving.  If creating your own copy you will need to add a access token called "HF_TOKEN" to your profile, then create a secret for your repo with the access code naming it "HF_TOKEN"  For the CSV as well you can copy the header and first few lines to your own then update the paths above which should work to save to your own repository for datasets.    
         commit_url = repo.push_to_hub()
-    return ""
 
+        f=get_df(DATASET_REPO_ID)
+        print(f)
+    return ""
+# ----------------------------------------------- For Memory
+    
 mname = "facebook/blenderbot-400M-distill"
 model = BlenderbotForConditionalGeneration.from_pretrained(mname)
 tokenizer = BlenderbotTokenizer.from_pretrained(mname)
 
-
 def take_last_tokens(inputs, note_history, history):
     """Filter the last 128 tokens"""
     if inputs['input_ids'].shape[1] > 128:
@@ -123,12 +73,10 @@ def add_note_to_history(note, note_history):
     note_history = '</s> <s>'.join(note_history)
     return [note_history]
 
-
 title = "💬ChatBack🧠💾"
 description = """Chatbot With persistent memory dataset allowing multiagent system AI to access a shared dataset as memory pool with stored interactions. 
  Current Best SOTA Chatbot:  https://huggingface.co/facebook/blenderbot-400M-distill?text=Hey+my+name+is+ChatBack%21+Are+you+ready+to+rock%3F  """
 
-
 def chat(message, history):
     history = history or []
     if history: 
@@ -142,23 +90,18 @@ def chat(message, history):
     response = tokenizer.batch_decode(reply_ids, skip_special_tokens=True)[0]
     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]))
-    
-    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.
-    
+    history.append((list_history[-2], list_history[-1]))  
+    ret = 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
 
-
 gr.Interface(
     fn=chat,
     theme="huggingface",
     css=".footer {display:none !important}",
     inputs=["text", "state"],
-    outputs=["chatbot", "state"],
+    outputs=["chatbot", "state", "text"],
     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}) 🦃Thanks!🦃 Check out HF Datasets: https://huggingface.co/spaces/awacke1/FreddysDatasetViewer  SOTA papers code and datasets on chat are here: https://paperswithcode.com/datasets?q=chat&v=lst&o=newest"
-
     ).launch(debug=True)