Update app.py

app.py

@@ -5,8 +5,7 @@ import torch
 import re
 import random
 
-
-
+### FEEDBACKS UPDATE IN PERSISTENT MEMORY
 
 from pathlib import Path
 from huggingface_hub import CommitScheduler
@@ -18,7 +17,7 @@ JSON_DATASET_DIR.mkdir(parents=True, exist_ok=True)
 JSON_DATASET_PATH = JSON_DATASET_DIR / f"feedbacks.json"
 
 scheduler = CommitScheduler(
-    repo_id="bmi-labmedinfo/feedbacks_test",
+    repo_id="bmi-labmedinfo/feedbacks",
     repo_type="dataset",
     folder_path=JSON_DATASET_DIR,
     path_in_repo="data",
@@ -31,8 +30,7 @@ def save_json(last_state: dict, pos_or_neg: str) -> None:
             json.dump(last_state, f)
             f.write("\n")
 
-
-
+### /FEEDBACKS
 
 # Initialize the model
 model = AutoModelForCausalLM.from_pretrained("Detsutut/Igea-1B-instruct-v0.3-test4epochs-GGUF", model_file="unsloth.Q4_K_M.gguf", model_type="mistral", hf=True)
@@ -93,14 +91,12 @@ def generate_text(input_text, max_new_tokens=512, temperature=1, system_prompt="
     return f"<span>{input_text}</span><b style='color: {generated_text_color};'>{generated_text}</b>", {"input_prompt":prompt, "generated_text_raw":output[0]['generated_text'], "generated_text_displayed":generated_text}
 
 def positive_feedback(last_generated_text):
-    print("positive")
-    print(last_generated_text)
     save_json(last_generated_text,"positive")
+    gr.Info("Feedback collected. Thanks!")
 
 def negative_feedback(last_generated_text):
-    print("negative")
-    print(last_generated_text)
     save_json(last_generated_text,"negative")
+    gr.Info("Feedback collected. Thanks!")
     
 
 # Create the Gradio interface
@@ -125,10 +121,10 @@ with gr.Blocks(css="#outbox { border-radius: 8px !important; border: 1px solid #
 
     btn = gr.Button("Generate")
     btn.click(generate_text, [input_text, max_new_tokens, temperature, system_prompt], outputs=[output, last_generated_text])
-
-    btn_p = gr.Button("👍")
+    with gr.Row():
+        btn_p = gr.Button("👍")
+        btn_n = gr.Button("👎")
     btn_p.click(positive_feedback, inputs=[last_generated_text], outputs=None)
-    btn_n = gr.Button("👎")
     btn_n.click(negative_feedback, inputs=[last_generated_text], outputs=None)
 
 # Launch the interface