another reset

app.py

@@ -1,33 +1,17 @@
 import gradio as gr
 from huggingface_hub import InferenceClient
-from datetime import datetime
-import os
-import uuid
 
-# ---- System Prompt ----
 with open("system_prompt.txt", "r") as f:
     SYSTEM_PROMPT = f.read()
 
 MODEL_NAME = "HuggingFaceH4/zephyr-7b-beta"
 
-DATASET_REPO = "frimelle/companion-chat-logs"
-HF_TOKEN = os.environ.get("HF_TOKEN")  # set in Space secrets
-
+"""
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
 client = InferenceClient(MODEL_NAME)
 
-# ---- Setup logging ----
-LOG_DIR = "chat_logs"
-os.makedirs(LOG_DIR, exist_ok=True)
-session_id = str(uuid.uuid4())
-
-def log_chat(session_id, user_msg, bot_msg):
-    timestamp = datetime.now().strftime("%Y-%m-%d %H:%M:%S")
-    log_path = os.path.join(LOG_DIR, f"{session_id}.txt")
-    with open(log_path, "a", encoding="utf-8") as f:
-        f.write(f"[{timestamp}] User: {user_msg}\n")
-        f.write(f"[{timestamp}] Bot: {bot_msg}\n\n")
 
-# ---- Respond Function with Logging ----
 def respond(
     message,
     history: list[tuple[str, str]],
@@ -48,32 +32,38 @@ def respond(
 
     response = ""
 
-    for chunk in client.chat_completion(
+    for message in client.chat_completion(
         messages,
         max_tokens=max_tokens,
         stream=True,
         temperature=temperature,
         top_p=top_p,
     ):
-        token = chunk.choices[0].delta.content
-        if token:
-            response += token
-            yield response
+        token = message.choices[0].delta.content
 
-    # Save full message after stream ends
-    log_chat(session_id, message, response)
+        response += token
+        yield response
 
-# ---- Gradio Interface ----
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
 demo = gr.ChatInterface(
     respond,
-    #additional_inputs=[
-    #    gr.Textbox(value=SYSTEM_PROMPT, label="System message"),
-    #    gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-    #    gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-    #    gr.Slider(minimum=0.1, maximum=1.0, value=0.95, step=0.05, label="Top-p (nucleus sampling)"),
-    #],
-    title="BoundrAI"
+    additional_inputs=[
+        gr.Textbox(value=SYSTEM_PROMPT, label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
 )
 
+
 if __name__ == "__main__":
     demo.launch()