add session id

app.py

@@ -17,64 +17,62 @@ with open("system_prompt.txt", "r") as f:
 client = InferenceClient(MODEL_NAME)
 api = HfApi()
 
-# ---- Chatbot function with per-user session ID ----
-def respond(message, history, session_id):
-    if session_id is None:
-        session_id = str(uuid.uuid4())  # Generate a new unique ID
+# ---- Chatbot Class with per-user session ID ----
+class SessionChatBot:
+    def __init__(self):
+        self.session_id = str(uuid.uuid4())
+        self.today_date = datetime.now().strftime("%Y-%m-%d")
+        self.local_log_path = f"chatlog_{self.today_date}_{self.session_id}.jsonl"
+        self.remote_log_path = f"sessions/{self.today_date}/{self.session_id}.jsonl"
 
-    today_date = datetime.now().strftime("%Y-%m-%d")
-    local_log_path = f"chatlog_{today_date}_{session_id}.jsonl"
-    remote_log_path = f"sessions/{today_date}/{session_id}.jsonl"
+    def append_to_session_log(self, user_message, assistant_message):
+        row = {
+            "timestamp": datetime.now().isoformat(),
+            "user": user_message,
+            "assistant": assistant_message,
+            "system_prompt": SYSTEM_PROMPT,
+            "session_id": self.session_id
+        }
+        with open(self.local_log_path, "a", encoding="utf-8") as f:
+            f.write(json.dumps(row) + "\n")
+        api.upload_file(
+            path_or_fileobj=self.local_log_path,
+            path_in_repo=self.remote_log_path,
+            repo_id=DATASET_REPO,
+            repo_type="dataset",
+            token=HF_TOKEN
+        )
 
-    # Construct conversation history
-    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
-    for user_msg, bot_msg in history:
-        if user_msg:
-            messages.append({"role": "user", "content": user_msg})
-        if bot_msg:
-            messages.append({"role": "assistant", "content": bot_msg})
-    messages.append({"role": "user", "content": message})
+    def respond(self, message, history):
+        messages = [{"role": "system", "content": SYSTEM_PROMPT}]
+        for user_msg, bot_msg in history:
+            if user_msg:
+                messages.append({"role": "user", "content": user_msg})
+            if bot_msg:
+                messages.append({"role": "assistant", "content": bot_msg})
+        messages.append({"role": "user", "content": message})
 
-    # Generate response
-    response = ""
-    for chunk in client.chat_completion(
-        messages,
-        max_tokens=512,
-        stream=True,
-        temperature=0.7,
-        top_p=0.95,
-    ):
-        token = chunk.choices[0].delta.content
-        if token:
-            response += token
-            yield response, session_id  # Yield response and session ID state
+        response = ""
+        for chunk in client.chat_completion(
+            messages,
+            max_tokens=512,
+            stream=True,
+            temperature=0.7,
+            top_p=0.95,
+        ):
+            token = chunk.choices[0].delta.content
+            if token:
+                response += token
+                yield response
 
-    # ---- Logging ----
-    row = {
-        "timestamp": datetime.now().isoformat(),
-        "user": message,
-        "assistant": response,
-        "system_prompt": SYSTEM_PROMPT,
-        "session_id": session_id
-    }
+        # Save log after full response
+        self.append_to_session_log(message, response)
 
-    with open(local_log_path, "a", encoding="utf-8") as f:
-        f.write(json.dumps(row) + "\n")
+# ---- Instantiate a new bot for each user session ----
+def create_chatbot():
+    return SessionChatBot().respond
 
-    api.upload_file(
-        path_or_fileobj=local_log_path,
-        path_in_repo=remote_log_path,
-        repo_id=DATASET_REPO,
-        repo_type="dataset",
-        token=HF_TOKEN
-    )
-
-# ---- Gradio Interface with session state ----
-demo = gr.ChatInterface(
-    fn=respond,
-    additional_inputs=[gr.State(None)],
-    title="BoundrAI",
-)
+demo = gr.ChatInterface(fn=create_chatbot(), title="BoundrAI")
 
 if __name__ == "__main__":
     demo.launch()