add usage loggers

src/handler.py

@@ -130,13 +130,14 @@ def translate_text(lang, text):
     except Exception as e:
         return text
     
-def add_question_ticker():
+def add_question_ticker(query=None):
     try:
         web_counter_collection.update_one(
                 {"type": "web"},
                 {
                     "$inc": {"counter": +1},
-                    "$set": {"timestamp": datetime.now(timezone.utc)}
+                    "$set": {"timestamp": datetime.now(timezone.utc)},
+                    "$set": {"query": query}
                 },
                 upsert=True
             )

src/model.py

@@ -8,7 +8,7 @@ import os
 import re
 from prompt import PROFESSIONAL_PROMPT
 from langchain.chains import ConversationalRetrievalChain
-from langchain.memory import ConversationBufferMemory
+from langchain.memory import ConversationBufferMemory, ConversationBufferWindowMemory
 from datetime import datetime, timezone
 from handler import is_feedback_message, extract_feedback_content, OPENAI_KEY, collection, store_last_qna, add_question_ticker
 
@@ -20,14 +20,15 @@ embeddings = OpenAIEmbeddings(
 )
 
 def init_memory():
-    return ConversationBufferMemory(memory_key="chat_history", return_messages=True, output_key='answer')
+    return ConversationBufferWindowMemory(memory_key="chat_history", k=3, return_messages=True, output_key='answer')
 
 memory_store = {}
 
-def get_user_memory(user_id: str) -> ConversationBufferMemory:
+def get_user_memory(user_id: str) -> ConversationBufferWindowMemory:
     if user_id not in memory_store:
-        memory_store[user_id] = ConversationBufferMemory(
+        memory_store[user_id] = ConversationBufferWindowMemory(
             memory_key="chat_history",
+            k=3,
             return_messages=True,
             output_key="answer"
         )
@@ -53,8 +54,9 @@ llm = ChatOpenAI(
 qa_chains = {}
 
 def create_conversational_chain(user_id: None):
-    memory = get_user_memory(user_id) if user_id else init_memory()
+    memory = init_memory()
 
+    print(f"🧠 Total memory messages: {len(memory.chat_memory.messages)}")
     retriever = vector_store.as_retriever(
         search_type="similarity",
         search_kwargs={"k": 3, "score_threshold": 0.8}
@@ -78,13 +80,12 @@ def clean_answer(raw_answer):
 
 def ask(query, user_id="anonymous"):
     try:
-        if user_id != "anonymous":
-            qa = create_conversational_chain(user_id)
-        else:
-            qa = create_conversational_chain("anonymous")
-
+        qa = create_conversational_chain("anonymous")
+        add_question_ticker(query)
         result = qa({"question": query})
-        add_question_ticker()
+
+        usage = result.get('__raw', {}).get('usage', {})
+        print(f"🔍🔍🔍🔍🔍🔍 Tokens used: {usage}")
 
         if not result['source_documents']:
             return f"Sorry, no relevant information found on the question asked. Please contact immigration customer service through https://www.imigrasi.go.id/hubungi."

whatsapp_flask/Dockerfile

@@ -1,12 +0,0 @@
-FROM python:3.9-slim
-
-WORKDIR /app
-
-COPY . .
-
-RUN pip install --no-cache-dir -r requirements.txt
-
-ENV PORT=5000
-EXPOSE 5000
-
-CMD ["python", "app.py"]

whatsapp_flask/app.py

@@ -1,34 +0,0 @@
-from flask import Flask, request, jsonify
-from model import ask, check_question_feedback
-from handler import save_feedback
-
-app = Flask(__name__)
-
-@app.route("/")
-def root():
-    return "Instant Immigration Bot API is running."
-
-@app.route("/ask", methods=["POST"])
-def handle_question():
-    data = request.json
-    query = data.get("query")
-    user_id = data.get("user_id", "anonymous")
-
-    if not query:
-        return jsonify({"error": "No query provided"}), 400
-
-    result = check_question_feedback(query, user_id)
-    
-    if result["is_feedback"]:
-        last_qna = result["last_qna"]
-        if not last_qna["question"]:
-            return jsonify({"message": "Sorry, please ask a question first before providing feedback."}), 400
-
-        save_result = save_feedback(result["feedback_obj"], last_qna)
-        return jsonify({"message": save_result}), 200
-
-    answer = ask(query, user_id)
-    return jsonify({"answer": answer})
-
-if __name__ == "__main__":
-    app.run(host="0.0.0.0", port=5000)

whatsapp_flask/requirements.txt

@@ -1,11 +0,0 @@
-huggingface_hub==0.25.2
-streamlit
-streamlit-option-menu
-pymongo
-langchain
-langchain-openai
-langchain-mongodb
-python-dotenv
-openai
-datetime
-flask