adding logging

.chainlit/config.toml

@@ -67,7 +67,7 @@ edit_message = true
 # Name of the assistant.
 name = "Ronald AI"
 
-logo = "/public/logo_1.png"
+logo = "/public/logo_dark.png"
 
 default_theme = "dark"
 

.gitignore

@@ -1 +1,3 @@
-.idea
+.idea
+
+.env

app.py

@@ -3,7 +3,10 @@ from llama_index.core import VectorStoreIndex, SimpleDirectoryReader, StorageCon
 from llama_index.embeddings.huggingface import HuggingFaceEmbedding
 from llama_index.llms.openrouter import OpenRouter
 import os
+from loguru import logger
 
+logger.add("logs/ronald_ai.log", rotation="1 MB", retention="7 days", level="INFO")
+logger.info("Starting Ronald AI App")
 
 @cl.set_starters
 async def set_starters():
@@ -16,7 +19,7 @@ async def set_starters():
 
         cl.Starter(
             label="Project highlights",
-            message="List Ronald’s most impactful projects in bullet points. For each, include the project name, tools used, the problem it addressed, and the outcome. Format the response in markdown.",
+            message="List Ronald’s most impactful projects in bullet points. For each, include the project name, tools used, the problem it addressed, and the outcome. Use clear paragraphs or bullet points for readability.",
             icon="https://cdn-icons-png.flaticon.com/512/979/979585.png",
         ),
 
@@ -49,6 +52,11 @@ async def set_starters():
 
 @cl.on_chat_start
 async def start():
+    api_key = os.getenv("API_KEY")
+    if not api_key:
+        logger.warning("API_KEY not found in environment variables.")
+    else:
+        logger.info("API_KEY loaded.")
     cl.user_session.set("llm", OpenRouter(
         model="opengvlab/internvl3-14b:free",
         temperature=0.1,
@@ -60,6 +68,7 @@ async def start():
         model_name="BAAI/bge-small-en-v1.5"
     )
     Settings.context_window = 4096
+    logger.info("LLM and embedding models initialized.")
 
     try:
         storage_context = StorageContext.from_defaults(persist_dir="storage")
@@ -99,12 +108,24 @@ async def start():
 
 @cl.on_message
 async def main(message: cl.Message):
-    query_engine = cl.user_session.get("query_engine")
+    try:
+        query_engine = cl.user_session.get("query_engine")
+        if query_engine is None:
+            raise ValueError("Query engine not found in session.")
+
+        msg = cl.Message(content="", author="Assistant")
+        logger.info(f"Received message: {message.content}")
+
+        res = await cl.make_async(query_engine.query)(message.content)
+        logger.info("LLM response received.")
 
-    msg = cl.Message(content="", author="Assistant")
-    res = await cl.make_async(query_engine.query)(message.content)
+        for token in res.response_gen:
+            await msg.stream_token(token)
 
-    for token in res.response_gen:
-        await msg.stream_token(token)
+        await msg.send()
+        logger.info("Message sent back to client.")
 
-    await msg.send()
+    except Exception as e:
+        error_msg = f"An error occurred: {str(e)}"
+        await cl.Message(content=error_msg, author="Assistant").send()
+        logger.error(error_msg)

logs/ronald_ai.log

@@ -0,0 +1,13 @@
+2025-06-12 12:30:47.741 | INFO     | app.py:<module>:9 - Starting Ronald AI App
+2025-06-12 12:30:49.701 | INFO     | app.py:start:59 - API_KEY loaded.
+2025-06-12 12:30:52.185 | INFO     | app.py:start:71 - LLM and embedding models initialized.
+2025-06-12 12:30:52.214 | INFO     | app.py:start:59 - API_KEY loaded.
+2025-06-12 12:30:53.003 | INFO     | app.py:start:71 - LLM and embedding models initialized.
+2025-06-12 12:30:53.062 | INFO     | app.py:start:59 - API_KEY loaded.
+2025-06-12 12:30:53.842 | INFO     | app.py:start:71 - LLM and embedding models initialized.
+2025-06-12 12:31:00.857 | INFO     | app.py:main:117 - Received message: List Ronald’s most impactful projects in bullet points. For each, include the project name, tools used, the problem it addressed, and the outcome. Use clear paragraphs or bullet points for readability.
+2025-06-12 12:31:01.419 | INFO     | app.py:main:120 - LLM response received.
+2025-06-12 12:31:03.741 | INFO     | app.py:main:126 - Message sent back to client.
+2025-06-12 12:31:36.349 | INFO     | app.py:main:117 - Received message: provide more
+2025-06-12 12:31:36.424 | INFO     | app.py:main:120 - LLM response received.
+2025-06-12 12:31:40.804 | INFO     | app.py:main:126 - Message sent back to client.

requirements.txt

@@ -1,4 +1,5 @@
 chainlit>=0.7.700
 llama-index-core~=0.12.41
 llama-index-embeddings-huggingface~=0.5.4
-llama-index-llms-openrouter~=0.3.2
+llama-index-llms-openrouter~=0.3.2
+loguru