enabled langsmith

.gitignore

@@ -1,8 +1,5 @@
 venv/*
 .env
-__pycache__/app.cpython-39.pyc
-__pycache__/app.cpython-311.pyc
-__pycache__/Chunking.cpython-39.pyc
-__pycache__/Chunking.cpython-311.pyc
+__pycache__/*
 .vscode/launch.json
 .vscode/settings.json

app.py

@@ -12,12 +12,17 @@ from langchain_community.vectorstores import Qdrant
 import chainlit as cl
 from chainlit.types import AskFileResponse
 from chainlit.cli import run_chainlit
-
+from uuid import uuid4
 import tempfile
 
 OPENAI_API_KEY = os.environ["OPENAI_API_KEY"] 
 GPT_MODEL = "gpt-4o-mini"
 
+# Used for Langsmith
+unique_id = uuid4().hex[0:8]
+os.environ["LANGCHAIN_TRACING_V2"] = "true"
+os.environ["LANGCHAIN_PROJECT"] = f"LangSmith LCEL RAG - {unique_id}"
+
 # Utility functions
 def save_file(file: AskFileResponse,file_ext:str) -> str:
     if file_ext == "application/pdf":
@@ -78,6 +83,7 @@ async def on_chat_start():
     ## Load file and split into chunks
     msg = cl.Message(content=f"Processing `{files[0].name}`...")
     await msg.send()
+    
     current_file_path = save_file(files[0], files[0].type)
     loader_splitter = TextLoaderAndSplitterWrapper(ChunkingStrategy.RECURSIVE_CHARACTER_CHAR_SPLITTER, current_file_path)
     documents = loader_splitter.load_documents() 
@@ -116,7 +122,7 @@ async def on_chat_start():
 async def main(message: cl.Message):
     chain = cl.user_session.get("chain")
     msg = cl.Message(content="")
-    response = chain.invoke({"question": message.content})
+    response = chain.invoke({"question": message.content}, {"tags" : ["Demo Run"]})
     msg.content= response["response"].content
     await msg.send()
     cl.user_session.set("chain", chain)

requirements.txt

@@ -114,4 +114,3 @@ wrapt==1.16.0
 wsproto==1.2.0
 yarl==1.9.6
 zipp==3.20.1
-