Update main.py

main.py

@@ -15,13 +15,30 @@ from langchain.agents import AgentExecutor
 from langchain.agents.agent_types import AgentType
 from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent, create_csv_agent
 
-from pandasai.llm import HuggingFaceTextGen
+from pandasai.llm import OpenAI
 from pandasai import SmartDataframe
 import chainlit as cl
 from chainlit.input_widget import TextInput, Select, Switch, Slider
 
 from deep_translator import GoogleTranslator
 
+@cl.password_auth_callback
+def auth_callback(username: str, password: str):
+    auth = json.loads(os.environ['CHAINLIT_AUTH_LOGIN'])
+    ident = next(d['ident'] for d in auth if d['ident'] == username)
+    pwd = next(d['pwd'] for d in auth if d['ident'] == username)
+    resultLogAdmin = bcrypt.checkpw(username.encode('utf-8'), bcrypt.hashpw(ident.encode('utf-8'), bcrypt.gensalt())) 
+    resultPwdAdmin = bcrypt.checkpw(password.encode('utf-8'), bcrypt.hashpw(pwd.encode('utf-8'), bcrypt.gensalt())) 
+    resultRole = next(d['role'] for d in auth if d['ident'] == username)
+    if resultLogAdmin and resultPwdAdmin and resultRole == "admindatapcc":
+        return cl.User(
+            identifier=ident + " : 🧑‍💼 Admin Datapcc", metadata={"role": "admin", "provider": "credentials"}
+        )
+    elif resultLogAdmin and resultPwdAdmin and resultRole == "userdatapcc":
+        return cl.User(
+            identifier=ident + " : 🧑‍🎓 User Datapcc", metadata={"role": "user", "provider": "credentials"}
+        )
+        
 @cl.step(type="tool")
 async def LLMistral():
     os.environ['HUGGINGFACEHUB_API_TOKEN'] = os.environ['HUGGINGFACEHUB_API_TOKEN']
@@ -33,9 +50,15 @@ async def LLMistral():
 
 @cl.step(type="tool")
 async def LLM():
-    os.environ['ANTHROPIC_API_KEY'] = os.environ['ANTHROPIC_API_KEY']
-    llm = AnthropicLLM(model='claude-3-haiku-20240307',temperature=0)
+    os.environ['OPENAI_API_KEY'] = os.environ['OPENAI_API_KEY']
+    llm = OpenAI(model="gpt-4o-2024-05-13")
     return llm
+
+@cl.step(type="tool")
+async def File():
+    llm = await LLM()
+    df = SmartDataframe("./public/ExpeCFA_LP_CAA.csv", config={"llm": llm})
+    return df
     
 @cl.set_chat_profiles
 async def chat_profile():
@@ -56,9 +79,8 @@ async def set_starters():
 @cl.on_message
 async def on_message(message: cl.Message):
     await cl.Message(f"> SURVEYIA").send()
-    model = await LLMistral()
     
-    df = SmartDataframe("./public/ExpeCFA_LP_CAA.csv", config={"llm": model})
+    df = await File()
     msg = cl.Message(content="")
     res = df.chat(message.content)
     #cb = cl.AsyncLangchainCallbackHandler()