updated

.gitignore

@@ -0,0 +1,5 @@
+.venv
+__pycache__
+.env
+chatbot.db
+.gradio

app.py

@@ -13,7 +13,6 @@ from pinecone import ServerlessSpec
 from langchain.schema import Document
 from dotenv import load_dotenv
 from prompt import system_prompt, retriever_prompt
-from test import llm
 import os
 import logging 
 import gradio as gr
@@ -170,6 +169,7 @@ prompt = ChatPromptTemplate.from_messages(
     ]
 )
 
+llm =Ollama(model='llama3.2', base_url='http://localhost:11434')
 question_answer_chain  = create_stuff_documents_chain(llm, prompt)
 rag_chain = create_retrieval_chain(retriever, question_answer_chain)
 
@@ -266,7 +266,26 @@ def logout(session_id):
         del base[session_id]  # Clear session history
     return None, "Logged out successfully.", None
 
-# Gradio UI
+import gradio as gr
+
+def enable_buttons(username, password):
+    is_valid = bool(username.strip()) and bool(password.strip())
+    return gr.update(interactive=is_valid), gr.update(interactive=is_valid)
+
+def login_user(username, password):
+    session_id, message, user_id = authenticate(username, password)
+    if session_id:
+        # Hide login, signup, and status, and show the chat interface and logout button
+        return session_id, user_id, message, "", "", get_chat_history(user_id), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False), gr.update(visible=False), gr.update(visible=True)
+    return None, None, message, username, password, [], gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+
+def signup_user(username, password):
+    message = signup(username, password)
+    return message, "", ""
+
+def logout_user():
+    return None, "", "", "", [], gr.update(visible=False), gr.update(visible=True), gr.update(visible=True), gr.update(visible=False), gr.update(visible=False)
+
 with gr.Blocks() as demo:
     gr.Markdown("## HumblebeeAI Customer Support Chatbot")
 
@@ -286,39 +305,25 @@ with gr.Blocks() as demo:
         send_button = gr.Button("Send")
         logout_button = gr.Button("Logout")
 
-    # 🔹 Enable buttons only when both username & password are filled
-    def enable_buttons(username, password):
-        is_valid = bool(username.strip()) and bool(password.strip())
-        return gr.update(interactive=is_valid), gr.update(interactive=is_valid)
-
+    # Enable buttons only when both username & password are filled
     username.change(enable_buttons, [username, password], [login_button, signup_button])
     password.change(enable_buttons, [username, password], [login_button, signup_button])
 
-    # 🔹 Login Logic (Clears Username & Password)
-    def login_user(username, password):
-        session_id, message, user_id = authenticate(username, password)
-        if session_id:
-            return session_id, user_id, message, "", "", get_chat_history(user_id), gr.update(visible=True)
-        return None, None, message, username, password, [], gr.update(visible=False)
-    
+    # Login Logic (Clears Username & Password)
     login_button.click(
         login_user, 
         [username, password], 
-        [session_state, user_id_state, login_status, username, password, chatbot, chat_interface]
+        [session_state, user_id_state, login_status, username, password, chatbot, chat_interface, username, password, send_button, logout_button]
     )
 
-    # 🔹 Signup Logic (Clears Username & Password)
-    def signup_user(username, password):
-        message = signup(username, password)
-        return message, "", ""
-
+    # Signup Logic (Clears Username & Password)
     signup_button.click(
         signup_user, 
         [username, password], 
         [login_status, username, password]
     )
 
-    # 🔹 Sending Messages
+    # Sending Messages
     send_button.click(
         get_response, 
         [msg, chatbot, session_state, user_id_state], 
@@ -331,13 +336,11 @@ with gr.Blocks() as demo:
         [msg, chatbot]
     )
 
-    # 🔹 Logout Logic (Clears Chat and Resets UI)
-    def logout_user():
-        return None, "", "", "", [], gr.update(visible=False)
-
+    # Logout Logic (Clears Chat and Resets UI)
     logout_button.click(
         logout_user, 
         None, 
-        [session_state, username, password, login_status, chatbot, chat_interface]
+        [session_state, username, password, login_status, chatbot, chat_interface, username, password, send_button, logout_button]
     )
-demo.launch(share=True)
+
+demo.launch(share=True)

test.py

@@ -1,101 +0,0 @@
-import requests
-from langchain.llms.base import LLM
-from typing import Optional, List
-from pydantic import Field
-import json
-
-
-class HumbleBeeLLM(LLM):
-    api_base: str = "https://humblebeeai-llm-host.hf.space"
-    username: str = Field(default=None, exclude=True)  # Exclude from Pydantic validation
-    password: str = Field(default=None, exclude=True)
-    token: Optional[str] = None
-
-    def __init__(self, username: str, password: str, **kwargs):
-        super().__init__(**kwargs)  # Initialize LangChain's LLM class properly
-        self.username = username
-        self.password = password
-        self.authenticate()
-
-    def authenticate(self):
-        """Logs in to get the token."""
-        login_payload = {
-            "username": self.username,
-            "password": self.password
-        }
-
-        try:
-            response = requests.post(
-                f"{self.api_base}/login",
-                data=login_payload,  # Must be 'data' instead of 'json' for form-urlencoded
-                headers={"Content-Type": "application/x-www-form-urlencoded"}
-            )
-
-            if response.status_code == 200:
-                self.token = response.json().get("access_token")
-            else:
-                print(f"Login failed: {response.status_code} - {response.text}")
-                raise Exception("Failed to authenticate.")
-
-        except requests.exceptions.RequestException as e:
-            raise Exception(f"Error during authentication: {str(e)}")
-
-    def _call(self, prompt: str, stop: Optional[List[str]] = None) -> str:
-        """Sends a request to the LLM API and handles streaming responses."""
-        if not self.token:
-            self.authenticate()
-
-        headers = {
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {self.token}"
-        }
-        payload = {"query": prompt}
-
-        try:
-            response = requests.post(f"{self.api_base}/generate?stream=true", json=payload, headers=headers, stream=True)
-
-            if response.status_code == 200:
-                # Read the streaming response and reconstruct it token by token
-                full_response = ""
-                for line in response.iter_lines():
-                    if line:
-                        try:
-                            # Clean up the streamed JSON line
-                            data = json.loads(line.decode("utf-8").replace("data: ", ""))
-                            token_content = data.get("content", "")
-                            full_response += token_content
-                            print(token_content, end="", flush=True)  # Print each token as it arrives
-                        except json.JSONDecodeError:
-                            continue  # Ignore invalid JSON lines
-
-                return full_response.strip()  # Return the full response after all tokens
-
-            else:
-                print(f"Error {response.status_code}: {response.text}")
-                return f"Error {response.status_code}: {response.text}"
-
-        except requests.exceptions.RequestException as e:
-            return f"Request error: {str(e)}"
-
-    @property
-    def _identifying_params(self):
-        return {"api_base": self.api_base}
-
-    @property
-    def _llm_type(self):
-        return "humblebee-llm"
-
-# ✅ Usage Example
-llm = HumbleBeeLLM(username="new", password="newuser")
-
-"""# Invoke with LangChain's API
-while True:
-    query = input("\n...\n")
-    
-    if query.lower() == 'bye':  # Case insensitive check
-        print("Goodbye!")
-        break  # Exit loop when 'bye' is entered
-    
-    response = llm.invoke(query)
-
-"""