update_chatbot

.devcontainer/devcontainer.json

@@ -1,22 +0,0 @@
-// For format details, see https://aka.ms/devcontainer.json. For config options, see the
-// README at: https://github.com/devcontainers/templates/tree/main/src/debian
-{
-	"name": "Debian",
-	// Or use a Dockerfile or Docker Compose file. More info: https://containers.dev/guide/dockerfile
-	"image": "mcr.microsoft.com/devcontainers/base:bullseye",
-	"features": {
-		"ghcr.io/akhildevelops/devcontainer-features/pip:0": {}
-	}
-
-	// Features to add to the dev container. More info: https://containers.dev/features.
-	// "features": {},
-
-	// Use 'forwardPorts' to make a list of ports inside the container available locally.
-	// "forwardPorts": [],
-
-	// Configure tool-specific properties.
-	// "customizations": {},
-
-	// Uncomment to connect as root instead. More info: https://aka.ms/dev-containers-non-root.
-	// "remoteUser": "root"
-}

Dockerfile

@@ -0,0 +1,20 @@
+# Use an official Python runtime as a parent image
+FROM python:3.9-slim
+
+# Set the working directory in the container
+WORKDIR /app
+
+# Copy the current directory contents into the container at /app
+COPY . /app
+
+# Install any necessary dependencies specified in requirements.txt
+RUN pip install --no-cache-dir -r requirements.txt
+
+# Make port 8501 available to the world outside this container
+EXPOSE 8501
+
+# Define environment variable for Streamlit
+ENV STREAMLIT_SERVER_HEADLESS=true
+
+# Run Streamlit when the container launches
+CMD ["streamlit", "run", "app.py", "--server.port=8501", "--server.address=0.0.0.0"]

app.py

@@ -1,47 +1,128 @@
 import streamlit as st
-import os
-import getpass
+import asyncio
+# import os
+# import getpass
 import time
-from chatbot_helper import oracle_db
+from chatbot_helper import oracle_db,question_suggestion_api,send_chatbot_request
 from llama_index.core.llms import ChatMessage
-from pinecone import Pinecone
+# from pinecone import Pinecone
 from llama_index.llms.groq import Groq
 from semantic_router.encoders import HuggingFaceEncoder
 
 st.title("🤖 Welcome in :blue[_fam_ _properties_] ChatBot :sunglasses:")
 
-index_name = "fam-rag"
-docs = []
-history_docs = []
+# index_name = "fam-rag"
+# docs = []
+# history_docs = []
 
-encoder = HuggingFaceEncoder(name="dwzhu/e5-base-4k")
+# encoder = HuggingFaceEncoder(name="dwzhu/e5-base-4k")
 
 # groq_client = Groq(api_key="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")
 # st.secrets['REPLICATE_API_TOKEN']
 llm = Groq(model="llama3-70b-8192", api_key=st.secrets["GROQ_API_KEY"])
 
 # configure client
-pc = Pinecone(api_key=st.secrets["PINECONE_API_KEY"])
+# pc = Pinecone(api_key=st.secrets["PINECONE_API_KEY"])
 
-index = pc.Index(index_name)
-time.sleep(1)
+# index = pc.Index(index_name)
+# time.sleep(1)
 
 
+def onclickQuestion(question):
+    st.session_state.messages.append(ChatMessage(role= "user", content=question))
+    generate_llm(question)
+    
+def generate_llm(text):
+    resp =  asyncio.run(send_chatbot_request(text,st.secrets["COHERE_API_KEY"]))
+    print(resp)   
+    
+    # with st.chat_message("assistant"):
+    #     st.write(resp)
+    
+    st.session_state.messages.append(ChatMessage(role= "assistant", content= resp))
+
+
+
+
+
+# Call the API with an empty string to retrieve questions
+    
+def get_questions(message: str):
+    return asyncio.run(question_suggestion_api(message))
+# questions = question_suggestion_api("")
+
+@st.dialog("Sign Up")
+def email_form():
+    name = st.text_input("Name")
+    email = st.text_input("Email")
+    print(name)
+    print(email)
+    st.button('submit')
+
 if "messages" not in st.session_state:
     st.session_state.messages = [
-    
         ChatMessage(role="system", content="You are a real state assistant that helps users find best properties in Dubai that fit there requirement")
-]
+]        
+
+if len(st.session_state.messages) >= 9:
+    st.button('Sign In',on_click=email_form)
+        
+else:
+
+
+            
+    prompt = st.chat_input("What is up?")
+
+
+    # Display the existing chat messages via `st.chat_message`.
+
+                # if placeholder.button(question):
+                #     prompt = question
+    # Create a chat input field to allow the user to enter a message. This will display
+    # automatically at the bottom of the page.
+
+
+
+    print(len(st.session_state.messages))
+    if len(st.session_state.messages) > 1 or prompt:
+        
+        with st.container(height=450):
+                        
+            if prompt:
+                
+                # with st.chat_message("user"):
+                #     st.markdown(prompt)
+                
+                st.session_state.messages.append(ChatMessage(role= "user", content=prompt))
+                generate_llm(prompt)
+            
+            for message in st.session_state.messages:
+                if message.role != "system":
+                    with st.chat_message(message.role):
+                        st.markdown(message.content)
+
 
-# Display the existing chat messages via `st.chat_message`.
-for message in st.session_state.messages:
-    if message.role != "system":
-        with st.chat_message(message.role):
-            st.markdown(message.content)
+# if st.session_state.messages[-1].role == 'assistant' or len(st.session_state.messages) == 1:
 
-# Create a chat input field to allow the user to enter a message. This will display
-# automatically at the bottom of the page.
-if prompt := st.chat_input("What is up?"):
+    # print(st.session_state.messages[-1].content)
+    # print(st.session_state.messages[-1].role == 'assistant')
+    
+    # if len(st.session_state.messages) == 1:
+    #     questions = get_questions("")
+    # else:
+    #     questions = get_questions(st.session_state.messages[-1].content)
+
+    # if questions:
+    #     # Create an empty container to position the buttons
+    #     placeholder = st.container(height=200)
+
+    #     # Dynamically create buttons for each question
+    #     for index,question in enumerate(questions):
+    #         placeholder.button(question,key=index,on_click=lambda q=question: onclickQuestion(q))
+                
+    # print(questions)
+    # print(st.session_state.messages)
+                
 
     # Store and display the current prompt.    
 
@@ -54,44 +135,43 @@ if prompt := st.chat_input("What is up?"):
     #     ],
     #     stream=True,
     # ) 
-    with st.chat_message("user"):
-        st.markdown(prompt)
     
-    if not prompt.__contains__("Yes") or not prompt.__contains__("No"):
-        docs = oracle_db(prompt, 5)
-        if len(history_docs) == 3:
-            history_docs.pop(0) 
-            history_docs.append(docs)
-            print(history_docs)
-            print(len(history_docs))
-        else:
-            history_docs.append(docs)
-            print(history_docs)
-            print(len(history_docs))
+    
+    # if not prompt.__contains__("Yes") or not prompt.__contains__("No"):
+    #     docs = oracle_db(prompt, 5)
+    #     if len(history_docs) == 3:
+    #         history_docs.pop(0) 
+    #         history_docs.append(docs)
+    #         print(history_docs)
+    #         print(len(history_docs))
+    #     else:
+    #         history_docs.append(docs)
+    #         print(history_docs)
+    #         print(len(history_docs))
             
             
 
         # result = generate(prompt, docs, groq_client, st.session_state.messages)
 
-    docs = "\n---\n".join([str(i) for doc in history_docs for i in doc ])
+    # docs = "\n---\n".join([str(i) for doc in history_docs for i in doc ])
     
-    system_message =f'''
-        You are a real state assistant and agent act as that and help users find best properties and there transition in Dubai that fit there requirement using the
-        context and chat history provided below. 
-        please be precise when you answer the user with Full specifications and details and get the answer from your history if the question is not related to the context.
-        if you ask the user a yes/no question do not use the provided context for response, use chat history for answer instead.
+    # system_message =f'''
+    #     You are a real state assistant and agent act as that and help users find best properties and there transition in Dubai that fit there requirement using the
+    #     context and chat history provided below. 
+    #     please be precise when you answer the user with Full specifications and details and get the answer from your history if the question is not related to the context.
+    #     if you ask the user a yes/no question do not use the provided context for response, use chat history for answer instead.
     
-        if the context or the chat history may not have the answer of the question get the answer from chat history if not related please
-        ask user to provide you more information
-        \n\n
-        CONTEXT:\n
-        {docs}
-        '''
-    for i, k in enumerate(st.session_state.messages):
-        if k.role =="system":
-            st.session_state.messages[i].content = system_message
-
-    st.session_state.messages.append(ChatMessage(role= "user", content=prompt))
+    #     if the context or the chat history may not have the answer of the question get the answer from chat history if not related please
+    #     ask user to provide you more information
+    #     \n\n
+    #     CONTEXT:\n
+    #     {docs}
+    #     '''
+    # for i, k in enumerate(st.session_state.messages):
+    #     if k.role =="system":
+    #         st.session_state.messages[i].content = system_message
+
+        
 
     # generate response
     # chat_response = groq_client.chat.completions.create(
@@ -102,14 +182,18 @@ if prompt := st.chat_input("What is up?"):
     #     ],
     #     stream=True
     # )
-    resp = llm.stream_chat(st.session_state.messages)
-    print(st.session_state.messages)
+    # resp = llm.stream_chat(st.session_state.messages)
+        # resp =  asyncio.run(send_chatbot_request(prompt,st.secrets["COHERE_API_KEY"]))
+    
+    # print(st.session_state.messages)
 
     # Stream the response to the chat using `st.write_stream`, then store it in 
     # session state.
-    print(resp)
-    res = [i.delta for i in resp ]
-    with st.chat_message("assistant"):
-        response = st.write_stream(res)
-
-    st.session_state.messages.append(ChatMessage(role= "assistant", content= "".join([i for i in response])))
+    # print(resp)
+        
+        # print(resp)   
+    
+        # with st.chat_message("assistant"):
+        #     st.write(resp)
+        
+        # st.session_state.messages.append(ChatMessage(role= "assistant", content= resp))

chatbot_helper.py

@@ -1,3 +1,7 @@
+import requests
+import asyncio
+
+
 def get_docs(question: str, top_k: int, encoder, pinecone_index) -> list[str]:
     # encode query
     xq = encoder([question])
@@ -56,4 +60,81 @@ def oracle_db(query:str, top_k:int) -> list[dict]:
     print(query)
     print(exist)
     connection.close()
-    return exist
+    return exist
+
+
+async def question_suggestion_api(message:str)-> list:
+    questions = []
+
+    # The URL endpoint
+    url = "http://91.75.21.131:9080/ords/ai/rag/question_suggestion"
+
+    # The payload to be sent with the POST request
+    payload = {
+        'response': message  # Replace with the actual response data
+    }
+
+    # Making the POST request
+    response = requests.post(url, params=payload)
+    await asyncio.sleep(2)
+    
+    print(response.text)
+    
+    # Check if the request was successful
+    if response.status_code == 200:
+        # Parse the response JSON
+        data = response.json()
+        print(data)
+
+        # Extract and print the list of questions
+        questions = data.get('expected_responses', [])
+        
+        if questions:
+            print("Questions:")
+            for idx, question in enumerate(questions):
+                print(f"{idx}. {question}")
+        else:
+            print("No questions found in the response.")
+    else:
+        print(f"Request failed with status code: {response.status_code}")
+        
+    return questions
+
+
+
+
+async def send_chatbot_request(question, cohere_api_key)-> dict:
+    # The URL endpoint
+    url = "http://91.75.21.131:9080/ords/ai/rag/chatbot"
+
+    # The payload to be sent with the POST request
+    payload = {
+        'question': question,
+        'cohere_api_key': cohere_api_key
+    }
+
+    # Making the POST request
+    try:
+        response = requests.post(url, params=payload,timeout=26)
+        await asyncio.sleep(3)
+        print("hello")
+        
+
+        # Check if the request was successful
+        if response.status_code == 200:
+                # Parse the response JSON
+                data = response.json()
+                generations = data.get("generations",[])[0]
+                print(generations)
+                result = generations.get('text','')
+                return result
+        else:
+            return f"Request failed with status code: {response.status_code}"
+    
+    except ValueError:
+        return "Error: Unable to parse JSON response."
+    except requests.Timeout:
+        print("The request timed out. Please try again.")
+    except requests.RequestException as e:
+        print(f"An error occurred: {e}")
+    

packages.txt

@@ -1,6 +0,0 @@
---only-upgrade 
---only-upgrade build-essential
---only-upgrade pkg-config
---only-upgrade cmake
---only-upgrade libpthread-stubs0-dev
---only-upgrade stdc++