app.py

@@ -0,0 +1,18 @@
+import streamlit as st
+import langchain
+
+st.title('Ask maargdarshak')
+
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+
+for message in st.session_state.messages:
+    st.chat_message(message['role']).markdown(message['content'])
+
+
+prompt = st.chat_input("Ask your question here")
+
+if prompt:
+    st.chat_message('user').markdown(prompt)
+    st.session_state.messages.append({'role':'user', 'content':prompt})
+

app_response.py

@@ -0,0 +1,70 @@
+import streamlit as st
+import requests
+
+
+# Streamlit App
+def chatbot():
+    st.title("Chatbot powered by Ollama")
+
+    # Initialize session state for storing the chat history
+    if "chat_history" not in st.session_state:
+        st.session_state["chat_history"] = []
+
+    # User input section
+    user_input = st.text_input("You: ", "")
+
+    if user_input:
+        # Get Ollama response
+        response = query_ollama(user_input)
+        # Append the conversation to the chat history
+        st.session_state["chat_history"].append({"role": "user", "text": user_input})
+        st.session_state["chat_history"].append({"role": "bot", "text": response})
+
+    # Display chat history
+    if st.session_state["chat_history"]:
+        for chat in st.session_state["chat_history"]:
+            if chat["role"] == "user":
+                st.write(f"**You:** {chat['text']}")
+            else:
+                st.write(f"**Bot:** {chat['text']}")
+
+
+# Function to query Ollama locally
+
+def query_ollama(prompt):
+    # Assuming Ollama API is running locally on port 11434
+    url = "http://localhost:11434/api/generate"
+    payload = {
+        "model": "llama2",  # Change model name if necessary
+        "prompt": prompt
+    }
+    headers = {
+        "Content-Type": "application/json"
+    }
+
+    try:
+        response = requests.post(url, json=payload, headers=headers)
+
+        # Print the status code and response text for debugging
+        print(f"Status Code: {response.status_code}")
+        print(f"Response Text: {response.text}")
+
+        # Check if the response is successful
+        if response.status_code == 200:
+            try:
+                response_json = response.json()
+                return response_json.get("output", "Sorry, I couldn't generate a response.")
+            except ValueError:
+                st.error("The server returned an invalid response. Please check the API.")
+                return "Invalid response format"
+        else:
+            st.error(f"Error from API: {response.status_code}")
+            return f"Error: {response.status_code}"
+
+    except requests.exceptions.RequestException as e:
+        st.error(f"Request failed: {e}")
+        return "Failed to communicate with the server."
+
+
+if __name__ == "__main__":
+    chatbot()

cookies.py

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+import streamlit as st
+import time
+from cookies_manager import EncryptedCookieManager
+
+# This should be your unique encryption key, which should be kept secure.
+cookie_manager = EncryptedCookieManager(
+    prefix="myapp_",  # Define a prefix for the cookie to avoid conflicts
+    password="your_secure_cookie_password"  # Replace with your secure password
+)
+
+# Initialize cookies
+if not cookie_manager.ready():
+    st.stop()
+
+
+def get_user_timestamp():
+    # Check if timestamp already exists in cookies
+    timestamp = cookie_manager.get("user_timestamp")
+
+    if timestamp:
+        st.write(f"Welcome back! Your session started at: {timestamp}")
+        return timestamp
+    else:
+        # Generate a new timestamp in milliseconds
+        new_timestamp = str(int(time.time() * 1000))
+        cookie_manager.set("user_timestamp", new_timestamp, max_age=3600 * 24 * 7)  # Store the timestamp for 7 days
+        st.write(f"New session started! Your timestamp is: {new_timestamp}")
+        return new_timestamp
+
+
+# Chatbot function
+def chatbot():
+    st.title("Chatbot with Timestamps in Cookies")
+
+    # Retrieve or create timestamp for the user
+    timestamp = get_user_timestamp()
+
+    # Display the chat prompt
+    user_input = st.text_input("You: ", "")
+
+    if user_input:
+        # Here, instead of querying Ollama, we simulate a chatbot response
+        st.write(f"**Bot:** You said '{user_input}' at {timestamp}")
+
+
+# Main
+if __name__ == "__main__":
+    chatbot()