Update page1.py

page1.py

@@ -1,195 +1,16 @@
 import streamlit as st
-from langchain_core.messages import HumanMessage
-from langchain_google_genai import ChatGoogleGenerativeAI
-from langchain.chains import LLMChain
-from langchain.prompts import PromptTemplate
-from langchain.memory import ConversationBufferMemory
-from langchain.memory.chat_message_histories import StreamlitChatMessageHistory
-from streamlit_chat import message
 import time
 import random
 import os
-api = os.environ.get("api_key")
 
 def text():
+    st.title("Home of ForgeStudio")
     st.markdown("""
-                <style>
-                    .anim-typewriter {
-                        animation: typewriter 3s steps(40) 1s 1 normal both, blinkTextCursor 800ms steps(40) infinite normal;
-                        overflow: hidden;
-                        white-space: nowrap;
-                        border-right: 3px solid;
-                        font-family: serif;
-                        font-size: 0.9em;
-                    }
-                    @keyframes typewriter {
-                        from {
-                            width: 0;
-                        }
-                        to {
-                            width: 100%;
-                            height: 100%
-                        }
-                    }
-                    @keyframes blinkTextCursor {
-                        from {
-                            border-right-color: rgba(255, 255, 255, 0.75);
-                        }
-                        to {
-                            border-right-color: transparent;
-                        }
-                    }
-                </style>
-            """, unsafe_allow_html=True)
-    text ="Hello 👋, how may I assist you today?"
-    animated_output = f'<div class="line-1 anim-typewriter">{text}</div>'
+    ## About
+    This is modern webui for new AI types.
 
-    with st.chat_message("assistant").markdown(animated_output,unsafe_allow_html=True ):
-        st.markdown(animated_output,unsafe_allow_html=True)
-    apiKey = api
-    msgs = StreamlitChatMessageHistory(key="special_app_key")
+    ## How to use
+    In the navigate menu there is options of AI types.
 
-    memory = ConversationBufferMemory(memory_key="history", chat_memory=msgs)
-    if len(msgs.messages) == 0:
-        msgs.add_ai_message("How can I help you?")
-    template = """You are an AI chatbot having a conversation with a human.
-
-    {history}
-    Human: {human_input}
-    AI: """
-    prompt = PromptTemplate(input_variables=["history", "human_input"], template=template)
-    llm_chain = LLMChain( llm = ChatGoogleGenerativeAI(model="gemini-pro", google_api_key=apiKey), prompt=prompt, memory = memory)
-
-    if 'messages' not in st.session_state:
-        st.session_state['messages'] = []
-
-    for message in st.session_state.messages:
-        with st.chat_message(message["role"]):
-            st.markdown(message["content"])
-
-    prompt = st.chat_input("Say something")
-
-    if prompt:
-        with st.chat_message("user").markdown(prompt):
-            st.session_state.messages.append(
-                {
-                    "role": "user",
-                    "content": prompt
-                }
-            )
-        # Custom HTML and CSS for three-dot animation
-        spinner_html = """
-        <div class="col-3">
-        <div class="snippet" data-title="dot-pulse">
-          <div class="stage">
-            <div class="dot-pulse"></div>
-          </div>
-        </div>
-      </div>
-        """
-
-        spinner_css = """
-        .dot-pulse {
-  position: relative;
-  left: -9999px;
-
-  width: 10px;
-  height: 10px;
-  border-radius: 5px;
-  background-color: #9880ff;
-  color: #9880ff;
-  box-shadow: 9999px 0 0 -5px;
-  animation: dot-pulse 1.5s infinite linear;
-  animation-delay: 0.25s;
-}
-.dot-pulse::before, .dot-pulse::after {
-  content: "";
-  display: inline-block;
-  position: absolute;
-  top: 0;
-  width: 10px;
-  height: 10px;
-  border-radius: 5px;
-  background-color: #9880ff;
-  color: #9880ff;
-}
-.dot-pulse::before {
-  box-shadow: 9984px 0 0 -5px;
-  animation: dot-pulse-before 1.5s infinite linear;
-  animation-delay: 0s;
-}
-.dot-pulse::after {
-  box-shadow: 10014px 0 0 -5px;
-  animation: dot-pulse-after 1.5s infinite linear;
-  animation-delay: 0.5s;
-}
-
-@keyframes dot-pulse-before {
-  0% {
-    box-shadow: 9984px 0 0 -5px;
-  }
-  30% {
-    box-shadow: 9984px 0 0 2px;
-  }
-  60%, 100% {
-    box-shadow: 9984px 0 0 -5px;
-  }
-}
-@keyframes dot-pulse {
-  0% {
-    box-shadow: 9999px 0 0 -5px;
-  }
-  30% {
-    box-shadow: 9999px 0 0 2px;
-  }
-  60%, 100% {
-    box-shadow: 9999px 0 0 -5px;
-  }
-}
-@keyframes dot-pulse-after {
-  0% {
-    box-shadow: 10014px 0 0 -5px;
-  }
-  30% {
-    box-shadow: 10014px 0 0 2px;
-  }
-  60%, 100% {
-    box-shadow: 10014px 0 0 -5px;
-  }
-}
-        """
-
-        st.markdown(f'<style>{spinner_css}</style>', unsafe_allow_html=True)
-        st.markdown(spinner_html, unsafe_allow_html=True)
-
-        for chunk in llm_chain.stream(prompt):
-            text_output = chunk.get("text", "")
-        st.markdown('<style>.dot-pulse { visibility: hidden; }</style>', unsafe_allow_html=True)
-
-        with st.chat_message("assistant").markdown(text_output):
-            st.session_state.messages.append(
-                {
-                    "role": "assistant",
-                    "content": text_output
-                }
-            )
-
-        #with st.chat_message("assistant"):
-            #message_placeholder = st.empty()
-            #full_response = ""
-            #assistant_response = random.choice(
-            #[
-                #"Hello there! How can I assist you today?",
-                #"Hi, human! Is there anything I can help you with?",
-               # "Do you need help?",
-           # ]
-      #  )
-        # Simulate stream of response with milliseconds delay
-           # for chunk in text_output.split():
-              #  full_response += chunk + " "
-           #     time.sleep(0.05)
-            # Add a blinking cursor to simulate typing
-          #      message_placeholder.markdown(full_response + "▌")
-        #    message_placeholder.markdown(full_response)
-    # Add assistant response to chat history
-      #  st.session_state.messages.append({"role": "assistant", "content": full_response})
+    ### Build by [@ehristoforu](https://github.com/ehristoforu)
+    """)