Delete pages/AI Search.py

pages/AI Search.py

@@ -1,77 +0,0 @@
-from langchain.agents import ConversationalChatAgent, AgentExecutor
-from langchain.memory import ConversationBufferMemory
-from langchain_community.callbacks import StreamlitCallbackHandler
-from langchain_community.chat_message_histories import StreamlitChatMessageHistory
-from langchain_community.tools import DuckDuckGoSearchRun
-from langchain_core.runnables import RunnableConfig
-from langchain_openai import ChatOpenAI
-from dotenv import load_dotenv
-import os
-
-load_dotenv()
-
-openai_api_key = os.getenv("OPENAI_API_KEY")
-
-import streamlit as st
-
-st.title("Chat with search")
-
-
-if "steps" not in st.session_state:
-    st.session_state.steps = {}
-
-msgs = StreamlitChatMessageHistory()
-memory = ConversationBufferMemory(
-    chat_memory=msgs, return_messages=True, memory_key="chat_history", output_key="output"
-)
-
-# Remove the sidebar button and add a button in the main content area
-if st.button("Reset chat history", key="reset_chat_history"):
-    msgs.clear()
-    msgs.add_ai_message("How can I help you?")
-    st.session_state.steps = {}
-
-avatars = {"human": "user", "ai": "assistant"}
-for idx, msg in enumerate(msgs.messages):
-    with st.chat_message(avatars[msg.type]):
-        # Render intermediate steps if any were saved
-        for step in st.session_state.steps.get(str(idx), []):
-            if step[0].tool == "_Exception":
-                continue
-            with st.status(f"**{step[0].tool}**: {step[0].tool_input}", state="complete"):
-                st.write(step[0].log)
-                st.write(step[1])
-        st.write(msg.content)
-
-if prompt := st.chat_input(placeholder="Who won the Women's U.S. Open in  2018?"):
-    st.chat_message("user").write(prompt)
-
-    llm = ChatOpenAI(model_name="gpt-3.5-turbo", openai_api_key=openai_api_key, streaming=True)
-    tools = [DuckDuckGoSearchRun(name="Search")]
-    chat_agent = ConversationalChatAgent.from_llm_and_tools(llm=llm, tools=tools)
-    executor = AgentExecutor.from_agent_and_tools(
-        agent=chat_agent,
-        tools=tools,
-        memory=memory,
-        return_intermediate_steps=True,
-        handle_parsing_errors=True,
-    )
-    with st.chat_message("assistant"):
-        st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False)
-        cfg = RunnableConfig()
-        cfg["callbacks"] = [st_cb]
-        response = executor.invoke(prompt, cfg)
-        st.write(response["output"])
-        st.session_state.steps[str(len(msgs.messages) -  1)] = response["intermediate_steps"]
-
-# Add custom CSS to position the button next to the input field
-st.markdown("""
-<style>
-    .stButton > button {
-        margin-top:  10px;
-    }
-    .stButton > button[data-baseweb="button"] {
-        margin-left:  10px;
-    }
-</style>
-""", unsafe_allow_html=True)