Main

.vscode/settings.json

@@ -0,0 +1,5 @@
+{
+    "githubPullRequests.ignoredPullRequestBranches": [
+        "main"
+    ]
+}

Chatbot.py

@@ -1,29 +1,34 @@
-from openai import OpenAI
+from langchain.chains import ConversationalRetrievalChain
+from langchain.chains.llm import LLMChain
+from langchain.schema import Document
+from langchain_community.llms import Ollama
+
 import streamlit as st
 
 with st.sidebar:
-    openai_api_key = st.text_input("OpenAI API Key", key="chatbot_api_key", type="password")
-    "[Get an OpenAI API key](https://platform.openai.com/account/api-keys)"
-    "[View the source code](https://github.com/streamlit/llm-examples/blob/main/Chatbot.py)"
-    "[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/streamlit/llm-examples?quickstart=1)"
+    st.text_input("choose version")
+
+#    openai_api_key = st.text_input("OpenAI API Key", key="chatbot_api_key", type="password")
+#    "[Get an OpenAI API key](https://platform.openai.com/account/api-keys)"
+#    "[View the source code](https://github.com/streamlit/llm-examples/blob/main/Chatbot.py)"
+#    "[![Open in GitHub Codespaces](https://github.com/codespaces/badge.svg)](https://codespaces.new/streamlit/llm-examples?quickstart=1)"
 
-st.title("💬 Chatbot")
-st.caption("🚀 A Streamlit chatbot powered by OpenAI")
+st.title("💬 AIA Chatbot")
+st.caption("🚀 AIA 課程查詢機器人")
 if "messages" not in st.session_state:
     st.session_state["messages"] = [{"role": "assistant", "content": "How can I help you?"}]
 
 for msg in st.session_state.messages:
     st.chat_message(msg["role"]).write(msg["content"])
 
+llm = Ollama(model="llama3", base_url="http://3ece-140-109-17-42.ngrok-free.app")
+
 if prompt := st.chat_input():
-    if not openai_api_key:
-        st.info("Please add your OpenAI API key to continue.")
-        st.stop()
 
-    client = OpenAI(api_key=openai_api_key)
     st.session_state.messages.append({"role": "user", "content": prompt})
     st.chat_message("user").write(prompt)
-    response = client.chat.completions.create(model="gpt-3.5-turbo", messages=st.session_state.messages)
-    msg = response.choices[0].message.content
+    response = llm.invoke(st.session_state.messages)
+    #msg = response.choices[0].message.content
+    msg = response
     st.session_state.messages.append({"role": "assistant", "content": msg})
     st.chat_message("assistant").write(msg)