using gpt-4o-mini

Author: shashankdeshpande

pages/1_💬_basic_chatbot.py

@@ -2,7 +2,6 @@
 import streamlit as st
 from streaming import StreamHandler
 
-from langchain_openai import ChatOpenAI
 from langchain.chains import ConversationChain
 
 st.set_page_config(page_title="Chatbot", page_icon="💬")
@@ -13,11 +12,11 @@
 class BasicChatbot:
 
     def __init__(self):
-        self.openai_model = utils.configure_openai()
+        utils.sync_st_session()
+        self.llm = utils.configure_llm()
 
     def setup_chain(self):
-        llm = ChatOpenAI(model_name=self.openai_model, temperature=0, streaming=True)
-        chain = ConversationChain(llm=llm, verbose=True)
+        chain = ConversationChain(llm=self.llm, verbose=True)
         return chain
 
     @utils.enable_chat_history

pages/2_⭐_context_aware_chatbot.py

@@ -2,7 +2,6 @@
 import streamlit as st
 from streaming import StreamHandler
 
-from langchain_openai import ChatOpenAI
 from langchain.chains import ConversationChain
 from langchain.memory import ConversationBufferMemory
 
@@ -14,13 +13,13 @@
 class ContextChatbot:
 
     def __init__(self):
-        self.openai_model = utils.configure_openai()
+        utils.sync_st_session()
+        self.llm = utils.configure_llm()
 
     @st.cache_resource
     def setup_chain(_self):
         memory = ConversationBufferMemory()
-        llm = ChatOpenAI(model_name=_self.openai_model, temperature=0, streaming=True)
-        chain = ConversationChain(llm=llm, memory=memory, verbose=True)
+        chain = ConversationChain(llm=_self.llm, memory=memory, verbose=True)
         return chain
 
     @utils.enable_chat_history

pages/3_🌐_chatbot_with_internet_access.py

@@ -2,11 +2,12 @@
 import streamlit as st
 
 from langchain import hub
-from langchain_openai import OpenAI
+from langchain_openai import ChatOpenAI
 from langchain.memory import ConversationBufferMemory
 from langchain_community.tools import DuckDuckGoSearchRun
 from langchain_community.callbacks import StreamlitCallbackHandler
-from langchain.agents import AgentExecutor, Tool, create_react_agent
+from langchain.agents import AgentExecutor, create_react_agent
+from langchain_core.tools import Tool
 
 st.set_page_config(page_title="ChatWeb", page_icon="🌐")
 st.header('Chatbot with Internet Access')
@@ -16,7 +17,8 @@
 class InternetChatbot:
 
     def __init__(self):
-        self.openai_model = utils.configure_openai()
+        utils.sync_st_session()
+        self.llm = utils.configure_llm()
 
     @st.cache_resource(show_spinner='Connecting..')
     def setup_agent(_self):
@@ -34,9 +36,8 @@ def setup_agent(_self):
         prompt = hub.pull("hwchase17/react-chat")
 
         # Setup LLM and Agent
-        llm = OpenAI(temperature=0, streaming=True)
         memory = ConversationBufferMemory(memory_key="chat_history")
-        agent = create_react_agent(llm, tools, prompt)
+        agent = create_react_agent(_self.llm, tools, prompt)
         agent_executor = AgentExecutor(agent=agent, tools=tools, memory=memory, verbose=True)
         return agent_executor, memory
 

pages/4_📄_chat_with_your_documents.py

@@ -8,8 +8,8 @@
 from langchain.chains import ConversationalRetrievalChain
 from langchain_community.document_loaders import PyPDFLoader
 from langchain_community.embeddings import HuggingFaceEmbeddings
-from langchain.text_splitter import RecursiveCharacterTextSplitter
 from langchain_community.vectorstores import DocArrayInMemorySearch
+from langchain_text_splitters import RecursiveCharacterTextSplitter
 
 st.set_page_config(page_title="ChatPDF", page_icon="📄")
 st.header('Chat with your documents (Basic RAG)')
@@ -19,7 +19,8 @@
 class CustomDataChatbot:
 
     def __init__(self):
-        self.openai_model = utils.configure_openai()
+        utils.sync_st_session()
+        self.llm = utils.configure_llm()
 
     def save_file(self, file):
         folder = 'tmp'
@@ -65,9 +66,8 @@ def setup_qa_chain(self, uploaded_files):
         )
 
         # Setup LLM and QA chain
-        llm = ChatOpenAI(model_name=self.openai_model, temperature=0, streaming=True)
         qa_chain = ConversationalRetrievalChain.from_llm(
-            llm=llm,
+            llm=self.llm,
             retriever=retriever,
             memory=memory,
             return_source_documents=True,

pages/5_🛢_chat_with_sql_db.py

@@ -17,7 +17,8 @@
 class SqlChatbot:
 
     def __init__(self):
-        self.openai_model = utils.configure_openai()
+        utils.sync_st_session()
+        self.llm = utils.configure_llm()
 
     def setup_db(_self, db_uri):
         if db_uri == 'USE_SAMPLE_DB':
@@ -33,10 +34,8 @@ def setup_db(_self, db_uri):
         return db
 
     def setup_sql_agent(_self, db):
-        llm = ChatOpenAI(model_name=_self.openai_model, temperature=0, streaming=True)
-
         agent = create_sql_agent(
-            llm=llm,
+            llm=_self.llm,
             db=db,
             top_k=10,
             verbose=True,

requirements.txt

@@ -1,11 +1,12 @@
-langchain==0.1.17
-langchain_community==0.0.36
-langchain_openai==0.1.4
-langchainhub==0.1.15
-streamlit==1.33.0
-openai==1.25.0
-duckduckgo-search==5.3.0
-pypdf==4.2.0
-sentence-transformers==2.7.0
+langchain==0.2.9
+langchain_community==0.2.7
+langchain_core==0.2.21
+langchain_openai==0.1.17
+langchain_text_splitters==0.2.2
+openai==1.35.15
+SQLAlchemy==2.0.31
+streamlit==1.36.0
+duckduckgo-search==6.2.1
+pypdf==4.3.0
+sentence-transformers==3.0.1
 docarray==0.40.0
-SQLAlchemy==2.0.29

streaming.py

@@ -1,4 +1,4 @@
-from langchain.callbacks.base import BaseCallbackHandler
+from langchain_core.callbacks import BaseCallbackHandler
 
 class StreamHandler(BaseCallbackHandler):
 

utils.py

@@ -1,8 +1,9 @@
 import os
 import openai
-import random
 import streamlit as st
 from datetime import datetime
+from langchain_openai import ChatOpenAI
+from langchain_community.chat_models import ChatOllama
 
 #decorator
 def enable_chat_history(func):
@@ -40,39 +41,56 @@ def display_msg(msg, author):
     st.session_state.messages.append({"role": author, "content": msg})
     st.chat_message(author).write(msg)
 
-def configure_openai():
+def choose_custom_openai_key():
     openai_api_key = st.sidebar.text_input(
         label="OpenAI API Key",
         type="password",
-        value=st.session_state['OPENAI_API_KEY'] if 'OPENAI_API_KEY' in st.session_state else '',
-        placeholder="sk-..."
+        placeholder="sk-...",
+        key="SELECTED_OPENAI_API_KEY"
         )
-    if openai_api_key:
-        st.session_state['OPENAI_API_KEY'] = openai_api_key
-        os.environ['OPENAI_API_KEY'] = openai_api_key
-    else:
+    if not openai_api_key:
         st.error("Please add your OpenAI API key to continue.")
         st.info("Obtain your key from this link: https://platform.openai.com/account/api-keys")
         st.stop()
 
-    model = "gpt-3.5-turbo"
+    model = "gpt-4o-mini"
     try:
-        client = openai.OpenAI()
+        client = openai.OpenAI(api_key=openai_api_key)
         available_models = [{"id": i.id, "created":datetime.fromtimestamp(i.created)} for i in client.models.list() if str(i.id).startswith("gpt")]
         available_models = sorted(available_models, key=lambda x: x["created"])
         available_models = [i["id"] for i in available_models]
 
         model = st.sidebar.selectbox(
             label="Model",
             options=available_models,
-            index=available_models.index(st.session_state['OPENAI_MODEL']) if 'OPENAI_MODEL' in st.session_state else 0
+            key="SELECTED_OPENAI_MODEL"
         )
-        st.session_state['OPENAI_MODEL'] = model
     except openai.AuthenticationError as e:
         st.error(e.body["message"])
         st.stop()
     except Exception as e:
         print(e)
         st.error("Something went wrong. Please try again later.")
         st.stop()
-    return model
+    return model, openai_api_key
+
+def configure_llm():
+    available_llms = ["gpt-4o-mini","llama3:8b","use your openai api key"]
+    llm_opt = st.sidebar.radio(
+        label="LLM",
+        options=available_llms,
+        key="SELECTED_LLM"
+        )
+
+    if llm_opt == "llama3:8b":
+        llm = ChatOllama(model="llama3", base_url=st.secrets["OLLAMA_ENDPOINT"])
+    elif llm_opt == "gpt-4o-mini":
+        llm = ChatOpenAI(model_name=llm_opt, temperature=0, streaming=True, api_key=st.secrets["OPENAI_API_KEY"])
+    else:
+        model, openai_api_key = choose_custom_openai_key()
+        llm = ChatOpenAI(model_name=model, temperature=0, streaming=True, api_key=openai_api_key)
+    return llm
+
+def sync_st_session():
+    for k, v in st.session_state.items():
+        st.session_state[k] = v