adding example of context aware chatbot, other minor ui improvements

Author: shashankdeshpande

Home.py

@@ -8,15 +8,18 @@
 
 st.header("Chatbot Implementations with Langchain")
 st.write("""
+[![view source code ](https://img.shields.io/badge/GitHub%20Repository-gray?logo=github)](https://github.com/shashankdeshpande/langchain-chatbot)
+![Visitors](https://api.visitorbadge.io/api/visitors?path=https%3A%2F%2Flangchain-chatbot.streamlit.app&label=Visitors&labelColor=%235d5d5d&countColor=%231e7ebf&style=flat)
+""")
+st.write("""
 Langchain is a powerful framework designed to streamline the development of applications using Language Models (LLMs). It provides a comprehensive integration of various components, simplifying the process of assembling them to create robust applications.
 
 Leveraging the power of Langchain, the creation of chatbots becomes effortless. Here are a few examples of chatbot implementations catering to different use cases:
 
 - **Basic Chatbot**: Engage in interactive conversations with the LLM.
+- **Context aware chatbot**: A chatbot that remembers previous conversations and provides responses accordingly.
 - **Chatbot with Internet Access**: An internet-enabled chatbot capable of answering user queries about recent events.
 - **Chat with your documents** Empower the chatbot with the ability to access custom documents, enabling it to provide answers to user queries based on the referenced information.
 
 To explore sample usage of each chatbot, please navigate to the corresponding chatbot section.
-
-GitHub Repository: https://github.com/shashankdeshpande/langchain-chatbot
 """)

README.md

@@ -10,6 +10,9 @@ Here are a few examples of chatbot implementations using Langchain and Streamlit
 -  **Basic Chatbot** \
   Engage in interactive conversations with the LLM.
 
+- **Context aware chatbot** \
+  A chatbot that remembers previous conversations and provides responses accordingly.
+
 -  **Chatbot with Internet Access** \
   An internet-enabled chatbot capable of answering user queries about recent events.
 

pages/1_💬_basic_chatbot.py

@@ -8,11 +8,7 @@
 st.set_page_config(page_title="Chatbot", page_icon="💬")
 st.header('Basic Chatbot')
 st.write('Allows users to interact with the LLM')
-with st.expander("Implementation details"):
-    st.markdown("""
-    - LLM - [OpenAI](https://python.langchain.com/docs/ecosystem/integrations/openai#llm)
-    - Chain - [ConversationChain](https://github.com/hwchase17/langchain/blob/1d649b127eb10c426f9b9a67cbd1fe6ec8e6befa/langchain/chains/conversation/base.py#L12)
-    """)
+st.write('[![view source code ](https://img.shields.io/badge/view_source_code-gray?logo=github)](https://github.com/shashankdeshpande/langchain-chatbot/blob/master/pages/1_%F0%9F%92%AC_basic_chatbot.py)')
 
 class Basic:
 

pages/2_⭐_context_aware_chatbot.py

@@ -0,0 +1,40 @@
+import utils
+import streamlit as st
+from streaming import StreamHandler
+
+from langchain.llms import OpenAI
+from langchain.chains import ConversationChain
+from langchain.memory import ConversationBufferMemory
+
+st.set_page_config(page_title="Context aware chatbot", page_icon="⭐")
+st.header('Context aware chatbot')
+st.write('Enhancing Chatbot Interactions through Context Awareness')
+st.write('[![view source code ](https://img.shields.io/badge/view_source_code-gray?logo=github)](https://github.com/shashankdeshpande/langchain-chatbot/blob/master/pages/2_%E2%AD%90_context_aware_chatbot.py)')
+
+class Basic:
+
+    def __init__(self):
+        utils.configure_openai_api_key()
+        self.openai_model = "gpt-3.5-turbo"
+    
+    @st.cache_resource
+    def setup_chain(_self):
+        memory = ConversationBufferMemory()
+        llm = OpenAI(model_name=_self.openai_model, temperature=0, streaming=True)
+        chain = ConversationChain(llm=llm, memory=memory, verbose=True)
+        return chain
+    
+    @utils.enable_chat_history
+    def main(self):
+        chain = self.setup_chain()
+        user_query = st.chat_input(placeholder="Ask me anything!")
+        if user_query:
+            utils.display_msg(user_query, 'user')
+            with st.chat_message("assistant"):
+                st_cb = StreamHandler(st.empty())
+                response = chain.run(user_query, callbacks=[st_cb])
+                st.session_state.messages.append({"role": "assistant", "content": response})
+
+if __name__ == "__main__":
+    obj = Basic()
+    obj.main()

…ges/2_🌐_chatbot_with_internet_access.py …ges/3_🌐_chatbot_with_internet_access.pypages/2_🌐_chatbot_with_internet_access.py renamed to pages/3_🌐_chatbot_with_internet_access.py pages/2_🌐_chatbot_with_internet_access.py renamed to pages/3_🌐_chatbot_with_internet_access.py

@@ -10,12 +10,7 @@
 st.set_page_config(page_title="ChatWeb", page_icon="🌐")
 st.header('Chatbot with Internet Access')
 st.write('Equipped with internet access, enables users to ask questions about recent events')
-with st.expander("Implementation details"):
-    st.markdown("""
-    - LLM - [OpenAI](https://python.langchain.com/docs/ecosystem/integrations/openai#llm)
-    - Tools - [DuckDuckGoSearch](https://python.langchain.com/docs/modules/agents/tools/integrations/ddg)
-    - Agent - [ReAct](https://python.langchain.com/docs/modules/agents/agent_types/react)
-    """)
+st.write('[![view source code ](https://img.shields.io/badge/view_source_code-gray?logo=github)](https://github.com/shashankdeshpande/langchain-chatbot/blob/master/pages/3_%F0%9F%8C%90_chatbot_with_internet_access.py)')
 
 class ChatbotTools:
 

pages/3_📄_chat_with_your_documents.py pages/4_📄_chat_with_your_documents.pypages/3_📄_chat_with_your_documents.py renamed to pages/4_📄_chat_with_your_documents.py

@@ -14,17 +14,7 @@
 st.set_page_config(page_title="ChatPDF", page_icon="📄")
 st.header('Chat with your documents')
 st.write('Has access to custom documents and can respond to user queries by referring to the content within those documents')
-with st.expander("Implementation details"):
-    st.markdown("""
-    - LLM - [OpenAI](https://python.langchain.com/docs/ecosystem/integrations/openai#llm)
-    - Document Loader - [PyPDFLoader](https://python.langchain.com/docs/modules/data_connection/document_loaders/how_to/pdf#using-pypdf)
-    - Document Splitter - [RecursiveCharacterTextSplitter](https://python.langchain.com/docs/modules/data_connection/document_transformers/text_splitters/recursive_text_splitter)
-    - Embeddings - [HuggingFaceEmbeddings](https://python.langchain.com/docs/modules/data_connection/text_embedding/integrations/huggingfacehub)
-    - Vector store - [DocArrayInMemorySearch](https://python.langchain.com/docs/modules/data_connection/vectorstores/integrations/docarray_in_memory)
-    - Document Retriever - [Vector store-backed retriever: Maximum Marginal Relevance](https://python.langchain.com/docs/modules/data_connection/retrievers/how_to/vectorstore#maximum-marginal-relevance-retrieval)
-    - Memory - [ConversationBufferMemory](https://python.langchain.com/docs/modules/memory/how_to/buffer)
-    - Chain - [ConversationalRetrievalChain](https://python.langchain.com/docs/modules/agents/agent_types/react)
-    """)
+st.write('[![view source code ](https://img.shields.io/badge/view_source_code-gray?logo=github)](https://github.com/shashankdeshpande/langchain-chatbot/blob/master/pages/4_%F0%9F%93%84_chat_with_your_documents.py)')
 
 class CustomDataChatbot: