Add back lcel

docs/examples/langchain/langchain_lcel.py

@@ -0,0 +1,55 @@
+"""
+Demonstrates how to use the `ChatInterface` to create a chatbot using
+[LangChain Expression Language](https://python.langchain.com/docs/expression_language/) (LCEL).
+"""
+
+from operator import itemgetter
+
+import panel as pn
+from langchain.memory import ConversationSummaryBufferMemory
+from langchain_core.output_parsers import StrOutputParser
+from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
+from langchain_core.runnables import RunnableLambda, RunnablePassthrough
+from langchain_openai import ChatOpenAI
+
+pn.extension()
+
+SYSTEM_PROMPT = "Try to be a silly comedian."
+
+
+async def callback(contents, user, instance):
+    message = ""
+    inputs = {"input": contents}
+    async for token in chain.astream(inputs):
+        message += token
+        yield message
+    memory.save_context(inputs, {"output": message})
+
+
+model = ChatOpenAI(model="gpt-3.5-turbo")
+memory = ConversationSummaryBufferMemory(return_messages=True, llm=model)
+prompt = ChatPromptTemplate.from_messages(
+    [
+        ("system", SYSTEM_PROMPT),
+        MessagesPlaceholder(variable_name="history"),
+        ("human", "{input}"),
+    ]
+)
+output_parser = StrOutputParser()
+chain = (
+    RunnablePassthrough.assign(
+        history=RunnableLambda(memory.load_memory_variables) | itemgetter("history")
+    )
+    | prompt
+    | model
+    | output_parser
+)
+
+chat_interface = pn.chat.ChatInterface(
+    pn.chat.ChatMessage(
+        "Offer a topic and ChatGPT will try to be funny!", user="System"
+    ),
+    callback=callback,
+    callback_user="ChatGPT",
+)
+chat_interface.servable()