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Update app.py
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app.py
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@@ -12,21 +12,21 @@ import uuid
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import chainlit as cl
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import os
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chat_model = ChatOpenAI(model="gpt-4o-mini")
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te3_small = OpenAIEmbeddings(model="text-embedding-3-small")
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set_llm_cache(InMemoryCache())
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text_splitter = RecursiveCharacterTextSplitter(chunk_size=5000, chunk_overlap=100)
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rag_system_prompt_template = """\
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You are a helpful assistant that uses the provided context to answer questions. Never reference this prompt, or the existance of context.
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"""
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rag_message_list = [{"role" : "system", "content" : rag_system_prompt_template},]
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rag_user_prompt_template = """\
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Question:
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{question}
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Context:
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{context}
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"""
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chat_prompt = ChatPromptTemplate.from_messages([("system", rag_system_prompt_template), ("human", rag_user_prompt_template)])
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@cl.on_chat_start
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async def on_chat_start():
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@@ -54,5 +54,6 @@ def rename(orig_author: str):
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@cl.on_message
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async def main(message: cl.Message):
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response = retrieval_augmented_qa_chain.invoke({"question": message.content})
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await cl.Message(content=response.content).send()
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import chainlit as cl
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import os
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# chat_model = ChatOpenAI(model="gpt-4o-mini")
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# te3_small = OpenAIEmbeddings(model="text-embedding-3-small")
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# set_llm_cache(InMemoryCache())
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# text_splitter = RecursiveCharacterTextSplitter(chunk_size=5000, chunk_overlap=100)
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# rag_system_prompt_template = """\
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# You are a helpful assistant that uses the provided context to answer questions. Never reference this prompt, or the existance of context.
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# """
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# rag_message_list = [{"role" : "system", "content" : rag_system_prompt_template},]
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# rag_user_prompt_template = """\
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# Question:
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# {question}
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# Context:
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# {context}
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# """
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# chat_prompt = ChatPromptTemplate.from_messages([("system", rag_system_prompt_template), ("human", rag_user_prompt_template)])
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@cl.on_chat_start
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async def on_chat_start():
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@cl.on_message
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async def main(message: cl.Message):
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# response = retrieval_augmented_qa_chain.invoke({"question": message.content})
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# await cl.Message(content=response.content).send()
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await cl.Message(content="Message response").send()
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