init

Dockerfile

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+FROM python:3.9
+RUN useradd -m -u 1000 user
+USER user
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+WORKDIR $HOME/app
+COPY --chown=user . $HOME/app
+COPY ./requirements.txt ~/app/requirements.txt
+RUN pip install -r requirements.txt
+COPY . .
+CMD ["chainlit", "run", "app.py", "--port", "7860"]

app.py

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+
+import chainlit as cl
+import os
+from dotenv import load_dotenv
+from langchain_openai import OpenAIEmbeddings
+from langchain_core.prompts import ChatPromptTemplate
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.vectorstores import Pinecone
+from operator import itemgetter
+from langchain.schema.runnable import RunnablePassthrough
+from langchain_openai import ChatOpenAI
+from langchain.schema.runnable.config import RunnableConfig
+from langchain_core.output_parsers import StrOutputParser
+from langchain.text_splitter import RecursiveCharacterTextSplitter
+from langchain_community.document_loaders import UnstructuredPDFLoader
+from transformers import AutoTokenizer, AutoModelForCausalLM,BitsAndBytesConfig
+import torch
+from langchain_community.llms.huggingface_pipeline import HuggingFacePipeline
+
+
+load_dotenv()
+
+
+RAG_PROMPT = """
+
+CONTEXT:
+{context}
+
+QUERY:
+{question}
+
+You house builder and can only provide your answers from the context. 
+You can only provide a response in danish
+
+Don't tell in your response that you are getting it from the context.
+
+"""
+
+
+text_splitter = RecursiveCharacterTextSplitter(
+    chunk_size = 1800,
+    chunk_overlap = 50,
+    length_function=len,
+    is_separator_regex=True,
+    separators=[
+        "\n\n",
+        "\n",
+        " ",
+        ".",
+        ",",
+        "\u200B",
+        "\uff0c",
+        "\u3001",
+        "\uff0e",
+        "\u3002",
+        "",
+    ],
+)
+
+bnb_config = BitsAndBytesConfig(
+    load_in_4bit=True,
+    bnb_4bit_quant_type="nf4",
+    bnb_double_quant=True,
+    bnb_4bit_compute_dtype=torch.float16,
+)
+
+
+# tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3-mini-4k-instruct", 
+#                                           trust_remote_code=True,
+#                                           quantization_config=bnb_config,
+#                                           attn_implementation='eager',
+#                                           device_map='auto',)
+# model = AutoModelForCausalLM.from_pretrained("microsoft/Phi-3-mini-4k-instruct", trust_remote_code=True)
+
+
+# hf = HuggingFacePipeline.from_model_id(
+#     model_id="microsoft/Phi-3-mini-4k-instruct",
+#     task="text-generation",
+#     device_map="auto",
+#     pipeline_kwargs={"max_new_tokens": 10},
+# )
+
+
+loader = UnstructuredPDFLoader("./br_syvoghalvfjerds.pdf")
+data = loader.load_and_split(text_splitter)
+
+embedding_model = OpenAIEmbeddings(model="text-embedding-3-small")
+
+vector_store = Pinecone.from_documents(data, embedding_model, index_name=os.environ.get('index'))
+retriever = vector_store.as_retriever()
+
+rag_prompt = ChatPromptTemplate.from_template(RAG_PROMPT)
+
+model = ChatOpenAI(model="gpt-3.5-turbo")
+
+@cl.on_chat_start
+async def main():
+    mecanic_qa_chain = ""
+    mecanic_qa_chain = (
+        {"context": itemgetter("question") | retriever, "question": itemgetter("question")}
+        | RunnablePassthrough.assign(context=itemgetter("context"))
+        | rag_prompt | model | StrOutputParser()
+    )
+
+    cl.user_session.set("runnable", mecanic_qa_chain)
+
+@cl.on_message
+async def on_message(message: cl.Message):
+    runnable = cl.user_session.get("runnable")
+    msg = cl.Message(content="")
+
+    async for chunk in runnable.astream(
+        {"question":message.content},
+        config=RunnableConfig(callbacks=[cl.LangchainCallbackHandler()]),
+    ):
+        await msg.stream_token(chunk)

chainlit.md

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+welcome to bygningsreglementer!

requirements.txt

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+chainlit==0.7.700
+cohere==4.37
+openai
+python-dotenv==1.0.0
+langchain
+langchain-community
+langchain-openai
+pdfminer
+pinecone-client
+unstructured
+pdf2image
+transformers
+bitsandbytes