?? ?????? Llama2 ??? ???? Excel ???? ????? ???? ??? ??? ??? ???????.

??? ??? ?? ?

1. ?? ??? ?????.
2. ???? ?? ??? ??? ????.
3. ?? ??? ?? ???? ?? ??????? ?????.
4. ?? Llama2 ??? ???? ??? ???? ??? ????. ?? ??? ?????.

?? ??:

???(≥ 3.8)
?????: langchain, pandas, unstructured, Chroma

1??: ??? ??

%pip install -q unstructured langchain
%pip install -q "unstructured[all-docs]"

2??: Excel ?? ??

import pandas as pd

excel_path = "Book2.xlsx"
if excel_path:
    df = pd.read_excel(excel_path)
    data = df.to_string(index=False)
else:
    print("Upload an Excel file")

3??: ???? ???? ?? ??????? ??

??? ??? ???? ???? ?? ? ??? ?? ? ?? ??? ???? ?????. ??? ??? Chroma ?? ??????? ?????.

from langchain_text_splitters import RecursiveCharacterTextSplitter
from langchain_community.embeddings import OllamaEmbeddings
from langchain_community.vectorstores import Chroma

text_splitter = RecursiveCharacterTextSplitter(chunk_size=7500, chunk_overlap=100)
chunks = text_splitter.split_text(data)

embedding_model = OllamaEmbeddings(model="nomic-embed-text", show_progress=False)
vector_db = Chroma.from_texts(
    texts=chunks, 
    embedding=embedding_model,
    collection_name="local-rag"
)

4??: Llama2 ?? ???

ChatOllama? ???? Llama2 ??? ??? ?????.

from langchain_community.chat_models import ChatOllama

local_model = "llama2"
llm = ChatOllama(model=local_model)

5??: ?? ???? ??

??? Excel ??? ?? ? ??? ???? ?????. ??? ???? ???? ???? ????

from langchain.prompts import PromptTemplate

QUERY_PROMPT = PromptTemplate(
    input_variables=["question"],
    template="""You are an AI assistant. Answer the user's questions based on the column names: 
    Id, order_id, name, sales, refund, and status. Original question: {question}"""
)

6??: ??? ??

Llama2 ??? ??? ??? ? ??? ?? ???????? ?? ??? ????? ???? ?????.

from langchain.retrievers.multi_query import MultiQueryRetriever

retriever = MultiQueryRetriever.from_llm(
    vector_db.as_retriever(), 
    llm,
    prompt=QUERY_PROMPT
)

7??: ?? ?? ??

?? ??? ??? ?????.

1. ????? ???? ???
2. ??? ??? ??? ???? ????
3. ??? ???? Llama2 ??.
4. ?? ??? ???? ?? ??.

from langchain.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough
from langchain_core.output_parsers import StrOutputParser

template = """Answer the question based ONLY on the following context:
{context}
Question: {question}
"""

prompt = ChatPromptTemplate.from_template(template)

chain = (
    {"context": retriever, "question": RunnablePassthrough()}
    | prompt
    | llm
    | StrOutputParser()
)

8??: ????

?? ??? ??? ?????! ??? ?? ?? ??? ???? ??? ??? ????.

raw_result = chain.invoke("How many rows are there?")
final_result = f"{raw_result}\n\nIf you have more questions, feel free to ask!"
print(final_result)

?? ??

?? Excel ???? ? ??? ???? ? ?? ??? ??? ????.

Based on the provided context, there are 10 rows in the table.
If you have more questions, feel free to ask!

??:

? ?? ??? ???? Llama2 ??? ??? ??? ???? Excel ???? ??? ??? ??? ????. ??? ??? ?? ?? ???? ?? ??? ??? ?? ????? ??? ?? ??? ? ????!

? LinkedIn?? UI ?? ??? ?????.

BChat Excel ??: Excel ?? ?? ??? ?? ??? AI ?? ??

? ??? Excel? ???? LlamaChat?? ??? ?? ??]? ?? ?????. ??? ??? PHP ??? ????? ?? ?? ??? ?????!