Advanced RAG: Fine-Tune Embeddings from HuggingFace for RAG
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# pip install beyondllm
# pip install llama-index-embeddings-fastembed
from beyondllm import source,retrieve,embeddings,llms,generator
import os
from getpass import getpass
os.environ['HUGGINGFACE_ACCESS_TOKEN'] = getpass("Enter your HF API token:")
data = source.fit("sample.pdf", dtype="pdf")
embed_model = embeddings.FastEmbedEmbeddings()
retriever = auto_retriever(
data=data, embed_model=embed_model,
type="hybrid", top_k=5, mode="OR"
)
llm = HuggingFaceHubModel(model="mistralai/Mistral-7B-Instruct-v0.2")
pipeline = generator.Generate(question="<replace-with-your-query>",llm=llm,retriever=retriever)
print(pipeline.call())