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Abhimanyu Aryan 🧞
A
Abhimanyu Aryan 🧞
Offline, last seen 3 months ago
Joined September 25, 2024
also what's wrong with this?
5 comments
L
A
Is their a simple implementation of that in isolation? This codebase is quite messy for head as a starting point. I would like to understand the basic concept
11 comments
A
g
question how is colbert producing embeddings using colbertv2 in llamaindex? Are you using transformers.jl for that?
1 comment
T
Hi,

I am new to RAG and basically I pulled an article from about SQL Injection from Wikipedia and wrote the code following the llama index tutorials from deeplearning

Plain Text
documents = SimpleDirectoryReader(
    input_files = ["./docs/sql-injection.txt"]
).load_data()

document = Document(text="\n\n".join([doc.text for doc in documents]))

sentence_index = build_sentence_window_index(
    document,
    llm,
    embed_model="local:BAAI/bge-small-en-v1.5",
    save_dir="sentence_index"
)

sentence_window_engine = get_sentence_window_query_engine(sentence_index)

window_response = sentence_window_engine.query("""
        what is sql injection?
""")
print(str(window_response))


And it return me


The context does not provide information on what SQL injection is.

What is happening here?

When I pass it research paper in pdf format. It reads the pdf and returns me the answer. What's wrong with SQL_injection.txt scenario?
7 comments
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T
How is colbert v2 implemented in llamaIndex. Where can I see code?
2 comments
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I am working on deep learning ai course. Can anyone help me fix these imports? I think the API is updated now?

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from llama_index import ServiceContext, VectorStoreIndex, StorageContext
from llama_index.node_parser import SentenceWindowNodeParser
from llama_index.indices.postprocessor import MetadataReplacementPostProcessor
from llama_index.indices.postprocessor import SentenceTransformerRerank
from llama_index import load_index_from_storage
4 comments
A
T
why would one use mongo vector database instead of VectorStoreIndex?
1 comment
L