.env
Generic
TEXT_EMBEDDINGS_MODEL=sentence-transformers/all-MiniLM-L6-v2
TEXT_EMBEDDINGS_MODEL_TYPE=HF # LlamaCpp or HF
USE_MLOCK=false
Ingestion
PERSIST_DIRECTORY=db
DOCUMENTS_DIRECTORY=source_documents
INGEST_CHUNK_SIZE=500
INGEST_CHUNK_OVERLAP=50
INGEST_N_THREADS=1
Generation
MODEL_TYPE=LlamaCpp # GPT4All or LlamaCpp
MODEL_PATH=eachadea/ggml-vicuna-7b-1.1/ggml-vic7b-q5_1.bin
MODEL_TEMP=0.8
MODEL_N_CTX=2048 # Max total size of prompt+answer
MODEL_MAX_TOKENS=1024 # Max size of answer
MODEL_STOP=[STOP]
CHAIN_TYPE=betterstuff
N_RETRIEVE_DOCUMENTS=100 # How many documents to retrieve from the db
N_FORWARD_DOCUMENTS=100 # How many documents to forward to the LLM, chosen among those retrieved
N_GPU_LAYERS=32
Python version
Python 3.10.10
System
Description: Ubuntu 22.04.2 LTS Release: 22.04 Codename: jammy
CASALIOY version
Latest Commit - ee9a4e5
Information
Related Components
Reproduction
I have fed the system a 5000 line csv file, with 30 columns.
Now I asked about overall insight from the data.
I can see in the terminal, it is only seeing top 5 or 7 documents, which is nothing but single row. So, this is giving me answer based on 5 or 7 rows, and thus no actual insight is coming
Point to be noted - I have kept only 1 document in the source documents folder to avoid information overlapping
Expected behavior
Should be able to understand the pattern in the data, and suggest some insights based on it.
.env
Generic
TEXT_EMBEDDINGS_MODEL=sentence-transformers/all-MiniLM-L6-v2
TEXT_EMBEDDINGS_MODEL_TYPE=HF # LlamaCpp or HF
USE_MLOCK=false
Ingestion
PERSIST_DIRECTORY=db
DOCUMENTS_DIRECTORY=source_documents
INGEST_CHUNK_SIZE=500
INGEST_CHUNK_OVERLAP=50
INGEST_N_THREADS=1
Generation
MODEL_TYPE=LlamaCpp # GPT4All or LlamaCpp
MODEL_PATH=eachadea/ggml-vicuna-7b-1.1/ggml-vic7b-q5_1.bin
MODEL_TEMP=0.8
MODEL_N_CTX=2048 # Max total size of prompt+answer
MODEL_MAX_TOKENS=1024 # Max size of answer
MODEL_STOP=[STOP]
CHAIN_TYPE=betterstuff
N_RETRIEVE_DOCUMENTS=100 # How many documents to retrieve from the db
N_FORWARD_DOCUMENTS=100 # How many documents to forward to the LLM, chosen among those retrieved
N_GPU_LAYERS=32
Python version
Python 3.10.10
System
Description: Ubuntu 22.04.2 LTS Release: 22.04 Codename: jammy
CASALIOY version
Latest Commit - ee9a4e5
Information
Related Components
Reproduction
I have fed the system a 5000 line csv file, with 30 columns.
Now I asked about overall insight from the data.
I can see in the terminal, it is only seeing top 5 or 7 documents, which is nothing but single row. So, this is giving me answer based on 5 or 7 rows, and thus no actual insight is coming
Point to be noted - I have kept only 1 document in the source documents folder to avoid information overlapping
Expected behavior
Should be able to understand the pattern in the data, and suggest some insights based on it.