Spaces:
Running
Running
File size: 2,081 Bytes
527151b 33adc14 527151b 33adc14 527151b 0f736a4 527151b 33adc14 527151b 33adc14 527151b 33adc14 527151b 33adc14 527151b 0f736a4 527151b 33adc14 527151b 33adc14 527151b 33adc14 0f736a4 527151b |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 |
log_dir: "storage/logs" # str
log_chunk_dir: "storage/logs/chunks" # str
device: "cpu" # str [cuda, cpu]
vectorstore:
load_from_HF: False # bool
reparse_files: True # bool
data_path: "storage/data" # str
url_file_path: "storage/data/urls.txt" # str
expand_urls: False # bool
db_option: "FAISS" # str [FAISS, Chroma, RAGatouille, RAPTOR]
db_path: "vectorstores" # str
model: "sentence-transformers/all-MiniLM-L6-v2" # str [sentence-transformers/all-MiniLM-L6-v2, text-embedding-ada-002']
search_top_k: 5 # int
score_threshold: 0.2 # float
faiss_params: # Not used as of now
index_path: "vectorstores/faiss.index" # str
index_type: "Flat" # str [Flat, HNSW, IVF]
index_dimension: 384 # int
index_nlist: 100 # int
index_nprobe: 10 # int
colbert_params:
index_name: "new_idx" # str
llm_params:
llm_arch: "langchain" # [langchain]
use_history: True # bool
generate_follow_up: False # bool
memory_window: 3 # int
llm_style: "Normal" # str [Normal, ELI5]
llm_loader: "gpt-4o-mini" # str [local_llm, gpt-3.5-turbo-1106, gpt-4, gpt-4o-mini]
openai_params:
temperature: 0.7 # float
local_llm_params:
temperature: 0.7 # float
repo_id: "TheBloke/TinyLlama-1.1B-Chat-v1.0-GGUF" # HuggingFace repo id
filename: "tinyllama-1.1b-chat-v1.0.Q5_0.gguf" # Specific name of gguf file in the repo
model_path: "storage/models/tinyllama-1.1b-chat-v1.0.Q5_0.gguf" # Path to the model file
stream: True # bool
pdf_reader: "pymupdf" # str [llama, pymupdf, gpt]
chat_logging:
log_chat: True # bool
platform: "literalai"
callbacks: True # bool
splitter_options:
use_splitter: True # bool
split_by_token: True # bool
remove_leftover_delimiters: True # bool
remove_chunks: False # bool
chunking_mode: "fixed" # str [fixed, semantic]
chunk_size: 500 # int
chunk_overlap: 50 # int
chunk_separators: ["\n\n", "\n", " ", ""] # list of strings
front_chunks_to_remove: null # int or None
last_chunks_to_remove: null # int or None
delimiters_to_remove: ['\t', '\n', " ", " "] # list of strings
|