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[dev] add support for .xml files

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zoazhyga
2024-08-10 19:28:22 +02:00
parent 0dc4e2781e
commit b4149c8d87
10 changed files with 329 additions and 37 deletions
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2
Makefile
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@@ -39,7 +39,7 @@ dev-windows:
(set PGPT_PROFILES=local & poetry run python -m uvicorn private_gpt.main:app --reload --port 8001)
dev:
PYTHONUNBUFFERED=1 PGPT_PROFILES=local poetry run python -m uvicorn private_gpt.main:app --reload --port 8001
PYTHONUNBUFFERED=1 PGPT_PROFILES=huglama poetry run python -m uvicorn private_gpt.main:app --reload --port 8001
########################################################################################################################
# Misc

37
experiments/llama_index.ipynb Normal file
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@@ -0,0 +1,37 @@
{
"cells": [
{
"cell_type": "code",
"execution_count": null,
"id": "initial_id",
"metadata": {
"collapsed": true
},
"outputs": [],
"source": [
""
]
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.6"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

217
poetry.lock generated
View File

@@ -2642,6 +2642,21 @@ striprtf = ">=0.0.26,<0.0.27"
[package.extras]
pymupdf = ["pymupdf (>=1.23.21,<2.0.0)"]
[[package]]
name = "llama-index-readers-smart-pdf-loader"
version = "0.1.4"
description = "llama-index readers smart_pdf_loader integration"
optional = false
python-versions = "<4.0,>=3.8.1"
files = [
{file = "llama_index_readers_smart_pdf_loader-0.1.4-py3-none-any.whl", hash = "sha256:ba21a0ba8b46cd5a5f1205b4601147e469dccccac57de2902cab44794047f57a"},
{file = "llama_index_readers_smart_pdf_loader-0.1.4.tar.gz", hash = "sha256:40b135750612b175eea16297749946a82238776b398683fc6b1a605e7208300d"},
]
[package.dependencies]
llama-index-core = ">=0.10.1,<0.11.0"
llmsherpa = ">=0.1.4,<0.2.0"
[[package]]
name = "llama-index-storage-docstore-postgres"
version = "0.1.3"
@@ -2765,6 +2780,178 @@ grpcio = ">=1.60.0,<2.0.0"
llama-index-core = ">=0.10.1,<0.11.0"
qdrant-client = ">=1.7.1"
[[package]]
name = "llmsherpa"
version = "0.1.4"
description = "Strategic APIs to Accelerate LLM Use Cases"
optional = false
python-versions = "*"
files = [
{file = "llmsherpa-0.1.4-py3-none-any.whl", hash = "sha256:88a651eacf221a997a9a9795903fbb70ddb211cd2e82831507de01284c917667"},
{file = "llmsherpa-0.1.4.tar.gz", hash = "sha256:18789840ded3d7e37db6a5c668dac2b0a58f20e426beaed3e60554dee0a5ecb0"},
]
[package.dependencies]
urllib3 = "*"
[[package]]
name = "lxml"
version = "5.2.2"
description = "Powerful and Pythonic XML processing library combining libxml2/libxslt with the ElementTree API."
optional = false
python-versions = ">=3.6"
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{file = "lxml-5.2.2.tar.gz", hash = "sha256:bb2dc4898180bea79863d5487e5f9c7c34297414bad54bcd0f0852aee9cfdb87"},
]
[package.extras]
cssselect = ["cssselect (>=0.7)"]
html-clean = ["lxml-html-clean"]
html5 = ["html5lib"]
htmlsoup = ["BeautifulSoup4"]
source = ["Cython (>=3.0.10)"]
[[package]]
name = "lz4"
version = "4.3.3"
@@ -4754,6 +4941,23 @@ files = [
[package.extras]
dev = ["atomicwrites (==1.4.1)", "attrs (==23.2.0)", "coverage (==7.4.1)", "hatch", "invoke (==2.2.0)", "more-itertools (==10.2.0)", "pbr (==6.0.0)", "pluggy (==1.4.0)", "py (==1.11.0)", "pytest (==8.0.0)", "pytest-cov (==4.1.0)", "pytest-timeout (==2.2.0)", "pyyaml (==6.0.1)", "ruff (==0.2.1)"]
[[package]]
name = "python-pptx"
version = "1.0.2"
description = "Create, read, and update PowerPoint 2007+ (.pptx) files."
optional = false
python-versions = ">=3.8"
files = [
{file = "python_pptx-1.0.2-py3-none-any.whl", hash = "sha256:160838e0b8565a8b1f67947675886e9fea18aa5e795db7ae531606d68e785cba"},
{file = "python_pptx-1.0.2.tar.gz", hash = "sha256:479a8af0eaf0f0d76b6f00b0887732874ad2e3188230315290cd1f9dd9cc7095"},
]
[package.dependencies]
lxml = ">=3.1.0"
Pillow = ">=3.3.2"
typing-extensions = ">=4.9.0"
XlsxWriter = ">=0.5.7"
[[package]]
name = "pytz"
version = "2024.1"
@@ -6477,6 +6681,17 @@ files = [
{file = "wrapt-1.16.0.tar.gz", hash = "sha256:5f370f952971e7d17c7d1ead40e49f32345a7f7a5373571ef44d800d06b1899d"},
]
[[package]]
name = "xlsxwriter"
version = "3.2.0"
description = "A Python module for creating Excel XLSX files."
optional = false
python-versions = ">=3.6"
files = [
{file = "XlsxWriter-3.2.0-py3-none-any.whl", hash = "sha256:ecfd5405b3e0e228219bcaf24c2ca0915e012ca9464a14048021d21a995d490e"},
{file = "XlsxWriter-3.2.0.tar.gz", hash = "sha256:9977d0c661a72866a61f9f7a809e25ebbb0fb7036baa3b9fe74afcfca6b3cb8c"},
]
[[package]]
name = "yarl"
version = "1.9.4"
@@ -6733,4 +6948,4 @@ vector-stores-qdrant = ["llama-index-vector-stores-qdrant"]
[metadata]
lock-version = "2.0"
python-versions = ">=3.11,<3.12"
content-hash = "7ec5345f582d22af25859e961a76dddb92efe5c58dab21a2a3ba0403f20e44f5"
content-hash = "205a43fecaf7521b9673728e72c043d1ce878ce3e53ebc48292bd45f64090471"

2
private_gpt/__init__.py
View File

@@ -4,7 +4,7 @@ import logging
import os
# Set to 'DEBUG' to have extensive logging turned on, even for libraries
ROOT_LOG_LEVEL = "INFO"
ROOT_LOG_LEVEL = "DEBUG"
PRETTY_LOG_FORMAT = (
"%(asctime)s.%(msecs)03d [%(levelname)-8s] %(name)+25s - %(message)s"

5
private_gpt/__main__.py
View File

@@ -8,4 +8,7 @@ from private_gpt.settings.settings import settings
# Set log_config=None to do not use the uvicorn logging configuration, and
# use ours instead. For reference, see below:
# https://github.com/tiangolo/fastapi/discussions/7457#discussioncomment-5141108
uvicorn.run(app, host="0.0.0.0", port=settings().server.port, log_config=None)
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=settings().server.port, log_config=None)

65
private_gpt/components/ingest/ingest_helper.py
View File

@@ -10,7 +10,23 @@ logger = logging.getLogger(__name__)
# Inspired by the `llama_index.core.readers.file.base` module
def _try_loading_included_file_formats() -> dict[str, type[BaseReader]]:
def _try_loading_included_file_formats(
llmsherpa_api_url: str = None,
) -> dict[str, type[BaseReader]]:
simple_pdf_extractor = None
if llmsherpa_api_url is not None:
try:
from llama_index.readers.smart_pdf_loader import SmartPDFLoader
# llmsherpa_api_url = "http://localhost:5010/api/parseDocument?renderFormat=all&useNewIndentParser=yes"
simple_pdf_extractor = SmartPDFLoader(
llmsherpa_api_url=llmsherpa_api_url,
)
except ImportError as e:
raise ImportError(
"`llama-index-readers-smart-pdf-loader` package not found"
) from e
try:
from llama_index.readers.file.docs import ( # type: ignore
DocxReader,
@@ -31,31 +47,36 @@ def _try_loading_included_file_formats() -> dict[str, type[BaseReader]]:
raise ImportError("`llama-index-readers-file` package not found") from e
default_file_reader_cls: dict[str, type[BaseReader]] = {
".hwp": HWPReader,
".pdf": PDFReader,
".docx": DocxReader,
".pptx": PptxReader,
".ppt": PptxReader,
".pptm": PptxReader,
".jpg": ImageReader,
".png": ImageReader,
".jpeg": ImageReader,
".mp3": VideoAudioReader,
".mp4": VideoAudioReader,
".csv": PandasCSVReader,
".epub": EpubReader,
".md": MarkdownReader,
".mbox": MboxReader,
".ipynb": IPYNBReader,
".hwp": HWPReader(),
# ".pdf": simple_pdf_extractor if simple_pdf_extractor else PDFReader,
".pdf": PDFReader(),
".docx": simple_pdf_extractor if simple_pdf_extractor else DocxReader(),
".pptx": PptxReader(),
".ppt": PptxReader(),
".pptm": PptxReader(),
".jpg": ImageReader(),
".png": ImageReader(),
".jpeg": ImageReader(),
# ".mp3": VideoAudioReader(),
# ".mp4": VideoAudioReader(),
".csv": simple_pdf_extractor if simple_pdf_extractor else PandasCSVReader(),
".xls": simple_pdf_extractor if simple_pdf_extractor else None,
".xlsx": simple_pdf_extractor if simple_pdf_extractor else None,
".epub": EpubReader(),
".md": MarkdownReader(),
".mbox": MboxReader(),
".ipynb": IPYNBReader(),
}
return default_file_reader_cls
# Patching the default file reader to support other file types
FILE_READER_CLS = _try_loading_included_file_formats()
FILE_READER_CLS = _try_loading_included_file_formats(
"http://localhost:5010/api/parseDocument?renderFormat=all&useNewIndentParser=yes"
)
FILE_READER_CLS.update(
{
".json": JSONReader,
".json": JSONReader(),
}
)
@@ -91,8 +112,10 @@ class IngestionHelper:
string_reader = StringIterableReader()
return string_reader.load_data([file_data.read_text()])
logger.debug("Specific reader found for extension=%s", extension)
return reader_cls().load_data(file_data)
logger.debug(
f"Specific reader found for extension=%s, {reader_cls=}", extension
)
return reader_cls.load_data(file_data.as_posix())
@staticmethod
def _exclude_metadata(documents: list[Document]) -> None:

3
pyproject.toml
View File

@@ -67,6 +67,9 @@ ollama = {version ="^0.3.0", optional = true}
# Optional HF Transformers
einops = {version = "^0.8.0", optional = true}
llama-index-readers-smart-pdf-loader = "^0.1.4"
python-pptx = "^1.0.2"
pillow = "^10.4.0"
[tool.poetry.extras]
ui = ["gradio", "ffmpy"]

22
settings-huglama.yaml
View File

@@ -1,18 +1,30 @@
server:
env_name: ${APP_ENV:huglama}
data:
local_data_folder: local_data/private_gpt
local_ingestion:
enabled: ${LOCAL_INGESTION_ENABLED:true}
allow_ingest_from: ["local_data/input_raw"]
llm:
mode: ollama
max_new_tokens: 10000
context_window: 100000
context_window: 12800
temperature: 0.1
embedding:
mode: huggingface
ingest_mode: parallel
ingest_mode: simple
# count_workers: 2
vectorstore:
database: qdrant
database: postgres
qdrant:
path: local_data/private_gpt/qdrant
postgres:
host: localhost
port: 5432
database: vector_db
user: user
password: pass31415
schema_name: private_gpt

1
settings-mock.yaml
View File

@@ -1,7 +1,6 @@
server:
env_name: ${APP_ENV:mock}
# This configuration allows you to use GPU for creating embeddings while avoiding loading LLM into vRAM
llm:
mode: mock

12
settings.yaml
View File

@@ -18,7 +18,7 @@ server:
data:
local_ingestion:
enabled: ${LOCAL_INGESTION_ENABLED:false}
enabled: ${LOCAL_INGESTION_ENABLED:true}
allow_ingest_from: ["*"]
local_data_folder: local_data/private_gpt
@@ -50,16 +50,16 @@ llm:
mode: llamacpp
prompt_style: "llama3"
# Should be matching the selected model
max_new_tokens: 512
context_window: 3900
max_new_tokens: 10000
context_window: 100000
# Select your tokenizer. Llama-index tokenizer is the default.
# tokenizer: meta-llama/Meta-Llama-3.1-8B-Instruct
# tokenizer: meta-llama/Meta-Llama-3.1-8B-Instruct
temperature: 0.1 # The temperature of the model. Increasing the temperature will make the model answer more creatively. A value of 0.1 would be more factual. (Default: 0.1)
rag:
similarity_top_k: 20
similarity_top_k: 30
#This value controls how many "top" documents the RAG returns to use in the context.
#similarity_value: 0.45
similarity_value: 0.45
#This value is disabled by default. If you enable this settings, the RAG will only use articles that meet a certain percentage score.
rerank:
enabled: false