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feat: Introduce OpenAI LLM provider and update API key handling

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This commit integrates OpenAI as a new Large Language Model (LLM) provider,
expanding the available options for content refinement.

Key changes include:
- Added `set_openai_api_key` to handle OpenAI API key retrieval from
  `config.ini` or environment variables.
- Modified `set_api_key` to dynamically read the LLM provider from `config.ini`
This commit is contained in:
nite
2025-11-12 02:51:18 +11:00
parent ae7c579580
commit 1a867844ce
6 changed files with 446 additions and 77 deletions
Download Patch File Download Diff File Expand all files Collapse all files

30
convert.py Normal file
View File

@@ -0,0 +1,30 @@
import argparse
import os
from pdf_convertor import save_md_images, convert_pdf_to_markdown
from pathlib import Path
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Convert PDF to Markdown.")
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("--pdf-path", type=str, help="Path to the input PDF file.")
group.add_argument("--all", action="store_true", help="Process all pdf.")
args = parser.parse_args()
if args.all:
input_dir = Path("input")
for filename in os.listdir(input_dir):
if not filename.endswith(".pdf"):
continue
pdf_path = input_dir.joinpath(filename)
with open(pdf_path, "rb") as pdf_file:
pdf = pdf_file.read()
md, images = convert_pdf_to_markdown(pdf)
output = Path("output").joinpath(Path(pdf_path).name.removesuffix(".pdf"))
save_md_images(output, md, images)
else:
pdf_path = Path(args.pdf_path)
with open(pdf_path, "rb") as pdf_file:
pdf = pdf_file.read()
md, images = convert_pdf_to_markdown(pdf)
output = Path("output").joinpath(pdf_path.name.removesuffix(".pdf"))
save_md_images(output, md, images)

27
llm.py
View File

@@ -2,11 +2,30 @@ import configparser
import os
def set_api_key(provider: str) -> None:
def set_api_key() -> None:
config = configparser.ConfigParser()
config.read("config.ini")
provider = config.get("llm", "PROVIDER", fallback="gemini")
if provider == "gemini":
set_gemini_api_key()
elif provider == "ollama":
set_ollama_config()
elif provider == "openai":
set_openai_api_key()
def set_openai_api_key() -> None:
config = configparser.ConfigParser()
config.read("config.ini")
openai_api_key = config.get("llm", "OPENAI_API_KEY", fallback=None)
if not os.environ.get("OPENAI_API_KEY"):
if openai_api_key:
os.environ["OPENAI_API_KEY"] = openai_api_key
else:
raise ValueError(
"Error: OPENAI_API_KEY not found in config.ini or environment variables"
)
return
def set_gemini_api_key() -> None:
@@ -41,9 +60,11 @@ def get_model_name() -> str:
config.read("config.ini")
provider = config.get("llm", "PROVIDER", fallback="gemini")
if provider == "gemini":
return config.get("llm", "MODEL_NAME", fallback="gemini-2.5-flash")
return config.get("llm", "GEMINI_MODEL_NAME", fallback="gemini-2.5-flash")
elif provider == "ollama":
return config.get("llm", "MODEL_NAME", fallback="gemma3:latest")
return config.get("llm", "OLLAMA_MODEL_NAME", fallback="gemma3:latest")
elif provider == "openai":
return config.get("llm", "OPENAI_MODEL_NAME", fallback="gpt-5-mini")
return "gemini-2.5-flash" # Default fallback

64
pdf_convertor.py
View File

@@ -13,6 +13,7 @@ from docling_core.types.doc.base import ImageRefMode
from langchain_core.messages import HumanMessage, SystemMessage
from langchain_google_genai import ChatGoogleGenerativeAI
from langchain_ollama import ChatOllama
from langchain_openai import ChatOpenAI
from llm import set_api_key, get_model_name, get_temperature
from io import BytesIO
from pathlib import Path
@@ -120,7 +121,7 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
config.read("config.ini")
provider = config.get("llm", "PROVIDER", fallback="gemini")
set_api_key(provider)
set_api_key()
try:
if provider == "gemini":
@@ -135,6 +136,11 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
num_ctx=256000,
num_predict=-1,
)
elif provider == "openai":
llm = ChatOpenAI(
model=get_model_name(),
temperature=get_temperature(),
)
else:
raise ValueError(f"Unsupported LLM provider: {provider}")
except Exception as e:
@@ -147,21 +153,12 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
# 添加 Markdown
human_message_parts = []
if provider == "gemini":
human_message_parts.append(
{
"type": "media",
"mime_type": "text/markdown",
"data": base64.b64encode(md.encode("UTF-8")).decode("utf-8"),
}
)
elif provider == "ollama":
human_message_parts.append(
{
"type": "text",
"text": md,
}
)
human_message_parts.append(
{
"type": "text",
"text": md,
}
)
# 添加图片
for image_name in images.keys():
@@ -171,21 +168,14 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
"text": f"This is image: '{image_name}':\n",
}
)
if provider == "gemini":
human_message_parts.append(
{
"type": "media",
"mime_type": "image/png",
"data": base64.b64encode(images[image_name]).decode("utf-8"),
}
)
if provider == "ollama":
human_message_parts.append(
{
"type": "image_url",
"image_url": f"data:image/png;base64,{base64.b64encode(images[image_name]).decode('utf-8')}",
}
)
human_message_parts.append(
{
"type": "image_url",
"image_url": {
"url": f"data:image/png;base64,{base64.b64encode(images[image_name]).decode('utf-8')}"
},
}
)
# 添加 PDF
if provider == "gemini":
@@ -202,6 +192,18 @@ def refine_content(md: str, images: dict[str, bytes], pdf: bytes) -> str:
},
]
)
if provider == "openai":
human_message_parts.extend(
[
{
"type": "file",
"file": {
"filename": "origin.pdf",
"file_data": f"data:application/pdf;base64,{base64.b64encode(pdf).decode('utf-8')}",
},
},
]
)
if provider == "ollama":
doc = fitz.open(stream=pdf, filetype="pdf")
for page_num in range(doc.page_count):

1
pyproject.toml
View File

@@ -10,5 +10,6 @@ dependencies = [
"langchain-community>=0.4.1",
"langchain-google-genai>=3.0.0",
"langchain-ollama>=1.0.0",
"langchain-openai>=1.0.2",
"pymupdf>=1.26.6",
]

44
refine.py
View File

@@ -1,23 +1,43 @@
import argparse # New import
import argparse
from pdf_convertor import load_md_file, save_md_images, refine_content
from pathlib import Path
if __name__ == "__main__":
parser = argparse.ArgumentParser(description="Refine Markdown content from PDF.")
parser.add_argument(
"--md-path", type=str, required=True, help="Path to the input Markdown file."
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument("--md-path", type=str, help="Path to the input Markdown file.")
group.add_argument(
"--all",
action="store_true",
help="Process all markdown files in the output directory.",
)
args = parser.parse_args()
md_path = args.md_path
pdf_path = Path("input").joinpath(Path(args.md_path).parent.name + ".pdf")
if args.all:
output_dir = Path("output")
for md_file_path in output_dir.glob("*/index.md"):
md_path = md_file_path
pdf_path = Path("input").joinpath(md_file_path.parent.name + ".pdf")
output = Path(md_path).parent
output.mkdir(parents=True, exist_ok=True)
output = md_file_path.parent
output.mkdir(parents=True, exist_ok=True)
md, images = load_md_file(md_path)
with open(pdf_path, "rb") as pdf_file:
pdf = pdf_file.read()
md = refine_content(md, images, pdf)
md, images = load_md_file(md_path)
with open(pdf_path, "rb") as pdf_file:
pdf = pdf_file.read()
md = refine_content(md, images, pdf)
save_md_images(output, md, images, md_name="index_refined.md")
save_md_images(output, md, images, md_name="index_refined.md")
else:
md_path = Path(args.md_path)
pdf_path = Path("input").joinpath(md_path.parent.name + ".pdf")
output = md_path.parent
output.mkdir(parents=True, exist_ok=True)
md, images = load_md_file(md_path)
with open(pdf_path, "rb") as pdf_file:
pdf = pdf_file.read()
md = refine_content(md, images, pdf)
save_md_images(output, md, images, md_name="index_refined.md")

357
uv.lock generated
View File

@@ -2,9 +2,12 @@ version = 1
revision = 3
requires-python = ">=3.13"
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"python_full_version >= '3.14' and python_full_version < '4' and sys_platform == 'darwin'",
"python_full_version >= '3.14' and python_full_version < '4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
"(python_full_version >= '3.14' and python_full_version < '4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '3.14' and python_full_version < '4' and sys_platform != 'darwin' and sys_platform != 'linux')",
"python_full_version >= '4' and sys_platform == 'darwin'",
"python_full_version >= '4' and platform_machine == 'aarch64' and sys_platform == 'linux'",
"(python_full_version >= '4' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version >= '4' and sys_platform != 'darwin' and sys_platform != 'linux')",
"python_full_version < '3.14' and sys_platform == 'darwin'",
"python_full_version < '3.14' and platform_machine == 'aarch64' and sys_platform == 'linux'",
"(python_full_version < '3.14' and platform_machine != 'aarch64' and sys_platform == 'linux') or (python_full_version < '3.14' and sys_platform != 'darwin' and sys_platform != 'linux')",
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version = "2.61.1"
version = "2.61.2"
source = { registry = "https://pypi.org/simple" }
dependencies = [
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@@ -292,6 +304,7 @@ dependencies = [
{ name = "docling-core", extra = ["chunking"] },
{ name = "docling-ibm-models" },
{ name = "docling-parse" },
{ name = "easyocr", marker = "python_full_version >= '3.14' and python_full_version < '4'" },
{ name = "filetype" },
{ name = "huggingface-hub" },
{ name = "lxml" },
@@ -315,9 +328,9 @@ dependencies = [
{ name = "tqdm" },
{ name = "typer" },
]
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