pip install py-zerox

from pyzerox import zerox
import os
import json
import asyncio


### Model Setup (Use only Vision Models) Refer: https://docs.litellm.ai/docs/providers ###


## placeholder for additional model kwargs which might be required for some models
kwargs = {}


## system prompt to use for the vision model
custom_system_prompt = None


# to override
# custom_system_prompt = "For the below pdf page, do something..something..." ## example


###################### Example for OpenAI ######################
model = "gpt-4o-mini" ## openai model
os.environ["OPENAI_API_KEY"] = "" ## your-api-key




###################### Example for Azure OpenAI ######################
model = "azure/gpt-4o-mini" ## "azure/<your_deployment_name>" -> format <provider>/<model>
os.environ["AZURE_API_KEY"] = "" # "your-azure-api-key"
os.environ["AZURE_API_BASE"] = "" # "https://example-endpoint.openai.azure.com"
os.environ["AZURE_API_VERSION"] = "" # "2023-05-15"




###################### Example for Gemini ######################
model = "gemini/gpt-4o-mini" ## "gemini/<gemini_model>" -> format <provider>/<model>
os.environ['GEMINI_API_KEY'] = "" # your-gemini-api-key




###################### Example for Anthropic ######################
model="claude-3-opus-20240229"
os.environ["ANTHROPIC_API_KEY"] = "" # your-anthropic-api-key


###################### Vertex ai ######################
model = "vertex_ai/gemini-1.5-flash-001" ## "vertex_ai/<model_name>" -> format <provider>/<model>
## GET CREDENTIALS
## RUN ##
# !gcloud auth application-default login - run this to add vertex credentials to your env
## OR ##
file_path = 'path/to/vertex_ai_service_account.json'


# Load the JSON file
with open(file_path, 'r') as file:
    vertex_credentials = json.load(file)


# Convert to JSON string
vertex_credentials_json = json.dumps(vertex_credentials)


vertex_credentials=vertex_credentials_json


## extra args
kwargs = {"vertex_credentials": vertex_credentials}


###################### For other providers refer: https://docs.litellm.ai/docs/providers ######################


# Define main async entrypoint
async def main():
    file_path = "https://omni-demo-data.s3.amazonaws.com/test/cs101.pdf" ## local filepath and file URL supported


    ## process only some pages or all
    select_pages = None ## None for all, but could be int or list(int) page numbers (1 indexed)


    output_dir = "./output_test" ## directory to save the consolidated markdown file
    result = await zerox(file_path=file_path, model=model, output_dir=output_dir,
                        custom_system_prompt=custom_system_prompt,select_pages=select_pages, kwargs)
    return result




# run the main function:
result = asyncio.run(main())


# print markdown result
print(result)

async def zerox(
    cleanup: bool = True,
    concurrency: int = 10,
    file_path: Optional[str] = "",
    maintain_format: bool = False,
    model: str = "gpt-4o-mini",
    output_dir: Optional[str] = None,
    temp_dir: Optional[str] = None,
    custom_system_prompt: Optional[str] = None,
    select_pages: Optional[Union[int, Iterable[int]]] = None,
    kwargs
) -> ZeroxOutput:
  ...