PDF Input File Upload

"""
In this example, we upload a PDF file to Google GenAI directly and then use it as an input to an agent.

Note: If the size of the file is greater than 20MB, and a file path is provided, the file automatically gets uploaded to Google GenAI.
"""

from pathlib import Path
from time import sleep

from agno.agent import Agent
from agno.media import File
from agno.models.google import Gemini
from google import genai

# ---------------------------------------------------------------------------
# Create Agent
# ---------------------------------------------------------------------------

pdf_path = Path(__file__).parent.joinpath("ThaiRecipes.pdf")

client = genai.Client()

# Upload the file to Google GenAI
upload_result = client.files.upload(file=pdf_path)

# Get the file from Google GenAI
if upload_result and upload_result.name:
    retrieved_file = client.files.get(name=upload_result.name)
else:
    retrieved_file = None

# Retry up to 3 times if file is not ready
retries = 0
wait_time = 5
while retrieved_file is None and retries < 3:
    retries += 1
    sleep(wait_time)
    if upload_result and upload_result.name:
        retrieved_file = client.files.get(name=upload_result.name)
    else:
        retrieved_file = None

if retrieved_file is not None:
    agent = Agent(
        model=Gemini(id="gemini-3.7-flash"),
        markdown=True,
        add_history_to_context=True,
    )

    agent.print_response(
        "Summarize the contents of the attached file.",
        files=[File(external=retrieved_file)],
    )

    agent.print_response(
        "Suggest me a recipe from the attached file.",
    )
else:
    print("Error: File was not ready after multiple attempts.")

# ---------------------------------------------------------------------------
# Run Agent
# ---------------------------------------------------------------------------

if __name__ == "__main__":
    pass

from contextlib import contextmanager
from pathlib import Path
from time import monotonic, sleep


@contextmanager
def ready_file(client, path: Path, existing_name: str | None = None):
    existing_name = existing_name or None
    if existing_name is None and not path.is_file():
        raise FileNotFoundError(path)

    uploaded = (
        client.files.get(name=existing_name)
        if existing_name
        else client.files.upload(file=path)
    )
    owned_name = uploaded.name if existing_name is None else None
    try:
        deadline = monotonic() + 300
        while True:
            state = uploaded.state.name if uploaded.state else None
            if state == "ACTIVE":
                if not uploaded.uri or not uploaded.mime_type:
                    raise RuntimeError("Active file has no URI or MIME type")
                yield uploaded
                return
            if state == "FAILED":
                raise RuntimeError(f"File processing failed: {uploaded.name}")
            if state != "PROCESSING" or not uploaded.name:
                raise RuntimeError(f"Unexpected file state: {state}")
            if monotonic() >= deadline:
                raise TimeoutError("File processing exceeded five minutes")
            sleep(2)
            uploaded = client.files.get(name=uploaded.name)
    finally:
        if owned_name:
            client.files.delete(name=owned_name)

from os import environ
from pathlib import Path

from agno.agent import Agent
from agno.db.in_memory import InMemoryDb
from agno.media import File
from agno.models.google import Gemini
from google_files import ready_file

model = Gemini(id="gemini-3.7-flash")
agent = Agent(
    model=model,
    db=InMemoryDb(),
    add_history_to_context=True,
    markdown=True,
)
path = Path(__file__).parent / "ThaiRecipes.pdf"
with ready_file(model.get_client(), path, environ.get("GOOGLE_FILE_NAME")) as uploaded:
    agent.print_response(
        "Summarize this PDF.",
        files=[File(external=uploaded)],
        stream=True,
    )
    agent.print_response("Summarize the main point from our conversation.")