# Pinned to the version verified locally (Python 3.13). When deploying, set the
# HF Space README `sdk_version` to match. If the Space's Gradio SDK only supports
# <=5.x, repin here AND move `theme` back into gr.Blocks(...) in app.py.
#
# This is the LIGHT set the HF Space installs for the stub-mode demo (the default).
# Heavy real-model deps (torch/transformers/...) live in requirements-model.txt so
# the Space build stays fast — nothing heavy is imported at module load in stub mode
# (llm.py imports torch/transformers only inside _load(); pypdf is imported lazily).
#
# gradio is pinned to 6.10.0 because the custom-frontend server (server.py) uses
# `gradio.Server`. On newer gradio (6.17.x) a custom gradio.Server breaks under the
# Space runtime — the app starts but the Space flips to RUNTIME_ERROR. 6.10.0 is a
# version gradio's `Server` examples ship and runs cleanly here. (The official
# MiniCPM-V-4.6 demo uses 6.14.0 with the same pattern, so 6.10–6.14 is the known-
# good band; 6.10.0 is what we verified.)
#
# It also resolves with the real model: 6.10.0 allows huggingface-hub <2.0,>=0.33.5,
# i.e. hub 1.x, which MiniCPM-V 4.6's modern transformers (5.x) wants. (The old
# huggingface-hub<1.0 constraint was specific to the retired MiniCPM4.1-8B text
# model and no longer applies — see requirements-model.txt.)
#
# A gradio-SDK Space force-installs sdk_version's gradio for the WHOLE Space, so
# stub + real-model share one gradio. Keep this in lockstep with the README
# `sdk_version` and requirements-model.txt.
gradio==6.10.0
# server.py (custom frontend) — FastAPI/uvicorn are pulled in by gradio, but we
# pin them explicitly so the Space is self-documenting and robust to drift.
fastapi
uvicorn
# Needed for the PDF upload endpoint.
python-multipart
# PDF text extraction (pure-python, lightweight).
pypdf

# --- Real model (MiniCPM-V 4.6), folded in for the LIVE real-model deploy -----
# A gradio Space installs THIS file (not requirements-model.txt), so the heavy
# deps live here now that the Space serves the real model on ZeroGPU with
# RECALL_STUB=0. Verified to resolve with gradio==6.10.0 (HF Job, l4x1):
# transformers 5.12 + huggingface-hub 1.19 + torch 2.12. See requirements-model.txt
# for the rationale; keep the two in lockstep.
transformers>=4.44.0   # native MiniCPMV4_6ForConditionalGeneration (latest 5.x)
torch
torchvision            # vision tower; must match torch
accelerate
sentencepiece          # MiniCPM-V tokenizer backend
pillow                 # images passed to the model as PIL.Image
PyMuPDF                # render scanned/image-only PDF pages -> images
spaces                 # HF ZeroGPU @spaces.GPU decorator