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requirements-model.txt

@@ -1,48 +1,15 @@
-# Real-model dependencies — only needed when RECALL_STUB=0.
-# Superset of the light demo set. Install with:
-#     pip install -r requirements-model.txt
+# Real-model dependencies.
 #
-# Target: openbmb/MiniCPM-V-4.6 (multimodal, ~9B) to read image-only / scanned
-# PDFs. Aligned with the official Space (openbmb/MiniCPM-V-4.6-Demo), which runs
-# the same custom-frontend gradio.Server + ZeroGPU pattern as this app.
+# These are now FOLDED INTO requirements.txt, because the Space serves the live
+# MiniCPM-V 4.6 model (ZeroGPU, RECALL_STUB=0) and a Gradio Space installs
+# requirements.txt — not this file. So requirements.txt is the single source of
+# truth for the real-model deps (transformers 5.x, torch, torchvision, accelerate,
+# sentencepiece, pillow, PyMuPDF, spaces); this file just installs it.
 #
-# DEPLOY (real model on the Space):
-#   * Fold these into requirements.txt for the model deploy (a Gradio Space
-#     installs requirements.txt, not this file) — see NAH-7.
-#   * Switch hardware back to ZeroGPU AND register the inference under @spaces.GPU,
-#     and name the gradio.Server `demo` — a ZeroGPU Space with no @spaces.GPU fn
-#     flips to RUNTIME_ERROR (that's why the stub demo runs on CPU; see server.py).
+# Why the gradio==6.10.0 pin still holds with modern transformers: 6.10.0 allows
+# huggingface-hub<2.0 (i.e. hub 1.x), which MiniCPM-V 4.6's transformers 5.x wants.
+# Do NOT move to MiniCPM-V 4.6+ versions needing a different stack without
+# re-checking the resolve (verified on an HF Job: gradio 6.10 + transformers 5.12
+# + hub 1.19 + torch 2.12). MiniCPM-V is loaded via the native
+# MiniCPMV4_6ForConditionalGeneration class (trust_remote_code=True).
 -r requirements.txt
-
-# --- transformers / model ---
-# MiniCPM-V 4.6 is a NATIVE transformers architecture
-# (`from transformers import MiniCPMV4_6ForConditionalGeneration`), so it needs a
-# recent transformers (5.x) — NOT the old trust_remote_code path. The official
-# demo declares `transformers>=4.44.0` and relies on latest providing the class.
-#
-# NOTE: this DROPS the previous `transformers<5.0` cap. That cap existed only for
-# the old MiniCPM4.1-8B *text* model (its trust_remote_code broke on 5.x, forcing
-# huggingface-hub<1.0). 4.6 uses new transformers (hub>=1.0), and gradio==6.10.0
-# allows hub<2.0, so gradio 6.10.0 + transformers 5.x + hub 1.x resolve together.
-# Moving to 4.6 therefore RETIRES the old MiniCPM4.1-8B / hub<1.0 constraint.
-transformers>=4.44.0
-torch
-torchvision           # vision tower; must match the installed torch
-accelerate
-sentencepiece         # tokenizer backend the MiniCPM-V processor uses
-
-# --- image + PDF handling ---
-pillow                # images are passed to the model as PIL.Image objects
-# Render image-only / scanned PDF pages -> PIL images to feed the vision model.
-# PyMuPDF is a pure wheel (no poppler/ffmpeg system dep) — works on a Space as-is.
-# (Neither MiniCPM demo does PDFs; this is our addition for image-based PDFs.)
-PyMuPDF
-
-# --- video (OPTIONAL) ---
-# Only needed if you later accept video input. Requires the `ffmpeg` system package
-# (add a packages.txt with `ffmpeg`). Not needed for image-based PDFs, so left out:
-# av
-
-# HF ZeroGPU GPU decorator (effect-free off-Space). Pulls in gradio, so it must
-# resolve against the gradio pin in requirements.txt — not the latest gradio.
-spaces

requirements.txt

@@ -31,3 +31,18 @@ uvicorn
 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