From 15f8d1af656a22fa0acc0cea8dfb5daccba97213 Mon Sep 17 00:00:00 2001 From: Jerome Picault Date: Tue, 21 Jul 2026 07:45:28 +0000 Subject: [PATCH] Remove Gradio GUI and Hugging Face deployment MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit Hugging Face Gradio Spaces are no longer free, so drop the Gradio front-end and the HF publish path, keeping the NiceGUI GUI as the only front-end. The shared view logic refactor (conflens/view.py) is kept β€” app.py still uses it. Removed: - conflens/gradio_app.py, space_app.py, requirements.txt (HF Space entry/deps) - .github/workflows/sync-hf-space.yml + .github/huggingface/ (HF sync + metadata) - tests/test_gradio_app.py - pyproject: the `gradio` extra and the `conflens-gradio` console script - test.yml: revert to `uv sync` (no gradio extra); uv.lock re-locked (gradio gone) Docs (README, AGENTS, CLAUDE, ARCHITECTURE) updated back to a single NiceGUI front-end while keeping view.py as the GUI-agnostic view layer. --- .github/huggingface/space_readme_header.md | 19 - .github/workflows/sync-hf-space.yml | 58 --- .github/workflows/test.yml | 4 +- AGENTS.md | 12 +- CLAUDE.md | 17 +- README.md | 53 +-- conflens/gradio_app.py | 522 --------------------- docs/ARCHITECTURE.md | 10 +- pyproject.toml | 7 +- requirements.txt | 12 - space_app.py | 28 -- tests/test_gradio_app.py | 45 -- uv.lock | 251 +--------- 13 files changed, 39 insertions(+), 999 deletions(-) delete mode 100644 .github/huggingface/space_readme_header.md delete mode 100644 .github/workflows/sync-hf-space.yml delete mode 100644 conflens/gradio_app.py delete mode 100644 requirements.txt delete mode 100644 space_app.py delete mode 100644 tests/test_gradio_app.py diff --git a/.github/huggingface/space_readme_header.md b/.github/huggingface/space_readme_header.md deleted file mode 100644 index 5b5a11c..0000000 --- a/.github/huggingface/space_readme_header.md +++ /dev/null @@ -1,19 +0,0 @@ ---- -title: ConfLens -emoji: πŸ”Ž -colorFrom: blue -colorTo: indigo -sdk: gradio -app_file: space_app.py -python_version: "3.12" -suggested_hardware: cpu-basic -pinned: false -license: mpl-2.0 -short_description: Browse, theme-classify and topic-model conference papers ---- - - diff --git a/.github/workflows/sync-hf-space.yml b/.github/workflows/sync-hf-space.yml deleted file mode 100644 index 8135df2..0000000 --- a/.github/workflows/sync-hf-space.yml +++ /dev/null @@ -1,58 +0,0 @@ -name: Sync to Hugging Face Space - -# Mirror main to a Hugging Face **Docker** Space on every push, keeping the Space -# in sync with this repo. The Space builds the repo's Dockerfile (which serves on -# 0.0.0.0:8080 β€” matched by `app_port: 8080` in the Space metadata). -# -# One-time setup (see README β†’ "Deploy to Hugging Face Spaces"): -# 1. Create a Gradio Space on huggingface.co. -# 2. Add a repo secret HF_TOKEN (a HF access token with write scope). -# 3. Optionally set repo variables HF_USERNAME / HF_SPACE (they default to -# "picault" and "conflens"). -# 4. Add your LLM API keys as *Space* secrets in the Space settings. -on: - push: - branches: [main] - workflow_dispatch: - -concurrency: - group: hf-sync - cancel-in-progress: true - -jobs: - sync: - runs-on: ubuntu-latest - steps: - - name: Checkout (full history) - uses: actions/checkout@v4 - with: - fetch-depth: 0 - lfs: true - - - name: Prepend Space metadata to README - run: | - set -euo pipefail - cat .github/huggingface/space_readme_header.md README.md > README.hf - mv README.hf README.md - git config user.name "github-actions[bot]" - git config user.email "41898282+github-actions[bot]@users.noreply.github.com" - git add README.md - git commit -m "Add Hugging Face Space metadata [skip ci]" - - - name: Push to Hugging Face Space - env: - HF_TOKEN: ${{ secrets.HF_TOKEN }} - # HF owner defaults to 'picault' (the HF username differs from the - # GitHub owner 'picaultj'); override with the HF_USERNAME repo variable. - HF_USERNAME: ${{ vars.HF_USERNAME || 'picault' }} - HF_SPACE: ${{ vars.HF_SPACE || 'conflens' }} - run: | - set -euo pipefail - if [ -z "${HF_TOKEN:-}" ]; then - echo "::error::Missing HF_TOKEN secret. Add a Hugging Face write token as a repo secret named HF_TOKEN (see README β†’ Deploy to Hugging Face Spaces)." - exit 1 - fi - echo "Syncing to https://huggingface.co/spaces/${HF_USERNAME}/${HF_SPACE}" - git push --force \ - "https://${HF_USERNAME}:${HF_TOKEN}@huggingface.co/spaces/${HF_USERNAME}/${HF_SPACE}.git" \ - HEAD:main diff --git a/.github/workflows/test.yml b/.github/workflows/test.yml index 7619e30..a731e23 100644 --- a/.github/workflows/test.yml +++ b/.github/workflows/test.yml @@ -23,8 +23,8 @@ jobs: with: enable-cache: true - - name: Sync dependencies (base + dev + gradio) - run: uv sync --extra gradio # so the Gradio GUI is covered by the suite + - name: Sync dependencies (base + dev) + run: uv sync - name: Tests (pytest) run: uv run pytest -q diff --git a/AGENTS.md b/AGENTS.md index 3f898ff..8f36940 100644 --- a/AGENTS.md +++ b/AGENTS.md @@ -17,19 +17,15 @@ save/load a run). Python 3.13, managed with **uv**. ```bash uv sync # base install (Anthropic, OpenAI, LiteLLM + NiceGUI) -uv sync --extra gradio # + the Gradio GUI uv sync --extra bertopic # + BERTopic topic backend (heavy) cp .env.example .env # add provider key(s); loaded automatically uv run conference-analyzer # NiceGUI GUI on http://localhost:6868 -uv run conflens-gradio # Gradio GUI on http://localhost:7860 uv run conference-analyzer --clear-cache # wipe the on-disk cache ``` -**Two front-ends, kept in parity:** `app.py` (NiceGUI) and `gradio_app.py` -(Gradio, deployed to Hugging Face). All non-UI logic lives in `view.py` + -`pipeline.py`; when you change a user-facing feature, update **both** GUIs. See -[CLAUDE.md](CLAUDE.md). +The GUI (`app.py`) is a thin **NiceGUI** presentation layer; all non-UI logic +lives in `view.py` + `pipeline.py` β€” put behaviour changes there. Docker: `docker compose up --build` (see the README). @@ -66,8 +62,8 @@ regexes over heavyweight parsers, small focused modules). | Area | Module | |------|--------| -| GUIs (feature parity) | `app.py` (NiceGUI), `gradio_app.py` (Gradio) | -| Shared view logic | `view.py` (filter/sort/highlight/compute_view/exports) | +| UI (NiceGUI) | `app.py` | +| View logic | `view.py` (filter/sort/highlight/compute_view/exports) | | Exports | `pptx_export.py`, `bibtex.py` | | Orchestration | `pipeline.py` (`AnalysisConfig`, `run_analysis`) | | Sources | `sources.py` (registry + `make_source`; `IJCAISource`, `OpenReviewSource`, `PSCCSource`, `DBLPSource`), `scraper.py` (`AnthologyScraper` β€” also serves EMNLP/NAACL) | diff --git a/CLAUDE.md b/CLAUDE.md index bbe2a6a..ef339c0 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -25,16 +25,9 @@ repository or its GitHub artifacts: feature (the `anthropic` provider and `claude-*` model ids in `llm.py`) and stays β€” this policy is about tooling attribution, not the app's providers. -## Two front-ends (persistent β€” keep both maintained) +## Front-end (NiceGUI) -The app ships **two GUIs with feature parity**: - -- **NiceGUI** β€” `conflens/app.py` (console script `conference-analyzer`); run - locally / in Docker. -- **Gradio** β€” `conflens/gradio_app.py` (console script `conflens-gradio`); this - is the front-end deployed to Hugging Face Spaces. - -All non-UI logic (filtering, sorting, highlighting, the computed view, exports) -lives in **`conflens/view.py`** and the pipeline β€” put behaviour changes there so -both GUIs inherit them. When you add or change a user-facing feature, **update -both `app.py` and `gradio_app.py`** so they stay in parity. +The app has a single **NiceGUI** GUI in `conflens/app.py` (console script +`conference-analyzer`). All non-UI logic (filtering, sorting, highlighting, the +computed view, exports) lives in **`conflens/view.py`** and the pipeline β€” put +behaviour changes there so the UI stays a thin presentation layer. diff --git a/README.md b/README.md index 68dc9e9..3c84f09 100644 --- a/README.md +++ b/README.md @@ -12,9 +12,7 @@ [![uv](https://img.shields.io/badge/managed%20by-uv-DE5FE9.svg?logo=uv&logoColor=white)](https://docs.astral.sh/uv/) [![Built with NiceGUI](https://img.shields.io/badge/UI-NiceGUI-2b6cb0.svg)](https://nicegui.io) -A desktop-style web app β€” with **two interchangeable front-ends**, -[NiceGUI](https://nicegui.io) (local/Docker) and [Gradio](https://gradio.app) -(deployed to Hugging Face Spaces) β€” that: +A desktop-style web app (built with [NiceGUI](https://nicegui.io)) that: 1. **Browses** papers from a chosen **source** and retrieves their abstracts: - the [ACL Anthology](https://aclanthology.org) (default; e.g. `acl-2026`), @@ -44,7 +42,7 @@ A desktop-style web app β€” with **two interchangeable front-ends**, ## Contents -- [Quick start](#quick-start) Β· [Run with Docker](#run-with-docker) Β· [Deploy to Hugging Face Spaces](#deploy-to-hugging-face-spaces) Β· [LLM providers](#llm-providers) +- [Quick start](#quick-start) Β· [Run with Docker](#run-with-docker) Β· [LLM providers](#llm-providers) - [Architecture](#architecture) Β· [How it works](#how-it-works) - [Configuration](#configuration-in-the-ui) Β· [Features](#features) - [Caching](#caching) Β· [Cost](#cost) Β· [BERTopic](#optional-bertopic) @@ -57,15 +55,10 @@ Requires Python 3.13+ and [uv](https://docs.astral.sh/uv/). ```bash uv sync # Claude, OpenAI, LiteLLM work out of the box cp .env.example .env # then fill in your provider key(s) -uv run conference-analyzer # NiceGUI GUI β†’ http://localhost:6868 +uv run conference-analyzer # or: uv run python run.py ``` -Prefer **Gradio** (same features; the front-end deployed to Hugging Face)? - -```bash -uv sync --extra gradio -uv run conflens-gradio # Gradio GUI β†’ http://localhost:7860 -``` +Then open . Keys are read from `.env` (loaded automatically) or the process environment; you can also paste a key into the app's **API key** field at runtime. @@ -99,44 +92,6 @@ docker run --rm -p 6868:6868 --env-file .env \ To also build the optional BERTopic backend into the image: `docker build --build-arg EXTRAS="--extra bertopic" -t conference-analyzer .` -### Deploy to Hugging Face Spaces - -The **Gradio** front-end is deployed to Hugging Face as a **Gradio SDK Space** -(free CPU tier). HF installs [`requirements.txt`](requirements.txt) and runs -[`space_app.py`](space_app.py), which serves `conflens.gradio_app`. A GitHub -Action mirrors `main` to the Space on every push, so it stays in sync. - -**One-time setup:** - -1. **Create the Space** β€” on , pick **Gradio β†’ - Blank**, **CPU basic** hardware (this app is CPU-only; ZeroGPU errors with - *"No @spaces.GPU function detected"*), and note its owner + name (e.g. - `your-user/conflens`). -2. **Give GitHub a token** β€” create a Hugging Face access token with **write** - scope (Settings β†’ Access Tokens) and add it to this GitHub repo as a secret - named **`HF_TOKEN`** (Settings β†’ Secrets and variables β†’ Actions). -3. **Point the action at your Space** *(optional)* β€” the workflow defaults to - owner `picault` and space `conflens` (the HF username differs from the GitHub - owner). If your Space differs, set repo **variables** `HF_USERNAME` and - `HF_SPACE`. -4. **Add your API keys as *Space* secrets** β€” in the Space's *Settings β†’ - Variables and secrets*, add whatever your provider needs (e.g. - `ANTHROPIC_API_KEY`, or `OPENAI_API_KEY` / `OPENAI_BASE_URL`; see - [`.env.example`](.env.example)). The app reads them as environment variables. - -That's it β€” push to `main` (or run the **Sync to Hugging Face Space** workflow -manually) and the Space rebuilds. The Space metadata (`sdk: gradio`, -`app_file: space_app.py`, …) lives in -[`.github/huggingface/space_readme_header.md`](.github/huggingface/space_readme_header.md); -the action prepends it to the README it pushes, so the GitHub README stays clean. - -> The Space's filesystem is ephemeral, so the on-disk cache resets on rebuild. -> For persistent caching, attach Hugging Face **persistent storage** and set -> `HOME` (or a `--cache-dir`) to point at its `/data` mount. - -> The Docker image above still runs the **NiceGUI** app (`0.0.0.0:6868`) for -> local/self-hosted use; the two front-ends share all analysis logic. - ### LLM providers The classifier and topic engine work with three providers, chosen in the UI: diff --git a/conflens/gradio_app.py b/conflens/gradio_app.py deleted file mode 100644 index d9b1cd4..0000000 --- a/conflens/gradio_app.py +++ /dev/null @@ -1,522 +0,0 @@ -"""Gradio front-end for ConfLens β€” feature-parity with the NiceGUI app. - -This is the front-end deployed to Hugging Face Spaces (Gradio SDK Spaces are -free). It shares all non-UI logic with the NiceGUI app via :mod:`conflens.view` -and :mod:`conflens.pipeline`, so keep behavioural changes in those shared modules -and mirror only the *presentation* here and in ``app.py``. -""" - -from __future__ import annotations - -import html -import os -import tempfile -import threading -import time -from typing import Optional - -import gradio as gr - -from . import view -from .cache import default_cache_dir -from .llm import DEFAULT_MODELS, MODEL_SUGGESTIONS, PROVIDERS, env_key_for -from .models import AnalysisResult -from .pipeline import AnalysisConfig, Progress, run_analysis -from .sources import SOURCES -from .view import TOPIC_COLORS - -_CACHE_DIR = default_cache_dir() - -# Sober palette (mirrors app.py). -PRIMARY = "#1f4e79" -INK = "#1a202c" -MUTED = "#64748b" -LINE = "#e2e8f0" - -_CSS = """ -.conflens mark { background:#fde68a; color:inherit; padding:0 1px; border-radius:2px; } -.conflens .ca-card { border:1px solid %s; border-radius:10px; background:#fff; - padding:14px 18px; margin-bottom:14px; } -.conflens a.ca-title { color:%s; font-weight:600; text-decoration:none; } -.conflens a.ca-title:hover { text-decoration:underline; } -.conflens .ca-badge { display:inline-block; color:#fff; border-radius:6px; - padding:1px 7px; font-size:.72rem; font-weight:600; text-decoration:none; margin-left:4px; } -.conflens .muted { color:%s; font-size:.82rem; } -""" % (LINE, PRIMARY, MUTED) - - -# --------------------------------------------------------------------------- # -# HTML rendering (presentation only; all logic comes from view.compute_view) -# --------------------------------------------------------------------------- # -def _chart_html(names: list[str], counts: list[int]) -> str: - if not names: - return "" - top = max(counts) or 1 - rows = [] - for i, (name, c) in enumerate(zip(names, counts)): - color = TOPIC_COLORS[i % len(TOPIC_COLORS)] - width = max(2, round(100 * c / top)) - rows.append( - f'
' - f'
{html.escape(name)}
' - f'
' - f'
' - f'
{c}
' - ) - return ( - '
' - "Papers per topic
%s
" % (INK, "".join(rows)) - ) - - -def _paper_html(p, kws: list[str], also_in: list[str], dup: Optional[str], also_label: str) -> str: - if kws: - title = view.highlight(p.title, kws) - else: - title = html.escape(p.title) - if p.url: - title_html = ( - f'{title}' - ) - else: - title_html = f'{title}' - - badges = "" - if dup: - badges += ( - f'near-dup' - ) - if p.confidence is not None: - badges += ( - f'{p.confidence:.0%}' - ) - if p.pdf_url: - badges += ( - f'PDF' - ) - - parts = [ - f'
', - f'
{title_html}{badges}
', - ] - if p.authors: - auth = ", ".join(p.authors[:6]) + ("…" if len(p.authors) > 6 else "") - parts.append(f'
{html.escape(auth)}
') - if also_in: - parts.append( - f'
{html.escape(also_label)}' - f'{html.escape(", ".join(also_in))}
' - ) - if p.abstract: - body = view.highlight(p.abstract, kws) if kws else html.escape(p.abstract) - parts.append( - f'
Abstract' - f'
{body}
' - "
" - ) - if p.reason: - parts.append(f'
Why: {html.escape(p.reason)}
') - parts.append("
") - return "".join(parts) - - -def _render_html(result: AnalysisResult, min_conf, query, author, sort, is_global) -> tuple[str, str]: - """Return (results_html, status_text) for the current filters.""" - if result is None: - return "", "" - kws = view.keywords(query or "") - vd = view.compute_view( - result, min_conf=float(min_conf or 0), query=query or "", - author=author or "", sort=sort or "confidence", - ) - blocks = [_chart_html(vd.names, vd.counts)] - - if is_global: - papers = vd.flat - card = [ - '
', - f'
All matching papers ({len(papers)})
', - ] - if not papers: - card.append('
No papers match the current filters.
') - for p in papers: - card.append(_paper_html( - p, kws, - [vd.topic_name[tid] for tid in p.topic_ids if tid in vd.topic_name], - view.dup_title(p, vd.all_by_id), "Topics: ", - )) - card.append("
") - blocks.append("".join(card)) - shown_papers, shown_topics = len(papers), (1 if papers else 0) - else: - shown_papers = shown_topics = 0 - for tv in vd.grouped: - t, papers = tv.topic, tv.papers - shown_papers += len(papers) - shown_topics += 1 - color = TOPIC_COLORS[t.topic_id % len(TOPIC_COLORS)] - badge = ( - f"{len(papers)} of {t.count}" if len(papers) != t.count - else f"{t.count} paper{'s' if t.count != 1 else ''}" - ) - card = [ - '
', - f'
' - f'' - f'{html.escape(t.name)}' - f'{badge}
', - ] - if t.description: - card.append( - f'
' - f'{html.escape(t.description)}
' - ) - if t.findings: - items = "".join(f"
  • {html.escape(f)}
    • " for f in t.findings) - card.append( - f'
    ' - f'
    Main findings across this topic
    ' - f'
      {items}
    ' - ) - card.append(f'
    Papers ({len(papers)})
    ') - for p in papers: - card.append(_paper_html( - p, kws, view.also_in(p, t.topic_id, vd.topic_name), - view.dup_title(p, vd.all_by_id), "Also in: ", - )) - card.append("
    ") - blocks.append("".join(card)) - if shown_topics == 0: - blocks.append('
    No papers match the current filters.
    ') - - scope = "in one list" if is_global else f"Β· {shown_topics} of {vd.total_topics} topics" - status = ( - f"Show β‰₯ {float(min_conf or 0):.2f} confidence β€” " - f"{shown_papers} of {vd.total_relevant} papers {scope}" - ) - return f'
    {"".join(blocks)}
    ', status - - -def _summary_md(result: AnalysisResult) -> str: - if result is None: - return "" - bits = [ - f"**{result.scanned}** scanned", - f"**{len(result.relevant_papers)}** relevant to *{result.theme}*", - f"**{len(result.topics)}** topics", - ] - if result.duplicate_groups: - bits.append(f"**{result.duplicate_groups}** near-duplicate groups") - link = f" Β· [source]({result.event_url})" if result.event_url else "" - return " Β· ".join(bits) + link - - -def _provider_hint(provider: str, suggestions: str) -> str: - env_var = { - "anthropic": "ANTHROPIC_API_KEY", - "openai": "OPENAI_API_KEY", - "litellm": "LITELLM_API_KEY / OPENAI_API_KEY", - }.get(provider, "") - parts = [] - if env_key_for(provider): - parts.append(f"Using `{env_var}` from the environment.") - else: - parts.append(f"No `{env_var}` found β€” set it or fill the API key field.") - if provider == "litellm": - parts.append("LiteLLM: set the LLM endpoint.") - return " ".join(parts) - - -# --------------------------------------------------------------------------- # -# Export helpers (write bytes to a temp file for DownloadButton) -# --------------------------------------------------------------------------- # -def _write_temp(data: bytes, name: str) -> str: - path = os.path.join(tempfile.mkdtemp(prefix="conflens_"), name) - with open(path, "wb") as fh: - fh.write(data) - return path - - -def _dl_json(result): - if result is None: - raise gr.Error("Run or load an analysis first.") - return _write_temp(view.json_bytes(result), "analysis.json") - - -def _dl_csv(result): - if result is None: - raise gr.Error("Run or load an analysis first.") - return _write_temp(view.csv_bytes(result), "analysis.csv") - - -def _dl_bibtex(result): - if result is None: - raise gr.Error("Run or load an analysis first.") - from .bibtex import build_bibtex - - return _write_temp(build_bibtex(result).encode("utf-8"), "papers.bib") - - -def _dl_pptx(result): - if result is None: - raise gr.Error("Run or load an analysis first.") - from .pptx_export import build_pptx - - try: - data = build_pptx(result) - except Exception as e: # missing dependency / render failure - raise gr.Error(str(e)) - return _write_temp(data, "analysis.pptx") - - -# --------------------------------------------------------------------------- # -# Analyze / load lifecycle -# --------------------------------------------------------------------------- # -def _validate(model, event, provider, llm_base_url) -> Optional[str]: - if not (model or "").strip(): - return "Please set a model before running." - if not (event or "").strip(): - return "Please set the event / target." - if provider == "litellm" and not (llm_base_url or "").strip(): - return "LiteLLM needs an LLM endpoint." - return None - - -def _populate(result: AnalysisResult): - """Outputs tuple shared by analyze() and load() to fill the results panel.""" - html_, status = _render_html(result, result.min_confidence, "", "", "confidence", False) - return ( - result, # result_state - _summary_md(result), # summary_md - html_, # results_html - status, # status_md - gr.update(choices=view.author_choices(result), value=None), # author_dd - gr.update(value=result.min_confidence), # conf_slider - gr.update(value=""), # search_box - gr.update(value="confidence"), # sort_dd - gr.update(value=False), # global_chk - gr.update(visible=True), # results_group - ) - - -def analyze( - source, base_url, event, theme, theme_def, provider, model, backend, - llm_base_url, api_key, max_papers, n_topics, min_conf, refresh, - progress=gr.Progress(), -): - err = _validate(model, event, provider, llm_base_url) - if err: - raise gr.Error(err) - cfg = AnalysisConfig( - source=source, - base_url=(base_url or "").strip(), - event=(event or "").strip(), - theme=(theme or "").strip() or "Agentic AI", - theme_definition=(theme_def or "").strip(), - provider=provider, - model=(model or "").strip(), - llm_base_url=(llm_base_url or "").strip(), - api_key=(api_key or "").strip(), - max_papers=int(max_papers or 150), - n_topics=int(n_topics or 8), - min_confidence=float(min_conf), - topic_backend=backend, - refresh=bool(refresh), - ) - prog = Progress() - box: dict = {} - - def work(): - try: - box["r"] = run_analysis(cfg, prog, _CACHE_DIR) - except Exception as e: # surface to the user - prog.error = str(e) - - th = threading.Thread(target=work, daemon=True) - th.start() - progress(0.0, desc="Starting…") - while th.is_alive(): - progress(min(prog.fraction, 0.99), desc=prog.message or "Working…") - time.sleep(0.25) - th.join() - if prog.error: - raise gr.Error(prog.error) - progress(1.0, desc="Done") - result = box.get("r") - if result is None or (not result.relevant_papers and not result.topics): - empty = AnalysisResult(theme=cfg.theme, event_url=result.event_url if result else "") - return ( - empty, _summary_md(result) if result else "", - '
    ' - "No matching papers were found for this theme.
    ", - "", gr.update(choices=[], value=None), gr.update(value=cfg.min_confidence), - gr.update(value=""), gr.update(value="confidence"), gr.update(value=False), - gr.update(visible=True), - ) - return _populate(result) - - -def load_run(file): - if not file: - return (None, "", "", "", gr.update(), gr.update(), gr.update(), - gr.update(), gr.update(), gr.update(visible=False)) - try: - with open(file, "rb") as fh: - import json - result = AnalysisResult.from_dict(json.loads(fh.read().decode("utf-8"))) - except Exception as e: - raise gr.Error(f"Could not load run: {e}") - if not result.relevant_papers and not result.topics: - raise gr.Error("That file doesn't look like a saved analysis run.") - return _populate(result) - - -def rerender(result, min_conf, query, author, sort, is_global): - if result is None: - return "", "" - return _render_html(result, min_conf, query, author, sort, is_global) - - -# --------------------------------------------------------------------------- # -# Blocks layout -# --------------------------------------------------------------------------- # -def build_demo() -> "gr.Blocks": - default_provider = "litellm" - with gr.Blocks(title="ConfLens β€” Conference Paper Analyzer") as demo: - # Inject CSS via a ") - gr.Markdown("## πŸ”Ž ConfLens β€” Conference Paper Analyzer\nBrowse Β· classify by theme Β· discover topics") - result_state = gr.State(None) - - with gr.Accordion("Configuration", open=True): - with gr.Row(): - source_dd = gr.Dropdown( - choices=[(v["label"], k) for k, v in SOURCES.items()], - value="aclanthology", label="Source", - ) - base_url_tb = gr.Textbox( - value=SOURCES["aclanthology"]["base"], - label=SOURCES["aclanthology"]["base_label"], - ) - event_tb = gr.Textbox( - value=SOURCES["aclanthology"]["target"], - label=SOURCES["aclanthology"]["target_label"], - ) - with gr.Row(): - theme_tb = gr.Textbox(value="Agentic AI", label="Theme") - provider_dd = gr.Dropdown(choices=PROVIDERS, value=default_provider, label="LLM provider") - model_tb = gr.Textbox(value=DEFAULT_MODELS[default_provider], label="Model") - backend_dd = gr.Dropdown( - choices=[("LLM topics", "llm"), ("BERTopic", "bertopic")], - value="llm", label="Topic engine", - ) - theme_def_tb = gr.Textbox( - label="Theme definition (optional)", - placeholder="Clarify what counts as this theme β€” what to include / exclude", - ) - with gr.Row(): - llm_base_url_tb = gr.Textbox( - value=os.environ.get("OPENAI_BASE_URL", ""), - label="LLM endpoint (LiteLLM / OpenAI-compatible)", - ) - api_key_tb = gr.Textbox(label="API key (optional β€” overrides env var)", type="password") - key_hint_md = gr.Markdown(_provider_hint(default_provider, "")) - with gr.Row(): - max_papers_num = gr.Number(value=150, precision=0, label="Max papers to scan") - n_topics_num = gr.Number(value=8, precision=0, label="Target number of topics") - min_conf_num = gr.Slider(0, 1, value=0.5, step=0.05, label="Minimum confidence") - with gr.Row(): - refresh_chk = gr.Checkbox(value=False, label="Refresh from source (ignore cache)") - load_file = gr.File(label="Load saved run (.json)", file_types=[".json"]) - analyze_btn = gr.Button("Analyze", variant="primary") - - with gr.Group(visible=False) as results_group: - summary_md = gr.Markdown() - with gr.Row(): - dl_pptx_btn = gr.DownloadButton("PPTX", size="sm") - dl_json_btn = gr.DownloadButton("JSON", size="sm") - dl_csv_btn = gr.DownloadButton("CSV", size="sm") - dl_bib_btn = gr.DownloadButton("BibTeX", size="sm") - with gr.Row(): - search_box = gr.Textbox( - label="Filter by keywords (comma-separated; each may contain spaces)", - scale=3, - ) - sort_dd = gr.Dropdown( - choices=[("Confidence", "confidence"), ("Title", "title"), ("Year", "year")], - value="confidence", label="Sort by", scale=1, - ) - with gr.Row(): - author_dd = gr.Dropdown(choices=[], value=None, label="Filter by author", - allow_custom_value=True, scale=2) - conf_slider = gr.Slider(0, 1, value=0.5, step=0.05, label="Show β‰₯ confidence", scale=2) - global_chk = gr.Checkbox(value=False, label="Search all topics", scale=1) - status_md = gr.Markdown() - results_html = gr.HTML() - - # -- wiring --------------------------------------------------------- # - def on_source(source): - cfg = SOURCES.get(source, {}) - return ( - gr.update(value=cfg.get("base", ""), label=cfg.get("base_label", "Base URL")), - gr.update(value=cfg.get("target", ""), label=cfg.get("target_label", "Target")), - ) - - source_dd.change(on_source, [source_dd], [base_url_tb, event_tb]) - - def on_provider(provider): - sugg = ", ".join(MODEL_SUGGESTIONS.get(provider, [])) - return gr.update(value=DEFAULT_MODELS.get(provider, ""), info=f"e.g. {sugg}"), \ - _provider_hint(provider, sugg) - - provider_dd.change(on_provider, [provider_dd], [model_tb, key_hint_md]) - - analyze_outputs = [ - result_state, summary_md, results_html, status_md, author_dd, - conf_slider, search_box, sort_dd, global_chk, results_group, - ] - analyze_btn.click( - analyze, - [source_dd, base_url_tb, event_tb, theme_tb, theme_def_tb, provider_dd, - model_tb, backend_dd, llm_base_url_tb, api_key_tb, max_papers_num, - n_topics_num, min_conf_num, refresh_chk], - analyze_outputs, - ) - load_file.change(load_run, [load_file], analyze_outputs) - - view_inputs = [result_state, conf_slider, search_box, author_dd, sort_dd, global_chk] - for ctrl in (conf_slider, search_box, author_dd, sort_dd, global_chk): - ctrl.change(rerender, view_inputs, [results_html, status_md]) - - dl_json_btn.click(_dl_json, [result_state], [dl_json_btn]) - dl_csv_btn.click(_dl_csv, [result_state], [dl_csv_btn]) - dl_bib_btn.click(_dl_bibtex, [result_state], [dl_bib_btn]) - dl_pptx_btn.click(_dl_pptx, [result_state], [dl_pptx_btn]) - - return demo - - -def main() -> None: - """Launch the Gradio app (console script: ``conflens-gradio``).""" - try: - from dotenv import load_dotenv - - load_dotenv() - except ImportError: - pass - port = int(os.environ.get("PORT", "7860")) - build_demo().launch(server_name="0.0.0.0", server_port=port) - - -if __name__ == "__main__": - main() diff --git a/docs/ARCHITECTURE.md b/docs/ARCHITECTURE.md index 11a9e8a..4da70e5 100644 --- a/docs/ARCHITECTURE.md +++ b/docs/ARCHITECTURE.md @@ -1,9 +1,8 @@ # Architecture -ConfLens is a small, single-process web app. It has **two interchangeable -front-ends** β€” NiceGUI (`app.py`, local/Docker) and Gradio (`gradio_app.py`, -deployed to Hugging Face) β€” that share all non-UI logic via `view.py` and the -pipeline. A front end drives a +ConfLens is a small, single-process web app. A **NiceGUI** front end (`app.py`) +is a thin presentation layer over the shared view logic (`view.py`) and the +pipeline, which drives a linear pipeline β€” **browse β†’ classify β†’ topic-model β†’ summarize** β€” over a pluggable *source* (which conference) and a pluggable *LLM provider* (which model). Everything expensive is cached on disk. @@ -117,8 +116,7 @@ sequenceDiagram |--------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | `cli.py` | Console entry point (`conflens`); `--clear-cache`, `--host/--port`; loads `.env`. | | `app.py` | **NiceGUI** GUI: configuration form, input validation, progress, and the interactive results view (ECharts chart, per-topic findings + papers, live re-threshold / search / sort / facet, save + load a run), exports. | -| `gradio_app.py` | **Gradio** GUI (deployed to Hugging Face) β€” same features via HTML rendering; launched by `space_app.py`. | -| `view.py` | GUI-agnostic view logic shared by both front-ends: `keywords`/`matches`/`highlight`/`sort_papers`/`compute_view` + CSV/JSON export bytes. | +| `view.py` | GUI-agnostic view logic used by `app.py`: `keywords`/`matches`/`highlight`/`sort_papers`/`compute_view` + CSV/JSON export bytes. | | `pipeline.py` | `AnalysisConfig` + `run_analysis()` orchestrating the stages with a `Progress` object (supports cooperative cancel). | | `sources.py` | Source interface + registry + `make_source()`; `IJCAISource`, `OpenReviewSource`, `PSCCSource`, `DBLPSource`, shared `_robust_get`. | | `scraper.py` | `AnthologyScraper` (ACL Anthology adapter, also serving EMNLP / NAACL) + shared HTML helpers. | diff --git a/pyproject.toml b/pyproject.toml index b68b769..c20dfae 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -18,14 +18,9 @@ dependencies = [ # Optional embedding-based topic backend. Heavy (pulls in sentence-transformers # / torch); install with `uv sync --extra bertopic`. bertopic = ["bertopic>=0.16"] -# Gradio front-end (the one deployed to Hugging Face Spaces). The NiceGUI GUI -# ships in the base install; install this to run the Gradio GUI locally with -# `uv sync --extra gradio` then `uv run conflens-gradio`. -gradio = ["gradio>=4.44"] [project.scripts] -conference-analyzer = "conflens.cli:main" # NiceGUI GUI -conflens-gradio = "conflens.gradio_app:main" # Gradio GUI +conference-analyzer = "conflens.cli:main" [dependency-groups] # Installed by default with `uv sync`; used for tests + linting / CI. diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 210cb8a..0000000 --- a/requirements.txt +++ /dev/null @@ -1,12 +0,0 @@ -# Dependencies for the Hugging Face Gradio Space (sdk: gradio). -# -# HF installs these with pip, then runs space_app.py (which imports the conflens -# package from this repo). Deliberately excludes nicegui β€” the Space runs the -# Gradio GUI only. Keep in sync with the runtime deps in pyproject.toml -# (everything except nicegui) plus gradio. -anthropic>=0.40 -openai>=1.40 -litellm>=1.40 -python-pptx>=0.6.21 -python-dotenv>=1.0 -gradio>=4.44 diff --git a/space_app.py b/space_app.py deleted file mode 100644 index 1cbf8d5..0000000 --- a/space_app.py +++ /dev/null @@ -1,28 +0,0 @@ -"""Hugging Face Space entry point (Gradio SDK). - -The Space's README metadata sets ``app_file: space_app.py``. HF imports this -module, finds the module-level ``demo`` and serves it. Running it directly -(``python space_app.py``) launches locally too. - -The Space runs on free **CPU** hardware, so Gradio's SSR (which spawns a Node -sidecar) is disabled β€” the app is plain server-rendered Python. Set the Space -hardware to *CPU basic*; ZeroGPU hardware would error with "No @spaces.GPU -function detected" because this app has no GPU code. -""" - -import os - -from conflens.gradio_app import build_demo - -# Disable Gradio SSR (Node proxy) β€” set before any launch, whether HF launches -# `demo` itself or this file is run directly. -os.environ.setdefault("GRADIO_SSR_MODE", "false") - -demo = build_demo() - -if __name__ == "__main__": - demo.launch( - server_name="0.0.0.0", - server_port=int(os.environ.get("PORT", "7860")), - ssr_mode=False, - ) diff --git a/tests/test_gradio_app.py b/tests/test_gradio_app.py deleted file mode 100644 index ae3ce50..0000000 --- a/tests/test_gradio_app.py +++ /dev/null @@ -1,45 +0,0 @@ -import pytest - -pytest.importorskip("gradio") # only runs when the `gradio` extra is installed - -from conflens.models import AnalysisResult, Paper, Topic # noqa: E402 - - -def _result() -> AnalysisResult: - papers = [ - Paper("p1", "Agentic Planning", "http://x/1", "http://x/1.pdf", - ["Ada Lovelace"], "tool agents", True, 0.9, "core", [0, 1]), - Paper("p2", "Graph Networks", "http://x/2", "http://x/2.pdf", - ["Marie Curie"], "gnn", True, 0.6, "core", [1]), - ] - topics = [Topic(0, "Agents", "d", ["f"], ["p1"]), Topic(1, "Graphs", "d", ["f"], ["p1", "p2"])] - return AnalysisResult("Agentic AI", "https://x", 50, papers, papers, topics, 0, 0.5) - - -def test_render_html_highlights_and_filters(): - from conflens import gradio_app as g - - html_, status = g._render_html(_result(), 0.5, "agent", "", "confidence", False) - assert "" in html_ # keyword highlighted - assert "Papers per topic" in html_ # chart rendered - assert "Agents" in html_ # topic card - assert "of 2 papers" in status - - # raising the threshold hides the 0.60 paper in global mode - h2, s2 = g._render_html(_result(), 0.7, "", "", "title", True) - assert "Graph Networks" not in h2 - assert "1 of 2 papers" in s2 - - -def test_build_demo_constructs(): - from conflens import gradio_app as g - - demo = g.build_demo() - 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