From 86f65386aee443997c7345e9f35167e87fc0ece1 Mon Sep 17 00:00:00 2001 From: LittleLucifer1 <2697699085@qq.com> Date: Sun, 1 Mar 2026 14:35:27 +0800 Subject: [PATCH 1/4] Add beamer code --- .../p2b_pagecontent_to_beamer_agent.py | 85 +++++++ .../p2v_beamer_code_debug_agent.py | 14 +- .../promptstemplates/prompts_repo.py | 95 +++++-- dataflow_agent/state.py | 30 +++ dataflow_agent/toolkits/p2vtool/p2v_tool.py | 78 ++++++ dataflow_agent/workflow/registry.py | 5 +- .../workflow/wf_paper2ppt_beamer.py | 235 ++++++++++++++++++ dataflow_agent/workflow/wf_paper2video.py | 223 +---------------- fastapi_app/workflow_adapters/wa_paper2ppt.py | 2 +- frontend-workflow/vite.config.ts | 50 ++-- 10 files changed, 557 insertions(+), 260 deletions(-) create mode 100644 dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py create mode 100644 dataflow_agent/workflow/wf_paper2ppt_beamer.py diff --git a/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py b/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py new file mode 100644 index 00000000..9e5e12be --- /dev/null +++ b/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py @@ -0,0 +1,85 @@ +""" +P2bPagecontentToBeamer agent +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +从 paper2page_content 产出的 pagecontent（结构化大纲）生成 LaTeX Beamer 代码。 +输入：pagecontent (list[dict]: title, layout_description, key_points, asset_ref) +输出：latex_code，写入 state.beamer_code_path。 +""" + +from __future__ import annotations + +from pathlib import Path +from typing import Any, Dict, Optional + +from dataflow_agent.state import MainState +from dataflow_agent.toolkits.tool_manager import ToolManager +from dataflow_agent.logger import get_logger +from dataflow_agent.agentroles.cores.base_agent import BaseAgent +from dataflow_agent.agentroles.cores.registry import register +from dataflow_agent.toolkits.p2vtool.p2v_tool import extract_beamer_code + +log = get_logger(__name__) + + +# ---------------------------------------------------------------------- +# Agent Definition +# ---------------------------------------------------------------------- +@register("p2b_pagecontent_to_beamer") +class P2bPagecontentToBeamer(BaseAgent): + """从 pagecontent（结构化大纲）生成 Beamer LaTeX 代码""" + + @classmethod + def create(cls, tool_manager: Optional[ToolManager] = None, **kwargs): + return cls(tool_manager=tool_manager, **kwargs) + + @property + def role_name(self) -> str: + return "p2b_pagecontent_to_beamer" + + @property + def system_prompt_template_name(self) -> str: + return "system_prompt_for_p2b_pagecontent_to_beamer" + + @property + def task_prompt_template_name(self) -> str: + return "task_prompt_for_p2b_pagecontent_to_beamer" + + def get_task_prompt_params(self, pre_tool_results: Dict[str, Any]) -> Dict[str, Any]: + return { + "pagecontent": pre_tool_results.get("pagecontent", "[]"), + "output_language": pre_tool_results.get("output_language", "English"), + "pdf_images_working_dir": pre_tool_results.get("pdf_images_working_dir", ""), + } + + def get_default_pre_tool_results(self) -> Dict[str, Any]: + return {} + + def update_state_result( + self, + state: MainState, + result: Dict[str, Any], + pre_tool_results: Dict[str, Any], + ): + raw = result.get("latex_code", "") if isinstance(result, dict) else "" + beamer_code = "" + if isinstance(raw, str): + beamer_code = extract_beamer_code(raw) + if not beamer_code: + log.error("p2b_pagecontent_to_beamer: 未得到有效 Beamer 代码") + super().update_state_result(state, result, pre_tool_results) + return + + result_path = getattr(state, "result_path", "") or "" + if result_path: + base = Path(result_path).expanduser().resolve() + else: + req = getattr(state, "request", None) + paper_pdf_path = getattr(req, "paper_pdf_path", "") if req else "" + base = Path(paper_pdf_path).expanduser().resolve().parent if paper_pdf_path else Path(".").resolve() + auto_dir = base / "auto" + auto_dir.mkdir(parents=True, exist_ok=True) + beamer_code_path = auto_dir / "beamer_code.tex" + beamer_code_path.write_text(beamer_code, encoding="utf-8") + state.beamer_code_path = str(beamer_code_path) + log.info("p2b_pagecontent_to_beamer: Beamer 代码已写入 %s", beamer_code_path) + super().update_state_result(state, result, pre_tool_results) diff --git a/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py b/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py index afa15a60..eec57bac 100644 --- a/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py +++ b/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py @@ -58,6 +58,15 @@ def get_default_pre_tool_results(self) -> Dict[str, Any]: """若调用方未显式传入，返回默认前置工具结果""" return {} + async def execute_pre_tools(self, state: MainState) -> Dict[str, Any]: + """先执行父类前置工具；若 state 上有 pre_tool_results（workflow 内注入），则合并进结果，保证 beamer_code/code_debug_result 能进入 prompt。""" + results = await super().execute_pre_tools(state) + inject = getattr(state, "pre_tool_results", None) or {} + for key in ("beamer_code", "code_debug_result"): + if key in inject: + results[key] = inject[key] + return results + # ---------- 结果写回 ---------- def update_state_result( self, @@ -73,9 +82,12 @@ def update_state_result( tex_path = Path(beamer_code_path) tex_path.write_text(beamer_code, encoding='utf-8') - # 编译最新的tex代码 + # 编译最新的 tex 代码并写回 state，便于调用方判断是否仍存在 error/warning from dataflow_agent.toolkits.p2vtool.p2v_tool import compile_tex is_beamer_wrong, is_beamer_warning, code_debug_result = compile_tex(beamer_code_path) + state.is_beamer_wrong = is_beamer_wrong + state.is_beamer_warning = is_beamer_warning + state.code_debug_result = code_debug_result state.ppt_path = beamer_code_path.replace(".tex", ".pdf") log.info(f"将更新好的beamer code写回 {beamer_code_path}") else: diff --git a/dataflow_agent/promptstemplates/prompts_repo.py b/dataflow_agent/promptstemplates/prompts_repo.py index b8409aab..6204ba59 100644 --- a/dataflow_agent/promptstemplates/prompts_repo.py +++ b/dataflow_agent/promptstemplates/prompts_repo.py @@ -1794,23 +1794,81 @@ class Paper2VideoPrompt: ## Source Content (Markdown) {pdf_markdown} +""" + + system_prompt_for_p2b_pagecontent_to_beamer = """ +You are an expert in LaTeX Beamer. Your task is to convert **one slide's** structured outline (pagecontent) into a **single, structurally complete, compilable** Beamer LaTeX document. + +**Context:** You generate slide content **one page at a time**. Each output must be a **full Beamer document** that compiles on its own (with Tectonic or TeX Live). Do not output a bare frame or fragment. + +**Required document structure (do not omit any part):** +1. \\documentclass{{beamer}} +2. Preamble: \\usetheme, \\usecolortheme (or similar), and font packages (see below). +3. \\begin{{document}} +4. **Exactly one** \\begin{{frame}}...\\end{{frame}} containing the slide content. +5. \\end{{document}} + +**CRITICAL:** Ensure every \\begin{{frame}} has a matching \\end{{frame}}, and the document ends with \\end{{document}}. Avoid the error "!File ended while scanning use of \\frame". + +**Font and package rules (strict):** +- **STRICTLY FORBIDDEN:** Times New Roman, Arial, Calibri, TeX Gyre Termes, or any non-standard TeX Live font. Use \\usepackage{{lmodern}} or default LaTeX fonts only. +- **Do NOT use** \\usepackage{{resizebox}} (invalid/grammar issues). +- If output_language is Chinese, you **must** include in the preamble: \\usepackage{{fontspec}} and \\usepackage{{ctex}}. + +**Syntax rules:** +- **Do not use & in frame titles** (causes "Misplaced alignment tab character &"). Use "and" or comma instead. +- **Underscore in plain text:** In LaTeX, underscore `_` is reserved for math subscripts. Any `_` in normal text (e.g. function names like generate_from_input, variable names like user_inputs, system_prompt) **must** be written as \\_ (backslash-underscore). Example: `user_inputs` → `user\\_inputs`, `generate_from_input` → `generate\\_from\\_input`. Otherwise you get "Missing $ inserted" and compilation fails. +- Use \\alert{{}} for key terms or math symbols when appropriate. +- For literal percent sign in text use \\% (e.g. 5\\%). + +**Content:** Use the given title, layout_description, key_points, and asset_ref. For image paths (e.g. in asset_ref), prepend the absolute base path given by pdf_images_working_dir and use \\includegraphics[width=0.8\\textwidth]{{...}} with \\caption and \\label. For table references (e.g. Table_2) use tabular/booktabs or a placeholder. + +**Output:** Return only one JSON object with key "latex_code" containing the **entire** document from \\documentclass to \\end{{document}}, ready to compile. +""" + + task_prompt_for_p2b_pagecontent_to_beamer = """ +Generate **one** LaTeX Beamer slide as a **complete, compilable document**. The input is a **single slide's** pagecontent (one JSON object). Your output must be a full Beamer file: \\documentclass{{beamer}} + preamble + \\begin{{document}} + **one** \\begin{{frame}}...\\end{{frame}} + \\end{{document}}. + +## Output language +{output_language} + +## Images base directory (absolute path prefix for \\includegraphics) +{pdf_images_working_dir} + +## This slide's pagecontent (single object) +{pagecontent} + +## Format requirements +- Font: use \\usepackage{{lmodern}} or default fonts only. **Do not use** Times New Roman, TeX Gyre Termes, resizebox. +- Chinese: if output language is Chinese, add \\usepackage{{fontspec}} and \\usepackage{{ctex}} in the preamble. +- No **&** in frame title (use "and" or comma). +- **Underscores in text:** Write \\_ for every underscore in normal text (e.g. user\\_inputs, generate\\_from\\_input), or you get "Missing $ inserted". +- Literal percent: use 5\\% not 5%. +- Every \\begin{{frame}} must have \\end{{frame}}; document must end with \\end{{document}}. + +## Output format +Return a valid JSON object with a single key "latex_code". + +{{ + "latex_code": "FULL_BEAMER_DOCUMENT_WITH_ONE_FRAME_HERE" +}} """ system_prompt_for_p2v_beamer_code_debug = """ -You are an expert in repairing LaTeX beamer code. +You are an expert in repairing LaTeX beamer code. You must preserve all slide content exactly as written (including text, figures, and layout). -Your goal is to correct LaTeX compilation errors and return clean, compilable LaTeX code. +Your goal is to fix LaTeX compilation **errors** and **warnings** (e.g. Overfull box) and return clean, compilable LaTeX code. Your output must: - Be directly compilable using **tectonic** (a simplified TeX Live) - Never include explanations, comments, or English/Chinese text outside the LaTeX code - """ task_prompt_for_p2v_beamer_code_debug = """ -(Critical!) Do not modify the file path, ignore the folloing message: "warning: accessing absolute path: " -You are given a LaTeX beamer code for the slides of a research paper and its error information. -You should correct these errors but do not change the slide content (e.g., text, figures and layout). +(Critical!) Do not modify the file path; ignore the following message: "warning: accessing absolute path: " + +You are given a LaTeX beamer code for the slides of a research paper and its compilation log (errors and/or warnings). +Fix the reported issues but do not change the slide content (e.g., text, figures and layout). ## Content Preservation Rules (Strict) - You MUST NOT delete, replace, or reduce the number of figures/images. @@ -1819,23 +1877,30 @@ class Paper2VideoPrompt: ONLY if necessary to fix compilation or layout issues. - Keep the slide text content unchanged as much as possible. -## Some instruction +## Overfull box (warning) +When the log contains **Overfull \\hbox** or **Overfull \\vbox** (content or font too large), fix by: +- Reducing font size (e.g. \\small, \\footnotesize in the frame or for specific blocks). +- Reducing image/figure width or scale (e.g. width=0.7\\textwidth instead of 0.9\\textwidth). +- Do NOT remove or truncate text or figures; only resize or rescale to fit. + +## Other instructions **Font Safety**: **MUST** remove or comment out any usage of the `fontspec` package if and only if it causes errors (as it depends on system fonts). -For instance, if you encounter the error message: Package fontspec Error: The font "Latin Modern Roman" cannot be found, just remove or comment out it and use default TeX Live fonts. +For instance, if you see: Package fontspec Error: The font "Latin Modern Roman" cannot be found, remove or comment it out and use default TeX Live fonts. -**Image Loading Errors**: -If the compiler reports an image loading **error**, such as: "Unable to load picture or PDF file" or "! LaTeX Error: Cannot determine size of graphic", the model **MUST** remove the entire command responsible for loading that specific graphic. +**Image Loading Errors**: +If the compiler reports an image loading **error** (e.g. "Unable to load picture or PDF file" or "! LaTeX Error: Cannot determine size of graphic"), **MUST** remove the entire command that loads that graphic. -Output Format: -- Return a JSON object with a single key "latex_code". +## Output format +Return a JSON object with a single key "latex_code". {{ "latex_code": "YOUR_GENERATED_latex_beamer_code_HERE" }} -# Only output latex code which should be ready to compile using tectonic (simple version of TeX Live). +Output only the JSON; the latex code must be ready to compile with tectonic. -The LateX beamer code is: +The LaTeX beamer code is: {beamer_code} -The compilation error message is: + +The compilation log (errors and/or warnings) is: {code_debug_result} """ diff --git a/dataflow_agent/state.py b/dataflow_agent/state.py index a45fe0ba..34269725 100644 --- a/dataflow_agent/state.py +++ b/dataflow_agent/state.py @@ -164,6 +164,36 @@ class Paper2VideoState(MainState): video_path: str = "" +# ==================== Paper2PptBeamer 相关 State 和 Request 定义 ==================== +@dataclass +class Paper2PptBeamerRequest(MainRequest): + """仅用于 PDF → Beamer PPT 工作流""" + paper_pdf_path: str = "" + + +# ==================== Paper2PptBeamer 生成 State ====================== +@dataclass +class Paper2PptBeamerState(MainState): + """用于 pagecontent → Beamer PPT 工作流（接在 paper2page_content 之后）""" + request: Paper2PptBeamerRequest = field(default_factory=Paper2PptBeamerRequest) + + # 来自上游 paper2page_content 的产出 + pagecontent: List[Dict[str, Any]] = field(default_factory=list) + result_path: str = "" + mineru_root: str = "" + minueru_output: str = "" # 论文全文/摘要，供 table_extractor 等使用 + + beamer_code_path: str = "" + is_beamer_wrong: bool = False + is_beamer_warning: bool = False + code_debug_result: str = "" + ppt_path: str = "" + img_size_debug: bool = True + + # 每页单独生成时的路径列表（页序） + per_page_beamer_paths: List[str] = field(default_factory=list) + per_page_pdf_paths: List[str] = field(default_factory=list) + # ==================== Planning Agent 相关 State ==================== @dataclass diff --git a/dataflow_agent/toolkits/p2vtool/p2v_tool.py b/dataflow_agent/toolkits/p2vtool/p2v_tool.py index 18544260..7b18adf9 100644 --- a/dataflow_agent/toolkits/p2vtool/p2v_tool.py +++ b/dataflow_agent/toolkits/p2vtool/p2v_tool.py @@ -1121,6 +1121,84 @@ def compile_tex(beamer_code_path: str): code_debug_result = e.stderr return is_beamer_wrong, is_beamer_warning, code_debug_result + +def is_overfull_warning(code_debug_result: str) -> bool: + """是否包含 Overfull 类 warning（内容过高/过宽），需要尝试修复。""" + if not code_debug_result: + return False + return "Overfull" in code_debug_result + + +def is_ignorable_warning_only(code_debug_result: str) -> bool: + """是否仅包含可忽略的 warning（如访问绝对路径），无需修复。""" + if not code_debug_result: + return True + lower = code_debug_result.lower() + if "warning" not in lower: + return True + # 若只有 absolute path 类提示，视为可忽略 + if "overfull" in lower: + return False + if "absolute path" in lower or "accessing absolute path" in lower: + return True + return False + + +def is_table_asset(asset_ref: Any) -> bool: + """asset_ref 为 Table 时通常为 'Table_1' / 'Table 2' 等形式，无实际文件路径。""" + if not asset_ref: + return False + return str(asset_ref).strip().lower().startswith("table") + + +def ensure_minueru_output(state: Any) -> None: + """若 state 无 minueru_output，尝试从 mineru_root 下首个 .md 读取（供 table_extractor 使用）。""" + if getattr(state, "minueru_output", "") and str(state.minueru_output).strip(): + return + mineru_root = getattr(state, "mineru_root", "") or "" + if not mineru_root: + return + root = Path(mineru_root).expanduser().resolve() + if not root.is_dir(): + return + md_files = list(root.glob("*.md")) + if not md_files: + return + target = md_files[0] + if len(md_files) > 1: + for f in md_files: + if f.stat().st_size > target.stat().st_size: + target = f + try: + state.minueru_output = target.read_text(encoding="utf-8")[:30000] + except Exception as e: + log.warning("从 mineru_root 读取 md 失败: %s", e) + + +def merge_pdfs(pdf_paths: List[str], output_path: Union[str, Path]) -> str: + """将多份 PDF 按顺序合并为一份。要求 pdf_paths 中路径存在且为 PDF。""" + if not pdf_paths: + raise ValueError("merge_pdfs: pdf_paths 不能为空") + try: + import fitz # PyMuPDF + except ImportError: + raise ImportError("merge_pdfs 需要 PyMuPDF (pip install pymupdf)") + out = Path(output_path).expanduser().resolve() + out.parent.mkdir(parents=True, exist_ok=True) + merged = fitz.open() + for p in pdf_paths: + path = Path(p).expanduser().resolve() + if not path.is_file(): + log.warning("merge_pdfs: 跳过不存在的文件 %s", path) + continue + with fitz.open(path) as src: + merged.insert_pdf(src) + merged.save(out) + merged.close() + log.info("merge_pdfs: 已合并 %s 个 PDF -> %s", len(pdf_paths), out) + return str(out) + + def beamer_code_validator(content: str, parsed_result: Dict[str, Any]) -> Tuple[bool, Optional[str]]: """检查tex是否是正确的""" from tempfile import TemporaryDirectory diff --git a/dataflow_agent/workflow/registry.py b/dataflow_agent/workflow/registry.py index 501f757a..6cfa16e0 100644 --- a/dataflow_agent/workflow/registry.py +++ b/dataflow_agent/workflow/registry.py @@ -8,7 +8,10 @@ class RuntimeRegistry: def register(cls, name: str, factory: Callable): # 同一个对象重复登记 → 忽略 if name in cls._workflows: - if cls._workflows[name] is factory: + if cls._workflows[name] is factory: + return + # 同一函数被导入两次（如先被包批量 import，再作为 __main__ 执行）时，忽略第二次 + if getattr(cls._workflows[name], "__qualname__", None) == getattr(factory, "__qualname__", None): return raise ValueError( f"Workflow '{name}' already registered by " diff --git a/dataflow_agent/workflow/wf_paper2ppt_beamer.py b/dataflow_agent/workflow/wf_paper2ppt_beamer.py new file mode 100644 index 00000000..9addeea2 --- /dev/null +++ b/dataflow_agent/workflow/wf_paper2ppt_beamer.py @@ -0,0 +1,235 @@ +""" +paper2ppt_beamer workflow +~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ +pagecontent（来自 paper2page_content）→ 每页单独生成 Beamer → 每页编译成 PDF → 合并为一份 PDF → _end_。 +调用方需先跑 paper2page_content，再传入带 pagecontent / result_path / mineru_root 的 state。 +""" + +from __future__ import annotations + +import json +import shutil +from pathlib import Path + +from dataflow_agent.state import Paper2PptBeamerRequest, Paper2PptBeamerState +from dataflow_agent.graphbuilder.graph_builder import GenericGraphBuilder +from dataflow_agent.workflow.registry import register +from dataflow_agent.toolkits.p2vtool.p2v_tool import ( + compile_tex, + merge_pdfs, + is_overfull_warning, + is_table_asset, + ensure_minueru_output, +) +from dataflow_agent.logger import get_logger + +log = get_logger(__name__) + + +@register("paper2ppt_beamer_pagecontent") +def create_paper2ppt_beamer_graph() -> GenericGraphBuilder: + """ + Workflow factory: dfa run --wf paper2ppt_beamer_pagecontent + pagecontent → 每页 pagecontent_to_beamer + compile → merge_slides → _end_ + """ + builder = GenericGraphBuilder( + state_model=Paper2PptBeamerState, + entry_point="_start_", + ) + + def _request_language(state: Paper2PptBeamerState) -> str: + req = state.request + if isinstance(req, dict): + return req.get("language", "en") + return getattr(req, "language", "en") + + @builder.pre_tool("pagecontent", "p2b_pagecontent_to_beamer") + def get_pagecontent(state: Paper2PptBeamerState): + pc = getattr(state, "pagecontent", None) + return pc or [] + + @builder.pre_tool("output_language", "p2b_pagecontent_to_beamer") + def get_output_language(state: Paper2PptBeamerState): + language_map = {"en": "English", "zh": "Chinese"} + return language_map.get(_request_language(state), "English") + + @builder.pre_tool("pdf_images_working_dir", "p2b_pagecontent_to_beamer") + def get_pdf_images_working_dir(state: Paper2PptBeamerState): + result_path = getattr(state, "result_path", "") or "" + if result_path: + return str(Path(result_path).expanduser().resolve() / "auto") + return "" + + # ---------------------------------------------------------------------- + # NODES + # ---------------------------------------------------------------------- + + async def p2b_pagecontent_to_beamer( + state: Paper2PptBeamerState, + ) -> Paper2PptBeamerState: + from dataflow_agent.agentroles import create_simple_agent, create_react_agent + + pages = getattr(state, "pagecontent", None) or [] + result_path = Path(getattr(state, "result_path", "") or ".").expanduser().resolve() + auto_dir = result_path / "auto" + auto_dir.mkdir(parents=True, exist_ok=True) + + max_error_retries = 2 + max_warning_fixes = 3 + + p2b_agent = create_simple_agent( + name="p2b_pagecontent_to_beamer", + model_name="gpt-5.2-codex-medium", + temperature=0.1, + parser_type="json", + ) + debug_agent = create_simple_agent( + name="p2v_beamer_code_debug", + model_name="gpt-5.2-codex-medium", + temperature=0.1, + parser_type="json", + ) + + per_page_beamer_paths: list[str] = [] + per_page_pdf_paths: list[str] = [] + full_pagecontent = list(pages) + + for i, one_page in enumerate(pages): + log.info("生成第 %s/%s 页 Beamer 并编译", i + 1, len(pages)) + state.pagecontent = [one_page] + + # ---------- Table：asset_ref 为 Table_1 等时先跑 table_extractor，再改写 asset_ref ---------- + asset_ref = one_page.get("asset_ref") or one_page.get("asset") or "" + asset_ref = str(asset_ref).strip() if asset_ref else "" + if asset_ref and is_table_asset(asset_ref): + table_img_path = one_page.get("table_img_path") or one_page.get("table_png_path") or "" + table_img_path = str(table_img_path).strip() + if not table_img_path: + ensure_minueru_output(state) + state.asset_ref = asset_ref + state.result_path = str(result_path) + table_agent = create_react_agent( + name="table_extractor", + temperature=0.1, + max_retries=6, + parser_type="json", + ) + state = await table_agent.execute(state=state) + table_img_path = str(getattr(state, "table_img_path", "") or "").strip() + if table_img_path and Path(table_img_path).exists(): + table_in_auto = auto_dir / f"table_page{i}.png" + shutil.copy(table_img_path, table_in_auto) + one_page["asset_ref"] = table_in_auto.name + one_page["table_img_path"] = str(table_in_auto) + state.pagecontent = [one_page] + log.info("第 %s 页表格已提取并写入 %s", i + 1, table_in_auto) + else: + log.warning("第 %s 页表格提取未得到 table_img_path，Beamer 中该页表格可能缺失", i + 1) + + page_tex = auto_dir / f"page_{i}.tex" + is_wrong = True + is_warning = False + code_debug_result = "" + + # ---------- Error 重试 ---------- + for error_attempt in range(max_error_retries): + state = await p2b_agent.execute(state=state) + if not getattr(state, "beamer_code_path", ""): + log.warning("第 %s 页未得到 beamer 代码，第 %s 次重试", i + 1, error_attempt + 1) + continue + shutil.copy(state.beamer_code_path, page_tex) + try: + is_wrong, is_warning, code_debug_result = compile_tex(str(page_tex)) + except Exception as e: + is_wrong, is_warning, code_debug_result = True, True, str(e) + log.warning("第 %s 页编译异常: %s", i + 1, e) + if not is_wrong: + break + log.warning("第 %s 页编译 error，第 %s/%s 次重新生成", i + 1, error_attempt + 1, max_error_retries) + + if is_wrong: + log.warning("第 %s 页经 %s 次重试仍有 error，跳过", i + 1, max_error_retries) + per_page_beamer_paths.append(str(page_tex)) + continue + + # ---------- Warning 修复（Overfull）：通过 state.pre_tool_results 注入，供 debug agent 的 execute_pre_tools 合并进 prompt ---------- + if is_warning and is_overfull_warning(code_debug_result): + for fix_attempt in range(max_warning_fixes): + state.beamer_code_path = str(page_tex) + state.is_beamer_wrong = is_wrong + state.is_beamer_warning = is_warning + state.code_debug_result = code_debug_result + state.pre_tool_results = { + "beamer_code": page_tex.read_text(encoding="utf-8"), + "code_debug_result": code_debug_result, + } + state = await debug_agent.execute(state) + + is_wrong = getattr(state, "is_beamer_wrong", True) + is_warning = getattr(state, "is_beamer_warning", False) + code_debug_result = getattr(state, "code_debug_result", "") + if is_wrong: + break + if not is_warning or not is_overfull_warning(code_debug_result): + break + log.info("第 %s 页 Overfull warning，第 %s/%s 次修复", i + 1, fix_attempt + 1, max_warning_fixes) + + per_page_beamer_paths.append(str(page_tex)) + pdf_path = page_tex.with_suffix(".pdf") + if pdf_path.exists(): + per_page_pdf_paths.append(str(pdf_path)) + + state.pagecontent = full_pagecontent + state.per_page_beamer_paths = per_page_beamer_paths + state.per_page_pdf_paths = per_page_pdf_paths + log.info("每页生成与编译完成: %s 个 tex, %s 个 pdf", len(per_page_beamer_paths), len(per_page_pdf_paths)) + return state + + def merge_slides_node(state: Paper2PptBeamerState) -> Paper2PptBeamerState: + log.info("开始执行 merge_slides_node") + pdf_paths = getattr(state, "per_page_pdf_paths", None) or [] + if not pdf_paths: + log.warning("无每页 PDF，无法合并") + return state + result_path = Path(getattr(state, "result_path", "") or ".").expanduser().resolve() + merged_path = result_path / "auto" / "merged.pdf" + state.ppt_path = merge_pdfs(pdf_paths, merged_path) + log.info("合并完成: %s", state.ppt_path) + return state + + def _start_(state: Paper2PptBeamerState) -> Paper2PptBeamerState: + return state + + def _end_(state: Paper2PptBeamerState) -> Paper2PptBeamerState: + return state + + nodes = { + "_start_": _start_, + "p2b_pagecontent_to_beamer": p2b_pagecontent_to_beamer, + "merge_slides": merge_slides_node, + "_end_": _end_, + } + + edges = [ + ("_start_", "p2b_pagecontent_to_beamer"), + ("p2b_pagecontent_to_beamer", "merge_slides"), + ("merge_slides", "_end_"), + ] + + builder.add_nodes(nodes).add_edges(edges) + return builder + +if __name__ == "__main__": + import asyncio + + result_path = Path("outputs/default/paper2ppt/1772284521/input") + pagecontent = [{'title': 'DataFlow: LLM驱动的统一数据准备与工作流自动化框架', 'layout_description': '整页居中布局，仅包含标题、副标题和汇报人信息。标题大号加粗居中，副标题为论文完整英文标题置于标题下方，作者及汇报人信息放在页面下方居中，不放任何图表。', 'key_points': ['DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI', '作者：Hao Liang 等，机构：Peking University 等', '汇报人：XXX'], 'asset_ref': None}, {'title': '研究背景与问题：LLM时代的数据准备挑战', 'layout_description': '上方简要小结背景，两栏布局：左侧为要点式文本，右侧为对比表格示意区（可用表格或示意图说明现有系统特点对比），下方一行突出本工作目标。', 'key_points': ['LLM 发展依赖大规模、高质量、语义丰富的数据准备流程，涉及合成、精炼、过滤和领域特定转换。', '当前实践以临时脚本和松散工作流为主，缺乏统一抽象、原子算子与可优化、可重现的数据流表示。', '传统大数据引擎（Spark、Dask、Hadoop）对模型闭环、GPU高效批处理和文本语义操作支持不足，工程负担巨大。', '现有数据准备系统如 NeMo Curator、Data-Juicer 主要聚焦提取与过滤，对多步生成与语义精炼的模型闭环工作流支持有限。', '研究问题：如何构建一个以 LLM 为一等公民、可编程、可复用、可扩展的统一数据准备框架？'], 'asset_ref': None}, {'title': 'DataFlow 概览：目标、定位与整体架构', 'layout_description': '上部用一两行文字概述 DataFlow 作为统一系统的定位，中间居中放系统架构示意图（核心执行引擎+管线+CLI+Agent+生态），下方采用两列要点：左列列出六大设计目标，右列说明系统范围与工作流。', 'key_points': ['系统定位：面向多领域 LLM 数据准备的统一、自动化系统，以 LLM 驱动合成与精炼为核心，覆盖文本、数学推理、代码、Text-to-SQL、Agentic RAG 和大规模知识抽取。', '设计目标：易用性（PyTorch 风格、IDE 友好）、可扩展性（模块化算子与管线）、统一范式（跨领域抽象）、性能效率（不牺牲 SOTA 表现）、智能自动化（Agent 解释自然语言意图）、开源与社区生态。', '核心组件：全局存储抽象、统一 LLM Serving、算子库、Prompt 模板、管线 Zoo，以及基于 Python 包的扩展生态 DataFlow-Ecosystem。', '用户控制层：命令行工具链（CLI）用于脚本化执行，DataFlow-Agent 将自然语言规格翻译为可执行管线并迭代调试。', '输出形态：高质量、任务对齐的数据集，可直接用于下游 LLM 训练与评测。'], 'asset_ref': 'images/ba397b4c85a1c1bd0022e9dd145db42f9ab3f956df48273d92694b3cad820a48.jpg'}, {'title': '框架设计：存储抽象、接口层次与算子生态', 'layout_description': '左右分栏布局：左侧重点用流程步骤和要点解释全局存储抽象与算子交互模式，右侧上方放算子执行模式示意图，下方用简短 bullet 解释层次化接口（Serving/Operator/Prompt/Pipeline）。', 'key_points': ['全局存储抽象：以表格化键值结构统一表示指令、回答、CoT、评分与元数据，DataFlowStorage 提供 backend 无关的 read()/write() 接口，算子只面向逻辑视图。', '算子执行模式：遵循统一的 read–transform–write 流程，可以在不修改内部逻辑的前提下重排、复用与批处理；默认实现基于 Pandas，支持 JSON/JSONL/CSV/Parquet 等格式。', '统一 LLM Serving API：generate_from_input(user_inputs, system_prompt, json_schema) 将本地引擎（vLLM、SGLang）与在线服务（ChatGPT、Gemini）统一抽象，屏蔽批处理、重试与限流细节。', '层次化接口：算子定义可复用数据变换单元，Prompt 模板声明输入渲染和输出结构约束，管线将算子按显式依赖组合成多阶段工作流，可编译验证与优化。', '算子与生态：近 200 个可复用算子，分为生成、评估、过滤、精炼四大类，搭配 90+ Prompt 模板，并通过 Python 包实现 DataFlow-Extensions，形成可插拔、社区驱动的 DataFlow-Ecosystem。'], 'asset_ref': 'images/31c09ede8e57c6b583ac2663f145fd113a811470772998506d502e3bb5ebf3ea.jpg'}, {'title': 'DataFlow-Agent 与实验结果：自动化管线构建与性能提升', 'layout_description': '上半部分两列：左列介绍 DataFlow-Agent 的角色设计与智能管线推荐，右列概括六大用例管线（文本、数学、代码、Text-to-SQL、Agentic RAG、知识抽取）。下半部分用要点强调核心实验结果与性能增益。', 'key_points': ['DataFlow-Agent 作为编排层：基于 AgentRoles 理解自然语言规格，执行算子合成、管线规划与迭代验证，可自动构造和调试新的数据准备工作流。', '智能管线推荐：面向目标任务与数据源，自动选择合适的算子组合与模板，降低工程门槛，加速原型迭代。', '六大代表性用例：文本数据准备、数学推理数据、代码处理、Text-to-SQL 数据生成、Agentic RAG 数据构造、从网页/PDF 的大规模知识抽取。', '实验结果（部分）：Text-to-SQL 管线在仅使用 <0.1M 样本的情况下，相比 250 万样本 SynSQL 提升约 +3% 执行准确率；代码管线在多个基准上平均提升超过 7%。', '统一数据集效果：将文本、数学、代码数据融合为 DataFlowInstruct-10K，仅 10K 样本即可让 Qwen2-base/Qwen2.5-base 超过在 100 万 Infinity-Instruct 上训练的同规模模型，并接近对应 Instruct 模型性能。', '整体结论：DataFlow 管线在六个场景中普遍带来 1–3 分甚至更高的性能增益，验证了统一抽象与 LLM 驱动数据合成在质量与数据效率上的优势。'], 'asset_ref': 'images/80627ebb10b377adbb7f5c301c785fa17fd0ba4b8a49b0942f308faba59aa249.jpg'}, {'title': '总结与致谢', 'layout_description': '上方 concise 总结本文贡献，中间用要点强调框架价值与未来方向，下方居中放置“致谢”字样及感谢合作者和数据/代码开源社区，不放图表。', 'key_points': ['工作总结：提出 DataFlow——一个以 LLM 为中心、具备可编程算子与 PyTorch 风格管线抽象的统一数据准备框架，系统性提升了 LLM 数据构造的可复用性、可重现性与可扩展性。', '技术贡献：构建近 200 个算子与六大高性能模板管线，提供统一 LLM Serving、全局存储、层次化接口与扩展生态，并通过 DataFlow-Agent 实现自然语言到可执行管线的自动化映射。', '实证结论：在文本、数学、代码、Text-to-SQL、Agentic RAG、知识抽取等多场景中，DataFlow 生成的数据显著提升下游 LLM 性能和数据效率，部分场景超过精心人工或专用合成数据集。', '未来方向：进一步扩展多模态与多语言算子与管线，强化分布式执行与调优能力，推动 DataFlow 成为数据中心 AI 时代社区共享的统一数据准备协议。', '致谢：感谢合作者、开源社区（模型、数据、工具）及相关项目团队对本工作的支持与启发。'], 'asset_ref': None}] + + graph_builder = create_paper2ppt_beamer_graph().build() + state = Paper2PptBeamerState( + request=Paper2PptBeamerRequest(language="zh"), + pagecontent=pagecontent, + result_path=str(result_path), + mineru_root=str(result_path), + ) + state = asyncio.run(graph_builder.ainvoke(state)) diff --git a/dataflow_agent/workflow/wf_paper2video.py b/dataflow_agent/workflow/wf_paper2video.py index a3702a5e..ff540bf9 100644 --- a/dataflow_agent/workflow/wf_paper2video.py +++ b/dataflow_agent/workflow/wf_paper2video.py @@ -22,9 +22,9 @@ from langgraph.graph import StateGraph from langgraph.prebuilt import ToolNode, tools_condition from dataflow_agent.toolkits.p2vtool.p2v_tool import ( - compile_tex, beamer_code_validator, get_image_paths, parse_script_with_cursor, + get_image_paths, parse_script_with_cursor, transcribe_with_whisperx, cursor_infer, get_audio_paths, get_audio_length, - clean_text, parser_beamer_latex, resize_latex_image, + clean_text, talking_gen_per_slide, render_video_with_cursor_from_json, add_subtitles, merge_wav_files, get_mp4_duration_ffprobe, speech_task_wrapper_with_cloud_tts, @@ -50,75 +50,9 @@ def create_paper2video_graph() -> GenericGraphBuilder: entry_point="_start_") # 自行修改入口 # ---------------------------------------------------------------------- - # TOOLS (pre_tool definitions) + # TOOLS (pre_tool definitions，仅 paper2video 相关) # ---------------------------------------------------------------------- - @builder.pre_tool("pdf_markdown", "p2v_extract_pdf") - def get_markdown(state: Paper2VideoState): - import subprocess - paper_pdf_path = Path(state.request.get("paper_pdf_path", "")) - if not paper_pdf_path.exists(): - log.error(f"PDF 文件不存在: {paper_pdf_path}") - return "" - paper_pdf_dir = paper_pdf_path.with_suffix('').parent - if not paper_pdf_path.with_suffix('').exists(): - #fixme: 这里需要修改为部署机器上的mineru - # run_mineru_pdf_extract(str(paper_pdf_path), str(paper_pdf_dir), "modelscope") - pass - paper_base_path = paper_pdf_path.with_suffix('').expanduser().resolve() - paper_output_dir = paper_base_path - markdown_path = paper_output_dir / "auto" / f"{paper_base_path.name}.md" - if not markdown_path.exists(): - log.error(f"Markdown 文件不存在: {str(markdown_path)}") - return "" - try: - markdown_content = markdown_path.read_text(encoding='utf-8') - return markdown_content - except Exception as e: - log.error(f'读取 markdown 文件内容失败：{markdown_path}. 错误：{e}') - return "" - - @builder.pre_tool("pdf_images_working_dir", "p2v_extract_pdf") - def get_images_relative_path(state: Paper2VideoState): - paper_pdf_path = Path(state.request.get("paper_pdf_path", "")) - if not paper_pdf_path.exists(): - log.error(f"PDF 文件不存在: {paper_pdf_path}") - return "" - paper_base_path = paper_pdf_path.with_suffix('').expanduser().resolve() - paper_output_dir = paper_base_path - images_dir = paper_output_dir/"auto" - if not images_dir.exists(): - log.error(f"没有生成对应的图片，MinerU 识别图像失败：{images_dir}") - return "" - return str(images_dir) - - @builder.pre_tool("output_language", "p2v_extract_pdf") - def get_language(state: Paper2VideoState): - language_map = { - 'en': "English", - 'zh': "Chinese", - } - language = state.request.language - return language_map.get(language, "English") - - @builder.pre_tool("is_beamer_wrong", "p2v_beamer_code_debug") - def get_is_code_wrong(state: Paper2VideoState): - return state.is_beamer_wrong - - @builder.pre_tool("is_beamer_warning", "p2v_beamer_code_debug") - def get_is_code_warning(state: Paper2VideoState): - return state.is_beamer_warning - - @builder.pre_tool("code_debug_result", "p2v_beamer_code_debug") - def get_compile_result(state: Paper2VideoState): - return state.code_debug_result - - @builder.pre_tool("beamer_code", "p2v_beamer_code_debug") - def get_beamer_code(state: Paper2VideoState): - beamer_code_path = state.beamer_code_path - beamer_code = Path(beamer_code_path).read_text(encoding='utf-8') - return beamer_code - @builder.pre_tool("video_language", "p2v_subtitle_and_cursor") def get_video_language(state: Paper2VideoState): language = "Chinese" if state.request.language == "zh" else "English" @@ -147,128 +81,8 @@ def get_video_language(state: Paper2VideoState): # ---------------------------------------------------------------------- # ============================================================== - # NODES + # NODES (仅 paper2video 相关) # ============================================================== - async def extract_pdf_node(state: Paper2VideoState) -> Paper2VideoState: - from dataflow_agent.agentroles import create_vlm_agent - log.info("开始执行extract_pdf_node节点") - agent = create_vlm_agent( - name="p2v_extract_pdf", - vlm_mode="understanding", # 视觉模式: 'understanding', 'generation', 'edit' - image_detail="high", # 图像细节: 'low', 'high', 'auto' - model_name="gpt-4o-2024-11-20", # 视觉模型 - temperature=0.1, - max_image_size=(2048, 2048), # 最大图像尺寸 - - # additional_params={}, # 额外VLM参数，可以存放图片用法为："input_image": image_path - ) - - state = await agent.execute(state=state) - - # 可选：处理执行结果 - # agent_result = state.agent_results.get(agent.role_name, {}) - # log.info(f"Agent {agent.role_name} 执行结果: {agent_result}") - - return state - - def compile_beamer_node(state: Paper2VideoState) -> Paper2VideoState: - log.info(f"开始执行compile_beamer_node") - beamer_code_path = state.beamer_code_path - state.is_beamer_wrong, state.is_beamer_warning, state.code_debug_result = compile_tex(beamer_code_path) - if not state.is_beamer_warning: - log.info(f"Beamer 代码编译成功，无需调试") - state.ppt_path = state.beamer_code_path.replace(".tex", ".pdf") - return state - - async def beamer_code_debug_node(state: Paper2VideoState) -> Paper2VideoState: - from dataflow_agent.agentroles import create_react_agent - log.info(f"开始执行 p2v_beamer_code_debug node节点") - agent = create_react_agent( - name="p2v_beamer_code_debug", - model_name="gpt-4o-2024-11-20", - max_retries=10, - validators=[beamer_code_validator], - ) - state = await agent.execute(state) - return state - - async def beamer_code_upgrade_node(state: Paper2VideoState) -> Paper2VideoState: - log.info(f"开始执行 p2v_beamer_code_debug node节点") - from dataflow_agent.agentroles import create_vlm_agent - from tempfile import TemporaryDirectory - import subprocess - from pdf2image import convert_from_path - - beamer_code_path = state.beamer_code_path - old_beamer_code = Path(beamer_code_path).read_text(encoding='utf-8') - - head, frames_code = parser_beamer_latex(old_beamer_code) - final_frames = [] - doc_header = ["\\documentclass{beamer}", head, "\\begin{document}"] - doc_footer = ["\\end{document}"] - - for frame_code in frames_code: - current_frame_content = ["\\begin{frame}", frame_code, "\\end{frame}"] - - if "includegraphics" not in frame_code: - final_frames.extend(current_frame_content) - continue - - attempt_code = current_frame_content - img_size_debug = True - - while img_size_debug: - with TemporaryDirectory() as temp_dir_name: - temp_dir = Path(temp_dir_name) - # 在临时目录中创建 .tex 文件 - tex_path = temp_dir / "input.tex" - - full_temp_tex = doc_header + attempt_code + doc_footer - tex_path.write_text("\n".join(full_temp_tex), encoding='utf-8') - try: - subprocess.run( - ["tectonic", str(tex_path)], - check=True, capture_output=True, text=True, cwd=temp_dir - ) - - frame_pdf_path = tex_path.with_suffix('.pdf') - img_path = tex_path.with_suffix('.png') - - if frame_pdf_path.exists(): - images = convert_from_path(str(frame_pdf_path)) - images[0].save(str(img_path)) - - agent = create_vlm_agent( - name="p2v_beamer_code_upgrade", - vlm_mode="understanding", - model_name="gpt-4o-2024-11-20", - additional_params={"input_image": str(img_path)}, - ) - - state = await agent.execute(state=state) - img_size_debug = getattr(state, 'img_size_debug', False) - - if img_size_debug: - log.info(f"当前图片尺寸超出了ppt一页，需要修改：{attempt_code}") - attempt_code = resize_latex_image(attempt_code) - else: - final_frames.extend(attempt_code) - else: - log.error("PDF 未生成，跳过调试") - final_frames.extend(attempt_code) - break - except Exception as e: - log.error(f"解析单张ppt发生了错误: {e}") - final_frames.extend(attempt_code) - break - full_new_code = doc_header + final_frames + doc_footer - Path(beamer_code_path).write_text("\n".join(full_new_code), encoding='utf-8') - compile_tex(beamer_code_path) - state.ppt_path = str(Path(beamer_code_path).with_suffix(".pdf")) - log.info(f"将更新好的beamer code写回 {beamer_code_path}") - - return state - async def subtitle_and_cursor(state: Paper2VideoState) -> Paper2VideoState: ''' @@ -756,25 +570,6 @@ def merge_all(state: Paper2VideoState): state.video_path = str(tmp_merage_3) return state - async def compile_beamer_condition(state: Paper2VideoState): - # todo: 暂时先这样判断 - if state.is_beamer_warning: - return "p2v_beamer_code_debug" - else: - return "_end_" - - - async def pdf2ppt_node(state: Paper2VideoState) -> Paper2VideoState: - - log.info(f"开始执行 pdf2ppt node节点") - from dataflow_agent.agentroles import create_simple_agent - # agent = create_simple_agent( - # name="" - # ) - - - return state - def _stage_condition(state: Paper2VideoState): if state.request.script_stage: log.critical("进入subtitle_and_cursor stage") @@ -797,19 +592,13 @@ def _after_speech_condition(state: Paper2VideoState): # ============================================================== nodes = { "_start_": lambda state: state, - "p2v_extract_pdf": extract_pdf_node, - "compile_beamer": compile_beamer_node, - "p2v_beamer_code_debug": beamer_code_debug_node, - "p2v_beamer_code_upgrade": beamer_code_upgrade_node, "p2v_subtitle_and_cursor": subtitle_and_cursor, "p2v_refine_subtitle_and_cursor": refine_subtitle_and_cursor, "p2v_generate_speech": generate_speech, "p2v_generate_talking_video": generate_talking_video, "p2v_generate_cursor": generate_cursor, - "p2v_merge": merge_all, - "pdf2ppt": pdf2ppt_node, - - '_end_': lambda state: state, # 终止节点 + "p2v_merge": merge_all, + "_end_": lambda state: state, } # ------------------------------------------------------------------ diff --git a/fastapi_app/workflow_adapters/wa_paper2ppt.py b/fastapi_app/workflow_adapters/wa_paper2ppt.py index a6a11894..b59d60fe 100644 --- a/fastapi_app/workflow_adapters/wa_paper2ppt.py +++ b/fastapi_app/workflow_adapters/wa_paper2ppt.py @@ -355,7 +355,7 @@ async def run_paper2ppt_full_pipeline(req: Paper2PPTRequest) -> Paper2PPTRespons state_pc.pagecontent = pagecontent state_pc.result_path = final_result_path - state_pp: Paper2FigureState = await run_workflow("paper2ppt", state_pc) + state_pp: Paper2FigureState = await run_workflow("paper2ppt_parallel_consistent_style", state_pc) ppt_pdf_path = getattr(state_pp, "ppt_pdf_path", "") ppt_pptx_path = getattr(state_pp, "ppt_pptx_path", "") diff --git a/frontend-workflow/vite.config.ts b/frontend-workflow/vite.config.ts index 52dcfe69..92531ab6 100644 --- a/frontend-workflow/vite.config.ts +++ b/frontend-workflow/vite.config.ts @@ -1,42 +1,42 @@ import { defineConfig } from 'vite' import react from '@vitejs/plugin-react' -// export default defineConfig({ -// plugins: [react()], -// server: { -// port: 3123, -// open: true, -// allowedHosts: true, -// proxy: { -// '/api': { -// target: 'http://localhost:8123', -// changeOrigin: true, -// }, -// '/outputs': { -// target: 'http://localhost:8123', -// changeOrigin: true, -// }, -// }, -// }, -// }) - export default defineConfig({ plugins: [react()], server: { - port: 3111, + port: 3123, open: true, allowedHosts: true, proxy: { '/api': { - // target: 'http://localhost:8000', - target: 'http://paper2any-test-back.nas.cpolar.cn/', // FastAPI 后端地址 + target: 'http://localhost:8123', changeOrigin: true, }, '/outputs': { - // target: 'http://localhost:8000', - target: 'http://paper2any-test-back.nas.cpolar.cn/', + target: 'http://localhost:8123', changeOrigin: true, }, }, }, -}) \ No newline at end of file +}) + +// export default defineConfig({ +// plugins: [react()], +// server: { +// port: 3111, +// open: true, +// allowedHosts: true, +// proxy: { +// '/api': { +// // target: 'http://localhost:8000', +// target: 'http://paper2any-test-back.nas.cpolar.cn/', // FastAPI 后端地址 +// changeOrigin: true, +// }, +// '/outputs': { +// // target: 'http://localhost:8000', +// target: 'http://paper2any-test-back.nas.cpolar.cn/', +// changeOrigin: true, +// }, +// }, +// }, +// }) \ No newline at end of file From a154a2c4cf12b4e9d8bf82b4538dbcc9293fa6c4 Mon Sep 17 00:00:00 2001 From: LittleLucifer1 <2697699085@qq.com> Date: Mon, 2 Mar 2026 10:29:24 +0800 Subject: [PATCH 2/4] Upgrade the beamer code --- .../p2b_pagecontent_to_beamer_agent.py | 31 ++++++++++++++--- .../p2v_beamer_code_debug_agent.py | 28 +++++++++++++++- .../workflow/wf_paper2ppt_beamer.py | 33 ++++--------------- 3 files changed, 60 insertions(+), 32 deletions(-) diff --git a/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py b/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py index 9e5e12be..83328621 100644 --- a/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py +++ b/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py @@ -54,16 +54,39 @@ def get_task_prompt_params(self, pre_tool_results: Dict[str, Any]) -> Dict[str, def get_default_pre_tool_results(self) -> Dict[str, Any]: return {} + def _get_beamer_code_from_result(self, result: Dict[str, Any]) -> str: + """从 result 中取出 Beamer 代码，兼容规范 dict 或解析失败时的 {"raw": content}。""" + raw = result.get("latex_code", "") if isinstance(result, dict) else "" + if isinstance(raw, str) and raw: + code = extract_beamer_code(raw) + if code: + return code + # 解析失败时 result 可能为 {"raw": content}，尝试从原始文本提取 + raw_content = result.get("raw", "") if isinstance(result, dict) else "" + if isinstance(raw_content, str) and raw_content: + code = extract_beamer_code(raw_content) + if code: + return code + try: + from dataflow_agent.utils import robust_parse_json + parsed = robust_parse_json(raw_content) + if isinstance(parsed, dict): + raw = parsed.get("latex_code", "") + if isinstance(raw, str) and raw: + code = extract_beamer_code(raw) + if code: + return code + except Exception: + pass + return "" + def update_state_result( self, state: MainState, result: Dict[str, Any], pre_tool_results: Dict[str, Any], ): - raw = result.get("latex_code", "") if isinstance(result, dict) else "" - beamer_code = "" - if isinstance(raw, str): - beamer_code = extract_beamer_code(raw) + beamer_code = self._get_beamer_code_from_result(result) if not beamer_code: log.error("p2b_pagecontent_to_beamer: 未得到有效 Beamer 代码") super().update_state_result(state, result, pre_tool_results) diff --git a/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py b/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py index eec57bac..7bf617d0 100644 --- a/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py +++ b/dataflow_agent/agentroles/paper2any_agents/p2v_beamer_code_debug_agent.py @@ -18,6 +18,7 @@ from dataflow_agent.logger import get_logger from dataflow_agent.agentroles.cores.base_agent import BaseAgent from dataflow_agent.agentroles.cores.registry import register +from dataflow_agent.toolkits.p2vtool.p2v_tool import extract_beamer_code log = get_logger(__name__) @@ -67,6 +68,31 @@ async def execute_pre_tools(self, state: MainState) -> Dict[str, Any]: results[key] = inject[key] return results + def _get_beamer_code_from_result(self, result: Dict[str, Any]) -> str: + """从 result 中取出 Beamer 代码，兼容规范 dict 或解析失败时的 {"raw": content}。""" + raw = result.get("latex_code", "") if isinstance(result, dict) else "" + if isinstance(raw, str) and raw: + code = extract_beamer_code(raw) + if code: + return code + raw_content = result.get("raw", "") if isinstance(result, dict) else "" + if isinstance(raw_content, str) and raw_content: + code = extract_beamer_code(raw_content) + if code: + return code + try: + from dataflow_agent.utils import robust_parse_json + parsed = robust_parse_json(raw_content) + if isinstance(parsed, dict): + raw = parsed.get("latex_code", "") + if isinstance(raw, str) and raw: + code = extract_beamer_code(raw) + if code: + return code + except Exception: + pass + return "" + # ---------- 结果写回 ---------- def update_state_result( self, @@ -75,7 +101,7 @@ def update_state_result( pre_tool_results: Dict[str, Any], ): """将推理结果 {latex_code: xxxx} 写回 MainState""" - beamer_code = result.get("latex_code", '') + beamer_code = self._get_beamer_code_from_result(result) beamer_code_path = state.beamer_code_path if beamer_code and beamer_code_path: from pathlib import Path diff --git a/dataflow_agent/workflow/wf_paper2ppt_beamer.py b/dataflow_agent/workflow/wf_paper2ppt_beamer.py index 9addeea2..983dc743 100644 --- a/dataflow_agent/workflow/wf_paper2ppt_beamer.py +++ b/dataflow_agent/workflow/wf_paper2ppt_beamer.py @@ -19,7 +19,6 @@ merge_pdfs, is_overfull_warning, is_table_asset, - ensure_minueru_output, ) from dataflow_agent.logger import get_logger @@ -67,15 +66,16 @@ def get_pdf_images_working_dir(state: Paper2PptBeamerState): async def p2b_pagecontent_to_beamer( state: Paper2PptBeamerState, ) -> Paper2PptBeamerState: - from dataflow_agent.agentroles import create_simple_agent, create_react_agent + from dataflow_agent.agentroles import create_simple_agent pages = getattr(state, "pagecontent", None) or [] result_path = Path(getattr(state, "result_path", "") or ".").expanduser().resolve() auto_dir = result_path / "auto" auto_dir.mkdir(parents=True, exist_ok=True) + # fixme: 这里硬编码了重试的次数，后续可能需要修改 max_error_retries = 2 - max_warning_fixes = 3 + max_warning_fixes = 5 p2b_agent = create_simple_agent( name="p2b_pagecontent_to_beamer", @@ -98,33 +98,12 @@ async def p2b_pagecontent_to_beamer( log.info("生成第 %s/%s 页 Beamer 并编译", i + 1, len(pages)) state.pagecontent = [one_page] - # ---------- Table：asset_ref 为 Table_1 等时先跑 table_extractor，再改写 asset_ref ---------- + # asset_ref 为 Table_1 等时直接忽略，不跑 table_extractor asset_ref = one_page.get("asset_ref") or one_page.get("asset") or "" asset_ref = str(asset_ref).strip() if asset_ref else "" if asset_ref and is_table_asset(asset_ref): - table_img_path = one_page.get("table_img_path") or one_page.get("table_png_path") or "" - table_img_path = str(table_img_path).strip() - if not table_img_path: - ensure_minueru_output(state) - state.asset_ref = asset_ref - state.result_path = str(result_path) - table_agent = create_react_agent( - name="table_extractor", - temperature=0.1, - max_retries=6, - parser_type="json", - ) - state = await table_agent.execute(state=state) - table_img_path = str(getattr(state, "table_img_path", "") or "").strip() - if table_img_path and Path(table_img_path).exists(): - table_in_auto = auto_dir / f"table_page{i}.png" - shutil.copy(table_img_path, table_in_auto) - one_page["asset_ref"] = table_in_auto.name - one_page["table_img_path"] = str(table_in_auto) - state.pagecontent = [one_page] - log.info("第 %s 页表格已提取并写入 %s", i + 1, table_in_auto) - else: - log.warning("第 %s 页表格提取未得到 table_img_path，Beamer 中该页表格可能缺失", i + 1) + one_page["asset_ref"] = None + state.pagecontent = [one_page] page_tex = auto_dir / f"page_{i}.tex" is_wrong = True From 50e3c27be56e80dd13391ddd9de308498dc2b0fb Mon Sep 17 00:00:00 2001 From: LittleLucifer1 <2697699085@qq.com> Date: Tue, 17 Mar 2026 19:15:56 +0800 Subject: [PATCH 3/4] =?UTF-8?q?=E5=A2=9E=E5=8A=A0=E4=BA=862beamer=E7=9A=84?= =?UTF-8?q?=E5=8A=9F=E8=83=BD?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .../p2b_pagecontent_to_beamer_agent.py | 15 +- .../promptstemplates/prompts_repo.py | 3 +- .../workflow/wf_paper2ppt_beamer.py | 186 +++--- fastapi_app/routers/paper2ppt.py | 37 +- fastapi_app/schemas.py | 8 + fastapi_app/services/paper2ppt_service.py | 9 +- fastapi_app/workflow_adapters/wa_paper2ppt.py | 123 +++- frontend-workflow/src/App.tsx | 4 +- .../src/components/AppSidebar.tsx | 37 +- .../src/components/Paper2PptBeamerPage.tsx | 597 ++++++++++++++++++ .../src/components/paper2ppt/GenerateStep.tsx | 27 +- .../src/components/paper2ppt/OutlineStep.tsx | 49 +- .../src/components/paper2ppt/index.tsx | 18 +- .../src/components/paper2ppt/types.ts | 2 + frontend-workflow/src/locales/en/common.json | 8 +- .../src/locales/en/paper2ppt.json | 4 + frontend-workflow/src/locales/zh/common.json | 8 +- .../src/locales/zh/paper2ppt.json | 4 + 18 files changed, 993 insertions(+), 146 deletions(-) create mode 100644 frontend-workflow/src/components/Paper2PptBeamerPage.tsx diff --git a/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py b/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py index 83328621..c4dc68d5 100644 --- a/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py +++ b/dataflow_agent/agentroles/paper2any_agents/p2b_pagecontent_to_beamer_agent.py @@ -51,6 +51,15 @@ def get_task_prompt_params(self, pre_tool_results: Dict[str, Any]) -> Dict[str, "pdf_images_working_dir": pre_tool_results.get("pdf_images_working_dir", ""), } + async def execute_pre_tools(self, state: MainState) -> Dict[str, Any]: + """执行前置工具；若 state 上带有 pagecontent（并行时每页的 state），则优先使用，避免用到图节点注册时捕获的全量 pagecontent。""" + results = await super().execute_pre_tools(state) + pagecontent = getattr(state, "pagecontent", None) + if pagecontent is not None and isinstance(pagecontent, list) and len(pagecontent) > 0: + results["pagecontent"] = pagecontent + log.debug("使用 state.pagecontent 作为本页 pagecontent（共 %s 项）", len(pagecontent)) + return results + def get_default_pre_tool_results(self) -> Dict[str, Any]: return {} @@ -99,9 +108,9 @@ def update_state_result( req = getattr(state, "request", None) paper_pdf_path = getattr(req, "paper_pdf_path", "") if req else "" base = Path(paper_pdf_path).expanduser().resolve().parent if paper_pdf_path else Path(".").resolve() - auto_dir = base / "auto" - auto_dir.mkdir(parents=True, exist_ok=True) - beamer_code_path = auto_dir / "beamer_code.tex" + output_dir = base / "output" + output_dir.mkdir(parents=True, exist_ok=True) + beamer_code_path = output_dir / "beamer_code.tex" beamer_code_path.write_text(beamer_code, encoding="utf-8") state.beamer_code_path = str(beamer_code_path) log.info("p2b_pagecontent_to_beamer: Beamer 代码已写入 %s", beamer_code_path) diff --git a/dataflow_agent/promptstemplates/prompts_repo.py b/dataflow_agent/promptstemplates/prompts_repo.py index 6204ba59..e1f0391b 100644 --- a/dataflow_agent/promptstemplates/prompts_repo.py +++ b/dataflow_agent/promptstemplates/prompts_repo.py @@ -1803,7 +1803,7 @@ class Paper2VideoPrompt: **Required document structure (do not omit any part):** 1. \\documentclass{{beamer}} -2. Preamble: \\usetheme, \\usecolortheme (or similar), and font packages (see below). +2. Preamble: **must** use \\usetheme{{Madrid}} (fixed theme). You may add \\usecolortheme and font packages (see below). 3. \\begin{{document}} 4. **Exactly one** \\begin{{frame}}...\\end{{frame}} containing the slide content. 5. \\end{{document}} @@ -1839,6 +1839,7 @@ class Paper2VideoPrompt: {pagecontent} ## Format requirements +- **Theme: use \\usetheme{{Madrid}} in the preamble** (fixed; do not use other themes). - Font: use \\usepackage{{lmodern}} or default fonts only. **Do not use** Times New Roman, TeX Gyre Termes, resizebox. - Chinese: if output language is Chinese, add \\usepackage{{fontspec}} and \\usepackage{{ctex}} in the preamble. - No **&** in frame title (use "and" or comma). diff --git a/dataflow_agent/workflow/wf_paper2ppt_beamer.py b/dataflow_agent/workflow/wf_paper2ppt_beamer.py index 983dc743..a86d4275 100644 --- a/dataflow_agent/workflow/wf_paper2ppt_beamer.py +++ b/dataflow_agent/workflow/wf_paper2ppt_beamer.py @@ -7,9 +7,11 @@ from __future__ import annotations +import asyncio import json import shutil from pathlib import Path +from dataclasses import replace from dataflow_agent.state import Paper2PptBeamerRequest, Paper2PptBeamerState from dataflow_agent.graphbuilder.graph_builder import GenericGraphBuilder @@ -54,9 +56,9 @@ def get_output_language(state: Paper2PptBeamerState): @builder.pre_tool("pdf_images_working_dir", "p2b_pagecontent_to_beamer") def get_pdf_images_working_dir(state: Paper2PptBeamerState): - result_path = getattr(state, "result_path", "") or "" - if result_path: - return str(Path(result_path).expanduser().resolve() / "auto") + mineru_root = getattr(state, "mineru_root", "") or "" + if mineru_root: + return str(Path(mineru_root).expanduser().resolve()) return "" # ---------------------------------------------------------------------- @@ -70,22 +72,23 @@ async def p2b_pagecontent_to_beamer( pages = getattr(state, "pagecontent", None) or [] result_path = Path(getattr(state, "result_path", "") or ".").expanduser().resolve() - auto_dir = result_path / "auto" - auto_dir.mkdir(parents=True, exist_ok=True) + output_dir = result_path / "output" + output_dir.mkdir(parents=True, exist_ok=True) - # fixme: 这里硬编码了重试的次数，后续可能需要修改 - max_error_retries = 2 - max_warning_fixes = 5 + # 未得到有效 Beamer 代码（如 LLM 500/usage_limit）或编译失败时重试 + max_error_retries = 3 + retry_delay_seconds = 3 # 无有效代码时延迟再试，缓解限流/usage_limit + max_warning_fixes = 2 p2b_agent = create_simple_agent( name="p2b_pagecontent_to_beamer", - model_name="gpt-5.2-codex-medium", + model_name="gpt-5-codex", temperature=0.1, parser_type="json", ) debug_agent = create_simple_agent( name="p2v_beamer_code_debug", - model_name="gpt-5.2-codex-medium", + model_name="gpt-5-codex", temperature=0.1, parser_type="json", ) @@ -94,69 +97,105 @@ async def p2b_pagecontent_to_beamer( per_page_pdf_paths: list[str] = [] full_pagecontent = list(pages) - for i, one_page in enumerate(pages): - log.info("生成第 %s/%s 页 Beamer 并编译", i + 1, len(pages)) - state.pagecontent = [one_page] - - # asset_ref 为 Table_1 等时直接忽略，不跑 table_extractor - asset_ref = one_page.get("asset_ref") or one_page.get("asset") or "" - asset_ref = str(asset_ref).strip() if asset_ref else "" - if asset_ref and is_table_asset(asset_ref): - one_page["asset_ref"] = None - state.pagecontent = [one_page] - - page_tex = auto_dir / f"page_{i}.tex" - is_wrong = True - is_warning = False - code_debug_result = "" - - # ---------- Error 重试 ---------- - for error_attempt in range(max_error_retries): - state = await p2b_agent.execute(state=state) - if not getattr(state, "beamer_code_path", ""): - log.warning("第 %s 页未得到 beamer 代码，第 %s 次重试", i + 1, error_attempt + 1) - continue - shutil.copy(state.beamer_code_path, page_tex) - try: - is_wrong, is_warning, code_debug_result = compile_tex(str(page_tex)) - except Exception as e: - is_wrong, is_warning, code_debug_result = True, True, str(e) - log.warning("第 %s 页编译异常: %s", i + 1, e) - if not is_wrong: - break - log.warning("第 %s 页编译 error，第 %s/%s 次重新生成", i + 1, error_attempt + 1, max_error_retries) - - if is_wrong: - log.warning("第 %s 页经 %s 次重试仍有 error，跳过", i + 1, max_error_retries) - per_page_beamer_paths.append(str(page_tex)) - continue - - # ---------- Warning 修复（Overfull）：通过 state.pre_tool_results 注入，供 debug agent 的 execute_pre_tools 合并进 prompt ---------- - if is_warning and is_overfull_warning(code_debug_result): - for fix_attempt in range(max_warning_fixes): - state.beamer_code_path = str(page_tex) - state.is_beamer_wrong = is_wrong - state.is_beamer_warning = is_warning - state.code_debug_result = code_debug_result - state.pre_tool_results = { - "beamer_code": page_tex.read_text(encoding="utf-8"), - "code_debug_result": code_debug_result, - } - state = await debug_agent.execute(state) - - is_wrong = getattr(state, "is_beamer_wrong", True) - is_warning = getattr(state, "is_beamer_warning", False) - code_debug_result = getattr(state, "code_debug_result", "") - if is_wrong: - break - if not is_warning or not is_overfull_warning(code_debug_result): + # 并行度，避免 API 限流 + max_concurrent_pages = 4 + semaphore = asyncio.Semaphore(max_concurrent_pages) + + async def process_one_page( + i: int, + one_page: dict, + ) -> tuple[int, str, str | None]: + """处理单页，返回 (页索引, tex 路径, pdf 路径或 None)。""" + async with semaphore: + log.info("生成第 %s/%s 页 Beamer 并编译", i + 1, len(pages)) + one_page = dict(one_page) + # asset_ref 为 Table_1 等时直接忽略，不跑 table_extractor + asset_ref = one_page.get("asset_ref") or one_page.get("asset") or "" + asset_ref = str(asset_ref).strip() if asset_ref else "" + if asset_ref and is_table_asset(asset_ref): + one_page["asset_ref"] = None + + page_state = replace( + state, + pagecontent=[one_page], + beamer_code_path="", + is_beamer_wrong=False, + is_beamer_warning=False, + code_debug_result="", + ) + page_tex = output_dir / f"page_{i}.tex" + is_wrong = True + is_warning = False + code_debug_result = "" + + # ---------- Error 重试（含未得到有效代码，如 LLM 500/usage_limit）---------- + for error_attempt in range(max_error_retries): + page_state = await p2b_agent.execute(state=page_state) + if not getattr(page_state, "beamer_code_path", ""): + log.warning("第 %s 页未得到 beamer 代码（可能 LLM 限流/500），第 %s/%s 次重试", i + 1, error_attempt + 1, max_error_retries) + if error_attempt < max_error_retries - 1: + await asyncio.sleep(retry_delay_seconds) + continue + shutil.copy(page_state.beamer_code_path, page_tex) + try: + is_wrong, is_warning, code_debug_result = compile_tex(str(page_tex)) + except Exception as e: + is_wrong, is_warning, code_debug_result = True, True, str(e) + log.warning("第 %s 页编译异常: %s", i + 1, e) + if not is_wrong: break - log.info("第 %s 页 Overfull warning，第 %s/%s 次修复", i + 1, fix_attempt + 1, max_warning_fixes) - - per_page_beamer_paths.append(str(page_tex)) - pdf_path = page_tex.with_suffix(".pdf") - if pdf_path.exists(): - per_page_pdf_paths.append(str(pdf_path)) + log.warning("第 %s 页编译 error，第 %s/%s 次重新生成", i + 1, error_attempt + 1, max_error_retries) + + if is_wrong: + log.warning("第 %s 页经 %s 次重试仍有 error，跳过", i + 1, max_error_retries) + return (i, str(page_tex), None) + + # ---------- Warning 修复（Overfull）---------- + if is_warning and is_overfull_warning(code_debug_result): + for fix_attempt in range(max_warning_fixes): + page_state.beamer_code_path = str(page_tex) + page_state.is_beamer_wrong = is_wrong + page_state.is_beamer_warning = is_warning + page_state.code_debug_result = code_debug_result + page_state.pre_tool_results = { + "beamer_code": page_tex.read_text(encoding="utf-8"), + "code_debug_result": code_debug_result, + } + page_state = await debug_agent.execute(page_state) + is_wrong = getattr(page_state, "is_beamer_wrong", True) + is_warning = getattr(page_state, "is_beamer_warning", False) + code_debug_result = getattr(page_state, "code_debug_result", "") + if is_wrong: + break + if not is_warning or not is_overfull_warning(code_debug_result): + break + log.info("第 %s 页 Overfull warning，第 %s/%s 次修复", i + 1, fix_attempt + 1, max_warning_fixes) + + pdf_path = page_tex.with_suffix(".pdf") + pdf_str = str(pdf_path) if pdf_path.exists() else None + return (i, str(page_tex), pdf_str) + + # 并行处理所有页，保持页序 + results = await asyncio.gather( + *[process_one_page(i, one_page) for i, one_page in enumerate(pages)], + return_exceptions=True, + ) + # 按页索引排序，保证与原始页序一致（gather 完成顺序可能乱序） + tex_by_index: dict[int, str] = {} + pdf_by_index: dict[int, str] = {} + for r in results: + if isinstance(r, Exception): + log.exception("某页处理异常: %s", r) + continue + i, tex_path, pdf_path = r + tex_by_index[i] = tex_path + if pdf_path: + pdf_by_index[i] = pdf_path + for idx in range(len(pages)): + if idx in tex_by_index: + per_page_beamer_paths.append(tex_by_index[idx]) + if idx in pdf_by_index: + per_page_pdf_paths.append(pdf_by_index[idx]) state.pagecontent = full_pagecontent state.per_page_beamer_paths = per_page_beamer_paths @@ -171,7 +210,7 @@ def merge_slides_node(state: Paper2PptBeamerState) -> Paper2PptBeamerState: log.warning("无每页 PDF，无法合并") return state result_path = Path(getattr(state, "result_path", "") or ".").expanduser().resolve() - merged_path = result_path / "auto" / "merged.pdf" + merged_path = result_path / "output" / "merged.pdf" state.ppt_path = merge_pdfs(pdf_paths, merged_path) log.info("合并完成: %s", state.ppt_path) return state @@ -180,6 +219,7 @@ def _start_(state: Paper2PptBeamerState) -> Paper2PptBeamerState: return state def _end_(state: Paper2PptBeamerState) -> Paper2PptBeamerState: + log.info(f"The ppt_path is {state.ppt_path}") return state nodes = { diff --git a/fastapi_app/routers/paper2ppt.py b/fastapi_app/routers/paper2ppt.py index fc826c4f..4a011da8 100644 --- a/fastapi_app/routers/paper2ppt.py +++ b/fastapi_app/routers/paper2ppt.py @@ -1,11 +1,14 @@ from __future__ import annotations import base64 +import os from pathlib import Path from typing import Any, Dict, Optional from fastapi import APIRouter, Depends, File, Form, HTTPException, Request, UploadFile +from fastapi_app.config import settings + from fastapi_app.schemas import ( ErrorResponse, FullPipelineRequest, @@ -32,8 +35,8 @@ def get_service() -> Paper2PPTService: ) async def paper2ppt_pagecontent_json( request: Request, - chat_api_url: str = Form(...), - api_key: str = Form(...), + chat_api_url: Optional[str] = Form(""), + api_key: Optional[str] = Form(""), email: Optional[str] = Form(None), # 输入相关：支持 text/pdf/pptx/topic input_type: str = Form(...), # 'text' | 'pdf' | 'pptx' | 'topic' @@ -51,15 +54,23 @@ async def paper2ppt_pagecontent_json( pdf_as_slides: str = Form("false"), # PPT/PDF 转图片时的渲染 DPI（None 表示默认） render_dpi: Optional[int] = Form(None), + # 生成方式：image_gen=图生模型，beamer=Beamer 代码 + ppt_mode: str = Form("image_gen"), service: Paper2PPTService = Depends(get_service), ): """ 只跑 paper2page_content，返回 pagecontent + result_path。 + beamer 模式下若未传 chat_api_url/api_key，使用服务端默认（DF_API_URL/DF_API_KEY）。 """ + _url = (chat_api_url or "").strip() + _key = (api_key or "").strip() + if ppt_mode == "beamer" and (not _url or not _key): + _url = _url or os.getenv("DF_API_URL", "") + _key = _key or os.getenv("DF_API_KEY", "") req = PageContentRequest( - chat_api_url=chat_api_url, - api_key=api_key, + chat_api_url=_url, + api_key=_key, email=email, input_type=input_type, text=text, @@ -71,6 +82,7 @@ async def paper2ppt_pagecontent_json( use_long_paper=use_long_paper, pdf_as_slides=pdf_as_slides, render_dpi=render_dpi, + ppt_mode=ppt_mode if ppt_mode in ("image_gen", "beamer") else "image_gen", ) data = await service.get_page_content( @@ -90,8 +102,8 @@ async def paper2ppt_pagecontent_json( async def paper2ppt_ppt_json( request: Request, img_gen_model_name: str = Form(...), - chat_api_url: str = Form(...), - api_key: str = Form(...), + chat_api_url: Optional[str] = Form(""), + api_key: Optional[str] = Form(""), email: Optional[str] = Form(None), # 控制参数 style: str = Form(""), @@ -112,18 +124,26 @@ async def paper2ppt_ppt_json( page_id: Optional[int] = Form(None), # 页面编辑提示词（get_down=true 时必传） edit_prompt: Optional[str] = Form(None), + # 生成方式：image_gen=图生模型，beamer=Beamer 代码（beamer 模式下无逐页编辑） + ppt_mode: str = Form("image_gen"), service: Paper2PPTService = Depends(get_service), ): """ 只跑 paper2ppt： - get_down=false：生成模式（需要 pagecontent） - get_down=true：编辑模式（需要 page_id(0-based) + edit_prompt，pagecontent 可选） + beamer 模式下若未传 chat_api_url/api_key，使用服务端默认。 """ + _url = (chat_api_url or "").strip() + _key = (api_key or "").strip() + if ppt_mode == "beamer" and (not _url or not _key): + _url = _url or settings.DEFAULT_LLM_API_URL + _key = _key or os.getenv("DF_API_KEY", "") req = PPTGenerationRequest( img_gen_model_name=img_gen_model_name, - chat_api_url=chat_api_url, - api_key=api_key, + chat_api_url=_url, + api_key=_key, email=email, style=style, aspect_ratio=aspect_ratio, @@ -136,6 +156,7 @@ async def paper2ppt_ppt_json( page_id=page_id, edit_prompt=edit_prompt, image_resolution=image_resolution, + ppt_mode=ppt_mode if ppt_mode in ("image_gen", "beamer") else "image_gen", ) data = await service.generate_ppt( diff --git a/fastapi_app/schemas.py b/fastapi_app/schemas.py index 1dc45121..a02ce45c 100644 --- a/fastapi_app/schemas.py +++ b/fastapi_app/schemas.py @@ -221,6 +221,8 @@ class PageContentRequest(BaseModel): pdf_as_slides: str = "false" # PPT/PDF 转图片时的渲染 DPI（None 表示使用默认值） render_dpi: Optional[int] = None + # 生成方式：image_gen=图生模型，beamer=Beamer 代码 + ppt_mode: Literal["image_gen", "beamer"] = "image_gen" class OutlineRefineRequest(BaseModel): @@ -311,6 +313,8 @@ class PPTGenerationRequest(BaseModel): edit_prompt: Optional[str] = None # 图像生成分辨率（1K/2K/4K 等） image_resolution: Optional[str] = None + # 生成方式：image_gen=图生模型，beamer=Beamer 代码 + ppt_mode: Literal["image_gen", "beamer"] = "image_gen" class FullPipelineRequest(BaseModel): @@ -327,6 +331,8 @@ class FullPipelineRequest(BaseModel): style: str = "" model: str = settings.PAPER2PPT_DEFAULT_MODEL use_long_paper: str = "false" + # 生成方式：image_gen=图生模型，beamer=Beamer 代码 + ppt_mode: Literal["image_gen", "beamer"] = "image_gen" class Paper2PPTRequest(BaseModel): @@ -377,6 +383,8 @@ class Paper2PPTRequest(BaseModel): all_edited_down: bool = False use_ai_edit: bool = False + # 生成方式：image_gen=图生模型，beamer=Beamer 代码 + ppt_mode: Literal["image_gen", "beamer"] = "image_gen" def get(self, key: str, default=None): """ diff --git a/fastapi_app/services/paper2ppt_service.py b/fastapi_app/services/paper2ppt_service.py index dabd6fa7..03bba6a3 100644 --- a/fastapi_app/services/paper2ppt_service.py +++ b/fastapi_app/services/paper2ppt_service.py @@ -189,11 +189,13 @@ async def get_page_content( page_count=req.page_count, use_long_paper=use_long_paper_bool, render_dpi=req.render_dpi, + ppt_mode=getattr(req, "ppt_mode", "image_gen") or "image_gen", ) resp_model = await run_paper2page_content_wf_api(p2ppt_req, result_path=run_dir) resp_dict = resp_model.model_dump() + resp_dict["ppt_mode"] = getattr(req, "ppt_mode", "image_gen") or "image_gen" if request is not None: resp_dict["pagecontent"] = self._convert_pagecontent_paths_to_urls( resp_dict.get("pagecontent", []), request @@ -289,8 +291,9 @@ async def generate_ppt( if key in item and item[key]: item[key] = _from_outputs_url(item[key]) - # 转换字符串布尔值 - get_down_bool = str(req.get_down).lower() in ("true", "1", "yes") + # 转换字符串布尔值；Beamer 模式不支持逐页编辑，强制为生成模式 + ppt_mode = getattr(req, "ppt_mode", "image_gen") or "image_gen" + get_down_bool = str(req.get_down).lower() in ("true", "1", "yes") and ppt_mode != "beamer" all_edited_down_bool = str(req.all_edited_down).lower() in ("true", "1", "yes") # 校验编辑/生成模式 @@ -320,6 +323,7 @@ async def generate_ppt( email=req.email or "", all_edited_down=all_edited_down_bool, image_resolution=req.image_resolution or "2K", + ppt_mode=getattr(req, "ppt_mode", "image_gen") or "image_gen", ) resp_model = await run_paper2ppt_wf_api( @@ -382,6 +386,7 @@ async def run_full_pipeline( style=req.style, email=req.email or "", use_long_paper=req.use_long_paper, + ppt_mode=getattr(req, "ppt_mode", "image_gen") or "image_gen", ) resp_model = await run_paper2ppt_full_pipeline(p2ppt_req) diff --git a/fastapi_app/workflow_adapters/wa_paper2ppt.py b/fastapi_app/workflow_adapters/wa_paper2ppt.py index b59d60fe..28cf3a9e 100644 --- a/fastapi_app/workflow_adapters/wa_paper2ppt.py +++ b/fastapi_app/workflow_adapters/wa_paper2ppt.py @@ -16,7 +16,7 @@ from typing import Any, List from dataflow_agent.logger import get_logger -from dataflow_agent.state import Paper2FigureState +from dataflow_agent.state import Paper2FigureState, Paper2PptBeamerState, Paper2PptBeamerRequest from dataflow_agent.toolkits.multimodaltool.mineru_tool import _shrink_markdown from dataflow_agent.utils import get_project_root from dataflow_agent.workflow import run_workflow @@ -209,6 +209,31 @@ async def run_paper2page_content_refine_wf_api( return Paper2PPTResponse(**resp_data) +def _beamer_per_page_pdfs_to_ppt_pages(result_path: Path, per_page_pdf_paths: list[str]) -> None: + """将 Beamer 每页 PDF 转为 PNG，写入 result_path/ppt_pages/page_000.png 等，供前端展示。""" + if not per_page_pdf_paths: + return + try: + from pdf2image import convert_from_path + except ImportError: + log.warning("[wa_paper2ppt] pdf2image 未安装，跳过 Beamer 每页预览图生成") + return + ppt_pages_dir = result_path / "ppt_pages" + ppt_pages_dir.mkdir(parents=True, exist_ok=True) + for i, pdf_path in enumerate(per_page_pdf_paths): + p = Path(pdf_path) + if not p.exists(): + continue + try: + images = convert_from_path(str(p), first_page=1, last_page=1, dpi=150) + if images: + out_name = f"page_{i:03d}.png" + images[0].save(ppt_pages_dir / out_name, "PNG") + log.info("[wa_paper2ppt] Beamer 页 %s -> %s", i, out_name) + except Exception as e: + log.warning("[wa_paper2ppt] Beamer 页 %s 转 PNG 失败: %s", i, e) + + async def run_paper2ppt_wf_api( req: Paper2PPTRequest, pagecontent: list[dict] | None = None, @@ -287,27 +312,72 @@ async def run_paper2ppt_wf_api( log.info( f"[paper2ppt_wf_api] start, result_path={getattr(state, 'result_path', None)}, " - f"pagecontent_len={len(getattr(state, 'pagecontent', []) or [])}" + f"pagecontent_len={len(getattr(state, 'pagecontent', []) or [])}, ppt_mode={getattr(req, 'ppt_mode', 'image_gen')}" ) - # final_state: Paper2FigureState = await run_workflow("paper2ppt_parallel", state) + ppt_mode = getattr(req, "ppt_mode", "image_gen") or "image_gen" + + if ppt_mode == "beamer": + # Beamer 路径：pagecontent → paper2ppt_beamer_pagecontent → merged PDF，并生成每页 PNG 供前端展示 + if not base_dir: + raise ValueError("result_path is required for beamer mode") + pc = getattr(state, "pagecontent", []) or [] + if not pc: + return Paper2PPTResponse(success=False, ppt_pdf_path="", ppt_pptx_path="", pagecontent=[], result_path=str(base_dir)) + lang = getattr(req, "language", "en") or "en" + # 将 API 配置从请求传入，否则 agent 会用默认/空 key 导致 401 + api_url = getattr(req, "chat_api_url", "") or "" + api_key = getattr(req, "api_key", "") or getattr(req, "chat_api_key", "") or "" + model = getattr(req, "model", "") or "gpt-4o" + beamer_req = Paper2PptBeamerRequest( + language=lang, + chat_api_url=api_url, + api_key=api_key, + chat_api_key=api_key, + model=model, + ) + state_beamer = Paper2PptBeamerState( + request=beamer_req, + pagecontent=pc, + result_path=str(base_dir), + mineru_root=str(base_dir / "input" / "auto"), + minueru_output=getattr(state, "mineru_output", "") or "", + ) + final_beamer = await run_workflow("paper2ppt_beamer_pagecontent", state_beamer) + if isinstance(final_beamer, dict): + ppt_pdf_path = final_beamer.get("ppt_path") or "" + per_page_pdf_paths = final_beamer.get("per_page_pdf_paths") or [] + pagecontent = final_beamer.get("pagecontent") or [] + else: + ppt_pdf_path = getattr(final_beamer, "ppt_path", "") or "" + per_page_pdf_paths = getattr(final_beamer, "per_page_pdf_paths", []) or [] + pagecontent = getattr(final_beamer, "pagecontent", []) or [] + _beamer_per_page_pdfs_to_ppt_pages(base_dir, per_page_pdf_paths) + resp_data = { + "success": True, + "ppt_pdf_path": str(ppt_pdf_path) if ppt_pdf_path else "", + "ppt_pptx_path": "", + "pagecontent": pagecontent, + "result_path": str(base_dir), + } + return Paper2PPTResponse(**resp_data) + + # 图生模型路径 log.critical(f'[wa_paper2ppt] req.ref_img 路径 {req.ref_img}') final_state: Paper2FigureState = await run_workflow("paper2ppt_parallel_consistent_style", state) - # 提取关键输出 ppt_pdf_path = getattr(final_state, "ppt_pdf_path", "") ppt_pptx_path = getattr(final_state, "ppt_pptx_path", "") final_pagecontent = getattr(final_state, "pagecontent", []) or [] final_result_path = getattr(final_state, "result_path", result_path or "") - resp_data: dict[str, Any] = { + resp_data = { "success": True, "ppt_pdf_path": str(ppt_pdf_path) if ppt_pdf_path else "", "ppt_pptx_path": str(ppt_pptx_path) if ppt_pptx_path else "", "pagecontent": final_pagecontent, "result_path": final_result_path, } - return Paper2PPTResponse(**resp_data) @@ -347,26 +417,57 @@ async def run_paper2ppt_full_pipeline(req: Paper2PPTRequest) -> Paper2PPTRespons final_result_path = getattr(state_pc, "result_path", str(result_root)) # ---------- 第二步：paper2ppt ---------- - # 复用 state_pc 继续执行 paper2ppt，避免丢失中间状态 + ppt_mode = getattr(req, "ppt_mode", "image_gen") or "image_gen" log.info( - f"[paper2ppt_full_pipeline] step2 paper2ppt, " + f"[paper2ppt_full_pipeline] step2 paper2ppt, ppt_mode={ppt_mode}, " f"result_path={final_result_path}, pagecontent_len={len(pagecontent)}" ) + + if ppt_mode == "beamer": + result_root_path = Path(final_result_path) + api_url = getattr(req, "chat_api_url", "") or "" + api_key = getattr(req, "api_key", "") or getattr(req, "chat_api_key", "") or "" + model = getattr(req, "model", "") or "gpt-4o" + beamer_req = Paper2PptBeamerRequest( + language=getattr(req, "language", "en") or "en", + chat_api_url=api_url, + api_key=api_key, + chat_api_key=api_key, + model=model, + ) + state_beamer = Paper2PptBeamerState( + request=beamer_req, + pagecontent=pagecontent, + result_path=final_result_path, + mineru_root=str(result_root_path / "input" / "auto"), + minueru_output=getattr(state_pc, "minueru_output", "") or "", + ) + final_beamer = await run_workflow("paper2ppt_beamer_pagecontent", state_beamer) + ppt_pdf_path = getattr(final_beamer, "ppt_path", "") or "" + per_page_pdf_paths = getattr(final_beamer, "per_page_pdf_paths", []) or [] + _beamer_per_page_pdfs_to_ppt_pages(result_root_path, per_page_pdf_paths) + resp_data = { + "success": True, + "ppt_pdf_path": str(ppt_pdf_path) if ppt_pdf_path else "", + "ppt_pptx_path": "", + "pagecontent": getattr(final_beamer, "pagecontent", []) or pagecontent, + "result_path": final_result_path, + } + return Paper2PPTResponse(**resp_data) + state_pc.pagecontent = pagecontent state_pc.result_path = final_result_path - state_pp: Paper2FigureState = await run_workflow("paper2ppt_parallel_consistent_style", state_pc) ppt_pdf_path = getattr(state_pp, "ppt_pdf_path", "") ppt_pptx_path = getattr(state_pp, "ppt_pptx_path", "") final_pagecontent = getattr(state_pp, "pagecontent", []) or [] - resp_data: dict[str, Any] = { + resp_data = { "success": True, "ppt_pdf_path": str(ppt_pdf_path) if ppt_pdf_path else "", "ppt_pptx_path": str(ppt_pptx_path) if ppt_pptx_path else "", "pagecontent": final_pagecontent, "result_path": final_result_path, } - return Paper2PPTResponse(**resp_data) diff --git a/frontend-workflow/src/App.tsx b/frontend-workflow/src/App.tsx index 624f865e..0c923a5b 100644 --- a/frontend-workflow/src/App.tsx +++ b/frontend-workflow/src/App.tsx @@ -3,6 +3,7 @@ import ParticleBackground from './components/ParticleBackground'; import Paper2GraphTechExpPage from './components/Paper2GraphTechExpPage'; import Paper2GraphDrawioPage from './components/Paper2GraphDrawioPage'; import Paper2PptPage from './components/Paper2PptPage'; +import Paper2PptBeamerPage from './components/Paper2PptBeamerPage'; import Pdf2PptPage from './components/Pdf2PptPage'; import Image2PptPage from './components/Image2PptPage'; import Image2DrawioPage from './components/Image2DrawioPage'; @@ -23,7 +24,7 @@ import { AppSidebar } from './components/AppSidebar'; function App() { const { t } = useTranslation('common'); - const [activePage, setActivePage] = useState<'paper2figure-tech-exp' | 'paper2figure-model-drawio' | 'paper2drawio-ai' | 'paper2ppt' | 'paper2video' | 'pdf2ppt' | 'image2ppt' | 'image2drawio' | 'ppt2polish' | 'knowledge' | 'files' | 'paper2drawio' | 'paper2rebuttal'>('paper2figure-tech-exp'); + const [activePage, setActivePage] = useState<'paper2figure-tech-exp' | 'paper2figure-model-drawio' | 'paper2drawio-ai' | 'paper2ppt' | 'paper2ppt_beamer' | 'paper2video' | 'pdf2ppt' | 'image2ppt' | 'image2drawio' | 'ppt2polish' | 'knowledge' | 'files' | 'paper2drawio' | 'paper2rebuttal'>('paper2figure-tech-exp'); const [showFilesModal, setShowFilesModal] = useState(false); const [showAccountModal, setShowAccountModal] = useState(false); const [sidebarOpen, setSidebarOpen] = useState(false); @@ -84,6 +85,7 @@ function App() { {activePage === 'paper2figure-model-drawio' && } {activePage === 'paper2drawio-ai' && } {activePage === 'paper2ppt' && } + {activePage === 'paper2ppt_beamer' && } {activePage === 'paper2video' && } {activePage === 'pdf2ppt' && } {activePage === 'image2ppt' && } diff --git a/frontend-workflow/src/components/AppSidebar.tsx b/frontend-workflow/src/components/AppSidebar.tsx index 4b6b621f..f2b578de 100644 --- a/frontend-workflow/src/components/AppSidebar.tsx +++ b/frontend-workflow/src/components/AppSidebar.tsx @@ -35,7 +35,7 @@ interface AppSidebarProps { export const AppSidebar = ({ isOpen, onClose, activePage, onPageChange }: AppSidebarProps) => { const { t } = useTranslation('common'); - const [menuView, setMenuView] = useState<'main' | 'paper2figure'>('main'); + const [menuView, setMenuView] = useState<'main' | 'paper2figure' | 'paper2ppt'>('main'); useEffect(() => { if (!isOpen) setMenuView('main'); @@ -65,6 +65,23 @@ export const AppSidebar = ({ isOpen, onClose, activePage, onPageChange }: AppSid } ]), [t]); + const paper2pptChildren = useMemo(() => ([ + { + id: 'paper2ppt', + labelKey: t('app.navSub.paper2pptImageGen'), + tooltipKey: t('app.navSubTooltip.paper2pptImageGen'), + icon: Presentation, + gradient: 'from-purple-500 to-pink-500' + }, + { + id: 'paper2ppt_beamer', + labelKey: t('app.navSub.paper2pptBeamer'), + tooltipKey: t('app.navSubTooltip.paper2pptBeamer'), + icon: Presentation, + gradient: 'from-indigo-500 to-purple-500' + } + ]), [t]); + const navigationItems: NavigationItem[] = [ { id: 'paper2figure', @@ -88,7 +105,7 @@ export const AppSidebar = ({ isOpen, onClose, activePage, onPageChange }: AppSid gradient: 'from-rose-500 to-pink-500' }, { - id: 'paper2ppt', + id: 'paper2ppt-group', labelKey: t('app.nav.paper2ppt'), tooltipKey: t('app.navTooltip.paper2ppt'), icon: Presentation, @@ -144,6 +161,7 @@ export const AppSidebar = ({ isOpen, onClose, activePage, onPageChange }: AppSid }; const paper2figureActive = paper2figureChildren.some(child => child.id === activePage); + const paper2pptActive = paper2pptChildren.some(child => child.id === activePage); return ( <> @@ -162,7 +180,7 @@ export const AppSidebar = ({ isOpen, onClose, activePage, onPageChange }: AppSid {/* Header */}
- {menuView === 'paper2figure' && ( + {(menuView === 'paper2figure' || menuView === 'paper2ppt') && ( )}

- {menuView === 'paper2figure' ? t('app.nav.paper2figure') : t('app.sidebar.navigation')} + {menuView === 'paper2figure' ? t('app.nav.paper2figure') : menuView === 'paper2ppt' ? t('app.nav.paper2ppt') : t('app.sidebar.navigation')}

@@ -234,7 +257,7 @@ export const AppSidebar = ({ isOpen, onClose, activePage, onPageChange }: AppSid className="absolute inset-0 p-4 overflow-y-auto overflow-x-hidden transition-transform duration-300" style={{ transform: menuView === 'main' ? 'translateX(100%)' : 'translateX(0)' }} > - {paper2figureChildren.map((child) => { + {(menuView === 'paper2figure' ? paper2figureChildren : paper2pptChildren).map((child) => { const ChildIcon = child.icon; const isChildActive = activePage === child.id; return ( diff --git a/frontend-workflow/src/components/Paper2PptBeamerPage.tsx b/frontend-workflow/src/components/Paper2PptBeamerPage.tsx new file mode 100644 index 00000000..e0c15173 --- /dev/null +++ b/frontend-workflow/src/components/Paper2PptBeamerPage.tsx @@ -0,0 +1,597 @@ +import React, { useState, ChangeEvent } from 'react'; +import { useTranslation } from 'react-i18next'; +import { API_KEY } from '../config/api'; +import { getApiSettings } from '../services/apiSettingsService'; +import { useAuthStore } from '../stores/authStore'; +import { + UploadCloud, Settings2, Loader2, Download, RotateCcw, FileText, Type, Lightbulb +} from 'lucide-react'; +import type { UploadMode } from './paper2ppt/types'; +import type { Step, SlideOutline, GenerateResult } from './paper2ppt/types'; +import { MAX_FILE_SIZE } from './paper2ppt/constants'; +import StepIndicator from './paper2ppt/StepIndicator'; +import OutlineStep from './paper2ppt/OutlineStep'; +import GenerateStep from './paper2ppt/GenerateStep'; + +const Paper2PptBeamerPage: React.FC = () => { + const { t } = useTranslation(['paper2ppt', 'common']); + const { user } = useAuthStore(); + + const [currentStep, setCurrentStep] = useState('upload'); + const [uploadMode, setUploadMode] = useState('file'); + const [textContent, setTextContent] = useState(''); + const [selectedFile, setSelectedFile] = useState(null); + const [isDragOver, setIsDragOver] = useState(false); + const [pageCount, setPageCount] = useState(6); + const [language, setLanguage] = useState<'zh' | 'en'>('en'); + const [isSubmitting, setIsSubmitting] = useState(false); + const [error, setError] = useState(null); + + const [resultPath, setResultPath] = useState(null); + const [outlineData, setOutlineData] = useState([]); + const [editingId, setEditingId] = useState(null); + const [editContent, setEditContent] = useState<{ + title: string; + layout_description: string; + key_points: string[]; + }>({ title: '', layout_description: '', key_points: [] }); + const [outlineFeedback, setOutlineFeedback] = useState(''); + const [isRefiningOutline, setIsRefiningOutline] = useState(false); + + const [generateResults, setGenerateResults] = useState([]); + const [currentSlideIndex, setCurrentSlideIndex] = useState(0); + const [isGenerating, setIsGenerating] = useState(false); + const [slidePrompt, setSlidePrompt] = useState(''); + const [downloadUrl, setDownloadUrl] = useState(null); + + const apiSettings = getApiSettings(user?.id || null); + const chatApiUrl = apiSettings?.apiUrl || ''; + const apiKey = apiSettings?.apiKey || ''; + + const handleFileChange = (e: ChangeEvent) => { + const file = e.target.files?.[0]; + if (!file) return; + const ext = file.name.split('.').pop()?.toLowerCase(); + if (ext !== 'pdf') { + setError('仅支持 PDF 格式'); + return; + } + if (file.size > MAX_FILE_SIZE) { + setError('文件大小超过 50MB 限制'); + return; + } + setSelectedFile(file); + setError(null); + }; + + const handleDrop = (e: React.DragEvent) => { + e.preventDefault(); + setIsDragOver(false); + const file = e.dataTransfer.files?.[0]; + if (!file) return; + const ext = file.name.split('.').pop()?.toLowerCase(); + if (ext !== 'pdf') { + setError('仅支持 PDF 格式'); + return; + } + if (file.size > MAX_FILE_SIZE) { + setError('文件大小超过 50MB 限制'); + return; + } + setSelectedFile(file); + setError(null); + }; + + // ---------- Step 1: 仅调用 page-content，进入大纲步骤 ---------- + const handleStartParse = async () => { + if (uploadMode === 'file' && !selectedFile) { + setError('请上传 PDF 文件'); + return; + } + if ((uploadMode === 'text' || uploadMode === 'topic') && !textContent.trim()) { + setError(uploadMode === 'topic' ? '请输入主题' : '请输入文本内容'); + return; + } + + setError(null); + setIsSubmitting(true); + + try { + const formData = new FormData(); + if (uploadMode === 'file' && selectedFile) { + formData.append('file', selectedFile); + formData.append('input_type', 'pdf'); + } else { + formData.append('text', textContent.trim()); + formData.append('input_type', uploadMode); + } + formData.append('email', user?.id || user?.email || ''); + formData.append('chat_api_url', chatApiUrl.trim()); + formData.append('api_key', apiKey.trim()); + formData.append('model', 'gpt-4o'); + formData.append('language', language); + formData.append('style', ''); + formData.append('gen_fig_model', 'gemini-3-pro-image-preview'); + formData.append('page_count', String(pageCount)); + formData.append('use_long_paper', 'false'); + formData.append('ppt_mode', 'beamer'); + + const res = await fetch('/api/v1/paper2ppt/page-content', { + method: 'POST', + headers: { 'X-API-Key': API_KEY }, + body: formData, + }); + + if (!res.ok) { + const errBody = await res.json().catch(() => ({})); + throw new Error(errBody?.error || errBody?.detail || '解析失败'); + } + + const data = await res.json(); + if (!data.success) throw new Error(data.error || '解析失败'); + + const path = data.result_path; + const pagecontent = data.pagecontent; + if (!path || !pagecontent?.length) { + throw new Error('未返回 result_path 或 pagecontent'); + } + + setResultPath(path); + const slides: SlideOutline[] = pagecontent.map((item: any, index: number) => ({ + id: String(index + 1), + pageNum: index + 1, + title: item.title || `第 ${index + 1} 页`, + layout_description: item.layout_description || '', + key_points: item.key_points || [], + asset_ref: item.asset_ref ?? null, + })); + setOutlineData(slides); + setCurrentStep('outline'); + } catch (err) { + setError(err instanceof Error ? err.message : '请求失败'); + } finally { + setIsSubmitting(false); + } + }; + + // ---------- Outline 编辑与确认：确认后调用 generate (beamer)，进入逐页预览 ---------- + const handleEditStart = (slide: SlideOutline) => { + setEditingId(slide.id); + setEditContent({ + title: slide.title, + layout_description: slide.layout_description, + key_points: [...slide.key_points], + }); + }; + + const handleEditSave = () => { + if (!editingId) return; + setOutlineData((prev) => + prev.map((s) => + s.id === editingId + ? { + ...s, + title: editContent.title, + layout_description: editContent.layout_description, + key_points: editContent.key_points, + } + : s + ) + ); + setEditingId(null); + }; + + const handleEditCancel = () => setEditingId(null); + + const handleKeyPointChange = (index: number, value: string) => { + setEditContent((prev) => { + const next = [...prev.key_points]; + next[index] = value; + return { ...prev, key_points: next }; + }); + }; + + const handleAddKeyPoint = () => { + setEditContent((prev) => ({ ...prev, key_points: [...prev.key_points, ''] })); + }; + + const handleRemoveKeyPoint = (index: number) => { + setEditContent((prev) => ({ + ...prev, + key_points: prev.key_points.filter((_, i) => i !== index), + })); + }; + + const handleDeleteSlide = (id: string) => { + setOutlineData((prev) => + prev.filter((s) => s.id !== id).map((s, i) => ({ ...s, pageNum: i + 1 })) + ); + }; + + const handleAddSlide = (index: number) => { + setOutlineData((prev) => { + const newSlide: SlideOutline = { + id: String(Date.now()), + pageNum: 0, + title: '新页面', + layout_description: '左右图文', + key_points: [''], + asset_ref: null, + }; + const next = [...prev]; + next.splice(index + 1, 0, newSlide); + return next.map((s, i) => ({ + ...s, + pageNum: i + 1, + title: s.title === '新页面' ? `第 ${i + 1} 页` : s.title, + })); + }); + }; + + const handleMoveSlide = (index: number, direction: 'up' | 'down') => { + const next = [...outlineData]; + const target = direction === 'up' ? index - 1 : index + 1; + if (target < 0 || target >= next.length) return; + [next[index], next[target]] = [next[target], next[index]]; + setOutlineData(next.map((s, i) => ({ ...s, pageNum: i + 1 }))); + }; + + const handleConfirmOutline = async () => { + if (!resultPath) { + setError('缺少 result_path'); + return; + } + setError(null); + setIsGenerating(true); + setIsRefiningOutline(true); // 禁用大纲确认按钮，防止重复提交 + + const pagecontent = outlineData.map((s) => ({ + title: s.title, + layout_description: s.layout_description, + key_points: s.key_points, + asset_ref: s.asset_ref, + })); + + try { + const form = new FormData(); + form.append('img_gen_model_name', 'gemini-3-pro-image-preview'); + form.append('chat_api_url', chatApiUrl.trim()); + form.append('api_key', apiKey.trim()); + form.append('model', 'gpt-4o'); + form.append('language', language); + form.append('style', ''); + form.append('aspect_ratio', '16:9'); + form.append('email', user?.id || user?.email || ''); + form.append('result_path', resultPath); + form.append('get_down', 'false'); + form.append('all_edited_down', 'true'); + form.append('ppt_mode', 'beamer'); + form.append('pagecontent', JSON.stringify(pagecontent)); + + const res = await fetch('/api/v1/paper2ppt/generate', { + method: 'POST', + headers: { 'X-API-Key': API_KEY }, + body: form, + }); + + if (!res.ok) { + const errBody = await res.json().catch(() => ({})); + throw new Error(errBody?.error || errBody?.detail || '生成失败'); + } + + const data = await res.json(); + if (!data.success) throw new Error(data.error || '生成失败'); + + const pdfUrl = + data.ppt_pdf_path || + (data.all_output_files && + data.all_output_files.find( + (url: string) => url.endsWith('.pdf') && !url.includes('input') + )); + if (pdfUrl) setDownloadUrl(pdfUrl); + + const results: GenerateResult[] = outlineData.map((slide, index) => { + const pageNumStr = String(index).padStart(3, '0'); + let afterImage = ''; + if (data.all_output_files && Array.isArray(data.all_output_files)) { + const url = data.all_output_files.find((u: string) => + u.includes(`ppt_pages/page_${pageNumStr}.png`) + ); + if (url) afterImage = url; + } + return { + slideId: slide.id, + beforeImage: '', + afterImage, + status: 'done' as const, + versionHistory: [], + currentVersionIndex: -1, + }; + }); + + setGenerateResults(results); + setCurrentSlideIndex(0); + setCurrentStep('generate'); + } catch (err) { + setError(err instanceof Error ? err.message : '生成失败'); + } finally { + setIsGenerating(false); + setIsRefiningOutline(false); + } + }; + + const handleConfirmSlide = () => { + setError(null); + if (currentSlideIndex < outlineData.length - 1) { + setCurrentSlideIndex((i) => i + 1); + setSlidePrompt(''); + } else { + setCurrentStep('complete'); + } + }; + + const handleRegenerateSlide = () => {}; // Beamer 不支持逐页重新生成 + const handleRevertToVersion = () => {}; // Beamer 无版本历史 + + const handleReset = () => { + setCurrentStep('upload'); + setResultPath(null); + setOutlineData([]); + setGenerateResults([]); + setDownloadUrl(null); + setError(null); + setCurrentSlideIndex(0); + setEditingId(null); + setEditContent({ title: '', layout_description: '', key_points: [] }); + setOutlineFeedback(''); + setSelectedFile(null); + setTextContent(''); + }; + + // ---------- 完成页：下载 PDF ---------- + if (currentStep === 'complete') { + return ( +
+
+
+

生成完成

+

Beamer PDF 已生成，可下载。

+ {downloadUrl && ( +
+ + 下载 PDF + +
+ +
+
+ )} + {error &&
{error}
} +
+
+
+ ); + } + + // ---------- 上传步骤 ---------- + if (currentStep === 'upload') { + return ( +
+
+
+ +
+

+ Beamer · PDF +

+

+ + Paper2PPT Beamer + +

+

+ 上传 PDF、长文本或 Topic，解析后可在第二步编辑大纲，再生成 LaTeX Beamer 逐页预览与 PDF。 +

+
+ +
+
+
+ {[ + { id: 'file' as const, label: t('upload.tabs.file'), icon: FileText }, + { id: 'text' as const, label: t('upload.tabs.text'), icon: Type }, + { id: 'topic' as const, label: t('upload.tabs.topic'), icon: Lightbulb }, + ].map((item) => ( + + ))} +
+ + {uploadMode === 'file' ? ( +
{ + e.preventDefault(); + setIsDragOver(true); + }} + onDragLeave={(e) => { + e.preventDefault(); + setIsDragOver(false); + }} + onDrop={handleDrop} + > + +

{t('upload.dropzone.dragText')}

+

{t('upload.dropzone.supportText')}

+ + {selectedFile && ( +

✓ {selectedFile.name}

+ )} +
+ ) : ( +