From 1790b496b3af7f7abc0809b2ddd37b1725c9533c Mon Sep 17 00:00:00 2001 From: Pine Date: Sat, 30 May 2026 12:51:19 +0800 Subject: [PATCH] =?UTF-8?q?(all)=EF=BC=9A=E5=A2=9E=E5=8A=A0=E6=A1=8C?= =?UTF-8?q?=E9=9D=A2=E7=A8=8B=E5=BA=8F?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .gitignore | 5 + .python-version | 1 + .streamlit/secrets.toml.example | 41 - build_scripts/__init__.py | 1 + build_scripts/build.py | 229 ++ build_scripts/runtauri.py | 16 + geo_tool.py | 254 +- geo_tool.py.bak | 611 +++ main.py | 23 + modules/ui/theme.py | 24 + pyproject.toml | 40 + requirements.txt | 35 - run_bundle.py | 49 + src-tauri/.gitignore | 4 + src-tauri/Cargo.lock | 4941 +++++++++++++++++++++++++ src-tauri/Cargo.toml | 25 + src-tauri/build.rs | 3 + src-tauri/capabilities/default.json | 11 + src-tauri/icons/128x128.png | Bin 0 -> 11059 bytes src-tauri/icons/128x128@2x.png | Bin 0 -> 23137 bytes src-tauri/icons/32x32.png | Bin 0 -> 2225 bytes src-tauri/icons/Square107x107Logo.png | Bin 0 -> 9202 bytes src-tauri/icons/Square142x142Logo.png | Bin 0 -> 12530 bytes src-tauri/icons/Square150x150Logo.png | Bin 0 -> 13032 bytes src-tauri/icons/Square284x284Logo.png | Bin 0 -> 25943 bytes src-tauri/icons/Square30x30Logo.png | Bin 0 -> 2078 bytes src-tauri/icons/Square310x310Logo.png | Bin 0 -> 28507 bytes src-tauri/icons/Square44x44Logo.png | Bin 0 -> 3419 bytes src-tauri/icons/Square71x71Logo.png | Bin 0 -> 6027 bytes src-tauri/icons/Square89x89Logo.png | Bin 0 -> 7551 bytes src-tauri/icons/StoreLogo.png | Bin 0 -> 3971 bytes src-tauri/icons/icon.icns | Bin 0 -> 277003 bytes src-tauri/icons/icon.ico | Bin 0 -> 37710 bytes src-tauri/icons/icon.png | Bin 0 -> 49979 bytes src-tauri/src/lib.rs | 167 + src-tauri/src/lib.rs.bak | 167 + src-tauri/src/main.rs | 6 + src-tauri/tauri.conf.json | 41 + uv.lock | 2658 +++++++++++++ 39 files changed, 9167 insertions(+), 185 deletions(-) create mode 100644 .python-version delete mode 100644 .streamlit/secrets.toml.example create mode 100644 build_scripts/__init__.py create mode 100644 build_scripts/build.py create mode 100644 build_scripts/runtauri.py create mode 100644 geo_tool.py.bak create mode 100644 main.py create mode 100644 pyproject.toml delete mode 100644 requirements.txt create mode 100644 run_bundle.py create mode 100644 src-tauri/.gitignore create mode 100644 src-tauri/Cargo.lock create mode 100644 src-tauri/Cargo.toml create mode 100644 src-tauri/build.rs create mode 100644 src-tauri/capabilities/default.json create mode 100644 src-tauri/icons/128x128.png create mode 100644 src-tauri/icons/128x128@2x.png create mode 100644 src-tauri/icons/32x32.png create mode 100644 src-tauri/icons/Square107x107Logo.png create mode 100644 src-tauri/icons/Square142x142Logo.png create mode 100644 src-tauri/icons/Square150x150Logo.png create mode 100644 src-tauri/icons/Square284x284Logo.png create mode 100644 src-tauri/icons/Square30x30Logo.png create mode 100644 src-tauri/icons/Square310x310Logo.png create mode 100644 src-tauri/icons/Square44x44Logo.png create mode 100644 src-tauri/icons/Square71x71Logo.png create mode 100644 src-tauri/icons/Square89x89Logo.png create mode 100644 src-tauri/icons/StoreLogo.png create mode 100644 src-tauri/icons/icon.icns create mode 100644 src-tauri/icons/icon.ico create mode 100644 src-tauri/icons/icon.png create mode 100644 src-tauri/src/lib.rs create mode 100644 src-tauri/src/lib.rs.bak create mode 100644 src-tauri/src/main.rs create mode 100644 src-tauri/tauri.conf.json create mode 100644 uv.lock diff --git a/.gitignore b/.gitignore index 34217da..b9316e7 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,8 @@ +# Python 打包产物 +dist_python/ +build_python/ +*.spec + # SQLite 数据库文件 *.db *.sqlite diff --git a/.python-version b/.python-version new file mode 100644 index 0000000..e4fba21 --- /dev/null +++ b/.python-version @@ -0,0 +1 @@ +3.12 diff --git a/.streamlit/secrets.toml.example b/.streamlit/secrets.toml.example deleted file mode 100644 index 9d0732c..0000000 --- a/.streamlit/secrets.toml.example +++ /dev/null @@ -1,41 +0,0 @@ -# Streamlit Secrets 配置文件 -# 复制此文件为 secrets.toml 并填入真实的 API Key -# 注意：secrets.toml 已在 .gitignore 中，不会被提交到仓库 - -[api_keys] -# DeepSeek API Key（推荐，性价比高） -deepseek = "" - -# OpenAI API Key（可选） -# openai = "" - -# 通义千问 API Key（可选） -# tongyi = "" - -# Groq API Key（可选） -# groq = "" - -# Moonshot (Kimi) API Key（可选） -# moonshot = "" - -# 豆包 API Key（可选，格式：access_key:secret_key:endpoint_id） -# doubao = "" - -# 文心一言 API Key（可选，格式：app_key:app_secret） -# wenxin = "" - -# 通义万相 API Key（图片生成，可选） -# tongyi_wanxiang = "" - -[app_config] -# 品牌名称 -brand = "" - -# 品牌优势 -advantages = "" - -# 竞品列表（换行分隔） -competitors = "" - -# LLM 温度参数 -temperature = 0.7 diff --git a/build_scripts/__init__.py b/build_scripts/__init__.py new file mode 100644 index 0000000..d7ba418 --- /dev/null +++ b/build_scripts/__init__.py @@ -0,0 +1 @@ +# build_scripts package diff --git a/build_scripts/build.py b/build_scripts/build.py new file mode 100644 index 0000000..0e437e8 --- /dev/null +++ b/build_scripts/build.py @@ -0,0 +1,229 @@ +#!/usr/bin/env python3 +""" +GEO Tool — 跨平台打包构建脚本 + +用法: + python build_scripts/build.py # 打包 Python 可执行文件 + python build_scripts/build.py --clean # 先清理旧构建再打包 + python build_scripts/build.py tauri # 打包 Python 可执行文件 + 构建 Tauri 桌面应用 + +输出: + dist_python/geo_tool_app (macOS / Linux) + dist_python/geo_tool_app.exe (Windows) + src-tauri/target/release/GEO工具 (Tauri 桌面应用) + +依赖: + pip install pyinstaller + cargo tauri build (for tauri 命令) +""" + +import argparse +import os +import shutil +import subprocess +import sys +from pathlib import Path + +# ── 项目根目录 ──────────────────────────────────────────────── +PROJECT_ROOT = Path(__file__).resolve().parent.parent +SPEC_FILE = PROJECT_ROOT / "geo_tool_app.spec" +DIST_DIR = PROJECT_ROOT / "dist_python" +BUILD_DIR = PROJECT_ROOT / "build_python" +TAURI_DIR = PROJECT_ROOT / "src-tauri" + + +def check_prerequisites(): + """检查必要工具是否已安装""" + # 检查 PyInstaller + try: + import PyInstaller # noqa: F401 + except ImportError: + print("正在安装 PyInstaller ...") + subprocess.check_call( + [sys.executable, "-m", "pip", "install", "pyinstaller"], + cwd=str(PROJECT_ROOT), + ) + + # 检查项目依赖是否已安装 + try: + import streamlit # noqa: F401 + except ImportError: + print("正在安装项目依赖 ...") + # 优先用 uv，否则 pip install pyproject.toml + for installer in ["uv", "pip"]: + try: + subprocess.check_call( + [installer, "sync"] if installer == "uv" else [installer, "install", "."], + cwd=str(PROJECT_ROOT), + ) + break + except (subprocess.CalledProcessError, FileNotFoundError): + continue + + +def clean_build(): + """清理之前的构建产物""" + for d in [DIST_DIR, BUILD_DIR]: + if d.exists(): + print(f" 清理 {d} ...") + shutil.rmtree(d) + + # 清理 spec 生成的临时目录 + temp_spec_dir = PROJECT_ROOT / "__pycache__" + if temp_spec_dir.exists(): + shutil.rmtree(temp_spec_dir) + + +def build_tauri(): + """先打包 Python 可执行文件，然后构建 Tauri 桌面应用""" + build() + print("\n正在构建 Tauri 桌面应用 ...\n") + result = subprocess.run( + ["cargo", "tauri", "build"], + cwd=str(TAURI_DIR), + ) + if result.returncode != 0: + print(f"\n[错误] Tauri 构建失败 (返回码: {result.returncode})") + sys.exit(1) + + print("\n" + "=" * 60) + print(" Tauri 构建完成!") + release_dir = TAURI_DIR / "target" / "release" + if sys.platform == "darwin": + bundles = list(release_dir.glob("*.dmg")) + list((release_dir / "bundle" / "dmg").glob("*.dmg")) + list((release_dir / "bundle" / "macos").glob("*.app")) + elif sys.platform == "win32": + bundles = list(release_dir.glob("*.msi")) + list((release_dir / "bundle" / "msi").glob("*.msi")) + else: + bundles = list(release_dir.glob("GEO工具")) + list(release_dir.glob("*.AppImage")) + for b in bundles: + size_mb = b.stat().st_size / (1024 * 1024) if b.is_file() else sum(f.stat().st_size for f in b.rglob("*")) / (1024 * 1024) + print(f" 输出: {b} ({size_mb:.1f} MB)") + print("=" * 60) + + +def build(): + """执行 PyInstaller 打包""" + # 确保 run_bundle.py 存在 + entry_point = PROJECT_ROOT / "run_bundle.py" + if not entry_point.exists(): + print(f"[错误] 未找到入口文件: {entry_point}") + sys.exit(1) + + # 检查关键资源是否存在（给出警告而非中断） + resources = [ + ("geo_tool.py", "file"), + ("config.json", "file"), + ("geo_data.db", "file"), + (".streamlit", "dir"), + ("modules", "dir"), + ] + for path, _kind in resources: + p = PROJECT_ROOT / path + if not p.exists(): + print(f"[警告] 资源不存在: {p}") + + # 构建命令 + cmd = [ + sys.executable, + "-m", + "PyInstaller", + str(SPEC_FILE), + "--distpath", + str(DIST_DIR), + "--workpath", + str(BUILD_DIR), + "--clean", + "--noconfirm", + ] + + print("=" * 60) + print(" GEO Tool — 打包构建") + print("=" * 60) + print(f" 平台: {sys.platform}") + print(f" Python: {sys.version}") + print(f" 入口: {entry_point}") + print(f" Spec: {SPEC_FILE}") + print(f" 输出目录: {DIST_DIR}") + print("=" * 60) + + # 执行打包 + result = subprocess.run(cmd, cwd=str(PROJECT_ROOT)) + + if result.returncode != 0: + print(f"\n[错误] 打包失败 (返回码: {result.returncode})") + print(f" 请检查 {BUILD_DIR}/ 下的日志文件获取详细错误信息。") + sys.exit(1) + + # 输出结果 + print("\n" + "=" * 60) + print(" 打包完成!") + print("=" * 60) + + # 查找产物 + if sys.platform == "win32": + output = DIST_DIR / "geo_tool_app.exe" + elif sys.platform == "darwin": + output = DIST_DIR / "geo_tool_app" + else: + output = DIST_DIR / "geo_tool_app" + + if output.exists(): + size_mb = output.stat().st_size / (1024 * 1024) + print(f" 输出文件: {output}") + print(f" 文件大小: {size_mb:.1f} MB") + else: + # macOS 下可能生成 .app + app_bundle = DIST_DIR / "geo_tool_app.app" + if app_bundle.exists(): + size_mb = sum(f.stat().st_size for f in app_bundle.rglob("*")) / (1024 * 1024) + print(f" 输出文件: {app_bundle}") + print(f" 文件大小: {size_mb:.1f} MB") + + print(f" 运行方式: 双击 {output.name} 或终端执行 {output}") + print("=" * 60) + + +def main(): + parser = argparse.ArgumentParser( + description="GEO Tool 跨平台打包脚本", + ) + parser.add_argument( + "mode", + nargs="?", + default="python", + choices=["python", "tauri"], + help="打包模式: python (默认) 或 tauri (Python + 桌面壳)", + ) + parser.add_argument( + "--clean", + action="store_true", + help="构建前清理旧的 dist 和 build 目录", + ) + parser.add_argument( + "--skip-deps", + action="store_true", + help="跳过依赖检查（仅安装 PyInstaller）", + ) + args = parser.parse_args() + + # 切换到项目根目录 + os.chdir(str(PROJECT_ROOT)) + + # 清理 + if args.clean: + print("清理旧的构建产物 ...") + clean_build() + + # 检查环境 + if not args.skip_deps: + check_prerequisites() + + # 打包 + if args.mode == "tauri": + build_tauri() + else: + build() + + +if __name__ == "__main__": + main() diff --git a/build_scripts/runtauri.py b/build_scripts/runtauri.py new file mode 100644 index 0000000..f1a1a56 --- /dev/null +++ b/build_scripts/runtauri.py @@ -0,0 +1,16 @@ +## 写一个脚本，用于进入tauri项目目录，安装依赖，并运行tauri开发环境 + +import os +import subprocess + + +def main(): + # 进入tauri项目目录 + os.chdir("./src-tauri") + + # 安装依赖 + subprocess.check_call(["cargo", "run"]) + +if __name__ == "__main__": + main() + diff --git a/geo_tool.py b/geo_tool.py index 429cce0..a08dafb 100644 --- a/geo_tool.py +++ b/geo_tool.py @@ -22,10 +22,10 @@ from modules.ui.tab_knowledge import render_tab_knowledge from modules.ui.state import ss_init, init_session_state from modules.ui.theme import inject_global_theme -APP_TITLE = "GEO 智能内容优化平台" +APP_TITLE = "丑橘GEO内容优化平台" # ------------------- 页面配置 & 极简美学 CSS（产品级精修，仍然克制） ------------------- -st.set_page_config(page_title="GEO 智能内容优化平台", layout="wide", initial_sidebar_state="expanded") +st.set_page_config(page_title="丑橘GEO内容优化平台", layout="wide", initial_sidebar_state="collapsed") inject_global_theme() init_session_state() @@ -62,62 +62,8 @@ def record_api_cost(operation_type: str, provider: str, model: str, input_text: import logging logging.warning(f"记录 API 成本失败: {e}") -with st.expander("📖 关于 GEO（Generative Engine Optimization）", expanded=False): - st.markdown(""" -### 🎯 什么是 GEO？ -**GEO（Generative Engine Optimization，生成式引擎优化）** 是针对 AI 搜索引擎的内容优化策略。 - -传统 SEO 优化的是 Google、百度等传统搜索引擎的排名；而 GEO 优化的是 ChatGPT、Perplexity、Google SGE 等 AI 搜索引擎在回答用户问题时，**是否会引用您的品牌和内容**。 - -### 💡 为什么需要 GEO？ - -当用户向 AI 提问时（例如"最好的 XX 软件是什么？"），AI 会从互联网内容中检索信息并生成回答。如果您的品牌没有出现在 AI 可检索的高质量内容中，就会在 AI 时代失去曝光机会。 - -**GEO 的目标**：让您的品牌在 AI 回答中被优先、准确、可信地提及。 - ---- - -### 🔄 GEO 优化工作流 - -本工具提供完整的 GEO 优化闭环： - -| 阶段 | 功能 | 说明 | -|------|------|------| -| 1️⃣ 关键词策略 | 关键词蒸馏 | 生成针对 AI 搜索的口语化、长尾关键词 | -| 2️⃣ 内容创作 | 自动创作 | 基于知识库生成结构化、专业的内容 | -| 3️⃣ 内容优化 | 文章优化 | E-E-A-T 强化、事实密度增强、Schema 生成 | -| 4️⃣ 效果验证 | 多模型验证 | 用多个 AI 模型验证品牌是否被提及 | -| 5️⃣ 数据分析 | AI 数据报表 | 提及率趋势、ROI 分析、竞品对比 | -| 6️⃣ 内容分发 | 平台同步 | 多平台发布，扩大 AI 可检索内容 | - ---- - -### 📊 GEO 核心指标 - -| 指标 | 说明 | -|------|------| -| **品牌提及率** | AI 回答中提及品牌的频率 | -| **E-E-A-T 评分** | 专业性、经验性、权威性、可信度 | -| **事实密度** | 内容中可验证信息的密度 | -| **引用位置** | 品牌在 AI 回答中的位置（前 1/3 优先） | - ---- - -### 🌐 支持平台 - -**内容发布平台（20+）**：知乎、小红书、CSDN、B站、GitHub、微信公众号等 - -**AI 验证平台（7）**：DeepSeek、OpenAI、通义千问、Groq、Moonshot、豆包、文心一言 - ---- - -### 📚 更多资源 - -- [GEO 学术论文](https://arxiv.org/abs/2311.09735) - GEO 原始研究 -- [项目文档](DOCS.md) - 完整功能文档 -- [快速开始](docs/guides/QUICK_START_GUIDE.md) - 新手入门指南 -""") +# =================== 函数定义：配置管理（在 expander 之前定义，因为 expander 内使用了它们） =================== def load_default_cfg(): """ @@ -153,7 +99,6 @@ def load_default_cfg(): # 从 st.secrets 读取敏感信息（优先级更高） try: if hasattr(st, 'secrets') and st.secrets: - # 读取 API Keys if "api_keys" in st.secrets: api_keys = st.secrets["api_keys"] if "deepseek" in api_keys and api_keys["deepseek"]: @@ -161,15 +106,13 @@ def load_default_cfg(): base_cfg["verify_keys"]["DeepSeek"] = api_keys["deepseek"] if "tongyi_wanxiang" in api_keys and api_keys["tongyi_wanxiang"]: base_cfg["tongyi_wanxiang_api_key"] = api_keys["tongyi_wanxiang"] - - # 读取应用配置（如果存在） + if "app_config" in st.secrets: app_config = st.secrets["app_config"] for key in ["brand", "advantages", "competitors", "temperature"]: if key in app_config and app_config[key]: base_cfg[key] = app_config[key] except FileNotFoundError: - # secrets.toml 不存在时静默忽略，用户可通过侧边栏配置 pass except Exception as e: import logging @@ -180,9 +123,14 @@ def load_default_cfg(): def save_cfg_to_file(cfg: dict) -> None: """ - 将当前生效的非敏感配置写入本地 config.json。 - 敏感信息（API Keys）不会保存到此文件，仅保存到 .streamlit/secrets.toml。 + 将配置持久化到本地文件： + - 非敏感配置 → config.json + - API Keys + 品牌信息 → .streamlit/secrets.toml """ + import tomllib + import tomli_w # type: ignore + + # ── 1. 非敏感配置 → config.json ── config_path = Path(__file__).with_name("config.json") try: data = {} @@ -194,50 +142,132 @@ def save_cfg_to_file(cfg: dict) -> None: data.update(loaded) except Exception as e: import logging - logging.warning(f"读取配置文件失败: {e}") + logging.warning(f"读取 config.json 失败: {e}") data = {} - - # 只保存非敏感配置 - sensitive_keys = {"gen_api_key", "verify_keys", "tongyi_wanxiang_api_key"} + for key in ["gen_provider", "verify_providers", "brand", "advantages", "competitors", "temperature"]: if key in cfg: data[key] = cfg[key] - + with config_path.open("w", encoding="utf-8") as f: json.dump(data, f, ensure_ascii=False, indent=2) - - # 提示用户如何保存 API Keys - if any(key in cfg for key in sensitive_keys): - try: - st.info("💡 API Keys 需要在 `.streamlit/secrets.toml` 文件中手动配置。") - except Exception: - pass - + except Exception as e: import logging - logging.error(f"保存配置文件失败: {e}") + logging.error(f"保存 config.json 失败: {e}") + + # ── 2. API Keys + 品牌信息 → .streamlit/secrets.toml ── + secrets_path = Path(__file__).parent / ".streamlit" / "secrets.toml" + try: + # 读取现有的 secrets.toml（如果存在） + existing = {} + if secrets_path.exists(): + try: + with secrets_path.open("rb") as f: + existing = tomllib.load(f) + except Exception: + existing = {} + + # 构建新的 api_keys 段 + new_api_keys = existing.get("api_keys", {}) + + # gen_api_key → deepseek + if "gen_api_key" in cfg and cfg["gen_api_key"]: + new_api_keys["deepseek"] = cfg["gen_api_key"] + + # verify_keys → 各 provider 的 key + verify_keys = cfg.get("verify_keys", {}) + provider_map = { + "DeepSeek": "deepseek", + "OpenAI (GPT)": "openai", + "Groq": "groq", + "Moonshot (Kimi)": "moonshot", + "Tongyi (通义千问)": "tongyi", + "豆包（字节跳动）": "doubao", + "文心一言（百度）": "wenxin", + } + for display_name, key_name in provider_map.items(): + if display_name in verify_keys and verify_keys[display_name]: + new_api_keys[key_name] = verify_keys[display_name] + + # tongyi_wanxiang_api_key + if "tongyi_wanxiang_api_key" in cfg and cfg["tongyi_wanxiang_api_key"]: + new_api_keys["tongyi_wanxiang"] = cfg["tongyi_wanxiang_api_key"] + + # 构建新的 app_config 段 + new_app_config = existing.get("app_config", {}) + for key in ["brand", "advantages", "competitors"]: + if key in cfg and cfg[key]: + new_app_config[key] = cfg[key] + if "temperature" in cfg: + new_app_config["temperature"] = cfg["temperature"] + + # 写出 TOML + secrets_path.parent.mkdir(parents=True, exist_ok=True) + with secrets_path.open("wb") as f: + content = {"api_keys": new_api_keys, "app_config": new_app_config} + tomli_w.dump(content, f) + + except ImportError: + # tomli_w 未安装 — 回退到手动写 TOML 字符串 + _save_secrets_fallback(secrets_path, cfg) + except Exception as e: + import logging + logging.error(f"保存 secrets.toml 失败: {e}") try: - st.warning("⚠️ 无法将配置写入本地 config.json，但当前会话已生效。请检查文件权限。") + st.warning("⚠️ 无法将 API Key 写入 .streamlit/secrets.toml，但当前会话已生效。") except Exception: pass -ss_init("cfg", load_default_cfg()) +def _save_secrets_fallback(secrets_path: Path, cfg: dict) -> None: + """tomli_w 不可用时的纯文本备选方案""" + try: + secrets_path.parent.mkdir(parents=True, exist_ok=True) -# 模块1：关键词（补充 init_session_state 中未包含的） -ss_init("keyword_tool", KeywordTool()) # 托词工具实例 + lines = ["# Streamlit Secrets（自动保存）\n"] + + lines.append("\n[api_keys]\n") + if cfg.get("gen_api_key"): + lines.append(f'deepseek = "{cfg["gen_api_key"]}"\n') + + verify_keys = cfg.get("verify_keys", {}) + provider_map = { + "DeepSeek": "deepseek", + "OpenAI (GPT)": "openai", + "Groq": "groq", + "Moonshot (Kimi)": "moonshot", + "Tongyi (通义千问)": "tongyi", + "豆包（字节跳动）": "doubao", + "文心一言（百度）": "wenxin", + } + for display_name, key_name in provider_map.items(): + if display_name in verify_keys and verify_keys[display_name]: + lines.append(f'{key_name} = "{verify_keys[display_name]}"\n') + + if cfg.get("tongyi_wanxiang_api_key"): + lines.append(f'tongyi_wanxiang = "{cfg["tongyi_wanxiang_api_key"]}"\n') + + lines.append("\n[app_config]\n") + for key in ["brand", "advantages", "competitors"]: + if cfg.get(key): + lines.append(f'{key} = "{cfg[key]}"\n') + if "temperature" in cfg: + lines.append(f"temperature = {cfg['temperature']}\n") + + with secrets_path.open("w", encoding="utf-8") as f: + f.writelines(lines) + + except Exception as e: + import logging + logging.error(f"保存 secrets.toml（备选方案）失败: {e}") -# 模块2：内容（补充 init_session_state 中未包含的） -ss_init("multimodal_descriptions", {}) # 多模态描述（配图描述、视频脚本等） -ss_init("image_descriptions", []) # 图片描述列表 -ss_init("detail_tab_active", "🎨 增强工具") # 保存当前激活的详情Tab -# ------------------- 工具函数 ------------------- def validate_cfg(cfg: dict): """验证配置完整性，返回 (是否有效, 错误列表)。""" errors = [] warnings = [] - + if not cfg.get("gen_api_key", "").strip(): errors.append("生成&优化 LLM 的 API Key 未填写") @@ -249,7 +279,7 @@ def validate_cfg(cfg: dict): for vp in verify_providers: if not verify_keys.get(vp, "").strip(): errors.append(f"验证模型 {vp} 的 API Key 未填写") - + if not cfg.get("brand", "").strip(): warnings.append("品牌名称未填写（部分功能需要）") if not cfg.get("advantages", "").strip(): @@ -258,28 +288,12 @@ def validate_cfg(cfg: dict): return (len(errors) == 0), errors + warnings -def model_defaults(provider: str) -> str: - from modules.llm_factory import get_default_model - return get_default_model(provider) +# 初始化默认配置（要在 expander 之前，因为 expander 内访问了 cfg） +ss_init("cfg", load_default_cfg()) - -# ------------------- 缓存 LLM 客户端（显著降低“频繁 Loading”） ------------------- -@st.cache_resource(show_spinner=False) -def build_llm(provider: str, api_key: str, model: str, temperature: float): - """ - - 使用 cache_resource 缓存客户端，避免每次 rerun 重建 - - 统一使用 llm_factory 模块构建 LLM - """ - from modules.llm_factory import build_llm as _build_llm - return _build_llm(provider, api_key, model, temperature) - - -# ------------------- 侧边栏：全局配置（分组折叠） ------------------- -with st.sidebar: - st.header("⚙️ 全局配置") +with st.expander("配置", expanded=False): - # LLM 配置组 - with st.expander("🤖 LLM 配置", expanded=True): + with st.expander("LLM 配置", expanded=True): PROVIDER_LIST = ["DeepSeek", "OpenAI (GPT)", "Tongyi (通义千问)", "Groq", "Moonshot (Kimi)", "豆包（字节跳动）", "文心一言（百度）"] gen_provider = st.selectbox( @@ -423,6 +437,28 @@ with st.sidebar: st.caption("闭环：关键词 → 创作 → 优化 → 验证") + + + + +def model_defaults(provider: str) -> str: + from modules.llm_factory import get_default_model + return get_default_model(provider) + + +# ------------------- 缓存 LLM 客户端（显著降低“频繁 Loading”） ------------------- +@st.cache_resource(show_spinner=False) +def build_llm(provider: str, api_key: str, model: str, temperature: float): + """ + - 使用 cache_resource 缓存客户端，避免每次 rerun 重建 + - 统一使用 llm_factory 模块构建 LLM + """ + from modules.llm_factory import build_llm as _build_llm + return _build_llm(provider, api_key, model, temperature) + + +# ------------------- 侧边栏：全局配置（分组折叠） ------------------- + cfg = st.session_state.cfg brand = cfg["brand"] advantages = cfg["advantages"] @@ -620,4 +656,4 @@ with tab10: with tab11: render_tab_knowledge(kb) -st.caption("最完整版：GitHub模板 + 真实多模型验证 + 现有文章优化 + RAG知识库 • GEO全闭环，专注AI品牌影响力") +st.caption("一站式GEO优化平台｜ 多模型验证 + 文章优化 + RAG知识库 • GEO全闭环，专注AI品牌影响力") diff --git a/geo_tool.py.bak b/geo_tool.py.bak new file mode 100644 index 0000000..98aea26 --- /dev/null +++ b/geo_tool.py.bak @@ -0,0 +1,611 @@ +import streamlit as st +from pathlib import Path +import json +from typing import Optional +from modules.data_storage import DataStorage +from modules.keyword_tool import KeywordTool +from modules.roi_analyzer import ROIAnalyzer +from modules.knowledge_base import KnowledgeBase +from modules.ui import ( + tab_keywords, + tab_autowrite, + tab_optimize, + tab_validation, + tab_history, + tab_reports, + tab_workflow, + tab_resources, + tab_platform_sync, + tab_config_optimizer, +) +from modules.ui.tab_knowledge import render_tab_knowledge +from modules.ui.state import ss_init, init_session_state +from modules.ui.theme import inject_global_theme + +APP_TITLE = "GEO 智能内容优化平台" + +# ------------------- 页面配置 & 极简美学 CSS（产品级精修，仍然克制） ------------------- +st.set_page_config(page_title="GEO 智能内容优化平台", layout="wide", initial_sidebar_state="expanded") + +inject_global_theme() +init_session_state() +st.title(APP_TITLE) + +st.caption("🚀 AI 驱动的品牌内容策略 · 让您的品牌在 AI 对话中脱颖而出") + +# ------------------- 初始化数据存储（SQLite） ------------------- +storage = DataStorage(storage_type="sqlite", db_path="geo_data.db") + +# ------------------- 初始化知识库（RAG） ------------------- +kb = KnowledgeBase(storage_path="knowledge_base") + +# ------------------- 成本记录辅助函数 ------------------- +def estimate_tokens(text: str) -> int: + """估算文本的 token 数量：中文约 1.5 字符 = 1 token，英文约 4 字符 = 1 token""" + if not text: + return 0 + chinese_chars = sum(1 for char in text if '\u4e00' <= char <= '\u9fff') + other_chars = len(text) - chinese_chars + estimated_tokens = int(chinese_chars / 1.5 + other_chars / 4) + return max(estimated_tokens, len(text) // 4) + +def record_api_cost(operation_type: str, provider: str, model: str, input_text: str, output_text: str, keyword: Optional[str] = None, platform: Optional[str] = None, brand: Optional[str] = None): + """记录 API 调用成本""" + try: + roi_analyzer = ROIAnalyzer() + input_tokens = estimate_tokens(input_text) + output_tokens = estimate_tokens(output_text) + total_tokens = input_tokens + output_tokens + cost_usd, cost_cny = roi_analyzer.calculate_cost(provider, model, input_tokens, output_tokens) + storage.save_api_call(operation_type=operation_type, provider=provider, model=model, input_tokens=input_tokens, output_tokens=output_tokens, total_tokens=total_tokens, cost_usd=cost_usd, cost_cny=cost_cny, keyword=keyword, platform=platform, brand=brand) + except Exception as e: + import logging + logging.warning(f"记录 API 成本失败: {e}") + +def load_default_cfg(): + """ + 从项目根目录的 config.json 读取默认配置，如果不存在则使用内置默认值。 + 敏感信息（API Keys）优先从 .streamlit/secrets.toml 读取。 + """ + base_cfg = { + "gen_provider": "DeepSeek", + "gen_api_key": "", + "verify_providers": ["DeepSeek"], + "verify_keys": { + "DeepSeek": "" + }, + "tongyi_wanxiang_api_key": "", + "brand": "", + "advantages": "", + "competitors": "", + "temperature": 0.7, + } + + # 从 config.json 读取非敏感配置 + config_path = Path(__file__).with_name("config.json") + if config_path.exists(): + try: + with config_path.open("r", encoding="utf-8") as f: + file_cfg = json.load(f) + if isinstance(file_cfg, dict): + base_cfg.update(file_cfg) + except Exception as e: + import logging + logging.warning(f"配置文件加载失败: {e}") + + # 从 st.secrets 读取敏感信息（优先级更高） + try: + if hasattr(st, 'secrets') and st.secrets: + # 读取 API Keys + if "api_keys" in st.secrets: + api_keys = st.secrets["api_keys"] + if "deepseek" in api_keys and api_keys["deepseek"]: + base_cfg["gen_api_key"] = api_keys["deepseek"] + base_cfg["verify_keys"]["DeepSeek"] = api_keys["deepseek"] + if "tongyi_wanxiang" in api_keys and api_keys["tongyi_wanxiang"]: + base_cfg["tongyi_wanxiang_api_key"] = api_keys["tongyi_wanxiang"] + + # 读取应用配置（如果存在） + if "app_config" in st.secrets: + app_config = st.secrets["app_config"] + for key in ["brand", "advantages", "competitors", "temperature"]: + if key in app_config and app_config[key]: + base_cfg[key] = app_config[key] + except FileNotFoundError: + # secrets.toml 不存在时静默忽略，用户可通过侧边栏配置 + pass + except Exception as e: + import logging + logging.warning(f"读取 secrets.toml 失败: {e}") + + return base_cfg + + +def save_cfg_to_file(cfg: dict) -> None: + """ + 将当前生效的非敏感配置写入本地 config.json。 + 敏感信息（API Keys）不会保存到此文件，仅保存到 .streamlit/secrets.toml。 + """ + config_path = Path(__file__).with_name("config.json") + try: + data = {} + if config_path.exists(): + try: + with config_path.open("r", encoding="utf-8") as f: + loaded = json.load(f) + if isinstance(loaded, dict): + data.update(loaded) + except Exception as e: + import logging + logging.warning(f"读取配置文件失败: {e}") + data = {} + + # 只保存非敏感配置 + sensitive_keys = {"gen_api_key", "verify_keys", "tongyi_wanxiang_api_key"} + for key in ["gen_provider", "verify_providers", "brand", "advantages", "competitors", "temperature"]: + if key in cfg: + data[key] = cfg[key] + + with config_path.open("w", encoding="utf-8") as f: + json.dump(data, f, ensure_ascii=False, indent=2) + + # 提示用户如何保存 API Keys + if any(key in cfg for key in sensitive_keys): + try: + st.info("💡 API Keys 需要在 `.streamlit/secrets.toml` 文件中手动配置。") + except Exception: + pass + + except Exception as e: + import logging + logging.error(f"保存配置文件失败: {e}") + try: + st.warning("⚠️ 无法将配置写入本地 config.json，但当前会话已生效。请检查文件权限。") + except Exception: + pass + + +ss_init("cfg", load_default_cfg()) + +# 模块1：关键词（补充 init_session_state 中未包含的） +ss_init("keyword_tool", KeywordTool()) # 托词工具实例 + +# 模块2：内容（补充 init_session_state 中未包含的） +ss_init("multimodal_descriptions", {}) # 多模态描述（配图描述、视频脚本等） +ss_init("image_descriptions", []) # 图片描述列表 +ss_init("detail_tab_active", "🎨 增强工具") # 保存当前激活的详情Tab + +# ------------------- 工具函数 ------------------- +def validate_cfg(cfg: dict): + """验证配置完整性，返回 (是否有效, 错误列表)。""" + errors = [] + warnings = [] + + if not cfg.get("gen_api_key", "").strip(): + errors.append("生成&优化 LLM 的 API Key 未填写") + + verify_providers = cfg.get("verify_providers", []) + verify_keys = cfg.get("verify_keys", {}) + if not verify_providers: + errors.append("至少选择一个验证模型") + + for vp in verify_providers: + if not verify_keys.get(vp, "").strip(): + errors.append(f"验证模型 {vp} 的 API Key 未填写") + + if not cfg.get("brand", "").strip(): + warnings.append("品牌名称未填写（部分功能需要）") + if not cfg.get("advantages", "").strip(): + warnings.append("核心优势未填写（部分功能需要）") + + return (len(errors) == 0), errors + warnings + + +def model_defaults(provider: str) -> str: + from modules.llm_factory import get_default_model + return get_default_model(provider) + + +# ------------------- 缓存 LLM 客户端（显著降低“频繁 Loading”） ------------------- +@st.cache_resource(show_spinner=False) +def build_llm(provider: str, api_key: str, model: str, temperature: float): + +with st.expander("📖 关于 GEO（Generative Engine Optimization）", expanded=False): + st.markdown(""" + +**GEO（Generative Engine Optimization，生成式引擎优化）** 是针对 AI 搜索引擎的内容优化策略。 + +传统 SEO 优化的是 Google、百度等传统搜索引擎的排名；而 GEO 优化的是 ChatGPT、Perplexity、Google SGE 等 AI 搜索引擎在回答用户问题时，**是否会引用您的品牌和内容**。 + +### 💡 为什么需要 GEO？ + +当用户向 AI 提问时（例如"最好的 XX 软件是什么？"），AI 会从互联网内容中检索信息并生成回答。如果您的品牌没有出现在 AI 可检索的高质量内容中，就会在 AI 时代失去曝光机会。 + +**GEO 的目标**：让您的品牌在 AI 回答中被优先、准确、可信地提及。 + +--- + +### 🔄 GEO 优化工作流 + +本工具提供完整的 GEO 优化闭环： + +| 阶段 | 功能 | 说明 | +|------|------|------| +| 1️⃣ 关键词策略 | 关键词蒸馏 | 生成针对 AI 搜索的口语化、长尾关键词 | +| 2️⃣ 内容创作 | 自动创作 | 基于知识库生成结构化、专业的内容 | +| 3️⃣ 内容优化 | 文章优化 | E-E-A-T 强化、事实密度增强、Schema 生成 | +| 4️⃣ 效果验证 | 多模型验证 | 用多个 AI 模型验证品牌是否被提及 | +| 5️⃣ 数据分析 | AI 数据报表 | 提及率趋势、ROI 分析、竞品对比 | +| 6️⃣ 内容分发 | 平台同步 | 多平台发布，扩大 AI 可检索内容 | + +--- + +### 📊 GEO 核心指标 + +| 指标 | 说明 | +|------|------| +| **品牌提及率** | AI 回答中提及品牌的频率 | +| **E-E-A-T 评分** | 专业性、经验性、权威性、可信度 | +| **事实密度** | 内容中可验证信息的密度 | +| **引用位置** | 品牌在 AI 回答中的位置（前 1/3 优先） | + +--- + +### 🌐 支持平台 + +**内容发布平台（20+）**：知乎、小红书、CSDN、B站、GitHub、微信公众号等 + +**AI 验证平台（7）**：DeepSeek、OpenAI、通义千问、Groq、Moonshot、豆包、文心一言 + +--- + +### 📚 更多资源 + +- [GEO 学术论文](https://arxiv.org/abs/2311.09735) - GEO 原始研究 +- [项目文档](DOCS.md) - 完整功能文档 +- [快速开始](docs/guides/QUICK_START_GUIDE.md) - 新手入门指南 +""") +""") + # LLM 配置组 + with st.expander("🤖 LLM 配置", expanded=True): + PROVIDER_LIST = ["DeepSeek", "OpenAI (GPT)", "Tongyi (通义千问)", "Groq", "Moonshot (Kimi)", "豆包（字节跳动）", "文心一言（百度）"] + + gen_provider = st.selectbox( + "生成&优化 LLM", + PROVIDER_LIST, + index=PROVIDER_LIST.index(st.session_state.cfg["gen_provider"]) if st.session_state.cfg["gen_provider"] in PROVIDER_LIST else 0, + key="sb_gen_provider", + ) + + # API Key 输入提示 + api_key_help = "" + if gen_provider == "豆包（字节跳动）": + api_key_help = "格式：access_key:secret_key:endpoint_id（用冒号分隔）" + elif gen_provider == "文心一言（百度）": + api_key_help = "格式：app_key:app_secret（用冒号分隔）" + + gen_api_key = st.text_input( + f"{gen_provider} API Key（生成&优化用）", + type="password", + value=st.session_state.cfg.get("gen_api_key", ""), + key="sb_gen_api_key", + help=api_key_help if api_key_help else None, + ) + + # 验证配置组 + with st.expander("🔍 验证配置", expanded=False): + verify_providers = st.multiselect( + "选择验证模型", + PROVIDER_LIST, + default=st.session_state.cfg.get("verify_providers", []), + key="sb_verify_providers", + ) + + verify_keys = {} + old_keys = st.session_state.cfg.get("verify_keys", {}) + for vp in verify_providers: + vp_help = "" + if vp == "豆包（字节跳动）": + vp_help = "格式：access_key:secret_key:endpoint_id（用冒号分隔）" + elif vp == "文心一言（百度）": + vp_help = "格式：app_key:app_secret（用冒号分隔）" + + verify_keys[vp] = st.text_input( + f"{vp} API Key（验证用）", + type="password", + value=old_keys.get(vp, ""), + key=f"sb_verify_key_{vp}", + help=vp_help if vp_help else None, + ) + + # 品牌信息组 + with st.expander("🏢 品牌信息", expanded=True): + brand = st.text_input("主品牌名称", value=st.session_state.cfg.get("brand", ""), key="sb_brand") + + advantages = st.text_area( + "核心优势/卖点（AI专属）", + value=st.session_state.cfg.get("advantages", ""), + height=120, + key="sb_advantages", + ) + + competitors = st.text_area( + "竞品品牌（每行一个）", + value=st.session_state.cfg.get("competitors", ""), + height=100, + key="sb_competitors", + ) + + # 高级设置组 + with st.expander("⚙️ 高级设置", expanded=False): + temperature = st.slider( + "生成温度（更稳→更低）", + 0.0, + 1.0, + float(st.session_state.cfg.get("temperature", 0.7)), + 0.05, + key="sb_temperature", + ) + + tongyi_wanxiang_api_key = st.text_input( + "通义万相 API Key（图片生成）", + type="password", + value=st.session_state.cfg.get("tongyi_wanxiang_api_key", ""), + key="sb_tongyi_wanxiang_api_key", + help="阿里云 DashScope API Key，用于生成文章配图。", + ) + + # 应用配置按钮 + apply_cfg = st.button("应用配置", use_container_width=True, type="primary") + + if apply_cfg or not st.session_state.cfg_applied: + # 优先从主 key 读取值（如果使用了临时 key 更新，值已同步到主 key） + brand_value = st.session_state.get("sb_brand", brand) + advantages_value = st.session_state.get("sb_advantages", advantages) + + st.session_state.cfg = { + "gen_provider": gen_provider, + "gen_api_key": gen_api_key, + "verify_providers": verify_providers, + "verify_keys": verify_keys, + "tongyi_wanxiang_api_key": tongyi_wanxiang_api_key, + "brand": brand_value, + "advantages": advantages_value, + "competitors": competitors, + "temperature": temperature, + } + + ok, errs = validate_cfg(st.session_state.cfg) + st.session_state.cfg_valid = ok + st.session_state.cfg_errors = errs + + if ok: + # 仅在配置合法时才写入本地配置文件，并标记为已应用 + save_cfg_to_file(st.session_state.cfg) + st.session_state.cfg_applied = True + else: + st.session_state.cfg_applied = False + + if not st.session_state.cfg_valid: + with st.container(border=True): + st.markdown("**⚠️ 完成配置后即可使用全部功能**") + for err in st.session_state.cfg_errors: + st.markdown(f"• {err}") + else: + with st.container(border=True): + st.markdown("**✅ 配置已就绪**") + st.caption("所有功能已解锁，可以开始使用") + + st.markdown("---") + if st.button("重置全部结果（不删除配置）", use_container_width=True, key="sb_reset_all"): + st.session_state.keywords = [] + st.session_state.generated_contents = [] + st.session_state.zip_bytes = None + st.session_state.zip_filename = "" + st.session_state.optimized_article = "" + st.session_state.opt_changes = "" + st.session_state.verify_combined = None + st.session_state.config_optimization_result = None + st.session_state.config_hash = None + st.toast("已重置全部结果。") + + st.caption("闭环：关键词 → 创作 → 优化 → 验证") + +cfg = st.session_state.cfg +brand = cfg["brand"] +advantages = cfg["advantages"] +temperature = float(cfg.get("temperature", 0.7)) + +competitor_list = [c.strip() for c in cfg["competitors"].split("\n") if c.strip()] +_seen = set() +clean_competitors = [] +for c in competitor_list: + cl = c.lower() + if cl == brand.lower(): + continue + if cl in _seen: + continue + _seen.add(cl) + clean_competitors.append(c) +competitor_list = clean_competitors + +# ------------------- 初始化 LLM（仅在 cfg_valid 时；且 build_llm 已缓存） ------------------- +gen_llm = None +verify_llms = {} + +if st.session_state.cfg_valid: + try: + gen_llm = build_llm(cfg["gen_provider"], cfg["gen_api_key"], model_defaults(cfg["gen_provider"]), temperature) + except Exception as e: + st.error(f"生成LLM加载失败：{e}") + + for vp in cfg["verify_providers"]: + key = cfg["verify_keys"].get(vp, "").strip() + if not key: + continue + try: + verify_llms[vp] = build_llm(vp, key, model_defaults(vp), temperature) + except Exception as e: + st.error(f"{vp}验证LLM加载失败：{e}") + +# ------------------- KPI 总览（极简但更像产品） ------------------- +k1, k2, k3, k4 = st.columns(4) +k1.metric("关键词", len(st.session_state.keywords), border=True) +k2.metric("内容包", len(st.session_state.generated_contents), border=True) +k3.metric("文章优化", "已生成" if bool(st.session_state.optimized_article) else "未生成", border=True) +k4.metric("验证结果", "已生成" if st.session_state.verify_combined is not None else "未生成", border=True) + +st.markdown("---") + +# ------------------- 主导航：Tabs（流程更清晰） ------------------- +tab1, tab2, tab3, tab4, tab5, tab6, tab7, tab8, tab9, tab10, tab11 = st.tabs([ + "🎯 关键词蒸馏", + "✍️ 自动创作", + "🔧 文章优化", + "✅ 多模型验证", + "📚 历史记录", + "📊 AI 数据报表", + "⚙️ 工作流自动化", + "📦 GEO 资源库", + "🔄 平台同步", + "🛠️ 配置优化助手", + "📚 品牌知识库" +]) + +# ======================= +# Tab1：关键词蒸馏 +# ======================= +with tab1: + tab_keywords.render_tab_keywords( + storage, + ss_init, + gen_llm, + brand, + advantages + ) + + +# ======================= +# Tab2：自动创作内容（含批量 ZIP / GitHub 模板） +# ======================= +with tab2: + tab_autowrite.render_tab_autowrite( + storage, + ss_init, + gen_llm, + brand, + advantages, + cfg, + record_api_cost, + model_defaults + ) + + +# ======================= +# Tab3：文章优化 +# ======================= +with tab3: + tab_optimize.render_tab_optimize( + storage, + ss_init, + gen_llm, + brand, + advantages, + cfg, + record_api_cost, + model_defaults, + ) + + +# ======================= +# Tab4：多模型验证 & 竞品对比 +# ======================= +with tab4: + tab_validation.render_tab_validation( + storage, + ss_init, + brand, + advantages, + competitor_list, + verify_llms, + record_api_cost, + model_defaults, + ) + + +# ======================= +# Tab5：历史记录 +# ======================= +with tab5: + tab_history.render_tab_history(storage, brand) + + +# ======================= +# Tab6：AI 数据报表 +# ======================= +with tab6: + tab_reports.render_tab_reports( + storage, + ss_init, + gen_llm, + brand, + advantages, + competitor_list, + verify_llms, + record_api_cost, + model_defaults, + ) + + +# ======================= +# Tab7：工作流自动化 +# ======================= +with tab7: + tab_workflow.render_tab_workflow( + storage, + ss_init, + gen_llm, + brand, + advantages, + competitor_list, + verify_llms, + record_api_cost, + model_defaults, + ) + +# ======================= +# Tab8：GEO 资源库 +# ======================= +with tab8: + tab_resources.render_tab_resources(storage, brand) + + +# ======================= +# Tab9：平台同步 +# ======================= +with tab9: + tab_platform_sync.render_tab_platform_sync(storage, brand) + + +# ======================= +# Tab10：配置优化助手 +# ======================= +with tab10: + tab_config_optimizer.render_tab_config_optimizer( + storage, + cfg, + brand, + advantages, + competitor_list, + build_llm, + model_defaults, + ) + + +# ======================= +# Tab11：品牌知识库（RAG） +# ======================= +with tab11: + render_tab_knowledge(kb) + +st.caption("最完整版：GitHub模板 + 真实多模型验证 + 现有文章优化 + RAG知识库 • GEO全闭环，专注AI品牌影响力") diff --git a/main.py b/main.py new file mode 100644 index 0000000..ea8f04e --- /dev/null +++ b/main.py @@ -0,0 +1,23 @@ +import sys + +def main(): + + sys.argv = [ + "streamlit", + "run", + "geo_tool.py", + "--server.port", "8501", + "--server.address", "127.0.0.1", + "--server.headless", "true", + "--browser.gatherUsageStats", "false", + "--global.developmentMode", "false", + "--logger.level", "error", + ] + + from streamlit.web.cli import main as streamlit_main + streamlit_main() + pass + + +if __name__ == "__main__": + main() diff --git a/modules/ui/theme.py b/modules/ui/theme.py index 7e673e7..e9afa4d 100644 --- a/modules/ui/theme.py +++ b/modules/ui/theme.py @@ -521,6 +521,30 @@ div[data-testid="stVerticalBlock"] > div { [data-testid="stHorizontalBlock"] { gap: 0.5rem !important; } +/* ========== 隐藏整个页眉（含 Deploy、菜单、状态等） ========== */ +header[data-testid="stHeader"] { + display: none !important; +} + +/* ========== 隐藏右上角Deploy和菜单按钮 ========== */ +/* 隐藏 Streamlit 自带的 Deploy 按钮 */ +button[kind="header"]:has(div[data-testid="stStatusWidget"]), +button[kind="headerNoBorder"]:has(div[data-testid="stStatusWidget"]), + +/* 隐藏右上角的...菜单按钮 */ +[data-testid="stMainMenu"] > div > button, +.stMainMenu, + +/* 隐藏状态图标 */ +[data-testid="stStatusWidget"] { + display: none !important; +} + +/* 补偿页眉高度 */ +.appview-container .main { + margin-top: 0 !important; +} + """, unsafe_allow_html=True, diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 0000000..d7fa392 --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,40 @@ +[project] +name = "aigeotools" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.12" +dependencies = [ + "dashscope>=1.25.19", + "langchain-core>=1.4.0", + "langchain-deepseek>=1.0.1", + "langchain-groq>=1.1.2", + "langchain-moonshot>=0.1.0", + "langchain-openai>=1.2.2", + "pandas>=3.0.3", + "plotly>=6.7.0", + "pyperclip>=1.11.0", + "streamlit>=1.58.0", + "tomli-w>=1.2.0", + "watchdog>=6.0.0", +] + +[build-system] +requires = ["setuptools"] +build-backend = "setuptools.build_meta" + +[tool.setuptools.packages.find] +include = ["build_scripts*"] + +[dependency-groups] +dev = [ + "pyinstaller>=6.20.0", +] + +[tool.uv] +package = true + +[project.scripts] +python-build = "build_scripts.build:main" +tauri-run = "build_scripts.runtauri:main" +tauri-build = "build_scripts.build:build_tauri" diff --git a/requirements.txt b/requirements.txt deleted file mode 100644 index 445cd0b..0000000 --- a/requirements.txt +++ /dev/null @@ -1,35 +0,0 @@ -# 核心依赖 -streamlit>=1.30,<2 -pandas>=2.0,<3 -plotly>=5.0,<6 - -# LangChain 核心 -langchain-core>=1.2,<2 -langchain-community>=0.4,<1 - -# LangChain 提供商（按需安装） -langchain-openai>=1.1,<2 -langchain-groq>=1.1,<2 -langchain-deepseek>=1.0,<2 -langchain-moonshot>=0.1.0,<1 -langchain-aliyun>=0.1.0,<1 - -# 平台同步功能依赖 -httpx>=0.24.0 -pyperclip>=1.8.2 - -# ============================================================ -# 可选依赖（根据需要取消注释） -# ============================================================ - -# 通义万相图片生成（阿里云） -# dashscope>=1.0,<2 - -# 文心一言（百度） -# qianfan>=0.1.0 - -# 豆包（字节跳动） -# pip install 'volcengine-python-sdk[ark]' - -# LangChain 文心一言支持 -# langchain-wenxin>=0.1.0,<1 diff --git a/run_bundle.py b/run_bundle.py new file mode 100644 index 0000000..9163089 --- /dev/null +++ b/run_bundle.py @@ -0,0 +1,49 @@ +""" +GEO Tool — PyInstaller 打包入口 + +打包后自动切换工作目录到解压路径，确保 config.json、geo_data.db、 +.streamlit/、knowledge_base/ 等资源文件的相对路径正常工作。 +""" + +import os +import sys +from pathlib import Path + + +def main(): + # 判断是否在 PyInstaller 打包环境中运行 + if getattr(sys, "frozen", False): + bundle_dir = Path(sys._MEIPASS) + else: + bundle_dir = Path(__file__).parent + + # 切换到打包目录，确保所有相对路径能正确解析 + os.chdir(str(bundle_dir)) + + # 确保运行时目录存在（打包时可能为空目录导致不被包含） + (bundle_dir / "knowledge_base").mkdir(exist_ok=True) + + # 重写 argv 启动 Streamlit + # 注意：此应用将被嵌入桌面壳（Tauri）中运行，因此： + # - headless=true：不自动打开浏览器，由桌面壳接管 + # - port=8501：固定端口 + # - gatherUsageStats=false / developmentMode=false：关闭遥测与在线服务 + # - logger.level=error：静默启动，减少控制台输出 + sys.argv = [ + "streamlit", + "run", + "geo_tool.py", + "--server.port", "8501", + "--server.address", "127.0.0.1", + "--server.headless", "true", + "--browser.gatherUsageStats", "false", + "--global.developmentMode", "false", + "--logger.level", "error", + ] + + from streamlit.web.cli import main as streamlit_main + streamlit_main() + + +if __name__ == "__main__": + main() diff --git a/src-tauri/.gitignore b/src-tauri/.gitignore new file mode 100644 index 0000000..502406b --- /dev/null +++ b/src-tauri/.gitignore @@ -0,0 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z-Z#NVZ~k7(&o=lg*jNtqR^G}kt5mjL*sbWYE3WhW-D~ApZv1)e5FTE0{^~O;z^(lO zb{Z9dBQ{KRPl8Y)yHs?}w@C&XDfb08K@=4NK!*l|P#4AM%#yNe#3~|-%b|mkMfjR1seCoi?DE5+n0dikSY)(~K(n8h zfDn%VdVBj>); + +/// 等待指定端口可连接，最多等待 timeout_secs 秒 +fn wait_for_port(host: &str, port: u16, timeout_secs: u64) -> bool { + let start = std::time::Instant::now(); + while start.elapsed() < std::time::Duration::from_secs(timeout_secs) { + if std::net::TcpStream::connect((host, port)).is_ok() { + return true; + } + std::thread::sleep(std::time::Duration::from_millis(200)); + } + false +} + +/// 停止 Streamlit 子进程 +/// +/// - Unix: 先 SIGTERM（优雅退出），等待 3 秒无响应后 SIGKILL +/// - Windows: 直接 TerminateProcess +fn kill_streamlit(child: &mut Child) { + #[cfg(unix)] + { + // 先发 SIGTERM 请求优雅退出 + let _ = Command::new("kill") + .arg("-TERM") + .arg(child.id().to_string()) + .spawn(); + std::thread::sleep(std::time::Duration::from_secs(3)); + + // 尝试 wait（如果已退出则返回 Ok(Some(status))） + if let Ok(Some(_)) = child.try_wait() { + log::info!("Streamlit 进程已优雅退出"); + return; + } + log::warn!("Streamlit 进程未响应 SIGTERM，强制终止..."); + } + + // 强制终止 + let _ = child.kill(); + let _ = child.wait(); +} + +#[cfg_attr(mobile, tauri::mobile_entry_point)] +pub fn run() { + let app = tauri::Builder::default() + .setup(|app| { + if cfg!(debug_assertions) { + app.handle().plugin( + tauri_plugin_log::Builder::default() + .level(log::LevelFilter::Info) + .build(), + )?; + } + + let child = if cfg!(debug_assertions) { + // ── 开发模式 ── 使用系统安装的 streamlit ── + let manifest_dir = + std::path::PathBuf::from(env!("CARGO_MANIFEST_DIR")); + let project_root = manifest_dir.parent().unwrap_or(&manifest_dir); + let script_path = project_root.join("geo_tool.py"); + + log::info!( + "[开发模式] 启动 Streamlit: {:?}", + script_path + ); + + Command::new("streamlit") + .args([ + "run", + script_path.to_str().unwrap_or("geo_tool.py"), + "--server.port", + "8501", + "--server.address", + "127.0.0.1", + "--server.headless", + "true", + "--browser.gatherUsageStats", + "false", + "--logger.level", + "error", + ]) + .current_dir(project_root) + .stdout(Stdio::null()) + .stderr(Stdio::null()) + .spawn() + } else { + // ── 生产模式 ── 使用 PyInstaller 打包的独立可执行文件 ── + let resource_dir = app + .path() + .resource_dir() + .expect("无法获取资源目录"); + + let exe_name = if cfg!(target_os = "windows") { + "geo_tool_app.exe" + } else { + "geo_tool_app" + }; + let exe_path = resource_dir.join("_up_").join("dist").join(exe_name); + + log::info!( + "[生产模式] 启动打包应用: {:?}", + exe_path + ); + + let mut cmd = Command::new(&exe_path); + cmd.current_dir(&resource_dir) + .stdin(Stdio::null()) + .stdout(Stdio::null()) + .stderr(Stdio::null()); + + // Windows: 不显示控制台窗口 + #[cfg(target_os = "windows")] + { + use std::os::windows::process::CommandExt; + const CREATE_NO_WINDOW: u32 = 0x08000000u32; + cmd.creation_flags(CREATE_NO_WINDOW); + } + + cmd.spawn() + }; + + match child { + Ok(child) => { + log::info!("Streamlit 进程已启动 (PID: {})", child.id()); + app.manage(StreamlitProcess(Mutex::new(Some(child)))); + } + Err(e) => { + log::error!("启动 Streamlit 失败: {}", e); + eprintln!( + "错误：无法启动 Streamlit 服务。请确保已安装 streamlit。\n {}", + e + ); + } + } + + // 等待 Streamlit 就绪（最多 15 秒） + if !wait_for_port("127.0.0.1", 8501, 15) { + log::warn!("Streamlit 在 15 秒内未能就绪"); + } else { + log::info!("Streamlit 已就绪 (127.0.0.1:8501)"); + } + + Ok(()) + }) + .build(tauri::generate_context!()) + .expect("error while building tauri application"); + + app.run(|app_handle, event| { + // 窗口关闭 → 停止子进程 → 退出应用 + if let tauri::RunEvent::ExitRequested { .. } = event { + if let Some(state) = app_handle.try_state::() { + if let Ok(mut guard) = state.0.lock() { + if let Some(ref mut child) = *guard { + log::info!("正在停止 Streamlit 进程..."); + kill_streamlit(child); + log::info!("Streamlit 进程已停止"); + } + } + } + // 确保应用进程完全退出 + std::process::exit(0); + } + }); +} diff --git a/src-tauri/src/lib.rs.bak b/src-tauri/src/lib.rs.bak new file mode 100644 index 0000000..f438f39 --- /dev/null +++ b/src-tauri/src/lib.rs.bak @@ -0,0 +1,167 @@ +use std::process::{Child, Command, Stdio}; +use std::sync::Mutex; +use tauri::Manager; + +struct StreamlitProcess(Mutex>); + +/// 等待指定端口可连接，最多等待 timeout_secs 秒 +fn wait_for_port(host: &str, port: u16, timeout_secs: u64) -> bool { + let start = std::time::Instant::now(); + while start.elapsed() < std::time::Duration::from_secs(timeout_secs) { + if std::net::TcpStream::connect((host, port)).is_ok() { + return true; + } + std::thread::sleep(std::time::Duration::from_millis(200)); + } + false +} + +/// 停止 Streamlit 子进程 +/// +/// - Unix: 先 SIGTERM（优雅退出），等待 3 秒无响应后 SIGKILL +/// - Windows: 直接 TerminateProcess +fn kill_streamlit(child: &mut Child) { + #[cfg(unix)] + { + // 先发 SIGTERM 请求优雅退出 + let _ = Command::new("kill") + .arg("-TERM") + .arg(child.id().to_string()) + .spawn(); + std::thread::sleep(std::time::Duration::from_secs(3)); + + // 尝试 wait（如果已退出则返回 Ok(Some(status))） + if let Ok(Some(_)) = child.try_wait() { + log::info!("Streamlit 进程已优雅退出"); + return; + } + log::warn!("Streamlit 进程未响应 SIGTERM，强制终止..."); + } + + // 强制终止 + let _ = child.kill(); + let _ = child.wait(); +} + +#[cfg_attr(mobile, tauri::mobile_entry_point)] +pub fn run() { + let app = tauri::Builder::default() + .setup(|app| { + if cfg!(debug_assertions) { + app.handle().plugin( + tauri_plugin_log::Builder::default() + .level(log::LevelFilter::Info) + .build(), + )?; + } + + let child = if cfg!(debug_assertions) { + // ── 开发模式 ── 使用系统安装的 streamlit ── + let manifest_dir = + std::path::PathBuf::from(env!("CARGO_MANIFEST_DIR")); + let project_root = manifest_dir.parent().unwrap_or(&manifest_dir); + let script_path = project_root.join("geo_tool.py"); + + log::info!( + "[开发模式] 启动 Streamlit: {:?}", + script_path + ); + + Command::new("streamlit") + .args([ + "run", + script_path.to_str().unwrap_or("geo_tool.py"), + "--server.port", + "8501", + "--server.address", + "127.0.0.1", + "--server.headless", + "true", + "--browser.gatherUsageStats", + "false", + "--logger.level", + "error", + ]) + .current_dir(project_root) + .stdout(Stdio::null()) + .stderr(Stdio::null()) + .spawn() + } else { + // ── 生产模式 ── 使用 PyInstaller 打包的独立可执行文件 ── + let resource_dir = app + .path() + .resource_dir() + .expect("无法获取资源目录"); + + let exe_name = if cfg!(target_os = "windows") { + "geo_tool_app.exe" + } else { + "geo_tool_app" + }; + let exe_path = resource_dir.join(exe_name); + + log::info!( + "[生产模式] 启动打包应用: {:?}", + exe_path + ); + + let mut cmd = Command::new(&exe_path); + cmd.current_dir(&resource_dir) + .stdin(Stdio::null()) + .stdout(Stdio::null()) + .stderr(Stdio::null()); + + // Windows: 不显示控制台窗口 + #[cfg(target_os = "windows")] + { + use std::os::windows::process::CommandExt; + const CREATE_NO_WINDOW: u32 = 0x08000000u32; + cmd.creation_flags(CREATE_NO_WINDOW); + } + + cmd.spawn() + }; + + match child { + Ok(child) => { + log::info!("Streamlit 进程已启动 (PID: {})", child.id()); + app.manage(StreamlitProcess(Mutex::new(Some(child)))); + } + Err(e) => { + log::error!("启动 Streamlit 失败: {}", e); + eprintln!( + "错误：无法启动 Streamlit 服务。请确保已安装 streamlit。\n {}", + e + ); + } + } + + // 等待 Streamlit 就绪（最多 15 秒） + if !wait_for_port("127.0.0.1", 8501, 15) { + log::warn!("Streamlit 在 15 秒内未能就绪"); + } else { + log::info!("Streamlit 已就绪 (127.0.0.1:8501)"); + } + + Ok(()) + }) + .build(tauri::generate_context!()) + .expect("error while building tauri application"); + + app.run(|app_handle, event| { + // 窗口关闭 → 停止子进程 → 退出应用 + if let tauri::RunEvent::ExitRequested { .. } = event { + if let Some(state) = app_handle.try_state::() { + if let Ok(mut guard) = state.0.lock() { + if let Some(ref mut child) = *guard { + log::info!("正在停止 Streamlit 进程..."); + kill_streamlit(child); + log::info!("Streamlit 进程已停止"); + } + } + } + // 确保应用进程完全退出 + std::process::exit(0); + } + }); +} diff --git a/src-tauri/src/main.rs b/src-tauri/src/main.rs new file mode 100644 index 0000000..ad5fe83 --- /dev/null +++ b/src-tauri/src/main.rs @@ -0,0 +1,6 @@ +// Prevents additional console window on Windows in release, DO NOT REMOVE!! +#![cfg_attr(not(debug_assertions), windows_subsystem = "windows")] + +fn main() { + app_lib::run(); +} diff --git a/src-tauri/tauri.conf.json b/src-tauri/tauri.conf.json new file mode 100644 index 0000000..4d6a789 --- /dev/null +++ b/src-tauri/tauri.conf.json @@ -0,0 +1,41 @@ +{ + "$schema": "https://schema.tauri.app/config/2", + "productName": "\u4e11\u6a58GEO", + "version": "0.1.0", + "identifier": "com.pinesound.geo-tool", + "build": { + "frontendDist": "http://localhost:8501", + "devUrl": "http://localhost:8501" + }, + "app": { + "windows": [ + { + "title": "\u4e11\u6a58\u6587\u5316\u4f20\u5a92GEO\u5185\u5bb9\u4f18\u5316\u5e73\u53f0", + "width": 1400, + "height": 900, + "minWidth": 1000, + "minHeight": 700, + "resizable": true, + "fullscreen": false, + "center": true + } + ], + "security": { + "csp": null + } + }, + "bundle": { + "active": true, + 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