feat: 添加播客生成器Web应用基础架构
实现基于Next.js的播客生成器Web应用，包含以下主要功能： - 完整的Next.js项目结构配置 - 播客生成API接口 - 音频文件服务API - TTS配置管理 - 响应式UI组件 - 本地存储和状态管理 - 音频可视化组件 - 全局样式和主题配置 新增配置文件包括： - Next.js、Tailwind CSS、ESLint等工具配置 - 环境变量示例文件 - 启动脚本和构建检查脚本 - 类型定义和工具函数库
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hex2077
118
main.py
118
main.py
@@ -1,5 +1,5 @@
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from fastapi import FastAPI, Request, HTTPException, Depends, Form, Header
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from fastapi.responses import FileResponse, JSONResponse
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from fastapi.responses import FileResponse, JSONResponse, StreamingResponse
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from typing import Optional, Dict
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import uuid
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import asyncio
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@@ -13,10 +13,14 @@ import json
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import argparse
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from enum import Enum
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import shutil
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from PIL import Image, ImageDraw
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import random
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import schedule
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import threading
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from contextlib import asynccontextmanager # 导入 asynccontextmanager
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import httpx # 导入 httpx 库
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from io import BytesIO # 导入 BytesIO
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import base64 # 导入 base64
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from podcast_generator import generate_podcast_audio_api
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@@ -155,7 +159,9 @@ async def _generate_podcast_task(
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podUsers_json_content: str,
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threads: int,
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tts_provider: str,
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callback_url: Optional[str] = None # 新增回调地址参数
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callback_url: Optional[str] = None, # 新增回调地址参数
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output_language: Optional[str] = None,
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usetime: Optional[str] = None,
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):
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task_results[auth_id][task_id]["status"] = TaskStatus.RUNNING
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try:
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@@ -164,6 +170,8 @@ async def _generate_podcast_task(
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parser.add_argument("--base-url", default=base_url, help="OpenAI API base URL (default: https://api.openai.com/v1).")
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parser.add_argument("--model", default=model, help="OpenAI model to use (default: gpt-3.5-turbo).")
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parser.add_argument("--threads", type=int, default=threads, help="Number of threads to use for audio generation (default: 1).")
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parser.add_argument("--output-language", default=output_language, help="Output language for the podcast script (default: Chinese).")
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parser.add_argument("--usetime", default=usetime, help="Time duration for the podcast script (default: 10 minutes).")
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args = parser.parse_args([])
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actual_config_path = tts_provider_map.get(tts_provider)
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@@ -181,6 +189,11 @@ async def _generate_podcast_task(
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task_results[auth_id][task_id]["status"] = TaskStatus.COMPLETED
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task_results[auth_id][task_id].update(podcast_generation_results)
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print(f"\nPodcast generation completed for task {task_id}. Output file: {podcast_generation_results.get('output_audio_filepath')}")
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# 生成并编码像素头像
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avatar_bytes = generate_pixel_avatar(str(task_id)) # 使用 task_id 作为种子
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avatar_base64 = base64.b64encode(avatar_bytes).decode('utf-8')
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task_results[auth_id][task_id]["avatar_base64"] = avatar_base64 # 存储 Base64 编码的头像数据
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except Exception as e:
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task_results[auth_id][task_id]["status"] = TaskStatus.FAILED
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task_results[auth_id][task_id]["result"] = str(e)
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@@ -231,7 +244,9 @@ async def generate_podcast_submission(
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podUsers_json_content: str = Form(...),
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threads: int = Form(1),
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tts_provider: str = Form("index-tts"),
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callback_url: Optional[str] = Form(None) # 新增回调地址参数
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callback_url: Optional[str] = Form(None),
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output_language: Optional[str] = Form(None),
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usetime: Optional[str] = Form(None),
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):
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# 1. 验证 tts_provider
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if tts_provider not in tts_provider_map:
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@@ -265,7 +280,9 @@ async def generate_podcast_submission(
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podUsers_json_content,
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threads,
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tts_provider,
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callback_url # 传递回调地址
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callback_url,
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output_language,
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usetime
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)
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return {"message": "Podcast generation started.", "task_id": task_id}
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@@ -287,6 +304,10 @@ async def get_podcast_status(
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"output_audio_filepath": task_info.get("output_audio_filepath"),
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"overview_content": task_info.get("overview_content"),
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"podcast_script": task_info.get("podcast_script"),
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"avatar_base64": task_info.get("avatar_base64"), # 添加 Base64 编码的头像数据
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"audio_duration": task_info.get("audio_duration"),
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"title": task_info.get("title"),
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"tags": task_info.get("tags"),
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"error": task_info["result"] if task_info["status"] == TaskStatus.FAILED else None,
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"timestamp": task_info["timestamp"]
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})
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@@ -299,6 +320,14 @@ async def download_podcast(file_name: str):
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raise HTTPException(status_code=404, detail="File not found.")
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return FileResponse(file_path, media_type='audio/mpeg', filename=file_name)
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@app.get("/avatar/{username}")
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async def get_avatar(username: str):
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"""
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根据用户名生成并返回一个像素头像。
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"""
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avatar_bytes = generate_pixel_avatar(username)
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return StreamingResponse(BytesIO(avatar_bytes), media_type="image/png")
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@app.get("/get-voices")
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async def get_voices(tts_provider: str = "tts"):
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config_path = tts_provider_map.get(tts_provider)
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@@ -325,6 +354,87 @@ async def get_voices(tts_provider: str = "tts"):
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async def read_root():
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return {"message": "FastAPI server is running!"}
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def generate_pixel_avatar(seed_string: str) -> bytes:
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"""
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根据给定的字符串生成一个48x48像素的像素头像。
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头像具有确定性（相同输入字符串生成相同头像）和对称性。
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"""
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size = 48
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pixel_grid_size = 5 # 内部像素网格大小 (例如 5x5)
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# 使用SHA256哈希作为随机种子，确保确定性
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hash_object = hashlib.sha256(seed_string.encode('utf-8'))
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hash_hex = hash_object.hexdigest()
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# 将哈希值转换为整数，作为随机数生成器的种子
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random.seed(int(hash_hex, 16))
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# 创建一个空白的48x48 RGBA图像
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img = Image.new('RGBA', (size, size), (255, 255, 255, 0)) # 透明背景
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draw = ImageDraw.Draw(img)
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# 随机生成头像的主颜色 (饱和度较高，亮度适中)
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hue = random.randint(0, 360)
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saturation = random.randint(70, 100) # 高饱和度
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lightness = random.randint(40, 60) # 适中亮度
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# 将HSL转换为RGB
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def hsl_to_rgb(h, s, l):
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h /= 360
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s /= 100
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l /= 100
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if s == 0:
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return (int(l * 255), int(l * 255), int(l * 255), 255)
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def hue_to_rgb(p, q, t):
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if t < 0: t += 1
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if t > 1: t -= 1
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if t < 1/6: return p + (q - p) * 6 * t
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if t < 1/2: return q
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if t < 2/3: return p + (q - p) * (2/3 - t) * 6
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return p
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q = l * (1 + s) if l < 0.5 else l + s - l * s
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p = 2 * l - q
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r = hue_to_rgb(p, q, h + 1/3)
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g = hue_to_rgb(p, q, h)
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b = hue_to_rgb(p, q, h - 1/3)
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return (int(r * 255), int(g * 255), int(b * 255), 255)
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main_color = hsl_to_rgb(hue, saturation, lightness)
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# 生成像素网格
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# 只需生成一半的网格，然后对称复制
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pixels = [[0 for _ in range(pixel_grid_size)] for _ in range(pixel_grid_size)]
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for y in range(pixel_grid_size):
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for x in range((pixel_grid_size + 1) // 2): # 只生成左半部分或中间列
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if random.random() > 0.5: # 50% 的几率填充像素
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pixels[y][x] = 1 # 填充
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pixels[y][pixel_grid_size - 1 - x] = 1 # 对称填充
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# 计算每个内部像素在最终图像中的大小
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pixel_width = size // pixel_grid_size
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pixel_height = size // pixel_grid_size
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# 绘制像素
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for y in range(pixel_grid_size):
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for x in range(pixel_grid_size):
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if pixels[y][x] == 1:
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draw.rectangle(
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[x * pixel_width, y * pixel_height, (x + 1) * pixel_width, (y + 1) * pixel_height],
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fill=main_color
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)
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# 将图像转换为字节流
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from io import BytesIO
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byte_io = BytesIO()
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img.save(byte_io, format='PNG')
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return byte_io.getvalue()
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def run_scheduler():
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"""在循环中运行调度器，直到设置停止事件。"""
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while not stop_scheduler_event.is_set():
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