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| FROM tiangolo/uvicorn-gunicorn-fastapi:python3.12 | ||
| FROM python:3.12-slim | ||
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| # 设置工作目录 | ||
| WORKDIR /app | ||
| RUN apt-get update && apt-get install -y git ffmpeg && \ | ||
| apt-get clean && rm -rf /var/lib/apt/lists/* | ||
| RUN useradd -m -u 1000 user | ||
| USER user | ||
| ENV HOME=/home/user \ | ||
| PATH=/home/user/.local/bin:$PATH | ||
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| # 将当前目录内容复制到容器的 /app 中 | ||
| COPY . /app | ||
| # 设置工作目录 | ||
| WORKDIR $HOME/app | ||
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| # 安装项目依赖 | ||
| COPY --chown=user requirements.txt . | ||
| RUN pip install --no-cache-dir -r requirements.txt | ||
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| # 安装 FFmpeg | ||
| RUN apt-get update && apt-get install -y ffmpeg | ||
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| # 设置环境变量 | ||
| ENV FIREWORKS_API_KEY=${FIREWORKS_API_KEY} | ||
| COPY --chown=user . . | ||
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| # 暴露端口 8000 供应用使用 | ||
| EXPOSE 8000 | ||
| EXPOSE 7860 | ||
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| # 运行应用 | ||
| CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"] | ||
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| CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "7860"] |
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| --- | ||
| title: PodcastLM Backend | ||
| emoji: 👀 | ||
| colorFrom: gray | ||
| colorTo: green | ||
| sdk: docker | ||
| pinned: false | ||
| license: mit | ||
| --- | ||
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| Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference |
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| import os | ||
| import random | ||
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| from fastapi import APIRouter, Query | ||
| from constants import GRADIO_CACHE_DIR, MELO_TTS_LANGUAGE_MAPPING, SUNO_LANGUAGE_MAPPING | ||
| from utils import generate_podcast_audio, generate_script | ||
| from prompts import LANGUAGE_MODIFIER, LENGTH_MODIFIERS, QUESTION_MODIFIER, SYSTEM_PROMPT, TONE_MODIFIER | ||
| from schema import ShortDialogue | ||
| from loguru import logger | ||
| from pydub import AudioSegment | ||
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| from tempfile import NamedTemporaryFile | ||
| import uuid | ||
| from fastapi import APIRouter, BackgroundTasks, Form, HTTPException, UploadFile, File | ||
| from fastapi.responses import StreamingResponse, JSONResponse | ||
| import json | ||
| from typing import Dict, Optional | ||
| from utils import combine_audio, generate_dialogue, generate_podcast_info, generate_podcast_summary, get_pdf_text | ||
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| router = APIRouter() | ||
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| @router.get("/") | ||
| def generate(input: str = Query(..., description="Input string")): | ||
| random_voice_number = random.randint(1, 9) | ||
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| modified_system_prompt = SYSTEM_PROMPT | ||
| question = "introduce chatgpt" | ||
| tone = "funny" | ||
| language = "English" | ||
| length = "Short (1-2 min)" | ||
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| if question: | ||
| modified_system_prompt += f"\n\n{QUESTION_MODIFIER} {question}" | ||
| if tone: | ||
| modified_system_prompt += f"\n\n{TONE_MODIFIER} {tone}." | ||
| if length: | ||
| modified_system_prompt += f"\n\n{LENGTH_MODIFIERS[length]}" | ||
| if language: | ||
| modified_system_prompt += f"\n\n{LANGUAGE_MODIFIER} {language}." | ||
| @router.post("/generate_transcript") | ||
| async def generate_transcript( | ||
| pdfFile: Optional[UploadFile] = File(None), | ||
| textInput: str = Form(...), | ||
| tone: str = Form(...), | ||
| duration: str = Form(...), | ||
| language: str = Form(...), | ||
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| llm_output = generate_script(modified_system_prompt, "introduce chatgpt", ShortDialogue) | ||
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| logger.info(f"Generated dialogue: {llm_output}") | ||
| ): | ||
| pdfContent = await get_pdf_text(pdfFile) | ||
| new_text = pdfContent | ||
| return StreamingResponse(generate_dialogue(new_text,textInput, tone, duration, language), media_type="application/json") | ||
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| @router.get("/test") | ||
| def test(): | ||
| return {"message": "Hello World"} | ||
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| @router.post("/summarize") | ||
| async def get_summary( | ||
| textInput: str = Form(...), | ||
| tone: str = Form(...), | ||
| duration: str = Form(...), | ||
| language: str = Form(...), | ||
| pdfFile: Optional[UploadFile] = File(None) | ||
| ): | ||
| pdfContent = await get_pdf_text(pdfFile) | ||
| new_text = pdfContent | ||
| return StreamingResponse( | ||
| generate_podcast_summary( | ||
| new_text, | ||
| textInput, | ||
| tone, | ||
| duration, | ||
| language, | ||
| ), | ||
| media_type="application/json" | ||
| ) | ||
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| audio_segments = [] | ||
| transcript = "" | ||
| total_characters = 0 | ||
| @router.post("/pod_info") | ||
| async def get_pod_info( | ||
| textInput: str = Form(...), | ||
| tone: str = Form(...), | ||
| duration: str = Form(...), | ||
| language: str = Form(...), | ||
| pdfFile: Optional[UploadFile] = File(None) | ||
| ): | ||
| pdfContent = await get_pdf_text(pdfFile) | ||
| new_text = pdfContent[:100] | ||
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| return StreamingResponse(generate_podcast_info(new_text, textInput, tone, duration, language), media_type="application/json") | ||
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| for line in llm_output.dialogue: | ||
| print(f"Generating audio for {line.speaker}: {line.text}") | ||
| logger.info(f"Generating audio for {line.speaker}: {line.text}") | ||
| if line.speaker == "Host (Jane)": | ||
| speaker = f"**Host**: {line.text}" | ||
| else: | ||
| speaker = f"**{llm_output.name_of_guest}**: {line.text}" | ||
| transcript += speaker + "\n\n" | ||
| total_characters += len(line.text) | ||
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| language_for_tts = SUNO_LANGUAGE_MAPPING[language] | ||
| task_status: Dict[str, Dict] = {} | ||
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| # Get audio file path | ||
| audio_file_path = generate_podcast_audio( | ||
| line.text, line.speaker, language_for_tts, random_voice_number | ||
| ) | ||
| # Read the audio file into an AudioSegment | ||
| audio_segment = AudioSegment.from_file(audio_file_path) | ||
| audio_segments.append(audio_segment) | ||
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| # Concatenate all audio segments | ||
| combined_audio = sum(audio_segments) | ||
| @router.post("/generate_audio") | ||
| async def audio( | ||
| background_tasks: BackgroundTasks, | ||
| text: str = Form(...), | ||
| language: str = Form(...) | ||
| ): | ||
| task_id = str(uuid.uuid4()) | ||
| task_status[task_id] = {"status": "processing"} | ||
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| background_tasks.add_task(combine_audio, task_status, task_id, text, language) | ||
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| # Export the combined audio to a temporary file | ||
| temporary_directory = GRADIO_CACHE_DIR | ||
| os.makedirs(temporary_directory, exist_ok=True) | ||
| return JSONResponse(content={"task_id": task_id, "status": "processing"}) | ||
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| temporary_file = NamedTemporaryFile( | ||
| dir=temporary_directory, | ||
| delete=False, | ||
| suffix=".mp3", | ||
| ) | ||
| combined_audio.export(temporary_file.name, format="mp3") | ||
| logger.info(f"Generated {total_characters} characters of audio") | ||
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| # Delete any files in the temp directory that end with .mp3 and are over a day old | ||
| # for file in glob.glob(f"{temporary_directory}*.mp3"): | ||
| # if ( | ||
| # os.path.isfile(file) | ||
| # and time.time() - os.path.getmtime(file) > GRADIO_CLEAR_CACHE_OLDER_THAN | ||
| # ): | ||
| # os.remove(file) | ||
| @router.get("/audio_status/{task_id}") | ||
| async def get_audio_status(task_id: str): | ||
| if task_id not in task_status: | ||
| raise HTTPException(status_code=404, detail="Task not found") | ||
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| status = task_status[task_id] | ||
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| if status["status"] == "completed": | ||
| return JSONResponse(content={ | ||
| "status": "completed", | ||
| "audio_url": status["audio_url"] | ||
| }) | ||
| elif status["status"] == "failed": | ||
| return JSONResponse(content={ | ||
| "status": "failed", | ||
| "error": status["error"] | ||
| }) | ||
| else: | ||
| return JSONResponse(content={ | ||
| "status": "processing" | ||
| }) | ||
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| print(temporary_file.name) | ||
| print(transcript) | ||
| return {"message": f"Hello World, input: {temporary_file}"} | ||
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