mirror of
https://github.com/bytedance/deer-flow.git
synced 2026-06-10 09:25:57 +00:00
feat: MiniMax provider for image/video/podcast skills + new music-generation skill (#3437)
* docs(spec): MiniMax integration for generation skills + new music skill Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * docs(plan): MiniMax generation providers implementation plan Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * test(skills): add importlib loader + FakeResp for skill tests * test(skills): register loaded module in sys.modules; raise requests.HTTPError in FakeResp * feat(image-generation): add MiniMax provider with env auto-detect Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(image-generation): guard unknown provider, derive ref MIME, strengthen tests Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(video-generation): add MiniMax provider with async poll/download Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(video-generation): surface base_resp errors while polling; add timeout test * feat(podcast-generation): add MiniMax t2a_v2 provider with env auto-detect Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * refactor(podcast-generation): restore TTS credential guard; add volcengine + voice tests Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * feat(music-generation): new MiniMax music skill via skill-creator Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * refactor(music-generation): treat empty lyrics as absent; test no-audio-data path * refactor(skills): add request timeouts to MiniMax network calls Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * Potential fix for pull request finding 'Explicit returns mixed with implicit (fall through) returns' Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com> * fix(models): strip inconsistent user-message names for MiniMax chat DeerFlow middlewares tag user messages with provenance names (user-input, summary, loop_warning); langchain serializes them into the OpenAI-compatible payload and MiniMax rejects mismatched user-message names with "user name must be consistent (2013)". PatchedChatMiniMax now drops the per-message name from user-role messages. Point the config.example MiniMax models at PatchedChatMiniMax so they also get reasoning_content mapping. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(image-generation): MiniMax sends JSON prompt field, guard 1500-char limit MiniMax image-01 takes one text string capped at 1500 chars, but the skill was sending the whole structured JSON. The MiniMax provider now extracts the JSON `prompt` field (relying on prompt_optimizer to expand it) and fails fast with a clear error before calling the API when that field exceeds 1500 chars. Authoring stays provider-agnostic; Gemini still receives the full JSON. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * feat(podcast-generation): per-provider TTS concurrency and retry/backoff Each TTS provider owns its concurrency internally — MiniMax runs single-threaded to reduce rate-limit failures, Volcengine keeps 4 workers — with automatic retry and backoff on transient HTTP and base_resp errors. No caller-facing concurrency knob. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(skills): address Copilot review comments on generation skills - video: add raise_for_status + timeout to the Gemini download/POST/poll calls so non-2xx responses surface as clear HTTP errors instead of JSON/KeyError or hangs - video: check the task Fail status before the generic base_resp check so the failure keeps its task_id context - video/image: create the output file parent directory before writing (matching music-generation) so nested output paths do not raise FileNotFoundError - music: require a non-empty prompt and fail fast with ValueError instead of sending an empty prompt to the API Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(scripts): reclaim dev ports across worktrees in make stop/dev All deer-flow worktrees (main checkout + linked worktrees) hardcode the same dev ports (8001/3000/2026), so a service started from any worktree must be reclaimable from another. stop_all now resolves the set of worktree roots (DEERFLOW_ROOTS) and treats a process as deer-flow-owned when its open files live under any of them. It also force-kills survivors on 2026 alongside 8001/3000, fixing `make dev` aborting on the nginx port preflight when a prior nginx lingered on 2026. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(view-image): hide the injected image-context message from the UI ViewImageMiddleware injects a HumanMessage (text + base64 images) so the vision model can see viewed images, but it was the only internal injector that set neither hide_from_ui nor a hidden name, so it leaked into the chat UI (and IM channels) as a user bubble reading "Here are the images you've viewed:". Mark it with additional_kwargs={"hide_from_ui": True}, matching todo/dynamic_context injections, which the frontend isHiddenFromUIMessage and the channel sender already honor. The model still receives the full content. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> * fix(minimax): mark M2.7 models as text-only (no vision) MiniMax M2.7 / M2.7-highspeed do not support vision; only M3 does. The provider config asserted vision support for M2.7 in four places. - config.example.yaml: 4 M2.7 entries -> supports_vision: false - backend/docs/CONFIGURATION.md: M2.7 + highspeed -> supports_vision: false - wizard: add LLMProvider.model_vision_overrides + extra_config_for() so selecting an M2.7 model writes supports_vision: false while M3 (default) keeps vision; wire it through setup_wizard.py - tests: M2.7-highspeed fixture -> supports_vision=False; add test_minimax_vision_is_per_model Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> --------- Co-authored-by: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Co-authored-by: Willem Jiang <willem.jiang@gmail.com> Co-authored-by: Copilot Autofix powered by AI <223894421+github-code-quality[bot]@users.noreply.github.com>
This commit is contained in:
DanielWalnut
@@ -3,6 +3,8 @@ import base64
|
||||
import json
|
||||
import logging
|
||||
import os
|
||||
import random
|
||||
import time
|
||||
import uuid
|
||||
from concurrent.futures import ThreadPoolExecutor, as_completed
|
||||
from typing import Literal, Optional
|
||||
@@ -12,8 +14,14 @@ import requests
|
||||
logging.basicConfig(level=logging.INFO)
|
||||
logger = logging.getLogger(__name__)
|
||||
|
||||
MINIMAX_DEFAULT_HOST = "https://api.minimaxi.com"
|
||||
# MiniMax base_resp codes worth retrying: unknown, timeout, RPM limit, TPM limit.
|
||||
MINIMAX_RETRYABLE_CODES = {1000, 1001, 1002, 1039}
|
||||
DEFAULT_TTS_MAX_RETRIES = 4
|
||||
DEFAULT_MAX_WORKERS = 4
|
||||
DEFAULT_MINIMAX_MAX_WORKERS = 1
|
||||
|
||||
|
||||
# Types
|
||||
class ScriptLine:
|
||||
def __init__(self, speaker: Literal["male", "female"] = "male", paragraph: str = ""):
|
||||
self.speaker = speaker
|
||||
@@ -30,113 +38,243 @@ class Script:
|
||||
script = cls(locale=data.get("locale", "en"))
|
||||
for line in data.get("lines", []):
|
||||
script.lines.append(
|
||||
ScriptLine(
|
||||
speaker=line.get("speaker", "male"),
|
||||
paragraph=line.get("paragraph", ""),
|
||||
)
|
||||
ScriptLine(speaker=line.get("speaker", "male"),
|
||||
paragraph=line.get("paragraph", ""))
|
||||
)
|
||||
return script
|
||||
|
||||
|
||||
def text_to_speech(text: str, voice_type: str) -> Optional[bytes]:
|
||||
"""Convert text to speech using Volcengine TTS."""
|
||||
def _resolve_provider(override_env: str, existing_provider: str, has_existing_creds: bool) -> str:
|
||||
override = os.getenv(override_env)
|
||||
if override:
|
||||
return override.strip().lower()
|
||||
if has_existing_creds:
|
||||
return existing_provider
|
||||
if os.getenv("MINIMAX_API_KEY"):
|
||||
return "minimax"
|
||||
raise ValueError(
|
||||
f"No credentials found. Set VOLCENGINE_TTS_APPID + VOLCENGINE_TTS_ACCESS_TOKEN "
|
||||
f"for {existing_provider}, or MINIMAX_API_KEY for minimax "
|
||||
f"(optionally force with {override_env})."
|
||||
)
|
||||
|
||||
|
||||
def _resolve_tts_provider() -> str:
|
||||
has_volc = bool(
|
||||
os.getenv("VOLCENGINE_TTS_APPID") and os.getenv("VOLCENGINE_TTS_ACCESS_TOKEN")
|
||||
)
|
||||
provider = _resolve_provider("PODCAST_GENERATION_PROVIDER", "volcengine", has_volc)
|
||||
if provider not in ("volcengine", "minimax"):
|
||||
raise ValueError(
|
||||
f"Unknown podcast provider: {provider!r} (use 'volcengine' or 'minimax')"
|
||||
)
|
||||
return provider
|
||||
|
||||
|
||||
def _default_max_retries() -> int:
|
||||
try:
|
||||
return int(os.getenv("MINIMAX_TTS_MAX_RETRIES", str(DEFAULT_TTS_MAX_RETRIES)))
|
||||
except ValueError:
|
||||
return DEFAULT_TTS_MAX_RETRIES
|
||||
|
||||
|
||||
def _default_max_workers(provider: str) -> int:
|
||||
"""Each provider owns its own concurrency: MiniMax stays low to avoid rate
|
||||
limits, Volcengine keeps the historical default. Not user-tunable by design.
|
||||
"""
|
||||
if provider == "minimax":
|
||||
return DEFAULT_MINIMAX_MAX_WORKERS
|
||||
return DEFAULT_MAX_WORKERS
|
||||
|
||||
|
||||
def _parse_retry_after(response) -> Optional[float]:
|
||||
"""Return the server-provided Retry-After (seconds), if any."""
|
||||
headers = getattr(response, "headers", None) or {}
|
||||
value = headers.get("Retry-After")
|
||||
try:
|
||||
return float(value) if value else None
|
||||
except (TypeError, ValueError):
|
||||
return None
|
||||
|
||||
|
||||
def _backoff_sleep(attempt: int, retry_after: Optional[float]) -> None:
|
||||
"""Sleep with exponential backoff + jitter, honoring Retry-After when present.
|
||||
|
||||
Jitter de-synchronizes concurrent workers that all got rate-limited at once,
|
||||
avoiding a thundering-herd retry storm.
|
||||
"""
|
||||
base = retry_after if retry_after else min(2 ** attempt, 30)
|
||||
time.sleep(base + random.uniform(0, 1))
|
||||
|
||||
|
||||
def text_to_speech_volcengine(
|
||||
text: str, voice_type: str, max_retries: Optional[int] = None
|
||||
) -> Optional[bytes]:
|
||||
"""Convert text to speech using Volcengine TTS (returns base64-decoded mp3 bytes).
|
||||
|
||||
Retries with exponential backoff on transient HTTP errors (429 / 5xx).
|
||||
"""
|
||||
app_id = os.getenv("VOLCENGINE_TTS_APPID")
|
||||
access_token = os.getenv("VOLCENGINE_TTS_ACCESS_TOKEN")
|
||||
cluster = os.getenv("VOLCENGINE_TTS_CLUSTER", "volcano_tts")
|
||||
|
||||
if not app_id or not access_token:
|
||||
raise ValueError(
|
||||
"VOLCENGINE_TTS_APPID and VOLCENGINE_TTS_ACCESS_TOKEN environment variables must be set"
|
||||
)
|
||||
|
||||
if max_retries is None:
|
||||
max_retries = _default_max_retries()
|
||||
url = "https://openspeech.bytedance.com/api/v1/tts"
|
||||
|
||||
# Authentication: Bearer token with semicolon separator
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer;{access_token}",
|
||||
}
|
||||
|
||||
headers = {"Content-Type": "application/json", "Authorization": f"Bearer;{access_token}"}
|
||||
payload = {
|
||||
"app": {
|
||||
"appid": app_id,
|
||||
"token": "access_token", # literal string, not the actual token
|
||||
"cluster": cluster,
|
||||
},
|
||||
"app": {"appid": app_id, "token": "access_token", "cluster": cluster},
|
||||
"user": {"uid": "podcast-generator"},
|
||||
"audio": {
|
||||
"voice_type": voice_type,
|
||||
"encoding": "mp3",
|
||||
"speed_ratio": 1.2,
|
||||
},
|
||||
"request": {
|
||||
"reqid": str(uuid.uuid4()), # must be unique UUID
|
||||
"text": text,
|
||||
"text_type": "plain",
|
||||
"operation": "query",
|
||||
},
|
||||
"audio": {"voice_type": voice_type, "encoding": "mp3", "speed_ratio": 1.2},
|
||||
"request": {"reqid": str(uuid.uuid4()), "text": text,
|
||||
"text_type": "plain", "operation": "query"},
|
||||
}
|
||||
|
||||
try:
|
||||
response = requests.post(url, json=payload, headers=headers)
|
||||
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
response = requests.post(url, json=payload, headers=headers, timeout=60)
|
||||
except Exception as e:
|
||||
logger.error(f"TTS error: {e}")
|
||||
if attempt < max_retries:
|
||||
_backoff_sleep(attempt, None)
|
||||
continue
|
||||
return None
|
||||
if response.status_code == 429 or response.status_code >= 500:
|
||||
logger.warning(
|
||||
f"Volcengine TTS transient HTTP {response.status_code} "
|
||||
f"(attempt {attempt + 1}/{max_retries + 1})"
|
||||
)
|
||||
if attempt < max_retries:
|
||||
_backoff_sleep(attempt, _parse_retry_after(response))
|
||||
continue
|
||||
return None
|
||||
if response.status_code != 200:
|
||||
logger.error(f"TTS API error: {response.status_code} - {response.text}")
|
||||
return None
|
||||
|
||||
result = response.json()
|
||||
if result.get("code") != 3000:
|
||||
logger.error(f"TTS error: {result.get('message')} (code: {result.get('code')})")
|
||||
return None
|
||||
|
||||
audio_data = result.get("data")
|
||||
if audio_data:
|
||||
return base64.b64decode(audio_data)
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"TTS error: {str(e)}")
|
||||
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def _process_line(args: tuple[int, ScriptLine, int]) -> tuple[int, Optional[bytes]]:
|
||||
def text_to_speech_minimax(
|
||||
text: str, voice_id: str, max_retries: Optional[int] = None
|
||||
) -> Optional[bytes]:
|
||||
"""Convert text to speech using MiniMax t2a_v2 (returns hex-decoded mp3 bytes).
|
||||
|
||||
Retries with exponential backoff on HTTP 429/5xx and on retryable base_resp
|
||||
codes (rate/TPM limits, timeouts). Permanent errors (auth, balance, bad input)
|
||||
are not retried.
|
||||
"""
|
||||
api_key = os.getenv("MINIMAX_API_KEY")
|
||||
host = os.getenv("MINIMAX_API_HOST", MINIMAX_DEFAULT_HOST).rstrip("/")
|
||||
if max_retries is None:
|
||||
max_retries = _default_max_retries()
|
||||
payload = {
|
||||
"model": os.getenv("MINIMAX_TTS_MODEL", "speech-2.6-hd"),
|
||||
"text": text,
|
||||
"voice_setting": {"voice_id": voice_id, "speed": 1.0, "vol": 1.0, "pitch": 0},
|
||||
"audio_setting": {"sample_rate": 32000, "bitrate": 128000, "format": "mp3", "channel": 1},
|
||||
"output_format": "hex",
|
||||
}
|
||||
for attempt in range(max_retries + 1):
|
||||
try:
|
||||
response = requests.post(
|
||||
f"{host}/v1/t2a_v2",
|
||||
headers={"Authorization": f"Bearer {api_key}", "Content-Type": "application/json"},
|
||||
json=payload,
|
||||
timeout=60,
|
||||
)
|
||||
except Exception as e:
|
||||
logger.error(f"MiniMax TTS error: {e}")
|
||||
if attempt < max_retries:
|
||||
_backoff_sleep(attempt, None)
|
||||
continue
|
||||
return None
|
||||
if response.status_code == 429 or response.status_code >= 500:
|
||||
logger.warning(
|
||||
f"MiniMax TTS rate-limited HTTP {response.status_code} "
|
||||
f"(attempt {attempt + 1}/{max_retries + 1})"
|
||||
)
|
||||
if attempt < max_retries:
|
||||
_backoff_sleep(attempt, _parse_retry_after(response))
|
||||
continue
|
||||
return None
|
||||
if response.status_code != 200:
|
||||
logger.error(f"MiniMax TTS error: {response.status_code} - {response.text}")
|
||||
return None
|
||||
result = response.json()
|
||||
base = result.get("base_resp") or {}
|
||||
code = base.get("status_code", 0)
|
||||
if code in MINIMAX_RETRYABLE_CODES:
|
||||
logger.warning(
|
||||
f"MiniMax TTS retryable error {code}: {base.get('status_msg')} "
|
||||
f"(attempt {attempt + 1}/{max_retries + 1})"
|
||||
)
|
||||
if attempt < max_retries:
|
||||
_backoff_sleep(attempt, None)
|
||||
continue
|
||||
return None
|
||||
if code != 0:
|
||||
logger.error(f"MiniMax TTS error {code}: {base.get('status_msg')}")
|
||||
return None
|
||||
audio_hex = (result.get("data") or {}).get("audio")
|
||||
if audio_hex:
|
||||
return bytes.fromhex(audio_hex)
|
||||
return None
|
||||
return None
|
||||
|
||||
|
||||
def _process_line(args: tuple[int, ScriptLine, int, str]) -> tuple[int, Optional[bytes]]:
|
||||
"""Process a single script line for TTS. Returns (index, audio_bytes)."""
|
||||
i, line, total = args
|
||||
|
||||
# Select voice based on speaker gender
|
||||
if line.speaker == "male":
|
||||
voice_type = "zh_male_yangguangqingnian_moon_bigtts" # Male voice
|
||||
i, line, total, provider = args
|
||||
logger.info(f"Processing line {i + 1}/{total} ({line.speaker}) via {provider}")
|
||||
if provider == "minimax":
|
||||
if line.speaker == "male":
|
||||
voice = os.getenv("MINIMAX_TTS_VOICE_MALE", "male-qn-qingse")
|
||||
else:
|
||||
voice = os.getenv("MINIMAX_TTS_VOICE_FEMALE", "female-tianmei")
|
||||
audio = text_to_speech_minimax(line.paragraph, voice)
|
||||
else:
|
||||
voice_type = "zh_female_sajiaonvyou_moon_bigtts" # Female voice
|
||||
|
||||
logger.info(f"Processing line {i + 1}/{total} ({line.speaker})")
|
||||
audio = text_to_speech(line.paragraph, voice_type)
|
||||
|
||||
if line.speaker == "male":
|
||||
voice = "zh_male_yangguangqingnian_moon_bigtts"
|
||||
else:
|
||||
voice = "zh_female_sajiaonvyou_moon_bigtts"
|
||||
audio = text_to_speech_volcengine(line.paragraph, voice)
|
||||
if not audio:
|
||||
logger.warning(f"Failed to generate audio for line {i + 1}")
|
||||
|
||||
return (i, audio)
|
||||
|
||||
|
||||
def tts_node(script: Script, max_workers: int = 4) -> list[bytes]:
|
||||
"""Convert script lines to audio chunks using TTS with multi-threading."""
|
||||
logger.info(f"Converting script to audio using {max_workers} workers...")
|
||||
def tts_node(script: Script) -> list[bytes]:
|
||||
"""Convert script lines to audio chunks using TTS with multi-threading.
|
||||
|
||||
Concurrency is owned by the resolved provider (see _default_max_workers);
|
||||
there is no caller-facing knob. Fails loudly: if any line cannot be
|
||||
synthesized (even after retries), raise rather than silently emitting an
|
||||
incomplete podcast.
|
||||
"""
|
||||
total = len(script.lines)
|
||||
|
||||
# Handle empty script case
|
||||
if total == 0:
|
||||
raise ValueError("Script contains no lines to process")
|
||||
|
||||
# Validate required environment variables before starting TTS
|
||||
if not os.getenv("VOLCENGINE_TTS_APPID") or not os.getenv("VOLCENGINE_TTS_ACCESS_TOKEN"):
|
||||
provider = _resolve_tts_provider()
|
||||
max_workers = _default_max_workers(provider)
|
||||
if provider == "volcengine" and not (
|
||||
os.getenv("VOLCENGINE_TTS_APPID") and os.getenv("VOLCENGINE_TTS_ACCESS_TOKEN")
|
||||
):
|
||||
raise ValueError(
|
||||
"Missing required environment variables: VOLCENGINE_TTS_APPID and VOLCENGINE_TTS_ACCESS_TOKEN must be set"
|
||||
"Volcengine TTS selected but VOLCENGINE_TTS_APPID / "
|
||||
"VOLCENGINE_TTS_ACCESS_TOKEN are not set"
|
||||
)
|
||||
if provider == "minimax" and not os.getenv("MINIMAX_API_KEY"):
|
||||
raise ValueError("MiniMax TTS selected but MINIMAX_API_KEY is not set")
|
||||
logger.info(f"Converting script to audio using {max_workers} workers (provider={provider})...")
|
||||
tasks = [(i, line, total, provider) for i, line in enumerate(script.lines)]
|
||||
|
||||
tasks = [(i, line, total) for i, line in enumerate(script.lines)]
|
||||
|
||||
# Use ThreadPoolExecutor for parallel TTS generation
|
||||
results: dict[int, Optional[bytes]] = {}
|
||||
failed_indices: list[int] = []
|
||||
with ThreadPoolExecutor(max_workers=max_workers) as executor:
|
||||
@@ -144,81 +282,52 @@ def tts_node(script: Script, max_workers: int = 4) -> list[bytes]:
|
||||
for future in as_completed(futures):
|
||||
idx, audio = future.result()
|
||||
results[idx] = audio
|
||||
# Use `not audio` to catch both None and empty bytes
|
||||
if not audio:
|
||||
failed_indices.append(idx)
|
||||
|
||||
# Log failed lines with 1-based indices for user-friendly output
|
||||
if failed_indices:
|
||||
logger.warning(
|
||||
f"Failed to generate audio for {len(failed_indices)}/{total} lines: "
|
||||
f"line numbers {sorted(i + 1 for i in failed_indices)}"
|
||||
)
|
||||
|
||||
# Collect results in order, skipping failed ones
|
||||
audio_chunks = []
|
||||
for i in range(total):
|
||||
audio = results.get(i)
|
||||
if audio:
|
||||
audio_chunks.append(audio)
|
||||
|
||||
logger.info(f"Generated {len(audio_chunks)}/{total} audio chunks successfully")
|
||||
|
||||
if not audio_chunks:
|
||||
raise ValueError(
|
||||
f"TTS generation failed for all {total} lines. "
|
||||
"Please check VOLCENGINE_TTS_APPID and VOLCENGINE_TTS_ACCESS_TOKEN environment variables."
|
||||
f"TTS failed for {len(failed_indices)}/{total} lines after retries: "
|
||||
f"line numbers {sorted(i + 1 for i in failed_indices)}. "
|
||||
f"This is usually transient API rate limiting — wait a moment and retry."
|
||||
)
|
||||
|
||||
|
||||
audio_chunks = [results[i] for i in range(total)]
|
||||
logger.info(f"Generated {len(audio_chunks)}/{total} audio chunks successfully")
|
||||
return audio_chunks
|
||||
|
||||
|
||||
def mix_audio(audio_chunks: list[bytes]) -> bytes:
|
||||
"""Combine audio chunks into a single audio file."""
|
||||
logger.info("Mixing audio chunks...")
|
||||
|
||||
if not audio_chunks:
|
||||
raise ValueError("No audio chunks to mix - TTS generation may have failed")
|
||||
|
||||
output = b"".join(audio_chunks)
|
||||
|
||||
if len(output) == 0:
|
||||
raise ValueError("Mixed audio is empty - TTS generation may have failed")
|
||||
|
||||
logger.info(f"Audio mixing complete: {len(output)} bytes")
|
||||
return output
|
||||
|
||||
|
||||
def generate_markdown(script: Script, title: str = "Podcast Script") -> str:
|
||||
"""Generate a markdown script from the podcast script."""
|
||||
lines = [f"# {title}", ""]
|
||||
|
||||
for line in script.lines:
|
||||
speaker_name = "**Host (Male)**" if line.speaker == "male" else "**Host (Female)**"
|
||||
lines.append(f"{speaker_name}: {line.paragraph}")
|
||||
lines.append("")
|
||||
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def generate_podcast(
|
||||
script_file: str,
|
||||
output_file: str,
|
||||
transcript_file: Optional[str] = None,
|
||||
) -> str:
|
||||
"""Generate a podcast from a script JSON file."""
|
||||
|
||||
# Read script JSON
|
||||
def generate_podcast(script_file: str, output_file: str,
|
||||
transcript_file: Optional[str] = None) -> str:
|
||||
with open(script_file, "r", encoding="utf-8") as f:
|
||||
script_json = json.load(f)
|
||||
|
||||
if "lines" not in script_json:
|
||||
raise ValueError(f"Invalid script format: missing 'lines' key. Got keys: {list(script_json.keys())}")
|
||||
|
||||
raise ValueError(
|
||||
f"Invalid script format: missing 'lines' key. Got keys: {list(script_json.keys())}"
|
||||
)
|
||||
script = Script.from_dict(script_json)
|
||||
logger.info(f"Loaded script with {len(script.lines)} lines")
|
||||
|
||||
# Generate transcript markdown if requested
|
||||
if transcript_file:
|
||||
title = script_json.get("title", "Podcast Script")
|
||||
markdown_content = generate_markdown(script, title)
|
||||
@@ -229,16 +338,11 @@ def generate_podcast(
|
||||
f.write(markdown_content)
|
||||
logger.info(f"Generated transcript to {transcript_file}")
|
||||
|
||||
# Convert to audio
|
||||
audio_chunks = tts_node(script)
|
||||
|
||||
if not audio_chunks:
|
||||
raise Exception("Failed to generate any audio")
|
||||
|
||||
# Mix audio
|
||||
output_audio = mix_audio(audio_chunks)
|
||||
|
||||
# Save output
|
||||
output_dir = os.path.dirname(output_file)
|
||||
if output_dir:
|
||||
os.makedirs(output_dir, exist_ok=True)
|
||||
@@ -253,30 +357,15 @@ def generate_podcast(
|
||||
|
||||
if __name__ == "__main__":
|
||||
parser = argparse.ArgumentParser(description="Generate podcast from script JSON file")
|
||||
parser.add_argument(
|
||||
"--script-file",
|
||||
required=True,
|
||||
help="Absolute path to script JSON file",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--output-file",
|
||||
required=True,
|
||||
help="Output path for generated podcast MP3",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--transcript-file",
|
||||
required=False,
|
||||
help="Output path for transcript markdown file (optional)",
|
||||
)
|
||||
|
||||
parser.add_argument("--script-file", required=True, help="Absolute path to script JSON file")
|
||||
parser.add_argument("--output-file", required=True, help="Output path for generated podcast MP3")
|
||||
parser.add_argument("--transcript-file", required=False,
|
||||
help="Output path for transcript markdown file (optional)")
|
||||
args = parser.parse_args()
|
||||
|
||||
try:
|
||||
result = generate_podcast(
|
||||
args.script_file,
|
||||
args.output_file,
|
||||
args.transcript_file,
|
||||
)
|
||||
result = generate_podcast(args.script_file, args.output_file,
|
||||
args.transcript_file)
|
||||
print(result)
|
||||
except Exception as e:
|
||||
import traceback
|
||||
|
||||
Reference in New Issue
Block a user