From 38db690ae8f3ec04494c6c0b4f36c91b873c4914 Mon Sep 17 00:00:00 2001 From: guo zebin Date: Wed, 4 Mar 2026 17:36:42 +0800 Subject: [PATCH] v4.3.1 MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 1.增加音频缓存功能，降低tts费率； 2.优化透传接口流式断句逻辑，域名、版本号等不断句； 3.优化数字人接口流式文本输出顺序； 4.llm透传功能接入langsmith，配置环境变量后可通过langsmith平台调优prompt； 5.优化配置中心加载逻辑，人设配置依然保留。 --- asr/ali_nls.py | 368 +++++++++--------- bionicmemory/core/memory_system.py | 22 +- core/fay_core.py | 469 +++++++++++++++++----- faymcp/mcp_server.py | 606 +++++++++++++++-------------- faymcp/static/images/Logo.png | Bin 8779 -> 8386 bytes gui/flask_server.py | 382 +++++++++++++----- gui/static/images/Logo.png | Bin 8779 -> 8386 bytes main.py | 8 +- requirements.txt | 68 ++-- test/ovr_lipsync/test_olipsync.py | 164 ++++---- utils/config_util.py | 129 +++--- utils/stream_text_processor.py | 112 +++++- 12 files changed, 1490 insertions(+), 838 deletions(-) diff --git a/asr/ali_nls.py b/asr/ali_nls.py index 525af8a..2ecaa51 100644 --- a/asr/ali_nls.py +++ b/asr/ali_nls.py @@ -1,190 +1,206 @@ -from threading import Thread -from threading import Lock -import websocket -import json -import time -import ssl -import wave -import _thread as thread -from aliyunsdkcore.client import AcsClient -from aliyunsdkcore.request import CommonRequest - -from core import wsa_server -from scheduler.thread_manager import MyThread -from utils import util -from utils import config_util as cfg -from core.authorize_tb import Authorize_Tb - -__running = True -__my_thread = None -_token = '' - - +from threading import Thread +from threading import Lock +import websocket +import json +import time +import ssl +import wave +import _thread as thread +from aliyunsdkcore.client import AcsClient +from aliyunsdkcore.request import CommonRequest + +from core import wsa_server +from scheduler.thread_manager import MyThread +from utils import util +from utils import config_util as cfg +from core.authorize_tb import Authorize_Tb + +__running = True +__my_thread = None +_token = '' + + def __post_token(): global _token - __client = AcsClient( - cfg.key_ali_nls_key_id, - cfg.key_ali_nls_key_secret, - "cn-shanghai" - ) + if not cfg.key_ali_nls_key_id or not cfg.key_ali_nls_key_secret: + util.log(2, "AliNLS 凭据未配置，跳过 token 刷新。") + return False - __request = CommonRequest() - __request.set_method('POST') - __request.set_domain('nls-meta.cn-shanghai.aliyuncs.com') - __request.set_version('2019-02-28') - __request.set_action_name('CreateToken') - info = json.loads(__client.do_action_with_exception(__request)) - _token = info['Token']['Id'] - authorize = Authorize_Tb() - authorize_info = authorize.find_by_userid(cfg.key_ali_nls_key_id) - if authorize_info is not None: - authorize.update_by_userid(cfg.key_ali_nls_key_id, _token, info['Token']['ExpireTime']*1000) - else: - authorize.add(cfg.key_ali_nls_key_id, _token, info['Token']['ExpireTime']*1000) + try: + __client = AcsClient( + cfg.key_ali_nls_key_id, + cfg.key_ali_nls_key_secret, + "cn-shanghai" + ) + + __request = CommonRequest() + __request.set_method('POST') + __request.set_domain('nls-meta.cn-shanghai.aliyuncs.com') + __request.set_version('2019-02-28') + __request.set_action_name('CreateToken') + info = json.loads(__client.do_action_with_exception(__request)) + _token = info['Token']['Id'] + authorize = Authorize_Tb() + authorize_info = authorize.find_by_userid(cfg.key_ali_nls_key_id) + if authorize_info is not None: + authorize.update_by_userid(cfg.key_ali_nls_key_id, _token, info['Token']['ExpireTime']*1000) + else: + authorize.add(cfg.key_ali_nls_key_id, _token, info['Token']['ExpireTime']*1000) + util.log(1, "AliNLS token刷新成功") + return True + except Exception as e: + util.log(2, f"AliNLS token刷新失败: {str(e)}") + return False def __runnable(): while __running: - __post_token() - time.sleep(60 * 60 * 12) - + if __post_token(): + time.sleep(60 * 60 * 12) + else: + time.sleep(60) def start(): MyThread(target=__runnable).start() - - -class ALiNls: - # 初始化 - def __init__(self, username): - self.__URL = 'wss://nls-gateway-cn-shenzhen.aliyuncs.com/ws/v1' - self.__ws = None - self.__frames = [] - self.started = False - self.__closing = False - self.__task_id = '' - self.done = False - self.finalResults = "" - self.username = username - self.data = b'' - self.__endding = False - self.__is_close = False - self.lock = Lock() - - def __create_header(self, name): - if name == 'StartTranscription': - self.__task_id = util.random_hex(32) - header = { - "appkey": cfg.key_ali_nls_app_key, - "message_id": util.random_hex(32), - "task_id": self.__task_id, - "namespace": "SpeechTranscriber", - "name": name - } - return header - - # 收到websocket消息的处理 - def on_message(self, ws, message): - try: - data = json.loads(message) - header = data['header'] - name = header['name'] - if name == 'TranscriptionStarted': - self.started = True - if name == 'SentenceEnd': - self.done = True - self.finalResults = data['payload']['result'] - if wsa_server.get_web_instance().is_connected(self.username): - wsa_server.get_web_instance().add_cmd({"panelMsg": self.finalResults, "Username" : self.username}) - if wsa_server.get_instance().is_connected(self.username): - content = {'Topic': 'human', 'Data': {'Key': 'log', 'Value': self.finalResults}, 'Username' : self.username} - wsa_server.get_instance().add_cmd(content) - ws.close()#TODO - elif name == 'TranscriptionResultChanged': - self.finalResults = data['payload']['result'] - if wsa_server.get_web_instance().is_connected(self.username): - wsa_server.get_web_instance().add_cmd({"panelMsg": self.finalResults, "Username" : self.username}) - if wsa_server.get_instance().is_connected(self.username): - content = {'Topic': 'human', 'Data': {'Key': 'log', 'Value': self.finalResults}, 'Username' : self.username} - wsa_server.get_instance().add_cmd(content) - - except Exception as e: - print(e) - # print("### message:", message) - - # 收到websocket的关闭要求 - def on_close(self, ws, code, msg): - self.__endding = True - self.__is_close = True - - # 收到websocket错误的处理 - def on_error(self, ws, error): - print("aliyun asr error:", error) - self.started = True #避免在aliyun asr出错时，recorder一直等待start状态返回 - - # 收到websocket连接建立的处理 - def on_open(self, ws): - self.__endding = False - #为了兼容多路asr，关闭过程数据 - def run(*args): - while self.__endding == False: - try: - if len(self.__frames) > 0: - with self.lock: - frame = self.__frames.pop(0) - if isinstance(frame, dict): - ws.send(json.dumps(frame)) - elif isinstance(frame, bytes): - ws.send(frame, websocket.ABNF.OPCODE_BINARY) - self.data += frame - else: - time.sleep(0.001) # 避免忙等 - except Exception as e: - print(e) - break - if self.__is_close == False: - for frame in self.__frames: - ws.send(frame, websocket.ABNF.OPCODE_BINARY) - frame = {"header": self.__create_header('StopTranscription')} - ws.send(json.dumps(frame)) - thread.start_new_thread(run, ()) - + + +class ALiNls: + # 初始化 + def __init__(self, username): + self.__URL = 'wss://nls-gateway-cn-shenzhen.aliyuncs.com/ws/v1' + self.__ws = None + self.__frames = [] + self.started = False + self.__closing = False + self.__task_id = '' + self.done = False + self.finalResults = "" + self.username = username + self.data = b'' + self.__endding = False + self.__is_close = False + self.lock = Lock() + + def __create_header(self, name): + if name == 'StartTranscription': + self.__task_id = util.random_hex(32) + header = { + "appkey": cfg.key_ali_nls_app_key, + "message_id": util.random_hex(32), + "task_id": self.__task_id, + "namespace": "SpeechTranscriber", + "name": name + } + return header + + # 收到websocket消息的处理 + def on_message(self, ws, message): + try: + data = json.loads(message) + header = data['header'] + name = header['name'] + if name == 'TranscriptionStarted': + self.started = True + if name == 'SentenceEnd': + self.done = True + self.finalResults = data['payload']['result'] + if wsa_server.get_web_instance().is_connected(self.username): + wsa_server.get_web_instance().add_cmd({"panelMsg": self.finalResults, "Username" : self.username}) + if wsa_server.get_instance().is_connected(self.username): + content = {'Topic': 'human', 'Data': {'Key': 'log', 'Value': self.finalResults}, 'Username' : self.username} + wsa_server.get_instance().add_cmd(content) + ws.close()#TODO + elif name == 'TranscriptionResultChanged': + self.finalResults = data['payload']['result'] + if wsa_server.get_web_instance().is_connected(self.username): + wsa_server.get_web_instance().add_cmd({"panelMsg": self.finalResults, "Username" : self.username}) + if wsa_server.get_instance().is_connected(self.username): + content = {'Topic': 'human', 'Data': {'Key': 'log', 'Value': self.finalResults}, 'Username' : self.username} + wsa_server.get_instance().add_cmd(content) + + except Exception as e: + print(e) + # print("### message:", message) + + # 收到websocket的关闭要求 + def on_close(self, ws, code, msg): + self.__endding = True + self.__is_close = True + + # 收到websocket错误的处理 + def on_error(self, ws, error): + print("aliyun asr error:", error) + self.started = True #避免在aliyun asr出错时，recorder一直等待start状态返回 + + # 收到websocket连接建立的处理 + def on_open(self, ws): + self.__endding = False + #为了兼容多路asr，关闭过程数据 + def run(*args): + while self.__endding == False: + try: + if len(self.__frames) > 0: + with self.lock: + frame = self.__frames.pop(0) + if isinstance(frame, dict): + ws.send(json.dumps(frame)) + elif isinstance(frame, bytes): + ws.send(frame, websocket.ABNF.OPCODE_BINARY) + self.data += frame + else: + time.sleep(0.001) # 避免忙等 + except Exception as e: + print(e) + break + if self.__is_close == False: + for frame in self.__frames: + ws.send(frame, websocket.ABNF.OPCODE_BINARY) + frame = {"header": self.__create_header('StopTranscription')} + ws.send(json.dumps(frame)) + thread.start_new_thread(run, ()) + def __connect(self): + if not _token: + util.log(2, "AliNLS token为空，本次语音识别连接跳过") + self.started = True + return + self.finalResults = "" self.done = False with self.lock: self.__frames.clear() - self.__ws = websocket.WebSocketApp(self.__URL + '?token=' + _token, on_message=self.on_message) - self.__ws.on_open = self.on_open - self.__ws.on_error = self.on_error - self.__ws.on_close = self.on_close - self.__ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE}) - - def send(self, buf): - with self.lock: - self.__frames.append(buf) - - def start(self): - Thread(target=self.__connect, args=[]).start() - data = { - 'header': self.__create_header('StartTranscription'), - "payload": { - "format": "pcm", - "sample_rate": 16000, - "enable_intermediate_result": True, - "enable_punctuation_prediction": False, - "enable_inverse_text_normalization": True, - "speech_noise_threshold": -1 - } - } - self.send(data) - - def end(self): - self.__endding = True - with wave.open('cache_data/input2.wav', 'wb') as wf: - # 设置音频参数 - n_channels = 1 # 单声道 - sampwidth = 2 # 16 位音频，每个采样点 2 字节 - wf.setnchannels(n_channels) - wf.setsampwidth(sampwidth) - wf.setframerate(16000) - wf.writeframes(self.data) - self.data = b'' + self.__ws = websocket.WebSocketApp(self.__URL + '?token=' + _token, on_message=self.on_message) + self.__ws.on_open = self.on_open + self.__ws.on_error = self.on_error + self.__ws.on_close = self.on_close + self.__ws.run_forever(sslopt={"cert_reqs": ssl.CERT_NONE}) + + def send(self, buf): + with self.lock: + self.__frames.append(buf) + + def start(self): + Thread(target=self.__connect, args=[]).start() + data = { + 'header': self.__create_header('StartTranscription'), + "payload": { + "format": "pcm", + "sample_rate": 16000, + "enable_intermediate_result": True, + "enable_punctuation_prediction": False, + "enable_inverse_text_normalization": True, + "speech_noise_threshold": -1 + } + } + self.send(data) + + def end(self): + self.__endding = True + with wave.open('cache_data/input2.wav', 'wb') as wf: + # 设置音频参数 + n_channels = 1 # 单声道 + sampwidth = 2 # 16 位音频，每个采样点 2 字节 + wf.setnchannels(n_channels) + wf.setsampwidth(sampwidth) + wf.setframerate(16000) + wf.writeframes(self.data) + self.data = b'' diff --git a/bionicmemory/core/memory_system.py b/bionicmemory/core/memory_system.py index c557ce3..1549550 100644 --- a/bionicmemory/core/memory_system.py +++ b/bionicmemory/core/memory_system.py @@ -17,7 +17,7 @@ from bionicmemory.algorithms.newton_cooling_helper import NewtonCoolingHelper, C from bionicmemory.core.chroma_service import ChromaService from bionicmemory.services.summary_service import SummaryService from bionicmemory.algorithms.clustering_suppression import ClusteringSuppression -from utils.api_embedding_service import get_embedding_service +from utils.api_embedding_service import get_embedding_service # 使用统一日志配置 from bionicmemory.utils.logging_config import get_logger @@ -238,7 +238,8 @@ class LongShortTermMemorySystem: logger.info(f"[仿生记忆] _prepare_document_data: embedding生成完成, 类型={type(embedding)}") except Exception as e: logger.error(f"生成embedding失败: {e}") - embedding = [] + # 返回None而不是空列表，让调用方知道这是一个失败的情况 + embedding = None # 准备元数据 current_time = datetime.now().isoformat() @@ -398,12 +399,15 @@ class LongShortTermMemorySystem: embedding_list = embedding.tolist() else: embedding_list = embedding - # 检查长度 + # 检查长度和维度 if len(embedding_list) > 0: embeddings_param = [embedding_list] + logger.debug(f"添加embedding到长期记忆: doc_id={doc_id}, 维度={len(embedding_list)}") else: + logger.warning(f"⚠️ Embedding为空列表: doc_id={doc_id}") embeddings_param = None else: + logger.warning(f"⚠️ Embedding为None: doc_id={doc_id}, 将不包含向量信息") embeddings_param = None self.chroma_service.add_documents( @@ -1046,6 +1050,16 @@ class LongShortTermMemorySystem: ) logger.info(f"[仿生记忆] 步骤1完成: doc_id={doc_id}, user_embedding类型={type(user_embedding)}") + # 检查embedding是否生成成功 + if user_embedding is None: + logger.warning("[仿生记忆] embedding生成失败，跳过记忆检索，使用默认响应") + return { + "system_prompt": "你是一个智能助手。由于技术问题，暂时无法访问历史记忆，但我会尽力帮助你。", + "retrieved_memories": [], + "user_doc_id": None, + "assistant_doc_id": None + } + # 使用用户embedding进行检索 logger.info("[仿生记忆] 步骤2: 使用用户embedding进行检索") query_embedding = user_embedding @@ -1485,4 +1499,4 @@ if __name__ == "__main__": stats_after['short_term_memory']['total_records'] == 0: logger.info(f"✅ 用户 {target_user_id} (key: {target_key[:10]}...) 历史记录清除成功！") else: - logger.warning(f"⚠️ 用户 {target_user_id} (key: {target_key[:10]}...) 历史记录可能未完全清除") + logger.warning(f"⚠️ 用户 {target_user_id} (key: {target_key[:10]}...) 历史记录可能未完全清除") diff --git a/core/fay_core.py b/core/fay_core.py index 1165f80..9639cf1 100644 --- a/core/fay_core.py +++ b/core/fay_core.py @@ -31,7 +31,9 @@ from queue import Queue import re # 添加正则表达式模块用于过滤表情符号 -import uuid +import uuid +import hashlib +from urllib.parse import urlparse, urljoin @@ -136,16 +138,24 @@ else: import platform -if platform.system() == "Windows": - - - import sys - - - sys.path.append("test/ovr_lipsync") - - - from test_olipsync import LipSyncGenerator +if platform.system() == "Windows": + + + import sys + + + _fay_runtime_dir = os.path.abspath(os.path.dirname(__file__)) + if hasattr(sys, "_MEIPASS"): + _fay_runtime_dir = os.path.abspath(sys._MEIPASS) + else: + _fay_runtime_dir = os.path.abspath(os.path.join(_fay_runtime_dir, "..")) + + _lipsync_dir = os.path.join(_fay_runtime_dir, "test", "ovr_lipsync") + if _lipsync_dir not in map(os.path.abspath, sys.path): + sys.path.insert(0, _lipsync_dir) + + + from test_olipsync import LipSyncGenerator @@ -237,7 +247,15 @@ class FeiFei: self.think_display_limit = 400 self.user_conv_map = {} #存储用户对话id及句子流序号，key为(username, conversation_id) - self.pending_isfirst = {} # 存储因prestart被过滤而延迟的isfirst标记，key为username + self.pending_isfirst = {} # 存储因prestart被过滤而延迟的isfirst标记，key为username + self.tts_cache = {} + self.tts_cache_limit = 1000 + self.tts_cache_lock = threading.Lock() + self.user_audio_conv_map = {} # 仅用于音频片段的连续序号（避免文本序号空洞导致乱序/缺包） + self.human_audio_order_map = {} + self.human_audio_order_lock = threading.Lock() + self.human_audio_reorder_wait_seconds = 0.2 + self.human_audio_first_wait_seconds = 1.2 @@ -868,7 +886,7 @@ class FeiFei: #获取不同情绪声音 - def __get_mood_voice(self): + def __get_mood_voice(self): voice = tts_voice.get_voice_of(config_util.config["attribute"]["voice"]) @@ -883,18 +901,168 @@ class FeiFei: styleList = voice.value["styleList"] - sayType = styleList["calm"] - - - return sayType - - - - - - # 合成声音 - - + sayType = styleList["calm"] + + + return sayType + + def __build_tts_cache_key(self, text, style): + tts_module = str(getattr(cfg, "tts_module", "") or "") + style_str = str(style or "") + voice_name = "" + try: + voice_name = str(config_util.config.get("attribute", {}).get("voice", "") or "") + except Exception: + voice_name = "" + if tts_module == "volcano": + try: + volcano_voice = str(getattr(cfg, "volcano_tts_voice_type", "") or "") + if volcano_voice: + voice_name = volcano_voice + except Exception: + pass + raw = f"{tts_module}|{voice_name}|{style_str}|{text}" + return hashlib.sha1(raw.encode("utf-8")).hexdigest() + + def __get_tts_cache(self, key): + with self.tts_cache_lock: + file_url = self.tts_cache.get(key) + if not file_url: + return None + if os.path.exists(file_url): + return file_url + with self.tts_cache_lock: + if key in self.tts_cache: + del self.tts_cache[key] + return None + + def __set_tts_cache(self, key, file_url): + if not file_url: + return + with self.tts_cache_lock: + self.tts_cache[key] = file_url + while len(self.tts_cache) > self.tts_cache_limit: + try: + self.tts_cache.pop(next(iter(self.tts_cache))) + except Exception: + break + + def __send_human_audio_ordered(self, content, username, conversation_id, conversation_msg_no, is_end=False): + now = time.time() + sent_messages = [] + data = content.get("Data", {}) if isinstance(content, dict) else {} + has_audio_payload = bool(data.get("Value")) or bool(data.get("HttpValue")) + is_end_marker_only = bool(is_end or data.get("IsEnd", 0)) and (not has_audio_payload) + + seq = None + try: + if conversation_msg_no is not None: + seq = int(conversation_msg_no) + except Exception: + seq = None + + # Fallback to direct send for legacy paths without sequence metadata. + if (not conversation_id) or (seq is None): + if is_end_marker_only: + return 0 + wsa_server.get_instance().add_cmd(content) + return 1 + + key = (username or "User", conversation_id) + with self.human_audio_order_lock: + state = self.human_audio_order_map.get(key) + if state is None: + state = { + "next_seq": None, + "buffer": {}, + "last_progress_time": now, + "first_wait_start": now, + "start_known": False, + "end_seq": None, + "pending_end_seq": None, + } + self.human_audio_order_map[key] = state + + next_seq = state.get("next_seq") + if (next_seq is not None) and (seq < next_seq): + return 0 + + def _mark_buffer_end(target_seq): + existed = state["buffer"].get(target_seq) + if isinstance(existed, dict): + existed_data = existed.get("Data", {}) + if isinstance(existed_data, dict): + existed_data["IsEnd"] = 1 + return True + return False + + if is_end_marker_only: + target_seq = None + if seq in state["buffer"]: + target_seq = seq + elif (seq - 1) in state["buffer"]: + target_seq = seq - 1 + elif state["buffer"]: + target_seq = max(state["buffer"].keys()) + + if (target_seq is not None) and _mark_buffer_end(target_seq): + end_seq = state.get("end_seq") + state["end_seq"] = target_seq if end_seq is None else max(end_seq, target_seq) + state["pending_end_seq"] = None + else: + state["pending_end_seq"] = seq + else: + if seq in state["buffer"]: + return 0 + state["buffer"][seq] = content + + pending_end_seq = state.get("pending_end_seq") + if pending_end_seq is not None: + if (seq == pending_end_seq) or (seq == pending_end_seq - 1): + if _mark_buffer_end(seq): + end_seq = state.get("end_seq") + state["end_seq"] = seq if end_seq is None else max(end_seq, seq) + state["pending_end_seq"] = None + + if is_end: + end_seq = state.get("end_seq") + state["end_seq"] = seq if end_seq is None else max(end_seq, seq) + + is_first_flag = bool(data.get("IsFirst", 0)) + if (not state["start_known"]) and is_first_flag: + state["start_known"] = True + state["next_seq"] = seq + state["last_progress_time"] = now + elif (not state["start_known"]) and (seq == 0): + state["start_known"] = True + state["next_seq"] = 0 + state["last_progress_time"] = now + elif (not state["start_known"]): + first_elapsed = now - state.get("first_wait_start", now) + if (first_elapsed >= self.human_audio_first_wait_seconds) and (0 in state["buffer"]): + state["start_known"] = True + state["next_seq"] = 0 + state["last_progress_time"] = now + + def _flush_contiguous(): + flush_count = 0 + while (state["next_seq"] is not None) and (state["next_seq"] in state["buffer"]): + sent_messages.append(state["buffer"].pop(state["next_seq"])) + state["next_seq"] += 1 + state["last_progress_time"] = now + flush_count += 1 + return flush_count + + _flush_contiguous() + + end_seq = state.get("end_seq") + if (end_seq is not None) and (state.get("next_seq") is not None) and (state["next_seq"] > end_seq) and (not state["buffer"]): + self.human_audio_order_map.pop(key, None) + + for message in sent_messages: + wsa_server.get_instance().add_cmd(message) + return len(sent_messages) + def say(self, interact, text, type = ""): @@ -1085,25 +1253,27 @@ class FeiFei: # 如果 conv_map_key 不存在，尝试使用 username 作为备用查找 - if not conv_info and text and text.strip(): + if not conv_info and text and text.strip(): # 查找所有匹配用户名的会话 - for (u, c), info in list(self.user_conv_map.items()): + for (u, c), info in list(self.user_conv_map.items()): - if u == username and info.get("content_id", 0) > 0: + if u == username and info.get("content_id", 0) > 0: - content_id = info.get("content_id", 0) + content_id = info.get("content_id", 0) + + + conv_info = info + conv = info.get("conversation_id", c) + conv_map_key = (username, conv) - conv_info = info - - - util.log(1, f"警告：使用备用会话 ({u}, {c}) 的 content_id={content_id}，原 key=({username}, {conv})") + util.log(1, f"警告：使用备用会话 ({u}, {c}) 的 content_id={content_id}，原 key=({username}, {conv})") break @@ -1157,10 +1327,27 @@ class FeiFei: - # 会话结束时清理 user_conv_map 中的对应条目，避免内存泄漏 + # 固化当前会话序号，避免异步音频线程读取时会话映射已被清理而回落为0 + current_conv_info = self.user_conv_map.get(conv_map_key, {}) + if (not current_conv_info) and (not conv): + for (u, c), info in list(self.user_conv_map.items()): + if u == username and info.get("conversation_id", ""): + current_conv_info = info + conv = info.get("conversation_id", c) + conv_map_key = (username, conv) + break + if current_conv_info: + interact.data["conversation_id"] = current_conv_info.get("conversation_id", conv) + interact.data["conversation_msg_no"] = current_conv_info.get("conversation_msg_no", 0) + else: + if conv: + interact.data["conversation_id"] = conv + interact.data["conversation_msg_no"] = interact.data.get("conversation_msg_no", 0) + + # 会话结束时清理 user_conv_map 中的对应条目，避免内存泄漏 - if is_end and conv_map_key in self.user_conv_map: + if is_end and conv_map_key in self.user_conv_map: del self.user_conv_map[conv_map_key] @@ -1394,7 +1581,15 @@ class FeiFei: tm = time.time() - result = self.sp.to_sample(filtered_text, self.__get_mood_voice()) + mood_voice = self.__get_mood_voice() + cache_key = self.__build_tts_cache_key(filtered_text, mood_voice) + cache_result = self.__get_tts_cache(cache_key) + if cache_result is not None: + result = cache_result + util.printInfo(1, interact.data.get('user'), 'TTS cache hit') + else: + result = self.sp.to_sample(filtered_text, mood_voice) + self.__set_tts_cache(cache_key, result) # 合成完成后再次检查会话是否仍有效，避免继续输出旧会话结果 @@ -1439,7 +1634,22 @@ class FeiFei: - if result is not None or is_first or is_end: + # 为数字人音频单独维护连续序号，避免 conversation_msg_no 因无音频片段产生空洞 + audio_conv_id = interact.data.get("conversation_id", "") or "" + audio_conv_key = (username, audio_conv_id) + audio_msg_no = None + if result is not None: + audio_msg_no = self.user_audio_conv_map.get(audio_conv_key, -1) + 1 + self.user_audio_conv_map[audio_conv_key] = audio_msg_no + elif is_end: + audio_msg_no = self.user_audio_conv_map.get(audio_conv_key, None) + if audio_conv_key in self.user_audio_conv_map: + del self.user_audio_conv_map[audio_conv_key] + interact.data["audio_conversation_msg_no"] = audio_msg_no + if is_end and audio_conv_key in self.user_audio_conv_map: + del self.user_audio_conv_map[audio_conv_key] + + if result is not None or is_first or is_end: # prestart 内容不需要进入音频处理流程 @@ -1490,7 +1700,26 @@ class FeiFei: # 发送HTTP GET请求以获取WAV文件内容 - response = requests.get(url, stream=True) + if url is None: + return None + + url = str(url).strip() + if not url: + return None + + if os.path.isfile(url): + return url + + parsed_url = urlparse(url) + if not parsed_url.scheme: + if url.startswith('//'): + url = 'http:' + url + else: + base_url = str(getattr(cfg, "fay_url", "") or "").strip() + if base_url: + url = urljoin(base_url.rstrip('/') + '/', url.lstrip('/')) + + response = requests.get(url, stream=True) response.raise_for_status() # 检查请求是否成功 @@ -1946,61 +2175,115 @@ class FeiFei: - #发送音频给数字人接口 - - - if file_url is not None and wsa_server.get_instance().get_client_output(interact.data.get("user")): - - - # 使用 (username, conversation_id) 作为 key 获取会话信息 - - - audio_username = interact.data.get("user", "User") - - - audio_conv_id = interact.data.get("conversation_id") or "" - - - audio_conv_info = self.user_conv_map.get((audio_username, audio_conv_id), {}) - - - content = {'Topic': 'human', 'Data': {'Key': 'audio', 'Value': os.path.abspath(file_url), 'HttpValue': f'{cfg.fay_url}/audio/' + os.path.basename(file_url), 'Text': text, 'Time': audio_length, 'Type': interact.interleaver, 'IsFirst': 1 if interact.data.get("isfirst", False) else 0, 'IsEnd': 1 if interact.data.get("isend", False) else 0, 'CONV_ID' : audio_conv_info.get("conversation_id", ""), 'CONV_MSG_NO' : audio_conv_info.get("conversation_msg_no", 0) }, 'Username' : interact.data.get('user'), 'robot': f'{cfg.fay_url}/robot/Speaking.jpg'} - - - #计算lips - - - if platform.system() == "Windows": - - - try: - - - lip_sync_generator = LipSyncGenerator() - - - viseme_list = lip_sync_generator.generate_visemes(os.path.abspath(file_url)) - - - consolidated_visemes = lip_sync_generator.consolidate_visemes(viseme_list) - - - content["Data"]["Lips"] = consolidated_visemes - - - except Exception as e: - - - print(e) - - - util.printInfo(1, interact.data.get("user"), "唇型数据生成失败") - - - wsa_server.get_instance().add_cmd(content) - - - util.printInfo(1, interact.data.get("user"), "数字人接口发送音频数据成功") + #发送音频给数字人接口 + + + if wsa_server.get_instance().get_client_output(interact.data.get("user")): + + + # 使用 (username, conversation_id) 作为 key 获取会话信息 + + + audio_username = interact.data.get("user", "User") + + + audio_conv_id = interact.data.get("conversation_id") or "" + + + audio_conv_info = self.user_conv_map.get((audio_username, audio_conv_id), {}) + msg_no_from_interact = interact.data.get("audio_conversation_msg_no", None) + conv_id_for_send = audio_conv_id if audio_conv_id else audio_conv_info.get("conversation_id", "") + if msg_no_from_interact is None: + fallback_no = interact.data.get("conversation_msg_no", None) + if fallback_no is None: + conv_msg_no_for_send = audio_conv_info.get("conversation_msg_no", 0) + else: + conv_msg_no_for_send = fallback_no + else: + conv_msg_no_for_send = msg_no_from_interact + + if file_url is not None: + + + content = {'Topic': 'human', 'Data': {'Key': 'audio', 'Value': os.path.abspath(file_url), 'HttpValue': f'{cfg.fay_url}/audio/' + os.path.basename(file_url), 'Text': text, 'Time': audio_length, 'Type': interact.interleaver, 'IsFirst': 1 if interact.data.get("isfirst", False) else 0, 'IsEnd': 1 if interact.data.get("isend", False) else 0, 'CONV_ID' : conv_id_for_send, 'CONV_MSG_NO' : conv_msg_no_for_send }, 'Username' : interact.data.get('user'), 'robot': f'{cfg.fay_url}/robot/Speaking.jpg'} + + + #计算lips + + + if platform.system() == "Windows": + + + try: + + + lip_sync_generator = LipSyncGenerator() + + + viseme_list = lip_sync_generator.generate_visemes(os.path.abspath(file_url)) + + + consolidated_visemes = lip_sync_generator.consolidate_visemes(viseme_list) + + + content["Data"]["Lips"] = consolidated_visemes + + + except Exception as e: + + + print(e) + + + util.printInfo(1, interact.data.get("user"), "唇型数据生成失败") + + + sent_count = self.__send_human_audio_ordered( + content, + audio_username, + conv_id_for_send, + conv_msg_no_for_send, + is_end=bool(interact.data.get("isend", False)), + ) + if sent_count > 0: + util.printInfo(1, interact.data.get("user"), "digital human audio sent") + else: + util.printInfo(1, interact.data.get("user"), "digital human audio queued") + elif bool(interact.data.get("isend", False)): + # 没有音频文件时，也要给数字人发送结束标记，避免客户端一直等待 + end_target_seq = conv_msg_no_for_send + try: + end_target_seq = int(conv_msg_no_for_send) + except Exception: + end_target_seq = conv_msg_no_for_send + end_content = { + 'Topic': 'human', + 'Data': { + 'Key': 'audio', + 'Value': '', + 'HttpValue': '', + 'Text': text, + 'Time': 0, + 'Type': interact.interleaver, + 'IsFirst': 1 if interact.data.get("isfirst", False) else 0, + 'IsEnd': 1, + 'CONV_ID': conv_id_for_send, + 'CONV_MSG_NO': end_target_seq + }, + 'Username': interact.data.get('user'), + 'robot': f'{cfg.fay_url}/robot/Speaking.jpg' + } + sent_count = self.__send_human_audio_ordered( + end_content, + audio_username, + conv_id_for_send, + end_target_seq, + is_end=True, + ) + if sent_count > 0: + util.printInfo(1, interact.data.get("user"), "digital human audio end sent") + else: + util.printInfo(1, interact.data.get("user"), "digital human audio end queued") diff --git a/faymcp/mcp_server.py b/faymcp/mcp_server.py index 3c3fb44..2a2431f 100644 --- a/faymcp/mcp_server.py +++ b/faymcp/mcp_server.py @@ -1,288 +1,318 @@ -#!/usr/bin/env python3 -# -*- coding: utf-8 -*- -""" -Fay broadcast MCP server (SSE transport). - -暴露 `broadcast_message` 工具，将文本/音频透传到 Fay 的 `/transparent-pass`。 - -环境变量： -- FAY_BROADCAST_API 默认 http://127.0.0.1:5000/transparent-pass -- FAY_BROADCAST_USER 默认 User -- FAY_BROADCAST_TIMEOUT 默认 10 -- FAY_MCP_SSE_HOST 默认 0.0.0.0 -- FAY_MCP_SSE_PORT 默认 8765 -- FAY_MCP_SSE_PATH SSE 路径（默认 /sse） -- FAY_MCP_MSG_PATH 消息 POST 路径（默认 /messages） -""" - -import asyncio -import logging -import os -import sys -import json -from typing import Any, Dict, Tuple, List, Optional - -try: - from mcp.server import Server - from mcp.types import Tool, TextContent - from mcp.server.sse import SseServerTransport - from faymcp import tool_registry - from faymcp import mcp_service -except ImportError: - print("缺少 mcp 库，请先安装：pip install mcp", file=sys.stderr) - sys.exit(1) - -try: - from starlette.applications import Starlette - from starlette.responses import Response - from starlette.routing import Mount, Route -except ImportError: - print("缺少 starlette，请先安装：pip install starlette sse-starlette", file=sys.stderr) - sys.exit(1) - -try: - import uvicorn -except ImportError: - print("缺少 uvicorn，请先安装：pip install uvicorn", file=sys.stderr) - sys.exit(1) - -try: - import requests -except ImportError: - print("缺少 requests，请先安装：pip install requests", file=sys.stderr) - sys.exit(1) - - -log = logging.getLogger("fay_mcp_server") -logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") - -SERVER_NAME = "fay_broadcast" - -DEFAULT_API_URL = os.environ.get("FAY_BROADCAST_API", "http://127.0.0.1:5000/transparent-pass") -DEFAULT_USER = os.environ.get("FAY_BROADCAST_USER", "User") -DEFAULT_SPEAKER = os.environ.get("FAY_BROADCAST_SPEAKER", "\u5e7f\u64ad\u6d88\u606f") -REQUEST_TIMEOUT = float(os.environ.get("FAY_BROADCAST_TIMEOUT", "10")) - -HOST = os.environ.get("FAY_MCP_SSE_HOST", "0.0.0.0") -PORT = int(os.environ.get("FAY_MCP_SSE_PORT", "8765")) -SSE_PATH = os.environ.get("FAY_MCP_SSE_PATH", "/sse") -MSG_PATH = os.environ.get("FAY_MCP_MSG_PATH", "/messages") - -server = None # Removed global singleton -sse_transport = SseServerTransport(MSG_PATH) - -# 聚合工具索引：namespaced_tool_name -> (server_id, tool_name) -_aggregated_index: Dict[str, Tuple[int, str]] = {} - - -def _text_content(text: str) -> TextContent: - try: - return TextContent(type="text", text=text) - except Exception: - return {"type": "text", "text": text} # type: ignore[return-value] - - -TOOLS: list[Tool] = [ - Tool( - name="broadcast_message", - description="通过 Fay 的 /transparent-pass 广播文本/音频（SSE 服务器）。", - inputSchema={ - "type": "object", - "properties": { - "text": {"type": "string", "description": "要广播的文本（audio_url为空时必填）"}, - "audio_url": {"type": "string", "description": "可选音频 URL"}, - "user": {"type": "string", "description": "目标用户名，默认 FAY_BROADCAST_USER 或 User"}, - "speaker": { - "type": "string", - "description": "\u5e7f\u64ad\u4eba\u663e\u793a\u540d\uff0c\u8f93\u51fa\u4e3a\"{speaker}\u8bf4\uff1a{text}\"", - }, - }, - "required": [], - }, - ) -] - - -async def _handle_list_tools() -> list[Tool]: - # 本地广播工具 + Fay 当前在线 MCP 工具的聚合视图（namespaced） - aggregated = [] - try: - aggregated = _build_aggregated_tools() - except Exception as e: - log.warning(f"Failed to build aggregated tools: {e}") - return TOOLS + aggregated - - -def _parse_arguments(arguments: Dict[str, Any]) -> Tuple[str, str, str, str]: - text = str(arguments.get("text", "") or "").strip() - audio_url = str(arguments.get("audio_url", "") or "").strip() - user = str(arguments.get("user", "") or "").strip() or DEFAULT_USER - speaker = str(arguments.get("speaker", "") or "").strip() or DEFAULT_SPEAKER - return text, audio_url, user, speaker - - -def _build_aggregated_tools() -> List[Tool]: - """ - 将 Fay 已连接的 MCP 工具聚合，对外暴露为 namespaced 名称： - : - """ - tools: List[Tool] = [] - _aggregated_index.clear() - - server_name_map = {s.get("id"): s.get("name", f"Server{s.get('id')}") for s in mcp_service.mcp_servers or []} - - for entry in tool_registry.get_enabled_tools(): - server_id = entry.get("server_id") - tool_name = entry.get("name") - if server_id is None or not tool_name: - continue - agg_name = f"{server_id}:{tool_name}" - desc = entry.get("description", "") - server_label = server_name_map.get(server_id, f"Server {server_id}") - agg_desc = f"{desc} [via {server_label}]" - input_schema = entry.get("inputSchema") or {} - tool = Tool( - name=agg_name, - description=agg_desc, - inputSchema=input_schema if isinstance(input_schema, dict) else {}, - ) - tools.append(tool) - _aggregated_index[agg_name] = (server_id, tool_name) - - return tools - - -async def _send_broadcast(payload: Dict[str, Any]) -> Tuple[bool, str]: - def _post() -> Tuple[bool, str]: - body = json.dumps(payload, ensure_ascii=True).encode("utf-8") - resp = requests.post( - DEFAULT_API_URL, - data=body, - headers={"Content-Type": "application/json; charset=utf-8"}, - timeout=REQUEST_TIMEOUT, - ) - try: - data = resp.json() - except Exception: - data = None - - if resp.ok: - if isinstance(data, dict): - msg = data.get("message") or data.get("msg") or "" - code = data.get("code") - if isinstance(code, int) and code >= 400: - return False, msg or f"Broadcast failed with code {code}" - return True, msg or "Broadcast sent via Fay." - return True, "Broadcast sent via Fay." - - err_detail = "" - if isinstance(data, dict): - err_detail = data.get("message") or data.get("error") or data.get("msg") or "" - if not err_detail: - err_detail = resp.text - return False, f"HTTP {resp.status_code}: {err_detail}" - - try: - return await asyncio.to_thread(_post) - except Exception as e: - return False, f"{type(e).__name__}: {e}" - - -async def _handle_call_tool(name: str, arguments: Dict[str, Any]) -> list[TextContent]: - # 本地广播 - if name == "broadcast_message": - text, audio_url, user, speaker = _parse_arguments(arguments or {}) - if not text and not audio_url: - return [_text_content("Either 'text' or 'audio_url' must be provided.")] - - payload: Dict[str, Any] = {"user": user} - if text: - payload["text"] = f"{speaker}\u8bf4\uff1a{text}" - if audio_url: - payload["audio"] = audio_url - - ok, message = await _send_broadcast(payload) - prefix = "success" if ok else "error" - return [_text_content(f"{prefix}: {message}")] - - # 聚合的远端 MCP 工具 - target = _aggregated_index.get(name) - if not target: - return [_text_content(f"Unknown tool: {name}")] - - server_id, tool_name = target - try: - success, result = await asyncio.to_thread(mcp_service.call_mcp_tool, server_id, tool_name, arguments or {}) - if not success: - return [_text_content(f"error: {result}")] - return _normalize_result(result) - except Exception as e: - return [_text_content(f"error: {type(e).__name__}: {e}")] - - -def _normalize_result(result: Any) -> List[TextContent]: - """ - 将上游返回的任意对象转换为 MCP 文本内容列表。 - """ - # 如果已经是 TextContent 或列表，直接返回 - try: - from mcp.types import TextContent - if isinstance(result, TextContent): - return [result] - except Exception: - pass - - if isinstance(result, list): - contents: List[TextContent] = [] - for item in result: - try: - if hasattr(item, "type") and getattr(item, "type", "") == "text" and hasattr(item, "text"): - contents.append(item) - continue - except Exception: - pass - try: - if isinstance(item, dict) and item.get("type") == "text": - contents.append(TextContent(type="text", text=str(item.get("text", "")))) # type: ignore - continue - except Exception: - pass - contents.append(_text_content(str(item))) - return contents - - return [_text_content(str(result))] - - -async def sse_endpoint(request): - # 为每个连接创建新的 Server 实例以支持并发 - local_server = Server(SERVER_NAME) - - # 注册工具处理程序 - local_server.list_tools()(_handle_list_tools) - local_server.call_tool()(_handle_call_tool) - - async with sse_transport.connect_sse(request.scope, request.receive, request._send) as (read_stream, write_stream): - await local_server.run(read_stream, write_stream, local_server.create_initialization_options()) - # 客户端断开时返回空响应，避免 NoneType 问题 - return Response() - - -routes = [ - Route(SSE_PATH, sse_endpoint, methods=["GET"]), - Mount(MSG_PATH, app=sse_transport.handle_post_message), -] - -app = Starlette(routes=routes) - - -def main(): - log.info(f"SSE MCP server started at http://{HOST}:{PORT}{SSE_PATH}") - log.info(f"Message endpoint mounted at {MSG_PATH}") - uvicorn.run(app, host=HOST, port=PORT, log_level="info") - - -if __name__ == "__main__": - try: - main() - except KeyboardInterrupt: - pass +#!/usr/bin/env python3 +# -*- coding: utf-8 -*- +""" +Fay broadcast MCP server (SSE transport). + +暴露 `broadcast_message` 工具，将文本/音频透传到 Fay 的 `/transparent-pass`。 + +环境变量： +- FAY_BROADCAST_API 默认 http://127.0.0.1:5000/transparent-pass +- FAY_BROADCAST_USER 默认 User +- FAY_BROADCAST_TIMEOUT 默认 10 +- FAY_MCP_SSE_HOST 默认 0.0.0.0 +- FAY_MCP_SSE_PORT 默认 8765 +- FAY_MCP_SSE_PATH SSE 路径（默认 /sse） +- FAY_MCP_MSG_PATH 消息 POST 路径（默认 /messages） +""" + +import asyncio +import logging +import os +import sys +import json +from typing import Any, Dict, Tuple, List, Optional + +try: + from mcp.server import Server + from mcp.types import Tool, TextContent + from mcp.server.sse import SseServerTransport + from faymcp import tool_registry + from faymcp import mcp_service +except ImportError: + print("缺少 mcp 库，请先安装：pip install mcp", file=sys.stderr) + sys.exit(1) + +try: + from starlette.applications import Starlette + from starlette.responses import Response + from starlette.routing import Mount, Route +except ImportError: + print("缺少 starlette，请先安装：pip install starlette sse-starlette", file=sys.stderr) + sys.exit(1) + +try: + import uvicorn +except ImportError: + print("缺少 uvicorn，请先安装：pip install uvicorn", file=sys.stderr) + sys.exit(1) + +try: + import requests +except ImportError: + print("缺少 requests，请先安装：pip install requests", file=sys.stderr) + sys.exit(1) + + +log = logging.getLogger("fay_mcp_server") +logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] %(message)s") + +SERVER_NAME = "fay_broadcast" + +DEFAULT_API_URL = os.environ.get("FAY_BROADCAST_API", "http://127.0.0.1:5000/transparent-pass") +DEFAULT_USER = os.environ.get("FAY_BROADCAST_USER", "User") +DEFAULT_SPEAKER = os.environ.get("FAY_BROADCAST_SPEAKER", "\u5e7f\u64ad\u6d88\u606f") +REQUEST_TIMEOUT = float(os.environ.get("FAY_BROADCAST_TIMEOUT", "10")) + +HOST = os.environ.get("FAY_MCP_SSE_HOST", "0.0.0.0") +PORT = int(os.environ.get("FAY_MCP_SSE_PORT", "8765")) +SSE_PATH = os.environ.get("FAY_MCP_SSE_PATH", "/sse") +MSG_PATH = os.environ.get("FAY_MCP_MSG_PATH", "/messages") + +server = None # Removed global singleton +sse_transport = SseServerTransport(MSG_PATH) + +# 聚合工具索引：namespaced_tool_name -> (server_id, tool_name) +_aggregated_index: Dict[str, Tuple[int, str]] = {} + + +def _text_content(text: str) -> TextContent: + try: + return TextContent(type="text", text=text) + except Exception: + return {"type": "text", "text": text} # type: ignore[return-value] + + +TOOLS: list[Tool] = [ + Tool( + name="broadcast_message", + description="通过 Fay 的 /transparent-pass 透传文本/音频。", + inputSchema={ + "type": "object", + "properties": { + "text": {"type": "string", "description": "要广播的文本（audio_url为空时必填）"}, + "audio_url": {"type": "string", "description": "可选音频 URL"}, + "user": {"type": "string", "description": "用户标识名称，默认 FAY_BROADCAST_USER 或 User"}, + "speaker": { + "type": "string", + "description": "发言人显示名，输出为\"{speaker}说：{text}\"", + }, + "queue": {"type": "boolean", "description": "是否走队列播放，默认 false"}, + "queue_playback": {"type": "boolean", "description": "兼容参数，等同 queue"}, + "enqueue": {"type": "boolean", "description": "兼容参数，等同 queue"}, + "mode": {"type": "string", "description": "兼容参数，值为 queue 时启用队列播放"}, + }, + "required": [], + }, + ) +] + +async def _handle_list_tools() -> list[Tool]: + # 本地广播工具 + Fay 当前在线 MCP 工具的聚合视图（namespaced） + aggregated = [] + try: + aggregated = _build_aggregated_tools() + except Exception as e: + log.warning(f"Failed to build aggregated tools: {e}") + return TOOLS + aggregated + + + +def _as_bool(value: Any) -> bool: + if isinstance(value, bool): + return value + if value is None: + return False + if isinstance(value, (int, float)): + return value != 0 + if isinstance(value, str): + v = value.strip().lower() + if v == "": + return False + return v in {"1", "true", "yes", "on", "y", "queue"} + return bool(value) + + +def _parse_arguments(arguments: Dict[str, Any]) -> Tuple[str, str, str, str, bool]: + text = str(arguments.get("text", "") or "").strip() + audio_url = str(arguments.get("audio_url", "") or "").strip() + user = str(arguments.get("user", "") or "").strip() or DEFAULT_USER + speaker = str(arguments.get("speaker", "") or "").strip() or DEFAULT_SPEAKER + if "queue" in arguments: + queue = _as_bool(arguments.get("queue")) + elif "queue_playback" in arguments: + queue = _as_bool(arguments.get("queue_playback")) + elif "enqueue" in arguments: + queue = _as_bool(arguments.get("enqueue")) + elif "mode" in arguments: + queue = str(arguments.get("mode", "") or "").strip().lower() == "queue" + else: + queue = False + return text, audio_url, user, speaker, queue +def _build_aggregated_tools() -> List[Tool]: + """ + 将 Fay 已连接的 MCP 工具聚合，对外暴露为 namespaced 名称： + : + """ + tools: List[Tool] = [] + _aggregated_index.clear() + + server_name_map = {s.get("id"): s.get("name", f"Server{s.get('id')}") for s in mcp_service.mcp_servers or []} + + for entry in tool_registry.get_enabled_tools(): + server_id = entry.get("server_id") + tool_name = entry.get("name") + if server_id is None or not tool_name: + continue + agg_name = f"{server_id}:{tool_name}" + desc = entry.get("description", "") + server_label = server_name_map.get(server_id, f"Server {server_id}") + agg_desc = f"{desc} [via {server_label}]" + input_schema = entry.get("inputSchema") or {} + tool = Tool( + name=agg_name, + description=agg_desc, + inputSchema=input_schema if isinstance(input_schema, dict) else {}, + ) + tools.append(tool) + _aggregated_index[agg_name] = (server_id, tool_name) + + return tools + + +async def _send_broadcast(payload: Dict[str, Any]) -> Tuple[bool, str]: + def _post() -> Tuple[bool, str]: + body = json.dumps(payload, ensure_ascii=True).encode("utf-8") + resp = requests.post( + DEFAULT_API_URL, + data=body, + headers={"Content-Type": "application/json; charset=utf-8"}, + timeout=REQUEST_TIMEOUT, + ) + try: + data = resp.json() + except Exception: + data = None + + if resp.ok: + if isinstance(data, dict): + msg = data.get("message") or data.get("msg") or "" + code = data.get("code") + if isinstance(code, int) and code >= 400: + return False, msg or f"透传失败，HTTP码 {code}" + return True, msg or "已发送透传请求。" + return True, "已发送透传请求。" + + err_detail = "" + if isinstance(data, dict): + err_detail = data.get("message") or data.get("error") or data.get("msg") or "" + if not err_detail: + err_detail = resp.text + return False, f"HTTP {resp.status_code}: {err_detail}" + + try: + return await asyncio.to_thread(_post) + except Exception as e: + return False, f"{type(e).__name__}: {e}" + + +async def _handle_call_tool(name: str, arguments: Dict[str, Any]) -> list[TextContent]: + # 本地广播 + if name == "broadcast_message": + text, audio_url, user, speaker, queue = _parse_arguments(arguments or {}) + if not text and not audio_url: + return [_text_content("text 或 audio_url 至少需提供一个。")] + + payload: Dict[str, Any] = {"user": user} + if text: + payload["text"] = f"{speaker}\u8bf4\uff1a{text}" + if audio_url: + payload["audio"] = audio_url + if queue: + payload["queue"] = True + payload["queue_playback"] = True + payload["mode"] = "queue" + + ok, message = await _send_broadcast(payload) + prefix = "成功" if ok else "失败" + return [_text_content(f"{prefix}: {message}")] + + target = _aggregated_index.get(name) + if not target: + return [_text_content(f"未知工具: {name}")] + + server_id, tool_name = target + try: + success, result = await asyncio.to_thread(mcp_service.call_mcp_tool, server_id, tool_name, arguments or {}) + if not success: + return [_text_content(f"error: {result}")] + return _normalize_result(result) + except Exception as e: + return [_text_content(f"error: {type(e).__name__}: {e}")] + + +def _normalize_result(result: Any) -> List[TextContent]: + """ + 将上游返回的任意对象转换为 MCP 文本内容列表。 + """ + # 如果已经是 TextContent 或列表，直接返回 + try: + from mcp.types import TextContent + if isinstance(result, TextContent): + return [result] + except Exception: + pass + + if isinstance(result, list): + contents: List[TextContent] = [] + for item in result: + try: + if hasattr(item, "type") and getattr(item, "type", "") == "text" and hasattr(item, "text"): + contents.append(item) + continue + except Exception: + pass + try: + if isinstance(item, dict) and item.get("type") == "text": + contents.append(TextContent(type="text", text=str(item.get("text", "")))) # type: ignore + continue + except Exception: + pass + contents.append(_text_content(str(item))) + return contents + + return [_text_content(str(result))] + + +async def sse_endpoint(request): + # 为每个连接创建新的 Server 实例以支持并发 + local_server = Server(SERVER_NAME) + + # 注册工具处理程序 + local_server.list_tools()(_handle_list_tools) + local_server.call_tool()(_handle_call_tool) + + async with sse_transport.connect_sse(request.scope, request.receive, request._send) as (read_stream, write_stream): + await local_server.run(read_stream, write_stream, local_server.create_initialization_options()) + # 客户端断开时返回空响应，避免 NoneType 问题 + return Response() + + +routes = [ + Route(SSE_PATH, sse_endpoint, methods=["GET"]), + Mount(MSG_PATH, app=sse_transport.handle_post_message), +] + +app = Starlette(routes=routes) + + +def main(): + log.info(f"SSE MCP server started at http://{HOST}:{PORT}{SSE_PATH}") + log.info(f"Message endpoint mounted at {MSG_PATH}") + uvicorn.run(app, host=HOST, port=PORT, log_level="info") + + +if __name__ == "__main__": + try: + main() + 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zDUc7Uh1px(lb9EFQNCXNIAKRg0#)@WSAXp%*MAfEB)k0gwh}ziS{#S~9;V;-6e)Ps z{44UU`Kvc5k?a3*Me8}@&2Q{YY!g VYAKA_Ap9gkqzi^>*J#?s{2w`6AI|^) diff --git a/gui/flask_server.py b/gui/flask_server.py index 5f55f5d..6e77616 100644 --- a/gui/flask_server.py +++ b/gui/flask_server.py @@ -10,8 +10,17 @@ from flask_cors import CORS import requests import datetime import pytz -import logging -import uuid +import logging +import uuid +from urllib.parse import urlparse, urljoin +try: + from langchain_openai import ChatOpenAI + from langchain_core.messages import HumanMessage, SystemMessage, AIMessage +except Exception: + ChatOpenAI = None + HumanMessage = None + SystemMessage = None + AIMessage = None import fay_booter from tts import tts_voice @@ -101,21 +110,77 @@ def _as_bool(value): return value.strip().lower() in ("1", "true", "yes", "y", "on") return False -def _build_llm_url(base_url: str) -> str: - if not base_url: - return "" +def _build_llm_url(base_url: str) -> str: + if not base_url: + return "" url = base_url.rstrip("/") if url.endswith("/chat/completions"): return url if url.endswith("/v1"): return url + "/chat/completions" - return url + "/v1/chat/completions" - - - -def _build_embedding_url(base_url: str) -> str: - if not base_url: - return "" + return url + "/v1/chat/completions" + + +def _normalize_openai_content(content): + if content is None: + return "" + if isinstance(content, str): + return content + if isinstance(content, list): + parts = [] + for item in content: + if isinstance(item, dict): + text = item.get("text") + if text is not None: + parts.append(str(text)) + continue + if "content" in item: + parts.append(_normalize_openai_content(item.get("content"))) + continue + parts.append(str(item)) + return "".join(parts) + if isinstance(content, dict): + if "text" in content: + return _normalize_openai_content(content.get("text")) + if "content" in content: + return _normalize_openai_content(content.get("content")) + return str(content) + + +def _build_langchain_messages(messages): + normalized = [] + if isinstance(messages, str): + normalized.append(HumanMessage(content=messages)) + return normalized + if not isinstance(messages, list): + return normalized + for msg in messages: + if not isinstance(msg, dict): + continue + role = str(msg.get("role", "user")).strip().lower() + content = _normalize_openai_content(msg.get("content")) + if content is None: + content = "" + if role == "system": + normalized.append(SystemMessage(content=content)) + elif role == "assistant": + normalized.append(AIMessage(content=content)) + else: + normalized.append(HumanMessage(content=content)) + return normalized + + +def _safe_text_from_chunk(chunk): + if chunk is None: + return "" + value = getattr(chunk, "content", "") + return _normalize_openai_content(value) + + + +def _build_embedding_url(base_url: str) -> str: + if not base_url: + return "" url = base_url.rstrip("/") if url.endswith("/v1/embeddings") or url.endswith("/embeddings"): return url @@ -123,9 +188,20 @@ def _build_embedding_url(base_url: str) -> str: return url[:-len("/v1/chat/completions")] + "/v1/embeddings" if url.endswith("/chat/completions"): return url[:-len("/chat/completions")] + "/embeddings" - if url.endswith("/v1"): - return url + "/embeddings" - return url + "/v1/embeddings" + if url.endswith("/v1"): + return url + "/embeddings" + return url + "/v1/embeddings" + + +def _build_langchain_base_url(base_url: str) -> str: + if not base_url: + return "" + url = base_url.rstrip("/") + if url.endswith("/v1/chat/completions"): + return url[:-len("/chat/completions")] + if url.endswith("/chat/completions"): + return url[:-len("/chat/completions")] + return url @__app.route('/api/submit', methods=['post']) def api_submit(): @@ -371,61 +447,111 @@ def api_send_v1_chat_completions(): if not data: return jsonify({'error': 'missing request body'}) try: - model = data.get('model', 'fay') - if model == 'llm': - try: - config_util.load_config() - llm_url = _build_llm_url(config_util.gpt_base_url) - api_key = config_util.key_gpt_api_key - model_engine = config_util.gpt_model_engine - except Exception as exc: - return jsonify({'error': f'LLM config load failed: {exc}'}), 500 - - if not llm_url: - return jsonify({'error': 'LLM base_url is not configured'}), 500 - - payload = dict(data) - if payload.get('model') == 'llm' and model_engine: - payload['model'] = model_engine - - stream_requested = _as_bool(payload.get('stream', False)) - headers = {'Content-Type': 'application/json'} - if api_key: - headers['Authorization'] = f'Bearer {api_key}' - - try: - if stream_requested: - resp = requests.post(llm_url, headers=headers, json=payload, stream=True) - - def generate(): - try: - for chunk in resp.iter_content(chunk_size=8192): - if not chunk: - continue - yield chunk - finally: - resp.close() - - content_type = resp.headers.get("Content-Type", "text/event-stream") - if "charset=" not in content_type.lower(): - content_type = f"{content_type}; charset=utf-8" - return Response( - generate(), - status=resp.status_code, - content_type=content_type, - ) - - resp = requests.post(llm_url, headers=headers, json=payload, timeout=60) - content_type = resp.headers.get("Content-Type", "application/json") - if "charset=" not in content_type.lower(): - content_type = f"{content_type}; charset=utf-8" - return Response( - resp.content, - status=resp.status_code, - content_type=content_type, - ) - except Exception as exc: - return jsonify({'error': f'LLM request failed: {exc}'}), 500 + model = data.get('model', 'fay') + if model == 'llm': + if ChatOpenAI is None or HumanMessage is None: + return jsonify({'error': 'langchain_openai or langchain_core is not available'}), 500 + try: + config_util.load_config() + api_key = config_util.key_gpt_api_key + model_engine = config_util.gpt_model_engine + base_url = _build_langchain_base_url(config_util.gpt_base_url) + except Exception as exc: + return jsonify({'error': f'LLM config load failed: {exc}'}), 500 + + if not base_url: + return jsonify({'error': 'LLM base_url is not configured'}), 500 + + payload = dict(data) + stream_requested = _as_bool(payload.get('stream', False)) + model_name = model_engine or payload.get('model') + lc_messages = _build_langchain_messages(payload.get('messages', [])) + if not lc_messages: + return jsonify({'error': 'messages is required'}), 400 + + llm_kwargs = { + "model": model_name, + "base_url": base_url, + "api_key": api_key, + "streaming": bool(stream_requested), + } + if payload.get("temperature") is not None: + llm_kwargs["temperature"] = payload.get("temperature") + if payload.get("max_tokens") is not None: + llm_kwargs["max_tokens"] = payload.get("max_tokens") + model_kwargs = {} + if payload.get("top_p") is not None: + model_kwargs["top_p"] = payload.get("top_p") + if model_kwargs: + llm_kwargs["model_kwargs"] = model_kwargs + + try: + llm_client = ChatOpenAI(**llm_kwargs) + run_cfg = { + "tags": ["fay", "api", "model-llm"], + "metadata": {"entrypoint": "api_send_v1_chat_completions", "model_alias": "llm"}, + } + if stream_requested: + stream_id = "chatcmpl-" + str(uuid.uuid4()) + def generate(): + try: + for chunk in llm_client.stream(lc_messages, config=run_cfg): + text_piece = _safe_text_from_chunk(chunk) + if text_piece is None or text_piece == "": + continue + message = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model_name, + "choices": [ + { + "delta": {"content": text_piece}, + "index": 0, + "finish_reason": None + } + ] + } + yield f"data: {json.dumps(message, ensure_ascii=False)}\n\n" + final_message = { + "id": stream_id, + "object": "chat.completion.chunk", + "created": int(time.time()), + "model": model_name, + "choices": [ + { + "delta": {}, + "index": 0, + "finish_reason": "stop" + } + ] + } + yield f"data: {json.dumps(final_message, ensure_ascii=False)}\n\n" + yield "data: [DONE]\n\n" + finally: + pass + return Response(generate(), content_type="text/event-stream; charset=utf-8") + + ai_resp = llm_client.invoke(lc_messages, config=run_cfg) + answer_text = _normalize_openai_content(getattr(ai_resp, "content", "")) + return jsonify({ + "id": "chatcmpl-" + str(uuid.uuid4()), + "object": "chat.completion", + "created": int(time.time()), + "model": model_name, + "choices": [ + { + "index": 0, + "message": { + "role": "assistant", + "content": answer_text + }, + "finish_reason": "stop" + } + ] + }) + except Exception as exc: + return jsonify({'error': f'LLM request failed: {exc}'}), 500 last_content = "" username = "User" @@ -1099,31 +1225,97 @@ def api_toggle_microphone(): #消息透传接口 -@__app.route('/transparent-pass', methods=['post']) -def transparent_pass(): - try: - data = request.form.get('data') - if data is None: - data = request.get_json() - else: - data = json.loads(data) - username = data.get('user', 'User') - response_text = data.get('text', None) - audio_url = data.get('audio', None) - if response_text or audio_url: - # 新消息到达，立即中断该用户之前的所有处理（文本流+音频队列） - util.printInfo(1, username, f'[API中断] 新消息到达，完整中断用户 {username} 之前的所有处理') - util.printInfo(1, username, f'[API中断] 用户 {username} 的文本流和音频队列已清空，准备处理新消息') - interact = Interact('transparent_pass', 2, {'user': username, 'text': response_text, 'audio': audio_url, 'isend':True, 'isfirst':True}) - util.printInfo(1, username, '透传播放：{}，{}'.format(response_text, audio_url), time.time()) - success = fay_booter.feiFei.on_interact(interact) - if (success == 'success'): - return jsonify({'code': 200, 'message' : '成功'}) - return jsonify({'code': 500, 'message' : '未知原因出错'}) - except Exception as e: - return jsonify({'code': 500, 'message': f'出错: {e}'}), 500 - -# 清除记忆API +@__app.route('/transparent-pass', methods=['post']) +def transparent_pass(): + try: + data = request.form.get('data') + if data is None: + data = request.get_json(silent=True) or {} + else: + data = json.loads(data) + + if isinstance(data, dict): + nested_data = data.get('data') + if isinstance(nested_data, dict): + data = nested_data + elif isinstance(nested_data, str): + nested_data = nested_data.strip() + if nested_data: + try: + data = json.loads(nested_data) + except Exception: + pass + + if not isinstance(data, dict): + data = {} + + username = data.get('user', 'User') + response_text = data.get('text', None) + audio_url = data.get('audio', None) + if isinstance(audio_url, str): + audio_url = audio_url.strip() + if audio_url: + parsed_audio = urlparse(audio_url) + if not parsed_audio.scheme: + if audio_url.startswith('//'): + audio_url = 'http:' + audio_url + else: + base_url = '' + origin = (request.headers.get('Origin') or '').strip() + referer = (request.headers.get('Referer') or '').strip() + if origin: + parsed_origin = urlparse(origin) + if parsed_origin.scheme and parsed_origin.netloc: + base_url = f'{parsed_origin.scheme}://{parsed_origin.netloc}/' + if (not base_url) and referer: + parsed_referer = urlparse(referer) + if parsed_referer.scheme and parsed_referer.netloc: + base_url = f'{parsed_referer.scheme}://{parsed_referer.netloc}/' + if not base_url: + base_url = request.host_url + audio_url = urljoin(base_url, audio_url) + else: + audio_url = None + + queue_mode = _as_bool(data.get('queue', False)) + if not queue_mode: + queue_mode = _as_bool(data.get('queue_playback', data.get('enqueue', False))) + if not queue_mode: + queue_mode = str(data.get('mode', '')).strip().lower() == 'queue' + if not queue_mode: + queue_mode = _as_bool(data.get('qutue', False)) + + if response_text or audio_url: + if queue_mode: + interact = Interact('transparent_pass', 2, { + 'user': username, + 'text': response_text, + 'audio': audio_url, + 'isend': True, + 'isfirst': True, + 'no_reply': True, + 'queue': True, + 'queue_playback': True + }) + else: + util.printInfo(1, username, f'[\u0041\u0050\u0049\u4e2d\u65ad] \u65b0\u6d88\u606f\u5230\u8fbe\uff0c\u5b8c\u6574\u4e2d\u65ad\u7528\u6237 {username} \u4e4b\u524d\u7684\u6240\u6709\u5904\u7406') + util.printInfo(1, username, f'[\u0041\u0050\u0049\u4e2d\u65ad] \u7528\u6237 {username} \u7684\u6587\u672c\u6d41\u548c\u97f3\u9891\u961f\u5217\u5df2\u6e05\u7a7a\uff0c\u51c6\u5907\u5904\u7406\u65b0\u6d88\u606f') + interact = Interact('transparent_pass', 2, { + 'user': username, + 'text': response_text, + 'audio': audio_url, + 'isend': True, + 'isfirst': True + }) + + util.printInfo(1, username, '\u900f\u4f20\u64ad\u653e\uff1a{},{}'.format(response_text, audio_url), time.time()) + success = fay_booter.feiFei.on_interact(interact) + if success == 'success': + return jsonify({'code': 200, 'message': '\u6210\u529f'}) + + return jsonify({'code': 500, 'message': '\u672a\u77e5\u539f\u56e0\u51fa\u9519'}) + except Exception as e: + return jsonify({'code': 500, 'message': f'\u51fa\u9519: {e}'}), 500 @__app.route('/api/clear-memory', methods=['POST']) def api_clear_memory(): try: diff --git a/gui/static/images/Logo.png b/gui/static/images/Logo.png index 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--- a/main.py +++ b/main.py @@ -2,7 +2,13 @@ import os import sys -os.environ['PATH'] += os.pathsep + os.path.join(os.getcwd(), "test", "ovr_lipsync", "ffmpeg", "bin") +def _resolve_runtime_dir(): + if hasattr(sys, "_MEIPASS"): + return os.path.abspath(sys._MEIPASS) + return os.path.abspath(os.path.dirname(__file__)) + +_RUNTIME_DIR = _resolve_runtime_dir() +os.environ['PATH'] += os.pathsep + os.path.join(_RUNTIME_DIR, "test", "ovr_lipsync", "ffmpeg", "bin") def _preload_config_center(argv): for i, arg in enumerate(argv): diff --git a/requirements.txt b/requirements.txt index 7281e61..7859298 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,35 +1,35 @@ -requests -numpy -pyaudio~=0.2.11 -websockets~=10.4 -ws4py~=0.5.1 -PyQt5==5.15.10 -PyQt5-sip==12.13.0 -PyQtWebEngine==5.15.6 -flask~=3.0.0 -openpyxl~=3.0.9 -flask_cors~=3.0.10 -websocket-client -azure-cognitiveservices-speech -aliyun-python-sdk-core -simhash -pytz -gevent -edge_tts -pydub -tenacity==8.2.3 -pygame -scipy -flask-httpauth -opencv-python -psutil -langchain -langchain_openai -langgraph -bs4 -schedule -mcp -python-docx -python-pptx -chromadb +requests +numpy +pyaudio~=0.2.11 +websockets~=10.4 +ws4py~=0.5.1 +#PyQt5==5.15.10 +#PyQt5-sip==12.13.0 +#PyQtWebEngine==5.15.6 +flask~=3.0.0 +openpyxl~=3.0.9 +flask_cors~=3.0.10 +websocket-client +azure-cognitiveservices-speech +aliyun-python-sdk-core +simhash +pytz +gevent +edge_tts +pydub +tenacity==8.2.3 +pygame +scipy +flask-httpauth +opencv-python +psutil +langchain +langchain_openai +langgraph +bs4 +schedule +mcp +python-docx +python-pptx +chromadb sentence_transformers \ No newline at end of file diff --git a/test/ovr_lipsync/test_olipsync.py b/test/ovr_lipsync/test_olipsync.py index 7c94824..1ca0c06 100644 --- a/test/ovr_lipsync/test_olipsync.py +++ b/test/ovr_lipsync/test_olipsync.py @@ -1,91 +1,95 @@ import subprocess import time import os -os.environ['PATH'] += os.pathsep + os.path.join(os.getcwd(), "test", "ovr_lipsync", "ffmpeg", "bin") +import sys +_RUNTIME_DIR = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))) +if hasattr(sys, "_MEIPASS"): + _RUNTIME_DIR = os.path.abspath(sys._MEIPASS) +os.environ['PATH'] += os.pathsep + os.path.join(_RUNTIME_DIR, "test", "ovr_lipsync", "ffmpeg", "bin") from pydub import AudioSegment import json - -def list_files(dir_path): - for root, dirs, files in os.walk(dir_path): - for file in files: - print(os.path.join(root, file)) - -class LipSyncGenerator: + +def list_files(dir_path): + for root, dirs, files in os.walk(dir_path): + for file in files: + print(os.path.join(root, file)) + +class LipSyncGenerator: def __init__(self): self.viseme_em = [ "sil", "PP", "FF", "TH", "DD", "kk", "CH", "SS", "nn", "RR", "aa", "E", "ih", "oh", "ou"] self.viseme = [] - self.exe_path = os.path.join(os.getcwd(), "test", "ovr_lipsync", "ovr_lipsync_exe", "ProcessWAV.exe") - - def run_exe_and_get_output(self, arguments): - process = subprocess.Popen([self.exe_path] + arguments, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) - - while True: - output = process.stdout.readline() - if output == b'' and process.poll() is not None: - break - if output: - self.viseme.append(output.strip().decode()) - rc = process.poll() - return rc - - def filter(self, viseme): - new_viseme = [] - for v in self.viseme: - if v in self.viseme_em: - new_viseme.append(v) - return new_viseme - - def generate_visemes(self, wav_filepath): - if wav_filepath.endswith(".mp3"): - wav_filepath = self.convert_mp3_to_wav(wav_filepath) - arguments = ["--print-viseme-name", wav_filepath] - self.run_exe_and_get_output(arguments) - - return self.filter(self.viseme) - - def consolidate_visemes(self, viseme_list): - if not viseme_list: - return [] - - result = [] - current_viseme = viseme_list[0] - count = 1 - - for viseme in viseme_list[1:]: - if viseme == current_viseme: - count += 1 - else: - result.append({"Lip": current_viseme, "Time": count*33}) # Multiply by 10 for duration in ms - current_viseme = viseme - count = 1 - - # Add the last viseme to the result - result.append({"Lip": current_viseme, "Time": count*33}) # Multiply by 10 for duration in ms - - new_data = [] - for i in range(len(result)): - if result[i]['Time'] < 30: - if len(new_data) > 0: - new_data[-1]['Time'] += result[i]['Time'] - else: - new_data.append(result[i]) - return new_data - - def convert_mp3_to_wav(self, mp3_filepath): - audio = AudioSegment.from_mp3(mp3_filepath) - # 使用 set_frame_rate 方法设置采样率 - audio = audio.set_frame_rate(44100) - wav_filepath = mp3_filepath.rsplit(".", 1)[0] + ".wav" - audio.export(wav_filepath, format="wav") - return wav_filepath -if __name__ == "__main__": - start_time = time.time() - lip_sync_generator = LipSyncGenerator() - viseme_list = lip_sync_generator.generate_visemes("E:\\github\\Fay\\samples\\fay-man.wav") - print(viseme_list) - consolidated_visemes = lip_sync_generator.consolidate_visemes(viseme_list) - print(json.dumps(consolidated_visemes)) - print(time.time() - start_time) + self.exe_path = os.path.join(_RUNTIME_DIR, "test", "ovr_lipsync", "ovr_lipsync_exe", "ProcessWAV.exe") + + def run_exe_and_get_output(self, arguments): + process = subprocess.Popen([self.exe_path] + arguments, stdout=subprocess.PIPE, stderr=subprocess.STDOUT) + + while True: + output = process.stdout.readline() + if output == b'' and process.poll() is not None: + break + if output: + self.viseme.append(output.strip().decode()) + rc = process.poll() + return rc + + def filter(self, viseme): + new_viseme = [] + for v in self.viseme: + if v in self.viseme_em: + new_viseme.append(v) + return new_viseme + + def generate_visemes(self, wav_filepath): + if wav_filepath.endswith(".mp3"): + wav_filepath = self.convert_mp3_to_wav(wav_filepath) + arguments = ["--print-viseme-name", wav_filepath] + self.run_exe_and_get_output(arguments) + + return self.filter(self.viseme) + + def consolidate_visemes(self, viseme_list): + if not viseme_list: + return [] + + result = [] + current_viseme = viseme_list[0] + count = 1 + + for viseme in viseme_list[1:]: + if viseme == current_viseme: + count += 1 + else: + result.append({"Lip": current_viseme, "Time": count*33}) # Multiply by 10 for duration in ms + current_viseme = viseme + count = 1 + + # Add the last viseme to the result + result.append({"Lip": current_viseme, "Time": count*33}) # Multiply by 10 for duration in ms + + new_data = [] + for i in range(len(result)): + if result[i]['Time'] < 30: + if len(new_data) > 0: + new_data[-1]['Time'] += result[i]['Time'] + else: + new_data.append(result[i]) + return new_data + + def convert_mp3_to_wav(self, mp3_filepath): + audio = AudioSegment.from_mp3(mp3_filepath) + # 使用 set_frame_rate 方法设置采样率 + audio = audio.set_frame_rate(44100) + wav_filepath = mp3_filepath.rsplit(".", 1)[0] + ".wav" + audio.export(wav_filepath, format="wav") + return wav_filepath +if __name__ == "__main__": + start_time = time.time() + lip_sync_generator = LipSyncGenerator() + viseme_list = lip_sync_generator.generate_visemes("E:\\github\\Fay\\samples\\fay-man.wav") + print(viseme_list) + consolidated_visemes = lip_sync_generator.consolidate_visemes(viseme_list) + print(json.dumps(consolidated_visemes)) + print(time.time() - start_time) diff --git a/utils/config_util.py b/utils/config_util.py index 150b758..ff73537 100644 --- a/utils/config_util.py +++ b/utils/config_util.py @@ -278,11 +278,11 @@ def load_config(force_reload=False): root_config_json_exists = os.path.exists(default_config_json_path) root_config_complete = root_system_conf_exists and root_config_json_exists - # 构建system.conf和config.json的完整路径 - config_center_fallback = False - if using_config_center: - system_conf_path = cache_system_conf_path - config_json_path = cache_config_json_path + # 构建system.conf和config.json相关路径. + config_center_fallback = False + if using_config_center: + system_conf_path = cache_system_conf_path + config_json_path = cache_config_json_path else: if ( system_conf_path is None @@ -308,29 +308,34 @@ def load_config(force_reload=False): loaded_from_api = False api_attempted = False if using_config_center: - if explicit_config_center: - util.log(1, f"检测到配置中心参数，优先加载项目配置: {CONFIG_SERVER['PROJECT_ID']}") - else: - util.log(1, f"未检测到本地system.conf或config.json，尝试从配置中心加载配置: {CONFIG_SERVER['PROJECT_ID']}") - api_config = load_config_from_api(CONFIG_SERVER['PROJECT_ID']) + if explicit_config_center: + util.log(1, f"检测到配置中心参数，优先加载项目配置: {CONFIG_SERVER['PROJECT_ID']}") + else: + util.log(1, f"未检测到本地system.conf或config.json，尝试从配置中心加载配置: {CONFIG_SERVER['PROJECT_ID']}") + api_config = load_config_from_api(CONFIG_SERVER['PROJECT_ID']) api_attempted = True if api_config: - util.log(1, "成功从配置中心加载配置") + util.log(1, "成功从配置中心加载配置") system_config = api_config['system_config'] config = api_config['config'] loaded_from_api = True if config_center_fallback: _bootstrap_loaded_from_api = True - # 缓存API配置到本地文件 - system_conf_path = cache_system_conf_path - config_json_path = cache_config_json_path - save_api_config_to_local(api_config, system_conf_path, config_json_path) - forced_loaded = True + # 将配置中心配置缓存到本地文件. + system_conf_path = cache_system_conf_path + config_json_path = cache_config_json_path + save_api_config_to_local( + api_config, + system_conf_path, + config_json_path, + save_config_json=not os.path.exists(config_json_path) + ) + forced_loaded = True _warn_public_config_once() else: - util.log(2, "配置中心加载失败，尝试使用缓存配置") + util.log(2, "配置中心加载失败，尝试使用缓存配置") sys_conf_exists = os.path.exists(system_conf_path) config_json_exists = os.path.exists(config_json_path) @@ -339,38 +344,48 @@ def load_config(force_reload=False): if (not sys_conf_exists or not config_json_exists) and not forced_loaded: if using_config_center: if not api_attempted: - util.log(1, "配置中心缓存缺失，尝试从配置中心加载配置...") + util.log(1, "配置中心缓存缺失，尝试从配置中心加载配置...") api_config = load_config_from_api(CONFIG_SERVER['PROJECT_ID']) api_attempted = True if api_config: - util.log(1, "成功从配置中心加载配置") + util.log(1, "成功从配置中心加载配置") system_config = api_config['system_config'] config = api_config['config'] loaded_from_api = True if config_center_fallback: _bootstrap_loaded_from_api = True - # 缓存API配置到本地文件 - system_conf_path = cache_system_conf_path - config_json_path = cache_config_json_path - save_api_config_to_local(api_config, system_conf_path, config_json_path) + # 将配置中心配置缓存到本地文件. + system_conf_path = cache_system_conf_path + config_json_path = cache_config_json_path + save_api_config_to_local( + api_config, + system_conf_path, + config_json_path, + save_config_json=not os.path.exists(config_json_path) + ) _warn_public_config_once() else: - # 使用提取的项目ID或全局项目ID - util.log(1, f"本地配置文件不完整（{system_conf_path if not sys_conf_exists else ''}{'和' if not sys_conf_exists and not config_json_exists else ''}{config_json_path if not config_json_exists else ''}不存在），尝试从API加载配置...") - api_config = load_config_from_api(CONFIG_SERVER['PROJECT_ID']) + # 使用项目配置或全局项目配置作为回退来源. + util.log(1, f"本地配置文件不完整，尝试从API加载配置...") + api_config = load_config_from_api(CONFIG_SERVER['PROJECT_ID']) if api_config: - util.log(1, "成功从配置中心加载配置") + util.log(1, "成功从配置中心加载配置") system_config = api_config['system_config'] config = api_config['config'] loaded_from_api = True - # 缓存API配置到本地文件 - system_conf_path = cache_system_conf_path - config_json_path = cache_config_json_path - save_api_config_to_local(api_config, system_conf_path, config_json_path) + # 将配置中心配置缓存到本地文件. + system_conf_path = cache_system_conf_path + config_json_path = cache_config_json_path + save_api_config_to_local( + api_config, + system_conf_path, + config_json_path, + save_config_json=not os.path.exists(config_json_path) + ) _warn_public_config_once() @@ -378,17 +393,17 @@ def load_config(force_reload=False): config_json_exists = os.path.exists(config_json_path) if using_config_center and (not sys_conf_exists or not config_json_exists): if _last_loaded_config is not None and _last_loaded_from_api: - util.log(2, "配置中心缓存不可用，继续使用内存中的配置") + util.log(2, "配置中心缓存不可用，继续使用内存中的配置") return _last_loaded_config if config_center_fallback and using_config_center and (not sys_conf_exists or not config_json_exists): cache_ready = os.path.exists(cache_system_conf_path) and os.path.exists(cache_config_json_path) if cache_ready: - util.log(2, "配置中心不可用，回退使用缓存配置") + util.log(2, "配置中心不可用，回退使用缓存配置") using_config_center = False system_conf_path = cache_system_conf_path config_json_path = cache_config_json_path else: - util.log(2, "配置中心不可用，回退使用本地配置文件") + util.log(2, "配置中心不可用，回退使用本地配置文件") using_config_center = False system_conf_path = default_system_conf_path config_json_path = default_config_json_path @@ -497,31 +512,33 @@ def load_config(force_reload=False): return config_dict -def save_api_config_to_local(api_config, system_conf_path, config_json_path): - """ - 将API加载的配置保存到本地文件 +def save_api_config_to_local(api_config, system_conf_path, config_json_path, save_config_json=True): + """ + Persist API config to local files. - Args: - api_config: API加载的配置字典 - system_conf_path: system.conf文件路径 - config_json_path: config.json文件路径 + Args: + api_config: API response dict. + system_conf_path: Path to system.conf. + config_json_path: Path to config.json. + save_config_json: Whether to write config.json. """ try: - # 确保目录存在 - os.makedirs(os.path.dirname(system_conf_path), exist_ok=True) - os.makedirs(os.path.dirname(config_json_path), exist_ok=True) - - # 保存system.conf - with open(system_conf_path, 'w', encoding='utf-8') as f: - api_config['system_config'].write(f) - - # 保存config.json - with codecs.open(config_json_path, 'w', encoding='utf-8') as f: - json.dump(api_config['config'], f, ensure_ascii=False, indent=4) - - util.log(1, f"已将配置中心配置缓存到本地文件: {system_conf_path} 和 {config_json_path}") - except Exception as e: - util.log(2, f"保存配置中心配置缓存到本地文件时出错: {str(e)}") + # 确保目录存在. + os.makedirs(os.path.dirname(system_conf_path), exist_ok=True) + os.makedirs(os.path.dirname(config_json_path), exist_ok=True) + + # 始终刷新 system.conf. + with open(system_conf_path, 'w', encoding='utf-8') as f: + api_config['system_config'].write(f) + + # 默认只在首次下载时保存config.json. + if save_config_json: + with codecs.open(config_json_path, 'w', encoding='utf-8') as f: + json.dump(api_config['config'], f, ensure_ascii=False, indent=4) + + util.log(1, f"已将配置中心配置缓存到本地文件: {system_conf_path} 和 {config_json_path}") + except Exception as e: + util.log(2, f"保存配置中心配置到本地文件时出错: {str(e)}") @synchronized def save_config(config_data): diff --git a/utils/stream_text_processor.py b/utils/stream_text_processor.py index fd0df5c..d13464e 100644 --- a/utils/stream_text_processor.py +++ b/utils/stream_text_processor.py @@ -1,4 +1,5 @@ -# -*- coding: utf-8 -*- +# -*- coding: utf-8 -*- +import re import time from utils import util from core import stream_manager @@ -27,6 +28,20 @@ class StreamTextProcessor: self.max_cache_size = max_cache_size # 常用中英文分句标点（UTF-8） self.punctuation_marks = ["，", "。", "；", "：", "、", "！", "？", ".", "!", "?", "\n"] + self.punctuation_mark_set = set(self.punctuation_marks) + self.url_regex_list = [ + re.compile( + r"(?i)\b(?:https?://|ftp://|file://|www\.)[^\s\u3002\uff01\uff1f\u3001\uff0c\uff1b\uff1a<>'\"\[\]\(\)\{\}]+" + ), + re.compile( + r"(?i)\b[a-z0-9](?:[a-z0-9-]{0,61}[a-z0-9])?" + r"(?:\.[a-z0-9](?:[a-z0-9-]{0,61}[a-z0-9])?)+" + r"(?::\d{2,5})?" + r"(?:/[^\s\u3002\uff01\uff1f\u3001\uff0c\uff1b\uff1a<>'\"\[\]\(\)\{\}]*)?" + r"(?:\?[^\s\u3002\uff01\uff1f\u3001\uff0c\uff1b\uff1a<>'\"\[\]\(\)\{\}]*)?" + r"(?:#[^\s\u3002\uff01\uff1f\u3001\uff0c\uff1b\uff1a<>'\"\[\]\(\)\{\}]*)?" + ), + ] def process_stream_text(self, text, username, is_qa=False, session_type="stream"): """ @@ -87,7 +102,7 @@ class StreamTextProcessor: # 动态缓存大小检查 if len(accumulated_text) > self.max_cache_size: - util.log(1, f"处理过程中缓存溢出，强制发送剩余文本") + util.log(1, "处理过程中缓存溢出，强制发送剩余文本") break iteration_count += 1 @@ -178,20 +193,95 @@ class StreamTextProcessor: """ try: indices = [] - for punct in self.punctuation_marks: - try: - index = text.find(punct) - if index != -1: - indices.append(index) - except Exception as e: - util.log(1, f"查找标点符号 '{punct}' 时出错: {str(e)}") + url_spans = self._find_url_spans(text) + for index, ch in enumerate(text): + if ch not in self.punctuation_mark_set: continue - - return sorted([i for i in indices if i != -1]) + if self._is_in_spans(index, url_spans): + continue + if ch == "." and self._is_protected_dot(text, index): + continue + indices.append(index) + return indices except Exception as e: util.log(1, f"查找标点符号时出错: {str(e)}") return [] + def _find_url_spans(self, text): + spans = [] + for regex in self.url_regex_list: + for match in regex.finditer(text): + start, end = match.span() + if end > start: + spans.append((start, end)) + if not spans: + return [] + spans.sort(key=lambda item: item[0]) + merged = [spans[0]] + for start, end in spans[1:]: + last_start, last_end = merged[-1] + if start <= last_end: + merged[-1] = (last_start, max(last_end, end)) + else: + merged.append((start, end)) + return merged + + @staticmethod + def _is_in_spans(index, spans): + for start, end in spans: + if start <= index < end: + return True + if index < start: + break + return False + + def _is_protected_dot(self, text, index): + """ + 判断英文句点是否位于不应截断的 token 内（如版本号、URL、域名等）。 + """ + try: + prev_char = text[index - 1] if index > 0 else "" + next_char = text[index + 1] if (index + 1) < len(text) else "" + + # 数字点位：1.2 / 3.14 / 192.168.1.1 + if prev_char.isdigit() and next_char.isdigit(): + return True + + token = self._extract_token_around(text, index).lower() + if not token: + return False + + # URL 写法 + if "://" in token or token.startswith("www."): + return True + + # 版本号写法：v1.2.3 / 1.2.3 + if re.match(r"^[a-z]*\d+\.\d+(\.\d+)*[a-z]*$", token): + return True + + # 域名/主机名（可带路径） + if re.match(r"^[a-z0-9-]+(\.[a-z0-9-]+)+(/\S*)?$", token): + return True + + return False + except Exception: + return False + + def _extract_token_around(self, text, index): + """ + 提取句点所在连续 token（按空白与中英文标点分隔）。 + """ + separators = set(" \t\r\n\"'()[]{}<>,!?;:" + "\uFF0C\u3002\uFF01\uFF1F\uFF1B\uFF1A\u3001") + left = index + right = index + 1 + + while left > 0 and text[left - 1] not in separators: + left -= 1 + while right < len(text) and text[right] not in separators: + right += 1 + + return text[left:right] + def _send_fallback_text(self, text, username, state_manager, conversation_id): """ 备用发送方案：直接发送完整文本（含首尾标记）