Refactor backend configuration management and update environment settings

- Replace the `config.py` module with a new `settings.py` to streamline environment variable management, focusing on database, CORS, and TURN settings.
- Update references throughout the backend codebase to use the new `settings` module instead of the deprecated `config`.
- Modify the `.env.example` file to reflect the new configuration approach, indicating that model provider credentials should be maintained separately.
- Enhance the `AssistantConfig` model to clarify the source of runtime connection information, ensuring it is injected from model resources rather than relying on defaults from the environment.
- Introduce new user scripts for audio and video management in the Tampermonkey environment, enhancing WebRTC capabilities.

backend/services/pipecat/pipeline.py

@@ -11,7 +11,6 @@ import base64
 from io import BytesIO
 from uuid import uuid4
 
-import config
 from loguru import logger
 from models import AssistantConfig
 from openai import AsyncOpenAI
@@ -77,6 +76,12 @@ VISION_ANALYSIS_SYSTEM_PROMPT = (
 )
 
 
+def _require(value: str, label: str) -> str:
+    if value:
+        return value
+    raise ValueError(f"缺少模型资源配置: {label}")
+
+
 def _vision_uses_main_llm(cfg: AssistantConfig) -> bool:
     """模型自己支持图片时,沿用 Pipecat 的同上下文视觉工具路径。"""
     return not cfg.vision_model_resource_id and cfg.llm_support_image_input
@@ -107,12 +112,12 @@ async def _analyze_image_with_vision_model(
     extra_body = cfg.vision_llm_values.get("extraBody")
     extra = {"extra_body": extra_body} if isinstance(extra_body, dict) else {}
     client = AsyncOpenAI(
-        api_key=cfg.vision_llm_api_key or config.LLM_API_KEY,
-        base_url=cfg.vision_llm_base_url or config.LLM_BASE_URL,
+        api_key=_require(cfg.vision_llm_api_key, "Vision LLM apiKey"),
+        base_url=_require(cfg.vision_llm_base_url, "Vision LLM apiUrl"),
     )
     try:
         response = await client.chat.completions.create(
-            model=cfg.vision_model or config.LLM_MODEL,
+            model=_require(cfg.vision_model, "Vision LLM modelId"),
             messages=[
                 {"role": "system", "content": VISION_ANALYSIS_SYSTEM_PROMPT},
                 {
@@ -665,9 +670,9 @@ async def run_pipeline(
         target = await engine.route(
             wf_state["current"],
             history,
-            api_key=cfg.llm_api_key or config.LLM_API_KEY,
-            base_url=cfg.llm_base_url or config.LLM_BASE_URL,
-            model=cfg.model or config.LLM_MODEL,
+            api_key=_require(cfg.llm_api_key, "LLM apiKey"),
+            base_url=_require(cfg.llm_base_url, "LLM apiUrl"),
+            model=_require(cfg.model, "LLM modelId"),
         )
         if target and target != wf_state["current"]:
             logger.info(f"文本兜底触发转移 → {engine.name(target)}")