chore: remove DashScope placeholder defaults, sync docs, and clean up debug prints

INFERENCE_GUIDE.md

@@ -1,10 +1,13 @@
 # Boogu Inference Guide
 
-This document describes the current Boogu inference entry point for
-text-to-image (T2I) generation and text/image-to-image (TI2I) editing:
+This document describes the Boogu inference entry points:
+
+- `inference.py` for Base/Edit models (T2I and TI2I)
+- `inference_turbo.py` for Turbo/Edit-Turbo models
 
 ```bash
 inference.py
+inference_turbo.py
 ```
 
 Many ready-to-run examples are available in:
@@ -21,6 +24,19 @@ the built-in instruction reasoner / rewriter. For most users, the fastest way to
 start is to copy one of these scripts and adjust only the model path, prompt,
 input image paths, device settings, and output name.
 
+Minimal Turbo example:
+
+```bash
+export device="cuda:0"
+
+python inference_turbo.py \
+  --pretrained_pipeline_name_or_path "models/Boogu-Image-0.1-Turbo" \
+  --instruction "A scenic mountain landscape in warm golden light" \
+  --height 1024 --width 1024 \
+  --output_image_path "outputs/test_turbo/out_1.png" \
+  --device "$device"
+```
+
 Most demo scripts also set:
 
 ```bash

README.md

@@ -143,7 +143,7 @@ conda create -y -n boogu python=3.10
 conda activate boogu
 # Instal necessary dependencies
 # PyTorch up to 2.11.0 with CUDA up to 12.8 is supported
-# Check `requirements/<torch>_<cuda>.txt`
+# Check `requirements/<torch>-<cuda>.txt`, for example `requirements/torch2.7-cu126.txt`
 pip install -r requirements/torch2.7-cu126.txt
 pip install -e .
 python utils/get_flash_attn.py
@@ -153,7 +153,9 @@ or
 
 ```bash
 bash quick_start.sh
-conda activate boogu
+# quick_start.sh may create boogu1/boogu2... if boogu already exists
+# Use the exact command printed at the end of quick_start.sh
+conda activate <env_name_printed_by_quick_start>
 ```
 
 ### Download Checkpoints
@@ -183,7 +185,7 @@ models/
     └── vae
 ```
 
-Then point inference to the local path via `--model models/Boogu-Image-0.1-Base`.
+Then point inference to the local path via `--pretrained_pipeline_name_or_path models/Boogu-Image-0.1-Base`.
 
 ### Flash Attention
 

README_CN.md

@@ -148,7 +148,7 @@ conda create -y -n boogu python=3.10
 conda activate boogu
 # 安装必要的依赖
 # 支持 PyTorch 最高 2.11.0，CUDA 最高 12.8
-# 查看 `requirements/<torch>_<cuda>.txt`
+# 查看 `requirements/<torch>-<cuda>.txt`，例如 `requirements/torch2.7-cu126.txt`
 pip install -r requirements/torch2.7-cu126.txt
 pip install -e .
 python utils/get_flash_attn.py
@@ -158,7 +158,9 @@ python utils/get_flash_attn.py
 
 ```bash
 bash quick_start.sh
-conda activate boogu
+# 如果 boogu 已存在，quick_start.sh 可能自动创建 boogu1/boogu2...
+# 请使用 quick_start.sh 结束时打印出的激活命令
+conda activate <quick_start.sh输出的环境名>
 ```
 
 ### 下载模型权重
@@ -172,6 +174,7 @@ pip install -U "huggingface_hub[cli]"
 huggingface-cli download Boogu/Boogu-Image-0.1-Base --local-dir models/Boogu-Image-0.1-Base
 huggingface-cli download Boogu/Boogu-Image-0.1-Turbo --local-dir models/Boogu-Image-0.1-Turbo
 huggingface-cli download Boogu/Boogu-Image-0.1-Edit --local-dir models/Boogu-Image-0.1-Edit
+huggingface-cli download Boogu/Boogu-Image-0.1-Edit-Turbo --local-dir models/Boogu-Image-0.1-Edit-Turbo
 ```
 
 下载后的目录结构示例：
@@ -187,7 +190,7 @@ models/
     └── vae
 ```
 
-然后通过 `--model models/Boogu-Image-0.1-Base` 指向本地路径进行推理。
+然后通过 `--pretrained_pipeline_name_or_path models/Boogu-Image-0.1-Base` 指向本地路径进行推理。
 
 ### Flash Attention
 

boogu/pipelines/boogu/pipeline_boogu.py

@@ -2078,7 +2078,7 @@ def _polish_instructions_with_remote_rewriter(
         ori_text: Union[str, List[str]],
         input_image_paths: Optional[Union[List[List[str]], List[str]]] = None,
         dashscope_base_http_api_url: str = "https://dashscope.aliyuncs.com/api/v1",
-        dashscope_api_key: str = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxx",
+        dashscope_api_key: Optional[str] = None,
         remote_model: str = "qwen-vl-max-latest",
         MAX_TRIES: int = 3,
     ) -> List[str]:
@@ -2152,7 +2152,7 @@ def _rewrite_text_instruction(
         use_dashscope_remote_rewriting: bool = False,
         dashscope_remote_rewriting_model: str = "qwen-vl-max-latest",
         dashscope_base_http_api_url: str = "https://dashscope.aliyuncs.com/api/v1",
-        dashscope_api_key: str = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxx",
+        dashscope_api_key: Optional[str] = None,
     ):
 
         max_images_per_sample = 0
@@ -2287,7 +2287,7 @@ def encode_instruction(
         use_dashscope_remote_rewriting: bool = False,
         dashscope_remote_rewriting_model: str = "qwen-vl-max-latest",
         dashscope_base_http_api_url: str = "https://dashscope.aliyuncs.com/api/v1",
-        dashscope_api_key: str = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxx",
+        dashscope_api_key: Optional[str] = None,
         system_prompt_follows_task_type: bool = False,
         task_type: str = "ti2i",
     ) -> Tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
@@ -2695,7 +2695,7 @@ def __call__(
         use_dashscope_remote_rewriting: bool = False,
         dashscope_remote_rewriting_model: str = "qwen-vl-max-latest",
         dashscope_base_http_api_url: str = "https://dashscope.aliyuncs.com/api/v1",
-        dashscope_api_key: str = "sk-xxxxxxxxxxxxxxxxxxxxxxxxxx",
+        dashscope_api_key: Optional[str] = None,
         system_prompt_follows_task_type: bool = False,
         ### Momentum Config
         use_boosted_orthogonal_guidance: bool = False,

boogu/schedulers/scheduling_flow_match_euler_discrete_time_shifting.py

@@ -234,20 +234,9 @@ def set_timesteps(
 
             timesteps = t_arr
 
-        # ######################debug############################
-        # print(f">> time_shift_version:  {self.config.time_shift_version}")
-        # print(f">> timesteps:  {timesteps}")
-        # print(f">> self.time_shift_v2_scaling_factor:  {self.time_shift_v2_scaling_factor}")
-        # #######################################################
-
         timesteps = torch.from_numpy(timesteps).to(dtype=torch.float32, device=device)
         _timesteps = torch.cat([timesteps, torch.ones(1, device=timesteps.device)])
 
-        # ######################debug############################
-        # print(f">> len _timesteps:  {len(_timesteps)}")
-        # print(f">> _timesteps:  {_timesteps}")
-        # #######################################################
-
         self.timesteps = timesteps
         self._timesteps = _timesteps
         self._step_index = None

demo_scripts/demo_ti2i_remote_reasoning.sh

@@ -44,7 +44,15 @@ use_rewrite_text_instruction=True
 use_dashscope_remote_rewriting=True
 dashscope_remote_rewriting_model="qwen-vl-max-latest"
 dashscope_base_http_api_url="https://dashscope.aliyuncs.com/api/v1"
-dashscope_api_key="sk-xxxxxxxxxxxxxxxxxxxxxxxxxx"
+# Read the DashScope API key from the environment instead of hardcoding a placeholder.
+# Export it before running this script, e.g.:
+#   export DASHSCOPE_API_KEY="sk-your-real-key-here"
+if [ -z "${DASHSCOPE_API_KEY:-}" ]; then
+    echo "Error: DASHSCOPE_API_KEY is not set. Export it before running this script, e.g.:" >&2
+    echo "  export DASHSCOPE_API_KEY=\"sk-your-real-key-here\"" >&2
+    exit 1
+fi
+dashscope_api_key="${DASHSCOPE_API_KEY}"
 
 save_rewritten_instruction=True
 save_rewritten_instruction_path="outputs/${experiment_name}/${case_name}_rewritten_instruction.json"

inference.py

@@ -448,8 +448,8 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument(
         "--dashscope_api_key",
         type=str,
-        default="sk-xxxxxxxxxxxxxxxxxxxxxxxxxx",
-        help="The api key for dashscope. Only takes effect when `use_rewrite_text_instruction` is True and `use_dashscope_remote_rewriting` is True.",
+        default=None,
+        help="The api key for dashscope. Only takes effect when `use_rewrite_text_instruction` is True and `use_dashscope_remote_rewriting` is True. Must be set to a valid key when `use_dashscope_remote_rewriting=True`; the pipeline will assert and refuse to run with the placeholder value.",
     )
 
     parser.add_argument(

inference_turbo.py

@@ -448,8 +448,8 @@ def parse_args() -> argparse.Namespace:
     parser.add_argument(
         "--dashscope_api_key",
         type=str,
-        default="sk-xxxxxxxxxxxxxxxxxxxxxxxxxx",
-        help="The api key for dashscope. Only takes effect when `use_rewrite_text_instruction` is True and `use_dashscope_remote_rewriting` is True.",
+        default=None,
+        help="The api key for dashscope. Only takes effect when `use_rewrite_text_instruction` is True and `use_dashscope_remote_rewriting` is True. Must be set to a valid key when `use_dashscope_remote_rewriting=True`; the pipeline will assert and refuse to run with the placeholder value.",
     )
 
     parser.add_argument(