black python formatter applyed

llama_bringup/launch/base.launch.py

@@ -41,25 +41,25 @@ def run_llama(context: LaunchContext, embedding, reranking):
             "n_ctx": LaunchConfiguration("n_ctx", default=512),
             "n_batch": LaunchConfiguration("n_batch", default=2048),
             "n_ubatch": LaunchConfiguration("n_batch", default=512),
-
+            # GPU params
             "n_gpu_layers": LaunchConfiguration("n_gpu_layers", default=0),
             "split_mode": LaunchConfiguration("split_mode", default="layer"),
             "main_gpu": LaunchConfiguration("main_gpu", default=0),
             "tensor_split": LaunchConfiguration("tensor_split", default="[0.0]"),
-
+            # attn params
             "grp_attn_n": LaunchConfiguration("grp_attn_n", default=1),
             "grp_attn_w": LaunchConfiguration("grp_attn_w", default=512),
-
+            # rope params
             "rope_freq_base": LaunchConfiguration("rope_freq_base", default=0.0),
             "rope_freq_scale": LaunchConfiguration("rope_freq_scale", default=0.0),
             "rope_scaling_type": LaunchConfiguration("rope_scaling_type", default=""),
-
+            # yarn params
             "yarn_ext_factor": LaunchConfiguration("yarn_ext_factor", default=-1.0),
             "yarn_attn_factor": LaunchConfiguration("yarn_attn_factor", default=1.0),
             "yarn_beta_fast": LaunchConfiguration("yarn_beta_fast", default=32.0),
             "yarn_beta_slow": LaunchConfiguration("yarn_beta_slow", default=1.0),
             "yarn_orig_ctx": LaunchConfiguration("yarn_orig_ctx", default=0),
-
+            # bool params
             "embedding": embedding,
             "reranking": reranking,
             "logits_all": LaunchConfiguration("logits_all", default=False),
@@ -68,44 +68,67 @@ def run_llama(context: LaunchContext, embedding, reranking):
             "warmup": LaunchConfiguration("warmup", default=True),
             "check_tensors": LaunchConfiguration("check_tensors", default=False),
             "flash_attn": LaunchConfiguration("flash_attn", default=False),
-
+            # cache params
             "no_kv_offload": LaunchConfiguration("no_kv_offload", default=False),
             "cache_type_k": LaunchConfiguration("cache_type_k", default="f16"),
             "cache_type_v": LaunchConfiguration("cache_type_v", default="f16"),
-
+            # CPU params
             "n_threads": LaunchConfiguration("n_threads", default=1),
             "cpu_mask": LaunchConfiguration("cpu_mask", default=""),
             "cpu_range": LaunchConfiguration("cpu_range", default=""),
             "priority": LaunchConfiguration("priority", default="normal"),
             "strict_cpu": LaunchConfiguration("strict_cpu", default=False),
             "poll": LaunchConfiguration("poll", default=50),
-
+            # batch CPU params
             "n_threads_batch": LaunchConfiguration("n_threads_batch", default=1),
             "cpu_mask_batch": LaunchConfiguration("cpu_mask_batch", default=""),
             "cpu_range_batch": LaunchConfiguration("cpu_range_batch", default=""),
             "priority_batch": LaunchConfiguration("priority_batch", default="normal"),
             "strict_cpu_batch": LaunchConfiguration("strict_cpu_batch", default=False),
             "poll_batch": LaunchConfiguration("poll_batch", default=50),
-
+            # switch context params
             "n_predict": LaunchConfiguration("n_predict", default=128),
             "n_keep": LaunchConfiguration("n_keep", default=-1),
-
+            # paths params
             "model": LaunchConfiguration("model", default=""),
-            "lora_adapters": ParameterValue(LaunchConfiguration("lora_adapters", default=[""]), value_type=List[str]),
-            "lora_adapters_scales": ParameterValue(LaunchConfiguration("lora_adapters_scales", default=[0.0]), value_type=List[float]),
+            "lora_adapters": ParameterValue(
+                LaunchConfiguration("lora_adapters", default=[""]), value_type=List[str]
+            ),
+            "lora_adapters_scales": ParameterValue(
+                LaunchConfiguration("lora_adapters_scales", default=[0.0]),
+                value_type=List[float],
+            ),
             "mmproj": LaunchConfiguration("mmproj", default=""),
             "numa": LaunchConfiguration("numa", default="none"),
             "pooling_type": LaunchConfiguration("pooling_type", default=""),
-
-            "prefix": ParameterValue(LaunchConfiguration("prefix", default=""), value_type=str),
-            "suffix": ParameterValue(LaunchConfiguration("suffix", default=""), value_type=str),
-            "stopping_words": ParameterValue(LaunchConfiguration("stopping_words", default=[""]), value_type=List[str]),
-            "image_prefix": ParameterValue(LaunchConfiguration("image_prefix", default=""), value_type=str),
-            "image_suffix": ParameterValue(LaunchConfiguration("image_suffix", default=""), value_type=str),
-            "image_text": ParameterValue(LaunchConfiguration("image_text", default="<image>"), value_type=str),
-
-            "system_prompt": ParameterValue(LaunchConfiguration("system_prompt", default=""), value_type=str),
-            "system_prompt_file": ParameterValue(LaunchConfiguration("system_prompt_file", default=""), value_type=str),
+            # prefix/suffix
+            "prefix": ParameterValue(
+                LaunchConfiguration("prefix", default=""), value_type=str
+            ),
+            "suffix": ParameterValue(
+                LaunchConfiguration("suffix", default=""), value_type=str
+            ),
+            "stopping_words": ParameterValue(
+                LaunchConfiguration("stopping_words", default=[""]),
+                value_type=List[str],
+            ),
+            "image_prefix": ParameterValue(
+                LaunchConfiguration("image_prefix", default=""), value_type=str
+            ),
+            "image_suffix": ParameterValue(
+                LaunchConfiguration("image_suffix", default=""), value_type=str
+            ),
+            "image_text": ParameterValue(
+                LaunchConfiguration("image_text", default="<image>"), value_type=str
+            ),
+            # prompt params
+            "system_prompt": ParameterValue(
+                LaunchConfiguration("system_prompt", default=""), value_type=str
+            ),
+            "system_prompt_file": ParameterValue(
+                LaunchConfiguration("system_prompt_file", default=""), value_type=str
+            ),
+            # debug
             "debug": LaunchConfiguration("debug", default=True),
         }
 
@@ -123,32 +146,36 @@ def run_llama(context: LaunchContext, embedding, reranking):
             name=llama_node_name,
             namespace="llama",
             parameters=[params],
-            condition=UnlessCondition(PythonExpression(
-                [LaunchConfiguration("use_llava")]))
+            condition=UnlessCondition(
+                PythonExpression([LaunchConfiguration("use_llava")])
+            ),
         ), Node(
             package="llama_ros",
             executable="llava_node",
             name="llava_node",
             namespace="llama",
             parameters=[params],
-            condition=IfCondition(PythonExpression(
-                [LaunchConfiguration("use_llava")]))
+            condition=IfCondition(PythonExpression([LaunchConfiguration("use_llava")])),
         )
 
     embedding = LaunchConfiguration("embedding")
     embedding_cmd = DeclareLaunchArgument(
         "embedding",
         default_value="False",
-        description="Whether the model is an embedding model")
+        description="Whether the model is an embedding model",
+    )
 
     reranking = LaunchConfiguration("reranking")
     reranking_cmd = DeclareLaunchArgument(
         "reranking",
         default_value="False",
-        description="Whether the model is an reranking model")
-
-    return LaunchDescription([
-        embedding_cmd,
-        reranking_cmd,
-        OpaqueFunction(function=run_llama, args=[embedding, reranking])
-    ])
+        description="Whether the model is an reranking model",
+    )
+
+    return LaunchDescription(
+        [
+            embedding_cmd,
+            reranking_cmd,
+            OpaqueFunction(function=run_llama, args=[embedding, reranking]),
+        ]
+    )

llama_bringup/launch/minicpm-2.6.launch.py

@@ -28,7 +28,14 @@
 
 
 def generate_launch_description():
-    return LaunchDescription([
-        create_llama_launch_from_yaml(os.path.join(
-            get_package_share_directory("llama_bringup"), "models", "MiniCPM-2.6.yaml"))
-    ])
+    return LaunchDescription(
+        [
+            create_llama_launch_from_yaml(
+                os.path.join(
+                    get_package_share_directory("llama_bringup"),
+                    "models",
+                    "MiniCPM-2.6.yaml",
+                )
+            )
+        ]
+    )

llama_bringup/launch/spaetzle.launch.py

@@ -28,7 +28,14 @@
 
 
 def generate_launch_description():
-    return LaunchDescription([
-        create_llama_launch_from_yaml(os.path.join(
-            get_package_share_directory("llama_bringup"), "models", "Spaetzle.yaml"))
-    ])
+    return LaunchDescription(
+        [
+            create_llama_launch_from_yaml(
+                os.path.join(
+                    get_package_share_directory("llama_bringup"),
+                    "models",
+                    "Spaetzle.yaml",
+                )
+            )
+        ]
+    )

llama_bringup/llama_bringup/utils.py

@@ -33,34 +33,41 @@
 
 def download_model(repo: str, file: str) -> str:
 
-    match = re.search(r'-(\d+)-of-(\d+)\.gguf', file)
+    match = re.search(r"-(\d+)-of-(\d+)\.gguf", file)
 
     if match:
         total_shards = int(match.group(2))
-        base_name = file[:match.start()]
+        base_name = file[: match.start()]
 
         # download shards
         for i in range(1, total_shards + 1):
             shard_file = f"{base_name}-{i:05d}-of-{total_shards:05d}.gguf"
-            hf_hub_download(repo_id=repo, filename=shard_file,
-                            force_download=False)
+            hf_hub_download(repo_id=repo, filename=shard_file, force_download=False)
 
         # return first shard
         return hf_hub_download(
             repo_id=repo,
             filename=f"{base_name}-00001-of-{total_shards:05d}.gguf",
-            force_download=False
+            force_download=False,
         )
 
     return hf_hub_download(repo_id=repo, filename=file, force_download=False)
 
 
 def load_prompt_type(prompt_file_name: str) -> Tuple:
-    file_path = os.path.join(get_package_share_directory(
-        "llama_bringup"), "prompts", f"{prompt_file_name}.yaml")
+    file_path = os.path.join(
+        get_package_share_directory("llama_bringup"),
+        "prompts",
+        f"{prompt_file_name}.yaml",
+    )
     with open(file_path, "r") as file:
         yaml_data = yaml.safe_load(file)
-    return yaml_data["prefix"], yaml_data["suffix"], yaml_data["stopping_words"], yaml_data["system_prompt"]
+    return (
+        yaml_data["prefix"],
+        yaml_data["suffix"],
+        yaml_data["stopping_words"],
+        yaml_data["system_prompt"],
+    )
 
 
 def create_llama_launch_from_yaml(file_path: str) -> IncludeLaunchDescription:
@@ -70,8 +77,11 @@ def create_llama_launch_from_yaml(file_path: str) -> IncludeLaunchDescription:
 
 
 def create_llama_launch(**kwargs) -> IncludeLaunchDescription:
-    prompt_data = load_prompt_type(kwargs["system_prompt_type"]) if kwargs.get(
-        "system_prompt_type") else ("", "", [], "")
+    prompt_data = (
+        load_prompt_type(kwargs["system_prompt_type"])
+        if kwargs.get("system_prompt_type")
+        else ("", "", [], "")
+    )
     kwargs["prefix"] = kwargs.get("prefix", prompt_data[0])
     kwargs["suffix"] = kwargs.get("suffix", prompt_data[1])
     kwargs["system_prompt"] = kwargs.get("system_prompt", prompt_data[3])
@@ -83,9 +93,14 @@ def create_llama_launch(**kwargs) -> IncludeLaunchDescription:
 
     # load models
     for key in ["model", "mmproj"]:
-        if not kwargs.get(key) and kwargs.get(f"{key}_repo") and kwargs.get(f"{key}_filename"):
+        if (
+            not kwargs.get(key)
+            and kwargs.get(f"{key}_repo")
+            and kwargs.get(f"{key}_filename")
+        ):
             kwargs[key] = download_model(
-                kwargs[f"{key}_repo"], kwargs[f"{key}_filename"])
+                kwargs[f"{key}_repo"], kwargs[f"{key}_filename"]
+            )
 
     # load lora adapters
     lora_adapters = []
@@ -122,8 +137,10 @@ def create_llama_launch(**kwargs) -> IncludeLaunchDescription:
         kwargs["use_llava"] = False
 
     return IncludeLaunchDescription(
-        PythonLaunchDescriptionSource(os.path.join(
-            get_package_share_directory("llama_bringup"), "launch", "base.launch.py")),
-        launch_arguments={key: str(value)
-                          for key, value in kwargs.items()}.items()
+        PythonLaunchDescriptionSource(
+            os.path.join(
+                get_package_share_directory("llama_bringup"), "launch", "base.launch.py"
+            )
+        ),
+        launch_arguments={key: str(value) for key, value in kwargs.items()}.items(),
     )

llama_cli/llama_cli/api/__init__.py

@@ -52,16 +52,15 @@ def launch_llm(file_path: str) -> None:
         print(f"File '{file_path}' does not exists")
         return
 
-    ld = LaunchDescription([
-        create_llama_launch_from_yaml(file_path)
-    ])
+    ld = LaunchDescription([create_llama_launch_from_yaml(file_path)])
     ls = LaunchService()
     ls.include_launch_description(ld)
     ls.run()
 
 
-def prompt_llm(prompt: str, reset: bool = False,
-               temp: float = 0.8, image_url: str = "") -> None:
+def prompt_llm(
+    prompt: str, reset: bool = False, temp: float = 0.8, image_url: str = ""
+) -> None:
 
     rclpy.init()
     llama_client = LlamaClientNode()
@@ -71,8 +70,7 @@ def prompt_llm(prompt: str, reset: bool = False,
     goal.sampling_config.temp = temp
 
     if image_url:
-        req = urllib.request.Request(
-            image_url, headers={"User-Agent": "Mozilla/5.0"})
+        req = urllib.request.Request(image_url, headers={"User-Agent": "Mozilla/5.0"})
         response = urllib.request.urlopen(req)
         arr = np.asarray(bytearray(response.read()), dtype=np.uint8)
         img = cv2.imdecode(arr, -1)

llama_cli/llama_cli/command/llama.py

@@ -29,8 +29,9 @@ class LlamaCommand(CommandExtension):
 
     def add_arguments(self, parser, cli_name):
         self._subparser = parser
-        add_subparsers_on_demand(parser, cli_name, "_verb",
-                                 "llama_cli.verb", required=False)
+        add_subparsers_on_demand(
+            parser, cli_name, "_verb", "llama_cli.verb", required=False
+        )
 
     def main(self, *, parser, args):
         if not hasattr(args, "_verb"):

llama_cli/llama_cli/verb/launch.py

@@ -28,8 +28,7 @@
 class LaunchVerb(VerbExtension):
 
     def add_arguments(self, parser, cli_name):
-        arg = parser.add_argument(
-            "file_path", help="path to the YAML of the LLM")
+        arg = parser.add_argument("file_path", help="path to the YAML of the LLM")
 
     def main(self, *, args):
         launch_llm(args.file_path)

llama_cli/llama_cli/verb/prompt.py

@@ -28,21 +28,26 @@
 class PromptVerb(VerbExtension):
 
     def add_arguments(self, parser, cli_name):
-        arg = parser.add_argument(
-            "prompt", help="prompt text for the LLM")
+        arg = parser.add_argument("prompt", help="prompt text for the LLM")
         parser.add_argument(
-            "-r", "--reset",
+            "-r",
+            "--reset",
             action="store_true",
-            help="Whether to reset the LLM and its context before prompting")
+            help="Whether to reset the LLM and its context before prompting",
+        )
         parser.add_argument(
-            "-t", "--temp",
-            metavar="N", type=positive_float, default=0.8,
-            help="Temperature value (default: 0.8)")
+            "-t",
+            "--temp",
+            metavar="N",
+            type=positive_float,
+            default=0.8,
+            help="Temperature value (default: 0.8)",
+        )
         parser.add_argument(
-            "--image-url",
-            type=str, default="",
-            help="Image URL to sent to the VLM")
+            "--image-url", type=str, default="", help="Image URL to sent to the VLM"
+        )
 
     def main(self, *, args):
-        prompt_llm(args.prompt, reset=args.reset,
-                   temp=args.temp, image_url=args.image_url)
+        prompt_llm(
+            args.prompt, reset=args.reset, temp=args.temp, image_url=args.image_url
+        )