X/dev

README.md

@@ -9,9 +9,9 @@
 * Extracting and classifying metadata from images/models
 * Consumer-grade GPU/CPU inference optimization
 * Misc UX/UI Experimentation
-* 🧨Diffusers, 🤗Transformers, 🦙Ollama, 🍏MLX, 🌀DSPy, 🚅LiteLLM<br><br>
+* 🧨Diffusers, 🤗Transformers, 🦙Ollama, 🍏MLX, 🌀DSPy, 🚅LiteLLM
+* :shipit: <br><br>
 
-# :shipit:
 [![Python application test status](https://github.com/darkshapes/nnll/actions/workflows/python-app.yml/badge.svg)](https://github.com/darkshapes/nnll/actions/workflows/python-app.yml) <br>
 ![commits per month](https://img.shields.io/github/commit-activity/m/darkshapes/nnll?color=indigo)<br>
 ![code size](https://img.shields.io/github/languages/code-size/darkshapes/nnll?color=navy)<br>

_version.py

@@ -17,5 +17,5 @@
 __version_tuple__: VERSION_TUPLE
 version_tuple: VERSION_TUPLE
 
-__version__ = version = '0.1.dev257+gee3125e.d20250412'
-__version_tuple__ = version_tuple = (0, 1, 'dev257', 'gee3125e.d20250412')
+__version__ = version = '0.1.dev272+g2ccb172.d20250422'
+__version_tuple__ = version_tuple = (0, 1, 'dev272', 'g2ccb172.d20250422')

nnll.egg-info/PKG-INFO

@@ -1,6 +1,6 @@
 Metadata-Version: 2.4
 Name: nnll
-Version: 0.1.dev257+gee3125e.d20250412
+Version: 0.1.dev272+g2ccb172.d20250422
 Summary: Neural Network Link Library : A comprehensive modular toolkit for Diffusion and Large Language Model inference processes.
 Author-email: darkshapes <91800957+exdysa@users.noreply.github.com>
 License: #// SPDX-License-Identifier: blessing
@@ -16,8 +16,10 @@ Keywords: ML,AI,neural network,library,diffusion,LLM,torch
 Requires-Python: >=3.10
 Description-Content-Type: text/markdown
 License-File: LICENSE
-Requires-Dist: structlog>=25.2.0
-Requires-Dist: viztracer>=1.0.3
+Requires-Dist: nnll_01
+Provides-Extra: nnll-01
+Requires-Dist: structlog>=25.2.0; extra == "nnll-01"
+Requires-Dist: viztracer>=1.0.3; extra == "nnll-01"
 Provides-Extra: nnll-02
 Requires-Dist: huggingface-hub>=0.29.3; extra == "nnll-02"
 Requires-Dist: litellm>=1.65.0; extra == "nnll-02"
@@ -27,7 +29,6 @@ Requires-Dist: aiohttp<=3.11.13,>=3.9.5; extra == "nnll-03"
 Requires-Dist: tqdm>=4.67.1; extra == "nnll-03"
 Provides-Extra: nnll-04
 Requires-Dist: gguf>=0.14.0; extra == "nnll-04"
-Requires-Dist: llama-cpp-python>=0.3.8; extra == "nnll-04"
 Requires-Dist: safetensors>=0.5.3; extra == "nnll-04"
 Provides-Extra: nnll-05
 Requires-Dist: networkx>=3.4.2; extra == "nnll-05"
@@ -102,6 +103,7 @@ Requires-Dist: torchvision>=0.21.0; extra == "nnll-62"
 Provides-Extra: nnll-64
 Requires-Dist: pillow>=11.1.0; extra == "nnll-64"
 Provides-Extra: all
+Requires-Dist: nnll[nnll_01]; extra == "all"
 Requires-Dist: nnll[nnll_02]; extra == "all"
 Requires-Dist: nnll[nnll_03]; extra == "all"
 Requires-Dist: nnll[nnll_04]; extra == "all"
@@ -150,9 +152,9 @@ Dynamic: license-file
 * Extracting and classifying metadata from images/models
 * Consumer-grade GPU/CPU inference optimization
 * Misc UX/UI Experimentation
-* 🧨Diffusers, 🤗Transformers, 🦙Ollama, 🍏MLX, 🌀DSPy, 🚅LiteLLM<br><br>
+* 🧨Diffusers, 🤗Transformers, 🦙Ollama, 🍏MLX, 🌀DSPy, 🚅LiteLLM
+* :shipit: <br><br>
 
-# :shipit:
 [![Python application test status](https://github.com/darkshapes/nnll/actions/workflows/python-app.yml/badge.svg)](https://github.com/darkshapes/nnll/actions/workflows/python-app.yml) <br>
 ![commits per month](https://img.shields.io/github/commit-activity/m/darkshapes/nnll?color=indigo)<br>
 ![code size](https://img.shields.io/github/languages/code-size/darkshapes/nnll?color=navy)<br>
@@ -205,7 +207,7 @@ Dynamic: license-file
 Some modules are full scripts and can be run from command line. These are written here:
 
 `zodiac`        - Experimental generative system<br>
-`astra`        - Experimental generative system<br>
+`astra`        - Live diagnostic console<br>
 `nnll-hash`    - Hash the layer metadata from models within a directory and write out to console.<br>
 `nnll-parse`   - Process metadata headers from a model file or directory of models and write out to individual JSON files.<br>
 `nnll-find`    - Search a local directory of model layer files (HuggingFace🤗 index.json, JSON from `nnll-parse`)<br>

nnll.egg-info/SOURCES.txt

@@ -4,7 +4,6 @@ README.md
 _version.py
 pyproject.toml
 pytest.ini
-textual.log
 uv.lock
 .github/workflows/python-app.yml
 nnll.egg-info/PKG-INFO
@@ -23,19 +22,6 @@ nnll_06/__init__.py
 nnll_07/__init__.py
 nnll_08/__init__.py
 nnll_09/__init__.py
-nnll_10/__init__.py
-nnll_10/package/__init__.py
-nnll_10/package/__main__.py
-nnll_10/package/carousel.py
-nnll_10/package/combo.tcss
-nnll_10/package/display_bar.py
-nnll_10/package/input_tag.py
-nnll_10/package/main_screen.py
-nnll_10/package/message_panel.py
-nnll_10/package/output_tag.py
-nnll_10/package/response_panel.py
-nnll_10/package/token_counters.py
-nnll_10/package/voice_panel.py
 nnll_11/__init__.py
 nnll_12/__init__.py
 nnll_12/__main__.py
@@ -50,6 +36,7 @@ nnll_17/__main__.py
 nnll_18/__init__.py
 nnll_19/__init__.py
 nnll_20/__init__.py
+nnll_21/__init__.py
 nnll_24/__init__.py
 nnll_25/__init__.py
 nnll_26/__init__.py
@@ -101,8 +88,7 @@ tests/test_05.py
 tests/test_07.py
 tests/test_08.py
 tests/test_10_register_types.py
-tests/test_14_draw_graph.py
-tests/test_14_graph.py
+tests/test_10_weight.py
 tests/test_15_register_types.py
 tests/test_24.py
 tests/test_25.py

nnll.egg-info/entry_points.txt

@@ -4,4 +4,3 @@ nnll-find = nnll_31:main
 nnll-hash = nnll_17:main
 nnll-index = nnll_43:main
 nnll-parse = nnll_36:main
-zodiac = nnll_10.package.__init__:main

nnll.egg-info/requires.txt

@@ -1,7 +1,7 @@
-structlog>=25.2.0
-viztracer>=1.0.3
+nnll_01
 
 [all]
+nnll[nnll_01]
 nnll[nnll_02]
 nnll[nnll_03]
 nnll[nnll_04]
@@ -50,7 +50,6 @@ tqdm>=4.67.1
 
 [nnll-04]
 gguf>=0.14.0
-llama-cpp-python>=0.3.8
 safetensors>=0.5.3
 
 [nnll-05]
@@ -146,3 +145,7 @@ torchvision>=0.21.0
 
 [nnll-64]
 pillow>=11.1.0
+
+[nnll_01]
+structlog>=25.2.0
+viztracer>=1.0.3

nnll.egg-info/top_level.txt

@@ -18,6 +18,7 @@ nnll_17
 nnll_18
 nnll_19
 nnll_20
+nnll_21
 nnll_24
 nnll_25
 nnll_26

nnll_08/__init__.py

@@ -30,13 +30,13 @@ def seed_planter(seed, deterministic=True) -> int:
 
     torch.manual_seed(seed)
     random.seed(seed)
-    if torch.cuda.is_available() is True:
-        if deterministic is True:
+    if torch.cuda.is_available():
+        if deterministic:
             return {"torch.backends.cudnn.deterministic": "True", "torch.backends.cudnn.benchmark": "False"}
         return torch.cuda.manual_seed(seed), torch.cuda.manual_seed_all(seed)
-    elif torch.backends.mps.is_available() is True:
+    elif torch.backends.mps.is_available():
         return torch.mps.manual_seed(seed)
-    elif torch.xpu.is_available() is True:
+    elif torch.xpu.is_available():
         return torch.xpu.manual_seed(seed)