admin/OpenJarvis
1
0
Fork 0
mirror of https://github.com/open-jarvis/OpenJarvis.git synced 2026-07-30 02:42:16 +00:00
Code Issues Packages Projects Releases Wiki Activity
Files
c1e01b1e8b406d90b6c1c19a2bb9e20396f4affd
OpenJarvis/src/openjarvis/intelligence/model_catalog.py
T
Jon Saad-Falconandkrypticmouse 8798e2ee4f init commit
2026-03-12 17:29:39 +00:00

797 lines
26 KiB
Python
Raw Blame History

"""Built-in model catalog with well-known ModelSpec entries."""
from __future__ import annotations
from typing import List
from openjarvis.core.registry import ModelRegistry
from openjarvis.core.types import ModelSpec, Quantization
BUILTIN_MODELS: List[ModelSpec] = [
# -----------------------------------------------------------------------
# Local models — Dense
# -----------------------------------------------------------------------
ModelSpec(
model_id="qwen3:8b",
name="Qwen3 8B",
parameter_count_b=8.2,
context_length=32768,
supported_engines=("vllm", "ollama", "llamacpp", "sglang"),
provider="alibaba",
metadata={
"architecture": "dense",
"hf_repo": "Qwen/Qwen3-8B",
},
),
ModelSpec(
model_id="qwen3:32b",
name="Qwen3 32B",
parameter_count_b=32.0,
context_length=32768,
min_vram_gb=20.0,
supported_engines=("ollama", "vllm"),
provider="alibaba",
metadata={
"architecture": "dense",
"hf_repo": "Qwen/Qwen3-32B",
},
),
# -----------------------------------------------------------------------
# Local models — Qwen3.5 (MoE)
# -----------------------------------------------------------------------
ModelSpec(
model_id="qwen3.5:3b",
name="Qwen3.5 3B",
parameter_count_b=3.0,
active_parameter_count_b=0.6,
context_length=131072,
supported_engines=("ollama", "vllm", "llamacpp", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-3B",
},
),
ModelSpec(
model_id="qwen3.5:8b",
name="Qwen3.5 8B",
parameter_count_b=8.0,
active_parameter_count_b=1.0,
context_length=131072,
supported_engines=("ollama", "vllm", "llamacpp", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-8B",
},
),
ModelSpec(
model_id="qwen3.5:14b",
name="Qwen3.5 14B",
parameter_count_b=14.0,
active_parameter_count_b=2.0,
context_length=131072,
supported_engines=("ollama", "vllm", "llamacpp", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-14B",
},
),
ModelSpec(
model_id="qwen3.5:35b",
name="Qwen3.5 35B",
parameter_count_b=35.0,
active_parameter_count_b=3.0,
context_length=131072,
supported_engines=("ollama", "vllm", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-35B",
},
),
ModelSpec(
model_id="qwen3.5:122b",
name="Qwen3.5 122B",
parameter_count_b=122.0,
active_parameter_count_b=10.0,
context_length=131072,
min_vram_gb=70.0,
supported_engines=("ollama", "vllm", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-122B",
},
),
ModelSpec(
model_id="qwen3.5:397b",
name="Qwen3.5 397B",
parameter_count_b=397.0,
active_parameter_count_b=17.0,
context_length=131072,
min_vram_gb=220.0,
supported_engines=("vllm", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-397B",
},
),
ModelSpec(
model_id="llama3.3:70b",
name="Llama 3.3 70B",
parameter_count_b=70.0,
context_length=131072,
min_vram_gb=40.0,
supported_engines=("ollama", "vllm"),
provider="meta",
metadata={
"architecture": "dense",
"hf_repo": "meta-llama/Llama-3.3-70B-Instruct",
},
),
ModelSpec(
model_id="llama3.2:3b",
name="Llama 3.2 3B",
parameter_count_b=3.0,
context_length=131072,
supported_engines=("ollama", "vllm", "llamacpp"),
provider="meta",
metadata={
"architecture": "dense",
"hf_repo": "meta-llama/Llama-3.2-3B-Instruct",
},
),
ModelSpec(
model_id="deepseek-coder-v2:16b",
name="DeepSeek Coder V2 16B",
parameter_count_b=16.0,
context_length=131072,
supported_engines=("ollama", "vllm"),
provider="deepseek",
metadata={
"architecture": "dense",
"hf_repo": "deepseek-ai/DeepSeek-Coder-V2-Lite-Instruct",
},
),
ModelSpec(
model_id="mistral:7b",
name="Mistral 7B",
parameter_count_b=7.0,
context_length=32768,
supported_engines=("ollama", "vllm", "llamacpp"),
provider="mistral",
metadata={
"architecture": "dense",
"hf_repo": "mistralai/Mistral-7B-Instruct-v0.3",
},
),
# -----------------------------------------------------------------------
# Local models — Mixture of Experts (MoE)
# -----------------------------------------------------------------------
ModelSpec(
model_id="gpt-oss:120b",
name="GPT-OSS 120B",
parameter_count_b=117.0,
active_parameter_count_b=5.1,
context_length=131072,
min_vram_gb=12.0,
supported_engines=("vllm", "ollama"),
provider="open-source",
metadata={
"architecture": "moe",
"hf_repo": "OpenBuddy/GPT-OSS-120B",
},
),
ModelSpec(
model_id="glm-4.7-flash",
name="GLM 4.7 Flash",
parameter_count_b=30.0,
active_parameter_count_b=3.0,
context_length=131072,
min_vram_gb=8.0,
supported_engines=("vllm", "sglang", "llamacpp"),
provider="zhipu",
metadata={
"architecture": "moe",
"hf_repo": "THUDM/GLM-4.7-Flash-Chat",
},
),
ModelSpec(
model_id="trinity-mini",
name="Trinity Mini",
parameter_count_b=26.0,
active_parameter_count_b=3.0,
context_length=128000,
min_vram_gb=8.0,
supported_engines=("vllm", "llamacpp"),
provider="trinity",
metadata={
"architecture": "moe",
"hf_repo": "TrinityAI/Trinity-Mini-26B",
},
),
# -----------------------------------------------------------------------
# Local models — Qwen3.5 (MoE, Gated DeltaNet + sparse MoE)
# -----------------------------------------------------------------------
ModelSpec(
model_id="qwen3.5:4b",
name="Qwen3.5 4B",
parameter_count_b=4.0,
active_parameter_count_b=0.5,
context_length=262144,
min_vram_gb=3.0,
supported_engines=("ollama", "vllm", "sglang", "llamacpp"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-4B",
},
),
ModelSpec(
model_id="qwen3.5:35b-a3b",
name="Qwen3.5 35B A3B",
parameter_count_b=35.0,
active_parameter_count_b=3.0,
context_length=262144,
min_vram_gb=8.0,
supported_engines=("ollama", "vllm", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-35B-A3B",
},
),
ModelSpec(
model_id="qwen3.5:122b-a10b",
name="Qwen3.5 122B A10B",
parameter_count_b=122.0,
active_parameter_count_b=10.0,
context_length=262144,
min_vram_gb=20.0,
supported_engines=("vllm", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-122B-A10B",
},
),
ModelSpec(
model_id="qwen3.5:397b-a17b",
name="Qwen3.5 397B A17B",
parameter_count_b=397.0,
active_parameter_count_b=17.0,
context_length=262144,
min_vram_gb=50.0,
supported_engines=("vllm", "sglang"),
provider="alibaba",
metadata={
"architecture": "moe",
"hf_repo": "Qwen/Qwen3.5-397B-A17B",
},
),
# -----------------------------------------------------------------------
# Local models — Unsloth GGUF Quantizations
# -----------------------------------------------------------------------
ModelSpec(
model_id="unsloth/Qwen3.5-35B-A3B-GGUF",
name="Qwen3.5 35B A3B (Unsloth GGUF)",
parameter_count_b=35.0,
active_parameter_count_b=3.0,
context_length=262144,
min_vram_gb=6.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/Qwen3.5-35B-A3B-GGUF",
"base_model": "Qwen/Qwen3.5-35B-A3B",
},
),
ModelSpec(
model_id="unsloth/Qwen3.5-122B-A10B-GGUF",
name="Qwen3.5 122B A10B (Unsloth GGUF)",
parameter_count_b=122.0,
active_parameter_count_b=10.0,
context_length=262144,
min_vram_gb=16.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/Qwen3.5-122B-A10B-GGUF",
"base_model": "Qwen/Qwen3.5-122B-A10B",
},
),
ModelSpec(
model_id="unsloth/Qwen3.5-397B-A17B-GGUF",
name="Qwen3.5 397B A17B (Unsloth GGUF)",
parameter_count_b=397.0,
active_parameter_count_b=17.0,
context_length=262144,
min_vram_gb=40.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/Qwen3.5-397B-A17B-GGUF",
"base_model": "Qwen/Qwen3.5-397B-A17B",
},
),
ModelSpec(
model_id="unsloth/GLM-5-GGUF",
name="GLM-5 (Unsloth GGUF)",
parameter_count_b=100.0,
context_length=131072,
min_vram_gb=12.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "dense",
"hf_repo": "unsloth/GLM-5-GGUF",
"base_model": "THUDM/GLM-5",
},
),
ModelSpec(
model_id="unsloth/GLM-4.7-Flash-GGUF",
name="GLM 4.7 Flash (Unsloth GGUF)",
parameter_count_b=30.0,
active_parameter_count_b=3.0,
context_length=131072,
min_vram_gb=6.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/GLM-4.7-Flash-GGUF",
"base_model": "THUDM/GLM-4.7-Flash-Chat",
},
),
ModelSpec(
model_id="unsloth/Qwen3-Coder-Next-GGUF",
name="Qwen3 Coder Next (Unsloth GGUF)",
parameter_count_b=80.0,
context_length=131072,
min_vram_gb=12.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/Qwen3-Coder-Next-GGUF",
"base_model": "Qwen/Qwen3-Coder-Next",
},
),
ModelSpec(
model_id="unsloth/MiniMax-M2.5-GGUF",
name="MiniMax M2.5 (Unsloth GGUF)",
parameter_count_b=229.0,
context_length=131072,
min_vram_gb=30.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/MiniMax-M2.5-GGUF",
"base_model": "MiniMax/MiniMax-M2.5",
},
),
ModelSpec(
model_id="unsloth/Kimi-K2.5-GGUF",
name="Kimi K2.5 (Unsloth GGUF)",
parameter_count_b=1000.0,
active_parameter_count_b=32.0,
context_length=131072,
min_vram_gb=40.0,
quantization=Quantization.GGUF,
supported_engines=("ollama", "llamacpp"),
provider="unsloth",
metadata={
"architecture": "moe",
"hf_repo": "unsloth/Kimi-K2.5-GGUF",
"base_model": "moonshotai/Kimi-K2.5",
},
),
# -----------------------------------------------------------------------
# Local models — LiquidAI LFM2.5 (Hybrid SSM+Transformer)
# -----------------------------------------------------------------------
ModelSpec(
model_id="LiquidAI/LFM2.5-1.2B-Instruct-GGUF",
name="LFM2.5 1.2B Instruct (GGUF)",
parameter_count_b=1.2,
context_length=32768,
min_vram_gb=1.0,
quantization=Quantization.GGUF,
supported_engines=("llamacpp", "ollama"),
provider="liquidai",
metadata={
"architecture": "hybrid_ssm_transformer",
"hf_repo": "LiquidAI/LFM2.5-1.2B-Instruct-GGUF",
"layers": "10 LIV convolution + 6 GQA",
"languages": 8,
},
),
ModelSpec(
model_id="LiquidAI/LFM2.5-1.2B-Instruct-MLX",
name="LFM2.5 1.2B Instruct (MLX)",
parameter_count_b=1.2,
context_length=32768,
min_vram_gb=1.0,
supported_engines=("mlx",),
provider="liquidai",
metadata={
"architecture": "hybrid_ssm_transformer",
"hf_repo": "LiquidAI/LFM2.5-1.2B-Instruct-MLX",
"layers": "10 LIV convolution + 6 GQA",
"languages": 8,
},
),
ModelSpec(
model_id="LiquidAI/LFM2.5-1.2B-Thinking-GGUF",
name="LFM2.5 1.2B Thinking (GGUF)",
parameter_count_b=1.2,
context_length=32768,
min_vram_gb=1.0,
quantization=Quantization.GGUF,
supported_engines=("llamacpp", "ollama"),
provider="liquidai",
metadata={
"architecture": "hybrid_ssm_transformer",
"hf_repo": "LiquidAI/LFM2.5-1.2B-Thinking-GGUF",
"layers": "10 LIV convolution + 6 GQA",
"variant": "reasoning-optimized",
"languages": 8,
},
),
ModelSpec(
model_id="LiquidAI/LFM2.5-1.2B-Thinking-MLX",
name="LFM2.5 1.2B Thinking (MLX)",
parameter_count_b=1.2,
context_length=32768,
min_vram_gb=1.0,
supported_engines=("mlx",),
provider="liquidai",
metadata={
"architecture": "hybrid_ssm_transformer",
"hf_repo": "LiquidAI/LFM2.5-1.2B-Thinking-MLX",
"layers": "10 LIV convolution + 6 GQA",
"variant": "reasoning-optimized",
"languages": 8,
},
),
# -----------------------------------------------------------------------
# Local models — TeichAI Distilled
# -----------------------------------------------------------------------
ModelSpec(
model_id="teichai/glm-4.7-flash-opus-distill",
name="GLM 4.7 Flash Claude Opus 4.5 Distill",
parameter_count_b=30.0,
active_parameter_count_b=3.0,
context_length=131072,
min_vram_gb=8.0,
supported_engines=("vllm", "llamacpp"),
provider="teichai",
metadata={
"architecture": "moe",
"hf_repo": (
"TeichAI/GLM-4.7-Flash-Claude-"
"Opus-4.5-High-Reasoning-Distill-GGUF"
),
"teacher": "Claude Opus 4.5",
"quantization": "GGUF Q4_K_M / Q8_0",
"license": "apache-2.0",
},
),
ModelSpec(
model_id="teichai/qwen3-14b-gpt5.2-distill",
name="Qwen3 14B GPT-5.2 Distill",
parameter_count_b=14.8,
context_length=32768,
min_vram_gb=10.0,
supported_engines=("vllm", "llamacpp"),
provider="teichai",
metadata={
"architecture": "dense",
"hf_repo": "TeichAI/Qwen3-14B-GPT-5.2-Distill-GGUF",
"teacher": "GPT-5.2",
"quantization": "GGUF Q4_K_M / Q8_0",
"license": "apache-2.0",
},
),
ModelSpec(
model_id="teichai/nemotron-14b-opus-distill",
name="Nemotron Cascade 14B Claude Opus Distill",
parameter_count_b=14.8,
context_length=32768,
min_vram_gb=10.0,
supported_engines=("vllm", "llamacpp"),
provider="teichai",
metadata={
"architecture": "dense",
"hf_repo": "TeichAI/Nemotron-Cascade-14B-Claude-Opus-Distill-GGUF",
"teacher": "Claude 4.5 Opus",
"quantization": "GGUF Q4_K_M / Q8_0",
"license": "apache-2.0",
},
),
# -----------------------------------------------------------------------
# Local models — IBM Granite
# -----------------------------------------------------------------------
ModelSpec(
model_id="granite3.3:8b",
name="Granite 3.3 8B",
parameter_count_b=8.0,
context_length=128000,
supported_engines=("ollama", "vllm", "llamacpp"),
provider="ibm",
metadata={
"architecture": "dense",
"hf_repo": "ibm-granite/granite-3.3-8b-instruct",
"url": "https://www.ibm.com/granite",
},
),
ModelSpec(
model_id="granite4.0-micro",
name="Granite 4.0 Micro 3B",
parameter_count_b=3.0,
context_length=128000,
supported_engines=("ollama", "vllm", "llamacpp"),
provider="ibm",
metadata={
"architecture": "dense",
"hf_repo": "ibm-granite/granite-4.0-micro",
"url": "https://www.ibm.com/granite",
},
),
ModelSpec(
model_id="granite4.0-h-small",
name="Granite 4.0 H Small 32B",
parameter_count_b=32.0,
active_parameter_count_b=9.0,
context_length=128000,
supported_engines=("ollama", "vllm"),
provider="ibm",
metadata={
"architecture": "moe",
"hf_repo": "ibm-granite/granite-4.0-h-small",
"url": "https://www.ibm.com/granite",
},
),
# -----------------------------------------------------------------------
# Cloud models — OpenAI
# -----------------------------------------------------------------------
ModelSpec(
model_id="gpt-4o",
name="GPT-4o",
parameter_count_b=0.0,
context_length=128000,
supported_engines=("cloud",),
provider="openai",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 2.50,
"pricing_output": 10.00,
"url": "https://platform.openai.com/docs/models/gpt-4o",
},
),
ModelSpec(
model_id="gpt-4o-mini",
name="GPT-4o Mini",
parameter_count_b=0.0,
context_length=128000,
supported_engines=("cloud",),
provider="openai",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 0.15,
"pricing_output": 0.60,
"url": "https://platform.openai.com/docs/models/gpt-4o-mini",
},
),
ModelSpec(
model_id="gpt-5-mini",
name="GPT-5 Mini",
parameter_count_b=0.0,
context_length=400000,
supported_engines=("cloud",),
provider="openai",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 0.25,
"pricing_output": 2.00,
"url": "https://platform.openai.com/docs/models",
},
),
ModelSpec(
model_id="gpt-5-mini-2025-08-07",
name="GPT-5 Mini (2025-08-07)",
parameter_count_b=0.0,
context_length=400000,
supported_engines=("cloud",),
provider="openai",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 0.25,
"pricing_output": 2.00,
"url": "https://platform.openai.com/docs/models",
},
),
# -----------------------------------------------------------------------
# Cloud models — Anthropic
# -----------------------------------------------------------------------
ModelSpec(
model_id="claude-sonnet-4-20250514",
name="Claude Sonnet 4",
parameter_count_b=0.0,
context_length=200000,
supported_engines=("cloud",),
provider="anthropic",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 3.00,
"pricing_output": 15.00,
"url": "https://docs.anthropic.com/en/docs/about-claude/models",
},
),
ModelSpec(
model_id="claude-opus-4-20250514",
name="Claude Opus 4",
parameter_count_b=0.0,
context_length=200000,
supported_engines=("cloud",),
provider="anthropic",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 15.00,
"pricing_output": 75.00,
"url": "https://docs.anthropic.com/en/docs/about-claude/models",
},
),
ModelSpec(
model_id="claude-opus-4-6",
name="Claude Opus 4.6",
parameter_count_b=0.0,
context_length=200000,
supported_engines=("cloud",),
provider="anthropic",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 5.00,
"pricing_output": 25.00,
"url": "https://docs.anthropic.com/en/docs/about-claude/models",
},
),
ModelSpec(
model_id="claude-sonnet-4-6",
name="Claude Sonnet 4.6",
parameter_count_b=0.0,
context_length=200000,
supported_engines=("cloud",),
provider="anthropic",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 3.00,
"pricing_output": 15.00,
"url": "https://docs.anthropic.com/en/docs/about-claude/models",
},
),
ModelSpec(
model_id="claude-haiku-4-5",
name="Claude Haiku 4.5",
parameter_count_b=0.0,
context_length=200000,
supported_engines=("cloud",),
provider="anthropic",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 1.00,
"pricing_output": 5.00,
"url": "https://docs.anthropic.com/en/docs/about-claude/models",
},
),
# -----------------------------------------------------------------------
# Cloud models — Google
# -----------------------------------------------------------------------
ModelSpec(
model_id="gemini-2.5-pro",
name="Gemini 2.5 Pro",
parameter_count_b=0.0,
context_length=1000000,
supported_engines=("cloud",),
provider="google",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 1.25,
"pricing_output": 10.00,
"url": "https://ai.google.dev/gemini-api/docs/models#gemini-2.5-pro",
},
),
ModelSpec(
model_id="gemini-2.5-flash",
name="Gemini 2.5 Flash",
parameter_count_b=0.0,
context_length=1000000,
supported_engines=("cloud",),
provider="google",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 0.30,
"pricing_output": 2.50,
"url": "https://ai.google.dev/gemini-api/docs/models#gemini-2.5-flash",
},
),
ModelSpec(
model_id="gemini-3-pro",
name="Gemini 3 Pro",
parameter_count_b=0.0,
context_length=1000000,
supported_engines=("cloud",),
provider="google",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 2.00,
"pricing_output": 12.00,
"url": "https://ai.google.dev/gemini-api/docs/models",
},
),
ModelSpec(
model_id="gemini-3-flash",
name="Gemini 3 Flash",
parameter_count_b=0.0,
context_length=1000000,
supported_engines=("cloud",),
provider="google",
requires_api_key=True,
metadata={
"architecture": "proprietary",
"pricing_input": 0.50,
"pricing_output": 3.00,
"url": "https://ai.google.dev/gemini-api/docs/models",
},
),
]
def register_builtin_models() -> None:
"""Populate ``ModelRegistry`` with well-known models."""
for spec in BUILTIN_MODELS:
if not ModelRegistry.contains(spec.model_id):
ModelRegistry.register_value(spec.model_id, spec)
def merge_discovered_models(engine_key: str, model_ids: List[str]) -> None:
"""Create minimal ``ModelSpec`` entries for models not already in the registry."""
for model_id in model_ids:
if not ModelRegistry.contains(model_id):
spec = ModelSpec(
model_id=model_id,
name=model_id,
parameter_count_b=0.0,
context_length=0,
supported_engines=(engine_key,),
)
ModelRegistry.register_value(model_id, spec)
__all__ = ["BUILTIN_MODELS", "merge_discovered_models", "register_builtin_models"]
Reference in New Issue View Git Blame Copy Permalink