Repository Analysis

google-gemma/cookbook

A collection of guides and examples for the Gemma open models from Google.

19.0 Moderate AI signal View on GitHub

Analysis Overview

This report presents the forensic synthetic code analysis of google-gemma/cookbook, a Jupyter Notebook project with 3,893 GitHub stars. SynthScan v2.0 examined 23,899 lines of code across 226 source files, recording 158 pattern matches distributed across 12 syntactic categories. The overall adjusted score of 19.0 places this repository in the Moderate AI signal band.

The scanner applied 160+ deterministic lexical heuristics, multi-line block detectors, abstract syntax tree depth profilers, and a cross-file Jaccard similarity matrix to construct a statistically normalised synthetic code estimate. All matches are individually weighted by severity coefficient and contextual multiplier before summation, and the resulting headline score is temporally discounted to account for the repository's development history relative to the commercial emergence of large language model coding tooling (November 2022 onward).

19.0
Adjusted Score
19.0
Raw Score
100%
Time Factor
2026-07-07
Last Push
3.9K
Stars
Jupyter Notebook
Language
23.9K
Lines of Code
226
Files
158
Pattern Hits
2026-07-14
Scan Date
0.15
HC Hit Rate

What These Metrics Mean

Adjusted Score
Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score
The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor
The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits
Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate
High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files
Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 33MEDIUM 60LOW 65

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 158 distinct pattern matches across 12 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Decorative Section Separators52 hits · 172 pts
SeverityFileLineSnippetContext
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py17# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py19# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py157# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py159# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py165# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py167# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py275# =============================================================================COMMENT
MEDIUM…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py277# =============================================================================COMMENT
MEDIUM.archive/Demos/spoken-language-tasks/setup_python.sh11# -------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py338 # ── 1. Token presence ───────────────────────────────────────────────COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py342 # ── 2. Expiry ───────────────────────────────────────────────────────COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py346 # ── 3. Signature ────────────────────────────────────────────────────COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py350 # ── 4. Scope ────────────────────────────────────────────────────────COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py354 # ── 5. Irreversibility class ceiling ────────────────────────────────COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py37# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py39# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py80# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py82# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py206# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py208# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py228# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py230# ---------------------------------------------------------------------------COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py369 # ── 7. Class 2 — confirmation callback required ─────────────────────COMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py381 # ── 8. Class 0 / 1 — allow ─────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/run.sh2# ─────────────────────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/run.sh15# ─────────────────────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/run.sh52# ─── Load agents from scenario ──────────────────────────────COMMENT
MEDIUMapps/concurrent/run.sh84# ─── Calculate window layout ────────────────────────────────COMMENT
MEDIUMapps/concurrent/run.sh112# ─── Build AppleScript to open windows ──────────────────────COMMENT
MEDIUMapps/concurrent/run.sh166# ─── Launch ────────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py28# ─── Palettes ───────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py72# ─── Agent Factories ───────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py132# ─── System Prompts ─────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py157# ─── Planning Prompts ───────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py211# ─── Card Renderers ─────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py291# ─── Page Builder ───────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/scenarios.py353# ─── Scenario Registry ──────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/dashboard.py96# ─── Hero Panel (big t/s number) ───────────────────────────COMMENT
MEDIUMapps/concurrent/demo/dashboard.py161# ─── Orchestrator Panel ────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/dashboard.py193# ─── Agent Grid ────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/dashboard.py275# ─── Combined Layout ──────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/utils.py15# ─── Shared Paths ───────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/utils.py20# ─── ANSI Colors ────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/utils.py31# ─── Metrics ────────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/utils.py51# ─── LLM Streaming ─────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/orchestrator.py27# ─── Step 1: Plan ───────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/orchestrator.py77# ─── Step 2: Dispatch ───────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/orchestrator.py104# ─── Step 3: Collect ────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/orchestrator.py135# ─── Step 4: Assemble ───────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/orchestrator.py162# ─── Main ────────────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/digits.py5# ─────────────────────────────────────────────────────────────COMMENT
MEDIUMapps/concurrent/demo/digits.py7# ─────────────────────────────────────────────────────────────COMMENT
Magic Placeholder Names25 hits · 145 pts
SeverityFileLineSnippetContext
HIGHapps/Gemma-on-Cloudrun/README.md37 --set-env-vars=API_KEY={YOUR_API_KEY} \CODE
HIGHapps/Gemma-on-Cloudrun/README.md51* `YOUR_API_KEY`: **Crucial for authentication**. Set this to a strong, unique API key string of your choice. This key wCOMMENT
HIGHapps/Gemma-on-Cloudrun/README.md62* Environment Variable: As shown in the deployment command: `--set-env-vars=API_KEY={YOUR_API_KEY}`.COMMENT
HIGHapps/Gemma-on-Cloudrun/README.md67You will need to include this `YOUR_API_KEY` in every request to your Cloud Run service, as shown in the [Interacting wiCODE
HIGHapps/Gemma-on-Cloudrun/README.md85* `<YOUR_API_KEY>`: The API key you configured during deployment.COMMENT
HIGHapps/Gemma-on-Cloudrun/README.md85* `<YOUR_API_KEY>`: The API key you configured during deployment.COMMENT
HIGHapps/Gemma-on-Cloudrun/README.md92curl "<cloud_run_url>/v1beta/models/<model>:generateContent?key={YOUR_API_KEY}" \CODE
HIGHapps/Gemma-on-Cloudrun/README.md104curl "<cloud_run_url>/v1beta/models/<model>:streamGenerateContent?key={YOUR_API_KEY}" \CODE
HIGHapps/Gemma-on-Cloudrun/README.md129client = genai.Client(api_key="<YOUR_API_KEY>", http_options=HttpOptions(base_url="<cloud_run_url>"))CODE
HIGHapps/Gemma-on-Cloudrun/README.md129client = genai.Client(api_key="<YOUR_API_KEY>", http_options=HttpOptions(base_url="<cloud_run_url>"))CODE
HIGHapps/Gemma-on-Cloudrun/README.md164 api_key="<YOUR_API_KEY>",CODE
HIGHapps/Gemma-on-Cloudrun/README.md164 api_key="<YOUR_API_KEY>",CODE
HIGHapps/Gemma-on-Cloudrun/README.md189 -H "Authorization: Bearer <YOUR_API_KEY>" \CODE
HIGHapps/Gemma-on-Cloudrun/README.md189 -H "Authorization: Bearer <YOUR_API_KEY>" \CODE
HIGHapps/Gemma-on-Cloudrun/README.md221 headers={'Authorization': 'Bearer <YOUR_API_KEY>'}CODE
HIGHapps/Gemma-on-Cloudrun/README.md221 headers={'Authorization': 'Bearer <YOUR_API_KEY>'}CODE
HIGHapps/Gemma-on-Cloudrun/README.md281 --set-env-vars=API_KEY={YOUR_API_KEY} \CODE
HIGHapps/Gemma-on-Cloudrun/README.md326client = genai.Client(api_key="<YOUR_API_KEY>", http_options=HttpOptions(base_url="<cloud_run_url>"))CODE
HIGHapps/Gemma-on-Cloudrun/README.md326client = genai.Client(api_key="<YOUR_API_KEY>", http_options=HttpOptions(base_url="<cloud_run_url>"))CODE
HIGHapps/Gemma-on-Cloudrun/code-examples/ollama_examples.py6 headers={'Authorization': 'Bearer <YOUR_API_KEY>'}CODE
HIGHapps/Gemma-on-Cloudrun/code-examples/ollama_examples.py6 headers={'Authorization': 'Bearer <YOUR_API_KEY>'}CODE
HIGHapps/Gemma-on-Cloudrun/code-examples/genai_examples.py5client = genai.Client(api_key="<YOUR_API_KEY>", http_options=HttpOptions(base_url="<cloud_run_url>"))CODE
HIGHapps/Gemma-on-Cloudrun/code-examples/genai_examples.py5client = genai.Client(api_key="<YOUR_API_KEY>", http_options=HttpOptions(base_url="<cloud_run_url>"))CODE
HIGHapps/Gemma-on-Cloudrun/code-examples/openai_examples.py5 api_key="<YOUR_API_KEY>",CODE
HIGHapps/Gemma-on-Cloudrun/code-examples/openai_examples.py5 api_key="<YOUR_API_KEY>",CODE
Cross-File Repetition8 hits · 40 pts
SeverityFileLineSnippetContext
HIGH…ail-assistant/email-processing-webapp/models/gemini.py0creates a message processor function with a persistent model.STRING
HIGH…mail-assistant/email-processing-webapp/models/gemma.py0creates a message processor function with a persistent model.STRING
HIGH…sistant/gemma-web-service/gemma_service/gemma_model.py0creates a message processor function with a persistent model.STRING
HIGH…e-tasks/k-mail-replier/k_mail_replier/models/gemini.py0creates a message processor function with a persistent model.STRING
HIGH…ge-tasks/k-mail-replier/k_mail_replier/models/gemma.py0creates a message processor function with a persistent model.STRING
HIGH…mail-assistant/email-processing-webapp/models/gemma.py0loads environment variables and configures the gemma model.STRING
HIGH…sistant/gemma-web-service/gemma_service/gemma_model.py0loads environment variables and configures the gemma model.STRING
HIGH…ge-tasks/k-mail-replier/k_mail_replier/models/gemma.py0loads environment variables and configures the gemma model.STRING
Structural Annotation Overuse14 hits · 25 pts
SeverityFileLineSnippetContext
LOW…3n-Submodels/RESPONSE_SUB_BILLION_AND_AUDIO_SLICING.md151#### Step 1: Identify Audio Encoder ConfigurationCOMMENT
LOW…3n-Submodels/RESPONSE_SUB_BILLION_AND_AUDIO_SLICING.md166#### Step 2: Recommended Audio Encoder ReductionCOMMENT
LOW…3n-Submodels/RESPONSE_SUB_BILLION_AND_AUDIO_SLICING.md182#### Step 3: Implementation RequirementsCOMMENT
LOW.archive/Guides/Gemma-3n-Submodels/README.md176### Step 1: Review the SummaryCOMMENT
LOW.archive/Guides/Gemma-3n-Submodels/README.md179### Step 2: Choose Your ConfigurationCOMMENT
LOW.archive/Guides/Gemma-3n-Submodels/README.md185### Step 3: Get the Configuration CodeCOMMENT
LOW.archive/Guides/Gemma-3n-Submodels/README.md190### Step 4: Apply to MatFormer LabCOMMENT
LOW.archive/Guides/Gemma-3n-Submodels/README.md193### Step 5: Test & DeployCOMMENT
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md44### Step 1: Prepare EnvironmentCOMMENT
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md55### Step 2: Set Model SourceCOMMENT
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md64### Step 3: Apply 0.9B ConfigurationCOMMENT
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md87### Step 4: Run Slicing PipelineCOMMENT
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md100### Step 5: Push to Hugging Face (Optional)COMMENT
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md114### Step 6: Load and TestCOMMENT
Modern AI Meta-Vocabulary7 hits · 20 pts
SeverityFileLineSnippetContext
MEDIUM.archive/Gemma/README.md7* [RAG (Retrieval Augmented Generation)](#rag) : How to build RAG systems with GemmaCOMMENT
MEDIUM.archive/Gemma/README.md11* [Agentic AI](#agentic-ai) : How to build an intelligent agents using Gemma modelsCOMMENT
MEDIUM.archive/Gemma/README.md70## RAGCOMMENT
MEDIUMexperiments/TxGemma/README.md7* [Agentic](#agentic): How to integrate TxGemma models into agentic workflowsCOMMENT
MEDIUMapps/Gemma_4_HDP_Agentic_Security/README.md72- **IETF draft:** https://datatracker.ietf.org/doc/draft-helixar-hdp-agentic-delegation/CODE
MEDIUMapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py9 https://datatracker.ietf.org/doc/draft-helixar-hdp-agentic-delegation/STRING
MEDIUMapps/concurrent/run.sh3# run.sh — Launch the multi-agent demo with Terminal windows.COMMENT
Unused Imports19 hits · 18 pts
SeverityFileLineSnippetContext
LOW…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py13CODE
LOW…ve/Demos/business-email-assistant/model-tuning/main.py20CODE
LOW…mail-assistant/email-processing-webapp/models/gemma.py17CODE
LOW…sistant/gemma-web-service/gemma_service/gemma_model.py18CODE
LOW…liGemma-on-Android/Python_Server/apiserver/api/test.py1CODE
LOW…emma-on-Android/Python_Server/apiserver/api/schemas.py1CODE
LOW…iGemma-on-Android/Python_Server/apiserver/api/admin.py1CODE
LOW…iGemma-on-Android/Python_Server/apiserver/api/tests.py1CODE
LOW…iGemma-on-Android/Python_Server/apiserver/api/views.py10CODE
LOW…iGemma-on-Android/Python_Server/apiserver/api/views.py14CODE
LOW…iGemma-on-Android/Python_Server/apiserver/api/views.py16CODE
LOW…-Android/Python_Server/apiserver/apiserver/settings.py14CODE
LOW.archive/Demos/spoken-language-tasks/k-gemma-it/main.py20CODE
LOWapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py20CODE
LOWapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py23CODE
LOWapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py28CODE
LOWapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py28CODE
LOWapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py28CODE
LOWapps/Gemma_4_HDP_Agentic_Security/hdp_middleware.py28CODE
Over-Commented Block14 hits · 14 pts
SeverityFileLineSnippetContext
LOW…s/Gemma-3n-Submodels/QUICK_START_SUB_BILLION_MODELS.md141COMMENT
LOW…ve/Demos/business-email-assistant/model-tuning/main.py1#COMMENT
LOW…usiness-email-assistant/email-processing-webapp/app.py1#COMMENT
LOW…ail-assistant/email-processing-webapp/models/gemini.py1#COMMENT
LOW…mail-assistant/email-processing-webapp/models/gemma.py1#COMMENT
LOW…sistant/gemma-web-service/gemma_service/gemma_model.py1#COMMENT
LOW…/gemma-web-service/gemma_service/gemma_service_main.py1#COMMENT
LOW.archive/Demos/spoken-language-tasks/setup_python.sh1#!/bin/bashCOMMENT
LOW.archive/Demos/spoken-language-tasks/setup_python.sh21# pip install "jax[cuda12]" # install jax for CUDA 12 driversCOMMENT
LOW.archive/Demos/spoken-language-tasks/k-gemma-it/main.py1#COMMENT
LOW…en-language-tasks/k-mail-replier/k_mail_replier/app.py1#COMMENT
LOW…e-tasks/k-mail-replier/k_mail_replier/models/gemini.py1#COMMENT
LOW…ge-tasks/k-mail-replier/k_mail_replier/models/gemma.py1#COMMENT
LOWapps/concurrent/run.sh1#!/bin/bashCOMMENT
Deep Nesting8 hits · 8 pts
SeverityFileLineSnippetContext
LOW…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py170CODE
LOW…ve/Demos/business-email-assistant/model-tuning/main.py51CODE
LOW…iGemma-on-Android/Python_Server/apiserver/api/views.py35CODE
LOWapps/concurrent/demo/dashboard.py53CODE
LOWapps/concurrent/demo/dashboard.py301CODE
LOWapps/concurrent/demo/utils.py53CODE
LOWapps/concurrent/demo/orchestrator.py106CODE
LOWapps/concurrent/demo/specialist.py21CODE
Hyper-Verbose Identifiers4 hits · 4 pts
SeverityFileLineSnippetContext
LOW…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py170def get_config_for_deployment(CODE
LOW…ve/Guides/Gemma-3n-Submodels/custom_slicing_configs.py250def create_config_comparison_table() -> pd.DataFrame:STRING
LOW…chive/Demos/Emoji-Gemma-on-Web/app-mediapipe/script.js154async function initializeAndAttachListeners() {CODE
LOW…/Demos/Emoji-Gemma-on-Web/app-transformersjs/script.js135async function initializeAndAttachListeners() {CODE
Excessive Try-Catch Wrapping3 hits · 4 pts
SeverityFileLineSnippetContext
MEDIUM…ve/Demos/business-email-assistant/model-tuning/main.py75 print(f"Error decoding JSON in file {filename}: {e}")CODE
LOWapps/concurrent/demo/utils.py129 except Exception as e:CODE
LOWapps/concurrent/demo/orchestrator.py156 except Exception:CODE
AI Structural Patterns3 hits · 3 pts
SeverityFileLineSnippetContext
LOW…mail-assistant/email-processing-webapp/models/gemma.py68CODE
LOW…sistant/gemma-web-service/gemma_service/gemma_model.py55CODE
LOW…/gemma-web-service/gemma_service/gemma_service_main.py39CODE
Example Usage Blocks1 hit · 2 pts
SeverityFileLineSnippetContext
LOWapps/concurrent/run.sh9# Usage:COMMENT