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▤TemplateAgentic capabilityFree

create-llama

CLI scaffolder for full-stack LlamaIndex RAG and agentic apps — Next.js, FastAPI, or Express in one command.

@ai-supply
Installs201k
⟳ upstream @llamaindex/server@0.3.0 · updated 1y ago
↗ Source repository
← More Agentic capabilityAgentic capability leaderboard →How we grade security →Source ↗
! Grade B · 75/100 · ReviewSecurity assessment
✓No compromise signals10capabilities surfaced1known CVE8of 20 OWASP controls clear
Broad capability surfaceSuspicious network referencesSuspicious network referencesSuspicious network references
scanned 17d ago·osv · gitleaks · opengrep · picklescan + heuristics·full breakdown in the Security tab ↓

create-llama

create-llama is an interactive CLI that bootstraps production-ready LlamaIndex applications in seconds. It generates a fully wired full-stack project — your choice of Next.js, Python FastAPI, or Express backend — with document ingestion, vector storage, chat UI, streaming, and optional agentic tools pre-configured.

Key Features

  • Full-stack templates: Next.js + Python FastAPI, Next.js + Express, or Python API-only
  • One-command setup: interactive prompts select model provider (OpenAI, Anthropic, Groq, Ollama), vector store (Pinecone, Chroma, Qdrant, in-memory), and data sources
  • Streaming chat UI: complete React chat interface with streaming tokens, file upload, and multi-turn history
  • Document pipelines: PDF, Markdown, HTML, CSV ingestion with chunking + embedding baked in
  • Agentic mode: toggle agent mode to add tool-calling loops with DuckDuckGo search, code interpreter, and custom tools
  • Production-ready: Docker Compose, Vercel deploy button, and .env management all included

Quick Start

npx create-llama@latest
# Interactive wizard: pick stack, model, vector store
# Then:
cd my-llama-app && npm run dev
npx ai-supply add create-llama-fullstack-scaffold

Curated mirror of the open-source create-llama (MIT). Get it from the source.

Rating rank
#1
of 35 in Agentic capability
Install rank
#12
of 35 in Agentic capability
Security score
75/100 · B
review
Security rank
#23
of 35 in Agentic capability
Installs
201k
cat avg 186k
This listing vs category average
Installs
this
cat avg
Security (of 100)
this
cat avg
Adoption trend
See the Agentic capability leaderboard →
! Security: Review · 7575/100 · grade Bscanned 17d ago
✓ no compromise signals11 risk-surface · 6/20 OWASP controls flagged

Compromise signals — malicious or tampered code (leaked secrets, backdoors, a dropped executable) — reduce the score, and known dependency CVEs carry a bounded penalty (they warrant review but never QUARANTINE — update the dependency to clear). Other dangerous-by-capability traits are risk surface, expected for some capabilities. Every finding is mapped to its OWASP control below.

Prompt card · med confidence (static)
{matrix.os}{secrets.OPENAI_API_KEY}{secrets.LLAMA_CLOUD_API_KEY}{matrix.frameworks}{matrix.vectordbs}{env.SERVER_PACKAGE_PATH}{github.ref}{secrets.GITHUB_TOKEN}{github.workflow}{secrets.NPM_TOKEN}{new_version}{secrets.PYPI_TOKEN}{env.PYTHON_VERSION}{github.workspace}{steps.get_whl_path.outputs.whl_file}{appName}{appPath}{root}{useCase}{templateFramework}{vectorDb}{port}{e}{responseBody}

Findings mapped to the OWASP Top 10 for LLM Applications (2025) and the OWASP Machine Learning Security Top 10. Expand any flagged control for the exact findings — compromise reduces the score; expected/risk-surface do not, except a known CVE, which carries a small bounded penalty (high/critical → Review).

OWASP Top 10 for LLM Applications
⚠LLM03Supply Chaincritical
Vulnerable/compromised dependencies, models or archives in the artifact.
•Dependency manifest — 18 npm dependencies declared · run-llama-create-llama-97a7d9b/package.jsonrisk surface
•Dependency manifest — 31 npm dependencies declared · run-llama-create-llama-97a7d9b/packages/create-llama/package.jsonrisk surface
•Dependency manifest — 6 npm dependencies declared · run-llama-create-llama-97a7d9b/packages/create-llama/templates/components/ts-proxy/package.jsonrisk surface
•Dependency manifest — 11 npm dependencies declared · run-llama-create-llama-97a7d9b/packages/create-llama/templates/types/llamaindexserver/nextjs/package.jsonrisk surface
•Dependency manifest — 1 npm dependencies declared · run-llama-create-llama-97a7d9b/python/llama-index-server/package.jsonrisk surface
•Vulnerable dependencies — 307 known vulnerabilities in: @ai-sdk/provider-utils@2.2.7, @eslint/plugin-kit@0.2.8, @modelcontextprotocol/sdk@1.13.2, ai@4.3.10, ajv@6.12.6, ajv@8.17.1, body-parser@2.2.0, brace-expansion@1.1.11 (CWE-1395)known CVE · -25 pts
⚠LLM05Improper Output Handlinghigh
Code that pipes model/user output into shell, eval, SQL or paths unsafely.
•Suspicious code patterns — pipe-to-shell install · run-llama-create-llama-97a7d9b/.github/workflows/e2e.yml (CWE-494)expected
•Suspicious code patterns — child_process exec · run-llama-create-llama-97a7d9b/packages/create-llama/e2e/python/resolve_dependencies.spec.ts (CWE-78)expected
•Suspicious code patterns — child_process exec; dynamic code execution · run-llama-create-llama-97a7d9b/packages/create-llama/e2e/utils.ts (CWE-78)expected
•Suspicious code patterns — dynamic code execution · run-llama-create-llama-97a7d9b/packages/create-llama/templates/components/reflex/extractor/app/services/extractor.py (CWE-95)expected
•Suspicious code patterns — OS command execution · run-llama-create-llama-97a7d9b/python/llama-index-server/examples/hitl/agent_workflow.py (CWE-78)expected
⚠LLM06Excessive Agencylow
Over-broad tool/permission surface or unrestricted egress.
•Broad capability surface — 3 high-impact capability categories referenced — verify least-privilege · run-llama-create-llama-97a7d9b/packages/create-llama/e2e/shared/llamaindexserver_template.spec.ts (CWE-272)risk surface
•Broad capability surface — 4 high-impact capability categories referenced — verify least-privilege · run-llama-create-llama-97a7d9b/pnpm-lock.yaml (CWE-272)risk surface
§LLM09MisinformationGovernance
Artifacts designed to produce false/deceptive output.
Detectable only by runtime behavioral evaluation; addressed via responsible-use attestation.
◷LLM10Unbounded ConsumptionRuntime-enforced
Unbounded loops/recursion causing DoS or runaway cost.
Enforced at runtime by the gateway (rate limits + spend caps + size caps); static check flags unbounded loops.
✓LLM01Prompt InjectionPassed
✓LLM02Sensitive Information DisclosurePassed
✓LLM04Data and Model PoisoningPassed
Backdoors/poisoning in training data or serialized models.
Behavioral poisoning needs model execution; static check covers unsafe serialization + dataset skew only.
✓LLM07System Prompt LeakagePassed
✓LLM08Vector and Embedding WeaknessesPassed
PII or plaintext source leakage in embedding/vector exports.
Embedding inversion/poisoning is largely runtime; static check covers PII in vector exports.
OWASP Machine Learning Security Top 10
⚠ML06AI Supply Chaincritical
Compromised PyPI/npm packages, typosquats, unsafe serialized models.
•Dependency manifest — 18 npm dependencies declared · run-llama-create-llama-97a7d9b/package.jsonrisk surface
•Dependency manifest — 31 npm dependencies declared · run-llama-create-llama-97a7d9b/packages/create-llama/package.jsonrisk surface
•Dependency manifest — 6 npm dependencies declared · run-llama-create-llama-97a7d9b/packages/create-llama/templates/components/ts-proxy/package.jsonrisk surface
•Dependency manifest — 11 npm dependencies declared · run-llama-create-llama-97a7d9b/packages/create-llama/templates/types/llamaindexserver/nextjs/package.jsonrisk surface
•Dependency manifest — 1 npm dependencies declared · run-llama-create-llama-97a7d9b/python/llama-index-server/package.jsonrisk surface
•Vulnerable dependencies — 307 known vulnerabilities in: @ai-sdk/provider-utils@2.2.7, @eslint/plugin-kit@0.2.8, @modelcontextprotocol/sdk@1.13.2, ai@4.3.10, ajv@6.12.6, ajv@8.17.1, body-parser@2.2.0, brace-expansion@1.1.11 (CWE-1395)known CVE · -25 pts
⚠ML09Output Integrityhigh
Middleware tampering with model outputs in transit.
Gateway enforces TLS + response integrity; static check flags output-rewriting code.
•Suspicious code patterns — pipe-to-shell install · run-llama-create-llama-97a7d9b/.github/workflows/e2e.yml (CWE-494)expected
•Suspicious code patterns — child_process exec · run-llama-create-llama-97a7d9b/packages/create-llama/e2e/python/resolve_dependencies.spec.ts (CWE-78)expected
•Suspicious code patterns — child_process exec; dynamic code execution · run-llama-create-llama-97a7d9b/packages/create-llama/e2e/utils.ts (CWE-78)expected
•Suspicious code patterns — dynamic code execution · run-llama-create-llama-97a7d9b/packages/create-llama/templates/components/reflex/extractor/app/services/extractor.py (CWE-95)expected
•Suspicious code patterns — OS command execution · run-llama-create-llama-97a7d9b/python/llama-index-server/examples/hitl/agent_workflow.py (CWE-78)expected
⚠ML05Model Theftlow
Unlicensed re-distribution / license-incompatible derivatives.
Static check verifies license declaration; extraction throttling is runtime.
•No license signal — no SPDX id or license keyword found · run-llama-create-llama-97a7d9b/.changeset/config.jsonrisk surface
§ML01Input Manipulation (Adversarial)Governance
Models vulnerable to adversarial perturbations.
Requires runtime robustness evaluation; addressed via publisher robustness attestation.
§ML03Model InversionGovernance
Training data reconstructable from a model's outputs.
Runtime/evaluation property; addressed via model-card data-provenance + DP attestation.
§ML04Membership InferenceGovernance
Determining whether a record was in the training set.
Runtime/evaluation property; addressed via overfitting disclosure + DP attestation.
§ML08Model SkewingGovernance
Models trained on skewed data producing biased output.
Requires fairness evaluation; addressed via model-card bias/limitations disclosure.
✓ML02Data PoisoningPassed
Poisoned training datasets with triggers or anomalous distributions.
Static check covers trigger phrasing, PII and label skew; full poisoning detection is runtime.
✓ML07Transfer Learning AttackPassed
Backdoored base models / LoRA adapters propagating to derivatives.
Backdoor detection needs behavioral probing; static check covers unsafe serialization + provenance.
✓ML10Model Poisoning (Weights)Passed
Tampered model weight files; integrity must be verifiable.
Static check enforces safe formats + records a content hash for downstream verification.
Other findings (9) · hygiene / uncategorized
•Unrecognized file type — '.gitignore' is not on the allowlist · run-llama-create-llama-97a7d9b/.gitignorerisk surface
•Unrecognized file type — '.?' is not on the allowlist · run-llama-create-llama-97a7d9b/.husky/pre-commitrisk surface
•Unrecognized file type — '.npmrc' is not on the allowlist · run-llama-create-llama-97a7d9b/.npmrcrisk surface
•Unrecognized file type — '.nvmrc' is not on the allowlist · run-llama-create-llama-97a7d9b/.nvmrcrisk surface
•Unrecognized file type — '.prettierignore' is not on the allowlist · run-llama-create-llama-97a7d9b/.prettierignorerisk surface
•Unrecognized file type — '.mjs' is not on the allowlist · run-llama-create-llama-97a7d9b/eslint.config.mjsrisk surface
•Suspicious network references — raw IP URL (9 URLs) · run-llama-create-llama-97a7d9b/packages/create-llama/helpers/env-variables.tsrisk surface
•Suspicious network references — raw IP URL (1 URLs) · run-llama-create-llama-97a7d9b/packages/create-llama/templates/components/providers/python/ollama/settings.pyrisk surface
•Suspicious network references — raw IP URL (17 URLs) · run-llama-create-llama-97a7d9b/packages/create-llama/templates/components/use-cases/python/agentic_rag/README-template.mdrisk surface
✔ verified source · pinned run-llama-create-llama-97a7d9b
Check against a policy

The same gate an agent runs before installing (POST /api/v1/trust/create-llama-fullstack-scaffold/check). Click a policy:

Consume create-llama programmatically. Authenticate with an API key or session — see Authorize an agent.

# Agents: CHECK BEFORE YOU INSTALL (no auth) — score, grade, level, capability manifest
curl https://ai-supply.store/api/v1/trust/create-llama-fullstack-scaffold

# Gate against your org policy (returns { pass, violations })
curl -X POST https://ai-supply.store/api/v1/trust/create-llama-fullstack-scaffold/check \
  -H "Content-Type: application/json" \
  -d '{"minGrade":"B","denyPermissions":["shell"],"denyUnknownEgress":true}'

# CLI
npx ai-supply add create-llama-fullstack-scaffold

# REST (install → download)
curl -X POST https://ai-supply.store/api/v1/listings/create-llama-fullstack-scaffold/install \
  -H "Authorization: Bearer $AIM_KEY"

# MCP tool
install_listing({ "slug": "create-llama-fullstack-scaffold" })
OpenAPI spec →
vlatest
! Security: Review · 751mo ago

Curated mirror — latest upstream source. See the repository for tagged releases.

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