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Fix code-docs drift, add CDK RUNTIME annotations, and add 96 cloud provider tests
- Remove phantom HuggingFace entry from auto-detect registries (TS + Python) - Add 5 missing providers to Python providers/__init__.py (AzureSpeech + 4 local) - Add RUNTIME annotations to 4 CDK classes (BaseDiscovery, KeyValueStorage, FileSecretStore, HttpHealthDiscovery) - Mark non-implemented connectors as Planned in ConnectorCatalogue - Fix stale connector IDs in docs and samples (linter-assisted) - Add 96 new TypeScript tests: 17 cloud provider suites, CONNECTOR_REGISTRY validation, Runtime Guard tests, LOCAL_PROVIDER_REGISTRY tests - Update test badges and counts: 775 Python + 466 TypeScript = 1,241 total Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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README.md

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<img src="https://img.shields.io/badge/typescript-5.0%2B-blue" alt="TypeScript 5.0+">
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<img src="https://img.shields.io/badge/docker-supported-2496ED" alt="Docker">
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<a href="LICENSE"><img src="https://img.shields.io/badge/license-MIT-green" alt="License"></a>
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<a href="https://github.com/ApartsinProjects/ModelMesh/actions"><img src="https://img.shields.io/badge/tests-808%20passed-brightgreen" alt="Tests"></a>
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<a href="https://github.com/ApartsinProjects/ModelMesh/actions"><img src="https://img.shields.io/badge/tests-1%2C241%20passed-brightgreen" alt="Tests"></a>
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<a href="https://apartsinprojects.github.io/ModelMesh/"><img src="https://img.shields.io/badge/docs-GitHub%20Pages-blue" alt="Documentation"></a>
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</p>
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git clone https://github.com/ApartsinProjects/ModelMesh.git
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cd ModelMesh
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# Run Python tests (640 tests)
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# Run Python tests (775 tests)
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pip install pytest
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cd src/python && python -m pytest ../../tests/ -v
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# Run TypeScript tests (168 tests)
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# Run TypeScript tests (466 tests)
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cd src/typescript && npm install && npm test
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```
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docs/ConnectorCatalogue.md

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docs/CoverageMatrix.md

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# Test Coverage Matrix
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Correlates documented features with test coverage. The project includes 775 Python tests across 14 test files and 370 TypeScript tests across 13 test files, for a total of 1,145 tests.
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Correlates documented features with test coverage. The project includes 775 Python tests across 14 test files and 466 TypeScript tests across 13 test files, for a total of 1,241 tests.
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---
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| CapabilityPool | 15 | `pool.test.ts` | Covered |
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| ModelMesh facade | 16 | `mesh.test.ts` | Covered |
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| Router | 5 | `router.test.ts` | Covered |
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| Pre-shipped Connectors + Local Providers + RuntimeEnvironment | 102 | `connectors.test.ts` | Covered |
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| MeshConfig + Auto-detect | 22 | `config.test.ts` | Covered |
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| Pre-shipped Connectors + Cloud/Local Providers + RuntimeEnvironment + Registry + Runtime Guard | 185 | `connectors.test.ts` | Covered |
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| MeshConfig + Auto-detect + LOCAL_PROVIDER_REGISTRY | 30 | `config.test.ts` | Covered |
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| MeshClient (OpenAI compat) | 16 | `client.test.ts` | Covered |
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| Secret Stores (env, dotenv, json, memory, encrypted, keyring) | 55 | `secret-stores.test.ts` | Covered |
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| CORS Proxy | 12 | `proxy.test.ts` | Covered |
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| **Total** | **370** | **13 files** | |
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| **Total** | **466** | **13 files** | |
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docs/SystemConfiguration.md

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enabled: true
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api_key: ${secrets:hf-api-key}
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anthropic.llm.v1:
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anthropic.claude.v1:
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enabled: false
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```
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enumerate_models: true
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huggingface.inference.v1:
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api_key: ${secrets:HF_API_KEY}
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deepseek.llm.v1:
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deepseek.api.v1:
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api_key: ${secrets:DEEPSEEK_API_KEY}
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pools:

docs/connectors/1password-connect.md

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- connector: openai.llm.v1
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auth:
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api_key: ${secrets:OPENAI_API_KEY}
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- connector: anthropic.llm.v1
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- connector: anthropic.claude.v1
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auth:
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api_key: ${secrets:ANTHROPIC_API_KEY}
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```

docs/connectors/anthropic-llm.md

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# Anthropic
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**ID:** `provider.anthropic.llm.v1`
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**ID:** `provider.anthropic.claude.v1`
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**Type:** Provider
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Anthropic is a safety-focused AI lab producing the Claude family of large language models. Claude models excel at reasoning, code generation, analysis, and long-context tasks. Anthropic emphasizes responsible AI development, and its models are known for following nuanced instructions and producing well-structured outputs. The API supports batch processing for high-volume workloads with significant cost savings.
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```yaml
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providers:
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anthropic.llm.v1:
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anthropic.claude.v1:
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api_key: ${secrets:ANTHROPIC_API_KEY}
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timeout: 120s
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max_tokens: 8192

docs/connectors/aws-secrets-manager.md

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- connector: openai.llm.v1
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auth:
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api_key: ${secrets:OPENAI_API_KEY}
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- connector: anthropic.llm.v1
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- connector: anthropic.claude.v1
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auth:
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api_key: ${secrets:ANTHROPIC_API_KEY}
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```

docs/connectors/deepseek-llm.md

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# DeepSeek
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**ID:** `provider.deepseek.llm.v1`
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**ID:** `provider.deepseek.api.v1`
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**Type:** Provider
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DeepSeek offers ultra-low-cost reasoning and chat models with the strongest price-to-performance ratio in the market. The DeepSeek platform provides two primary models: a general-purpose chat model and a dedicated reasoning model. New accounts receive 5 million free tokens with a 30-day expiry, and off-peak usage benefits from a 75% discount. DeepSeek models support tool calling and structured output, making them suitable for agent-based workflows at minimal cost.
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```yaml
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deepseek.llm.v1:
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deepseek.api.v1:
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api_key: ${secrets:DEEPSEEK_API_KEY}
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timeout: 60s
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max_retries: 3

docs/connectors/google-secret-manager.md

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- connector: openai.llm.v1
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auth:
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api_key: ${secrets:OPENAI_API_KEY}
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- connector: anthropic.llm.v1
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- connector: anthropic.claude.v1
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auth:
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api_key: ${secrets:ANTHROPIC_API_KEY}
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```

docs/connectors/groq-inference.md

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# Groq
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**ID:** `provider.groq.inference.v1`
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**ID:** `provider.groq.api.v1`
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**Type:** Provider
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Groq delivers ultra-fast AI inference powered by custom Language Processing Units (LPUs). Purpose-built silicon enables industry-leading throughput and latency for large language models, making Groq ideal for real-time applications that require sub-second response times. It supports text generation and speech-to-text workloads.
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groq.api.v1:
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```

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