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| {"config": "framework", "decision_job": "PATH_SELECTION", "limitations": ["Native method retained; numeric preference is not a probability or performance benchmark.", "Architecture proposals have no published canonical source; framework facts retain their original cutoff."], "payload_json": "{\"bestFor\": \"Python teams composing role-oriented multi-agent business processes that benefit from a concise crew abstraction and Flow-based approval routing.\", \"capabilities\": {\"approval\": {\"detail\": \"The human_feedback decorator pauses a Flow for review and can route approved, rejected, or revision outcomes to distinct listeners.\", \"sourceIds\": [\"CR-FLOWS\"], \"status\": \"native\"}, \"deployment\": {\"detail\": \"Python services can self-host crews and Flows; AMP offers GitHub-, CLI-, or Studio-driven managed deployments with generated API access.\", \"sourceIds\": [\"CR-AMP\", \"CR-PROD\"], \"status\": \"self-host-or-managed\"}, \"observability\": {\"detail\": \"CrewAI exposes execution tracing, while the managed AMP platform adds detailed traces, logs, team controls, and production monitoring.\", \"sourceIds\": [\"CR-DOCS\", \"CR-AMP\"], \"status\": \"integrated\"}, \"recovery\": {\"detail\": \"Persisted Flow state survives restarts and can resume by ID, but the deployment must supply durable storage and idempotent side-effect handling.\", \"sourceIds\": [\"CR-FLOWS\", \"CR-PROD\"], \"status\": \"configured\"}, \"state\": {\"detail\": \"The persist decorator stores Flow state, uses SQLite by default, and supports resuming or forking a persisted flow by state identifier.\", \"sourceIds\": [\"CR-FLOWS\"], \"status\": \"native\"}}, \"constraints\": \"Crews and Flows are different orchestration layers. Durable production behavior depends on configuring persistence and the surrounding runtime rather than assuming a crew definition is automatically recoverable.\", \"deploymentControl\": [\"self-host\", \"managed\"], \"disqualifiers\": [\"The core application stack is TypeScript or .NET with no Python service boundary\", \"The workflow requires graph-level checkpoint semantics to be the primary programming model\"], \"id\": \"crewai\", \"languages\": [\"python\"], \"license\": \"MIT\", \"modelStrategy\": [\"agnostic\"], \"name\": \"CrewAI\", \"orchestrationModel\": \"Role-based crews for agent collaboration plus event-driven Flows for routing, persistence, and approval points.\", \"priorities\": [\"multi-agent\", \"approval\", \"rapid-composition\", \"managed-cloud\"], \"release\": {\"publishedAt\": \"2026-08-27\", \"sourceId\": \"CR-REL\", \"track\": \"Python\", \"version\": \"1.15.18\"}, \"tradeoffs\": [\"Concise role and task composition\", \"Flows add operational control but create a second mental model\", \"Managed deployment and full observability are concentrated in CrewAI AMP\"]}", "record_id": "crewai", "record_type": "FRAMEWORK_PROFILE", "review_status": "NOT_REVIEWED", "snapshot_at": "2026-09-17T06:17:24Z", "source_commit_sha": "b1213f374722edde01ca74a7ccac68e835070705", "source_data_hash": "sha256:42ad1d6f7dae557ab024be640e13271ce9f8b19f81ffe808880de3bef3b5cd8b", "source_url": "https://github.com/PharosProduction/enterprise-ai-agent-frameworks/blob/b1213f374722edde01ca74a7ccac68e835070705/data/frameworks.json", "status": "DRAFT", "verified_at": null} |
| {"config": "framework", "decision_job": "PATH_SELECTION", "limitations": ["Native method retained; numeric preference is not a probability or performance benchmark.", "Architecture proposals have no published canonical source; framework facts retain their original cutoff."], "payload_json": "{\"bestFor\": \"Python products centered on OpenAI models that need a small orchestration surface, built-in tracing, sessions, guardrails, and tool approval.\", \"capabilities\": {\"approval\": {\"detail\": \"Tools can require approval, paused RunState can be serialized, and unresolved interruptions remain pending until approved or rejected.\", \"sourceIds\": [\"OA-HITL\"], \"status\": \"native\"}, \"deployment\": {\"detail\": \"The SDK runs inside a Python application; teams choose their hosting and add a durable orchestrator when workflows span long waits or process restarts.\", \"sourceIds\": [\"OA-RUN\"], \"status\": \"application-owned\"}, \"observability\": {\"detail\": \"Built-in tracing records model generations, tool calls, handoffs, guardrails, and custom events with controls for sensitive trace content.\", \"sourceIds\": [\"OA-TRACE\"], \"status\": \"native\"}, \"recovery\": {\"detail\": \"Serialized run state supports approval pause/resume; process-restart durability and automatic recovery use documented Dapr, Temporal, Restate, or DBOS integrations.\", \"sourceIds\": [\"OA-HITL\", \"OA-RUN\"], \"status\": \"external-runtime\"}, \"state\": {\"detail\": \"Sessions store conversation history through SQLite, Redis, SQLAlchemy, Dapr, encrypted, file-backed, or OpenAI-managed implementations.\", \"sourceIds\": [\"OA-RUN\"], \"status\": \"native\"}}, \"constraints\": \"The SDK manages the agent loop, but durable long-running recovery comes through Dapr, Temporal, Restate, DBOS, or application infrastructure rather than a built-in workflow server.\", \"deploymentControl\": [\"self-host\", \"managed\"], \"disqualifiers\": [\"Provider neutrality is a hard procurement requirement\", \"The system needs a built-in graph runtime and checkpoint manager without external workflow infrastructure\"], \"id\": \"openai-agents-sdk\", \"languages\": [\"python\"], \"license\": \"MIT\", \"modelStrategy\": [\"openai\", \"agnostic-with-adapters\"], \"name\": \"OpenAI Agents SDK\", \"orchestrationModel\": \"A compact runner with agents, tools, handoffs, guardrails, sessions, interruptions, and tracing.\", \"priorities\": [\"approval\", \"observability\", \"minimal-sdk\", \"openai-stack\"], \"release\": {\"publishedAt\": \"2026-08-19\", \"sourceId\": \"OA-REL\", \"track\": \"Python\", \"version\": \"0.22.0\"}, \"tradeoffs\": [\"Small API surface and first-party OpenAI integrations\", \"Provider adapters exist but the default path is OpenAI-first\", \"Durability adds an external orchestration dependency\"]}", "record_id": "openai-agents-sdk", "record_type": "FRAMEWORK_PROFILE", "review_status": "NOT_REVIEWED", "snapshot_at": "2026-09-17T06:17:24Z", "source_commit_sha": "b1213f374722edde01ca74a7ccac68e835070705", "source_data_hash": "sha256:42ad1d6f7dae557ab024be640e13271ce9f8b19f81ffe808880de3bef3b5cd8b", "source_url": "https://github.com/PharosProduction/enterprise-ai-agent-frameworks/blob/b1213f374722edde01ca74a7ccac68e835070705/data/frameworks.json", "status": "DRAFT", "verified_at": null} |
| {"config": "framework", "decision_job": "PATH_SELECTION", "limitations": ["Native method retained; numeric preference is not a probability or performance benchmark.", "Architecture proposals have no published canonical source; framework facts retain their original cutoff."], "payload_json": "{\"bestFor\": \"Multi-language teams using Gemini or Google Cloud that want one agent toolkit across local development, Agent Runtime, Cloud Run, and GKE.\", \"capabilities\": {\"approval\": {\"detail\": \"Graph workflows can request external human input and resume through the workflow runtime rather than hiding approval inside prompt text.\", \"sourceIds\": [\"GA-HITL\", \"GA-RESUME\"], \"status\": \"native\"}, \"deployment\": {\"detail\": \"Documented targets include Agent Runtime, Cloud Run, and GKE, with CLI support for CI/CD, service identity, secrets, scaling, and observability.\", \"sourceIds\": [\"GA-DEPLOY\"], \"status\": \"self-host-or-managed\"}, \"observability\": {\"detail\": \"OpenTelemetry instrumentation exports agent and tool traces; Google tooling connects traces to Cloud Trace and optional BigQuery analytics.\", \"sourceIds\": [\"GA-OBS\"], \"status\": \"integrated\"}, \"recovery\": {\"detail\": \"Resumable workflow sessions persist execution progress and continue graph work after interruption when backed by a persistent session service.\", \"sourceIds\": [\"GA-RESUME\", \"GA-STATE\"], \"status\": \"native\"}, \"state\": {\"detail\": \"Serializable session state is persisted by DatabaseSessionService or VertexAiSessionService; InMemorySessionService loses state on restart.\", \"sourceIds\": [\"GA-STATE\"], \"status\": \"native\"}}, \"constraints\": \"Session persistence depends on the selected SessionService, and operational features differ across SDK languages and deployment targets. In-memory sessions do not survive a restart.\", \"deploymentControl\": [\"self-host\", \"managed\"], \"disqualifiers\": [\"The organization requires a cloud-neutral operations plane\", \"The chosen language needs a feature that exists only in another ADK SDK\"], \"id\": \"google-adk\", \"languages\": [\"python\", \"typescript\", \"go\", \"java\", \"kotlin\"], \"license\": \"Apache-2.0\", \"modelStrategy\": [\"google\", \"agnostic\"], \"name\": \"Google ADK\", \"orchestrationModel\": \"LLM agents, deterministic sequential/parallel/loop agents, and graph workflows backed by sessions and events.\", \"priorities\": [\"multi-language\", \"managed-cloud\", \"observability\", \"google-stack\", \"multi-agent\"], \"release\": {\"publishedAt\": \"2026-08-26\", \"sourceId\": \"GA-REL\", \"track\": \"Python\", \"version\": \"2.8.0\"}, \"tradeoffs\": [\"Broad language coverage and Google Cloud deployment paths\", \"Strongest operational path assumes Google Cloud\", \"Teams must verify feature parity for their chosen language\"]}", "record_id": "google-adk", "record_type": "FRAMEWORK_PROFILE", "review_status": "NOT_REVIEWED", "snapshot_at": "2026-09-17T06:17:24Z", "source_commit_sha": "b1213f374722edde01ca74a7ccac68e835070705", "source_data_hash": "sha256:42ad1d6f7dae557ab024be640e13271ce9f8b19f81ffe808880de3bef3b5cd8b", "source_url": "https://github.com/PharosProduction/enterprise-ai-agent-frameworks/blob/b1213f374722edde01ca74a7ccac68e835070705/data/frameworks.json", "status": "DRAFT", "verified_at": null} |
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