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LLMs-Universal-Life-Science-and-Clinical-Skills- LangGraph_Self_Hosted

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name: langgraph-self-hosted description: Deploy LangGraph Platform-compatible backends (Aegra) to run regulated biomedical agent workflows on private infrastructure with security guardrails. keywords:

  • langgraph
  • self-hosted
  • agentic-ai
  • fastapi
  • postgres measurable_outcome: Stand up a LangGraph-compatible deployment (API + persistence) behind your firewall, register at least one graph, and route traffic through it within 4 hours. license: Apache-2.0 (Aegra) metadata: author: Agentic Architecture Guild version: "2026.03" compatibility:
  • system: Docker / Kubernetes
  • system: PostgreSQL 14+ allowed-tools:
  • docker
  • run_shell_command
  • web_fetch

LangGraph Self-Hosted Skill

LangGraph Platform launched managed hosting, but biomedical programs often need on-prem control, data residency, and custom auth. Use this skill to deploy Aegra—a drop-in, open-source implementation of LangGraph Deployments that speaks the same SDK and Agent Protocol APIs.

Architecture Overview

  • API layer: FastAPI app that implements LangGraph Deployments endpoints (graph registry, runs, state streaming).
  • State store: PostgreSQL for graph metadata, run state, audit logs.
  • Execution nodes: Containerized workers (Kubernetes or Docker Compose) running LangGraph clients to execute graphs.
  • Observability: Prometheus/Grafana optional; integrate with LangSmith or OpenTelemetry exporters.

Quickstart (Docker Compose)

git clone https://github.com/ibbybuilds/aegra.git
cd aegra
cp .env.example .env
# set DATABASE_URL, SECRET_KEY, and upstream LangGraph credentials
make compose-up
  • API served on 
    http://localhost:8000
    .
  • PostgreSQL seeded with migrations via Alembic.
  • LangGraph SDK points to 
    Aegra_BASE_URL
    in your 
    .env
    .

Registering a Graph

langgraph up \
  --url http://localhost:8000 \
  --api-key $AEGRA_API_KEY \
  --graph app.graph:graph
  • Graph definitions remain unchanged—same YAML/graph builder code as hosted LangGraph.
  • Use the LangGraph Python client or REST API to create deployments, schedule runs, and stream events.

Hardening Steps

  1. Rotate secrets – set 
    SECRET_KEY
    , 
    AEGRA_SERVICE_TOKEN
    , and database credentials via a vault service.
  2. Network segmentation – run API behind an internal ingress with mTLS; expose only necessary webhook endpoints.
  3. Patch dependencies – LangChain/LangGraph recently shipped fixes for remote-code-execution bugs triggered via untrusted tool definitions; pin patched versions (
    langchain>=0.3.12
    , 
    langgraph>=0.1.22
    ) and redeploy promptly. (Ref. 3)
  4. Audit logging – enable PostgreSQL logical decoding or ship logs to SIEM for FDA/21 CFR Part 11 traceability.
  5. Availability – run two API replicas + managed Postgres (Aurora, AlloyDB) with PITR.

Integration Tips

  • Agent Protocol – Aegra implements the Agent Protocol so you can connect client SDKs or third-party orchestrators without glue code (Ref. 2).
  • LangGraph Platform (managed) – If you later migrate to LangGraph’s hosted platform, the SDK endpoints remain the same (Ref. 1). Keep staging + prod environments consistent by storing graph configs in Git.
  • Cost control – Autoscale worker deployments and leverage spot instances for non-critical experiments.

References

  1. LangChain, LangGraph Platform overview (stateful agent orchestration + deployments). https://www.langchain.com/platform/langgraph
  2. Toolerific, Aegra – self-hosted LangGraph platform alternative (FastAPI + PostgreSQL implementation, Apache license). https://toolerific.ai/ai-tools/opensource/ibbybuilds-aegra
  3. TechRadar Pro, LangChain fixes serious vulnerabilities giving attackers ability to run malicious code (February 2026). https://www.techradar.com/pro/security/langchain-fixes-serious-vulnerabilities-that-gave-hackers-the-ability-to-run-malicious-code
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