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Attach Gateway

Identity & Memory side‑car for every LLM engine and multi‑agent framework. Add OIDC / DID SSO, A2A hand‑off, and a pluggable memory bus (Weaviate today) – all with one process.

PyPI


Why it exists

LLM engines such as Ollama or vLLM ship with zero auth. Agent‑to‑agent protocols (Google A2A, MCP, OpenHands) assume a Bearer token is already present but don't tell you how to issue or validate it. Teams end up wiring ad‑hoc reverse proxies, leaking ports, and copy‑pasting JWT code.

Attach Gateway is that missing resource‑server:

  • ✅ Verifies OIDC / JWT or DID‑JWT
  • ✅ Stamps X‑Attach‑User + X‑Attach‑Session headers so every downstream agent/tool sees the same identity
  • ✅ Implements /a2a/tasks/send + /tasks/status for Google A2A & OpenHands hand‑off
  • ✅ Mirrors prompts & responses to a memory backend (Weaviate Docker container by default)
  • ✅ Workflow traces (Temporal)

Run it next to any model server and get secure, shareable context in under 1 minute.


60‑second Quick‑start (local laptop)

Option 1: Install from PyPI (Recommended)

# 0) prerequisites: Python 3.12, Ollama installed, Auth0 account or DID token

# Install the package
pip install attach-dev

# 1) start memory in Docker (background tab)
# Mac M1/M2 users: use manual Docker command (see examples/README.md)
docker run --rm -d -p 6666:8080 \
  -e AUTHENTICATION_ANONYMOUS_ACCESS_ENABLED=true \
  semitechnologies/weaviate:1.30.5

# 2) export your short‑lived token
export JWT="<paste Auth0 or DID token>"
export OIDC_ISSUER=https://YOUR_DOMAIN.auth0.com
export OIDC_AUD=ollama-local
export MEM_BACKEND=weaviate
export WEAVIATE_URL=http://127.0.0.1:6666

# 3) run gateway
attach-gateway --port 8080 &

# 4) make a protected Ollama call via the gateway
curl -H "Authorization: Bearer $JWT" \
     -d '{"model":"tinyllama","messages":[{"role":"user","content":"hello"}]}' \
    http://localhost:8080/api/chat | jq .

Option 2: Install from Source

# 0) prerequisites: Python 3.12, Ollama installed, Auth0 account or DID token

git clone https://github.com/attach-dev/attach-gateway.git && cd attach-gateway
python -m venv .venv && source .venv/bin/activate
pip install -r requirements.txt


# 1) start memory in Docker (background tab)

python script/start_weaviate.py &

# 2) export your short‑lived token
export JWT="<paste Auth0 or DID token>"
export OIDC_ISSUER=https://YOUR_DOMAIN.auth0.com
export OIDC_AUD=ollama-local
export MEM_BACKEND=weaviate
export WEAVIATE_URL=http://127.0.0.1:6666

# 3) run gateway
uvicorn main:app --port 8080 &

# The gateway exposes your Auth0 credentials for the demo UI at
# `/auth/config`. The values are read from `AUTH0_DOMAIN`,
# `AUTH0_CLIENT` and `OIDC_AUD`.

# 4) make a protected Ollama call via the gateway
curl -H "Authorization: Bearer $JWT" \
     -d '{"model":"tinyllama","messages":[{"role":"user","content":"hello"}]}' \
    http://localhost:8080/api/chat | jq .

In another terminal, try the Temporal demo:

pip install temporalio  # optional workflow engine
python examples/temporal_adapter/worker.py &
python examples/temporal_adapter/client.py

You should see a JSON response plus X‑ATTACH‑Session‑Id header – proof the pipeline works.


Use in your project

  1. Copy .env.example.env and fill in OIDC + backend URLs
  2. pip install attach-dev python-dotenv
  3. attach-gateway (reads .env automatically)

→ See docs/configuration.md for framework integration and examples/ for code samples.


Architecture (planner → coder hand‑off)

flowchart TD
    %%────────────────────────────────
    %%  COMPONENTS  
    %%────────────────────────────────
    subgraph Front-end
        UI["Browser<br/> demo.html"]
    end

    subgraph Gateway
        GW["Attach Gateway<br/> (OIDC SSO + A2A)"]
    end

    subgraph Agents
        PL["Planner Agent<br/>FastAPI :8100"]
        CD["Coder Agent<br/>FastAPI :8101"]
    end

    subgraph Memory
        WV["Weaviate (Docker)\nclass MemoryEvent"]
    end

    subgraph Engine
        OL["Ollama / vLLM<br/>:11434"]
    end

    %%────────────────────────────────
    %%  USER FLOW
    %%────────────────────────────────
    UI -- ① POST /a2a/tasks/send<br/>Bearer JWT, prompt --> GW

    %%─ Planner hop
    GW -- ② Proxy → planner<br/>(X-Attach-User, Session) --> PL
    PL -- ③ Write plan doc --> WV
    PL -- ④ /a2a/tasks/send\nbody:{mem_id} --> GW

    %%─ Coder hop
    GW -- ⑤ Proxy → coder --> CD
    CD -- ⑥ GET plan by mem_id --> WV
    CD -- ⑦ POST /api/chat\nprompt(plan) --> GW
    GW -- ⑧ Proxy → Ollama --> OL
    OL -- ⑨ JSON response --> GW
    GW -- ⑩ Write response to Weaviate --> WV
    GW -- ⑪ /a2a/tasks/status = done --> UI
Loading

Key headers

Header Meaning
Authorization: Bearer <JWT> OIDC or DID token proved by gateway
X‑Attach‑User stable user ID (`auth0
X‑Attach‑Session deterministic hash (user + UA) for request trace

Live two‑agent demo

# pane 1 – memory (Docker)
python script/start_weaviate.py

# pane 2 – gateway
uvicorn main:app --port 8080

# pane 3 – planner agent
uvicorn examples.agents.planner:app --port 8100

# pane 4 – coder agent
uvicorn examples.agents.coder:app   --port 8101

# pane 5 – static chat UI
cd examples/static && python -m http.server 9000
open http://localhost:9000/demo.html

Type a request like "Write Python to sort a list." The browser shows:

  1. Planner message → logged in gateway, plan row appears in memory.
  2. Coder reply → code response, second memory row, status done.

Directory map

Path Purpose
auth/ OIDC & DID‑JWT verifiers
middleware/ JWT middleware, session header, mirror trigger
a2a/ /tasks/send & /tasks/status routes
mem/ pluggable memory writers (weaviate.py, sakana.py)
proxy/ Engine-agnostic HTTP proxy logic
examples/agents/ examples – Planner & Coder FastAPI services
examples/static/ demo.html chat page

Auth core

auth.verify_jwt() accepts three token formats and routes them automatically:

  1. Standard OIDC JWTs
  2. did:key tokens
  3. did:pkh tokens

Example DID-JWT request:

curl -X POST /v1/resource \
     -H "Authorization: Bearer did:key:z6Mki...<sig>.<payload>.<sig>"

💾 Memory: logs

Send Sakana-formatted logs to the gateway and they will be stored as MemoryEvent objects in Weaviate.

curl -X POST /v1/logs \
     -H "Authorization: Bearer $JWT" \
     -d '{"run_id":"abc","level":"info","message":"hi"}'
# => HTTP/1.1 202 Accepted

Token quotas

Attach Gateway can enforce per-user token limits. Install the optional dependency with pip install attach-gateway[quota] and set MAX_TOKENS_PER_MIN in your environment to enable the middleware. The counter defaults to the cl100k_base encoding; override with QUOTA_ENCODING if your model uses a different tokenizer. The default in-memory store works in a single process and is not shared between workers—requests retried across processes may be double-counted. Use Redis for production deployments.

Enable token quotas

# Optional: Enable token quotas
export MAX_TOKENS_PER_MIN=60000
pip install tiktoken  # or pip install attach-gateway[quota]

To customize the tokenizer:

export QUOTA_ENCODING=cl100k_base  # default

Roadmap

  • v0.2 — Protected‑resource metadata endpoint (OAuth 2.1), enhanced DID resolvers.
  • v0.3 — Token‑exchange (RFC 8693) for on‑behalf‑of delegation.
  • v0.4 — Attach Store v1 (Git‑style, policy guards).

License

MIT

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Drop-in OIDC & Google A2A auth + Weaviate memory for Ollama, vLLM and any local LLM server.

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