AgentPaaS Platform Documentation

AgentPaaS is a Platform-as-a-Service for deploying, managing, and running Lambda-calculus-based AI agents. It wraps the lambdagent DSL with a multi-tenant API server, persistent sessions, provider management, and monitoring.

Architecture Overview

                    CLI / HTTP Client
                          |
                    ┌─────▼─────┐
                    │  FastAPI   │   agentpaas/src/agentpaas/api/app.py
                    │  Server    │   (serve --dev)
                    └─────┬─────┘
                          |
           ┌──────────────┼──────────────┐
           |              |              |
    ┌──────▼──────┐ ┌────▼────┐ ┌───────▼───────┐
    │ Agent CRUD  │ │ Auth /  │ │ Status /      │
    │ + Execution │ │ Tenant  │ │ Metrics       │
    └──────┬──────┘ └─────────┘ └───────────────┘
           |
    ┌──────▼──────────────────────┐
    │   lambdagent Engine         │
    │   (Compiler + Runtime)      │
    │                             │
    │   YAML → Lambda Term → CEK  │
    │   ConversationLam (session) │
    └──────┬──────────────────────┘
           |
    ┌──────▼──────────────────────┐
    │   Unified Provider System   │
    │                             │
    │   claude-code  (no API key) │
    │   anthropic    (API key)    │
    │   ollama       (local)      │
    │   openai       (API key)    │
    │   dashscope    (API key)    │
    └─────────────────────────────┘

Key components:

FastAPI Server (agentpaas serve) — REST API with multi-tenant auth, SSE streaming, OpenAPI docs at /docs.
Agent Store — SQLite/Postgres-backed CRUD for agent configs, versions, run history.
lambdagent Engine — Compiles YAML into Lambda terms, executes via CEK machine with ReAct loops, tool routing, and beta-reduction tracing.
ConversationLam — Session-persistent Lambda abstraction that maintains conversation history across turns.
Unified Provider System — Five core providers with automatic detection and YAML-based switching.

Agent Lifecycle

1. Create

Define an agent via YAML config and deploy to the platform:

# Write YAML config
cat > my-agent.yml <<'EOF'
agentId: my-agent
name: MyAgent
type: react
model:
  provider: claude-code
  name: sonnet
systemPrompt: "You are a helpful research assistant."
react:
  maxSteps: 10
EOF

# Lint before deploying
python -m lambdagent lint my-agent.yml

# Deploy to PaaS
python -m agentpaas agent create --name my-agent --config my-agent.yml
# Output: Agent created: ag_abc123

2. Deploy

The agent is live immediately after agent create. The PaaS server compiles the YAML into a Lambda term at execution time, so no build step is needed. The API endpoint is:

POST /api/v1/agents/{agent_id}/run
POST /api/v1/agents/{agent_id}/run/stream   (SSE)

3. Chat (Interactive)

Use agentpaas chat for interactive multi-turn conversation:

agentpaas chat my-agent

The chat command resolves the agent by name (fuzzy match) or ID, opens an interactive session with SSE streaming, and maintains conversation context server-side.

With provider: claude-code in the YAML config, no API key is required -- the agent calls Claude Code CLI directly.

4. Update

Iterate on the agent config with automatic versioning:

# Edit config, then update
python -m agentpaas agent update ag_abc123 --config my-agent-v2.yml --changelog "Added search tools"

# View version history
python -m agentpaas agent versions ag_abc123

# Rollback if needed
python -m agentpaas agent rollback ag_abc123 --version 1

Each update increments the version. If the config content is unchanged, no new version is created.

Provider Configuration

AgentPaaS uses a unified provider system. The provider is specified in the agent's YAML config under model.provider:

Provider	Type	API Key Required	Notes
`claude-code`	Claude Code CLI	No	Uses Claude Code Max Plan subscription
`anthropic`	Anthropic API	Yes (`ANTHROPIC_API_KEY`)	Direct API access
`ollama`	Local inference	No	Requires `ollama serve` running locally
`openai`	OpenAI API	Yes (`OPENAI_API_KEY`)	GPT models
`dashscope`	Alibaba Cloud	Yes (`DASHSCOPE_API_KEY`)	Qwen models

Provider in YAML

model:
  provider: claude-code   # Switch provider here
  name: sonnet            # Model name (provider-specific)
  temperature: 0.0

Provider detection priority

When provider is not specified, the system auto-detects:

If model name has a known prefix (e.g., dashscope/qwen-max), use that provider.
If model name matches known patterns (e.g., claude-* -> anthropic, gpt-* -> openai).
Fall back to environment variable detection.

Managing providers via CLI

# List providers and status
python -m agentpaas provider list

# Test a provider connection
python -m agentpaas provider test anthropic

# Add/configure a provider
python -m agentpaas provider add dashscope --api-key sk-xxxx

Session Persistence via ConversationLam

ConversationLam is the core mechanism for multi-turn conversation support. It wraps any LLMProvider with conversation history management.

Lambda semantics

ConversationLam(provider, prompt) = lambda x. provider(history ++ [x])

Each apply() call:

Appends the input as a user message to the history.
Calls the provider with the full conversation (or windowed subset).
Records the assistant response.
Returns the response.

Key difference from stateless Lam

	`Lam`	`ConversationLam`
State	Stateless -- each call is independent	Stateful -- builds on all previous calls
History	None	Full message list with windowing
Use case	Single-shot tasks	Multi-turn chat, ReAct loops

Configuration

from lambdagent.conversation import ConversationLam
from lambdagent.providers.claude_code_provider import ClaudeCodeProvider

provider = ClaudeCodeProvider(config)
lam = ConversationLam(
    name="agent",
    provider=provider,
    system_prompt="You are a helpful assistant.",
    max_history_tokens=80000,   # Token window limit
    keep_recent_turns=20,       # Minimum recent turns to keep
)

r1 = lam.apply("read the README")       # Creates conversation
r2 = lam.apply("[tool result] ...")       # Continues with full memory
r3 = lam.apply("summarize what we did")   # Still remembers r1, r2

This is what eliminates hallucination in multi-step ReAct agents: the LLM sees its complete conversation history, not a lossy compressed state string.

MCP Isolation: --strict-mcp-config

By default, agents inherit globally available MCP tools. The --strict-mcp-config flag (or strictMcpConfig: true in YAML) enables MCP isolation: the agent can only access tools explicitly declared in its own config.

strictMcpConfig: true
mcp:
  onlineTool:
    my-server:
      - search
      - read_file
  localTools:
    - terminate

This is important for multi-tenant deployments where agents should not access each other's tools.

API Endpoints Overview

All endpoints are under /api/v1/ and require an API key header (X-API-Key).

Agents

Method	Path	Description
`POST`	`/agents`	Create agent
`GET`	`/agents`	List agents
`GET`	`/agents/{id}`	Get agent details
`PUT`	`/agents/{id}`	Update agent config
`DELETE`	`/agents/{id}`	Delete agent (soft)
`POST`	`/agents/{id}/rollback`	Rollback to version
`GET`	`/agents/{id}/versions`	List versions

Execution

Method	Path	Description
`POST`	`/agents/{id}/run`	Execute agent (sync)
`POST`	`/agents/{id}/run/stream`	Execute agent (SSE streaming)
`GET`	`/agents/{id}/runs`	List run history
`POST`	`/agents/{id}/runs/record`	Record external run

Auth & Tenants

Method	Path	Description
`POST`	`/auth/keys`	Create API key
`GET`	`/auth/keys`	List API keys
`DELETE`	`/auth/keys/{id}`	Revoke API key
`POST`	`/admin/tenants`	Create tenant
`GET`	`/admin/tenants/{id}`	Get tenant
`PUT`	`/admin/tenants/{id}/quota`	Update quota

Monitoring

Method	Path	Description
`GET`	`/status`	Platform overview
`GET`	`/status/agents`	All agents status
`GET`	`/status/agents/{id}`	Single agent status
`GET`	`/status/agents/{id}/health`	Health score
`GET`	`/metrics/overview`	Platform metrics
`GET`	`/billing/usage`	Usage/billing data

Traces

Method	Path	Description
`GET`	`/traces/{run_id}`	Get run trace
`GET`	`/traces/{run_id}/tools`	Get tool calls
`POST`	`/traces/{run_id}/confirm`	Confirm tool action

Other

Method	Path	Description
`GET`	`/health`	Server health check
`GET`	`/.well-known/agent.json`	Agent discovery
`GET`	`/jobs/{id}`	Async job status
`POST`	`/jobs/{id}/cancel`	Cancel async job

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