Robert Helewka
95fa6e6fc0
Make Pallas truly stateless per the 'Pallas is ephemeral' contract.
BREAKING (behavioural, not API):
* instance_scope changes from 'shared' to 'request' in pallas.server.
Each MCP tools/call now acquires a freshly-created fast-agent instance
via the existing create_instance / dispose_instance factories and
disposes it immediately after the response.
With 'shared' mode:
* Every MCP caller saw the same agent.message_history, so different
Daedalus conversations leaked into each other.
* Mid-chat context was silently truncated once the model window filled.
* Restarting the Pallas process wiped all in-flight conversation state,
even though Daedalus had it persisted in Postgres.
With 'request' mode the Pallas process holds no per-conversation state;
the caller (Daedalus) owns history and reseeds it on every turn.
send_message gains two optional arguments:
* history: list[{role, content, images?}] in chronological order,
converted to PromptMessageExtended and seeded onto the fresh
instance's message_history before agent.send().
* conversation_id: opaque string, logged for trace correlation only —
Pallas never interprets or persists it.
Malformed history entries (bad role, missing image data/mime_type, etc.)
are skipped with a warning rather than raising, so a single bad row
cannot wipe a whole conversation.
The {agent}_history MCP prompt is still registered under 'request'
scope for backward compatibility but always returns []; history lives
on the client.
Version bumped to 0.2.0.
Pallas — FastAgent MCP Bridge
Pallas is the generic runtime that turns fast-agent agent definitions into StreamableHTTP MCP servers.
It is completely deployment-agnostic: all environment-specific values (agent names, ports, hosts, model) live in the calling project's agents.yaml and fastagent.config.yaml.
Installation
pip install git+ssh://git@git.helu.ca:22022/r/pallas.git
Or as a project dependency in pyproject.toml:
dependencies = [
"pallas-mcp @ git+ssh://git@git.helu.ca:22022/r/pallas.git",
]
Usage
Pallas reads configuration from the working directory at runtime.
my-project/
├── agents/
│ ├── __init__.py
│ └── jarvis.py # FastAgent definitions
├── agents.yaml # Deployment topology
├── fastagent.config.yaml # FastAgent + model config
└── fastagent.secrets.yaml # API keys (gitignored)
Run from your project root:
pallas # start all agents + registry
pallas --agent jarvis # start a single agent
Or via python -m:
python -m pallas.server
agents.yaml format
name: my-project # used in log prefixes and registry names
version: "1.0.0"
host: my-host.example.com # hostname for registry URLs
namespace: com.example.my-project
registry_port: 8200
agents:
jarvis:
module: agents.jarvis # importable Python module path
port: 8201
title: Jarvis
description: "My assistant agent"
depends_on: [research] # optional: start these first
research:
module: agents.research
port: 8250
title: Research Agent
description: "Web search and knowledge graph"
fastagent.config.yaml extensions
Pallas reads two extra keys beyond the standard fast-agent config:
default_model: openai.my-custom-model-name
# Explicit capability declarations — avoids brittle name-regex heuristics
model_capabilities:
vision: false
context_window: 200000
max_output_tokens: 32000
Capabilities are published in the registry and used to register unknown models
with fast-agent's ModelDatabase.
Environment variable
| Variable | Default | Purpose |
|---|---|---|
PALLAS_AGENTS_CONFIG |
agents.yaml |
Override path to deployment config |
What Pallas provides
| Module | Purpose |
|---|---|
pallas.server |
CLI entry point and agent orchestration |
pallas.registry |
GET /.well-known/mcp/server.json registry server |
pallas.multimodal_server |
MultimodalAgentMCPServer — AgentMCPServer subclass with image support |
pallas.health |
LLM preflight validation + get_health MCP tool |