CopeNet

CopeNet is a continuity engine agent operator for people who want more than a chat box. It gives you a persistent workspace for running local and CLI-backed models, inspecting what they actually did, and turning useful sessions into repeatable workflows.

Product Tour

CopeNet keeps the operator surface compact: start from Home, work with agents, investigate markets, and inspect the evidence behind every run. The full catalog lives in the Feature Glossary.

Home

Home is the launchpad for active sessions, provider health, recent work, quick actions, market context, and system status.

Agents

Agents keeps persistent conversations beside their runtime context. Provider, model, profile, persona, Access, tools, and retained evidence stay visible instead of disappearing behind the answer.

Market

Market is a sectioned research workstation rather than a wall of tickers. The daily brief combines watchlists, SEC evidence, rotation, accumulation signals, macro context, and an accountable forward ledger.

Ticker workspace

Each ticker opens a chart-first workspace for price history, filings, financial overlays, alerts, comparisons, position context, and scoped agent research.

Observability

Observability reconstructs the work behind a response: model input, provider metadata, tool arguments and results, reasoning provenance, final output, usage, and the raw trace.

Why CopeNet

CopeNet started as a local-only project — small models on-device, no cloud dependency. That fell apart fast: small local models can't reliably plan multi-step tool use or hold an operator workflow together, so CopeNet grew a CLI-backed and subscription-backed provider layer (claude-cli, openai-codex) and, in September 2026, dropped the local runtimes entirely. Local-first is still the posture — sessions, transcripts, and control stay on your machine — but the models doing the reasoning are frontier-capable.

Most local AI tools stop at “send a prompt, get a reply.” CopeNet is built for the workflows that happen after that:

• Operate locally: keep models, transcripts, and sensitive context close to your machine
• Inspect runs: see traces, tool activity, runtime drift, and session state instead of guessing
• Reuse workflows: move from one-off chats to repeatable operator surfaces
• Compare runtimes: lock sessions to provider/model combinations so behavior stays explainable
• Extend without cloud lock-in: add prompts, tools, workflows, and knowledge sources without giving up local control

What You Can Do

CopeNet is evolving into an operator workspace, not just a chat client. Today it already supports:

• Agent sessions with persistent transcripts, first-send runtime binding (provider/profile lock; model + Access changeable mid-session), archive/restore, and inline tool execution
• Fleet rooms where ChatGPT and Claude independently research the same question, share evidence receipts after reveal, and critique each other in attributed follow-up turns
• Observability with a per-run timeline, provider reasoning provenance, exact tool evidence, model-input snapshots, and raw local traces
• Media imports for transcription and download-first workflows, including mobile-friendly remote use over Tailscale
• Experiments for comparing provider/model behavior across real runs
• Profile + Access layering: behavioral Profiles (markdown presets) plus a separate Read-only · Ask · Full Access permission axis with operator approvals and a persisted shell allowlist
• Market Monitor: a daily model-generated brief backed by live SEC filings, sector rotation, and a pre-registered forward ledger that scores its own calls

Providers

CopeNet runs two frontier lanes through one shared harness:

• claude-cli — local claude CLI subprocess
• openai-codex — OpenAI Codex via OAuth (uv run copenet auth login --provider openai-codex)

The goal is provider-agnostic operator tooling: one workspace, multiple runtimes, consistent session semantics. See docs/CAPABILITY-MATRIX.md for tool-loop and feature support per provider.

Quickstart

1) Prerequisites

• Python 3.12+
• uv
• Node.js 20+ and npm

You do not need a model provider or the separate CopeTech-Edgar repository before installing. CopeNet starts first, then Home walks you through either OpenAI Codex OAuth or Claude CLI setup.

2) Install dependencies

git clone https://github.com/pattty847/CopeNet.git
cd CopeNet
./scripts/setup.sh

That one command installs the Python environment, installs the frontend packages, and builds the UI. To include SEC filings, fundamentals, and insider evidence in Market, use ./scripts/setup.sh --with-sec. The optional package is fetched from GitHub; no sibling checkout is required. Market charts and price data still work without it.

3) Run CopeNet

uv run copenet

Open the desktop UI at:

• http://127.0.0.1:17123

On first launch, the Home page shows provider readiness:

• OpenAI Codex: choose Start OpenAI OAuth and finish in the browser.
• Claude CLI: install claude if it is missing, then run claude auth login.

You only need one ready provider to create a chat. The terminal equivalents are:

uv run copenet auth login --provider openai-codex
claude auth login

4) Optional: open it remotely on your own devices

CopeNet also works well over your tailnet for private mobile access:

# One-time setup: keep a random token in the dedicated, gitignored host env file.
umask 077
printf 'COPNET_TOKEN="%s"\nCOPNET_PORT=17123\n' \
  "$(python3 -c 'import secrets; print(secrets.token_urlsafe(32))')" > .copenet.env

# Launch on this Mac's Tailscale IPv4 only (not every local network interface).
COPNET_HOST=tailscale uv run --env-file .copenet.env copenet

Then open it from another device using your Tailscale hostname or tailnet IP. When the authentication banner appears, enter the same token once; CopeNet stores it only in that browser and reuses it on later visits. Do not embed the token in a shared URL.

Local Setup Notes

1. Run ./scripts/setup.sh once.
2. Run uv run copenet.
3. Open Home and finish setup for at least one provider.
4. Create a new session and pick provider, model, profile, and Access.
5. Send the first message to create the session and lock provider/profile/persona/workspace.

The operator may change model within the same provider and may change Access on later runs. Start a new chat for another provider, profile, persona, or workspace.

Configuration

Environment variables:

• COPNET_HOST (default: 127.0.0.1)
• COPNET_PORT (default: 17123)
• COPNET_TOKEN (default: dev-token on loopback only; a private token is required beyond localhost)
• COPNET_ALLOWED_ORIGINS (optional comma-separated browser WebSocket origins, such as https://host.example; include scheme and port when applicable). CopeNet's bind origin and local Vite dev origins are allowed automatically. Connections without an Origin header remain available to CLI clients.
• COPNET_DATA_DIR (default: ~/.copenet/sessions)
• COPNET_EXECUTION_MODE (safe | tools-enabled | unrestricted)
• COPNET_TRACE (1 to enable per-run JSONL traces)

Example:

umask 077
printf 'COPNET_TOKEN="%s"\nCOPNET_PORT=17123\n' \
  "$(python3 -c 'import secrets; print(secrets.token_urlsafe(32))')" > .copenet.env
uv run --env-file .copenet.env copenet

Bring Your Own Knowledge Base

CopeNet can integrate with curated local knowledge sources, including markdown-based creative or research libraries. The public repo does not assume any personal vault or branded workflow setup.

To sketch your own local setup, start with:

• config/knowledge-sources.example.toml

Then create your own ignored local override:

• config/knowledge-sources.local.toml

See docs/KNOWLEDGE-BASES.md for the pattern.

Prompt Presets

Prompt presets are markdown files under:

• src/copenet/prompts/presets/profiles/
• src/copenet/prompts/presets/task-modes/

The loader composes:

• profile for base behavior
• Access overlay for runtime authority (none, ask, or full-access)

Add your own by dropping .md files into those directories.

CLI Entry Points

• Full app (recommended):

uv run copenet

• Direct module entrypoint (normally unnecessary):

python -m copenet.host

Python Usage

from copenet import GatewayClient, GatewayConfig, Orchestrator, CopeNetWsServer

Docs

Getting Started

• Feature Glossary
• Startup
• Testing
• Knowledge Bases

Architecture

• Architecture
• App API — /api/v1 REST + SSE for external apps
• Event Contract — /ws frame protocol
• Session Continuity
• Capability Matrix
• Operator UX Model — three-layer tool truth (transcript / activity / inspector)

Runtime Debugging

• Tracing
• Debugging
• Runbook

Prototypes & Investigations

• Browser Agent Prototype

Troubleshooting

Provider unavailable

• Check the provider setup panel on Home first; it shows whether each provider is missing, signed out, or ready.
• claude-cli: install Claude Code so claude is on PATH, then run claude auth login.
• openai-codex: use Start OpenAI OAuth on Home, or run uv run copenet auth login --provider openai-codex.
• SEC-backed Market data missing: rerun ./scripts/setup.sh --with-sec. A separate CopeTech-Edgar checkout is not required.

Debugging a weird run

• Enable tracing: COPNET_TRACE=1 uv run copenet
• Reproduce the run once
• Open the newest file under ~/.copenet/logs/runs/
• Inspect the event order:
  • harness_planned
  • tool_requested
  • tool_executed or tool_blocked
  • assistant_finalized

See docs/TRACING.md for the trace schema and workflow.

Prompt/profile changes not applying

• Start a new session after changing the profile of a locked session
• Change Access explicitly in the runtime control; it applies to the next run
• Ensure preset markdown files are in the correct preset directories

Port already in use

COPNET_PORT=17124 uv run copenet

Project Status

CopeNet is actively evolving, but it is already a real operator workspace: persistent sessions, local-provider support, workflow surfaces, observability, and mobile-friendly remote access are all in place.

The direction is simple: make local agent systems inspectable, composable, and actually useful for real workflows.