fix: config saving and config loading

.env.example

@@ -0,0 +1,10 @@
+OLLAMA_BASE_URL=http://localhost:11434
+OLLAMA_MODEL=qwen3.5:9b
+OLLAMA_NUM_CTX=64512
+UEX_BASE_URL=https://api.uexcorp.space/2.0
+UEX_SECRET_KEY=
+UEX_BEARER_TOKEN=
+TRADERAI_USER_NAME=
+TRADERAI_MEMORY_PATH=
+UEX_NOTIFICATION_POLL_SECONDS=60
+REQUIRE_WRITE_APPROVAL=true

.gitea/workflows/release.yml

@@ -0,0 +1,74 @@
+name: Build Release EXE
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  build-windows-exe:
+    runs-on: windows-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.12"
+
+      - name: Install build dependencies
+        shell: pwsh
+        run: |
+          python -m pip install --upgrade pip
+          python -m pip install -e ".[dev]"
+
+      - name: Build TraderAI.exe
+        shell: pwsh
+        run: |
+          pyinstaller TraderAI.spec --noconfirm
+          if (-not (Test-Path -LiteralPath "dist\TraderAI.exe")) {
+            throw "dist\TraderAI.exe was not created."
+          }
+
+      - name: Attach EXE to release
+        shell: pwsh
+        env:
+          RELEASE_TOKEN: ${{ secrets.RELEASE_TOKEN }}
+          GITEA_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          $ErrorActionPreference = "Stop"
+          $event = Get-Content -LiteralPath $env:GITHUB_EVENT_PATH -Raw | ConvertFrom-Json
+          $releaseId = $event.release.id
+          if (-not $releaseId) {
+            throw "Release id was not present in the release event payload."
+          }
+
+          $token = $env:RELEASE_TOKEN
+          if ([string]::IsNullOrWhiteSpace($token)) {
+            $token = $env:GITEA_TOKEN
+          }
+          if ([string]::IsNullOrWhiteSpace($token)) {
+            throw "Set a RELEASE_TOKEN secret or enable the built-in GITHUB_TOKEN for Actions."
+          }
+
+          $apiUrl = $env:GITHUB_API_URL
+          if ([string]::IsNullOrWhiteSpace($apiUrl)) {
+            $apiUrl = "$($env:GITHUB_SERVER_URL.TrimEnd('/'))/api/v1"
+          }
+
+          $repoParts = $env:GITHUB_REPOSITORY.Split("/", 2)
+          if ($repoParts.Length -ne 2) {
+            throw "GITHUB_REPOSITORY must look like owner/repo. Value: $env:GITHUB_REPOSITORY"
+          }
+
+          $owner = [uri]::EscapeDataString($repoParts[0])
+          $repo = [uri]::EscapeDataString($repoParts[1])
+          $assetPath = Resolve-Path -LiteralPath "dist\TraderAI.exe"
+          $uploadUrl = "$apiUrl/repos/$owner/$repo/releases/$releaseId/assets?name=TraderAI.exe"
+
+          Invoke-RestMethod `
+            -Method Post `
+            -Uri $uploadUrl `
+            -Headers @{ Authorization = "token $token" } `
+            -Form @{ attachment = Get-Item -LiteralPath $assetPath }

.gitignore

@@ -0,0 +1,60 @@
+# Environment and secrets
+.env
+.env.*
+!.env.example
+
+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+.python-version
+.venv/
+venv/
+env/
+ENV/
+
+# Python packaging and build output
+build/
+dist/
+*.egg-info/
+.eggs/
+pip-wheel-metadata/
+.playwright-mcp/
+
+# Test and coverage output
+.pytest_cache/
+.coverage
+.coverage.*
+htmlcov/
+coverage.xml
+
+# Type checker and linter caches
+.mypy_cache/
+.ruff_cache/
+.pyre/
+.pytype/
+
+# FastAPI/Uvicorn/runtime files
+*.log
+*.pid
+data/
+*.sqlite3
+*.sqlite3-*
+
+# Frontend dependencies and build artifacts
+node_modules/
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+web/dist/
+web/build/
+
+# IDE and OS files
+.idea/
+.vscode/
+*.swp
+*.swo
+.DS_Store
+Thumbs.db
+desktop.ini

INSTRUCTIONS.md

@@ -1,2 +0,0 @@
-Use the UEX API spefications at https://app.swaggerhub.com/apis-docs/dolejska-daniel/UEX-API/v2.1#/Static/get_data_parameters.
-I want a ollama powered chat bot that can search marketplace listings on UEX, respond to messages regarding them, make offers etc. I will use a local model for this. 

README.md

@@ -0,0 +1,81 @@
+# TraderAI
+
+Local Ollama-powered chat for UEX marketplace workflows.
+
+## What It Does
+
+- Searches active/current UEX marketplace listings through `GET /marketplace_listings/`.
+- Reads authenticated marketplace negotiations and negotiation messages when `UEX_SECRET_KEY` or `UEX_BEARER_TOKEN` is set.
+- Drafts negotiation messages and marketplace listings as pending actions.
+- Requires browser approval before sending authenticated write requests to UEX.
+- Maintains local SQLite memory with searchable recall for user facts, preferences, and prior chat context.
+- Can create one-time or recurring wake jobs that prompt the assistant later and surface the result in the UI.
+- Loads the configured UEX user profile from `GET /user` so the assistant knows the current account username, display name, timezone, language, and marketplace-relevant profile details.
+- Polls authenticated `GET /user_notifications` for unread UEX notifications and surfaces new pending alerts in the chat notification queue.
+
+## Setup
+
+1. Install Python 3.11+.
+2. Install Ollama and pull a tool-capable model, for example:
+
+   ```powershell
+   ollama pull qwen3.5:9b
+   ```
+
+3. Create `.env` from `.env.example` and set `UEX_SECRET_KEY` and/or `UEX_BEARER_TOKEN` if you want authenticated actions.
+4. Install and run:
+
+   ```powershell
+   pip install -e .
+   uvicorn traderai.server:app --reload
+   ```
+
+5. Open `http://127.0.0.1:8000`.
+
+## Notes
+
+Ollama runs locally at `http://localhost:11434` by default. This app talks to Ollama's native chat API with tool schemas, then executes approved UEX calls in the FastAPI backend. `OLLAMA_NUM_CTX` controls the per-request Ollama context window; `64512` is the default because Ollama recommends at least 64k tokens for agent-style workflows when hardware allows it.
+
+## Releases And Updates
+
+Change the app version before cutting a release:
+
+```powershell
+.\scripts\set_version.ps1 0.2.0
+```
+
+Create a Gitea release with a matching tag such as `v0.2.0`. The release workflow builds `dist\TraderAI.exe` and attaches only that exe to the release.
+
+The desktop app can check `https://git.hudsonriggs.systems/LambdaBankingConglomerate/TraderAI/releases` from Settings > Updates. When a newer release has a `TraderAI.exe` attachment, the packaged app downloads it to the user app data update folder, exits, replaces the current exe, and relaunches.
+
+UEX marketplace posting and negotiation messages are guarded because they are account-affecting write actions. The model can draft them, but the UI approval button performs the final API call.
+
+The assistant gets runtime context on every chat: current date/time, authenticated UEX identity when credentials are configured, remembered user profile, last interaction time, relevant memories, and recent conversation excerpts. It is instructed to prefer open/current marketplace data, avoid historical sale information unless explicitly requested, and treat UEX prices as in-game aUEC/UEC credits rather than real-world dollars. Memory is stored locally at `TRADERAI_MEMORY_PATH`.
+
+Wake jobs can be created from chat, for example:
+
+```text
+At 9 PM remind yourself to check my open Polaris Bit negotiations.
+```
+
+or:
+
+```text
+Every day at 9 AM, wake up and check whether I have marketplace followups.
+```
+
+The scheduler accepts one-time ISO datetimes and five-field cron expressions through the `schedule_wake_job` tool. When a wake job fires, the assistant receives context like the current time and last interaction time, then places its response into the UI notification queue.
+
+UEX notifications are checked every `UEX_NOTIFICATION_POLL_SECONDS` seconds by default. New unread notifications are deduplicated locally, then displayed in the chat through the same notification queue used by wake jobs.
+
+## Sources Used
+
+- UEX SwaggerHub OpenAPI v2.1: https://app.swaggerhub.com/apis-docs/dolejska-daniel/UEX-API/v2.1
+- UEX marketplace listings docs: https://uexcorp.space/api/documentation/id/get_marketplace_listings/?is_kiosk=1
+- UEX negotiation message docs: https://uexcorp.space/api/documentation/id/post_marketplace_negotiations_messages/?is_kiosk=1
+- Ollama tool calling docs: https://docs.ollama.com/capabilities/tool-calling
+- Ollama API streaming/tool-call reference: https://github.com/ollama/ollama/blob/main/docs/api.md
+- Ollama context length docs: https://docs.ollama.com/context-length
+- SQLite FTS5 docs: https://www.sqlite.org/fts5.html
+- APScheduler AsyncIO scheduler docs: https://apscheduler.readthedocs.io/en/stable/modules/schedulers/asyncio.html
+- Letta/MemGPT memory hierarchy background: https://docs.letta.com/concepts/letta

TraderAI.Debug.spec

@@ -0,0 +1,55 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+from PyInstaller.utils.hooks import collect_all
+
+webview_datas, webview_binaries, webview_hiddenimports = collect_all("webview")
+
+
+a = Analysis(
+    ["traderai\\desktop.py"],
+    pathex=[],
+    binaries=webview_binaries,
+    datas=[("web", "web"), *webview_datas],
+    hiddenimports=[
+        *webview_hiddenimports,
+        "uvicorn.logging",
+        "uvicorn.loops",
+        "uvicorn.loops.auto",
+        "uvicorn.protocols",
+        "uvicorn.protocols.http",
+        "uvicorn.protocols.http.auto",
+        "uvicorn.protocols.websockets",
+        "uvicorn.protocols.websockets.auto",
+        "uvicorn.lifespan",
+        "uvicorn.lifespan.on",
+    ],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name="TraderAI.Debug",
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=True,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    icon="web\\art\\LBC_Logo.ico",
+    codesign_identity=None,
+    entitlements_file=None,
+)

TraderAI.spec

@@ -0,0 +1,55 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+from PyInstaller.utils.hooks import collect_all
+
+webview_datas, webview_binaries, webview_hiddenimports = collect_all("webview")
+
+
+a = Analysis(
+    ["traderai\\desktop.py"],
+    pathex=[],
+    binaries=webview_binaries,
+    datas=[("web", "web"), *webview_datas],
+    hiddenimports=[
+        *webview_hiddenimports,
+        "uvicorn.logging",
+        "uvicorn.loops",
+        "uvicorn.loops.auto",
+        "uvicorn.protocols",
+        "uvicorn.protocols.http",
+        "uvicorn.protocols.http.auto",
+        "uvicorn.protocols.websockets",
+        "uvicorn.protocols.websockets.auto",
+        "uvicorn.lifespan",
+        "uvicorn.lifespan.on",
+    ],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name="TraderAI",
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=False,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    icon="web\\art\\LBC_Logo.ico",
+    codesign_identity=None,
+    entitlements_file=None,
+)

pyproject.toml

@@ -0,0 +1,38 @@
+[project]
+name = "traderai"
+version = "0.0.2"
+description = "Local Ollama-powered assistant for UEX marketplace workflows."
+requires-python = ">=3.11"
+dependencies = [
+  "apscheduler>=3.10.4",
+  "fastapi>=0.115.0",
+  "httpx>=0.27.0",
+  "pywebview>=5.4",
+  "pydantic>=2.8.0",
+  "pydantic-settings>=2.4.0",
+  "python-dotenv>=1.0.1",
+  "tzlocal>=5.2",
+  "uvicorn[standard]>=0.30.0",
+]
+
+[project.optional-dependencies]
+dev = [
+  "pyinstaller>=6.11.0",
+  "pytest>=8.3.0",
+  "pytest-asyncio>=0.23.8",
+  "respx>=0.21.1",
+]
+
+[project.scripts]
+traderai-desktop = "traderai.desktop:main"
+
+[tool.pytest.ini_options]
+testpaths = ["tests"]
+pythonpath = ["."]
+
+[tool.setuptools.packages.find]
+include = ["traderai*"]
+
+
+
+

scripts/build_windows_exe.ps1

@@ -0,0 +1,16 @@
+$ErrorActionPreference = "Stop"
+
+$Root = Split-Path -Parent $PSScriptRoot
+Set-Location $Root
+
+$Python = Join-Path $Root ".venv\Scripts\python.exe"
+if (-not (Test-Path $Python)) {
+  $Python = "python"
+}
+
+& $Python -m ensurepip --upgrade
+& $Python -m pip install -e ".[dev]"
+& $Python -m PyInstaller --clean "TraderAI.spec"
+
+Write-Host ""
+Write-Host "Built dist\TraderAI.exe"

scripts/set_version.ps1

@@ -0,0 +1,29 @@
+param(
+  [Parameter(Mandatory = $true)]
+  [ValidatePattern('^v?\d+\.\d+\.\d+([-.+][0-9A-Za-z.-]+)?$')]
+  [string]$Version
+)
+
+$ErrorActionPreference = "Stop"
+$repoRoot = Resolve-Path -LiteralPath (Join-Path $PSScriptRoot "..")
+$cleanVersion = $Version.TrimStart("v")
+
+$pyprojectPath = Join-Path $repoRoot "pyproject.toml"
+$versionPath = Join-Path $repoRoot "traderai\version.py"
+$lockPath = Join-Path $repoRoot "uv.lock"
+
+$pyproject = Get-Content -LiteralPath $pyprojectPath -Raw
+$pyproject = $pyproject -replace '(?m)^version = "[^"]+"', "version = `"$cleanVersion`""
+Set-Content -LiteralPath $pyprojectPath -Value $pyproject -Encoding UTF8
+
+$versionModule = Get-Content -LiteralPath $versionPath -Raw
+$versionModule = $versionModule -replace '__version__ = "[^"]+"', "__version__ = `"$cleanVersion`""
+Set-Content -LiteralPath $versionPath -Value $versionModule -Encoding UTF8
+
+if (Test-Path -LiteralPath $lockPath) {
+  $lock = Get-Content -LiteralPath $lockPath -Raw
+  $lock = $lock -replace '(?s)(name = "traderai"\s+version = ")[^"]+(")', "`${1}$cleanVersion`${2}"
+  Set-Content -LiteralPath $lockPath -Value $lock -Encoding UTF8
+}
+
+Write-Host "TraderAI version set to $cleanVersion"

tests/test_agent.py

@@ -0,0 +1,92 @@
+import pytest
+
+from traderai.agent import OllamaAgent, SYSTEM_PROMPT
+from traderai.memory import MemoryStore
+
+
+class EmptyTools:
+    schemas = []
+
+    @property
+    def pending_actions(self):
+        return {}
+
+
+@pytest.mark.asyncio
+async def test_chat_events_warns_when_ollama_offline():
+    agent = OllamaAgent("http://127.0.0.1:1", "missing-model", EmptyTools())
+    events = []
+    async for event in agent.chat_events("hello"):
+        events.append(event)
+
+    assert events[0]["type"] == "warning"
+    assert "Ollama is offline" in events[0]["message"]
+    assert events[-1]["type"] == "done"
+
+
+def test_runtime_context_uses_previous_interaction_not_current_message(tmp_path):
+    memory = MemoryStore(str(tmp_path / "memory.sqlite3"))
+    memory.add_conversation("assistant", "older answer")
+    previous = memory.last_interaction()
+    assert previous is not None
+
+    memory.add_conversation("user", "current question")
+    current = memory.last_interaction()
+
+    agent = OllamaAgent("http://127.0.0.1:1", "missing-model", EmptyTools(), memory=memory)
+    context = agent._runtime_context("current question", previous_interaction=previous)
+
+    assert f"Previous interaction before this message: {previous['created_at']}" in context
+    assert f"Previous interaction before this message: {current['created_at']}" not in context
+    assert "Current local date/time:" in context
+
+
+def test_runtime_context_includes_uex_user_identity(tmp_path):
+    memory = MemoryStore(str(tmp_path / "memory.sqlite3"))
+    memory.set_profile(
+        "uex_user",
+        {
+            "username": "pilot_hudson",
+            "name": "Hudson",
+            "email": "hudson@example.test",
+            "timezone": "America/New_York",
+            "specializations": "trading,hauling",
+        },
+    )
+
+    agent = OllamaAgent("http://127.0.0.1:1", "missing-model", EmptyTools(), memory=memory)
+    context = agent._runtime_context("")
+
+    assert "You are speaking with UEX user pilot_hudson (Hudson)." in context
+    assert "timezone: America/New_York" in context
+    assert "specializations: trading,hauling" in context
+    assert "hudson@example.test" not in context
+
+
+def test_stream_metrics_include_reading_and_writing_rates():
+    metrics = OllamaAgent._stream_metrics(
+        {
+            "prompt_eval_count": 20,
+            "prompt_eval_duration": 2_000_000_000,
+            "eval_count": 30,
+            "eval_duration": 3_000_000_000,
+        }
+    )
+
+    assert metrics["reading_tokens"] == 20
+    assert metrics["reading_tokens_per_second"] == 10
+    assert metrics["writing_tokens"] == 30
+    assert metrics["writing_tokens_per_second"] == 10
+
+
+def test_system_prompt_prefers_current_marketplace_data():
+    assert "open/current" in SYSTEM_PROMPT
+    assert "Do not use historical sale data" in SYSTEM_PROMPT
+    assert "aUEC/UEC credits" in SYSTEM_PROMPT
+    assert "never real-world dollars" in SYSTEM_PROMPT
+
+
+def test_ollama_options_include_num_ctx():
+    agent = OllamaAgent("http://127.0.0.1:1", "missing-model", EmptyTools(), num_ctx=64000)
+
+    assert agent._ollama_options() == {"num_ctx": 64000}

tests/test_memory.py

@@ -0,0 +1,27 @@
+from traderai.memory import MemoryStore
+
+
+def test_memory_store_recalls_saved_fact(tmp_path):
+    store = MemoryStore(str(tmp_path / "memory.sqlite3"))
+    store.remember("preference", "The user prefers Polaris Bits searches to include barter listings.", importance=5)
+
+    results = store.recall("Polaris barter")
+
+    assert results
+    assert "Polaris Bits" in results[0]["content"]
+
+
+def test_memory_store_clear_selected_sections(tmp_path):
+    store = MemoryStore(str(tmp_path / "memory.sqlite3"))
+    store.remember("note", "Forgettable note")
+    store.add_conversation("user", "hello")
+    store.set_profile("configured_name", "Hudson")
+
+    deleted = store.clear(include_profile=False)
+    snapshot = store.inspect()
+
+    assert deleted["memories"] == 1
+    assert deleted["conversations"] == 1
+    assert snapshot["memories"] == []
+    assert snapshot["conversations"] == []
+    assert snapshot["profile"][0]["key"] == "configured_name"

tests/test_scheduler.py

@@ -0,0 +1,47 @@
+import pytest
+
+from traderai.memory import MemoryStore
+from traderai.scheduler import WakeScheduler
+
+
+class FakeUEXNotifications:
+    def __init__(self):
+        self.calls = 0
+
+    async def get_user_notifications(self):
+        self.calls += 1
+        return {
+            "status": "ok",
+            "notifications": [
+                {
+                    "id": 10,
+                    "message": "A buyer replied to your listing.",
+                    "redir": "/marketplace/negotiations/abc",
+                    "code": "negotiation_reply",
+                    "date_added": 123,
+                    "date_read": 0,
+                },
+                {
+                    "id": 11,
+                    "message": "Already read.",
+                    "date_added": 122,
+                    "date_read": 123,
+                },
+            ],
+        }
+
+
+@pytest.mark.asyncio
+async def test_poll_uex_notifications_adds_unread_once(tmp_path):
+    memory = MemoryStore(str(tmp_path / "memory.sqlite3"))
+    scheduler = WakeScheduler(memory)
+    scheduler.bind_uex_notifications(FakeUEXNotifications())
+
+    first = await scheduler.poll_uex_notifications()
+    second = await scheduler.poll_uex_notifications()
+    outbox = memory.inspect()["outbox"]
+
+    assert len(first) == 1
+    assert second == []
+    assert len(outbox) == 1
+    assert "A buyer replied to your listing." in outbox[0]["content"]

tests/test_tools.py

@@ -0,0 +1,281 @@
+import pytest
+import respx
+from httpx import Response
+
+from traderai.tools import ToolRegistry
+from traderai.uex_client import UEXClient
+
+
+class FakeUEX:
+    async def get(self, path, params=None, authenticated=False):
+        if path == "commodities_prices_history":
+            return {
+                "status": "ok",
+                "data": [
+                    {
+                        "id": 1,
+                        "id_terminal": 7,
+                        "id_commodity": 3,
+                        "commodity_name": "Gold",
+                        "terminal_name": "Port Tressler",
+                        "price_buy": 4000,
+                        "price_sell": 5000,
+                        "scu_buy": 100,
+                        "scu_sell": 20,
+                        "date_added": 100,
+                    },
+                    {
+                        "id": 2,
+                        "id_terminal": 7,
+                        "id_commodity": 3,
+                        "commodity_name": "Gold",
+                        "terminal_name": "Port Tressler",
+                        "price_buy": 4200,
+                        "price_sell": 4800,
+                        "scu_buy": 80,
+                        "scu_sell": 30,
+                        "date_added": 200,
+                    },
+                ],
+            }
+        if path == "marketplace_prices_history":
+            return {
+                "status": "ok",
+                "data": [
+                    {"id": 1, "item_name": "Widget", "operation": "sell", "price": 1000, "currency": "UEC", "date_added": 100},
+                    {"id": 2, "item_name": "Widget", "operation": "sell", "price": 1250, "currency": "UEC", "date_added": 200},
+                ],
+            }
+        if path == "currencies_index_history":
+            return {
+                "status": "ok",
+                "data": [
+                    {"id": 1, "currency": "UEC", "index_value": 100.0, "basket_value": 5000.0, "date_added": 100},
+                    {"id": 2, "currency": "UEC", "index_value": 110.0, "basket_value": 5500.0, "date_added": 200},
+                ],
+            }
+        if path == "commodities_prices":
+            return {
+                "status": "ok",
+                "data": [
+                    {
+                        "id": 10,
+                        "commodity_name": "Gold",
+                        "terminal_name": "Port Tressler",
+                        "price_buy": 4120,
+                        "price_sell": 5020,
+                        "scu_buy": 1200,
+                        "verbose_note": "x" * 300,
+                    },
+                    {
+                        "id": 11,
+                        "commodity_name": "Beryl",
+                        "terminal_name": "Area18",
+                        "price_buy": 2500,
+                        "price_sell": 3100,
+                    },
+                ],
+            }
+        assert path == "marketplace_listings"
+        return {
+            "data": [
+                {
+                    "id": 1,
+                    "slug": "gold-haul",
+                    "title": "Gold haul escort",
+                    "description": "Escort service",
+                    "operation": "sell",
+                    "type": "service",
+                    "price": 5000,
+                    "currency": "UEC",
+                    "unit": "run",
+                    "location": "Port Tressler",
+                    "user_username": "pilot_a",
+                    "date_expiration": 123,
+                },
+                {
+                    "id": 2,
+                    "slug": "armor-set",
+                    "title": "Armor set",
+                    "description": "Clean set",
+                    "operation": "sell",
+                    "type": "item",
+                    "price": 15000,
+                    "currency": "UEC",
+                    "unit": "set",
+                    "location": "Area18",
+                    "user_username": "pilot_b",
+                    "date_expiration": 456,
+                },
+            ]
+        }
+
+    async def delete(self, path, params=None, authenticated=True):
+        return {"status": "ok", "deleted": {"path": path, "params": params, "authenticated": authenticated}}
+
+
+@pytest.mark.asyncio
+async def test_search_marketplace_listings_filters_locally():
+    registry = ToolRegistry(FakeUEX())
+    result = await registry.search_marketplace_listings(query="gold", type="service", max_price=6000)
+    assert result["count"] == 1
+    assert result["listings"][0]["slug"] == "gold-haul"
+
+
+@pytest.mark.asyncio
+async def test_draft_message_creates_pending_action():
+    registry = ToolRegistry(FakeUEX())
+    result = await registry.draft_negotiation_message(hash="abc", message="Would you take 4500 UEC?")
+    pending = result["pending_action"]
+    assert pending["endpoint"] == "marketplace_negotiations_messages"
+    assert pending["payload"]["message"] == "Would you take 4500 UEC?"
+    assert pending["id"] in registry.pending_actions
+
+
+@pytest.mark.asyncio
+async def test_decline_pending_action_removes_without_sending():
+    registry = ToolRegistry(FakeUEX())
+    result = await registry.draft_negotiation_message(hash="abc", message="Would you take 4500 UEC?")
+    action_id = result["pending_action"]["id"]
+
+    declined = await registry.decline(action_id)
+
+    assert declined["declined"] is True
+    assert declined["pending_action"]["id"] == action_id
+    assert action_id not in registry.pending_actions
+
+
+def test_uex_client_uses_bearer_and_secret_headers():
+    client = UEXClient("https://api.uexcorp.space/2.0", secret_key="secret", bearer_token="bearer")
+
+    headers = client._headers(authenticated=True)
+
+    assert headers["secret-key"] == "secret"
+    assert headers["Authorization"] == "Bearer bearer"
+
+
+@pytest.mark.asyncio
+async def test_uex_get_projects_and_limits_results():
+    registry = ToolRegistry(FakeUEX())
+
+    result = await registry.execute(
+        "get_uex_commodities_prices",
+        {
+            "commodity_name": "Gold",
+            "ignored": "drop",
+            "fields": ["id", "commodity_name", "price_buy"],
+            "limit": 1,
+        },
+    )
+
+    assert result["resource"] == "commodities_prices"
+    assert result["params"] == {"commodity_name": "Gold"}
+    assert result["returned"] == 1
+    assert result["truncated"] is True
+    assert result["items"] == [{"id": 10, "commodity_name": "Gold", "price_buy": 4120}]
+
+
+@pytest.mark.asyncio
+async def test_uex_api_catalog_exposes_resources_without_live_call():
+    registry = ToolRegistry(FakeUEX())
+
+    result = await registry.uex_api_catalog(group="vehicles")
+
+    resources = [item["resource"] for item in result["get"]["vehicles"]]
+    assert "vehicles" in resources
+    assert "vehicles_prices" in resources
+    assert "wallet_add" in result["post"]
+
+
+@pytest.mark.asyncio
+async def test_draft_delete_approves_with_delete_method():
+    registry = ToolRegistry(FakeUEX())
+    result = await registry.execute("delete_uex_marketplace_listings", {"id": 123, "label": "Remove listing"})
+    action_id = result["pending_action"]["id"]
+
+    approved = await registry.approve(action_id)
+
+    assert result["pending_action"]["method"] == "DELETE"
+    assert approved["deleted"] == {
+        "path": "marketplace_listings",
+        "params": {"id": 123},
+        "authenticated": True,
+    }
+
+
+def test_schemas_expose_specific_uex_tools_instead_of_generic_api_tool():
+    registry = ToolRegistry(FakeUEX())
+
+    names = {schema["function"]["name"] for schema in registry.schemas}
+
+    assert "get_uex_commodities_prices" in names
+    assert "get_uex_vehicles" in names
+    assert "draft_uex_marketplace_advertise" in names
+    assert "delete_uex_marketplace_listings" in names
+    assert "uex_get" not in names
+    assert "uex_draft_post" not in names
+
+
+@pytest.mark.asyncio
+async def test_search_uex_api_index_finds_history_tools():
+    registry = ToolRegistry(FakeUEX())
+
+    result = await registry.execute("search_uex_api_index", {"query": "history", "history_only": True})
+
+    tools = {item["tool"] for item in result["get"]}
+    assert "get_uex_commodities_prices_history" in tools
+    assert "get_uex_marketplace_prices_history" in tools
+    assert "get_uex_currencies_index_history" in tools
+
+
+@pytest.mark.asyncio
+async def test_summarize_commodity_price_history_returns_trend_metrics():
+    registry = ToolRegistry(FakeUEX())
+
+    result = await registry.execute(
+        "summarize_uex_commodity_price_history",
+        {"id_terminal": 7, "id_commodity": 3},
+    )
+
+    assert result["resource"] == "commodities_prices_history"
+    assert result["count"] == 2
+    assert result["labels"] == {"commodity_name": "Gold", "terminal_name": "Port Tressler"}
+    assert result["metrics"]["price_buy"]["change"] == 200
+    assert result["metrics"]["price_sell"]["pct_change"] == -4.0
+
+
+@pytest.mark.asyncio
+async def test_summarize_marketplace_and_currency_history():
+    registry = ToolRegistry(FakeUEX())
+
+    market = await registry.execute("summarize_uex_marketplace_price_history", {"item_name": "Widget"})
+    currency = await registry.execute("summarize_uex_currency_index_history", {"currency": "UEC"})
+
+    assert market["metrics"]["price"]["pct_change"] == 25.0
+    assert currency["metrics"]["index_value"]["change"] == 10.0
+
+
+@pytest.mark.asyncio
+@respx.mock
+async def test_uex_client_get_user_normalizes_user_payload():
+    respx.get("https://api.uexcorp.space/2.0/user/").mock(
+        return_value=Response(200, json={"status": "ok", "data": [{"username": "pilot_hudson"}]})
+    )
+    client = UEXClient("https://api.uexcorp.space/2.0", bearer_token="bearer")
+
+    result = await client.get_user(authenticated=True)
+
+    assert result == {"status": "ok", "user": {"username": "pilot_hudson"}}
+
+
+@pytest.mark.asyncio
+@respx.mock
+async def test_uex_client_get_user_notifications_normalizes_payload():
+    respx.get("https://api.uexcorp.space/2.0/user_notifications/").mock(
+        return_value=Response(200, json={"status": "ok", "data": {"id": 7, "message": "Reply waiting", "date_read": 0}})
+    )
+    client = UEXClient("https://api.uexcorp.space/2.0", bearer_token="bearer")
+
+    result = await client.get_user_notifications()
+
+    assert result == {"status": "ok", "notifications": [{"id": 7, "message": "Reply waiting", "date_read": 0}]}

traderai/__init__.py

@@ -0,0 +1 @@
+"""TraderAI application package."""

traderai/agent.py

@@ -0,0 +1,412 @@
+from __future__ import annotations
+
+import json
+from collections.abc import AsyncIterator
+from typing import Any
+
+import httpx
+from tzlocal import get_localzone
+
+from traderai.memory import MemoryStore, iso_now, iso_now_in_zone, time_since
+from traderai.tools import ToolRegistry
+
+
+SYSTEM_PROMPT = """You are TraderAI, a local assistant for UEX marketplace work.
+Use tools when the user asks about UEX data, open/current listings, active negotiations, unread notifications, messages, offers, or posting ads.
+UEX credentials are configured server-side when available. Never ask the user to provide UEX_SECRET_KEY or UEX_BEARER_TOKEN in chat; call the authenticated UEX tool and only mention credential configuration if the tool returns an authentication error.
+Use the specific UEX tool for the needed endpoint, such as get_uex_commodities_prices or get_uex_vehicles. Use fields, limit, and summary mode so tool results stay compact.
+When the user asks for history, trends, changes over time, or past prices, prefer the summarize_uex_*_history tools when available; use search_uex_api_index(history_only=true) if you need to discover history endpoints.
+Prefer open and current UEX marketplace information. Do not use historical sale data, completed sale records, or sale/average-history information unless the user explicitly asks for historical sales.
+Treat UEX marketplace prices as in-game aUEC/UEC credits, never real-world dollars, unless the user explicitly says otherwise.
+For marketplace writes, draft the exact pending action and tell the user what will be sent; never claim it was sent until approval succeeds.
+Keep prices, listing ids, slugs, users, and UEX status codes precise. If data is missing, say what you need next."""
+
+
+class OllamaAgent:
+    def __init__(
+        self,
+        base_url: str,
+        model: str,
+        tools: ToolRegistry,
+        memory: MemoryStore | None = None,
+        user_name: str | None = None,
+        num_ctx: int | None = None,
+    ) -> None:
+        self.base_url = base_url.rstrip("/")
+        self.model = model
+        self.tools = tools
+        self.memory = memory
+        self.user_name = user_name
+        self.num_ctx = num_ctx
+        self.messages: list[dict[str, Any]] = [{"role": "system", "content": SYSTEM_PROMPT}]
+
+    async def health(self) -> dict[str, Any]:
+        try:
+            async with httpx.AsyncClient(timeout=3) as client:
+                response = await client.get(f"{self.base_url}/api/tags")
+            response.raise_for_status()
+            body = response.json()
+        except (httpx.HTTPError, ValueError) as exc:
+            return {
+                "online": False,
+                "model": self.model,
+                "base_url": self.base_url,
+                "message": f"Ollama is offline or unreachable at {self.base_url}. Start Ollama and make sure the model is pulled.",
+                "detail": str(exc),
+            }
+
+        models = [model.get("name") or model.get("model") for model in body.get("models", [])]
+        return {
+            "online": True,
+            "model": self.model,
+            "base_url": self.base_url,
+            "model_available": self.model in models,
+            "models": models,
+            "message": "Ollama is online.",
+        }
+
+    async def ensure_available(self) -> None:
+        health = await self.health()
+        if not health["online"]:
+            raise OllamaUnavailable(health["message"])
+
+    async def chat(self, content: str) -> dict[str, Any]:
+        await self.ensure_available()
+        previous_interaction = self.memory.last_interaction() if self.memory else None
+        if self.memory:
+            self.memory.add_conversation("user", content)
+        self.messages.append({"role": "user", "content": content})
+        for _ in range(5):
+            response = await self._ollama_chat(content, previous_interaction=previous_interaction)
+            message = response.get("message") or {}
+            tool_calls = message.get("tool_calls") or []
+            if not tool_calls:
+                self.messages.append({"role": "assistant", "content": message.get("content", "")})
+                if self.memory:
+                    self.memory.add_conversation("assistant", message.get("content", ""))
+                return {"message": message.get("content", ""), "pending_actions": self._pending_payloads()}
+
+            self.messages.append(message)
+            for call in tool_calls:
+                name, arguments = self._extract_call(call)
+                result = await self.tools.execute(name, arguments)
+                self.messages.append({"role": "tool", "tool_name": name, "content": json.dumps(result)})
+
+        fallback = "I hit the tool-call limit while working on that. Try narrowing the request or approve any pending action first."
+        self.messages.append({"role": "assistant", "content": fallback})
+        if self.memory:
+            self.memory.add_conversation("assistant", fallback)
+        return {"message": fallback, "pending_actions": self._pending_payloads()}
+
+    async def chat_events(self, content: str) -> AsyncIterator[dict[str, Any]]:
+        health = await self.health()
+        if not health["online"]:
+            yield {"type": "warning", "message": health["message"]}
+            yield {"type": "done", "pending_actions": self._pending_payloads()}
+            return
+
+        previous_interaction = self.memory.last_interaction() if self.memory else None
+        if self.memory:
+            self.memory.add_conversation("user", content)
+        self.messages.append({"role": "user", "content": content})
+        yield {"type": "status", "message": "Thinking"}
+
+        for _ in range(5):
+            assistant_message: dict[str, Any] = {"role": "assistant", "content": ""}
+            tool_calls: list[dict[str, Any]] = []
+
+            async for event in self._ollama_chat_stream(content, previous_interaction=previous_interaction):
+                message = event.get("message") or {}
+                chunk = message.get("content") or ""
+                if chunk:
+                    assistant_message["content"] += chunk
+                    yield {"type": "token", "content": chunk}
+                if message.get("tool_calls"):
+                    tool_calls.extend(message["tool_calls"])
+                if event.get("done"):
+                    metrics = self._stream_metrics(event)
+                    if metrics:
+                        yield {"type": "metrics", **metrics}
+
+            if not tool_calls:
+                self.messages.append(assistant_message)
+                if self.memory:
+                    self.memory.add_conversation("assistant", assistant_message.get("content", ""))
+                yield {"type": "done", "pending_actions": self._pending_payloads()}
+                return
+
+            assistant_message["tool_calls"] = tool_calls
+            self.messages.append(assistant_message)
+            for call in tool_calls:
+                name, arguments = self._extract_call(call)
+                yield {"type": "status", "message": self._tool_status(name)}
+                result = await self.tools.execute(name, arguments)
+                self.messages.append({"role": "tool", "tool_name": name, "content": json.dumps(result)})
+
+            yield {"type": "status", "message": "Writing response"}
+
+        fallback = "I hit the tool-call limit while working on that. Try narrowing the request or approve any pending action first."
+        self.messages.append({"role": "assistant", "content": fallback})
+        if self.memory:
+            self.memory.add_conversation("assistant", fallback)
+        yield {"type": "token", "content": fallback}
+        yield {"type": "done", "pending_actions": self._pending_payloads()}
+
+    async def generate_wake_response(self, wake_message: str) -> str:
+        await self.ensure_available()
+        self.messages.append({"role": "user", "content": wake_message})
+        response = await self._ollama_chat(wake_message)
+        message = response.get("message") or {}
+        content = message.get("content", "")
+        self.messages.append({"role": "assistant", "content": content})
+        if self.memory:
+            self.memory.add_conversation("system", wake_message)
+            self.memory.add_conversation("assistant", content)
+        return content or wake_message
+
+    async def _ollama_chat(self, query: str = "", previous_interaction: dict[str, Any] | None = None) -> dict[str, Any]:
+        async with httpx.AsyncClient(timeout=120) as client:
+            response = await client.post(
+                f"{self.base_url}/api/chat",
+                json={
+                    "model": self.model,
+                    "messages": self._messages_with_context(query, previous_interaction=previous_interaction),
+                    "tools": self.tools.schemas,
+                    "options": self._ollama_options(),
+                    "stream": False,
+                },
+            )
+        response.raise_for_status()
+        return response.json()
+
+    async def _ollama_chat_stream(
+        self,
+        query: str = "",
+        previous_interaction: dict[str, Any] | None = None,
+    ) -> AsyncIterator[dict[str, Any]]:
+        async with httpx.AsyncClient(timeout=120) as client:
+            async with client.stream(
+                "POST",
+                f"{self.base_url}/api/chat",
+                json={
+                    "model": self.model,
+                    "messages": self._messages_with_context(query, previous_interaction=previous_interaction),
+                    "tools": self.tools.schemas,
+                    "options": self._ollama_options(),
+                    "stream": True,
+                },
+            ) as response:
+                response.raise_for_status()
+                async for line in response.aiter_lines():
+                    if line:
+                        yield json.loads(line)
+
+    def _messages_with_context(
+        self,
+        query: str,
+        previous_interaction: dict[str, Any] | None = None,
+    ) -> list[dict[str, Any]]:
+        context = self._runtime_context(query, previous_interaction=previous_interaction)
+        if not context:
+            return self.messages
+        return [self.messages[0], {"role": "system", "content": context}, *self.messages[1:]]
+
+    def _runtime_context(self, query: str, previous_interaction: dict[str, Any] | None = None) -> str:
+        local_zone = get_localzone()
+        parts = [
+            f"Current local date/time: {iso_now()} UTC; {iso_now_in_zone(local_zone)} {local_zone}.",
+        ]
+        uex = getattr(self.tools, "uex", None)
+        if uex:
+            auth_methods = []
+            if uex.secret_key:
+                auth_methods.append("secret key")
+            if uex.bearer_token:
+                auth_methods.append("bearer token")
+            if auth_methods:
+                parts.append(
+                    "UEX API authentication is configured server-side with "
+                    + " and ".join(auth_methods)
+                    + "; use authenticated UEX tools directly and do not ask for tokens."
+                )
+            else:
+                parts.append("UEX API authentication is not configured server-side.")
+        if self.user_name:
+            parts.append(f"Known user name/handle: {self.user_name}.")
+
+        if self.memory is None:
+            return "\n".join(parts)
+
+        profile = self.memory.get_profile()
+        if profile:
+            identity = self._profile_identity(profile)
+            if identity:
+                parts.append(identity)
+            parts.append(f"Known user profile JSON: {json.dumps(self._profile_for_prompt(profile), ensure_ascii=True)}.")
+
+        last = previous_interaction if previous_interaction is not None else self.memory.last_interaction()
+        if last:
+            parts.append(
+                f"Previous interaction before this message: {last['created_at']} "
+                f"({time_since(last['created_at'])}, role {last['role']})."
+            )
+        else:
+            parts.append("Previous interaction before this message: none recorded.")
+
+        memories = self.memory.recall(query, limit=6)
+        if memories:
+            memory_text = "\n".join(
+                f"- [{item['kind']}, importance {item['importance']}] {item['content']}"
+                for item in memories
+            )
+            parts.append(f"Relevant long-term memories:\n{memory_text}")
+
+        recent = self.memory.recent_conversation(limit=6)
+        if recent:
+            recent_text = "\n".join(
+                f"- {item['created_at']} {item['role']}: {item['content'][:500]}"
+                for item in recent
+            )
+            parts.append(f"Recent conversation excerpts:\n{recent_text}")
+
+        return "\n".join(parts)
+
+    def _pending_payloads(self) -> list[dict[str, Any]]:
+        return [
+            {
+                "id": action.id,
+                "label": action.label,
+                "method": action.method,
+                "endpoint": action.endpoint,
+                "payload": action.payload,
+            }
+            for action in self.tools.pending_actions.values()
+        ]
+
+    def _ollama_options(self) -> dict[str, Any]:
+        if not self.num_ctx:
+            return {}
+        return {"num_ctx": self.num_ctx}
+
+    @staticmethod
+    def _tool_status(name: str) -> str:
+        if name.startswith("get_uex_"):
+            return f"Fetching UEX {name.removeprefix('get_uex_')}"
+        if name.startswith("draft_uex_"):
+            return f"Drafting UEX {name.removeprefix('draft_uex_')} for approval"
+        if name.startswith("delete_uex_"):
+            return f"Drafting UEX {name.removeprefix('delete_uex_')} delete for approval"
+        labels = {
+            "search_uex_api_index": "Searching UEX API index",
+            "summarize_uex_commodity_price_history": "Summarizing commodity price history",
+            "summarize_uex_marketplace_price_history": "Summarizing marketplace price history",
+            "summarize_uex_currency_index_history": "Summarizing currency index history",
+            "uex_api_catalog": "Checking UEX API catalog",
+            "uex_get": "Fetching UEX data",
+            "uex_draft_post": "Drafting UEX write for approval",
+            "uex_draft_delete": "Drafting UEX delete for approval",
+            "search_marketplace_listings": "Searching UEX listings",
+            "get_marketplace_listing": "Fetching listing details",
+            "list_marketplace_negotiations": "Checking negotiations",
+            "get_negotiation_messages": "Reading negotiation messages",
+            "draft_negotiation_message": "Drafting message for approval",
+            "draft_marketplace_listing": "Drafting listing for approval",
+            "check_uex_notifications": "Checking UEX notifications",
+        }
+        return labels.get(name, f"Running {name}")
+
+    @staticmethod
+    def _stream_metrics(event: dict[str, Any]) -> dict[str, Any]:
+        prompt_tokens = int(event.get("prompt_eval_count") or 0)
+        prompt_duration = int(event.get("prompt_eval_duration") or 0)
+        output_tokens = int(event.get("eval_count") or 0)
+        output_duration = int(event.get("eval_duration") or 0)
+
+        def rate(tokens: int, duration_ns: int) -> float | None:
+            if not tokens or not duration_ns:
+                return None
+            return tokens / (duration_ns / 1_000_000_000)
+
+        return {
+            "reading_tokens": prompt_tokens,
+            "reading_tokens_per_second": rate(prompt_tokens, prompt_duration),
+            "writing_tokens": output_tokens,
+            "writing_tokens_per_second": rate(output_tokens, output_duration),
+        }
+
+    @staticmethod
+    def _profile_identity(profile: dict[str, Any]) -> str:
+        user = profile.get("uex_user")
+        if not isinstance(user, dict):
+            configured = profile.get("configured_name")
+            return f"You are speaking with {configured}." if configured else ""
+
+        username = user.get("username") or user.get("user_username")
+        name = user.get("name")
+        fields = []
+        if username and name and username != name:
+            fields.append(f"You are speaking with UEX user {username} ({name}).")
+        elif username or name:
+            fields.append(f"You are speaking with UEX user {username or name}.")
+
+        details = []
+        for key, label in [
+            ("timezone", "timezone"),
+            ("language", "preferred language"),
+            ("specializations", "specializations"),
+            ("languages", "languages"),
+            ("archetypes", "archetypes"),
+        ]:
+            value = user.get(key)
+            if value:
+                details.append(f"{label}: {value}")
+        if details:
+            fields.append("UEX profile details: " + "; ".join(details) + ".")
+        return " ".join(fields)
+
+    @staticmethod
+    def _profile_for_prompt(profile: dict[str, Any]) -> dict[str, Any]:
+        user = profile.get("uex_user")
+        if not isinstance(user, dict):
+            return profile
+
+        useful_user_fields = [
+            "id",
+            "name",
+            "username",
+            "avatar",
+            "bio",
+            "website_url",
+            "timezone",
+            "language",
+            "day_availability",
+            "time_availability",
+            "specializations",
+            "languages",
+            "archetypes",
+            "is_datarunner",
+            "is_staff",
+            "is_away_game",
+            "date_rsi_verified",
+            "date_twitch_verified",
+        ]
+        prompt_profile = dict(profile)
+        prompt_profile["uex_user"] = {
+            key: user[key]
+            for key in useful_user_fields
+            if key in user and user[key] not in (None, "")
+        }
+        return prompt_profile
+
+    @staticmethod
+    def _extract_call(call: dict[str, Any]) -> tuple[str, dict[str, Any]]:
+        function = call.get("function") or {}
+        name = function.get("name") or call.get("name")
+        arguments = function.get("arguments") or call.get("arguments") or {}
+        if isinstance(arguments, str):
+            arguments = json.loads(arguments or "{}")
+        return name, arguments
+
+
+class OllamaUnavailable(RuntimeError):
+    pass

traderai/config.py

@@ -0,0 +1,154 @@
+from __future__ import annotations
+
+from functools import lru_cache
+import os
+from pathlib import Path
+import sys
+from typing import Any
+
+from pydantic import Field, field_validator
+from pydantic_settings import BaseSettings, SettingsConfigDict
+
+
+CONFIG_FIELDS: dict[str, dict[str, Any]] = {
+    "ollama_base_url": {"env": "OLLAMA_BASE_URL", "type": "string", "secret": False},
+    "ollama_model": {"env": "OLLAMA_MODEL", "type": "string", "secret": False},
+    "ollama_num_ctx": {"env": "OLLAMA_NUM_CTX", "type": "integer", "secret": False},
+    "uex_base_url": {"env": "UEX_BASE_URL", "type": "string", "secret": False},
+    "uex_secret_key": {"env": "UEX_SECRET_KEY", "type": "string", "secret": True},
+    "uex_bearer_token": {"env": "UEX_BEARER_TOKEN", "type": "string", "secret": True},
+    "traderai_user_name": {"env": "TRADERAI_USER_NAME", "type": "string", "secret": False},
+    "traderai_memory_path": {"env": "TRADERAI_MEMORY_PATH", "type": "string", "secret": False},
+    "uex_notification_poll_seconds": {"env": "UEX_NOTIFICATION_POLL_SECONDS", "type": "integer", "secret": False},
+    "require_write_approval": {"env": "REQUIRE_WRITE_APPROVAL", "type": "boolean", "secret": False},
+}
+
+
+def app_data_dir() -> Path:
+    if sys.platform == "win32":
+        root = os.environ.get("LOCALAPPDATA")
+        if root:
+            return Path(root) / "TraderAI"
+    return Path.home() / ".traderai"
+
+
+def ensure_app_data_dir() -> Path:
+    path = app_data_dir()
+    path.mkdir(parents=True, exist_ok=True)
+    return path
+
+
+def user_config_path() -> Path:
+    return ensure_app_data_dir() / ".env"
+
+
+def default_memory_path() -> Path:
+    return ensure_app_data_dir() / "traderai.sqlite3"
+
+
+def log_path() -> Path:
+    return ensure_app_data_dir() / "TraderAI.log"
+
+
+def edge_profile_dir() -> Path:
+    return ensure_app_data_dir() / "EdgeProfile"
+
+
+class Settings(BaseSettings):
+    model_config = SettingsConfigDict(
+        env_file=(".env", str(user_config_path())),
+        env_file_encoding="utf-8",
+    )
+
+    ollama_base_url: str = "http://localhost:11434"
+    ollama_model: str = "qwen3.5:9b"
+    ollama_num_ctx: int = 64512
+    uex_base_url: str = "https://api.uexcorp.space/2.0"
+    uex_secret_key: str | None = Field(default=None)
+    uex_bearer_token: str | None = Field(default=None)
+    traderai_user_name: str | None = Field(default=None)
+    traderai_memory_path: str = Field(default_factory=lambda: str(default_memory_path()))
+    uex_notification_poll_seconds: int = 60
+    require_write_approval: bool = True
+
+    @field_validator("uex_secret_key", "uex_bearer_token", "traderai_user_name", mode="before")
+    @classmethod
+    def _blank_optional(cls, value: Any) -> Any:
+        return None if value == "" else value
+
+    @field_validator("traderai_memory_path", mode="before")
+    @classmethod
+    def _blank_memory_path(cls, value: Any) -> Any:
+        return str(default_memory_path()) if value == "" or value is None else value
+
+
+@lru_cache
+def get_settings() -> Settings:
+    return Settings()
+
+
+def settings_payload(settings: Settings | None = None) -> dict[str, Any]:
+    current = settings or get_settings()
+    values = current.model_dump()
+    secrets_configured = {}
+    for key, meta in CONFIG_FIELDS.items():
+        if meta.get("secret"):
+            secrets_configured[key] = bool(values.get(key))
+            values[key] = ""
+    return {
+        "app_data_dir": str(ensure_app_data_dir()),
+        "config_path": str(user_config_path()),
+        "log_path": str(log_path()),
+        "edge_profile_dir": str(edge_profile_dir()),
+        "values": values,
+        "fields": CONFIG_FIELDS,
+        "secrets_configured": secrets_configured,
+    }
+
+
+def save_settings(values: dict[str, Any]) -> dict[str, Any]:
+    current = get_settings().model_dump()
+    next_values = dict(current)
+    for key, value in values.items():
+        if key not in CONFIG_FIELDS:
+            continue
+        if CONFIG_FIELDS[key].get("secret") and value == "":
+            continue
+        next_values[key] = _coerce_value(key, value)
+
+    path = user_config_path()
+    lines = [
+        "# TraderAI desktop configuration",
+        "# Saved by the app. Environment variables still override these values.",
+        "",
+    ]
+    for key, meta in CONFIG_FIELDS.items():
+        value = next_values.get(key)
+        lines.append(f"{meta['env']}={_env_value(value)}")
+    path.write_text("\n".join(lines) + "\n", encoding="utf-8")
+    get_settings.cache_clear()
+    return settings_payload(get_settings())
+
+
+def _coerce_value(key: str, value: Any) -> Any:
+    field_type = CONFIG_FIELDS[key]["type"]
+    if value == "":
+        return None if key in {"uex_secret_key", "uex_bearer_token", "traderai_user_name"} else ""
+    if field_type == "integer":
+        return int(value)
+    if field_type == "boolean":
+        if isinstance(value, bool):
+            return value
+        return str(value).strip().casefold() in {"1", "true", "yes", "on"}
+    return str(value)
+
+
+def _env_value(value: Any) -> str:
+    if value is None:
+        return ""
+    if isinstance(value, bool):
+        return "true" if value else "false"
+    text = str(value)
+    if not text or any(char.isspace() for char in text) or "#" in text:
+        return '"' + text.replace("\\", "\\\\").replace('"', '\\"') + '"'
+    return text

traderai/desktop.py

@@ -0,0 +1,229 @@
+from __future__ import annotations
+
+import os
+from pathlib import Path
+import shutil
+import socket
+import subprocess
+import sys
+import threading
+import time
+import traceback
+from typing import NoReturn
+
+import httpx
+import uvicorn
+
+from traderai.config import edge_profile_dir, log_path
+
+
+def resource_path(*parts: str) -> Path:
+    base = Path(getattr(sys, "_MEIPASS", Path(__file__).resolve().parent.parent))
+    return base.joinpath(*parts)
+
+
+def main() -> None:
+    try:
+        _chdir_to_app_dir()
+        _log("TraderAI desktop starting")
+        _log(f"cwd={Path.cwd()}")
+        _log(f"executable={sys.executable}")
+        _log(f"frozen={getattr(sys, 'frozen', False)} meipass={getattr(sys, '_MEIPASS', '')}")
+        port = _select_port()
+        url = f"http://127.0.0.1:{port}"
+        _log(f"selected_url={url}")
+        if _existing_server_ready(url):
+            _log("existing TraderAI backend found; opening window")
+            _open_window(url)
+            return
+        server_thread = threading.Thread(target=_run_server, args=(port,), daemon=True)
+        server_thread.start()
+        _log("backend thread started")
+        _wait_for_server(url)
+        _log("backend health check passed")
+        _open_window(url)
+        _log("webview closed")
+    except Exception:
+        _log("fatal startup error")
+        _log(traceback.format_exc())
+        raise
+
+
+def _chdir_to_app_dir() -> None:
+    if getattr(sys, "frozen", False):
+        os.chdir(Path(sys.executable).resolve().parent)
+
+
+def _select_port() -> int:
+    preferred = int(os.getenv("TRADERAI_PORT", "8765"))
+    if _port_available(preferred):
+        return preferred
+    _log(f"preferred port {preferred} is in use")
+    return _free_port()
+
+
+def _port_available(port: int) -> bool:
+    try:
+        with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
+            sock.bind(("127.0.0.1", port))
+        return True
+    except OSError:
+        return False
+
+
+def _free_port() -> int:
+    with socket.socket(socket.AF_INET, socket.SOCK_STREAM) as sock:
+        sock.bind(("127.0.0.1", 0))
+        return int(sock.getsockname()[1])
+
+
+def _existing_server_ready(url: str) -> bool:
+    try:
+        response = httpx.get(f"{url}/api/health", timeout=1)
+        return response.status_code < 500 and response.headers.get("content-type", "").startswith("application/json")
+    except httpx.HTTPError:
+        return False
+
+
+def _run_server(port: int) -> NoReturn:
+    try:
+        _log(f"backend starting on port {port}")
+        from traderai.server import app
+
+        config = uvicorn.Config(
+            app,
+            host="127.0.0.1",
+            port=port,
+            log_level="info",
+            log_config=None,
+            lifespan="on",
+        )
+        server = uvicorn.Server(config)
+        server.run()
+        _log("backend server stopped")
+        raise SystemExit(0)
+    except BaseException:
+        _log("backend thread crashed")
+        _log(traceback.format_exc())
+        raise
+
+
+def _wait_for_server(url: str) -> None:
+    deadline = time.monotonic() + 30
+    last_error = ""
+    while time.monotonic() < deadline:
+        try:
+            response = httpx.get(f"{url}/api/health", timeout=1)
+            _log(f"health probe status={response.status_code}")
+            if response.status_code < 500:
+                return
+        except httpx.HTTPError as exc:
+            last_error = str(exc)
+            _log(f"health probe failed: {last_error}")
+        time.sleep(0.25)
+    raise RuntimeError(f"TraderAI backend did not start within 30 seconds. {last_error}")
+
+
+def _open_window(url: str) -> None:
+    mode = os.getenv("TRADERAI_DESKTOP_UI", "edge").casefold()
+    _log(f"ui_mode={mode}")
+    if mode == "webview":
+        _open_webview(url)
+        return
+    if _open_edge_app(url):
+        return
+    _open_browser(url)
+
+
+def _open_webview(url: str) -> None:
+    _log("importing pywebview")
+    import webview
+
+    _log("creating pywebview window")
+    webview.create_window(
+        "TraderAI",
+        url,
+        width=1320,
+        height=860,
+        min_size=(980, 680),
+        text_select=True,
+        icon=str(resource_path("web", "art", "LBC_Logo.ico")),
+    )
+    _log("starting pywebview")
+    webview.start(gui="edgechromium", debug=False)
+
+
+def _open_edge_app(url: str) -> bool:
+    edge = _edge_path()
+    if not edge:
+        _log("msedge not found; falling back to default browser")
+        return False
+    profile_dir = edge_profile_dir()
+    profile_dir.mkdir(parents=True, exist_ok=True)
+    command = [
+        str(edge),
+        f"--app={url}",
+        f"--user-data-dir={profile_dir}",
+        "--new-window",
+        "--no-first-run",
+        "--disable-features=Translate",
+        f"--app-icon={resource_path('web', 'art', 'LBC_Logo.ico')}",
+    ]
+    _log(f"launching edge app: {' '.join(command)}")
+    process = subprocess.Popen(command)
+    _log(f"edge process id={process.pid}")
+    time.sleep(2)
+    if process.poll() is None:
+        process.wait()
+        _log("edge app process exited")
+        return True
+    _log(f"edge app process exited early code={process.returncode}; keeping backend alive")
+    _keep_alive()
+    return True
+
+
+def _open_browser(url: str) -> None:
+    import webbrowser
+
+    _log(f"opening default browser at {url}")
+    webbrowser.open(url)
+    _keep_alive()
+
+
+def _keep_alive() -> None:
+    _log("backend staying alive; close TraderAI from Task Manager if no app window owns this process")
+    while True:
+        time.sleep(60)
+
+
+def _edge_path() -> Path | None:
+    edge = shutil.which("msedge")
+    if edge:
+        return Path(edge)
+    candidates = [
+        Path(os.environ.get("ProgramFiles", "")) / "Microsoft" / "Edge" / "Application" / "msedge.exe",
+        Path(os.environ.get("ProgramFiles(x86)", "")) / "Microsoft" / "Edge" / "Application" / "msedge.exe",
+        Path(os.environ.get("LocalAppData", "")) / "Microsoft" / "Edge" / "Application" / "msedge.exe",
+    ]
+    for candidate in candidates:
+        if candidate.exists():
+            return candidate
+    return None
+
+
+def _log(message: str) -> None:
+    try:
+        log_path = _log_path()
+        timestamp = time.strftime("%Y-%m-%d %H:%M:%S")
+        with log_path.open("a", encoding="utf-8") as file:
+            file.write(f"[{timestamp}] {message}\n")
+    except Exception:
+        pass
+
+
+def _log_path() -> Path:
+    return log_path()
+
+
+if __name__ == "__main__":
+    main()

traderai/memory.py

@@ -0,0 +1,378 @@
+from __future__ import annotations
+
+import json
+import sqlite3
+from datetime import datetime, timezone
+from pathlib import Path
+from typing import Any
+from zoneinfo import ZoneInfo
+
+
+def utc_now() -> datetime:
+    return datetime.now(timezone.utc)
+
+
+def iso_now() -> str:
+    return utc_now().isoformat()
+
+
+def iso_now_in_zone(zone: ZoneInfo) -> str:
+    return utc_now().astimezone(zone).isoformat()
+
+
+def parse_iso(value: str) -> datetime:
+    parsed = datetime.fromisoformat(value)
+    if parsed.tzinfo is None:
+        return parsed.replace(tzinfo=timezone.utc)
+    return parsed
+
+
+def time_since(value: str, now: datetime | None = None) -> str:
+    then = parse_iso(value)
+    current = now or utc_now()
+    if current.tzinfo is None:
+        current = current.replace(tzinfo=timezone.utc)
+    seconds = max(0, int((current - then).total_seconds()))
+    if seconds < 60:
+        return f"{seconds} seconds ago"
+    minutes = seconds // 60
+    if minutes < 60:
+        return _plural(minutes, "minute") + " ago"
+    hours = minutes // 60
+    if hours < 24:
+        return _plural(hours, "hour") + " ago"
+    days = hours // 24
+    return _plural(days, "day") + " ago"
+
+
+def _plural(value: int, unit: str) -> str:
+    suffix = "" if value == 1 else "s"
+    return f"{value} {unit}{suffix}"
+
+
+class MemoryStore:
+    def __init__(self, path: str) -> None:
+        self.path = Path(path)
+        self.path.parent.mkdir(parents=True, exist_ok=True)
+        self._init_db()
+
+    def _connect(self) -> sqlite3.Connection:
+        connection = sqlite3.connect(self.path)
+        connection.row_factory = sqlite3.Row
+        return connection
+
+    def _init_db(self) -> None:
+        with self._connect() as db:
+            db.executescript(
+                """
+                CREATE TABLE IF NOT EXISTS conversations (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    role TEXT NOT NULL,
+                    content TEXT NOT NULL,
+                    created_at TEXT NOT NULL
+                );
+
+                CREATE TABLE IF NOT EXISTS memories (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    kind TEXT NOT NULL,
+                    content TEXT NOT NULL,
+                    importance INTEGER NOT NULL DEFAULT 3,
+                    metadata TEXT NOT NULL DEFAULT '{}',
+                    created_at TEXT NOT NULL,
+                    updated_at TEXT NOT NULL
+                );
+
+                CREATE VIRTUAL TABLE IF NOT EXISTS memories_fts USING fts5(
+                    content,
+                    kind UNINDEXED,
+                    content='memories',
+                    content_rowid='id'
+                );
+
+                CREATE TRIGGER IF NOT EXISTS memories_ai AFTER INSERT ON memories BEGIN
+                    INSERT INTO memories_fts(rowid, content, kind) VALUES (new.id, new.content, new.kind);
+                END;
+
+                CREATE TRIGGER IF NOT EXISTS memories_ad AFTER DELETE ON memories BEGIN
+                    INSERT INTO memories_fts(memories_fts, rowid, content, kind)
+                    VALUES('delete', old.id, old.content, old.kind);
+                END;
+
+                CREATE TRIGGER IF NOT EXISTS memories_au AFTER UPDATE ON memories BEGIN
+                    INSERT INTO memories_fts(memories_fts, rowid, content, kind)
+                    VALUES('delete', old.id, old.content, old.kind);
+                    INSERT INTO memories_fts(rowid, content, kind) VALUES (new.id, new.content, new.kind);
+                END;
+
+                CREATE TABLE IF NOT EXISTS user_profile (
+                    key TEXT PRIMARY KEY,
+                    value TEXT NOT NULL,
+                    updated_at TEXT NOT NULL
+                );
+
+                CREATE TABLE IF NOT EXISTS scheduled_jobs (
+                    id TEXT PRIMARY KEY,
+                    prompt TEXT NOT NULL,
+                    trigger_type TEXT NOT NULL,
+                    trigger_value TEXT NOT NULL,
+                    next_run_at TEXT,
+                    created_at TEXT NOT NULL,
+                    last_run_at TEXT,
+                    enabled INTEGER NOT NULL DEFAULT 1
+                );
+
+                CREATE TABLE IF NOT EXISTS outbox (
+                    id INTEGER PRIMARY KEY AUTOINCREMENT,
+                    content TEXT NOT NULL,
+                    created_at TEXT NOT NULL,
+                    delivered_at TEXT
+                );
+                """
+            )
+
+    def add_conversation(self, role: str, content: str) -> None:
+        with self._connect() as db:
+            db.execute(
+                "INSERT INTO conversations(role, content, created_at) VALUES (?, ?, ?)",
+                (role, content, iso_now()),
+            )
+
+    def last_interaction(self) -> dict[str, Any] | None:
+        with self._connect() as db:
+            row = db.execute(
+                "SELECT role, content, created_at FROM conversations ORDER BY id DESC LIMIT 1"
+            ).fetchone()
+        return dict(row) if row else None
+
+    def recent_conversation(self, limit: int = 8) -> list[dict[str, Any]]:
+        with self._connect() as db:
+            rows = db.execute(
+                "SELECT role, content, created_at FROM conversations ORDER BY id DESC LIMIT ?",
+                (limit,),
+            ).fetchall()
+        return [dict(row) for row in reversed(rows)]
+
+    def remember(self, kind: str, content: str, importance: int = 3, metadata: dict[str, Any] | None = None) -> dict[str, Any]:
+        now = iso_now()
+        with self._connect() as db:
+            cursor = db.execute(
+                """
+                INSERT INTO memories(kind, content, importance, metadata, created_at, updated_at)
+                VALUES (?, ?, ?, ?, ?, ?)
+                """,
+                (kind, content, importance, json.dumps(metadata or {}), now, now),
+            )
+            memory_id = cursor.lastrowid
+        return {"id": memory_id, "kind": kind, "content": content, "importance": importance, "created_at": now}
+
+    def recall(self, query: str, limit: int = 6) -> list[dict[str, Any]]:
+        if not query.strip():
+            return self.top_memories(limit)
+
+        with self._connect() as db:
+            try:
+                rows = db.execute(
+                    """
+                    SELECT m.id, m.kind, m.content, m.importance, m.metadata, m.created_at,
+                           bm25(memories_fts) AS rank
+                    FROM memories_fts
+                    JOIN memories m ON m.id = memories_fts.rowid
+                    WHERE memories_fts MATCH ?
+                    ORDER BY rank, m.importance DESC
+                    LIMIT ?
+                    """,
+                    (self._fts_query(query), limit),
+                ).fetchall()
+            except sqlite3.OperationalError:
+                rows = db.execute(
+                    """
+                    SELECT id, kind, content, importance, metadata, created_at
+                    FROM memories
+                    WHERE content LIKE ?
+                    ORDER BY importance DESC, id DESC
+                    LIMIT ?
+                    """,
+                    (f"%{query}%", limit),
+                ).fetchall()
+        return [self._memory_row(row) for row in rows]
+
+    def top_memories(self, limit: int = 6) -> list[dict[str, Any]]:
+        with self._connect() as db:
+            rows = db.execute(
+                """
+                SELECT id, kind, content, importance, metadata, created_at
+                FROM memories
+                ORDER BY importance DESC, updated_at DESC
+                LIMIT ?
+                """,
+                (limit,),
+            ).fetchall()
+        return [self._memory_row(row) for row in rows]
+
+    def inspect(self, limit: int = 50) -> dict[str, Any]:
+        with self._connect() as db:
+            memories = db.execute(
+                """
+                SELECT id, kind, content, importance, metadata, created_at, updated_at
+                FROM memories
+                ORDER BY importance DESC, updated_at DESC
+                LIMIT ?
+                """,
+                (limit,),
+            ).fetchall()
+            conversations = db.execute(
+                """
+                SELECT id, role, content, created_at
+                FROM conversations
+                ORDER BY id DESC
+                LIMIT ?
+                """,
+                (limit,),
+            ).fetchall()
+            profile_rows = db.execute(
+                "SELECT key, value, updated_at FROM user_profile ORDER BY key"
+            ).fetchall()
+            jobs = db.execute(
+                "SELECT * FROM scheduled_jobs ORDER BY enabled DESC, next_run_at"
+            ).fetchall()
+            outbox = db.execute(
+                "SELECT id, content, created_at, delivered_at FROM outbox ORDER BY id DESC LIMIT ?",
+                (limit,),
+            ).fetchall()
+
+        profile = []
+        for row in profile_rows:
+            item = dict(row)
+            try:
+                item["value"] = json.loads(item["value"])
+            except json.JSONDecodeError:
+                pass
+            profile.append(item)
+
+        return {
+            "path": str(self.path),
+            "memories": [self._memory_row(row) for row in memories],
+            "conversations": [dict(row) for row in conversations],
+            "profile": profile,
+            "scheduled_jobs": [dict(row) for row in jobs],
+            "outbox": [dict(row) for row in outbox],
+        }
+
+    def clear(
+        self,
+        include_memories: bool = True,
+        include_conversations: bool = True,
+        include_profile: bool = False,
+        include_jobs: bool = False,
+        include_outbox: bool = True,
+    ) -> dict[str, int]:
+        deleted: dict[str, int] = {}
+        with self._connect() as db:
+            if include_memories:
+                deleted["memories"] = db.execute("DELETE FROM memories").rowcount
+                db.execute("INSERT INTO memories_fts(memories_fts) VALUES('rebuild')")
+            if include_conversations:
+                deleted["conversations"] = db.execute("DELETE FROM conversations").rowcount
+            if include_profile:
+                deleted["profile"] = db.execute("DELETE FROM user_profile").rowcount
+            if include_jobs:
+                deleted["scheduled_jobs"] = db.execute("DELETE FROM scheduled_jobs").rowcount
+            if include_outbox:
+                deleted["outbox"] = db.execute("DELETE FROM outbox").rowcount
+        return deleted
+
+    def set_profile(self, key: str, value: Any) -> None:
+        with self._connect() as db:
+            db.execute(
+                """
+                INSERT INTO user_profile(key, value, updated_at) VALUES (?, ?, ?)
+                ON CONFLICT(key) DO UPDATE SET value=excluded.value, updated_at=excluded.updated_at
+                """,
+                (key, json.dumps(value), iso_now()),
+            )
+
+    def get_profile(self) -> dict[str, Any]:
+        with self._connect() as db:
+            rows = db.execute("SELECT key, value FROM user_profile").fetchall()
+        profile = {}
+        for row in rows:
+            try:
+                profile[row["key"]] = json.loads(row["value"])
+            except json.JSONDecodeError:
+                profile[row["key"]] = row["value"]
+        return profile
+
+    def add_job(
+        self,
+        job_id: str,
+        prompt: str,
+        trigger_type: str,
+        trigger_value: str,
+        next_run_at: str | None = None,
+    ) -> dict[str, Any]:
+        with self._connect() as db:
+            db.execute(
+                """
+                INSERT INTO scheduled_jobs(id, prompt, trigger_type, trigger_value, next_run_at, created_at, enabled)
+                VALUES (?, ?, ?, ?, ?, ?, 1)
+                ON CONFLICT(id) DO UPDATE SET
+                    prompt=excluded.prompt,
+                    trigger_type=excluded.trigger_type,
+                    trigger_value=excluded.trigger_value,
+                    next_run_at=excluded.next_run_at,
+                    enabled=1
+                """,
+                (job_id, prompt, trigger_type, trigger_value, next_run_at, iso_now()),
+            )
+        return {
+            "id": job_id,
+            "prompt": prompt,
+            "trigger_type": trigger_type,
+            "trigger_value": trigger_value,
+            "next_run_at": next_run_at,
+        }
+
+    def list_jobs(self) -> list[dict[str, Any]]:
+        with self._connect() as db:
+            rows = db.execute(
+                "SELECT * FROM scheduled_jobs WHERE enabled = 1 ORDER BY next_run_at IS NULL, next_run_at"
+            ).fetchall()
+        return [dict(row) for row in rows]
+
+    def mark_job_run(self, job_id: str, next_run_at: str | None = None) -> None:
+        with self._connect() as db:
+            db.execute(
+                "UPDATE scheduled_jobs SET last_run_at = ?, next_run_at = ? WHERE id = ?",
+                (iso_now(), next_run_at, job_id),
+            )
+
+    def add_outbox(self, content: str) -> None:
+        with self._connect() as db:
+            db.execute("INSERT INTO outbox(content, created_at) VALUES (?, ?)", (content, iso_now()))
+
+    def undelivered_outbox(self) -> list[dict[str, Any]]:
+        now = iso_now()
+        with self._connect() as db:
+            rows = db.execute(
+                "SELECT id, content, created_at FROM outbox WHERE delivered_at IS NULL ORDER BY id"
+            ).fetchall()
+            db.execute(
+                "UPDATE outbox SET delivered_at = ? WHERE delivered_at IS NULL",
+                (now,),
+            )
+        return [dict(row) for row in rows]
+
+    @staticmethod
+    def _fts_query(query: str) -> str:
+        tokens = [token.replace('"', "") for token in query.split() if token.strip()]
+        return " OR ".join(f'"{token}"' for token in tokens) or '""'
+
+    @staticmethod
+    def _memory_row(row: sqlite3.Row) -> dict[str, Any]:
+        data = dict(row)
+        if "metadata" in data:
+            try:
+                data["metadata"] = json.loads(data["metadata"])
+            except json.JSONDecodeError:
+                data["metadata"] = {}
+        return data

traderai/scheduler.py

@@ -0,0 +1,146 @@
+from __future__ import annotations
+
+from datetime import datetime
+from typing import Any
+from uuid import uuid4
+
+from apscheduler.schedulers.asyncio import AsyncIOScheduler
+from apscheduler.triggers.cron import CronTrigger
+from apscheduler.triggers.date import DateTrigger
+from apscheduler.triggers.interval import IntervalTrigger
+from tzlocal import get_localzone
+
+from traderai.memory import MemoryStore, iso_now, time_since
+
+
+UEX_NOTIFICATION_JOB_ID = "uex-notification-poll"
+
+
+class WakeScheduler:
+    def __init__(self, memory: MemoryStore) -> None:
+        self.memory = memory
+        self.scheduler = AsyncIOScheduler(timezone=get_localzone())
+        self.agent = None
+        self.uex = None
+        self.notification_poll_seconds = 60
+
+    def bind_agent(self, agent: Any) -> None:
+        self.agent = agent
+
+    def bind_uex_notifications(self, uex: Any, poll_seconds: int = 60) -> None:
+        self.uex = uex
+        self.notification_poll_seconds = max(15, poll_seconds)
+
+    def start(self) -> None:
+        if not self.scheduler.running:
+            self.scheduler.start()
+        self._schedule_notification_poll()
+        for job in self.memory.list_jobs():
+            self._schedule_existing(job)
+
+    def shutdown(self) -> None:
+        if self.scheduler.running:
+            self.scheduler.shutdown(wait=False)
+
+    def schedule_date(self, run_at: str, prompt: str, job_id: str | None = None) -> dict[str, Any]:
+        parsed = datetime.fromisoformat(run_at)
+        job_id = job_id or f"wake-{uuid4()}"
+        trigger = DateTrigger(run_date=parsed)
+        self.scheduler.add_job(self._run_job, trigger=trigger, id=job_id, args=[job_id, prompt], replace_existing=True)
+        return self.memory.add_job(job_id, prompt, "date", run_at, parsed.isoformat())
+
+    def schedule_cron(self, cron: str, prompt: str, job_id: str | None = None) -> dict[str, Any]:
+        job_id = job_id or f"wake-{uuid4()}"
+        trigger = CronTrigger.from_crontab(cron)
+        self.scheduler.add_job(self._run_job, trigger=trigger, id=job_id, args=[job_id, prompt], replace_existing=True)
+        next_run = self.scheduler.get_job(job_id).next_run_time
+        return self.memory.add_job(job_id, prompt, "cron", cron, next_run.isoformat() if next_run else None)
+
+    def list_jobs(self) -> list[dict[str, Any]]:
+        return self.memory.list_jobs()
+
+    def _schedule_existing(self, job: dict[str, Any]) -> None:
+        if job["trigger_type"] == "cron":
+            trigger = CronTrigger.from_crontab(job["trigger_value"])
+        elif job["trigger_type"] == "date":
+            trigger = DateTrigger(run_date=datetime.fromisoformat(job["trigger_value"]))
+        else:
+            return
+        self.scheduler.add_job(
+            self._run_job,
+            trigger=trigger,
+            id=job["id"],
+            args=[job["id"], job["prompt"]],
+            replace_existing=True,
+        )
+
+    async def _run_job(self, job_id: str, prompt: str) -> None:
+        last = self.memory.last_interaction()
+        last_text = f"{last['created_at']} ({time_since(last['created_at'])})" if last else "never"
+        wake_message = (
+            f"Scheduled wake job fired. Current time is {iso_now()}. "
+            f"The last chat interaction was {last_text}. Job instruction: {prompt}"
+        )
+        if self.agent is None:
+            self.memory.add_outbox(wake_message)
+            return
+
+        text = await self.agent.generate_wake_response(wake_message)
+        self.memory.add_outbox(text)
+        self.memory.mark_job_run(job_id)
+
+    def _schedule_notification_poll(self) -> None:
+        if self.uex is None:
+            return
+        self.scheduler.add_job(
+            self.poll_uex_notifications,
+            trigger=IntervalTrigger(seconds=self.notification_poll_seconds),
+            id=UEX_NOTIFICATION_JOB_ID,
+            replace_existing=True,
+            next_run_time=datetime.now(),
+        )
+
+    async def poll_uex_notifications(self) -> list[dict[str, Any]]:
+        if self.uex is None:
+            return []
+
+        response = await self.uex.get_user_notifications()
+        notifications = response.get("notifications") or []
+        pending = [item for item in notifications if not item.get("date_read")]
+        profile = self.memory.get_profile()
+        seen = set(profile.get("uex_seen_notification_keys") or [])
+        new_pending = [item for item in pending if self._notification_key(item) not in seen]
+
+        if new_pending:
+            for item in new_pending:
+                self.memory.add_outbox(self._notification_text(item))
+            seen.update(self._notification_key(item) for item in new_pending)
+            self.memory.set_profile("uex_seen_notification_keys", sorted(seen))
+            self.memory.set_profile("uex_last_notification_check", iso_now())
+        elif notifications:
+            seen.update(self._notification_key(item) for item in pending)
+            self.memory.set_profile("uex_seen_notification_keys", sorted(seen))
+            self.memory.set_profile("uex_last_notification_check", iso_now())
+
+        return new_pending
+
+    @staticmethod
+    def _notification_key(item: dict[str, Any]) -> str:
+        for key in ("code", "id"):
+            value = item.get(key)
+            if value not in (None, ""):
+                return f"{key}:{value}"
+        return f"notification:{item.get('date_added')}:{item.get('message')}"
+
+    @staticmethod
+    def _notification_text(item: dict[str, Any]) -> str:
+        message = item.get("message") or "You have a pending UEX notification."
+        redir = item.get("redir")
+        code = item.get("code")
+        details = []
+        if code:
+            details.append(f"code `{code}`")
+        if redir:
+            details.append(f"path `{redir}`")
+        suffix = f" ({', '.join(details)})" if details else ""
+        return f"UEX notification: {message}{suffix}"

traderai/server.py

@@ -0,0 +1,559 @@
+from __future__ import annotations
+
+import os
+import json
+import shutil
+import subprocess
+import sys
+import threading
+import time
+import webbrowser
+from pathlib import Path
+from typing import Any
+
+import httpx
+from fastapi import FastAPI
+from fastapi import HTTPException
+from fastapi.responses import FileResponse, StreamingResponse
+from fastapi.staticfiles import StaticFiles
+from pydantic import BaseModel
+
+from traderai.agent import OllamaAgent, OllamaUnavailable
+from traderai.config import save_settings, settings_payload
+from traderai.config import get_settings
+from traderai.memory import MemoryStore
+from traderai.scheduler import WakeScheduler
+from traderai.tools import ToolRegistry
+from traderai.uex_client import UEXClient
+from traderai.version import RELEASES_API_URL, RELEASES_URL, __version__
+
+
+def resource_path(*parts: str) -> Path:
+    base = Path(getattr(sys, "_MEIPASS", Path(__file__).resolve().parent.parent))
+    return base.joinpath(*parts)
+
+
+class ChatRequest(BaseModel):
+    message: str
+
+
+class ClearMemoryRequest(BaseModel):
+    include_memories: bool = True
+    include_conversations: bool = True
+    include_profile: bool = False
+    include_jobs: bool = False
+    include_outbox: bool = True
+
+
+class ConfigUpdateRequest(BaseModel):
+    values: dict
+
+
+class OllamaModelRequest(BaseModel):
+    model: str | None = None
+
+
+OLLAMA_DOWNLOAD_URL = "https://ollama.com/download/windows"
+UPDATE_ASSET_NAME = "TraderAI.exe"
+
+
+def create_app() -> FastAPI:
+    settings = get_settings()
+    memory = MemoryStore(settings.traderai_memory_path)
+    scheduler = WakeScheduler(memory)
+    uex = UEXClient(settings.uex_base_url, settings.uex_secret_key, settings.uex_bearer_token)
+    tools = ToolRegistry(uex, settings.require_write_approval, memory=memory, scheduler=scheduler)
+    agent = OllamaAgent(
+        settings.ollama_base_url,
+        settings.ollama_model,
+        tools,
+        memory=memory,
+        user_name=settings.traderai_user_name,
+        num_ctx=settings.ollama_num_ctx,
+    )
+    scheduler.bind_agent(agent)
+    scheduler.bind_uex_notifications(uex, settings.uex_notification_poll_seconds)
+
+    app = FastAPI(title="TraderAI")
+    static_dir = resource_path("web")
+    app.mount("/static", StaticFiles(directory=static_dir), name="static")
+
+    @app.on_event("startup")
+    async def startup() -> None:
+        await refresh_user_profile()
+        scheduler.start()
+
+    @app.on_event("shutdown")
+    async def shutdown() -> None:
+        scheduler.shutdown()
+
+    async def refresh_user_profile() -> None:
+        if settings.traderai_user_name:
+            memory.set_profile("configured_name", settings.traderai_user_name)
+            agent.user_name = agent.user_name or settings.traderai_user_name
+
+        try:
+            response = await uex.get_user(authenticated=True)
+        except Exception as exc:
+            memory.set_profile("uex_user_error", str(exc))
+            if settings.traderai_user_name:
+                try:
+                    response = await uex.get_user(username=settings.traderai_user_name)
+                except Exception:
+                    return
+            else:
+                return
+
+        data = response.get("user")
+        if data:
+            memory.set_profile("uex_user", data)
+            username = data.get("username") or data.get("user_username") or data.get("name")
+            if username:
+                agent.user_name = username
+
+    @app.get("/")
+    async def index() -> FileResponse:
+        return FileResponse(static_dir / "index.html")
+
+    @app.get("/api/health")
+    async def health() -> dict:
+        return {
+            "ollama": await agent.health(),
+            "user": memory.get_profile(),
+            "jobs": scheduler.list_jobs(),
+            "app_data_dir": settings_payload()["app_data_dir"],
+            "version": __version__,
+        }
+
+    @app.get("/api/config")
+    async def inspect_config() -> dict:
+        return settings_payload()
+
+    @app.post("/api/config")
+    async def update_config(request: ConfigUpdateRequest) -> dict:
+        updated = save_settings(request.values)
+        updated["restart_required"] = True
+        updated["message"] = "Configuration saved. Restart TraderAI for all settings to take effect."
+        return updated
+
+    @app.get("/api/ollama/status")
+    async def ollama_status() -> dict:
+        return await inspect_ollama()
+
+    @app.post("/api/ollama/launch")
+    async def launch_ollama() -> dict:
+        command = ollama_launch_command()
+        if not command:
+            raise HTTPException(status_code=404, detail="Ollama is not installed or was not found on PATH.")
+        try:
+            popen_hidden(command)
+        except OSError as exc:
+            raise HTTPException(status_code=500, detail=f"Could not launch Ollama: {exc}") from exc
+        status = await inspect_ollama()
+        status["message"] = "Ollama launch requested."
+        return status
+
+    @app.post("/api/ollama/pull")
+    async def pull_ollama_model(request: OllamaModelRequest) -> dict:
+        settings_now = get_settings()
+        model = (request.model or settings_now.ollama_model).strip()
+        if not model:
+            raise HTTPException(status_code=400, detail="No Ollama model is configured.")
+        cli = find_ollama_cli()
+        if not cli:
+            raise HTTPException(status_code=404, detail="Ollama CLI was not found.")
+        try:
+            popen_hidden([str(cli), "pull", model])
+        except OSError as exc:
+            raise HTTPException(status_code=500, detail=f"Could not start model install: {exc}") from exc
+        status = await inspect_ollama()
+        status["message"] = f"Started installing model {model}."
+        return status
+
+    @app.post("/api/ollama/install")
+    async def install_ollama() -> dict:
+        winget = shutil.which("winget")
+        if not winget:
+            return {
+                "started": False,
+                "message": "winget is not available on this system. Open the download page instead.",
+                "download_url": OLLAMA_DOWNLOAD_URL,
+            }
+        try:
+            popen_hidden(
+                [
+                    winget,
+                    "install",
+                    "-e",
+                    "--id",
+                    "Ollama.Ollama",
+                    "--accept-package-agreements",
+                    "--accept-source-agreements",
+                ]
+            )
+        except OSError as exc:
+            raise HTTPException(status_code=500, detail=f"Could not start Ollama install: {exc}") from exc
+        return {"started": True, "message": "Started Ollama install with winget.", "download_url": OLLAMA_DOWNLOAD_URL}
+
+    @app.post("/api/ollama/download")
+    async def download_ollama() -> dict:
+        webbrowser.open(OLLAMA_DOWNLOAD_URL)
+        return {"opened": True, "download_url": OLLAMA_DOWNLOAD_URL, "message": "Opened the Ollama download page."}
+
+    @app.get("/api/update/check")
+    async def check_update() -> dict:
+        return await inspect_update()
+
+    @app.post("/api/update/install")
+    async def install_update() -> dict:
+        update = await inspect_update()
+        if not update["available"]:
+            return {**update, "message": "TraderAI is already up to date."}
+        if not getattr(sys, "frozen", False):
+            return {
+                **update,
+                "started": False,
+                "message": "Update download is available, but self-update only runs from the packaged exe.",
+            }
+
+        asset_url = update.get("asset_download_url")
+        if not asset_url:
+            raise HTTPException(status_code=404, detail="The latest release does not include TraderAI.exe.")
+
+        downloaded = await download_update_asset(asset_url, update["latest_version"])
+        script = write_update_script(downloaded, Path(sys.executable))
+        updater_command = [
+            "powershell",
+            "-NoProfile",
+            "-ExecutionPolicy",
+            "Bypass",
+            "-File",
+            str(script),
+            "-ProcessId",
+            str(os.getpid()),
+            "-Source",
+            str(downloaded),
+            "-Target",
+            str(Path(sys.executable)),
+        ]
+        updater_kwargs: dict[str, Any] = {"stdout": subprocess.DEVNULL, "stderr": subprocess.DEVNULL}
+        if sys.platform == "win32":
+            updater_kwargs["creationflags"] = subprocess.CREATE_NO_WINDOW
+        subprocess.Popen(updater_command, **updater_kwargs)
+        threading.Thread(target=exit_after_update_response, daemon=True).start()
+        return {**update, "started": True, "message": "Update downloaded. TraderAI will restart into the new version."}
+
+    @app.post("/api/chat")
+    async def chat(request: ChatRequest) -> dict:
+        try:
+            return await agent.chat(request.message)
+        except OllamaUnavailable as exc:
+            raise HTTPException(status_code=503, detail=str(exc)) from exc
+
+    @app.post("/api/chat/stream")
+    async def chat_stream(request: ChatRequest) -> StreamingResponse:
+        async def events():
+            async for event in agent.chat_events(request.message):
+                yield f"data: {json.dumps(event)}\n\n"
+
+        return StreamingResponse(events(), media_type="text/event-stream")
+
+    @app.get("/api/pending-actions")
+    async def pending_actions() -> dict:
+        return {"pending_actions": agent._pending_payloads()}
+
+    @app.get("/api/notifications")
+    async def notifications() -> dict:
+        return {"notifications": memory.undelivered_outbox()}
+
+    @app.get("/api/wake-jobs")
+    async def wake_jobs() -> dict:
+        return {"scheduled_jobs": scheduler.list_jobs()}
+
+    @app.get("/api/memory")
+    async def inspect_memory(limit: int = 50) -> dict:
+        return memory.inspect(max(1, min(limit, 200)))
+
+    @app.post("/api/memory/clear")
+    async def clear_memory(request: ClearMemoryRequest) -> dict:
+        if request.include_jobs:
+            scheduler.shutdown()
+        deleted = memory.clear(
+            include_memories=request.include_memories,
+            include_conversations=request.include_conversations,
+            include_profile=request.include_profile,
+            include_jobs=request.include_jobs,
+            include_outbox=request.include_outbox,
+        )
+        if request.include_jobs:
+            scheduler.start()
+        return {"deleted": deleted, "memory": memory.inspect(50)}
+
+    @app.post("/api/approve/{action_id}")
+    async def approve(action_id: str) -> dict:
+        return await tools.approve(action_id)
+
+    @app.post("/api/decline/{action_id}")
+    async def decline(action_id: str) -> dict:
+        return await tools.decline(action_id)
+
+    return app
+
+
+async def inspect_ollama() -> dict[str, Any]:
+    settings = get_settings()
+    executable = find_ollama_executable()
+    cli = find_ollama_cli()
+    models: list[str] = []
+    online = False
+    detail = ""
+
+    try:
+        async with httpx.AsyncClient(timeout=3) as client:
+            response = await client.get(f"{settings.ollama_base_url.rstrip('/')}/api/tags")
+        response.raise_for_status()
+        body = response.json()
+        online = True
+        models = [item.get("name") or item.get("model") for item in body.get("models", [])]
+        models = [model for model in models if model]
+    except (httpx.HTTPError, ValueError) as exc:
+        detail = str(exc)
+
+    installed = bool(executable or cli)
+    model_available = settings.ollama_model in models
+    return {
+        "installed": installed,
+        "running": online,
+        "online": online,
+        "model_available": model_available,
+        "configured_model": settings.ollama_model,
+        "base_url": settings.ollama_base_url,
+        "num_ctx": settings.ollama_num_ctx,
+        "models": models,
+        "executable": str(executable) if executable else None,
+        "cli": str(cli) if cli else None,
+        "can_auto_install": bool(shutil.which("winget")),
+        "download_url": OLLAMA_DOWNLOAD_URL,
+        "message": ollama_status_message(installed, online, model_available, settings.ollama_model),
+        "detail": detail,
+    }
+
+
+def ollama_status_message(installed: bool, running: bool, model_available: bool, model: str) -> str:
+    if not installed:
+        return "Ollama is not installed."
+    if not running:
+        return "Ollama is installed but not running."
+    if not model_available:
+        return f'Ollama is running, but model "{model}" is not installed.'
+    return "Ollama is ready."
+
+
+def find_ollama_executable() -> Path | None:
+    candidates = [
+        shutil.which("ollama"),
+        os.environ.get("OLLAMA_EXE"),
+        os.path.join(os.environ.get("LOCALAPPDATA", ""), "Programs", "Ollama", "Ollama.exe"),
+        os.path.join(os.environ.get("LOCALAPPDATA", ""), "Programs", "Ollama", "ollama.exe"),
+        os.path.join(os.environ.get("ProgramFiles", ""), "Ollama", "Ollama.exe"),
+        os.path.join(os.environ.get("ProgramFiles", ""), "Ollama", "ollama.exe"),
+        os.path.join(os.environ.get("ProgramFiles(x86)", ""), "Ollama", "Ollama.exe"),
+        os.path.join(os.environ.get("ProgramFiles(x86)", ""), "Ollama", "ollama.exe"),
+    ]
+    for candidate in candidates:
+        if not candidate:
+            continue
+        path = Path(candidate)
+        if path.exists():
+            return path
+    return None
+
+
+def find_ollama_cli() -> Path | None:
+    candidates = [
+        shutil.which("ollama"),
+        os.path.join(os.environ.get("LOCALAPPDATA", ""), "Programs", "Ollama", "ollama.exe"),
+        os.path.join(os.environ.get("ProgramFiles", ""), "Ollama", "ollama.exe"),
+        os.path.join(os.environ.get("ProgramFiles(x86)", ""), "Ollama", "ollama.exe"),
+    ]
+    for candidate in candidates:
+        if not candidate:
+            continue
+        path = Path(candidate)
+        if path.exists():
+            return path
+    return None
+
+
+def ollama_launch_command() -> list[str] | None:
+    executable = find_ollama_executable()
+    if not executable:
+        return None
+    if executable.name == "Ollama.exe":
+        return [str(executable)]
+    return [str(executable), "serve"]
+
+
+def popen_hidden(command: list[str]) -> subprocess.Popen:
+    kwargs: dict[str, Any] = {"stdout": subprocess.DEVNULL, "stderr": subprocess.DEVNULL}
+    if sys.platform == "win32":
+        kwargs["creationflags"] = subprocess.CREATE_NO_WINDOW
+    return subprocess.Popen(command, **kwargs)
+
+
+async def inspect_update() -> dict[str, Any]:
+    try:
+        latest = await latest_release()
+    except (httpx.HTTPError, ValueError) as exc:
+        return {
+            "current_version": __version__,
+            "latest_version": None,
+            "available": False,
+            "release_url": RELEASES_URL,
+            "message": f"Could not check releases: {exc}",
+        }
+    if not latest:
+        return {
+            "current_version": __version__,
+            "latest_version": None,
+            "available": False,
+            "release_url": RELEASES_URL,
+            "message": "No releases were found.",
+        }
+
+    latest_version = normalize_version(latest.get("tag_name") or latest.get("name") or "")
+    asset = release_asset(latest, UPDATE_ASSET_NAME)
+    available = latest_version is not None and compare_versions(latest_version, __version__) > 0
+    return {
+        "current_version": __version__,
+        "latest_version": latest_version,
+        "available": available,
+        "release_name": latest.get("name") or latest.get("tag_name"),
+        "release_url": latest.get("html_url") or RELEASES_URL,
+        "asset_name": asset.get("name") if asset else None,
+        "asset_download_url": asset.get("browser_download_url") if asset else None,
+        "packaged": bool(getattr(sys, "frozen", False)),
+        "message": update_message(available, latest_version, bool(asset)),
+    }
+
+
+async def latest_release() -> dict[str, Any] | None:
+    async with httpx.AsyncClient(timeout=10, follow_redirects=True) as client:
+        response = await client.get(RELEASES_API_URL)
+    response.raise_for_status()
+    releases = response.json()
+    if not isinstance(releases, list):
+        return None
+    candidates = [
+        release
+        for release in releases
+        if isinstance(release, dict) and not release.get("draft") and not release.get("prerelease")
+    ]
+    if not candidates:
+        candidates = [release for release in releases if isinstance(release, dict) and not release.get("draft")]
+    if not candidates:
+        return None
+    return max(candidates, key=lambda release: version_parts(str(release.get("tag_name") or release.get("name") or "0")))
+
+
+def release_asset(release: dict[str, Any], name: str) -> dict[str, Any] | None:
+    assets = release.get("assets") or []
+    if not isinstance(assets, list):
+        return None
+    for asset in assets:
+        if isinstance(asset, dict) and str(asset.get("name", "")).casefold() == name.casefold():
+            return asset
+    for asset in assets:
+        download_url = str(asset.get("browser_download_url", "")) if isinstance(asset, dict) else ""
+        if download_url.casefold().endswith(f"/{name.casefold()}"):
+            return asset
+    return None
+
+
+async def download_update_asset(url: str, version: str) -> Path:
+    updates_dir = Path(settings_payload()["app_data_dir"]) / "updates"
+    updates_dir.mkdir(parents=True, exist_ok=True)
+    path = updates_dir / f"TraderAI-{version}.exe"
+    async with httpx.AsyncClient(timeout=120, follow_redirects=True) as client:
+        async with client.stream("GET", url) as response:
+            response.raise_for_status()
+            with path.open("wb") as file:
+                async for chunk in response.aiter_bytes():
+                    file.write(chunk)
+    return path
+
+
+def write_update_script(source: Path, target: Path) -> Path:
+    updates_dir = Path(settings_payload()["app_data_dir"]) / "updates"
+    updates_dir.mkdir(parents=True, exist_ok=True)
+    script = updates_dir / "apply-update.ps1"
+    script.write_text(
+        "\n".join(
+            [
+                "param(",
+                "  [Parameter(Mandatory=$true)][int]$ProcessId,",
+                "  [Parameter(Mandatory=$true)][string]$Source,",
+                "  [Parameter(Mandatory=$true)][string]$Target",
+                ")",
+                "$ErrorActionPreference = 'Stop'",
+                "try { Wait-Process -Id $ProcessId -Timeout 60 -ErrorAction SilentlyContinue } catch {}",
+                "Start-Sleep -Seconds 1",
+                "Copy-Item -LiteralPath $Source -Destination $Target -Force",
+                "Start-Process -FilePath $Target",
+            ]
+        )
+        + "\n",
+        encoding="utf-8",
+    )
+    return script
+
+
+def exit_after_update_response() -> None:
+    time.sleep(1.5)
+    os._exit(0)
+
+
+def update_message(available: bool, latest_version: str | None, has_asset: bool) -> str:
+    if not latest_version:
+        return "Could not determine the latest release version."
+    if not available:
+        return f"TraderAI {__version__} is up to date."
+    if not has_asset:
+        return f"TraderAI {latest_version} is available, but the release has no {UPDATE_ASSET_NAME} asset."
+    return f"TraderAI {latest_version} is available."
+
+
+def normalize_version(value: str) -> str | None:
+    text = value.strip()
+    if text.startswith("v"):
+        text = text[1:]
+    parts = text.split(".")
+    if len(parts) < 2:
+        return None
+    return text
+
+
+def compare_versions(left: str, right: str) -> int:
+    left_parts = version_parts(left)
+    right_parts = version_parts(right)
+    max_len = max(len(left_parts), len(right_parts))
+    left_parts.extend([0] * (max_len - len(left_parts)))
+    right_parts.extend([0] * (max_len - len(right_parts)))
+    return (left_parts > right_parts) - (left_parts < right_parts)
+
+
+def version_parts(version: str) -> list[int]:
+    text = normalize_version(version) or "0"
+    core = text.replace("-", ".").replace("+", ".").split(".")
+    parts: list[int] = []
+    for item in core:
+        digits = ""
+        for char in item:
+            if not char.isdigit():
+                break
+            digits += char
+        parts.append(int(digits or 0))
+    return parts
+
+
+app = create_app()

traderai/uex_client.py

@@ -0,0 +1,78 @@
+from __future__ import annotations
+
+from typing import Any
+
+import httpx
+
+
+class UEXError(RuntimeError):
+    pass
+
+
+class UEXClient:
+    def __init__(self, base_url: str, secret_key: str | None = None, bearer_token: str | None = None) -> None:
+        self.base_url = base_url.rstrip("/")
+        self.secret_key = secret_key
+        self.bearer_token = bearer_token
+
+    def _headers(self, authenticated: bool = False) -> dict[str, str]:
+        headers = {"Accept": "application/json"}
+        if authenticated:
+            if not self.secret_key and not self.bearer_token:
+                raise UEXError("UEX_SECRET_KEY or UEX_BEARER_TOKEN is required for this action.")
+            if self.secret_key:
+                headers["secret-key"] = self.secret_key
+            if self.bearer_token:
+                headers["Authorization"] = f"Bearer {self.bearer_token}"
+        return headers
+
+    async def get(self, path: str, params: dict[str, Any] | None = None, authenticated: bool = False) -> dict[str, Any]:
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.get(
+                f"{self.base_url}/{path.strip('/')}/",
+                params={k: v for k, v in (params or {}).items() if v is not None},
+                headers=self._headers(authenticated),
+            )
+        return self._handle_response(response)
+
+    async def get_user(self, username: str | None = None, authenticated: bool = False) -> dict[str, Any]:
+        body = await self.get("user", {"username": username}, authenticated=authenticated)
+        data = body.get("data")
+        if isinstance(data, list):
+            data = data[0] if data else None
+        return {"status": body.get("status"), "user": data}
+
+    async def get_user_notifications(self) -> dict[str, Any]:
+        body = await self.get("user_notifications", authenticated=True)
+        data = body.get("data") or []
+        if isinstance(data, dict):
+            data = [data]
+        return {"status": body.get("status"), "notifications": data}
+
+    async def post(self, path: str, payload: dict[str, Any], authenticated: bool = True) -> dict[str, Any]:
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.post(
+                f"{self.base_url}/{path.strip('/')}/",
+                json=payload,
+                headers=self._headers(authenticated),
+            )
+        return self._handle_response(response)
+
+    async def delete(self, path: str, params: dict[str, Any] | None = None, authenticated: bool = True) -> dict[str, Any]:
+        async with httpx.AsyncClient(timeout=30) as client:
+            response = await client.delete(
+                f"{self.base_url}/{path.strip('/')}/",
+                params={k: v for k, v in (params or {}).items() if v is not None},
+                headers=self._headers(authenticated),
+            )
+        return self._handle_response(response)
+
+    @staticmethod
+    def _handle_response(response: httpx.Response) -> dict[str, Any]:
+        try:
+            body = response.json()
+        except ValueError as exc:
+            raise UEXError(f"UEX returned non-JSON response: HTTP {response.status_code}") from exc
+        if response.status_code >= 400:
+            raise UEXError(f"UEX HTTP {response.status_code}: {body}")
+        return body

traderai/version.py

@@ -0,0 +1,10 @@
+from __future__ import annotations
+
+__version__ = "0.0.2"
+
+RELEASES_URL = "https://git.hudsonriggs.systems/LambdaBankingConglomerate/TraderAI/releases"
+RELEASES_API_URL = "https://git.hudsonriggs.systems/api/v1/repos/LambdaBankingConglomerate/TraderAI/releases"
+
+
+
+

web/app.js

@@ -0,0 +1,963 @@
+const form = document.getElementById("chat-form");
+const input = document.getElementById("message-input");
+const messages = document.getElementById("messages");
+const statusEl = document.getElementById("status");
+const pendingEl = document.getElementById("pending-actions");
+const warningEl = document.getElementById("warning");
+const memoryInspectorEl = document.getElementById("memory-inspector");
+const memoryRefreshButton = document.getElementById("memory-refresh");
+const memoryClearButton = document.getElementById("memory-clear");
+const configForm = document.getElementById("config-form");
+const configRefreshButton = document.getElementById("config-refresh");
+const configStatusEl = document.getElementById("config-status");
+const configPathsEl = document.getElementById("config-paths");
+const settingsToggle = document.getElementById("settings-toggle");
+const memoryToggle = document.getElementById("memory-toggle");
+const ollamaToggle = document.getElementById("ollama-toggle");
+const settingsPanel = document.getElementById("settings-panel");
+const memoryPanel = document.getElementById("memory-panel");
+const ollamaPanel = document.getElementById("ollama-panel");
+const ollamaForm = document.getElementById("ollama-config-form");
+const ollamaRefreshButton = document.getElementById("ollama-refresh");
+const ollamaDownloadButton = document.getElementById("ollama-download");
+const ollamaInstallButton = document.getElementById("ollama-install");
+const ollamaLaunchButton = document.getElementById("ollama-launch");
+const ollamaPullButton = document.getElementById("ollama-pull");
+const ollamaStatusEl = document.getElementById("ollama-status");
+const ollamaMessageEl = document.getElementById("ollama-message");
+const updateCheckButton = document.getElementById("update-check");
+const updateInstallButton = document.getElementById("update-install");
+const updateOpenReleasesButton = document.getElementById("update-open-releases");
+const updateStatusEl = document.getElementById("update-status");
+
+let ollamaOnline = true;
+let latestUpdate = null;
+
+if (window.lucide) {
+  window.lucide.createIcons();
+}
+
+function addMessage(role, text) {
+  const node = document.createElement("div");
+  node.className = `message ${role}`;
+  setMessageMarkdown(node, text);
+  messages.appendChild(node);
+  messages.scrollTop = messages.scrollHeight;
+  return node;
+}
+
+function setMessageMarkdown(node, text) {
+  const body = node.querySelector(".message-body") || node;
+  body.innerHTML = renderMarkdown(text);
+}
+
+function setMessageActivity(node, text, active = false) {
+  const activity = node.querySelector(".message-activity");
+  if (!activity) return;
+  if (text) appendThinkingStep(node, reasoningSummaryForStatus(text), { fallback: true });
+  const phase = activity.querySelector(".message-phase");
+  phase.innerHTML = "";
+  if (text) {
+    const label = document.createElement("span");
+    label.textContent = text;
+    phase.appendChild(label);
+  }
+  if (active) {
+    const dots = document.createElement("span");
+    dots.className = "working-dots";
+    dots.innerHTML = "<i></i><i></i><i></i>";
+    phase.appendChild(dots);
+  }
+}
+
+function setMessageMetrics(node, metrics) {
+  const metricsEl = node.querySelector(".message-metrics");
+  if (!metricsEl) return;
+  metricsEl.textContent = metrics || "";
+}
+
+function appendThinkingStep(node, text, options = {}) {
+  const steps = node.querySelector(".thinking-steps");
+  if (!steps || !text) return;
+  const previous = steps.lastElementChild?.textContent;
+  if (previous === text) return;
+  const item = document.createElement("li");
+  if (options.fallback) item.dataset.fallback = "true";
+  item.textContent = text;
+  steps.appendChild(item);
+}
+
+function appendThinkingText(node, text) {
+  const steps = node.querySelector(".thinking-steps");
+  if (!steps || !text) return;
+  node.querySelectorAll(".thinking-steps [data-fallback='true']").forEach((item) => item.remove());
+  node.dataset.hasModelThinking = "true";
+  let item = steps.querySelector(".thinking-raw-step");
+  if (!item) {
+    item = document.createElement("li");
+    item.className = "thinking-raw-step";
+    steps.appendChild(item);
+  }
+  item.textContent += text;
+}
+
+function createThinkTagParser(node) {
+  let buffer = "";
+  let inThinking = false;
+
+  const partialTagLength = (text) => {
+    const lower = text.toLowerCase();
+    const tags = ["<think>", "</think>"];
+    for (const tag of tags) {
+      for (let length = tag.length - 1; length > 0; length -= 1) {
+        if (lower.endsWith(tag.slice(0, length))) return length;
+      }
+    }
+    return 0;
+  };
+
+  const consume = (content, flush = false) => {
+    buffer += content;
+    let visible = "";
+
+    while (buffer) {
+      const lower = buffer.toLowerCase();
+      if (inThinking) {
+        const closeIndex = lower.indexOf("</think>");
+        if (closeIndex === -1) {
+          if (flush) {
+            appendThinkingText(node, buffer);
+            buffer = "";
+          } else {
+            const keep = partialTagLength(buffer);
+            appendThinkingText(node, buffer.slice(0, buffer.length - keep));
+            buffer = buffer.slice(buffer.length - keep);
+          }
+          break;
+        }
+        appendThinkingText(node, buffer.slice(0, closeIndex));
+        buffer = buffer.slice(closeIndex + "</think>".length);
+        inThinking = false;
+        continue;
+      }
+
+      const openIndex = lower.indexOf("<think>");
+      if (openIndex === -1) {
+        const keep = flush ? 0 : partialTagLength(buffer);
+        visible += buffer.slice(0, buffer.length - keep);
+        buffer = buffer.slice(buffer.length - keep);
+        break;
+      }
+
+      visible += buffer.slice(0, openIndex);
+      buffer = buffer.slice(openIndex + "<think>".length);
+      inThinking = true;
+    }
+
+    return visible;
+  };
+
+  return {
+    consume,
+    flush: () => consume("", true),
+  };
+}
+
+function reasoningSummaryForStatus(text) {
+  const summaries = {
+    Thinking: "Reading your request and deciding whether I need current UEX data, memory, or a draft action before answering.",
+    "Searching UEX listings": "Checking current UEX marketplace listings so the answer is grounded in live item data instead of stale memory.",
+    "Fetching listing details": "Opening the specific listing details to avoid guessing about price, seller, quantity, or status.",
+    "Checking negotiations": "Looking through active negotiations because replies and offers can change what the next move should be.",
+    "Reading negotiation messages": "Reading the negotiation thread so any drafted reply matches the actual conversation.",
+    "Drafting message for approval": "Preparing the exact message as a pending action because marketplace writes need your approval first.",
+    "Drafting listing for approval": "Preparing the listing payload as a pending action so you can review it before anything is posted.",
+    "Checking UEX notifications": "Checking notifications for fresh replies or alerts that could change the recommendation.",
+    "Writing response": "Turning the gathered context into a concise response with the relevant details and next action.",
+  };
+  if (summaries[text]) return summaries[text];
+  if (text.startsWith("Running ")) {
+    return `Using ${text.replace(/^Running\s+/, "")} to gather the missing context before answering.`;
+  }
+  return text;
+}
+
+function finishThinking(node) {
+  const thinking = node.querySelector(".thinking-log");
+  const label = node.querySelector(".thinking-summary-label");
+  if (!thinking || !label) return;
+  const startedAt = Number(thinking.dataset.startedAt || Date.now());
+  const elapsedSeconds = Math.max(1, Math.round((Date.now() - startedAt) / 1000));
+  label.textContent = `Thought for ${elapsedSeconds}s`;
+  thinking.classList.remove("thinking-active");
+}
+
+function ensureStreamingChrome(node) {
+  if (node.querySelector(".message-activity")) return;
+  node.innerHTML = "";
+  const activity = document.createElement("div");
+  activity.className = "message-activity";
+  const phase = document.createElement("span");
+  phase.className = "message-phase";
+  const metrics = document.createElement("span");
+  metrics.className = "message-metrics";
+  const thinking = document.createElement("details");
+  thinking.className = "thinking-log";
+  thinking.classList.add("thinking-active");
+  thinking.dataset.startedAt = String(Date.now());
+  const thinkingSummary = document.createElement("summary");
+  const thinkingLabel = document.createElement("span");
+  thinkingLabel.className = "thinking-summary-label";
+  thinkingLabel.textContent = "Thinking...";
+  const thinkingSteps = document.createElement("ol");
+  thinkingSteps.className = "thinking-steps";
+  const body = document.createElement("div");
+  body.className = "message-body";
+  activity.append(phase, metrics);
+  thinkingSummary.appendChild(thinkingLabel);
+  thinking.append(thinkingSummary, thinkingSteps);
+  node.append(activity, thinking, body);
+}
+
+function renderMarkdown(text) {
+  const lines = text.replace(/\r\n/g, "\n").split(/\n/);
+  const output = [];
+  let inList = false;
+  let inOrderedList = false;
+  let inCode = false;
+  let codeLines = [];
+
+  const closeLists = () => {
+    if (inList) {
+      output.push("</ul>");
+      inList = false;
+    }
+    if (inOrderedList) {
+      output.push("</ol>");
+      inOrderedList = false;
+    }
+  };
+
+  const flushCode = () => {
+    output.push(`<pre><code>${escapeHtml(codeLines.join("\n"))}</code></pre>`);
+    codeLines = [];
+    inCode = false;
+  };
+
+  const isTableAt = (index) => {
+    if (index + 1 >= lines.length) return false;
+    return isTableRow(lines[index]) && isTableDivider(lines[index + 1]);
+  };
+
+  for (let index = 0; index < lines.length; index += 1) {
+    const line = lines[index];
+    const trimmed = line.trim();
+
+    if (/^```/.test(trimmed)) {
+      if (inCode) {
+        flushCode();
+      } else {
+        closeLists();
+        inCode = true;
+      }
+      continue;
+    }
+
+    if (inCode) {
+      codeLines.push(line);
+      continue;
+    }
+
+    if (isTableAt(index)) {
+      closeLists();
+      const headers = splitTableRow(lines[index]);
+      const aligns = splitTableRow(lines[index + 1]).map((cell) => tableAlignment(cell));
+      const rows = [];
+      index += 2;
+      while (index < lines.length && isTableRow(lines[index])) {
+        rows.push(splitTableRow(lines[index]));
+        index += 1;
+      }
+      index -= 1;
+      output.push(renderTable(headers, aligns, rows));
+      continue;
+    }
+
+    const unorderedItem = line.match(/^(\s*)[-*+]\s+(.+)$/);
+    if (unorderedItem) {
+      if (inOrderedList) {
+        output.push("</ol>");
+        inOrderedList = false;
+      }
+      if (!inList) {
+        output.push("<ul>");
+        inList = true;
+      }
+      const nestedClass = unorderedItem[1].length >= 2 ? ' class="nested"' : "";
+      output.push(`<li${nestedClass}>${inlineMarkdown(unorderedItem[2])}</li>`);
+      continue;
+    }
+
+    const orderedItem = line.match(/^(\s*)\d+\.\s+(.+)$/);
+    if (orderedItem) {
+      if (inList) {
+        output.push("</ul>");
+        inList = false;
+      }
+      if (!inOrderedList) {
+        output.push("<ol>");
+        inOrderedList = true;
+      }
+      const nestedClass = orderedItem[1].length >= 2 ? ' class="nested"' : "";
+      output.push(`<li${nestedClass}>${inlineMarkdown(orderedItem[2])}</li>`);
+      continue;
+    }
+
+    closeLists();
+
+    if (/^>\s?/.test(trimmed)) {
+      output.push(`<blockquote>${inlineMarkdown(trimmed.replace(/^>\s?/, ""))}</blockquote>`);
+    } else if (/^---+$/.test(trimmed)) {
+      output.push("<hr>");
+    } else if (/^#{1,6}\s+/.test(trimmed)) {
+      const level = Math.min(4, trimmed.match(/^#+/)[0].length + 2);
+      output.push(`<h${level}>${inlineMarkdown(trimmed.replace(/^#{1,6}\s+/, ""))}</h${level}>`);
+    } else if (trimmed) {
+      output.push(`<p>${inlineMarkdown(line)}</p>`);
+    } else {
+      output.push("<br>");
+    }
+  }
+
+  if (inCode) flushCode();
+  closeLists();
+  return output.join("");
+}
+
+function inlineMarkdown(text) {
+  return escapeHtml(text)
+    .replace(/`([^`]+)`/g, "<code>$1</code>")
+    .replace(/\*\*(.+?)\*\*/g, "<strong>$1</strong>")
+    .replace(/\*([^*]+)\*/g, "<em>$1</em>")
+    .replace(/\[([^\]]+)\]\((https?:\/\/[^)\s]+)\)/g, '<a href="$2" target="_blank" rel="noreferrer">$1</a>');
+}
+
+function isTableRow(line) {
+  const trimmed = line.trim();
+  return trimmed.includes("|") && /^\|?.+\|.+\|?$/.test(trimmed);
+}
+
+function isTableDivider(line) {
+  return splitTableRow(line).every((cell) => /^:?-{3,}:?$/.test(cell.trim()));
+}
+
+function splitTableRow(line) {
+  return line
+    .trim()
+    .replace(/^\|/, "")
+    .replace(/\|$/, "")
+    .split("|")
+    .map((cell) => cell.trim());
+}
+
+function tableAlignment(cell) {
+  const trimmed = cell.trim();
+  if (trimmed.startsWith(":") && trimmed.endsWith(":")) return "center";
+  if (trimmed.endsWith(":")) return "right";
+  return "left";
+}
+
+function renderTable(headers, aligns, rows) {
+  const head = headers
+    .map((cell, index) => `<th style="text-align:${aligns[index] || "left"}">${inlineMarkdown(cell)}</th>`)
+    .join("");
+  const body = rows
+    .map((row) => {
+      const cells = headers
+        .map((_, index) => `<td style="text-align:${aligns[index] || "left"}">${inlineMarkdown(row[index] || "")}</td>`)
+        .join("");
+      return `<tr>${cells}</tr>`;
+    })
+    .join("");
+  return `<div class="table-wrap"><table><thead><tr>${head}</tr></thead><tbody>${body}</tbody></table></div>`;
+}
+
+function escapeHtml(text) {
+  return text
+    .replace(/&/g, "&amp;")
+    .replace(/</g, "&lt;")
+    .replace(/>/g, "&gt;")
+    .replace(/"/g, "&quot;")
+    .replace(/'/g, "&#039;");
+}
+
+function formatMetrics(event) {
+  const read = formatTokenMetric(event.reading_tokens, event.reading_tokens_per_second);
+  const wrote = formatTokenMetric(event.writing_tokens, event.writing_tokens_per_second);
+  return [read && `read ${read}`, wrote && `wrote ${wrote}`].filter(Boolean).join(" | ");
+}
+
+function formatTokenMetric(tokens, speed) {
+  if (!tokens) return "";
+  const speedText = typeof speed === "number" ? ` @ ${speed.toFixed(1)}/s` : "";
+  return `${tokens} tok${speedText}`;
+}
+
+function setWarning(text) {
+  warningEl.hidden = !text;
+  warningEl.textContent = text || "";
+}
+
+function fetchErrorMessage(error) {
+  if (error instanceof TypeError && /fetch/i.test(error.message)) {
+    return "TraderAI backend is not reachable. Close this app window and launch TraderAI.exe again.";
+  }
+  return error.message;
+}
+
+const configFieldIds = {
+  uex_base_url: "config-uex-base-url",
+  uex_secret_key: "config-uex-secret-key",
+  uex_bearer_token: "config-uex-bearer-token",
+  traderai_user_name: "config-traderai-user-name",
+  traderai_memory_path: "config-traderai-memory-path",
+  uex_notification_poll_seconds: "config-uex-notification-poll-seconds",
+  require_write_approval: "config-require-write-approval",
+};
+
+const ollamaFieldIds = {
+  ollama_base_url: "ollama-base-url",
+  ollama_model: "ollama-model",
+  ollama_num_ctx: "ollama-num-ctx",
+};
+
+async function refreshConfig() {
+  try {
+    const response = await fetch("/api/config");
+    const config = await response.json();
+    renderConfig(config);
+  } catch (error) {
+    configStatusEl.textContent = `Config load failed: ${fetchErrorMessage(error)}`;
+  }
+}
+
+function renderConfig(config) {
+  const values = config.values || {};
+  const secretsConfigured = config.secrets_configured || {};
+  for (const [key, id] of Object.entries(configFieldIds)) {
+    const field = document.getElementById(id);
+    if (!field) continue;
+    if (field.type === "checkbox") {
+      field.checked = Boolean(values[key]);
+    } else if (field.type === "password") {
+      field.value = "";
+      field.placeholder = secretsConfigured[key] ? "Configured" : "";
+    } else {
+      field.value = values[key] ?? "";
+    }
+  }
+  for (const [key, id] of Object.entries(ollamaFieldIds)) {
+    const field = document.getElementById(id);
+    if (!field) continue;
+    field.value = values[key] ?? "";
+  }
+  configPathsEl.textContent = `App data: ${config.app_data_dir}\nConfig: ${config.config_path}\nLog: ${config.log_path}\nEdge profile: ${config.edge_profile_dir}`;
+  configStatusEl.textContent = "";
+}
+
+async function saveConfig(event) {
+  event.preventDefault();
+  const values = {};
+  for (const [key, id] of Object.entries(configFieldIds)) {
+    const field = document.getElementById(id);
+    if (!field) continue;
+    values[key] = field.type === "checkbox" ? field.checked : field.value;
+  }
+  configStatusEl.textContent = "Saving";
+  try {
+    const response = await fetch("/api/config", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ values }),
+    });
+    const result = await response.json();
+    renderConfig(result);
+    configStatusEl.textContent = result.message || "Saved";
+    addMessage("assistant", "Config saved. Restart TraderAI for the new settings to fully apply.");
+  } catch (error) {
+    configStatusEl.textContent = `Config save failed: ${fetchErrorMessage(error)}`;
+  }
+}
+
+async function saveOllamaConfig(event) {
+  event.preventDefault();
+  const values = {};
+  for (const [key, id] of Object.entries(ollamaFieldIds)) {
+    const field = document.getElementById(id);
+    if (!field) continue;
+    values[key] = field.value;
+  }
+  setOllamaMessage("Saving Ollama config");
+  try {
+    const response = await fetch("/api/config", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ values }),
+    });
+    const result = await response.json();
+    renderConfig(result);
+    setOllamaMessage(result.message || "Saved");
+    await refreshOllamaStatus();
+  } catch (error) {
+    setOllamaMessage(`Ollama config save failed: ${fetchErrorMessage(error)}`);
+  }
+}
+
+async function refreshOllamaStatus() {
+  if (!ollamaStatusEl) return;
+  ollamaStatusEl.textContent = "Checking Ollama";
+  try {
+    const response = await fetch("/api/ollama/status");
+    const status = await response.json();
+    renderOllamaStatus(status);
+  } catch (error) {
+    ollamaStatusEl.textContent = `Ollama status failed: ${error.message}`;
+  }
+}
+
+function renderOllamaStatus(status) {
+  if (!ollamaStatusEl) return;
+  const models = status.models?.length ? status.models.join(", ") : "None detected";
+  const pillClass = status.installed && status.running && status.model_available ? "status-pill" : "status-pill warning";
+  ollamaStatusEl.innerHTML = `
+    <div class="${pillClass}">${escapeHtml(status.message || "Unknown")}</div>
+    <div class="ollama-status-grid">
+      ${ollamaStatusItem("Installed", status.installed ? "Yes" : "No")}
+      ${ollamaStatusItem("Running", status.running ? "Yes" : "No")}
+      ${ollamaStatusItem("Model", status.configured_model || "")}
+      ${ollamaStatusItem("Pulled", status.model_available ? "Yes" : "No")}
+      ${ollamaStatusItem("URL", status.base_url || "")}
+      ${ollamaStatusItem("Auto Install", status.can_auto_install ? "Available" : "Unavailable")}
+    </div>
+    ${ollamaStatusItem("Installed Models", models)}
+    ${status.detail ? ollamaStatusItem("Detail", status.detail) : ""}
+  `;
+  if (ollamaInstallButton) ollamaInstallButton.disabled = Boolean(status.installed);
+  if (ollamaLaunchButton) ollamaLaunchButton.disabled = !status.installed || Boolean(status.running);
+  if (ollamaPullButton) ollamaPullButton.disabled = !status.running || Boolean(status.model_available);
+}
+
+function ollamaStatusItem(label, value) {
+  return `<div class="ollama-status-item"><strong>${escapeHtml(label)}</strong><span>${escapeHtml(String(value ?? ""))}</span></div>`;
+}
+
+function setOllamaMessage(message) {
+  if (ollamaMessageEl) ollamaMessageEl.textContent = message || "";
+}
+
+async function postOllamaAction(endpoint, options = {}) {
+  setOllamaMessage("Working");
+  try {
+    const response = await fetch(endpoint, {
+      method: "POST",
+      headers: options.body ? { "Content-Type": "application/json" } : undefined,
+      body: options.body ? JSON.stringify(options.body) : undefined,
+    });
+    const result = await response.json();
+    if (!response.ok) throw new Error(result.detail || `HTTP ${response.status}`);
+    setOllamaMessage(result.message || "Done");
+    await refreshOllamaStatus();
+  } catch (error) {
+    setOllamaMessage(error.message);
+  }
+}
+
+function configuredOllamaModel() {
+  return document.getElementById("ollama-model")?.value || "";
+}
+
+async function checkForUpdate() {
+  if (!updateStatusEl) return;
+  updateStatusEl.textContent = "Checking releases";
+  try {
+    const response = await fetch("/api/update/check");
+    const result = await response.json();
+    latestUpdate = result;
+    renderUpdateStatus(result);
+  } catch (error) {
+    updateStatusEl.textContent = `Update check failed: ${error.message}`;
+    if (updateInstallButton) updateInstallButton.disabled = true;
+  }
+}
+
+function renderUpdateStatus(update) {
+  if (!updateStatusEl) return;
+  const lines = [
+    `Current: ${update.current_version || "unknown"}`,
+    `Latest: ${update.latest_version || "unknown"}`,
+    update.message || "",
+  ].filter(Boolean);
+  if (update.available && !update.asset_download_url) {
+    lines.push("The release needs a TraderAI.exe attachment before the app can self-update.");
+  }
+  if (update.available && update.asset_download_url && !update.packaged) {
+    lines.push("Self-update runs from the packaged desktop exe.");
+  }
+  updateStatusEl.textContent = lines.join("\n");
+  if (updateInstallButton) {
+    updateInstallButton.disabled = !update.available || !update.asset_download_url || !update.packaged;
+  }
+}
+
+async function installUpdate() {
+  if (!updateStatusEl) return;
+  updateStatusEl.textContent = "Downloading update";
+  try {
+    const response = await fetch("/api/update/install", { method: "POST" });
+    const result = await response.json();
+    latestUpdate = result;
+    renderUpdateStatus(result);
+  } catch (error) {
+    updateStatusEl.textContent = `Update failed: ${error.message}`;
+  }
+}
+
+function openReleasesPage() {
+  const url = latestUpdate?.release_url || "https://git.hudsonriggs.systems/LambdaBankingConglomerate/TraderAI/releases";
+  window.open(url, "_blank", "noreferrer");
+}
+
+function toggleSidebarPanel(panelName) {
+  const panels = {
+    settings: { panel: settingsPanel, button: settingsToggle },
+    memory: { panel: memoryPanel, button: memoryToggle },
+    ollama: { panel: ollamaPanel, button: ollamaToggle },
+  };
+  const target = panels[panelName];
+  if (!target?.panel || !target?.button) return;
+  const shouldOpen = target.panel.hidden;
+  for (const item of Object.values(panels)) {
+    if (!item.panel || !item.button) continue;
+    item.panel.hidden = true;
+    item.button.classList.remove("active");
+    item.button.setAttribute("aria-expanded", "false");
+  }
+  if (shouldOpen) {
+    target.panel.hidden = false;
+    target.button.classList.add("active");
+    target.button.setAttribute("aria-expanded", "true");
+    if (panelName === "settings") {
+      refreshConfig();
+      checkForUpdate();
+    }
+    if (panelName === "memory") refreshMemory();
+    if (panelName === "ollama") {
+      refreshConfig();
+      refreshOllamaStatus();
+    }
+  }
+}
+
+async function checkHealth() {
+  try {
+    const response = await fetch("/api/health");
+    const result = await response.json();
+    const health = result.ollama || {};
+    ollamaOnline = Boolean(health.online);
+    if (!ollamaOnline) {
+      statusEl.textContent = "Offline";
+      setWarning(health.message || "Ollama is offline. Start Ollama before chatting.");
+      return false;
+    }
+    if (health.model_available === false) {
+      setWarning(`Ollama is online, but model "${health.model}" is not pulled. Run: ollama pull ${health.model}`);
+    } else {
+      setWarning("");
+    }
+    statusEl.textContent = "Ready";
+    return true;
+  } catch (error) {
+    ollamaOnline = false;
+    statusEl.textContent = "Offline";
+    setWarning(`Could not check Ollama health: ${error.message}`);
+    return false;
+  }
+}
+
+function renderPending(actions) {
+  pendingEl.innerHTML = "";
+  if (!actions.length) {
+    pendingEl.className = "pending-empty";
+    pendingEl.textContent = "No pending actions";
+    return;
+  }
+  pendingEl.className = "";
+  for (const action of actions) {
+    const card = document.createElement("div");
+    card.className = "pending-card";
+    const title = document.createElement("strong");
+    title.textContent = action.label;
+    const endpoint = document.createElement("p");
+    endpoint.className = "muted";
+    endpoint.textContent = action.endpoint;
+    const payload = document.createElement("pre");
+    payload.textContent = JSON.stringify(action.payload, null, 2);
+    const approve = document.createElement("button");
+    approve.textContent = "Approve";
+    approve.addEventListener("click", () => approveAction(action.id));
+    const decline = document.createElement("button");
+    decline.className = "decline-button";
+    decline.textContent = "Decline";
+    decline.addEventListener("click", () => declineAction(action.id));
+    const controls = document.createElement("div");
+    controls.className = "pending-controls";
+    controls.append(decline, approve);
+    card.append(title, endpoint, payload, controls);
+    pendingEl.appendChild(card);
+  }
+}
+
+async function approveAction(id) {
+  statusEl.textContent = "Sending";
+  try {
+    const response = await fetch(`/api/approve/${id}`, { method: "POST" });
+    const result = await response.json();
+    addMessage("assistant", `Approval result:\n${JSON.stringify(result, null, 2)}`);
+    await refreshPending();
+  } catch (error) {
+    addMessage("assistant", `Approval failed: ${error.message}`);
+  } finally {
+    statusEl.textContent = "Ready";
+  }
+}
+
+async function declineAction(id) {
+  statusEl.textContent = "Declining";
+  try {
+    const response = await fetch(`/api/decline/${id}`, { method: "POST" });
+    const result = await response.json();
+    if (result.error) {
+      addMessage("assistant warning-message", `Decline failed: ${result.error}`);
+    } else {
+      addMessage("assistant", `Declined pending action: ${result.pending_action?.label || id}`);
+    }
+    await refreshPending();
+  } catch (error) {
+    addMessage("assistant warning-message", `Decline failed: ${error.message}`);
+  } finally {
+    statusEl.textContent = "Ready";
+  }
+}
+
+async function refreshPending() {
+  const response = await fetch("/api/pending-actions");
+  const result = await response.json();
+  renderPending(result.pending_actions || []);
+}
+
+function renderMemory(data) {
+  memoryInspectorEl.innerHTML = "";
+  const counts = document.createElement("div");
+  counts.className = "memory-counts";
+  counts.textContent = `${data.memories.length} memories | ${data.conversations.length} chat rows | ${data.profile.length} profile keys | ${data.scheduled_jobs.length} jobs`;
+  memoryInspectorEl.appendChild(counts);
+
+  const path = document.createElement("div");
+  path.className = "memory-path";
+  path.textContent = data.path;
+  memoryInspectorEl.appendChild(path);
+
+  memoryInspectorEl.appendChild(memoryGroup("Memories", data.memories, (item) => `${item.kind} (${item.importance})\n${item.content}`));
+  memoryInspectorEl.appendChild(memoryGroup("Profile", data.profile, (item) => `${item.key}\n${JSON.stringify(item.value, null, 2)}`));
+  memoryInspectorEl.appendChild(memoryGroup("Recent Chat", data.conversations, (item) => `${item.created_at} ${item.role}\n${item.content}`));
+  memoryInspectorEl.appendChild(memoryGroup("Wake Jobs", data.scheduled_jobs, (item) => `${item.id}\n${item.trigger_type}: ${item.trigger_value}\n${item.prompt}`));
+}
+
+function memoryGroup(title, items, formatter) {
+  const group = document.createElement("details");
+  group.className = "memory-group";
+  const summary = document.createElement("summary");
+  summary.textContent = `${title} (${items.length})`;
+  group.appendChild(summary);
+  if (!items.length) {
+    const empty = document.createElement("p");
+    empty.className = "muted";
+    empty.textContent = "Empty";
+    group.appendChild(empty);
+    return group;
+  }
+  for (const item of items.slice(0, 20)) {
+    const entry = document.createElement("pre");
+    entry.textContent = formatter(item);
+    group.appendChild(entry);
+  }
+  return group;
+}
+
+async function refreshMemory() {
+  try {
+    const response = await fetch("/api/memory?limit=50");
+    const data = await response.json();
+    renderMemory(data);
+  } catch (error) {
+    memoryInspectorEl.textContent = `Memory load failed: ${error.message}`;
+  }
+}
+
+async function clearMemory() {
+  const payload = {
+    include_memories: document.getElementById("clear-memories").checked,
+    include_conversations: document.getElementById("clear-conversations").checked,
+    include_profile: document.getElementById("clear-profile").checked,
+    include_jobs: document.getElementById("clear-jobs").checked,
+    include_outbox: document.getElementById("clear-outbox").checked,
+  };
+  if (!Object.values(payload).some(Boolean)) return;
+  const confirmed = window.confirm("Clear the selected TraderAI memory? This cannot be undone.");
+  if (!confirmed) return;
+  try {
+    const response = await fetch("/api/memory/clear", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify(payload),
+    });
+    const result = await response.json();
+    renderMemory(result.memory);
+    addMessage("assistant", `Memory cleared:\n${JSON.stringify(result.deleted, null, 2)}`);
+  } catch (error) {
+    addMessage("assistant warning-message", `Memory clear failed: ${error.message}`);
+  }
+}
+
+async function pollNotifications() {
+  try {
+    const response = await fetch("/api/notifications");
+    const result = await response.json();
+    for (const notification of result.notifications || []) {
+      addMessage("assistant", notification.content);
+    }
+  } catch {
+    // Notification polling should never interrupt chat.
+  }
+}
+
+form.addEventListener("submit", async (event) => {
+  event.preventDefault();
+  await sendMessage();
+});
+
+input.addEventListener("keydown", async (event) => {
+  if (event.key === "Enter" && !event.shiftKey) {
+    event.preventDefault();
+    await sendMessage();
+  }
+});
+
+memoryRefreshButton?.addEventListener("click", refreshMemory);
+memoryClearButton?.addEventListener("click", clearMemory);
+configRefreshButton?.addEventListener("click", refreshConfig);
+configForm?.addEventListener("submit", saveConfig);
+settingsToggle?.addEventListener("click", () => toggleSidebarPanel("settings"));
+memoryToggle?.addEventListener("click", () => toggleSidebarPanel("memory"));
+ollamaToggle?.addEventListener("click", () => toggleSidebarPanel("ollama"));
+ollamaForm?.addEventListener("submit", saveOllamaConfig);
+ollamaRefreshButton?.addEventListener("click", refreshOllamaStatus);
+ollamaDownloadButton?.addEventListener("click", () => postOllamaAction("/api/ollama/download"));
+ollamaInstallButton?.addEventListener("click", () => postOllamaAction("/api/ollama/install"));
+ollamaLaunchButton?.addEventListener("click", () => postOllamaAction("/api/ollama/launch"));
+ollamaPullButton?.addEventListener("click", () => postOllamaAction("/api/ollama/pull", { body: { model: configuredOllamaModel() } }));
+updateCheckButton?.addEventListener("click", checkForUpdate);
+updateInstallButton?.addEventListener("click", installUpdate);
+updateOpenReleasesButton?.addEventListener("click", openReleasesPage);
+
+async function sendMessage() {
+  const message = input.value.trim();
+  if (!message || input.disabled) return;
+  const healthy = await checkHealth();
+  if (!healthy) {
+    addMessage("assistant warning-message", "Ollama is offline. Start Ollama, then try again.");
+    return;
+  }
+  input.value = "";
+  input.disabled = true;
+  addMessage("user", message);
+  const assistantNode = addMessage("assistant streaming", "");
+  ensureStreamingChrome(assistantNode);
+  let assistantText = "";
+  const thinkParser = createThinkTagParser(assistantNode);
+  statusEl.textContent = "Working";
+  setMessageActivity(assistantNode, "Thinking", true);
+  setMessageMetrics(assistantNode, "");
+  try {
+    const response = await fetch("/api/chat/stream", {
+      method: "POST",
+      headers: { "Content-Type": "application/json" },
+      body: JSON.stringify({ message }),
+    });
+    if (!response.ok || !response.body) {
+      throw new Error(`HTTP ${response.status}`);
+    }
+    const reader = response.body.getReader();
+    const decoder = new TextDecoder();
+    let buffer = "";
+    while (true) {
+      const { value, done } = await reader.read();
+      if (done) break;
+      buffer += decoder.decode(value, { stream: true });
+      const events = buffer.split("\n\n");
+      buffer = events.pop() || "";
+      for (const rawEvent of events) {
+        const line = rawEvent.split("\n").find((entry) => entry.startsWith("data: "));
+        if (!line) continue;
+        const event = JSON.parse(line.slice(6));
+        if (event.type === "status") {
+          setMessageActivity(assistantNode, event.message, true);
+        } else if (event.type === "metrics") {
+          setMessageMetrics(assistantNode, formatMetrics(event));
+        } else if (event.type === "warning") {
+          setWarning(event.message);
+          assistantText += event.message;
+          setMessageMarkdown(assistantNode, assistantText);
+        } else if (event.type === "token") {
+          const visibleContent = thinkParser.consume(event.content);
+          if (visibleContent) {
+            assistantText += visibleContent;
+            setMessageMarkdown(assistantNode, assistantText);
+          }
+          messages.scrollTop = messages.scrollHeight;
+        } else if (event.type === "done") {
+          const visibleContent = thinkParser.flush();
+          if (visibleContent) {
+            assistantText += visibleContent;
+            setMessageMarkdown(assistantNode, assistantText);
+          }
+          renderPending(event.pending_actions || []);
+        }
+      }
+    }
+  } catch (error) {
+    const message = error.message.includes("503")
+      ? "Ollama is offline or unreachable. Start Ollama, then try again."
+      : `Chat failed: ${error.message}`;
+    setWarning(message);
+    setMessageMarkdown(assistantNode, message);
+  } finally {
+    assistantNode.classList.remove("streaming");
+    input.disabled = false;
+    input.focus();
+    statusEl.textContent = "Ready";
+    finishThinking(assistantNode);
+    setMessageActivity(assistantNode, "");
+  }
+}
+
+addMessage("assistant", "Tell me what to find or draft on UEX. I will ask for approval before sending anything.");
+refreshPending();
+refreshMemory();
+refreshConfig();
+refreshOllamaStatus();
+checkForUpdate();
+pollNotifications();
+checkHealth();
+setInterval(checkHealth, 30000);
+setInterval(pollNotifications, 15000);

web/art/ollama-icon.svg

@@ -0,0 +1 @@
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web/index.html

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+<!doctype html>
+<html lang="en">
+  <head>
+    <meta charset="utf-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1">
+    <title>TraderAI</title>
+    <link rel="icon" href="/static/art/LBC_Logo.ico" sizes="any">
+    <link rel="stylesheet" href="/static/styles.css">
+  </head>
+  <body>
+    <main class="shell">
+      <section class="workspace">
+        <header class="topbar">
+          <div class="brand-block">
+            <div class="logo-wrap" aria-hidden="true">
+              <img src="/static/art/LBC_Logo.png" alt="">
+            </div>
+            <div class="brand-copy">
+              <p class="eyebrow">Lambda Banking Conglomerate</p>
+              <h1>TraderAI</h1>
+              <p>Institutional marketplace intelligence for UEX operations</p>
+            </div>
+          </div>
+          <div class="status" id="status">Ready</div>
+        </header>
+        <div class="warning" id="warning" hidden></div>
+        <div class="messages" id="messages"></div>
+        <div class="composer-wrap">
+          <form class="composer" id="chat-form">
+            <textarea id="message-input" rows="2" placeholder="Search listings, draft a reply, prepare an offer..."></textarea>
+            <button type="submit">Send</button>
+          </form>
+        </div>
+      </section>
+      <aside class="actions">
+        <section class="side-section">
+          <h2>Pending Approval</h2>
+          <div id="pending-actions" class="pending-empty">No pending actions</div>
+        </section>
+        <section class="side-section sidebar-tools">
+          <div class="sidebar-tool-buttons" role="tablist" aria-label="Sidebar panels">
+            <button class="sidebar-tool-button" id="settings-toggle" type="button" aria-expanded="false" aria-controls="settings-panel" title="Settings">
+              <i data-lucide="settings" aria-hidden="true"></i>
+              <span>Settings</span>
+            </button>
+            <button class="sidebar-tool-button" id="memory-toggle" type="button" aria-expanded="false" aria-controls="memory-panel" title="Memory">
+              <i data-lucide="brain" aria-hidden="true"></i>
+              <span>Memory</span>
+            </button>
+            <button class="sidebar-tool-button" id="ollama-toggle" type="button" aria-expanded="false" aria-controls="ollama-panel" title="Ollama">
+              <img class="sidebar-tool-image" src="/static/art/ollama-icon.svg" alt="" onerror="this.remove();">
+              <i data-lucide="bot" aria-hidden="true"></i>
+              <span>Ollama</span>
+            </button>
+          </div>
+          <div class="sidebar-panel" id="settings-panel" hidden>
+            <div class="section-title-row">
+              <h2>Config</h2>
+              <button class="secondary small-button" id="config-refresh" type="button">Refresh</button>
+            </div>
+            <form class="config-form" id="config-form">
+              <label>UEX API URL<input id="config-uex-base-url" name="uex_base_url" type="text"></label>
+              <label>UEX Secret Key<input id="config-uex-secret-key" name="uex_secret_key" type="password" autocomplete="off"></label>
+              <label>UEX Bearer Token<input id="config-uex-bearer-token" name="uex_bearer_token" type="password" autocomplete="off"></label>
+              <label>UEX Username<input id="config-traderai-user-name" name="traderai_user_name" type="text"></label>
+              <label>Memory DB Path<input id="config-traderai-memory-path" name="traderai_memory_path" type="text"></label>
+              <label>Notification Poll Seconds<input id="config-uex-notification-poll-seconds" name="uex_notification_poll_seconds" type="number" min="15" step="15"></label>
+              <label class="config-check"><input id="config-require-write-approval" name="require_write_approval" type="checkbox"> Require write approval</label>
+              <div class="config-paths" id="config-paths"></div>
+              <button type="submit">Save Config</button>
+              <div class="config-status" id="config-status"></div>
+            </form>
+            <div class="update-box">
+              <div class="section-title-row">
+                <h2>Updates</h2>
+                <button class="secondary small-button" id="update-check" type="button">Check</button>
+              </div>
+              <div class="update-status" id="update-status"></div>
+              <div class="update-actions">
+                <button class="secondary small-button" id="update-open-releases" type="button">Releases</button>
+                <button class="small-button" id="update-install" type="button">Update</button>
+              </div>
+            </div>
+          </div>
+          <div class="sidebar-panel" id="memory-panel" hidden>
+            <div class="section-title-row">
+              <h2>Memory</h2>
+              <button class="secondary small-button" id="memory-refresh" type="button">Refresh</button>
+            </div>
+            <div class="memory-controls">
+              <label><input type="checkbox" id="clear-memories" checked> Memories</label>
+              <label><input type="checkbox" id="clear-conversations" checked> Chat</label>
+              <label><input type="checkbox" id="clear-outbox" checked> Notices</label>
+              <label><input type="checkbox" id="clear-profile"> Profile</label>
+              <label><input type="checkbox" id="clear-jobs"> Jobs</label>
+            </div>
+            <button class="danger-button" id="memory-clear" type="button">Clear Selected</button>
+            <div id="memory-inspector" class="memory-inspector"></div>
+          </div>
+          <div class="sidebar-panel" id="ollama-panel" hidden>
+            <div class="section-title-row">
+              <h2>Ollama</h2>
+              <button class="secondary small-button" id="ollama-refresh" type="button">Refresh</button>
+            </div>
+            <form class="config-form" id="ollama-config-form">
+              <label>Ollama URL<input id="ollama-base-url" name="ollama_base_url" type="text"></label>
+              <label>Model<input id="ollama-model" name="ollama_model" type="text"></label>
+              <label>Context Tokens<input id="ollama-num-ctx" name="ollama_num_ctx" type="number" min="1024" step="1024"></label>
+              <button type="submit">Save Ollama Config</button>
+            </form>
+            <div class="ollama-status" id="ollama-status"></div>
+            <div class="ollama-actions">
+              <button class="secondary small-button" id="ollama-download" type="button">Download</button>
+              <button class="secondary small-button" id="ollama-install" type="button">Auto Install</button>
+              <button class="secondary small-button" id="ollama-launch" type="button">Launch</button>
+              <button class="small-button" id="ollama-pull" type="button">Install Model</button>
+            </div>
+            <div class="config-status" id="ollama-message"></div>
+          </div>
+        </section>
+      </aside>
+    </main>
+    <script src="https://unpkg.com/lucide@0.562.0/dist/umd/lucide.min.js"></script>
+    <script src="/static/app.js"></script>
+  </body>
+</html>