path: root/docs/superpowers/plans/2026-08-09-external-providers.md

# External Cloud Providers Implementation Plan

> **For agentic workers:** REQUIRED SUB-SKILL: Use superpowers:subagent-driven-development (recommended) or superpowers:executing-plans to implement this plan task-by-task. Steps use checkbox (`- [ ]`) syntax for tracking.

**Goal:** Let llamachat use OpenAI-compatible cloud providers (together.ai, siliconflow) alongside the local llama.cpp router, with per-model metadata entered through a dialog and an approximate per-conversation cost shown beside the context meter.

**Architecture:** Providers become entries in a `[providers.*]` config table; the local router is one of them, named `local`, and a bare top-level `base_url` synthesizes it so existing configs keep working. Model ids are `provider:model`, except `local` which stays bare. Cloud models have no `presets.ini` entry, so context size, vision and prices come from a `models.ini` the app writes, prefilled from per-provider defaults. Token counts and the producing model move onto the `messages` table so cost survives reopening a conversation.

**Tech Stack:** Python 3.11+ standard library (`tomllib`, `configparser`, `subprocess`, `sqlite3`), `httpx` for HTTP, PySide6 for the dialog. No new dependencies.

**Spec:** `docs/superpowers/specs/2026-08-09-external-providers-design.md`

---

## Conventions for this codebase

Read this before Task 1. It is not optional context.

**Tests are not pytest.** `test_llamachat.py` is a single executable file of plain
functions. Each test ends with `print("ok  <short description>")`. Every test must
be registered by name in the `if __name__ == "__main__":` block at the bottom of the
file, in the order it should run. A test that is written but not registered never
runs, and the suite will still say "all checks passed".

Run the whole suite with:

```bash
./test_llamachat.py
```

There is no way to run a single test from the command line. To verify one test
fails or passes in isolation, run the suite and read that test's line. Adding a
temporary `if __name__` entry for just the new test is acceptable during a
red/green cycle but must be restored before committing.

**Every new source file needs the GPL header.** Copy it verbatim from the top of
`llamachat/config.py`, changing nothing but the docstring on the last line.

**Commits are GPG-signed automatically.** Do not pass `-c commit.gpgsign=false`.
Two git hooks scan for personal data and secrets; treat a rejection as correct.
Use `example.org`, fake keys like `sk-test-not-a-real-key`, and generic paths in
tests and fixtures. Never put a real API key anywhere, including a test.

**Style:** comments explain why, not what. Deliberate simplifications get a
`# ponytail:` comment naming the ceiling and the upgrade path. Match the
surrounding code's density.

---

## File Structure

**New files:**

| File | Responsibility |
| --- | --- |
| `llamachat/providers.py` | Parsing `[providers.*]`, splitting/joining model ids, filtering model lists, resolving API keys (`pass:`/`env:`/literal) with caching. No Qt, no HTTP. |
| `llamachat/models.py` | `models.ini` read/write, three-layer metadata resolution, cost arithmetic and formatting. No Qt, no HTTP. |
| `llamachat/modeldialog.py` | The Qt dialog for entering ctx size, vision and prices. Only file in this feature that imports PySide6. |

**Modified files:**

| File | Change |
| --- | --- |
| `llamachat/config.py` | Parse `[providers.*]`, synthesize `local` from bare `base_url`, add `models_path`. |
| `llamachat/backend.py` | `Client` gains `api_key` and sends `Authorization`. New `MultiClient` fans `models()` out across providers and routes requests by model id. |
| `llamachat/db.py` | Three nullable columns on `messages`, migration, and storing them. |
| `llamachat/ui.py` | Model list from `MultiClient`, metadata via `models.py` instead of `presets` alone, dialog triggers, cost label. |
| `test_llamachat.py` | New tests, each registered in the `__main__` block. |

**Dependency direction:** `providers.py` and `models.py` depend on nothing in the
project. `backend.py` imports `providers`. `ui.py` imports all three plus
`modeldialog`. Nothing imports `ui`.

---

## Task 1: Provider config parsing

**Files:**
- Create: `llamachat/providers.py`
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add to `test_llamachat.py`, after `test_config_defaults()`:

```python
def test_provider_parsing():
    """Providers come from [providers.*]; a bare base_url synthesizes local."""
    from llamachat import providers

    # A modern config with two providers.
    parsed = providers.parse(
        {
            "providers": {
                "local": {"base_url": "http://localhost:8181/"},
                "together": {
                    "base_url": "https://api.example.org",
                    "api_key": "env:TEST_KEY_NAME",
                    "filter": ["qwen", "deepseek"],
                    "ctx_size": 32768,
                    "price_in": 0.6,
                    "price_out": 0.9,
                },
            }
        }
    )
    assert set(parsed) == {"local", "together"}
    # Trailing slashes are stripped so URL joining stays predictable.
    assert parsed["local"].base_url == "http://localhost:8181"
    assert parsed["local"].api_key == ""
    assert parsed["together"].filter == ["qwen", "deepseek"]
    assert parsed["together"].ctx_size == 32768
    assert parsed["together"].price_in == 0.6
    assert parsed["together"].price_out == 0.9

    # An old config: bare base_url, no providers table at all.
    legacy = providers.parse({"base_url": "http://localhost:8181"})
    assert set(legacy) == {"local"}
    assert legacy["local"].base_url == "http://localhost:8181"

    # Both present: the explicit entry wins over the bare key.
    both = providers.parse(
        {
            "base_url": "http://ignored.example.org",
            "providers": {"local": {"base_url": "http://explicit.example.org"}},
        }
    )
    assert both["local"].base_url == "http://explicit.example.org"

    # A provider with no base_url is skipped rather than half-configured.
    broken = providers.parse(
        {"providers": {"local": {"base_url": "http://x.example.org"},
                       "bad": {"api_key": "literal"}}}
    )
    assert set(broken) == {"local"}

    # Unset numbers stay None so "unknown" is distinguishable from zero.
    assert parsed["local"].ctx_size is None
    assert parsed["local"].price_in is None

    # A [providers.local] that omits base_url inherits the bare one rather
    # than shadowing the local provider out of existence.
    partial = providers.parse(
        {
            "base_url": "http://localhost:8181",
            "providers": {"local": {"api_key": "env:SOME_VAR"}},
        }
    )
    assert set(partial) == {"local"}
    assert partial["local"].base_url == "http://localhost:8181"
    # The explicit entry's own fields survive the merge.
    assert partial["local"].api_key == "env:SOME_VAR"

    # A filter given as a bare string is one needle, not four.
    stringy = providers.parse(
        {"providers": {"p": {"base_url": "http://x.example.org",
                             "filter": "qwen"}}}
    )
    assert stringy["p"].filter == ["qwen"]
    print("ok  provider config parsing")
```

Register it in the `__main__` block immediately after `test_config_defaults()`:

```python
    test_config_defaults()
    test_provider_parsing()
```

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `ModuleNotFoundError: No module named 'llamachat.providers'`

- [ ] **Step 3: Write the implementation**

Create `llamachat/providers.py`. Copy the 14-line GPL header verbatim from the top
of `llamachat/config.py`, then:

```python
"""Provider definitions, model-id namespacing and API key resolution."""

import os
import subprocess
from dataclasses import dataclass, field

# The local llama.cpp router. Its models are shown and stored without a
# prefix, so an existing session pointing at a local model still resolves.
LOCAL = "local"

# A stuck pinentry must not freeze the worker thread forever.
KEY_TIMEOUT = 30


class KeyError_(Exception):
    """An api_key that could not be resolved, phrased for the user."""


@dataclass
class Provider:
    name: str
    base_url: str
    api_key: str = ""
    filter: list[str] = field(default_factory=list)
    # None rather than 0: unset must stay distinguishable from "zero".
    ctx_size: int | None = None
    vision: bool | None = None
    price_in: float | None = None
    price_out: float | None = None

    @property
    def is_local(self) -> bool:
        return self.name == LOCAL


def _number(raw, cast):
    if raw is None or raw == "":
        return None
    try:
        return cast(raw)
    except (TypeError, ValueError):
        return None


def parse(values: dict) -> dict[str, Provider]:
    """Build the provider table from already-loaded config values.

    Takes the raw dict rather than a path so config.py owns file reading and
    this stays testable without touching disk.
    """
    table = dict(values.get("providers") or {})

    # An old config has only a bare base_url. Fill it in as the local
    # provider's URL so nothing needs migrating, but never override an
    # explicit one. The test is the URL rather than the key: a
    # [providers.local] that only sets an api_key is adding detail to the
    # provider the user already has, not replacing it, and treating it as a
    # replacement would silently delete local entirely.
    bare = values.get("base_url")
    if bare and not (table.get(LOCAL) or {}).get("base_url"):
        table[LOCAL] = {**(table.get(LOCAL) or {}), "base_url": bare}

    out: dict[str, Provider] = {}
    for name, entry in table.items():
        entry = entry or {}
        base_url = str(entry.get("base_url") or "").rstrip("/")
        if not base_url:
            # ponytail: a provider with no URL is misconfigured, not a
            # partial one. Skipping beats inventing a default endpoint.
            continue
        # filter = "qwen" is an easy TOML slip for filter = ["qwen"], and
        # iterating the string would turn it into four single-character
        # needles that match nearly every model id.
        needles = entry.get("filter") or []
        if isinstance(needles, str):
            needles = [needles]
        vision = entry.get("vision")
        out[str(name)] = Provider(
            name=str(name),
            base_url=base_url,
            api_key=str(entry.get("api_key") or ""),
            filter=[str(f) for f in needles],
            ctx_size=_number(entry.get("ctx_size"), int),
            vision=None if vision is None else bool(vision),
            price_in=_number(entry.get("price_in"), float),
            price_out=_number(entry.get("price_out"), float),
        )
    return out
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including the line `ok  provider config parsing`

- [ ] **Step 5: Commit**

```bash
git add llamachat/providers.py test_llamachat.py
git commit -m "feat: parse provider definitions from config

Providers come from a [providers.*] table. A bare top-level base_url
synthesizes the local provider so existing configs keep working, and an
explicit [providers.local] wins over it. Unset numbers stay None so
'unknown' never collapses into zero.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 2: Model id namespacing and filtering

**Files:**
- Modify: `llamachat/providers.py`
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_provider_parsing()`:

```python
def test_model_ids_and_filtering():
    """Ids are provider:model, local stays bare, filters are substrings."""
    from llamachat import providers

    table = providers.parse(
        {
            "providers": {
                "local": {"base_url": "http://localhost:8181"},
                "together": {
                    "base_url": "https://api.example.org",
                    "filter": ["qwen", "deepseek"],
                },
                "unfiltered": {"base_url": "https://api2.example.org"},
            }
        }
    )

    # Local models carry no prefix, in the dropdown and in the database.
    assert providers.qualify("local", "gemma4") == "gemma4"
    assert providers.qualify("together", "Qwen/Qwen2.5") == "together:Qwen/Qwen2.5"

    # Splitting is the inverse, and only for providers that exist.
    assert providers.split("gemma4", table) == ("local", "gemma4")
    assert providers.split("together:Qwen/Qwen2.5", table) == (
        "together",
        "Qwen/Qwen2.5",
    )
    # An unknown prefix is part of the model name, not a provider. This is
    # what keeps a local model whose name contains a colon working.
    assert providers.split("weird:name", table) == ("local", "weird:name")
    # Only the first colon splits.
    assert providers.split("together:a:b", table) == ("together", "a:b")

    # Filtering is case-insensitive substring, any match wins.
    listed = [
        "Qwen/Qwen2.5-72B-Instruct-Turbo",
        "deepseek-ai/DeepSeek-V3",
        "meta-llama/Llama-3.3-70B",
    ]
    kept = providers.apply_filter(table["together"], listed)
    assert kept == [
        "Qwen/Qwen2.5-72B-Instruct-Turbo",
        "deepseek-ai/DeepSeek-V3",
    ]

    # No filter means everything.
    assert providers.apply_filter(table["unfiltered"], listed) == listed
    # The local provider is never filtered even if one is configured.
    table["local"].filter = ["nothing-matches-this"]
    assert providers.apply_filter(table["local"], listed) == listed
    # A filter matching nothing yields nothing, it does not fall back to all.
    table["together"].filter = ["zzz"]
    assert providers.apply_filter(table["together"], listed) == []
    print("ok  model ids and filtering")
```

Register it after `test_provider_parsing()` in the `__main__` block.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `AttributeError: module 'llamachat.providers' has no attribute 'qualify'`

- [ ] **Step 3: Write the implementation**

Append to `llamachat/providers.py`:

```python
def qualify(provider: str, model: str) -> str:
    """The stored, displayed id for one model. Local models stay bare."""
    if provider == LOCAL:
        return model
    return f"{provider}:{model}"


def split(model_id: str, table: dict[str, Provider]) -> tuple[str, str]:
    """Inverse of qualify, resolved against the configured providers.

    A prefix that is not a configured provider is treated as part of the
    model name, which keeps a bare local model containing a colon working.
    """
    prefix, sep, rest = model_id.partition(":")
    if sep and prefix in table and prefix != LOCAL:
        return prefix, rest
    return LOCAL, model_id


def apply_filter(provider: Provider, listed: list[str]) -> list[str]:
    """Keep models matching any of the provider's substrings.

    Case-insensitive, because provider ids capitalise inconsistently:
    "qwen" has to match "Qwen/Qwen2.5-72B-Instruct-Turbo".
    """
    if provider.is_local or not provider.filter:
        return list(listed)
    needles = [f.lower() for f in provider.filter if f]
    if not needles:
        return list(listed)
    return [m for m in listed if any(n in m.lower() for n in needles)]
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  model ids and filtering`

- [ ] **Step 5: Commit**

```bash
git add llamachat/providers.py test_llamachat.py
git commit -m "feat: namespace model ids by provider and filter model lists

Cloud models are addressed as provider:model; local ones stay bare so
existing sessions keep resolving. An unknown prefix is treated as part of
the model name rather than a provider. Filters are case-insensitive
substrings because provider ids capitalise inconsistently.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 3: API key resolution

**Files:**
- Modify: `llamachat/providers.py`
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_model_ids_and_filtering()`:

```python
def test_key_resolution():
    """api_key is prefix-dispatched, resolved lazily and cached."""
    from llamachat import providers

    resolver = providers.KeyResolver()

    # No key configured: no Authorization header, and nothing is run.
    empty = providers.Provider(name="local", base_url="http://x.example.org")
    assert resolver.resolve(empty) == ""

    # A literal key is used as-is.
    literal = providers.Provider(
        name="p", base_url="http://x.example.org", api_key="sk-test-not-a-real-key"
    )
    assert resolver.resolve(literal) == "sk-test-not-a-real-key"

    # env: reads the environment.
    os.environ["LLAMACHAT_TEST_KEY"] = "from-env"
    env = providers.Provider(
        name="e", base_url="http://x.example.org",
        api_key="env:LLAMACHAT_TEST_KEY",
    )
    assert resolver.resolve(env) == "from-env"
    del os.environ["LLAMACHAT_TEST_KEY"]

    # A missing env var is an error naming the provider, not a silent "".
    missing = providers.Provider(
        name="gone", base_url="http://x.example.org",
        api_key="env:LLAMACHAT_ABSENT_VAR",
    )
    try:
        resolver.resolve(missing)
        assert False, "a missing env var must raise"
    except providers.KeyError_ as exc:
        assert "gone" in str(exc)

    # pass: shells out. Substitute the runner rather than requiring gpg.
    calls = []

    def fake_run(cmd, timeout):
        calls.append((cmd, timeout))
        return "line-one\nline-two\n"

    passed = providers.Provider(
        name="together", base_url="http://x.example.org",
        api_key="pass:api/together",
    )
    cached = providers.KeyResolver(runner=fake_run)
    assert cached.resolve(passed) == "line-one"      # first line only
    assert calls[0][0] == ["pass", "show", "api/together"]
    assert calls[0][1] == providers.KEY_TIMEOUT

    # Cached: a second resolve must not shell out again.
    assert cached.resolve(passed) == "line-one"
    assert len(calls) == 1

    # A failing pass is reported, naming the provider.
    def boom(cmd, timeout):
        raise OSError("pass: entry not found")

    try:
        providers.KeyResolver(runner=boom).resolve(passed)
        assert False, "a failing pass must raise"
    except providers.KeyError_ as exc:
        assert "together" in str(exc)

    # Empty output is a failure too: an empty key would 401 confusingly.
    try:
        providers.KeyResolver(runner=lambda cmd, timeout: "  \n").resolve(passed)
        assert False, "empty pass output must raise"
    except providers.KeyError_:
        pass
    print("ok  api key resolution")
```

Register it after `test_model_ids_and_filtering()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `AttributeError: module 'llamachat.providers' has no attribute 'KeyResolver'`

- [ ] **Step 3: Write the implementation**

Append to `llamachat/providers.py`:

```python
def _run_pass(cmd: list[str], timeout: int) -> str:
    """Run `pass show NAME` and return its stdout."""
    result = subprocess.run(
        cmd, capture_output=True, text=True, timeout=timeout, check=True
    )
    return result.stdout


class KeyResolver:
    """Resolves api_key fields, lazily and once per process.

    Lazy matters: `pass` needs the GPG key, so a session that only touches
    local models must never trigger a pinentry. Resolved values stay in
    memory and are never written anywhere.
    """

    def __init__(self, runner=_run_pass):
        self._runner = runner
        self._cache: dict[str, str] = {}

    def resolve(self, provider: Provider) -> str:
        """The bearer token for this provider, or '' when it needs none."""
        spec = provider.api_key
        if not spec:
            return ""
        if provider.name in self._cache:
            return self._cache[provider.name]

        if spec.startswith("env:"):
            value = os.environ.get(spec[4:], "")
            if not value:
                raise KeyError_(
                    f"{provider.name}: environment variable {spec[4:]} is not set"
                )
        elif spec.startswith("pass:"):
            value = self._from_pass(provider, spec[5:])
        else:
            value = spec

        self._cache[provider.name] = value
        return value

    def _from_pass(self, provider: Provider, entry: str) -> str:
        try:
            out = self._runner(["pass", "show", entry], timeout=KEY_TIMEOUT)
        except subprocess.TimeoutExpired:
            raise KeyError_(
                f"{provider.name}: `pass show {entry}` timed out after "
                f"{KEY_TIMEOUT}s. Is a pinentry waiting for input?"
            )
        except Exception as exc:
            raise KeyError_(f"{provider.name}: `pass show {entry}` failed: {exc}")
        # A password store entry keeps the secret on the first line and
        # metadata below it.
        first = (out or "").strip().splitlines()
        if not first or not first[0].strip():
            raise KeyError_(f"{provider.name}: `pass show {entry}` returned nothing")
        return first[0].strip()
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  api key resolution`

- [ ] **Step 5: Commit**

```bash
git add llamachat/providers.py test_llamachat.py
git commit -m "feat: resolve provider API keys from pass, env or literal

One prefix-dispatched field. Resolution is lazy so a local-only session
never triggers a pinentry, cached for the process lifetime, and bounded
by a timeout so a stuck pinentry surfaces as an error instead of a frozen
send. Failures name the provider.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 4: Wire providers into config

**Files:**
- Modify: `llamachat/config.py:24-56` (DEFAULTS), `llamachat/config.py:76-95` (Config), `llamachat/config.py:110-152` (load)
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_key_resolution()`:

```python
def test_config_providers():
    """config.load exposes the provider table and the models.ini path."""
    with tempfile.TemporaryDirectory() as tmp:
        path = Path(tmp) / "config.toml"

        # A legacy config: bare base_url only.
        path.write_text('base_url = "http://localhost:9999"\n')
        cfg = config.load(path)
        assert set(cfg.providers) == {"local"}
        assert cfg.providers["local"].base_url == "http://localhost:9999"
        # base_url stays populated: existing code still reads it.
        assert cfg.base_url == "http://localhost:9999"
        assert cfg.models_path == path.parent / "models.ini"

        # A config with an explicit cloud provider.
        path.write_text(
            'base_url = "http://localhost:9999"\n'
            "\n"
            "[providers.together]\n"
            'base_url = "https://api.example.org"\n'
            'api_key = "pass:api/together"\n'
            'filter = ["qwen"]\n'
            "ctx_size = 32768\n"
            "price_in = 0.6\n"
            "price_out = 0.9\n"
        )
        cfg = config.load(path)
        assert set(cfg.providers) == {"local", "together"}
        assert cfg.providers["together"].api_key == "pass:api/together"
        assert cfg.providers["together"].filter == ["qwen"]
        assert cfg.providers["together"].price_out == 0.9

        # A config with no base_url and no providers still loads, with the
        # built-in default synthesizing local.
        path.write_text("request_timeout = 60\n")
        cfg = config.load(path)
        assert set(cfg.providers) == {"local"}
        assert cfg.providers["local"].base_url == config.DEFAULTS["base_url"]
    print("ok  config provider table")
```

Register it after `test_key_resolution()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `AttributeError: 'Config' object has no attribute 'providers'`

- [ ] **Step 3: Write the implementation**

In `llamachat/config.py`, add the import beside the existing ones:

```python
from . import providers as providers_mod
```

Add two fields to the `Config` dataclass, after `max_searches`:

```python
    max_searches: int
    providers: dict
    models_path: Path
```

In `load()`, after the `search_url`/`search_enabled` lines and before the
`return Config(`, add:

```python
    # Providers are built from the raw values so a bare base_url still
    # synthesizes the local entry. DEFAULTS supplies base_url when the file
    # names neither, which keeps a config with no network settings working.
    provider_table = providers_mod.parse(values)
```

Then add the two arguments to the `return Config(...)` call, after
`max_searches=int(values["max_searches"]),`:

```python
        providers=provider_table,
        models_path=path.parent / "models.ini",
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  config provider table`

- [ ] **Step 5: Commit**

```bash
git add llamachat/config.py test_llamachat.py
git commit -m "feat: expose the provider table from config

base_url stays populated so existing callers are untouched; the provider
table is built alongside it. models.ini sits beside config.toml and
state.ini, following the same pattern as the window layout.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 5: models.ini storage

**Files:**
- Create: `llamachat/models.py`
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_config_providers()`:

```python
def test_models_store():
    """models.ini round-trips per-model metadata and the cancel record."""
    from llamachat import models

    with tempfile.TemporaryDirectory() as tmp:
        path = Path(tmp) / "models.ini"
        store = models.ModelStore(path)

        # Nothing recorded yet.
        assert store.get("together:Qwen/Qwen2.5") is None
        assert store.was_offered("together:Qwen/Qwen2.5") is False

        store.save(
            "together:Qwen/Qwen2.5",
            models.ModelInfo(
                ctx_size=32768, vision=False, price_in=1.2, price_out=1.2
            ),
        )
        # A cancelled dialog records that it was offered, nothing more.
        store.mark_skipped("together:Llama-Vision-Free")

        # Reread from disk, not from memory: this is the round trip.
        fresh = models.ModelStore(path)
        info = fresh.get("together:Qwen/Qwen2.5")
        assert info.ctx_size == 32768
        assert info.vision is False
        assert info.price_in == 1.2
        assert info.price_out == 1.2
        assert fresh.was_offered("together:Qwen/Qwen2.5") is True

        assert fresh.get("together:Llama-Vision-Free") is None
        assert fresh.was_offered("together:Llama-Vision-Free") is True

        # Partial entries are legal: prices may be left blank.
        fresh.save("together:cheap", models.ModelInfo(ctx_size=8192))
        again = models.ModelStore(path)
        partial = again.get("together:cheap")
        assert partial.ctx_size == 8192
        assert partial.price_in is None
        assert partial.vision is None

        # A model id with a colon must survive being an ini section name.
        again.save("together:org/name:v2", models.ModelInfo(ctx_size=4096))
        assert models.ModelStore(path).get("together:org/name:v2").ctx_size == 4096
    print("ok  models.ini storage")
```

Register it after `test_config_providers()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `ModuleNotFoundError: No module named 'llamachat.models'`

- [ ] **Step 3: Write the implementation**

Create `llamachat/models.py` with the GPL header copied from `config.py`, then:

```python
"""Per-model metadata: what presets.ini cannot answer for a cloud model."""

import configparser
from dataclasses import dataclass
from pathlib import Path

# Recorded when the dialog is cancelled, so a model tried once never nags.
SKIPPED = "configured"


@dataclass
class ModelInfo:
    """What a model can tell us. Every field may be unknown."""
    ctx_size: int | None = None
    vision: bool | None = None
    price_in: float | None = None
    price_out: float | None = None

    def is_empty(self) -> bool:
        return all(
            v is None
            for v in (self.ctx_size, self.vision, self.price_in, self.price_out)
        )


def _get(section, key, cast):
    raw = section.get(key, "").strip()
    if not raw:
        return None
    try:
        return cast(raw)
    except ValueError:
        return None


def _get_bool(section, key):
    raw = section.get(key, "").strip().lower()
    if raw in ("true", "yes", "1", "on"):
        return True
    if raw in ("false", "no", "0", "off"):
        return False
    return None


class ModelStore:
    """models.ini, keyed by full model id.

    configparser rather than TOML because this file is written by the app,
    and tomllib is read-only in the standard library.
    """

    def __init__(self, path: Path):
        self.path = path
        # Model ids contain colons and slashes, so no key/value delimiter
        # may be inferred from a section name. Sections are safe as-is.
        self.parser = configparser.ConfigParser(interpolation=None)
        if path.exists():
            try:
                self.parser.read(path, encoding="utf-8")
            except configparser.Error:
                # ponytail: a corrupt file reads as empty; the dialog can
                # rewrite it. Failing to start over metadata is worse.
                self.parser = configparser.ConfigParser(interpolation=None)

    def get(self, model_id: str) -> ModelInfo | None:
        """Stored metadata, or None when there is none worth having."""
        if not self.parser.has_section(model_id):
            return None
        section = self.parser[model_id]
        info = ModelInfo(
            ctx_size=_get(section, "ctx_size", int),
            vision=_get_bool(section, "vision"),
            price_in=_get(section, "price_in", float),
            price_out=_get(section, "price_out", float),
        )
        return None if info.is_empty() else info

    def was_offered(self, model_id: str) -> bool:
        """Whether the dialog has already been shown for this model."""
        return self.parser.has_section(model_id)

    def save(self, model_id: str, info: ModelInfo) -> None:
        section = self._section(model_id)
        for key, value in (
            ("ctx_size", info.ctx_size),
            ("vision", info.vision),
            ("price_in", info.price_in),
            ("price_out", info.price_out),
        ):
            if value is None:
                section.pop(key, None)
            elif isinstance(value, bool):
                section[key] = "true" if value else "false"
            else:
                section[key] = str(value)
        section.pop(SKIPPED, None)
        self._write()

    def mark_skipped(self, model_id: str) -> None:
        """Record a cancelled dialog: offered, declined, do not ask again."""
        section = self._section(model_id)
        if not any(k != SKIPPED for k in section):
            section[SKIPPED] = "false"
        self._write()

    def _section(self, model_id: str):
        if not self.parser.has_section(model_id):
            self.parser.add_section(model_id)
        return self.parser[model_id]

    def _write(self) -> None:
        self.path.parent.mkdir(parents=True, exist_ok=True)
        with open(self.path, "w", encoding="utf-8") as fh:
            self.parser.write(fh)
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  models.ini storage`

- [ ] **Step 5: Commit**

```bash
git add llamachat/models.py test_llamachat.py
git commit -m "feat: store per-model metadata in models.ini

Cloud models have no presets.ini entry, so context size, vision and
prices are recorded per model in a file the app writes. A cancelled
dialog leaves a marker so a model tried once never asks again, which is
distinct from an absent section meaning never asked.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 6: Metadata resolution and cost arithmetic

**Files:**
- Modify: `llamachat/models.py`
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_models_store()`:

```python
def test_metadata_and_cost():
    """models.ini beats provider defaults beats unknown; cost sums per model."""
    from llamachat import models, providers

    table = providers.parse(
        {
            "providers": {
                "local": {"base_url": "http://localhost:8181"},
                "together": {
                    "base_url": "https://api.example.org",
                    "api_key": "env:X",
                    "ctx_size": 32768,
                    "price_in": 0.6,
                    "price_out": 0.9,
                },
                "free": {"base_url": "https://api3.example.org"},
            }
        }
    )

    with tempfile.TemporaryDirectory() as tmp:
        store = models.ModelStore(Path(tmp) / "models.ini")
        store.save(
            "together:specific",
            models.ModelInfo(ctx_size=8192, vision=True, price_in=5.0),
        )

        # Layer 1: models.ini wins where it has a value.
        info = models.resolve("together:specific", table, store)
        assert info.ctx_size == 8192
        assert info.vision is True
        assert info.price_in == 5.0
        # Layer 2 fills the gap models.ini left: price_out was never set.
        assert info.price_out == 0.9

        # Layer 2 alone for a model with no models.ini entry.
        other = models.resolve("together:other", table, store)
        assert other.ctx_size == 32768
        assert other.price_in == 0.6
        assert other.vision is None       # layer 3: still unknown

        # Layer 3 throughout for a provider that configured nothing.
        bare = models.resolve("free:anything", table, store)
        assert bare.ctx_size is None
        assert bare.price_in is None

        # Cost: prompt at the input rate, completion at the output rate.
        rows = [
            {"model": "together:other", "prompt_tokens": 1_000_000,
             "completion_tokens": 1_000_000},
            # A pre-migration row: no counts, no model. Contributes zero.
            {"model": None, "prompt_tokens": None, "completion_tokens": None},
        ]
        assert models.conversation_cost(rows, table, store) == 1.5

        # A mixed conversation prices each reply at what produced it.
        mixed = [
            {"model": "together:other", "prompt_tokens": 1_000_000,
             "completion_tokens": 0},
            {"model": "together:specific", "prompt_tokens": 1_000_000,
             "completion_tokens": 0},
        ]
        assert models.conversation_cost(mixed, table, store) == 5.6

        # An unpriced model contributes nothing rather than guessing.
        assert models.conversation_cost(
            [{"model": "free:anything", "prompt_tokens": 1_000_000,
              "completion_tokens": 0}], table, store
        ) == 0.0

        # Whether a model can be priced at all decides ? versus blank.
        assert models.is_priced("together:other", table, store) is True
        assert models.is_priced("free:anything", table, store) is False
        # Local is free, never unpriced.
        assert models.is_billable("gemma4", table) is False
        assert models.is_billable("free:anything", table) is False  # no api_key
        assert models.is_billable("together:other", table) is True

        # Formatting: cents matter, so three decimals below a dollar.
        assert models.format_cost(0.0) == "$0.000"
        assert models.format_cost(1.5) == "$1.50"
        assert models.format_cost(12.345) == "$12.35"
    print("ok  metadata resolution and cost")
```

Register it after `test_models_store()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `AttributeError: module 'llamachat.models' has no attribute 'resolve'`

- [ ] **Step 3: Write the implementation**

Append to `llamachat/models.py`. Add the import at the top of the file beside the
existing ones:

```python
from . import providers as providers_mod
```

Then append:

```python
def resolve(model_id: str, table: dict, store: "ModelStore") -> ModelInfo:
    """Merge the three metadata layers, most specific first.

    Per field, not per source: a models.ini entry that sets only ctx_size
    still inherits the provider's prices.
    """
    stored = store.get(model_id) or ModelInfo()
    name, _ = providers_mod.split(model_id, table)
    provider = table.get(name)

    def pick(from_store, from_provider):
        return from_store if from_store is not None else from_provider

    if provider is None:
        return stored
    return ModelInfo(
        ctx_size=pick(stored.ctx_size, provider.ctx_size),
        vision=pick(stored.vision, provider.vision),
        price_in=pick(stored.price_in, provider.price_in),
        price_out=pick(stored.price_out, provider.price_out),
    )


def is_billable(model_id: str, table: dict) -> bool:
    """Whether this model costs money, regardless of prices being known.

    Keyed on the provider having an api_key: that is what distinguishes a
    free local model from a cloud one whose price was never entered.
    """
    name, _ = providers_mod.split(model_id, table)
    provider = table.get(name)
    return bool(provider and not provider.is_local and provider.api_key)


def is_priced(model_id: str, table: dict, store: "ModelStore") -> bool:
    """Whether a cost can be computed for this model."""
    info = resolve(model_id, table, store)
    return info.price_in is not None or info.price_out is not None


def message_cost(row, table: dict, store: "ModelStore") -> float:
    """Cost of one stored assistant row, priced at the model that made it."""
    model_id = row["model"] if row["model"] else ""
    if not model_id:
        return 0.0
    info = resolve(model_id, table, store)
    prompt = row["prompt_tokens"] or 0
    completion = row["completion_tokens"] or 0
    total = 0.0
    if info.price_in is not None:
        total += prompt * info.price_in
    if info.price_out is not None:
        total += completion * info.price_out
    return total / 1_000_000


def conversation_cost(rows, table: dict, store: "ModelStore") -> float:
    """Everything spent in one conversation so far.

    Rows predating the token columns carry NULLs and contribute zero, so an
    old conversation reads as free rather than as a fabricated number.
    """
    return sum(message_cost(row, table, store) for row in rows)


def projected_cost(tokens: int, model_id: str, table: dict, store) -> float:
    """What sending `tokens` of input to this model would cost.

    Only the input rate: the length of the reply is unknowable in advance.
    """
    info = resolve(model_id, table, store)
    if info.price_in is None:
        return 0.0
    return tokens * info.price_in / 1_000_000


def format_cost(amount: float) -> str:
    """Money, with enough precision to see a cheap turn move the number."""
    if amount < 1:
        return f"${amount:.3f}"
    return f"${amount:.2f}"
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  metadata resolution and cost`

- [ ] **Step 5: Commit**

```bash
git add llamachat/models.py test_llamachat.py
git commit -m "feat: resolve model metadata in layers and compute cost

Resolution merges per field, not per source, so an entry setting only
ctx_size still inherits the provider's prices. Cost prices each reply at
the model that produced it, and rows predating the token columns
contribute zero rather than a fabricated number.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 7: Store token counts and the producing model

**Files:**
- Modify: `llamachat/db.py:35-43` (SCHEMA), `llamachat/db.py:101-124` (_migrate), `llamachat/db.py:210-231` (update_message)
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_metadata_and_cost()`:

```python
def test_token_column_migration():
    """A pre-token database opens, and new rows record counts and model."""
    import sqlite3

    with tempfile.TemporaryDirectory() as tmp:
        path = Path(tmp) / "old.db"
        conn = sqlite3.connect(path)
        conn.executescript(
            "CREATE TABLE sessions (id INTEGER PRIMARY KEY, mode TEXT,"
            " title TEXT, model TEXT, created_at INTEGER, updated_at INTEGER);"
            "CREATE TABLE messages (id INTEGER PRIMARY KEY, session_id INTEGER,"
            " role TEXT NOT NULL, content TEXT NOT NULL,"
            " created_at INTEGER NOT NULL);"
            "INSERT INTO sessions VALUES (1,'chat','old','m',0,0);"
            "INSERT INTO messages VALUES (1,1,'assistant','older reply',0);"
        )
        conn.commit()
        conn.close()

        history = db.History(path)
        rows = history.messages(1)
        # The pre-migration row survives and reads as unknown, not as zero.
        assert rows[0]["content"] == "older reply"
        assert rows[0]["prompt_tokens"] is None
        assert rows[0]["completion_tokens"] is None
        assert rows[0]["model"] is None

        mid = history.add_message(1, "assistant", "")
        history.update_message(
            mid, "new reply",
            prompt_tokens=1200, completion_tokens=340,
            model="together:Qwen/Qwen2.5",
        )
        fresh = history.messages(1)[1]
        assert fresh["prompt_tokens"] == 1200
        assert fresh["completion_tokens"] == 340
        assert fresh["model"] == "together:Qwen/Qwen2.5"

        # Omitting them leaves stored values alone, as with reasoning.
        history.update_message(mid, "edited")
        kept = history.messages(1)[1]
        assert kept["content"] == "edited"
        assert kept["prompt_tokens"] == 1200
        assert kept["model"] == "together:Qwen/Qwen2.5"
        history.close()
    print("ok  token column migration")
```

Register it after `test_metadata_and_cost()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `IndexError: No item with that key` (sqlite3.Row has no
`prompt_tokens` column)

- [ ] **Step 3: Write the implementation**

In `llamachat/db.py`, extend the `messages` table in `SCHEMA` so a fresh database
gets the columns directly. The block becomes:

```sql
CREATE TABLE IF NOT EXISTS messages (
    id                INTEGER PRIMARY KEY,
    session_id        INTEGER NOT NULL REFERENCES sessions(id) ON DELETE CASCADE,
    role              TEXT    NOT NULL,
    content           TEXT    NOT NULL,
    reasoning         TEXT    NOT NULL DEFAULT '',
    searches          TEXT,
    prompt_tokens     INTEGER,
    completion_tokens INTEGER,
    model             TEXT,
    created_at        INTEGER NOT NULL
);
```

In `_migrate()`, extend the `messages` entry of the `added` dict:

```python
            "messages": {
                "reasoning": "TEXT NOT NULL DEFAULT ''",
                # Nullable rather than defaulted: NULL means "no searches",
                # which is exactly what every pre-migration row wants.
                "searches": "TEXT",
                # Nullable for the same reason: an old row has no counts,
                # and zero would read as a reply that cost nothing.
                "prompt_tokens": "INTEGER",
                "completion_tokens": "INTEGER",
                # The model on `sessions` is the current one, which prices a
                # switched conversation wrongly. Record what actually replied.
                "model": "TEXT",
            },
```

Replace `update_message` with:

```python
    def update_message(
        self,
        message_id: int,
        content: str,
        reasoning: str | None = None,
        searches: str | None = None,
        prompt_tokens: int | None = None,
        completion_tokens: int | None = None,
        model: str | None = None,
    ) -> None:
        """Fill in a streamed reply. Omitted fields keep their stored value."""
        columns = ["content = ?"]
        values: list = [content]
        for column, value in (
            ("reasoning", reasoning),
            ("searches", searches),
            ("prompt_tokens", prompt_tokens),
            ("completion_tokens", completion_tokens),
            ("model", model),
        ):
            if value is not None:
                columns.append(f"{column} = ?")
                values.append(value)
        values.append(message_id)
        self.conn.execute(
            f"UPDATE messages SET {', '.join(columns)} WHERE id = ?", values
        )
        self.conn.commit()
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  token column migration`. `ok  reasoning column
migration` and `ok  search storage` must still pass, proving the rewritten
`update_message` kept its old behaviour.

- [ ] **Step 5: Commit**

```bash
git add llamachat/db.py test_llamachat.py
git commit -m "feat: record token counts and the producing model per message

Cost has to survive reopening a conversation, which means storing what
each reply used. The model goes on the message rather than the session
because sessions records only the current one, and a conversation that
switched models would otherwise be priced entirely at whichever is
selected now. All three columns are nullable so old rows read as unknown.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 8: Authorization header on the client

**Files:**
- Modify: `llamachat/backend.py:169-176` (Client.__init__), `:178-190` (models), `:192-224` (complete), `:299-337` (_stream_once)
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_token_column_migration()`:

```python
def test_client_auth_header():
    """A client with a key sends Bearer auth; one without sends no header."""
    sent = {}

    class _HttpxResponse:
        """Enough of an httpx response for Client.models().

        The existing _FakeResponse in this file wraps bytes for urlopen and
        has neither .json() nor .raise_for_status(), so it cannot stand in
        for an httpx call.
        """

        status_code = 200

        def __init__(self, payload):
            self._payload = payload

        def raise_for_status(self):
            return None

        def json(self):
            return self._payload

    def _recorder(url, timeout=None, headers=None):
        sent["url"] = url
        sent["headers"] = headers or {}
        return _HttpxResponse({"data": [{"id": "m1"}]})

    import httpx
    original = httpx.get
    try:
        httpx.get = _recorder

        assert backend.Client("http://x.example.org").models() == ["m1"]
        assert "Authorization" not in sent["headers"]

        backend.Client(
            "http://x.example.org", api_key="sk-test-not-a-real-key"
        ).models()
        assert sent["headers"]["Authorization"] == "Bearer sk-test-not-a-real-key"
    finally:
        httpx.get = original
    print("ok  client authorization header")
```

Register it after `test_token_column_migration()` in the `__main__` block.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `TypeError: Client.__init__() got an unexpected keyword argument 'api_key'`

- [ ] **Step 3: Write the implementation**

In `llamachat/backend.py`, replace `Client.__init__` with:

```python
    def __init__(self, base_url: str, timeout: int = 300, api_key: str = ""):
        self.base_url = base_url.rstrip("/")
        self.timeout = timeout
        self.api_key = api_key

    def _headers(self) -> dict:
        """Bearer auth when the provider needs it, nothing when it does not."""
        return {"Authorization": f"Bearer {self.api_key}"} if self.api_key else {}
```

Then add `headers=self._headers()` to each of the three outbound calls:

In `models()`:

```python
            resp = httpx.get(
                f"{self.base_url}/v1/models", timeout=10, headers=self._headers()
            )
```

In `complete()`, add the argument after `json={...}`:

```python
                timeout=httpx.Timeout(self.timeout, connect=10),
                headers=self._headers(),
            )
```

In `_stream_once()`, add it to the `httpx.stream` call:

```python
                timeout=httpx.Timeout(self.timeout, connect=10),
                headers=self._headers(),
            ) as resp:
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  client authorization header`

- [ ] **Step 5: Commit**

```bash
git add llamachat/backend.py test_llamachat.py
git commit -m "feat: send bearer auth when a provider needs a key

The local router needs none, so the header is omitted entirely rather
than sent empty.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 9: MultiClient routing

**Files:**
- Modify: `llamachat/backend.py` (append after `Client`)
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_client_auth_header()`:

```python
def test_multi_client():
    """Models fan out across providers; requests route by model id."""
    from llamachat import providers

    table = providers.parse(
        {
            "providers": {
                "local": {"base_url": "http://localhost:8181"},
                "together": {
                    "base_url": "https://api.example.org",
                    "api_key": "env:MULTI_TEST_KEY",
                    "filter": ["qwen"],
                },
                "down": {"base_url": "https://dead.example.org"},
            }
        }
    )
    os.environ["MULTI_TEST_KEY"] = "sk-test-not-a-real-key"

    listings = {
        "http://localhost:8181": ["gemma4", "qwen3.5-9b"],
        "https://api.example.org": [
            "Qwen/Qwen2.5-72B",
            "meta-llama/Llama-3.3-70B",
        ],
    }
    built = []

    class _StubClient:
        def __init__(self, base_url, timeout=300, api_key=""):
            self.base_url = base_url
            self.api_key = api_key
            built.append(self)

        def models(self):
            if self.base_url not in listings:
                raise backend.BackendError(f"cannot reach {self.base_url}")
            return listings[self.base_url]

    multi = backend.MultiClient(
        table, timeout=300, resolver=providers.KeyResolver(),
        client_factory=_StubClient,
    )
    listed, problems = multi.models()

    # Local models stay bare, cloud ones are prefixed, and the filter cut
    # the Llama model out of together's listing.
    assert listed == ["gemma4", "qwen3.5-9b", "together:Qwen/Qwen2.5-72B"]

    # The unreachable provider is reported, and did not break the rest.
    assert any("down" in p for p in problems)

    # Routing: the client for a cloud model carries that provider's key.
    client = multi.client_for("together:Qwen/Qwen2.5-72B")
    assert client.base_url == "https://api.example.org"
    assert client.api_key == "sk-test-not-a-real-key"

    # And a local model gets the local client with no key at all.
    local = multi.client_for("gemma4")
    assert local.base_url == "http://localhost:8181"
    assert local.api_key == ""

    # The bare model name is what goes on the wire, not the prefixed id.
    assert multi.wire_name("together:Qwen/Qwen2.5-72B") == "Qwen/Qwen2.5-72B"
    assert multi.wire_name("gemma4") == "gemma4"

    # A filter that matches nothing is reported by name with counts.
    table["together"].filter = ["zzz"]
    empty = backend.MultiClient(
        table, timeout=300, resolver=providers.KeyResolver(),
        client_factory=_StubClient,
    )
    _, notes = empty.models()
    assert any("together: 0 of 2" in n for n in notes)

    del os.environ["MULTI_TEST_KEY"]
    print("ok  multi-provider client")
```

Register it after `test_client_auth_header()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `AttributeError: module 'llamachat.backend' has no attribute 'MultiClient'`

- [ ] **Step 3: Write the implementation**

In `llamachat/backend.py`, add the import beside the existing `from . import search`:

```python
from . import providers as providers_mod
```

Append after the `Client` class:

```python
class MultiClient:
    """One façade over every configured provider.

    Holds a `Client` per provider, built on demand so a key is resolved only
    when that provider is actually used. The UI talks in prefixed model ids
    and never needs to know which endpoint one lives on.
    """

    def __init__(self, table, timeout=300, resolver=None, client_factory=Client):
        self.table = table
        self.timeout = timeout
        self.resolver = resolver or providers_mod.KeyResolver()
        self._factory = client_factory
        self._clients: dict[str, Client] = {}

    def client_for(self, model_id: str) -> Client:
        """The client that serves this model, resolving its key on first use."""
        name, _ = providers_mod.split(model_id, self.table)
        if name not in self._clients:
            provider = self.table[name]
            self._clients[name] = self._factory(
                provider.base_url,
                timeout=self.timeout,
                api_key=self.resolver.resolve(provider),
            )
        return self._clients[name]

    def wire_name(self, model_id: str) -> str:
        """The model name the provider itself expects, without our prefix."""
        _, model = providers_mod.split(model_id, self.table)
        return model

    def models(self) -> tuple[list[str], list[str]]:
        """Every offered model id, plus notes about what went wrong.

        A provider that is unreachable or whose filter matched nothing must
        not stop the others being listed: local models have to stay usable
        when the network is down.
        """
        listed: list[str] = []
        problems: list[str] = []
        for name, provider in self.table.items():
            try:
                available = self._listing_client(provider).models()
            except (BackendError, providers_mod.KeyError_) as exc:
                problems.append(f"{name}: {exc}")
                continue
            kept = providers_mod.apply_filter(provider, available)
            if available and not kept:
                problems.append(
                    f"{name}: 0 of {len(available)} models matched filter"
                )
            listed.extend(providers_mod.qualify(name, m) for m in kept)
        return listed, problems

    def _listing_client(self, provider) -> Client:
        """Listing needs a client too, and needs the key for a private API."""
        return self.client_for(providers_mod.qualify(provider.name, ""))
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  multi-provider client`

- [ ] **Step 5: Commit**

```bash
git add llamachat/backend.py test_llamachat.py
git commit -m "feat: fan model listing out across providers and route by id

A provider that is unreachable or whose filter matched nothing is
reported rather than fatal: local models must stay usable when the
network is down. Clients are built on demand so a key is resolved only
when that provider is really used.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 10: The model dialog

**Files:**
- Create: `llamachat/modeldialog.py`
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

The dialog's layout needs a running Qt application, but its field conversion does
not. Test the conversion, which is where the bugs live. Add after
`test_multi_client()`:

```python
def test_model_dialog_values():
    """The dialog's field text converts to ModelInfo, blanks meaning unknown."""
    from llamachat import models, modeldialog

    # Everything filled in.
    info = modeldialog.to_info(
        ctx_text="32768", vision=True, in_text="1.2", out_text="0.9"
    )
    assert info.ctx_size == 32768
    assert info.vision is True
    assert info.price_in == 1.2
    assert info.price_out == 0.9

    # Blank prices are legal and mean unpriced, not free.
    blank = modeldialog.to_info(
        ctx_text="8192", vision=False, in_text="", out_text="  "
    )
    assert blank.ctx_size == 8192
    assert blank.price_in is None
    assert blank.price_out is None

    # Garbage reads as unknown rather than crashing the dialog.
    junk = modeldialog.to_info(
        ctx_text="not a number", vision=False, in_text="free", out_text=""
    )
    assert junk.ctx_size is None
    assert junk.price_in is None

    # Prefill is the inverse: unknown becomes an empty field.
    assert modeldialog.to_fields(models.ModelInfo()) == ("", False, "", "")
    assert modeldialog.to_fields(
        models.ModelInfo(ctx_size=4096, vision=True, price_in=0.5)
    ) == ("4096", True, "0.5", "")
    print("ok  model dialog value conversion")
```

Register it after `test_multi_client()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `ModuleNotFoundError: No module named 'llamachat.modeldialog'`

- [ ] **Step 3: Write the implementation**

Create `llamachat/modeldialog.py` with the GPL header copied from `config.py`, then:

```python
"""Dialog for entering what presets.ini cannot answer about a model."""

from PySide6.QtWidgets import (
    QCheckBox,
    QDialog,
    QDialogButtonBox,
    QFormLayout,
    QLabel,
    QLineEdit,
    QVBoxLayout,
)

from .models import ModelInfo


def _number(text: str, cast):
    """Field text to a number, treating blank and garbage alike as unknown."""
    text = (text or "").strip()
    if not text:
        return None
    try:
        return cast(text)
    except ValueError:
        return None


def to_info(ctx_text: str, vision: bool, in_text: str, out_text: str) -> ModelInfo:
    """Build a ModelInfo from the dialog's raw field values."""
    return ModelInfo(
        ctx_size=_number(ctx_text, int),
        vision=bool(vision),
        price_in=_number(in_text, float),
        price_out=_number(out_text, float),
    )


def to_fields(info: ModelInfo) -> tuple[str, bool, str, str]:
    """The inverse, for prefilling. Unknown becomes an empty field."""
    return (
        "" if info.ctx_size is None else str(info.ctx_size),
        bool(info.vision),
        "" if info.price_in is None else str(info.price_in),
        "" if info.price_out is None else str(info.price_out),
    )


class ModelDialog(QDialog):
    """Context size, vision and prices for one model.

    Prefilled from the provider's defaults, so the common case is checking
    the numbers rather than typing them.
    """

    def __init__(self, model_id: str, info: ModelInfo, parent=None):
        super().__init__(parent)
        self.setWindowTitle("Model settings")
        self.model_id = model_id

        ctx, vision, price_in, price_out = to_fields(info)
        self.ctx = QLineEdit(ctx)
        self.ctx.setPlaceholderText("unknown")
        self.vision = QCheckBox("Accepts images")
        self.vision.setChecked(vision)
        self.price_in = QLineEdit(price_in)
        self.price_in.setPlaceholderText("unpriced")
        self.price_out = QLineEdit(price_out)
        self.price_out.setPlaceholderText("unpriced")

        layout = QVBoxLayout(self)
        heading = QLabel(f"<b>{model_id}</b>")
        heading.setTextInteractionFlags(heading.textInteractionFlags())
        layout.addWidget(heading)

        form = QFormLayout()
        form.addRow("Context size (tokens)", self.ctx)
        form.addRow("", self.vision)
        form.addRow("Input price (per 1M tokens)", self.price_in)
        form.addRow("Output price (per 1M tokens)", self.price_out)
        layout.addLayout(form)

        note = QLabel(
            "Leave prices empty if you do not want a cost estimate.\n"
            "Context size drives the meter and the attachment budget."
        )
        note.setWordWrap(True)
        layout.addWidget(note)

        buttons = QDialogButtonBox(
            QDialogButtonBox.Save | QDialogButtonBox.Cancel
        )
        buttons.accepted.connect(self.accept)
        buttons.rejected.connect(self.reject)
        layout.addWidget(buttons)

    def info(self) -> ModelInfo:
        """What the user entered."""
        return to_info(
            self.ctx.text(),
            self.vision.isChecked(),
            self.price_in.text(),
            self.price_out.text(),
        )
```

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  model dialog value conversion`

- [ ] **Step 5: Commit**

```bash
git add llamachat/modeldialog.py test_llamachat.py
git commit -m "feat: dialog for per-model context size, vision and prices

Field conversion is separated from the widget so the part with the edge
cases is testable without a running Qt application. Blank and unparseable
both read as unknown, which is what an empty price field has to mean.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 11: Cost label widget

**Files:**
- Modify: `llamachat/ui.py` (add after `_short`, around line 135)
- Modify: `test_llamachat.py`

- [ ] **Step 1: Write the failing test**

Add after `test_model_dialog_values()`:

```python
def test_cost_label_text():
    """The label distinguishes free, unpriced, and a real figure."""
    from llamachat import ui

    # A local model costs nothing, so the label says nothing.
    assert ui.cost_text(spent=0.0, projected=0.0, billable=False, priced=False) == ""

    # A cloud model whose price was never entered: ? rather than blank, so
    # it cannot be mistaken for free.
    assert ui.cost_text(
        spent=0.0, projected=0.0, billable=True, priced=False
    ) == "?"

    # Spent so far, with nothing composed yet.
    assert ui.cost_text(
        spent=0.043, projected=0.0, billable=True, priced=True
    ) == "$0.043"

    # Spent plus what sending the draft would add, kept visually separate.
    assert ui.cost_text(
        spent=0.043, projected=0.011, billable=True, priced=True
    ) == "$0.043 +$0.011"

    # A fresh conversation on a priced model still shows the projection.
    assert ui.cost_text(
        spent=0.0, projected=0.002, billable=True, priced=True
    ) == "$0.000 +$0.002"
    print("ok  cost label text")
```

Register it after `test_model_dialog_values()`.

- [ ] **Step 2: Run the suite to verify it fails**

Run: `./test_llamachat.py`
Expected: FAIL with `AttributeError: module 'llamachat.ui' has no attribute 'cost_text'`

- [ ] **Step 3: Write the implementation**

In `llamachat/ui.py`, add the import beside the existing project imports:

```python
from . import models as models_mod
```

Add after the `_short` function (around line 135):

```python
def cost_text(spent: float, projected: float, billable: bool, priced: bool) -> str:
    """The cost label beside the context meter.

    Three states, deliberately distinct: a local model shows nothing, a
    cloud model with no price entered shows '?', and a priced one shows
    what it has cost plus what the composed draft would add. Blank and '?'
    must not collapse into each other, or an unpriced cloud model reads as
    free.
    """
    if not billable:
        return ""
    if not priced:
        return "?"
    text = models_mod.format_cost(spent)
    if projected > 0:
        text += f" +{models_mod.format_cost(projected)}"
    return text


class CostLabel(QLabel):
    """A one-line money readout that hides itself when there is nothing to say."""

    def __init__(self):
        super().__init__("")
        self.setToolTip("")

    def set_cost(
        self, spent: float, projected: float, billable: bool, priced: bool
    ) -> None:
        text = cost_text(spent, projected, billable, priced)
        self.setText(text)
        self.setVisible(bool(text))
        if not billable:
            self.setToolTip("")
        elif not priced:
            self.setToolTip(
                "No prices set for this model.\n"
                "Use Model settings to enter them."
            )
        else:
            tip = f"{models_mod.format_cost(spent)} spent in this conversation"
            if projected > 0:
                tip += (
                    f"\n+{models_mod.format_cost(projected)} to send what is "
                    "composed now"
                )
            tip += "\nApproximate: based on the prices you entered."
            self.setToolTip(tip)
```

Confirm `QLabel` is in the `PySide6.QtWidgets` import list at the top of `ui.py`;
it is already imported, so no import change is needed beyond `models_mod`.

- [ ] **Step 4: Run the suite to verify it passes**

Run: `./test_llamachat.py`
Expected: PASS, including `ok  cost label text`

- [ ] **Step 5: Commit**

```bash
git add llamachat/ui.py test_llamachat.py
git commit -m "feat: cost label showing spend and the next send's projection

Three states stay distinct: blank for a free local model, ? for a cloud
model whose prices were never entered, and a figure when they were.
Collapsing the first two would make an unpriced cloud model read as free.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 12: Wire the window to providers

**Files:**
- Modify: `llamachat/__main__.py:155-165`
- Modify: `llamachat/ui.py:356-406` (`ChatWindow.__init__`), `:669-717` (model handling)

This task is wiring, not new logic, and its behaviour is covered by the tests
already written plus a manual check. No new automated test.

- [ ] **Step 1: Build the MultiClient at startup**

In `llamachat/__main__.py`, replace the client construction (line 159) with:

```python
    client = MultiClient(cfg.providers, cfg.request_timeout)
    presets = config.parse_presets(cfg.presets_path)
    store = models.ModelStore(cfg.models_path)
    window = ChatWindow(cfg, history, client, presets, store)
```

Update the imports at the top of `__main__.py`: replace the `Client` import with
`MultiClient` and add `from llamachat import models`. Check the existing import
lines and keep their style.

- [ ] **Step 2: Accept the store in the window**

In `llamachat/ui.py`, change `ChatWindow.__init__` (line 359) to take the new
argument and keep it:

```python
    def __init__(self, cfg, history, client, presets, store):
        ...
        self.presets = presets
        self.store = store
```

Add it right after the existing `self.presets = presets` line at 364.

- [ ] **Step 3: List models from every provider**

Replace `refresh_models` (line 669) with:

```python
    def refresh_models(self) -> None:
        """Repopulate the picker from every provider, keeping the selection."""
        previous = self.model_box.currentText()
        available, problems = self.client.models()
        if not available:
            self.show_status(
                "; ".join(problems) or "No models available", error=True
            )
            return

        self.model_box.blockSignals(True)
        self.model_box.clear()
        for name in available:
            info = self.model_info(name)
            label = f"{name} 👁" if info.vision else name
            self.model_box.addItem(label, name)
        self.model_box.blockSignals(False)

        target = previous or self.cfg.default_model
        if target:
            index = self.model_box.findData(_strip_marker(target))
            if index < 0:
                index = self.model_box.findText(target)
            if index >= 0:
                self.model_box.setCurrentIndex(index)
        # A provider that failed is worth saying so even when others worked.
        if problems:
            self.show_status("; ".join(problems), error=True)
        else:
            self.hide_status()
```

- [ ] **Step 4: Resolve metadata through the three layers**

Replace `current_preset`, `char_budget` and `vision_models` (lines 699-717) with:

```python
    def model_info(self, model_id: str):
        """Metadata for one model: models.ini, then provider, then presets.

        Local models get their context and vision from presets.ini, which
        the first two layers can still override if the user entered values.
        """
        info = models_mod.resolve(model_id, self.cfg.providers, self.store)
        preset = self.presets.get(model_id)
        if preset is not None:
            if info.ctx_size is None:
                info.ctx_size = preset.ctx_size
            if info.vision is None:
                info.vision = preset.vision
        return info

    def current_info(self):
        return self.model_info(self.current_model())

    def current_preset(self):
        return self.presets.get(self.current_model())

    def char_budget(self) -> int:
        ctx = self.current_info().ctx_size or 4096
        return int(ctx * self.cfg.chars_per_token * self.cfg.attach_ctx_fraction)

    def vision_models(self) -> list[str]:
        names = []
        for i in range(self.model_box.count()):
            name = self.model_box.itemData(i)
            if self.model_info(name).vision:
                names.append(name)
        return names
```

- [ ] **Step 5: Permit attachments on unknown-capability models**

In `_ensure_vision_model` (line 842), replace the opening check:

```python
        info = self.current_info()
        if info.vision:
            return True
        # Unknown is not the same as "no": a cloud model we know nothing
        # about may well accept images, and the API will say so if it does
        # not. Only a model known to lack vision gets stopped here.
        if info.vision is None:
            return True
```

- [ ] **Step 6: Route requests through the right client**

Every call that currently does `self.client.<method>(model, ...)` must become a
call on the routed client with the wire name. In `send()` (line 919) and
`_start_stream()` (line 1040), the model passed to `StreamWorker` must be split.
Change `_start_stream` to resolve both up front:

```python
    def _start_stream(self, model: str, messages: list[dict]) -> None:
        try:
            client = self.client.client_for(model)
        except providers_mod.KeyError_ as exc:
            self.show_status(str(exc), error=True)
            return
        wire = self.client.wire_name(model)
```

and pass `client` and `wire` to `StreamWorker` in place of `self.client` and
`model`. Add the import at the top of `ui.py`:

```python
from . import providers as providers_mod
```

Apply the same treatment in `_start_titling` (line 1133), which builds a
`TitleWorker`: resolve `client` and `wire` the same way, and on `KeyError_` skip
titling silently rather than showing an error, since titling is never the user's
own turn.

- [ ] **Step 7: Verify the whole suite still passes**

Run: `./test_llamachat.py`
Expected: PASS, all checks, ending in `all checks passed`

- [ ] **Step 8: Verify the app still starts against the local router**

Run: `./llamachat.py`
Expected: the window opens, the model dropdown lists the local models exactly as
before with no prefix, and sending a message works. Close it.

This is the check that the wiring is right; the unit tests cannot see it.

- [ ] **Step 9: Commit**

```bash
git add llamachat/ui.py llamachat/__main__.py
git commit -m "feat: list and route models through every configured provider

Metadata now resolves models.ini over provider defaults over presets.ini,
so a local model keeps getting its context and vision from the preset
while remaining overridable. A model whose vision support is unknown no
longer blocks an attachment: unknown is not the same as no, and the API
will reject an image if it really cannot take one.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 13: Dialog triggers

**Files:**
- Modify: `llamachat/ui.py:407-572` (`_build_ui`), `:719-725` (`_on_model_changed`)

- [ ] **Step 1: Add the on-demand button**

In `_build_ui`, immediately after the `model_box` is added to its layout, add:

```python
        self.model_settings_button = QToolButton()
        self.model_settings_button.setText("⚙")
        self.model_settings_button.setToolTip(
            "Context size, vision and prices for the selected model"
        )
        self.model_settings_button.clicked.connect(self.edit_model_settings)
```

Add it to the same layout the model box lives in, directly after it. Confirm
`QToolButton` is in the `PySide6.QtWidgets` import list at the top of `ui.py` and
add it if it is not.

- [ ] **Step 2: Add the trigger and editor methods**

Add after `vision_models` (around line 717):

```python
    def edit_model_settings(self, model_id: str | None = None) -> bool:
        """Open the dialog for one model. True when values were saved."""
        model_id = model_id or self.current_model()
        if not model_id:
            return False
        current = models_mod.resolve(model_id, self.cfg.providers, self.store)
        dialog = ModelDialog(model_id, current, self)
        if dialog.exec() != QDialog.Accepted:
            self.store.mark_skipped(model_id)
            return False
        self.store.save(model_id, dialog.info())
        self.update_meter()
        return True

    def _maybe_offer_model_settings(self, model_id: str) -> None:
        """Ask once, on first selection of an unconfigured cloud model.

        Local models are exempt: presets.ini already answers context and
        vision for them and they cost nothing. Cancelling records that the
        offer was made, so a model tried once never asks again.
        """
        if not model_id or not models_mod.is_billable(model_id, self.cfg.providers):
            return
        if self.store.was_offered(model_id):
            return
        self.edit_model_settings(model_id)
```

- [ ] **Step 3: Fire it on selection**

In `_on_model_changed` (line 719), add the offer before the existing body:

```python
    def _on_model_changed(self, _text: str) -> None:
        self._maybe_offer_model_settings(self.current_model())
```

Keep everything the method already does after that line.

- [ ] **Step 4: Add the imports**

At the top of `ui.py`, beside the other project imports:

```python
from .modeldialog import ModelDialog
```

Confirm `QDialog` is already imported from `PySide6.QtWidgets`; it is, since
`PromptDialog` subclasses it.

- [ ] **Step 5: Verify the suite still passes**

Run: `./test_llamachat.py`
Expected: PASS, all checks

- [ ] **Step 6: Verify the local path is unchanged**

Run: `./llamachat.py`
Expected: switching between local models opens no dialog. The ⚙ button opens the
dialog for the current local model, and Cancel leaves it unchanged. Close it.

- [ ] **Step 7: Commit**

```bash
git add llamachat/ui.py
git commit -m "feat: offer model settings on first use of a cloud model

Fires on selection rather than on send, so the interruption lands while
the user is already changing settings instead of mid-thought. Local
models never trigger it, and a cancelled dialog is recorded so a model
tried once never asks again.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 14: Show the cost

**Files:**
- Modify: `llamachat/ui.py:407-572` (`_build_ui`), `:993-1029` (`update_meter`), `:1075-1082` (`_on_usage`), `:1110-1123` (`_on_stream_finished`)

- [ ] **Step 1: Put the label beside the meter**

In `_build_ui`, immediately after the line that adds `self.meter` to its layout,
add:

```python
        self.cost = CostLabel()
```

and add it to the same layout directly after the meter.

- [ ] **Step 2: Track the reply's token counts**

In `_on_usage` (line 1075), record the counts so the finished reply can be stored
with them. Replace the method with:

```python
    @Slot(int, int)
    def _on_usage(self, prompt_tokens: int, total_tokens: int) -> None:
        """Replace the estimate with the counts the server reported."""
        info = self.current_info()
        limit = info.ctx_size or 0
        # What the next turn starts from is everything sent plus the reply.
        self.exact_tokens = total_tokens or prompt_tokens
        self.turn_prompt_tokens = prompt_tokens
        self.turn_completion_tokens = max(total_tokens - prompt_tokens, 0)
        self.meter.set_usage(self.exact_tokens, limit, exact=True)
        self.update_cost()
```

Initialise both counters to 0 in `_teardown_stream` (line 1185) and in
`ChatWindow.__init__` beside the other per-turn state:

```python
        self.turn_prompt_tokens = 0
        self.turn_completion_tokens = 0
```

- [ ] **Step 3: Store them with the finished reply**

In `_on_stream_finished` (line 1110), extend the `update_message` call:

```python
            self.history.update_message(
                self.assistant_message_id,
                self.assistant_buffer,
                self.reasoning_buffer,
                self._searches_json(),
                prompt_tokens=self.turn_prompt_tokens or None,
                completion_tokens=self.turn_completion_tokens or None,
                model=self.current_model(),
            )
```

- [ ] **Step 4: Compute and show the cost**

Add after `update_meter` (around line 1029):

```python
    def update_cost(self) -> None:
        """Refresh the money readout from stored counts plus the draft."""
        if not hasattr(self, "cost"):
            return  # still building the window
        model_id = self.current_model()
        billable = models_mod.is_billable(model_id, self.cfg.providers)
        priced = models_mod.is_priced(model_id, self.cfg.providers, self.store)
        if not billable or not priced:
            self.cost.set_cost(0.0, 0.0, billable, priced)
            return

        rows = (
            self.history.messages(self.session_id)
            if self.session_id is not None
            else []
        )
        spent = models_mod.conversation_cost(rows, self.cfg.providers, self.store)

        # Reopening a conversation resends its whole history, so the
        # projection has to price everything that would go out, not just
        # what was typed. That is what makes an expensive turn visible
        # before it is paid rather than after.
        pending = backend.estimate_tokens(
            self._chat_context(
                backend.build_user_content(
                    self.input.toPlainText(), self.attachments
                )
            ),
            self.cfg.chars_per_token,
        ) if self.session_id is not None or self.input.toPlainText() else 0
        projected = models_mod.projected_cost(
            pending, model_id, self.cfg.providers, self.store
        )
        self.cost.set_cost(spent, projected, billable, priced)
```

- [ ] **Step 5: Refresh it wherever the meter refreshes**

At the end of `update_meter` (line 1029), add:

```python
        self.update_cost()
```

Three more call sites, so switching model or reopening a conversation updates the
figure:

- At the end of `refresh_models`. **Task 12 rewrote this method**, so add the call
  to that rewritten version, at the very end of both the `if problems:` and `else:`
  branches, or on a single line after the whole `if/else`.
- At the end of the method that loads a session from the sidebar (around line
  1343, the one starting `session = self.history.get_session(session_id)`).
- At the end of `new_session` (line 789), so starting a fresh conversation clears
  the previous one's figure.

- [ ] **Step 6: Verify the suite still passes**

Run: `./test_llamachat.py`
Expected: PASS, all checks

- [ ] **Step 7: Verify against the local router**

Run: `./llamachat.py`
Expected: no cost label appears for a local model, the context meter behaves
exactly as before, and sending a message still works. Close it.

- [ ] **Step 8: Commit**

```bash
git add llamachat/ui.py
git commit -m "feat: show conversation cost and the next send's projection

The projection prices the whole request, not just the draft, because
reopening a conversation resends its entire history and that is billed
per turn on a cloud provider. Seeing it before sending is the whole point
of the readout.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 15: Config template and documentation

**Files:**
- Modify: `llamachat/config.py:155-215` (`write_default`)
- Modify: `README.md`
- Modify: `CHANGELOG.md`

- [ ] **Step 1: Document providers in the generated config**

In `write_default`, append to the written text, before the closing parenthesis:

```python
        '\n'
        '# External providers. The local router is a provider named "local",\n'
        '# synthesized from base_url above when no [providers.local] exists.\n'
        '# Any OpenAI-compatible endpoint works.\n'
        '#\n'
        '# Cloud models appear in the picker as provider:model. Local ones\n'
        '# stay bare, so nothing about the local setup changes.\n'
        '#\n'
        '# api_key accepts three forms:\n'
        '#   "pass:api/together"   read from the password store (preferred)\n'
        '#   "env:TOGETHER_KEY"    read from the environment\n'
        '#   "sk-..."              the key itself, in this file\n'
        '# It is read lazily, on the first request to that provider, so a\n'
        '# local-only session never unlocks the password store.\n'
        '#\n'
        '# filter keeps only models whose id contains one of these strings,\n'
        '# case-insensitively. Providers list hundreds of models; without a\n'
        '# filter the picker is unusable. Omit it to list them all.\n'
        '#\n'
        '# ctx_size, vision, price_in and price_out prefill the per-model\n'
        '# dialog. Prices are US dollars per million tokens. Everything the\n'
        '# dialog saves goes to models.ini beside this file, so none of\n'
        '# these has to be set here.\n'
        '#\n'
        '# [providers.together]\n'
        '# base_url = "https://api.together.xyz"\n'
        '# api_key = "pass:api/together"\n'
        '# filter = ["qwen", "deepseek"]\n'
        '# ctx_size = 32768\n'
        '# price_in = 0.60\n'
        '# price_out = 0.60\n'
```

- [ ] **Step 2: Verify the generated config still parses**

Run:

```bash
python3 -c "
import tempfile, tomllib
from pathlib import Path
import sys; sys.path.insert(0, '.')
from llamachat import config
with tempfile.TemporaryDirectory() as t:
    p = config.write_default(Path(t) / 'config.toml')
    tomllib.loads(p.read_text())
    cfg = config.load(p)
    assert set(cfg.providers) == {'local'}, cfg.providers
    print('generated config parses, providers:', list(cfg.providers))
"
```

Expected: `generated config parses, providers: ['local']`

The commented-out provider block must stay commented, or a fresh install would
try to reach an endpoint the user never configured.

- [ ] **Step 3: Document it in the README**

Add a section after the existing web search documentation, matching its tone and
depth. It must cover: the `[providers.*]` table with a worked together.ai example,
the three `api_key` forms and why `pass:` is preferred, lazy resolution meaning no
pinentry for local-only sessions, filtering and why it is needed, the per-model
dialog and `models.ini`, and the cost readout being an approximation based on
hand-entered prices.

State plainly, as the README already does for search: **a conversation resends its
whole history every turn, so a long conversation on a cloud provider is billed for
all of it on each message.** That is the behaviour most likely to surprise, and the
projection in the cost label exists to make it visible.

Also note that tool calling and reasoning output are known to vary between
providers, so web search on a cloud model may not work as it does locally.

- [ ] **Step 4: Add the changelog entry**

Add an `## [Unreleased]` section at the top of `CHANGELOG.md`, following the
existing format, describing: external OpenAI-compatible providers, `pass`/env/
literal key resolution, model filtering, the per-model settings dialog and
`models.ini`, per-conversation cost with projection, and the three new `messages`
columns. Note the cloud tool-calling caveat under a "Known limitations" line if
the file's format has one; otherwise state it in the entry itself.

- [ ] **Step 5: Verify the version test still passes**

`test_version_matches_changelog` matches `^## \[(\d+\.\d+\.\d+)\]` and asserts the
first hit equals `__version__`. `## [Unreleased]` does not match that pattern, so
it is skipped and `## [0.3.0]` stays the first hit. The entry is safe as long as
the heading is exactly `## [Unreleased]` and no version number is invented for it.

Run: `./test_llamachat.py`
Expected: PASS, including `ok  version matches changelog`

- [ ] **Step 6: Commit**

```bash
git add llamachat/config.py README.md CHANGELOG.md
git commit -m "docs: document external providers, keys and cost

The generated config ships the provider block commented out so a fresh
install never reaches an endpoint nobody configured. The README states
plainly that every turn resends the whole conversation, which is free
locally and billed per message on a cloud provider.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>"
```

---

## Task 16: End-to-end verification against a real provider

This task needs the user: it spends real money and needs a real API key. Do not
attempt it autonomously.

- [ ] **Step 1: Ask the user to configure one provider**

The user adds a `[providers.together]` block (or siliconflow) to their
`config.toml` with a `pass:` key and a filter, then starts llamachat.

- [ ] **Step 2: Verify listing and the dialog**

Expected: local models appear bare, cloud models appear as `provider:model` and
only those matching the filter. Selecting a cloud model for the first time opens
the settings dialog once. Cancelling it does not reopen it on reselection.

- [ ] **Step 3: Verify a cloud reply and the cost**

Send a short message to a cloud model with prices entered. Expected: the reply
streams, the cost label shows a figure, and it grows on the next message.

- [ ] **Step 4: Verify cost survives reopening**

Close and reopen the conversation from the history sidebar. Expected: the cost
label shows the accumulated figure, not zero.

- [ ] **Step 5: Verify the local path is untouched**

Switch back to a local model. Expected: no cost label, the meter behaves as
before, and web search still works exactly as it did in 0.3.0.

- [ ] **Step 6: Try web search on a cloud model and record what happens**

This is the known risk. Expected: unknown. Record the outcome, whether the tool
call is emitted, whether the reply arrives, and whether `reasoning_content` shows
up. If it fails, capture the shape of the response and open it as its own piece of
work rather than fixing it inside this one.

- [ ] **Step 7: Commit any fixes found**

Only if the earlier steps surfaced defects. Each fix gets a test first, following
the pattern of every task above.

---

## Notes for the implementer

**The local path is the one that must not regress.** Every task keeps local
models bare, unfiltered, and free of the dialog. If a change makes a local model
behave differently than it did in 0.3.0, that is a bug in the change, not an
acceptable cost.

**Never put a real API key in a test, a fixture or a commit message.** Two git
hooks scan for exactly this and will reject the commit. Use
`sk-test-not-a-real-key` and `example.org`.

**Cloud tool calling is unverified.** Task 16 step 6 is where that gets found out.
Nothing before it should assume search works on a cloud provider, and nothing
should assume it is broken either.