Adopt hatch-vcs dynamic versioning (reworks autotag, pypi-publish, desktop) (#538)

* build: adopt hatch-vcs dynamic versioning (#526)

Replace the static `version = "1.0.2"` with `dynamic = ["version"]` and
derive the version from git tags via hatch-vcs, so source and editable
checkouts report their true git describe version (e.g.
1.0.3.dev110+g<sha>) instead of a stale constant.

Config notes:
- Exclude .dev/.rc/desktop-* tags from derivation. setuptools_scm cannot
  bump custom .devN tags, so the base is taken from the latest plain
  release tag (vX.Y.Z) and the dev distance from commit count.
- Add fallback_version so builds without a git checkout (shallow CI
  clones, Docker COPY src/, source-zip installs) resolve to a sentinel
  instead of hard-failing. CI release builds inject the exact version via
  SETUPTOOLS_SCM_PRETEND_VERSION.

* ci(autotag): derive dev base from the latest release tag (#526)

pyproject no longer carries a static version, so read the base from the
latest plain release tag (vX.Y.Z) reachable from HEAD instead of grepping
pyproject. .dev/.rc/desktop-* tags are excluded so they cannot be mistaken
for the release base. The computed tag (vX.Y.Z.devN) is unchanged.

* ci(pypi-publish): pin build version from tag, drop sed injection (#526)

With dynamic versioning there is no static line to sed. Pin the exact
build version from the pushed tag via SETUPTOOLS_SCM_PRETEND_VERSION so
the published version equals the tag. This is required, not cosmetic: a
naive hatch-vcs build emits 1.0.3.devN+g<sha>, and PyPI rejects local
version segments on upload.

Also add a dry_run input that targets TestPyPI instead of PyPI, for
validating the release path without a production upload.

* ci(desktop): derive dispatch-fallback version from release tag (#526)

The workflow_dispatch fallback grepped the now-removed static pyproject
version. Derive its base from the latest release tag instead (matching
autotag), and give the build-and-release checkout full history and tags
so the derivation works.

---------

Co-authored-by: Jon Saad-Falcon <jonsaadfalcon@gmail.com>

.github/workflows/autotag.yml

@@ -21,14 +21,20 @@ jobs:
         id: version
         run: |
           set -euo pipefail
-          # Base version is the next patch above whatever is in pyproject.toml.
+          # Base version is the next patch above the latest plain release tag
+          # (vX.Y.Z) reachable from HEAD. pyproject.toml no longer carries a
+          # static version (#526 switched it to hatch-vcs), so the release tag
+          # is the source of truth. `.devN`/`.rcN`/`desktop-*` tags are excluded
+          # so they can't be mistaken for the release base.
           # Any future manual `X.Y.Z` release will outrank every `X.Y.Z.devN`
           # autotag — PEP 440 sorts dev releases strictly below the final.
-          BASE=$(grep -E '^version = "' pyproject.toml | head -1 | sed -E 's/^version = "([^"]+)"/\1/')
-          if [[ -z "$BASE" ]]; then
-            echo "::error::Could not parse version from pyproject.toml"
+          LATEST_RELEASE=$(git tag --list 'v[0-9]*' --merged HEAD \
+            | grep -E '^v[0-9]+\.[0-9]+\.[0-9]+$' | sort -V | tail -1)
+          if [[ -z "$LATEST_RELEASE" ]]; then
+            echo "::error::No release tag (vX.Y.Z) reachable from HEAD"
             exit 1
           fi
+          BASE="${LATEST_RELEASE#v}"
           MAJOR=$(echo "$BASE" | cut -d. -f1)
           MINOR=$(echo "$BASE" | cut -d. -f2)
           PATCH=$(echo "$BASE" | cut -d. -f3 | sed -E 's/[^0-9].*$//')

.github/workflows/claude-issues.yml

@@ -11,22 +11,33 @@ concurrency:
   group: claude-issues-${{ github.event.issue.number || github.run_id }}
   cancel-in-progress: true
 
+# Least-privilege: only what the issue-fixer job actually needs.
+# id-token (OIDC) is intentionally omitted — claude-code-action@v1 is passed
+# github_token directly, so OIDC is unused here.
 permissions:
   contents: write
   pull-requests: write
   issues: write
-  id-token: write
 
 jobs:
   fix:
     runs-on: ubuntu-latest
-    timeout-minutes: 60
+    timeout-minutes: 15
+    # Security gate: this job reaches secrets.ANTHROPIC_API_KEY and holds a
+    # write-scoped GITHUB_TOKEN. `issues` / `issue_comment` are public,
+    # attacker-controllable events that run in the base-repo context with full
+    # secret access, so the human-triggered paths are restricted to actors with
+    # write-level association (OWNER / MEMBER / COLLABORATOR). This blocks
+    # external / first-time contributors from draining the API budget or
+    # creating branches/PRs, while leaving maintainer use unaffected.
     if: |
       github.event_name == 'workflow_dispatch' ||
       (github.event_name == 'issues' &&
+       contains(fromJSON('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.issue.author_association) &&
        (contains(github.event.issue.labels.*.name, 'bug') ||
         contains(github.event.issue.labels.*.name, 'autofix'))) ||
       (github.event_name == 'issue_comment' &&
+       contains(fromJSON('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.comment.author_association) &&
        !github.event.issue.pull_request &&
        contains(github.event.comment.body, '@claude') &&
        github.actor != 'claude[bot]')

.github/workflows/claude-review.yml

@@ -11,23 +11,33 @@ concurrency:
   group: claude-review-${{ github.event.pull_request.number || github.event.issue.number || github.run_id }}
   cancel-in-progress: true
 
+# Least-privilege: PR review only needs to post comments on the PR.
+# id-token (OIDC) is omitted — claude-code-action@v1 is passed github_token
+# directly, so OIDC is unused here.
 permissions:
   contents: read
   pull-requests: write
   issues: write
-  id-token: write
 
 jobs:
   review:
     runs-on: ubuntu-latest
     timeout-minutes: 30
+    # Security gate: this job reaches secrets.ANTHROPIC_API_KEY. Both
+    # issue_comment and pull_request_review_comment are public,
+    # attacker-controllable events that run in the base-repo context with full
+    # secret access, so the @claude paths are restricted to actors with
+    # write-level association (OWNER / MEMBER / COLLABORATOR). External /
+    # first-time contributors cannot trigger the key; maintainers are unaffected.
     if: |
       github.event_name == 'workflow_dispatch' ||
       (github.event_name == 'issue_comment' &&
+       contains(fromJSON('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.comment.author_association) &&
        github.event.issue.pull_request &&
        contains(github.event.comment.body, '@claude') &&
        github.actor != 'claude[bot]') ||
       (github.event_name == 'pull_request_review_comment' &&
+       contains(fromJSON('["OWNER", "MEMBER", "COLLABORATOR"]'), github.event.comment.author_association) &&
        contains(github.event.comment.body, '@claude') &&
        github.actor != 'claude[bot]')
     steps:

.github/workflows/desktop.yml

@@ -114,6 +114,11 @@ jobs:
 
     steps:
       - uses: actions/checkout@v6
+        with:
+          # Full history + tags so the workflow_dispatch fallback in
+          # "Determine release info" can derive the dev version from the
+          # latest release tag (#526).
+          fetch-depth: 0
 
       - name: Install system dependencies (Linux)
         if: matrix.platform == 'ubuntu-22.04'
@@ -183,7 +188,16 @@ jobs:
             # workflow_dispatch fallback (manual UI dispatch without --ref).
             # Derive a PEP 440 dev version aligned with autotag.yml so we
             # don't burn the X.Y.Z release-version namespace.
-            BASE=$(grep -E '^version = "' pyproject.toml | head -1 | sed -E 's/^version = "([^"]+)"/\1/')
+            # pyproject.toml no longer carries a static version (#526), so the
+            # base comes from the latest plain release tag (vX.Y.Z), matching
+            # autotag.yml. .dev/.rc/desktop-* tags are excluded.
+            LATEST_RELEASE=$(git tag --list 'v[0-9]*' --merged HEAD \
+              | grep -E '^v[0-9]+\.[0-9]+\.[0-9]+$' | sort -V | tail -1)
+            if [[ -z "$LATEST_RELEASE" ]]; then
+              echo "::error::No release tag (vX.Y.Z) reachable from HEAD"
+              exit 1
+            fi
+            BASE="${LATEST_RELEASE#v}"
             MAJOR=$(echo "$BASE" | cut -d. -f1)
             MINOR=$(echo "$BASE" | cut -d. -f2)
             PATCH=$(echo "$BASE" | cut -d. -f3 | sed -E 's/[^0-9].*$//')

.github/workflows/pypi-publish.yml

@@ -12,6 +12,11 @@ on:
         description: 'Tag to publish (e.g. v1.0.2.dev500). Overrides github.ref.'
         required: false
         type: string
+      dry_run:
+        description: 'Dry run: build + validate, then publish to TestPyPI instead of PyPI (no production upload).'
+        required: false
+        default: false
+        type: boolean
 
 permissions:
   contents: read
@@ -67,27 +72,41 @@ jobs:
             exit 1
           }
 
-      - name: Set version from tag
+      - name: Resolve build version from tag
         env:
           REF: ${{ steps.ref.outputs.ref }}
         run: |
           set -euo pipefail
-          # Strip leading "v" if present (e.g. v1.0.2.dev500 -> 1.0.2.dev500)
+          # Strip leading "v" (e.g. v1.0.3.dev825 -> 1.0.3.dev825).
           VERSION="${REF#v}"
-          if [[ -z "$VERSION" ]]; then
-            echo "::error::Could not resolve version from ref '$REF'"
+          if ! [[ "$VERSION" =~ ^[0-9]+\.[0-9]+\.[0-9]+ ]]; then
+            echo "::error::ref '$REF' is not a version tag (expected vX.Y.Z[.devN]); pass -f tag=vX.Y.Z"
             exit 1
           fi
-          sed -i "s/^version = \".*\"/version = \"${VERSION}\"/" pyproject.toml
-          # Sanity check the substitution actually took
-          grep -q "^version = \"${VERSION}\"" pyproject.toml || {
-            echo "::error::sed failed to update pyproject.toml version"
-            exit 1
-          }
-          echo "Building version $VERSION"
+          # pyproject.toml is now dynamic = ["version"] via hatch-vcs (#526), so
+          # there is no static line to sed. setuptools_scm cannot bump custom
+          # `.devN` tags, so we pin the exact build version explicitly — the
+          # published version always equals the pushed tag.
+          echo "SETUPTOOLS_SCM_PRETEND_VERSION=${VERSION}" >> "$GITHUB_ENV"
+          echo "Building version ${VERSION}"
 
       - name: Build package
         run: uv build
 
+      - name: Publish to TestPyPI (dry run)
+        if: ${{ inputs.dry_run }}
+        env:
+          UV_PUBLISH_TOKEN: ${{ secrets.TEST_PYPI_API_TOKEN }}
+        run: |
+          set -euo pipefail
+          if [[ -z "${UV_PUBLISH_TOKEN:-}" ]]; then
+            echo "::warning::TEST_PYPI_API_TOKEN is not set — skipping the TestPyPI upload."
+            echo "Build + twine check passed, which validated version derivation and packaging end to end."
+            echo "To exercise a real upload, add a TEST_PYPI_API_TOKEN secret (or a TestPyPI trusted publisher)."
+            exit 0
+          fi
+          uv publish --publish-url https://test.pypi.org/legacy/
+
       - name: Publish to PyPI
+        if: ${{ !inputs.dry_run }}
         run: uv publish

pyproject.toml

@@ -1,10 +1,10 @@
 [build-system]
-requires = ["hatchling"]
+requires = ["hatchling", "hatch-vcs"]
 build-backend = "hatchling.build"
 
 [project]
 name = "OpenJarvis"
-version = "1.0.2"
+dynamic = ["version"]
 description = "OpenJarvis — modular AI assistant backend with composable intelligence primitives"
 readme = "README.md"
 # Upper bound: numpy 2.2.x (pinned transitively via datasets/pandas) ships no
@@ -154,6 +154,30 @@ Issues = "https://github.com/open-jarvis/OpenJarvis/issues"
 jarvis = "openjarvis.cli:main"
 openjarvis-eval = "openjarvis.evals.cli:main"
 
+# Version is derived from git tags by hatch-vcs (see #526). For source/editable
+# checkouts this yields the true `git describe` version (e.g. 1.0.3.dev109+g<sha>)
+# rather than a stale static string. CI release builds override this with
+# SETUPTOOLS_SCM_PRETEND_VERSION so the published version equals the pushed tag.
+#
+# setuptools_scm cannot bump custom `.devN` tags (only `.dev0`), so the autotag
+# `vX.Y.Z.devN` tags are deliberately EXCLUDED from version derivation here; the
+# base is taken from the latest plain release tag (vX.Y.Z) and the dev distance
+# is computed from commit count since that release.
+[tool.hatch.version]
+source = "vcs"
+
+[tool.hatch.version.raw-options]
+tag_regex = '^v(?P<version>[0-9]+\.[0-9]+\.[0-9]+)$'
+git_describe_command = [
+    "git", "describe", "--dirty", "--tags", "--long",
+    "--match", "v[0-9]*", "--exclude", "*dev*", "--exclude", "*rc*", "--exclude", "desktop-*",
+]
+# Builds without a git checkout (e.g. the `COPY src/ src/` Docker stages, which
+# never include .git) can't run `git describe`. Without a fallback that would
+# hard-fail the build. Mirror the runtime sentinel in src/openjarvis/__init__.py.
+# Such builds can inject the real version via SETUPTOOLS_SCM_PRETEND_VERSION.
+fallback_version = "0.0.0+unknown"
+
 [tool.hatch.build.targets.wheel]
 packages = ["src/openjarvis"]
 

src/openjarvis/core/config.py

@@ -946,8 +946,10 @@ class AgentConfig:
     system_prompt_path: str = ""  # path to system prompt file (.txt, .md)
     context_from_memory: bool = True  # inject relevant memory context into prompts
     default_system_prompt: str = (
-        "You are a helpful AI assistant running locally on the user's own "
-        "hardware through OpenJarvis. You are not a cloud service. Respond "
+        "You are OpenJarvis, a helpful AI assistant running locally on the "
+        "user's own hardware. You are not a cloud service, and you are not "
+        "Claude, ChatGPT, Gemini, or any other branded assistant. If asked "
+        "who or what you are, identify yourself as OpenJarvis. Respond "
         "helpfully, concisely, and accurately."
     )
 

src/openjarvis/engine/cloud.py

@@ -1,4 +1,7 @@
-"""Cloud inference engine — OpenAI, Anthropic, Google, and MiniMax API backends."""
+"""Cloud inference engine.
+
+OpenAI, Anthropic, Google, MiniMax, and DeepSeek API backends.
+"""
 
 from __future__ import annotations
 
@@ -48,6 +51,8 @@ PRICING: Dict[str, tuple[float, float]] = {
     "MiniMax-M2.7-highspeed": (0.60, 2.40),
     "MiniMax-M2.5": (0.30, 1.20),
     "MiniMax-M2.5-highspeed": (0.60, 2.40),
+    "deepseek-v4-flash": (0.27, 1.10),
+    "deepseek-v4-pro": (0.55, 2.19),
 }
 
 # Well-known model IDs per provider
@@ -83,6 +88,10 @@ _MINIMAX_MODELS = [
     "MiniMax-M2.5",
     "MiniMax-M2.5-highspeed",
 ]
+_DEEPSEEK_MODELS = [
+    "deepseek-v4-flash",
+    "deepseek-v4-pro",
+]
 
 # OpenRouter models — prefixed with "openrouter/" so they can be identified
 _OPENROUTER_POPULAR = [
@@ -111,6 +120,10 @@ def _is_minimax_model(model: str) -> bool:
     return model.lower().startswith("minimax")
 
 
+def _is_deepseek_model(model: str) -> bool:
+    return model.lower().startswith("deepseek")
+
+
 def _is_openrouter_model(model: str) -> bool:
     return model.startswith("openrouter/")
 
@@ -127,6 +140,35 @@ def _is_google_model(model: str) -> bool:
     return "gemini" in model.lower() and not _is_openrouter_model(model)
 
 
+# Positive prefix predicate for genuine OpenAI models. Kept in sync with
+# ``server/cloud_router.py:_OPENAI_PREFIXES`` so local-vs-cloud classification
+# agrees across the codebase. Used by ``_client_for_model``/``can_serve`` so the
+# cloud engine never claims it can serve an unrecognized (e.g. local Ollama)
+# model name just because an OpenAI key happens to be present (see #335).
+_OPENAI_PREFIXES = ("gpt-", "chatgpt-", "o1", "o3", "o4")
+
+
+def _is_openai_model(model: str) -> bool:
+    """True only for genuine OpenAI models (gpt-*, chatgpt-*, o1/o3/o4 series).
+
+    Defined positively so that an unrecognized model name (a local Ollama model
+    like ``qwen3.5:0.8b``, or a typo) is NOT treated as an OpenAI model. This is
+    the routing surface ``can_serve`` relies on; ``generate``/``stream`` keep
+    their OpenAI fall-through so an explicitly-requested unknown cloud model
+    still errors loudly at call time.
+
+    Caveat: a user may repoint the OpenAI client at an OpenAI-compatible server
+    (vLLM/LM Studio) via ``OPENAI_BASE_URL`` and legitimately serve non-gpt
+    names. That path is undocumented/untested in this engine; if it is added,
+    this predicate (or ``_client_for_model``) should treat a configured custom
+    base_url as "serves anything".
+    """
+    m = model.lower()
+    if m in (name.lower() for name in _OPENAI_MODELS):
+        return True
+    return m.startswith(_OPENAI_PREFIXES)
+
+
 def _is_openai_reasoning_model(model: str) -> bool:
     """Check if model is an OpenAI reasoning model that restricts temperature."""
     m = model.lower()
@@ -269,7 +311,7 @@ def _convert_tools_to_google(
 
 @EngineRegistry.register("cloud")
 class CloudEngine(InferenceEngine):
-    """Cloud inference via OpenAI, Anthropic, Google, and MiniMax SDKs."""
+    """Cloud inference via OpenAI, Anthropic, Google, MiniMax, and DeepSeek SDKs."""
 
     engine_id = "cloud"
     is_cloud = True
@@ -280,6 +322,7 @@ class CloudEngine(InferenceEngine):
         self._google_client: Any = None
         self._openrouter_client: Any = None
         self._minimax_client: Any = None
+        self._deepseek_client: Any = None
         self._codex_client: Any = None
         # Gemini thought_signatures: tool_call_id -> signature bytes
         self._thought_sigs: Dict[str, bytes] = {}
@@ -332,6 +375,17 @@ class CloudEngine(InferenceEngine):
                 )
             except ImportError:
                 pass
+        deepseek_key = os.environ.get("DEEPSEEK_API_KEY")
+        if deepseek_key:
+            try:
+                import openai
+
+                self._deepseek_client = openai.OpenAI(
+                    base_url="https://api.deepseek.com/v1",
+                    api_key=deepseek_key,
+                )
+            except ImportError:
+                pass
         # Codex — uses the OpenAI Responses API.
         # Supports both standard API keys (api.openai.com) and ChatGPT
         # OAuth tokens (chatgpt.com) via OPENAI_CODEX_BASE_URL override.
@@ -985,6 +1039,56 @@ class CloudEngine(InferenceEngine):
             ]
         return result
 
+    def _generate_deepseek(
+        self,
+        messages: Sequence[Message],
+        *,
+        model: str,
+        temperature: float,
+        max_tokens: int,
+        **kwargs: Any,
+    ) -> Dict[str, Any]:
+        if self._deepseek_client is None:
+            raise EngineConnectionError(
+                "DeepSeek client not available — set DEEPSEEK_API_KEY"
+            )
+        kwargs.pop("response_format", None)
+        create_kwargs: Dict[str, Any] = {
+            "model": model,
+            "messages": messages_to_dicts(messages),
+            "max_tokens": max_tokens,
+            "temperature": temperature,
+        }
+        t0 = time.monotonic()
+        resp = self._deepseek_client.chat.completions.create(**create_kwargs)
+        elapsed = time.monotonic() - t0
+        choice = resp.choices[0]
+        usage = resp.usage
+        prompt_tokens = usage.prompt_tokens if usage else 0
+        completion_tokens = usage.completion_tokens if usage else 0
+        result: Dict[str, Any] = {
+            "content": choice.message.content or "",
+            "usage": {
+                "prompt_tokens": prompt_tokens,
+                "completion_tokens": completion_tokens,
+                "total_tokens": (usage.total_tokens if usage else 0),
+            },
+            "model": resp.model,
+            "finish_reason": choice.finish_reason or "stop",
+            "cost_usd": estimate_cost(model, prompt_tokens, completion_tokens),
+            "ttft": elapsed,
+        }
+        if hasattr(choice.message, "tool_calls") and choice.message.tool_calls:
+            result["tool_calls"] = [
+                {
+                    "id": tc.id,
+                    "name": tc.function.name,
+                    "arguments": tc.function.arguments,
+                }
+                for tc in choice.message.tool_calls
+            ]
+        return result
+
     def generate(
         self,
         messages: Sequence[Message],
@@ -1006,6 +1110,8 @@ class CloudEngine(InferenceEngine):
             return self._generate_openrouter(messages, **kw)
         if _is_minimax_model(model):
             return self._generate_minimax(messages, **kw)
+        if _is_deepseek_model(model):
+            return self._generate_deepseek(messages, **kw)
         if _is_anthropic_model(model):
             return self._generate_anthropic(messages, **kw)
         if _is_google_model(model):
@@ -1036,6 +1142,9 @@ class CloudEngine(InferenceEngine):
         elif _is_minimax_model(model):
             async for token in self._stream_minimax(messages, **kw):
                 yield token
+        elif _is_deepseek_model(model):
+            async for token in self._stream_deepseek(messages, **kw):
+                yield token
         elif _is_anthropic_model(model):
             async for token in self._stream_anthropic(messages, **kw):
                 yield token
@@ -1254,6 +1363,30 @@ class CloudEngine(InferenceEngine):
             if delta and delta.content:
                 yield delta.content
 
+    async def _stream_deepseek(
+        self,
+        messages: Sequence[Message],
+        *,
+        model: str,
+        temperature: float,
+        max_tokens: int,
+        **kwargs: Any,
+    ) -> AsyncIterator[str]:
+        if self._deepseek_client is None:
+            raise EngineConnectionError("DeepSeek client not available")
+        create_kwargs: Dict[str, Any] = {
+            "model": model,
+            "messages": messages_to_dicts(messages),
+            "max_tokens": max_tokens,
+            "temperature": temperature,
+            "stream": True,
+        }
+        resp = self._deepseek_client.chat.completions.create(**create_kwargs)
+        for chunk in resp:
+            delta = chunk.choices[0].delta if chunk.choices else None
+            if delta and delta.content:
+                yield delta.content
+
     # -- stream_full: rich streaming with tool_calls support ----------------
 
     async def _stream_full_openai(
@@ -1307,6 +1440,18 @@ class CloudEngine(InferenceEngine):
                 "stream": True,
                 **kwargs,
             }
+        elif _is_deepseek_model(model):
+            client = self._deepseek_client
+            if client is None:
+                raise EngineConnectionError("DeepSeek client not available")
+            create_kwargs = {
+                "model": model,
+                "messages": messages_to_dicts(messages),
+                "max_tokens": max_tokens,
+                "temperature": temperature,
+                "stream": True,
+                **kwargs,
+            }
         else:
             client = self._openai_client
             if client is None:
@@ -1473,24 +1618,40 @@ class CloudEngine(InferenceEngine):
             models.extend(_OPENROUTER_POPULAR)
         if self._minimax_client is not None:
             models.extend(_MINIMAX_MODELS)
+        if self._deepseek_client is not None:
+            models.extend(_DEEPSEEK_MODELS)
         if self._codex_client is not None:
             models.extend(_CODEX_MODELS)
         return models
 
     def _client_for_model(self, model: str) -> Any:
         """Return the provider client ``generate``/``stream`` will dispatch to
-        for *model* (mirrors the routing in those methods)."""
+        for *model*, or ``None`` for a model this engine cannot route.
+
+        Mirrors the routing in ``generate``/``stream``, but is intentionally
+        *stricter* on the OpenAI fall-through: only genuine OpenAI models map to
+        the OpenAI client. Unrecognized names (e.g. a local Ollama model like
+        ``qwen3.5:0.8b``) return ``None`` so ``can_serve`` declines them and the
+        cloud engine is not mis-selected as a fallback when the local engine is
+        transiently down and any (even dummy) ``OPENAI_API_KEY`` is set (#335).
+        ``generate``/``stream`` keep their OpenAI fall-through, so an
+        explicitly-requested unknown cloud model still fails loudly at call time.
+        """
         if _is_codex_model(model):
             return self._codex_client
         if _is_openrouter_model(model):
             return self._openrouter_client
         if _is_minimax_model(model):
             return self._minimax_client
+        if _is_deepseek_model(model):
+            return self._deepseek_client
         if _is_anthropic_model(model):
             return self._anthropic_client
         if _is_google_model(model):
             return self._google_client
-        return self._openai_client
+        if _is_openai_model(model):
+            return self._openai_client
+        return None
 
     def can_serve(self, model: str) -> bool:
         """Return ``True`` only if the provider client for *model* exists.
@@ -1512,6 +1673,7 @@ class CloudEngine(InferenceEngine):
             or self._google_client is not None
             or self._openrouter_client is not None
             or self._minimax_client is not None
+            or self._deepseek_client is not None
             or self._codex_client is not None
         )
 

src/openjarvis/server/routes.py

@@ -43,6 +43,51 @@ def _to_messages(chat_messages) -> list[Message]:
     return messages
 
 
+def _ensure_identity_prompt(messages: list[Message], app_config) -> list[Message]:
+    """Prepend OpenJarvis's identity system prompt when the client omits one.
+
+    The desktop UI's chat backend posts only user/assistant turns to
+    ``/v1/chat/completions`` (see ``frontend/.../Chat/InputArea.tsx``), so
+    nothing grounds the model's identity. Without a system prompt the model
+    answers from its training identity (e.g. "I'm Claude", "I am Qwen"),
+    which is what #540 reported. The CLI paths inject this via
+    ``SystemPromptBuilder`` / ``BaseAgent``; the engine-direct server paths
+    did not. This mirrors the agent fallback in ``agents/_stubs.py``.
+
+    If any message already carries a system role, the caller has supplied
+    their own grounding and we leave the list untouched (no double-prompting).
+
+    Resolution of the identity text: ``app_config.agent.default_system_prompt``
+    when a config is wired onto ``app.state``; otherwise fall back to
+    ``load_config()``. Config resolution is wrapped so a broken/missing
+    config degrades to "no injection" rather than crashing the endpoint, but
+    the failure is logged (per REVIEW.md — never silently swallow).
+    """
+    if any(m.role == Role.SYSTEM for m in messages):
+        return messages
+
+    prompt = ""
+    try:
+        if app_config is not None:
+            prompt = app_config.agent.default_system_prompt or ""
+        else:
+            from openjarvis.core.config import load_config
+
+            prompt = load_config().agent.default_system_prompt or ""
+    except Exception:
+        logging.getLogger("openjarvis.server").debug(
+            "Identity system prompt resolution failed; "
+            "serving request without identity grounding",
+            exc_info=True,
+        )
+        return messages
+
+    if not prompt:
+        return messages
+
+    return [Message(role=Role.SYSTEM, content=prompt), *messages]
+
+
 @router.post("/v1/chat/completions")
 async def chat_completions(request_body: ChatCompletionRequest, request: Request):
     """Handle chat completion requests (streaming and non-streaming)."""
@@ -149,7 +194,7 @@ async def chat_completions(request_body: ChatCompletionRequest, request: Request
         # from the engine for true real-time output.
         if request_body.tools:
             return await _handle_stream_tools(
-                engine, model, request_body, complexity_info
+                engine, model, request_body, complexity_info, app_config=config
             )
         return await _handle_stream(
             engine,
@@ -157,6 +202,7 @@ async def chat_completions(request_body: ChatCompletionRequest, request: Request
             request_body,
             complexity_info,
             trace_store=getattr(request.app.state, "trace_store", None),
+            app_config=config,
         )
 
     # Non-streaming: use agent if available, otherwise direct engine call.
@@ -192,6 +238,7 @@ async def chat_completions(request_body: ChatCompletionRequest, request: Request
         request_body,
         bus=bus,
         complexity_info=complexity_info,
+        app_config=config,
     )
 
 
@@ -201,9 +248,11 @@ def _handle_direct(
     req: ChatCompletionRequest,
     bus=None,
     complexity_info=None,
+    app_config=None,
 ) -> ChatCompletionResponse:
     """Direct engine call without agent."""
     messages = _to_messages(req.messages)
+    messages = _ensure_identity_prompt(messages, app_config)
     kwargs: dict[str, Any] = {}
     if req.tools:
         kwargs["tools"] = req.tools
@@ -380,6 +429,8 @@ async def _handle_stream_tools(
     model: str,
     req: ChatCompletionRequest,
     complexity_info=None,
+    *,
+    app_config=None,
 ):
     """Stream a raw OpenAI-compat function-calling response via SSE.
 
@@ -397,6 +448,7 @@ async def _handle_stream_tools(
     from openjarvis.server.cloud_router import is_cloud_model
 
     messages = _to_messages(req.messages)
+    messages = _ensure_identity_prompt(messages, app_config)
     chunk_id = f"chatcmpl-{uuid.uuid4().hex[:12]}"
     use_cloud = is_cloud_model(model)
 
@@ -491,6 +543,7 @@ async def _handle_stream(
     complexity_info=None,
     *,
     trace_store=None,
+    app_config=None,
 ):
     """Stream response using SSE format.
 
@@ -509,6 +562,7 @@ async def _handle_stream(
     )
 
     messages = _to_messages(req.messages)
+    messages = _ensure_identity_prompt(messages, app_config)
     chunk_id = f"chatcmpl-{uuid.uuid4().hex[:12]}"
 
     # Last user message — recorded as the trace query.

tests/core/test_config.py

@@ -237,6 +237,14 @@ class TestAgentConfigNew:
             or isinstance(getattr(ac.__class__, "temperature", None), property) is False
         )
 
+    def test_default_system_prompt_anchors_identity(self) -> None:
+        """#540: the hardened wording must name OpenJarvis and explicitly
+        deny the model's training identity so distilled models stop
+        claiming to be Claude/ChatGPT/etc."""
+        prompt = AgentConfig().default_system_prompt
+        assert "OpenJarvis" in prompt
+        assert "not Claude" in prompt
+
 
 class TestNestedEngineConfig:
     def test_nested_access(self) -> None:
@@ -561,6 +569,7 @@ class TestWhatsAppBaileysChannelConfig:
 
 def test_mining_config_absent_means_none(tmp_path):
     from openjarvis.core.config import load_config
+
     cfg_path = tmp_path / "config.toml"
     cfg_path.write_text("")  # empty config
     cfg = load_config(cfg_path)

tests/engine/test_cloud.py

@@ -9,9 +9,13 @@ import pytest
 
 from openjarvis.core.registry import EngineRegistry
 from openjarvis.core.types import Message, Role
+from openjarvis.engine._base import EngineConnectionError
 from openjarvis.engine.cloud import (
     CloudEngine,
     _is_codex_model,
+    _is_deepseek_model,
+    _is_openai_model,
+    _is_openrouter_model,
     estimate_cost,
 )
 
@@ -457,6 +461,7 @@ class TestCloudEngineCanServe:
             "_google_client",
             "_openrouter_client",
             "_minimax_client",
+            "_deepseek_client",
             "_codex_client",
         ):
             setattr(eng, name, clients.get(name))
@@ -469,7 +474,154 @@ class TestCloudEngineCanServe:
         assert eng.can_serve("gemini-2.5-pro") is False
         assert eng.can_serve("openrouter/openai/gpt-4o") is False
 
+    def test_openai_key_does_not_claim_local_models(self) -> None:
+        """#335: with only the OpenAI client set (e.g. a present-but-dummy
+        OPENAI_API_KEY), the cloud engine must NOT claim it can serve a local
+        Ollama model name — otherwise it gets mis-selected as a fallback when
+        the local engine is transiently down and dies with "OpenAI client not
+        available". Only genuine OpenAI models route to the OpenAI client.
+        """
+        eng = self._engine(_openai_client=object())
+        # Local Ollama / unrecognized names are NOT served by the cloud engine.
+        assert eng.can_serve("qwen3.5:0.8b") is False
+        assert eng.can_serve("llama3.2") is False
+        assert eng.can_serve("mistral") is False
+        assert eng.can_serve("phi3:mini") is False
+        assert eng.can_serve("some-unknown-model") is False
+        # Genuine OpenAI families still served.
+        assert eng.can_serve("gpt-4o") is True
+        assert eng.can_serve("gpt-5.4") is True
+        assert eng.can_serve("o3-mini") is True
+
+    def test_unknown_model_not_served_even_with_all_clients(self) -> None:
+        """#335: an unrecognized model is declined regardless of how many
+        provider clients are configured — it never falls through to OpenAI."""
+        eng = self._engine(
+            _openai_client=object(),
+            _anthropic_client=object(),
+            _google_client=object(),
+            _minimax_client=object(),
+            _deepseek_client=object(),
+        )
+        assert eng.can_serve("qwen3.5:0.8b") is False
+        assert eng.can_serve("totally-made-up") is False
+
     def test_anthropic_only_serves_anthropic_models(self) -> None:
         eng = self._engine(_anthropic_client=object())
         assert eng.can_serve("claude-sonnet-4") is True
         assert eng.can_serve("gpt-4o") is False
+
+    def test_deepseek_only_serves_deepseek_models(self) -> None:
+        """The DeepSeek client serves deepseek-* models (and only those)."""
+        eng = self._engine(_deepseek_client=object())
+        assert eng.can_serve("deepseek-v4-flash") is True
+        assert eng.can_serve("deepseek-v4-pro") is True
+        assert eng.can_serve("DeepSeek-V4-Pro") is True  # case-insensitive
+        assert eng.can_serve("gpt-4o") is False
+        # OpenRouter-prefixed deepseek is NOT the direct DeepSeek provider.
+        assert eng.can_serve("openrouter/deepseek/deepseek-r1") is False
+
+
+class TestCloudEngineDeepSeek:
+    """PR #504: DeepSeek as a first-class cloud provider (OpenAI-compatible)."""
+
+    def test_is_deepseek_model_predicate(self) -> None:
+        assert _is_deepseek_model("deepseek-v4-flash") is True
+        assert _is_deepseek_model("deepseek-v4-pro") is True
+        assert _is_deepseek_model("DeepSeek-V4-Pro") is True  # case-insensitive
+        assert _is_deepseek_model("gpt-4o") is False
+        # No predicate collision: openrouter/deepseek/* belongs to OpenRouter.
+        assert _is_deepseek_model("openrouter/deepseek/deepseek-r1") is False
+        assert _is_openrouter_model("openrouter/deepseek/deepseek-r1") is True
+        # And a deepseek name is not mistaken for an OpenAI model.
+        assert _is_openai_model("deepseek-v4-pro") is False
+
+    def test_pricing_entries_present(self) -> None:
+        assert estimate_cost("deepseek-v4-flash", 1_000_000, 1_000_000) == (
+            pytest.approx(1.37)  # 0.27 + 1.10
+        )
+        assert estimate_cost("deepseek-v4-pro", 1_000_000, 1_000_000) == (
+            pytest.approx(2.74)  # 0.55 + 2.19
+        )
+
+    def test_init_wires_deepseek_client(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        """DEEPSEEK_API_KEY builds an openai client pointed at api.deepseek.com."""
+        for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY"):
+            monkeypatch.delenv(var, raising=False)
+        monkeypatch.setenv("DEEPSEEK_API_KEY", "sk-deepseek-test")
+
+        fake_openai = mock.MagicMock()
+        with mock.patch.dict("sys.modules", {"openai": fake_openai}):
+            EngineRegistry.register_value("cloud", CloudEngine)
+            engine = CloudEngine()
+
+        fake_openai.OpenAI.assert_any_call(
+            base_url="https://api.deepseek.com/v1",
+            api_key="sk-deepseek-test",
+        )
+        assert engine._deepseek_client is not None
+
+    def test_health_and_list_models_gated_on_deepseek_key(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY"):
+            monkeypatch.delenv(var, raising=False)
+        monkeypatch.setenv("DEEPSEEK_API_KEY", "sk-deepseek-test")
+
+        fake_openai = mock.MagicMock()
+        with mock.patch.dict("sys.modules", {"openai": fake_openai}):
+            EngineRegistry.register_value("cloud", CloudEngine)
+            engine = CloudEngine()
+
+        assert engine.health() is True
+        models = engine.list_models()
+        assert "deepseek-v4-flash" in models
+        assert "deepseek-v4-pro" in models
+        # can_serve must agree with list_models (regression for the missing
+        # _client_for_model deepseek branch flagged by the #504 verifier).
+        assert engine.can_serve("deepseek-v4-pro") is True
+        assert engine.can_serve("deepseek-v4-flash") is True
+
+    def test_generate_routes_to_deepseek_client(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY", "DEEPSEEK_API_KEY"):
+            monkeypatch.delenv(var, raising=False)
+
+        fake_usage = SimpleNamespace(
+            prompt_tokens=7, completion_tokens=3, total_tokens=10
+        )
+        fake_choice = SimpleNamespace(
+            message=SimpleNamespace(content="ds-hello"),
+            finish_reason="stop",
+        )
+        fake_resp = SimpleNamespace(
+            choices=[fake_choice], usage=fake_usage, model="deepseek-v4-pro"
+        )
+        fake_client = mock.MagicMock()
+        fake_client.chat.completions.create.return_value = fake_resp
+
+        EngineRegistry.register_value("cloud", CloudEngine)
+        engine = CloudEngine()
+        engine._deepseek_client = fake_client
+
+        result = engine.generate(
+            [Message(role=Role.USER, content="Hi")], model="deepseek-v4-pro"
+        )
+        assert result["content"] == "ds-hello"
+        assert result["usage"]["prompt_tokens"] == 7
+        # Routed to the DeepSeek client, not OpenAI.
+        fake_client.chat.completions.create.assert_called_once()
+
+    def test_generate_without_client_raises(
+        self, monkeypatch: pytest.MonkeyPatch
+    ) -> None:
+        for var in ("OPENAI_API_KEY", "ANTHROPIC_API_KEY", "DEEPSEEK_API_KEY"):
+            monkeypatch.delenv(var, raising=False)
+        EngineRegistry.register_value("cloud", CloudEngine)
+        engine = CloudEngine()
+        assert engine._deepseek_client is None
+        with pytest.raises(EngineConnectionError):
+            engine.generate(
+                [Message(role=Role.USER, content="Hi")], model="deepseek-v4-pro"
+            )

tests/engine/test_discovery.py

@@ -204,6 +204,54 @@ class TestGetEngine:
         assert result is not None
         assert result[0] == "local"
 
+    def test_dummy_openai_key_does_not_misroute_local_model(
+        self, monkeypatch: object
+    ) -> None:
+        """#335: a present-but-dummy OPENAI_API_KEY + a down local engine must
+        NOT cause a local Ollama model to be routed to the cloud engine.
+
+        Before the fix, CloudEngine.can_serve('qwen3.5:0.8b') returned True
+        whenever any OpenAI client existed (even a junk key), so get_engine
+        picked 'cloud' and the request later died with "OpenAI client not
+        available". With the strict _client_for_model fall-through it returns
+        None for unrecognized names, so get_engine declines cloud and (with the
+        local engine down) returns None — surfacing a "start your local engine"
+        failure instead.
+        """
+        from openjarvis.engine.cloud import CloudEngine
+
+        _reg("ollama", "ollama")
+        EngineRegistry.register_value("cloud", CloudEngine)
+
+        cfg = JarvisConfig()
+        cfg.engine.default = "ollama"
+
+        def _make(k, c):  # noqa: ANN001
+            if k == "ollama":
+                # Local engine is down (post-restart Ollama not yet up).
+                return _FakeEngine(healthy=False, models=["qwen3.5:0.8b"])
+            # Real CloudEngine with only a (dummy) OpenAI client wired.
+            eng = CloudEngine.__new__(CloudEngine)
+            for name in (
+                "_openai_client",
+                "_anthropic_client",
+                "_google_client",
+                "_openrouter_client",
+                "_minimax_client",
+                "_deepseek_client",
+                "_codex_client",
+            ):
+                setattr(eng, name, object() if name == "_openai_client" else None)
+            return eng
+
+        with mock.patch(
+            "openjarvis.engine._discovery._make_engine",
+            side_effect=_make,
+        ):
+            result = get_engine(cfg, model="qwen3.5:0.8b")
+        # Cloud must NOT be selected for a local model name.
+        assert result is None
+
     def test_model_none_preserves_model_agnostic_selection(self) -> None:
         """model=None keeps the legacy behaviour: first healthy engine wins."""
         _reg("primary", "primary")

tests/server/test_routes.py

@@ -487,6 +487,167 @@ class TestChatCompletions:
         assert data["choices"][0]["finish_reason"] == "stop"
 
 
+# ---------------------------------------------------------------------------
+# Identity system-prompt injection (#540)
+# ---------------------------------------------------------------------------
+
+
+def _make_capturing_engine(captured: list):
+    """Like ``_make_engine`` but records the messages each path receives.
+
+    ``engine.generate`` is a MagicMock so ``call_args`` works on the
+    direct/non-stream path. ``engine.stream`` / ``engine.stream_full`` are
+    plain async-generator FUNCTIONS, so they capture their ``messages``
+    argument into the shared *captured* list from inside the generator body
+    (``call_args`` does not apply to plain functions).
+    """
+    engine = MagicMock()
+    engine.engine_id = "mock"
+    engine.health.return_value = True
+    engine.list_models.return_value = ["test-model"]
+    engine.generate.return_value = {
+        "content": "ok",
+        "usage": {"prompt_tokens": 5, "completion_tokens": 3, "total_tokens": 8},
+        "model": "test-model",
+        "finish_reason": "stop",
+    }
+
+    async def mock_stream(messages, *, model, temperature=0.7, max_tokens=1024, **kw):
+        captured.append(messages)
+        for token in ["Hello", " ", "world"]:
+            yield token
+
+    async def mock_stream_full(
+        messages, *, model, temperature=0.7, max_tokens=1024, **kw
+    ):
+        from openjarvis.engine._stubs import StreamChunk
+
+        captured.append(messages)
+        yield StreamChunk(content="ok", finish_reason="stop")
+
+    engine.stream = mock_stream
+    engine.stream_full = mock_stream_full
+    return engine
+
+
+class TestIdentityPromptInjection:
+    """Regression for #540.
+
+    The desktop UI posts only user/assistant turns to the
+    OpenAI-compatible ``/v1/chat/completions`` endpoint, so the engine never
+    saw OpenJarvis's identity system prompt and the model answered from its
+    training identity ("I'm Claude", "I am Qwen", ...). The engine-direct
+    server handlers must now inject ``agent.default_system_prompt`` whenever
+    the client omits a system message — and must NOT inject a second one when
+    the client already supplies their own.
+    """
+
+    def test_stream_injects_identity_when_absent(self):
+        captured: list = []
+        engine = _make_capturing_engine(captured)
+        client = TestClient(create_app(engine, "test-model"))
+
+        resp = client.post(
+            "/v1/chat/completions",
+            json={
+                "model": "test-model",
+                "messages": [{"role": "user", "content": "who are you?"}],
+                "stream": True,
+            },
+        )
+        assert resp.status_code == 200
+        # Drain the stream so the generator body runs and records messages.
+        _ = resp.text
+        assert captured, "engine.stream was never called"
+        msgs = captured[-1]
+        assert msgs[0].role.value == "system"
+        assert "OpenJarvis" in msgs[0].content
+
+    def test_stream_no_double_injection_when_client_supplies_system(self):
+        captured: list = []
+        engine = _make_capturing_engine(captured)
+        client = TestClient(create_app(engine, "test-model"))
+
+        resp = client.post(
+            "/v1/chat/completions",
+            json={
+                "model": "test-model",
+                "messages": [
+                    {"role": "system", "content": "Be terse."},
+                    {"role": "user", "content": "who are you?"},
+                ],
+                "stream": True,
+            },
+        )
+        assert resp.status_code == 200
+        _ = resp.text
+        msgs = captured[-1]
+        system_msgs = [m for m in msgs if m.role.value == "system"]
+        assert len(system_msgs) == 1
+        assert system_msgs[0].content == "Be terse."
+
+    def test_direct_injects_identity_when_absent(self):
+        captured: list = []
+        engine = _make_capturing_engine(captured)
+        # No agent -> non-stream request goes through _handle_direct.
+        client = TestClient(create_app(engine, "test-model"))
+
+        resp = client.post(
+            "/v1/chat/completions",
+            json={
+                "model": "test-model",
+                "messages": [{"role": "user", "content": "who are you?"}],
+            },
+        )
+        assert resp.status_code == 200
+        assert engine.generate.called
+        msgs = engine.generate.call_args.args[0]
+        assert msgs[0].role.value == "system"
+        assert "OpenJarvis" in msgs[0].content
+
+    def test_direct_no_double_injection_when_client_supplies_system(self):
+        captured: list = []
+        engine = _make_capturing_engine(captured)
+        client = TestClient(create_app(engine, "test-model"))
+
+        resp = client.post(
+            "/v1/chat/completions",
+            json={
+                "model": "test-model",
+                "messages": [
+                    {"role": "system", "content": "Be terse."},
+                    {"role": "user", "content": "who are you?"},
+                ],
+            },
+        )
+        assert resp.status_code == 200
+        msgs = engine.generate.call_args.args[0]
+        system_msgs = [m for m in msgs if m.role.value == "system"]
+        assert len(system_msgs) == 1
+        assert system_msgs[0].content == "Be terse."
+
+    def test_stream_tools_injects_identity_when_absent(self):
+        captured: list = []
+        engine = _make_capturing_engine(captured)
+        client = TestClient(create_app(engine, "test-model"))
+
+        resp = client.post(
+            "/v1/chat/completions",
+            json={
+                "model": "test-model",
+                "messages": [{"role": "user", "content": "who are you?"}],
+                "tools": [{"type": "function", "function": {"name": "calc"}}],
+                "stream": True,
+            },
+        )
+        assert resp.status_code == 200
+        _ = resp.text
+        assert captured, "engine.stream_full was never called"
+        msgs = captured[-1]
+        assert msgs[0].role.value == "system"
+        assert "OpenJarvis" in msgs[0].content
+
+
 # ---------------------------------------------------------------------------
 # Models endpoint tests
 # ---------------------------------------------------------------------------