feat(providers): add LLM sampling controls

Signed-off-by: Deepak Jain <deepujain@gmail.com>

Author: deepujain

.env.example

@@ -23,6 +23,11 @@ SKILLSPECTOR_REASONING_EFFORT=
 # Optional language for human-readable LLM finding text. Machine-readable values
 # such as rule IDs and severity values remain unchanged.
 SKILLSPECTOR_OUTPUT_LANGUAGE=
+# Optional sampling controls. Temperature is supported by hosted providers;
+# seed is forwarded only to OpenAI-compatible and Azure OpenAI endpoints.
+# Unset or blank values preserve provider defaults.
+SKILLSPECTOR_TEMPERATURE=                                    # range: 0..1
+SKILLSPECTOR_SEED=                                           # integer
 
 # For SKILLSPECTOR_PROVIDER=anthropic.
 ANTHROPIC_API_KEY=

README.md

@@ -585,6 +585,8 @@ Issues (2)
 | `OPENAI_BASE_URL` | Override the OpenAI endpoint (e.g. point at Ollama). | Optional |
 | `SKILLSPECTOR_REASONING_EFFORT` | Optional provider- and model-dependent reasoning-effort setting. Non-empty values are trimmed and passed through unchanged; unset or blank preserves provider-default behavior. | Optional |
 | `SKILLSPECTOR_OUTPUT_LANGUAGE` | Short, single-line language label (letters, numbers, spaces, `_`, or `-`; maximum 64 characters) for human-readable LLM finding text such as messages, explanations, and remediation. Rule IDs, severity values, paths, code, and other machine-readable values remain unchanged. Unset, blank, or invalid values preserve the default output language. | Optional |
+| `SKILLSPECTOR_TEMPERATURE` | Optional sampling temperature from `0` to `1` for hosted providers. Unset or blank preserves the provider default. Lower values can reduce run-to-run variation but do not guarantee identical output. | Optional |
+| `SKILLSPECTOR_SEED` | Optional integer sampling seed for OpenAI-compatible and Azure OpenAI providers. Other hosted providers and CLI providers do not receive it. Provider support remains model-dependent. | Optional |
 | `ANTHROPIC_API_KEY` | Credential for the Anthropic provider (`SKILLSPECTOR_PROVIDER=anthropic`). | Required for LLM analysis when `SKILLSPECTOR_PROVIDER=anthropic` |
 | `ANTHROPIC_BASE_URL` | Override the native Anthropic endpoint (default: `https://api.anthropic.com`). | Optional |
 | `ANTHROPIC_PROXY_ENDPOINT_URL` | Full endpoint URL for the Anthropic proxy provider (Vertex-style raw-predict). | Required when `SKILLSPECTOR_PROVIDER=anthropic_proxy` |

docs/DEVELOPMENT.md

@@ -38,6 +38,8 @@ make install-dev
   - **Provider credential**: depends on the active provider — `NVIDIA_INFERENCE_KEY` (NVIDIA), `OPENAI_API_KEY` (OpenAI), or `ANTHROPIC_API_KEY` (Anthropic). See [llm_utils.py](../src/skillspector/llm_utils.py).
   - **`OPENAI_BASE_URL`**: Override the OpenAI endpoint (e.g. point at Ollama).
   - **`SKILLSPECTOR_MODEL`**: Override default model; see [constants.py](../src/skillspector/constants.py).
+  - **`SKILLSPECTOR_TEMPERATURE`**: Optional hosted-provider sampling temperature from `0` to `1`.
+  - **`SKILLSPECTOR_SEED`**: Optional integer seed for OpenAI-compatible and Azure OpenAI providers.
 
 - **Logging**: Internal/operational logging uses the stdlib `logging` module. User-facing output (report body, errors, progress) uses Rich `console.print()`.
   - **Env**: `SKILLSPECTOR_LOG_LEVEL` (DEBUG, INFO, WARNING, ERROR). Default is `"WARNING"` (defined in [constants.py](../src/skillspector/constants.py)).
@@ -300,6 +302,8 @@ Copy [.env.example](../.env.example) to `.env` in the project root and set value
 | `OPENAI_BASE_URL` | Override the OpenAI endpoint (e.g. point at Ollama). | `http://localhost:11434/v1` |
 | `SKILLSPECTOR_REASONING_EFFORT` | Optional provider- and model-dependent reasoning-effort setting. Non-empty values are trimmed and passed through unchanged; unset or blank preserves provider-default behavior. | `high` |
 | `SKILLSPECTOR_OUTPUT_LANGUAGE` | Optional short, single-line language label (letters, numbers, spaces, `_`, or `-`; maximum 64 characters) for human-readable LLM finding text. Rule IDs, severity values, paths, code, and other machine-readable values remain unchanged. Unset, blank, or invalid values preserve the default output language. | `Japanese` |
+| `SKILLSPECTOR_TEMPERATURE` | Optional sampling temperature from `0` to `1` for hosted providers. Unset or blank preserves provider defaults. Lower values reduce variation but do not guarantee identical output. | `0` |
+| `SKILLSPECTOR_SEED` | Optional integer sampling seed for OpenAI-compatible and Azure OpenAI providers. Provider/model support is best-effort; CLI providers ignore it. | `42` |
 | `ANTHROPIC_API_KEY` | Credential for `SKILLSPECTOR_PROVIDER=anthropic`. | `sk-ant-...` |
 | `SKILLSPECTOR_MODEL` | Override the active provider's bundled default model (see [README.md](../README.md) for per-provider defaults). For `claude_cli`, this is passed as `--model` to the `claude` binary. | `gpt-5.2` |
 

src/skillspector/providers/anthropic/provider.py

@@ -32,7 +32,7 @@
 from pydantic import SecretStr
 
 from skillspector.providers import registry
-from skillspector.providers.chat_models import resolve_reasoning_effort
+from skillspector.providers.chat_models import resolve_reasoning_effort, resolve_sampling_parameters
 
 # Default endpoint; overridden by ``ANTHROPIC_BASE_URL`` when set.
 ANTHROPIC_BASE_URL = "https://api.anthropic.com"
@@ -80,6 +80,7 @@ def create_chat_model(
         effort = resolve_reasoning_effort()
         if effort is not None:
             kwargs["effort"] = effort
+        kwargs.update(resolve_sampling_parameters())
         return ChatAnthropic(**kwargs)
 
     def get_context_length(self, model: str) -> int | None:

src/skillspector/providers/anthropic_proxy/provider.py

@@ -53,7 +53,7 @@
 from pydantic import SecretStr
 
 from skillspector.providers import registry
-from skillspector.providers.chat_models import resolve_reasoning_effort
+from skillspector.providers.chat_models import resolve_reasoning_effort, resolve_sampling_parameters
 
 REGISTRY_PATH = str(Path(__file__).with_name("model_registry.yaml"))
 
@@ -244,6 +244,7 @@ def create_chat_model(
         effort = resolve_reasoning_effort()
         if effort is not None:
             kwargs["effort"] = effort
+        kwargs.update(resolve_sampling_parameters())
         return _ChatAnthropicProxy(**kwargs)
 
     def get_context_length(self, model: str) -> int | None:

src/skillspector/providers/azure_openai/provider.py

@@ -37,6 +37,7 @@
 from pydantic import SecretStr
 
 from skillspector.providers import registry
+from skillspector.providers.chat_models import resolve_sampling_parameters
 
 REGISTRY_PATH = str(Path(__file__).with_name("model_registry.yaml"))
 
@@ -71,14 +72,16 @@ def create_chat_model(
         deployment = os.environ.get("AZURE_OPENAI_DEPLOYMENT", "").strip() or model
         api_version = os.environ.get("AZURE_OPENAI_API_VERSION", "").strip() or "2024-06-01"
 
-        return AzureChatOpenAI(
-            azure_endpoint=endpoint,
-            azure_deployment=deployment,
-            api_key=SecretStr(api_key),
-            api_version=api_version,
-            max_tokens=max_tokens,
-            timeout=timeout,
-        )
+        kwargs = {
+            "azure_endpoint": endpoint,
+            "azure_deployment": deployment,
+            "api_key": SecretStr(api_key),
+            "api_version": api_version,
+            "max_tokens": max_tokens,
+            "timeout": timeout,
+        }
+        kwargs.update(resolve_sampling_parameters(include_seed=True))
+        return AzureChatOpenAI(**kwargs)
 
     def get_context_length(self, model: str) -> int | None:
         return registry.lookup_context_length(REGISTRY_PATH, model)

src/skillspector/providers/bedrock/provider.py

@@ -41,6 +41,7 @@
 from langchain_core.language_models.chat_models import BaseChatModel
 
 from skillspector.providers import registry
+from skillspector.providers.chat_models import resolve_sampling_parameters
 
 BEDROCK_DEFAULT_REGION = "us-west-2"
 # Cross-region inference profile ID for Claude Sonnet 4.6. Public,
@@ -129,6 +130,7 @@ def create_chat_model(
         }
         if model.startswith("arn:"):
             kwargs["provider"] = "anthropic"
+        kwargs.update(resolve_sampling_parameters())
 
         return ChatBedrockConverse(**kwargs)
 

src/skillspector/providers/chat_models.py

@@ -34,6 +34,28 @@ def resolve_reasoning_effort() -> str | None:
     return reasoning_effort or None
 
 
+def resolve_sampling_parameters(*, include_seed: bool = False) -> dict[str, float | int]:
+    """Resolve optional, validated sampling controls for hosted providers."""
+    parameters: dict[str, float | int] = {}
+    raw_temperature = os.environ.get("SKILLSPECTOR_TEMPERATURE", "").strip()
+    if raw_temperature:
+        try:
+            temperature = float(raw_temperature)
+        except ValueError as exc:
+            raise ValueError("SKILLSPECTOR_TEMPERATURE must be a number between 0 and 1") from exc
+        if not 0 <= temperature <= 1:
+            raise ValueError("SKILLSPECTOR_TEMPERATURE must be between 0 and 1")
+        parameters["temperature"] = temperature
+
+    raw_seed = os.environ.get("SKILLSPECTOR_SEED", "").strip()
+    if include_seed and raw_seed:
+        try:
+            parameters["seed"] = int(raw_seed)
+        except ValueError as exc:
+            raise ValueError("SKILLSPECTOR_SEED must be an integer") from exc
+    return parameters
+
+
 def validate_base_url(url: str | None) -> None:
     """Warn if *url* is not a well-formed http(s) URL.
 
@@ -82,4 +104,5 @@ def create_openai_compatible_chat_model(
     reasoning_effort = resolve_reasoning_effort()
     if reasoning_effort:
         kwargs["reasoning_effort"] = reasoning_effort
+    kwargs.update(resolve_sampling_parameters(include_seed=True))
     return ChatOpenAI(**kwargs)

tests/unit/test_anthropic_proxy_provider.py

@@ -43,6 +43,8 @@ def _clean_env(monkeypatch: pytest.MonkeyPatch):
     monkeypatch.delenv("SKILLSPECTOR_PROVIDER", raising=False)
     monkeypatch.delenv("SKILLSPECTOR_SSL_VERIFY", raising=False)
     monkeypatch.delenv("SKILLSPECTOR_REASONING_EFFORT", raising=False)
+    monkeypatch.delenv("SKILLSPECTOR_TEMPERATURE", raising=False)
+    monkeypatch.delenv("SKILLSPECTOR_SEED", raising=False)
     monkeypatch.delenv("OPENAI_API_KEY", raising=False)
     monkeypatch.delenv("ANTHROPIC_API_KEY", raising=False)
     monkeypatch.delenv("NVIDIA_INFERENCE_KEY", raising=False)
@@ -134,6 +136,24 @@ def fake_proxy(**kwargs: object) -> dict[str, object]:
 
         assert "effort" not in captured
 
+    def test_temperature_is_forwarded(self, monkeypatch: pytest.MonkeyPatch) -> None:
+        captured: dict[str, object] = {}
+
+        def fake_proxy(**kwargs: object) -> dict[str, object]:
+            captured.update(kwargs)
+            return kwargs
+
+        monkeypatch.setattr(
+            "skillspector.providers.anthropic_proxy.provider._ChatAnthropicProxy", fake_proxy
+        )
+        monkeypatch.setenv("ANTHROPIC_PROXY_API_KEY", "bearer-tok")
+        monkeypatch.setenv("ANTHROPIC_PROXY_ENDPOINT_URL", "https://proxy.example.com/predict")
+        monkeypatch.setenv("SKILLSPECTOR_TEMPERATURE", "0.1")
+
+        AnthropicProxyProvider().create_chat_model("claude-sonnet-4-6", max_tokens=4096)
+
+        assert captured["temperature"] == 0.1
+
 
 class TestAnthropicProxyProviderMetadata:
     """Token-budget metadata and model resolution tests."""

tests/unit/test_bedrock_provider.py

@@ -51,6 +51,8 @@ def _clean_provider_env(monkeypatch: pytest.MonkeyPatch):
     monkeypatch.delenv("SKILLSPECTOR_MODEL_REGISTRY", raising=False)
     monkeypatch.delenv("AWS_PROFILE", raising=False)
     monkeypatch.delenv("AWS_REGION", raising=False)
+    monkeypatch.delenv("SKILLSPECTOR_TEMPERATURE", raising=False)
+    monkeypatch.delenv("SKILLSPECTOR_SEED", raising=False)
     registry._load.cache_clear()
     yield
     registry._load.cache_clear()
@@ -243,6 +245,28 @@ def test_plain_model_id_does_not_pin_provider(
 
         assert "provider" not in mock_chat.call_args.kwargs
 
+    @patch("skillspector.providers.bedrock.provider.ChatBedrockConverse")
+    @patch("skillspector.providers.bedrock.provider.boto3.Session")
+    def test_temperature_is_forwarded_without_openai_seed(
+        self,
+        mock_session: MagicMock,
+        mock_chat: MagicMock,
+        monkeypatch: pytest.MonkeyPatch,
+    ) -> None:
+        mock_session.return_value.get_credentials.return_value = MagicMock()
+        mock_session.return_value.client.return_value = MagicMock()
+        monkeypatch.setenv("SKILLSPECTOR_TEMPERATURE", "0.3")
+        monkeypatch.setenv("SKILLSPECTOR_SEED", "42")
+
+        BedrockProvider().create_chat_model(
+            "us.anthropic.claude-sonnet-4-6-20250915-v1:0",
+            max_tokens=1024,
+        )
+
+        kwargs = mock_chat.call_args.kwargs
+        assert kwargs["temperature"] == 0.3
+        assert "seed" not in kwargs
+
 
 class TestBedrockProviderSelection:
     """SKILLSPECTOR_PROVIDER=bedrock activates BedrockProvider."""