…probs

### What changes I have done

- Added `score_threshold` config field to `MultiRiskGraniteGuardianToolConfig` to optionally drop low-confidence detections and reduce false positives. Defaults to `0.0` (no filter) to preserve current behavior.
- Each entry in `risk_results` now includes a per-category `score` in [0, 1], derived from the logprob of the category's first emitted token in Step 2.
- Categories whose per-category score is below `score_threshold` are dropped from `detected_risks` and `risk_results`. Categories without a score (e.g., when Ollama does not return logprobs) pass through unfiltered as a graceful fallback.
- Step 1 decision remains label-based (`Yes`/`No`) as per the model card; no extra Ollama calls are added.

### Why

The multi-harm model's self-reported text confidence (e.g., `"High"`, `"Not Harmful"`) is effectively binary in practice and useless for thresholding. False positives on some categories (e.g., `Harmful` flagged on sarcasm) could not be filtered without manual category exclusion. Per-category logprob-derived scores give callers a real numeric signal to threshold on (e.g., `Violence=0.97` vs `Harmful=0.35` for the same input).

### How I made the changes

- `akd/guardrails/providers/granite_guardian.py`:
  - `MultiRiskGraniteGuardianToolConfig`: added `score_threshold: float = 0.0` with `ge=0.0, le=1.0` validation.
  - `_call_category_detection`: added top-level `logprobs: True` and `top_logprobs: 5` to the Ollama `/api/generate` request body (Ollama accepts these as top-level params, not inside `options`).
  - `_parse_categories_with_scores`: new helper that parses comma-separated categories and computes per-category scores as `exp(first_token_logprob)`.
  - `_first_token_logprob_per_category`: new static helper that walks the token stream, skipping whitespace/commas, and returns the logprob of the first token of each emitted category.
  - `_parse_categories`: kept as a thin wrapper over `_parse_categories_with_scores` for backward compatibility.
  - `_arun`: applies `score_threshold` as a filter in the Step 2 detected-categories list comprehension; builds `risk_results` with `{"is_risky": True, "score": <float|None>}` per category.

### How to test

- `uv run pytest tests/guardrails/` — existing tests still pass (8 failures in `test_granite_think.py` are pre-existing and require a live `granite3.3-guardian:8b` model).
- `uv run python scripts/test_multi_harm.py` with live Ollama + `granite-guardian-3.2-5b-multi-harm-GGUF` — verifies per-category scores appear in `risk_results` (e.g., Violence=0.97, Unethical Behavior=0.76 for the same violent input; Harmful=0.35 on sarcasm, correctly flagged as low-confidence).

### What

- Merged `_parse_categories` and `_parse_categories_with_scores` into a single `_parse_categories` method that returns `dict[GraniteHarmCategory, float | None]` (category -> per-category score).
- Removed the redundant `"scores"` key from the Step 2 return dict; `"categories"` now holds both the categories and their scores as a dict mapping.
- `unfiltered_categories` in `extra` now preserves per-category scores alongside the category list (previously was a bare list).

### Why

The previous split had `_parse_categories` as a thin list-returning wrapper over `_parse_categories_with_scores` purely for backward compatibility, but `_parse_categories` was only called internally and had no external consumers — dead weight. A single dict return is also a more natural fit: `risk_results` is already a dict of category -> metadata, and downstream consumers need both iteration and score lookup. Dicts preserve insertion order in Python 3.7+, so the model's emission order is kept.

### How

- `akd/guardrails/providers/granite_guardian.py`:
  - `_parse_categories`: now takes optional `token_logprobs`, returns `dict[GraniteHarmCategory, float | None]`. When `token_logprobs` is None/empty, scores are `None` (same behavior as the pre-logprobs version, just wrapped in dict keys instead of a list).
  - `_call_category_detection`: returns `{"categories": <dict>, "raw_response": ...}` (removed the separate `"scores"` key).
  - `_arun`: renamed local from `per_category_scores` to `category_scores`; iterates `category_scores.items()` directly in the filter comprehension; passes the whole `category_scores` dict as `extra["unfiltered_categories"]` to preserve scores in observability output.

### How to test

- `uv run pytest tests/guardrails/ --ignore=tests/guardrails/test_granite_think.py` — all 21 tests pass.
- `uv run python scripts/test_multi_harm.py` with live Ollama — confirms `risk_results` still has `score` per category and `extra["unfiltered_categories"]` now includes scores.