fix(ci): install tracing extra in test workflow

CI was missing --extra tracing, so mlflow wasn't installed and all
26 tracing tests failed with ImportError.  Also applies Black formatting.

Author: davidfarah2003

.github/workflows/test.yml

@@ -27,7 +27,7 @@ jobs:
       uses: astral-sh/setup-uv@v7
 
     - name: Install dependencies
-      run: uv sync --extra mcp
+      run: uv sync --extra mcp --extra tracing
 
     - name: Run tests with coverage
       run: |

ace/cli/__init__.py

@@ -2,7 +2,18 @@
 
 import click
 
-from ace.cli.cloud import upload, traces, run, insights, prompts, status, materialize, batch, setup, integrations
+from ace.cli.cloud import (
+    upload,
+    traces,
+    run,
+    insights,
+    prompts,
+    status,
+    materialize,
+    batch,
+    setup,
+    integrations,
+)
 
 
 @click.group()

ace/cli/cloud.py

@@ -141,7 +141,9 @@ def traces_list(as_json, api_key, base_url):
         return
 
     # Table header
-    click.echo(f"  {'ID':<36}  {'Filename':<40}  {'Type':<6}  {'Size':>8}  {'Uploaded'}")
+    click.echo(
+        f"  {'ID':<36}  {'Filename':<40}  {'Type':<6}  {'Size':>8}  {'Uploaded'}"
+    )
     click.echo(f"  {'-' * 36}  {'-' * 40}  {'-' * 6}  {'-' * 8}  {'-' * 10}")
     for t in items:
         tid = t.get("id", "?")
@@ -243,7 +245,9 @@ def traces_upload(paths, file_type, api_key, base_url):
         if item == "-":
             content = sys.stdin.read()
             ft = file_type or "txt"
-            trace_list.append({"filename": "stdin.txt", "content": content, "fileType": ft})
+            trace_list.append(
+                {"filename": "stdin.txt", "content": content, "fileType": ft}
+            )
             continue
 
         p = Path(item)
@@ -302,8 +306,16 @@ def traces_upload(paths, file_type, api_key, base_url):
 @_api_key_option
 @_base_url_option
 def run(
-    trace_ids, select_all, model, epochs, reflector_mode, anthropic_key, wait, as_json,
-    api_key, base_url,
+    trace_ids,
+    select_all,
+    model,
+    epochs,
+    reflector_mode,
+    anthropic_key,
+    wait,
+    as_json,
+    api_key,
+    base_url,
 ):
     """Run the analysis pipeline on selected traces.
 

ace/cli/setup.py

@@ -33,7 +33,6 @@
     validate_connection,
 )
 
-
 # ---------------------------------------------------------------------------
 # Terminal helpers
 # ---------------------------------------------------------------------------
@@ -396,10 +395,10 @@ def main() -> None:
     )
 
     # ace models
-    models_parser = subparsers.add_parser(
-        "models", help="Search available models"
+    models_parser = subparsers.add_parser("models", help="Search available models")
+    models_parser.add_argument(
+        "query", nargs="*", default=[], help="Search query (multiple terms = match all)"
     )
-    models_parser.add_argument("query", nargs="*", default=[], help="Search query (multiple terms = match all)")
     models_parser.add_argument("--provider", default=None, help="Filter by provider")
     models_parser.add_argument(
         "--limit", type=int, default=20, help="Max results (default: 20)"
@@ -462,7 +461,9 @@ def _cmd_models(query: str, provider: str | None, limit: int) -> None:
         in_cost = f"${m.input_cost_per_m:.2f}" if m.input_cost_per_m else "-"
         out_cost = f"${m.output_cost_per_m:.2f}" if m.output_cost_per_m else "-"
         key_status = f"{GREEN}\u2713{RESET}" if m.key_found else f"{RED}\u2717{RESET}"
-        print(f"{m.model:<45} {m.provider:<15} {in_cost:<10} {out_cost:<11} {key_status}")
+        print(
+            f"{m.model:<45} {m.provider:<15} {in_cost:<10} {out_cost:<11} {key_status}"
+        )
 
     if total > limit:
         print()

ace/core/context.py

@@ -10,7 +10,6 @@
 from .outputs import AgentOutput, ReflectorOutput
 from .skillbook import Skill, Skillbook, UpdateBatch
 
-
 # ---------------------------------------------------------------------------
 # ACESample — structural protocol for step access
 # ---------------------------------------------------------------------------

ace/core/skillbook.py

@@ -29,7 +29,9 @@
 # Constants
 # ---------------------------------------------------------------------------
 
-VALID_SKILL_TAGS: FrozenSet[str] = frozenset({"helpful", "harmful", "neutral"})  # deprecated
+VALID_SKILL_TAGS: FrozenSet[str] = frozenset(
+    {"helpful", "harmful", "neutral"}
+)  # deprecated
 
 # ---------------------------------------------------------------------------
 # Update operations
@@ -399,9 +401,7 @@ def to_dict(self, exclude_embeddings: bool = False) -> Dict[str, object]:
                 del skill_dict["embedding"]
             # Use InsightSource.to_dict() for clean sparse serialization
             # instead of the recursive asdict() which dumps empty/null fields.
-            skill_dict["sources"] = [
-                source.to_dict() for source in skill.sources
-            ]
+            skill_dict["sources"] = [source.to_dict() for source in skill.sources]
             skills_serialized[skill_id] = skill_dict
         return {
             "skills": skills_serialized,
@@ -588,9 +588,7 @@ def source_summary(self) -> Dict[str, Any]:
                     source_systems[src.source_system] = (
                         source_systems.get(src.source_system, 0) + 1
                     )
-                    trace_uids[src.trace_uid] = (
-                        trace_uids.get(src.trace_uid, 0) + 1
-                    )
+                    trace_uids[src.trace_uid] = trace_uids.get(src.trace_uid, 0) + 1
                     sq = src.sample_question or ""
                     if sq:
                         sample_questions[sq] = sample_questions.get(sq, 0) + 1

ace/deduplication/detector.py

@@ -67,7 +67,9 @@ def _embed_litellm(self, text: str) -> Optional[List[float]]:
             )
             return response.data[0]["embedding"]
         except Exception as e:
-            logger.warning("Failed to compute embedding via LiteLLM (%s): %s", type(e).__name__, e)
+            logger.warning(
+                "Failed to compute embedding via LiteLLM (%s): %s", type(e).__name__, e
+            )
             return None
 
     def _embed_batch_litellm(self, texts: List[str]) -> List[Optional[List[float]]]:
@@ -80,7 +82,11 @@ def _embed_batch_litellm(self, texts: List[str]) -> List[Optional[List[float]]]:
             response = litellm.embedding(model=self.config.embedding_model, input=texts)
             return [item["embedding"] for item in response.data]
         except Exception as e:
-            logger.warning("Failed to compute batch embeddings via LiteLLM (%s): %s", type(e).__name__, e)
+            logger.warning(
+                "Failed to compute batch embeddings via LiteLLM (%s): %s",
+                type(e).__name__,
+                e,
+            )
             return [None] * len(texts)
 
     # ------------------------------------------------------------------
@@ -98,7 +104,8 @@ def _embed_st(self, text: str) -> Optional[List[float]]:
         except Exception as e:
             logger.warning(
                 "Failed to compute embedding via sentence-transformers (%s): %s",
-                type(e).__name__, e,
+                type(e).__name__,
+                e,
             )
             return None
 
@@ -113,7 +120,8 @@ def _embed_batch_st(self, texts: List[str]) -> List[Optional[List[float]]]:
         except Exception as e:
             logger.warning(
                 "Failed to compute batch embeddings via sentence-transformers (%s): %s",
-                type(e).__name__, e,
+                type(e).__name__,
+                e,
             )
             return [None] * len(texts)
 

ace/deduplication/manager.py

@@ -134,7 +134,11 @@ def parse_consolidation_operations(
                         )
                     )
             except Exception as e:
-                logger.warning("Failed to parse consolidation operation (%s): %s", type(e).__name__, e)
+                logger.warning(
+                    "Failed to parse consolidation operation (%s): %s",
+                    type(e).__name__,
+                    e,
+                )
 
         logger.info("Parsed %d consolidation operations", len(operations))
         return operations

ace/deduplication/prompts.py

@@ -57,8 +57,7 @@ def generate_similarity_report(
             )
         )
 
-    parts.append(
-        """
+    parts.append("""
 ## Consolidation Operations Format
 
 Include consolidation operations in your response under a `consolidation_operations` key.
@@ -101,8 +100,7 @@ def generate_similarity_report(
 - UPDATE to add context tags like "[Batch Jobs]" or "[User-Facing API]" to differentiate
 - DELETE only when one is clearly redundant with no unique value
 
-"""
-    )
+""")
 
     return "".join(parts)
 

ace/implementations/skill_manager.py

@@ -104,9 +104,7 @@ def update_skills(
                 "root_cause_analysis": r.root_cause_analysis,
                 "correct_approach": r.correct_approach,
                 "key_insight": r.key_insight,
-                "extracted_learnings": [
-                    l.model_dump() for l in r.extracted_learnings
-                ],
+                "extracted_learnings": [l.model_dump() for l in r.extracted_learnings],
             }
             for r in reflections
         ]