chore: drop anthropic dependency — SDK migration complete

libs/openant-core/openant/cli.py

@@ -622,10 +622,9 @@ def cmd_report_data(args):
     and step reports — everything display-ready.
     """
     import html as html_mod
-    import anthropic
     from core.schemas import success, error
     from core.step_report import step_context
-    from utilities.llm_client import get_global_tracker
+    from utilities.llm_client import AnthropicClient, get_global_tracker
 
     results_path = args.results
     dataset_path = args.dataset
@@ -845,13 +844,9 @@ def cmd_report_data(args):
 {findings_text}
 """
                 print("[Report] Generating remediation guidance (LLM)...", file=sys.stderr)
-                client = anthropic.Anthropic()
-                response = client.messages.create(
-                    model="claude-sonnet-4-20250514",
-                    max_tokens=4096,
-                    messages=[{"role": "user", "content": prompt}],
-                )
-                remediation_html = response.content[0].text
+                # AnthropicClient handles usage tracking via the global TokenTracker.
+                remediation_client = AnthropicClient(model="claude-sonnet-4-20250514")
+                remediation_html = remediation_client.analyze_sync(prompt, max_tokens=4096)
 
                 # Post-process: linkify finding references like #4, #12-#14
                 import re
@@ -860,15 +855,11 @@ def _linkify_finding(m):
                     return f'<a href="#finding-{num}" class="finding-ref">#{num}</a>'
                 remediation_html = re.sub(r'#(\d+)', _linkify_finding, remediation_html)
 
-                # Track usage
-                usage = response.usage
-                tracker = get_global_tracker()
-                tracker.record_call(
-                    model="claude-sonnet-4-20250514",
-                    input_tokens=usage.input_tokens,
-                    output_tokens=usage.output_tokens,
+                last = remediation_client.get_last_call() or {}
+                print(
+                    f"  Remediation cost: ${last.get('cost_usd', 0.0):.4f}",
+                    file=sys.stderr,
                 )
-                print(f"  Remediation cost: ${(usage.input_tokens / 1e6) * 3.0 + (usage.output_tokens / 1e6) * 15.0:.4f}", file=sys.stderr)
 
             # --- Step reports ---
             step_reports_data = []

libs/openant-core/pyproject.toml

@@ -5,7 +5,6 @@ description = "Two-stage SAST tool using Claude for vulnerability analysis"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
-    "anthropic>=0.40.0",
     "claude-agent-sdk>=0.1.48",
     "python-dotenv>=1.0.0",
     "pydantic>=2.0.0",

libs/openant-core/utilities/context_enhancer.py

@@ -23,8 +23,6 @@
 from pathlib import Path
 from typing import Callable, Optional
 
-import anthropic  # Still used by shared_client below; removed in Step 5b once ContextAgent drops its client param.
-
 from .llm_client import AnthropicClient, TokenTracker, get_global_tracker, reset_global_tracker
 from .agentic_enhancer import RepositoryIndex, enhance_unit_with_agent, load_index_from_file
 from .rate_limiter import get_rate_limiter, is_rate_limit_error, is_retryable_error

libs/openant-core/utilities/rate_limiter.py

@@ -15,10 +15,15 @@
     rate_limiter = get_rate_limiter()
     rate_limiter.wait_if_needed()
 
-    # When catching RateLimitError
-    except anthropic.RateLimitError as e:
-        retry_after = float(e.response.headers.get("retry-after", 0))
-        rate_limiter.report_rate_limit(retry_after)
+    # Rate-limit detection happens centrally in llm_client._run_query, which
+    # raises utilities.sdk_errors.RateLimitError and calls
+    # rate_limiter.report_rate_limit(0) on every rate-limit event. Callers
+    # that need to attach state before re-raising:
+    from utilities.sdk_errors import RateLimitError
+    try:
+        ...
+    except RateLimitError:
+        # report_rate_limit already fired in _run_query
         raise
 """