fix: last 3 PromptModel violations — ai.prompt.model_required should be 0

DariuszNewecki · DariuszNewecki · commit d18f30019b3e · 2026-03-10T14:44:48.000+01:00
diff --git a/reports/audit/latest_audit.json b/reports/audit/latest_audit.json
@@ -1,6 +1,6 @@
 {
-  "audit_id": "ca070e3b-8f65-4c90-9a39-8c7f1cdd6cbb",
-  "timestamp": "2026-03-10T12:36:34Z",
+  "audit_id": "e0985eff-9204-4ee9-b9a1-ae0070de4869",
+  "timestamp": "2026-03-10T13:17:04Z",
   "passed": false,
   "findings_count": 140,
   "executed_rules": [
diff --git a/reports/audit_auto_ignored.json b/reports/audit_auto_ignored.json
@@ -1,4 +1,4 @@
 {
-  "generated_at": "2026-03-10T12:36:34Z",
+  "generated_at": "2026-03-10T13:17:04Z",
   "items": []
 }
diff --git a/reports/audit_auto_ignored.md b/reports/audit_auto_ignored.md
@@ -1,4 +1,4 @@
 # Audit Auto-Ignored Symbols
 
-- Generated: `2026-03-10T12:36:34Z`
+- Generated: `2026-03-10T13:17:04Z`
 - Total auto-ignored: **0**
diff --git a/reports/pytest-report.html b/reports/pytest-report.html
@@ -328,7 +328,7 @@
   </head>
   <body>
     <h1 id="title">pytest-report.html</h1>
-    <p>Report generated on 10-Mar-2026 at 13:36:28 by <a href="https://pypi.python.org/pypi/pytest-html">pytest-html</a>
+    <p>Report generated on 10-Mar-2026 at 14:16:58 by <a href="https://pypi.python.org/pypi/pytest-html">pytest-html</a>
         v4.1.1</p>
     <div id="environment-header">
       <h2>Environment</h2>
diff --git a/src/cli/logic/body_contracts_fixer.py b/src/cli/logic/body_contracts_fixer.py
@@ -4,13 +4,13 @@
 
 from __future__ import annotations
 
-import textwrap
 import time
 from pathlib import Path
 from typing import TYPE_CHECKING, Any
 
 from cli.logic.body_contracts_checker import check_body_contracts
 from shared.action_types import ActionImpact, ActionResult
+from shared.ai.prompt_model import PromptModel
 from shared.atomic_action import atomic_action
 from shared.logger import getLogger
 from shared.utils.parallel_processor import ThrottledParallelProcessor
@@ -22,10 +22,6 @@
 
 logger = getLogger(__name__)
 
-_BODY_UI_FIX_PROMPT = textwrap.dedent(
-    "\n    You are refactoring Python code for a constitutional system called CORE.\n\n    GOAL\n    ----\n    - Remove ALL terminal UI from the given module:\n      - No Rich imports or usage\n      - No console.print() or input()\n      - No direct os.environ / os.environ[...] access\n    - Preserve the module's behavior as a HEADLESS Body-layer service/logic.\n\n    CONTEXT\n    -------\n    CORE governance rules for Body code:\n    - Body modules MUST be headless:\n      - No Rich UI (Console, Progress, status, etc.)\n      - No console.print() / input() calls\n    - Configuration must come from shared.config.settings, not os.environ.\n    - Logging MUST use shared.logger.getLogger(__name__).\n\n    REQUIREMENTS\n    ------------\n    1. Remove or refactor any Rich / console imports and usage.\n       - If the module needs observability, use logger.debug/info/warning/error.\n    2. Remove or refactor console.print() / input() calls.\n       - Replace with logger.info/debug where appropriate, or return values.\n    3. Replace os.environ[...] or os.environ.get(...) with settings access\n       (e.g., shared.config.settings or an injected config object) when possible.\n       If you cannot infer an exact mapping, keep a FUTURE comment but do NOT\n       keep direct os.environ in the Body module.\n    4. DO NOT change public function signatures unless absolutely necessary.\n    5. DO NOT introduce any new UI dependencies.\n\n    OUTPUT FORMAT\n    -------------\n    Return ONLY the full corrected Python module.\n    DO NOT wrap it in backticks, comments, or explanation.\n    "
-)
-
 
 async def _process_single_file(
     item: tuple[Path, list[dict[str, Any]]],
@@ -53,18 +49,18 @@ async def _process_single_file(
         {f"- {v['rule_id']} @ line {v.get('line')}: {v['message']}" for v in vlist}
     )
     violation_summary = "\n".join(summary_lines)
-    prompt = (
-        _BODY_UI_FIX_PROMPT
-        + "\n\nFILE PATH:\n"
-        + str(path)
-        + "\n\nVIOLATIONS DETECTED:\n"
-        + violation_summary
-        + "\n\nCURRENT FILE CONTENT:\n\n"
-        + original_source
-    )
 
     try:
-        raw_response = await agent.make_request_async(prompt, user_id="fix_body_ui")
+        model = PromptModel.load("body_contracts_fixer")
+        raw_response = await model.invoke(
+            context={
+                "file_path": str(path),
+                "violation_summary": violation_summary,
+                "original_source": original_source,
+            },
+            client=agent,
+            user_id="fix_body_ui",
+        )
     except Exception as e:
         logger.warning("Body UI fixer: LLM request failed for %s: %s", path, e)
         return {
@@ -154,7 +150,6 @@ async def fix_body_ui_violations(
 
     # ID: dbf3bacb-1562-48e3-acfa-9127c985737b
     async def worker(item):
-        # Pass the file_handler from context
         return await _process_single_file(item, agent, write, core_context.file_handler)
 
     per_file_results = await processor.run_async(items, worker)
diff --git a/src/will/self_healing/test_generation/llm_correction.py b/src/will/self_healing/test_generation/llm_correction.py
@@ -3,21 +3,21 @@
 LLM-based code correction when automatic repairs are insufficient.
 
 This is the "last resort" - only called when deterministic fixes don't work.
+HEALED: attempt_correction uses PromptModel.invoke() — ai.prompt.model_required compliant.
 """
 
 from __future__ import annotations
 
 import json
-from pathlib import Path
 from typing import Any
 
 from body.self_healing.test_context_analyzer import ModuleContext
 from mind.governance.audit_context import AuditorContext
+from shared.ai.prompt_model import PromptModel
 from shared.infrastructure.config_service import ConfigService
 from shared.logger import getLogger
 from shared.utils.parsing import parse_write_blocks
 from will.orchestration.cognitive_service import CognitiveService
-from will.orchestration.prompt_pipeline import PromptPipeline
 from will.orchestration.validation_pipeline import validate_code_async
 
 from .code_extractor import CodeExtractor
@@ -65,40 +65,46 @@ async def attempt_correction(
                 "message": "Missing required correction context.",
             }
 
-        # Analyze violations to choose prompting strategy
         syntax_only = all(
             v.get("rule", "").startswith(("tooling.", "syntax.")) for v in violations
         )
 
-        # Build appropriate prompt
-        if self.config_service is not None:
-            repo_root = Path(await self.config_service.get("REPO_PATH", required=True))
-        else:
-            repo_root = self.auditor.repo_path
-
-        prompt = self._build_correction_prompt(
-            file_path=file_path,
-            code=code,
-            violations=violations,
-            module_context=module_context,
-            goal=goal,
-            syntax_only=syntax_only,
-            repo_root=repo_root,
-        )
+        violations_json = json.dumps(violations, indent=2)
 
-        # Get LLM response
         try:
             llm_client = await self.cognitive.aget_client_for_role("Coder")
-            llm_output = await llm_client.make_request_async(
-                prompt, user_id="self_correction"
-            )
+
+            if syntax_only:
+                model = PromptModel.load("llm_correction_syntax")
+                llm_output = await model.invoke(
+                    context={
+                        "file_path": file_path,
+                        "violations_json": violations_json,
+                        "code": code,
+                    },
+                    client=llm_client,
+                    user_id="self_correction",
+                )
+            else:
+                model = PromptModel.load("llm_correction_structural")
+                llm_output = await model.invoke(
+                    context={
+                        "file_path": file_path,
+                        "violations_json": violations_json,
+                        "code": code.strip(),
+                        "module_name": module_context.module_name,
+                        "import_path": module_context.import_path,
+                        "goal": goal,
+                    },
+                    client=llm_client,
+                    user_id="self_correction",
+                )
         except Exception as e:
             return {
                 "status": "error",
                 "message": f"LLM request failed: {e!s}",
             }
 
-        # Extract corrected code with lenient parsing
         corrected_code = self._extract_corrected_code(llm_output)
 
         if not corrected_code:
@@ -107,7 +113,6 @@ async def attempt_correction(
                 "message": "LLM did not produce valid code in any recognized format.",
             }
 
-        # Validate the corrected code
         validation_result = await validate_code_async(
             file_path, corrected_code, auditor_context=self.auditor
         )
@@ -117,7 +122,7 @@ async def attempt_correction(
                 "status": "correction_failed_validation",
                 "message": "The corrected code still fails validation.",
                 "violations": validation_result["violations"],
-                "code": corrected_code,  # Return the code so automatic repairs can try
+                "code": corrected_code,
             }
 
         return {
@@ -126,65 +131,6 @@ async def attempt_correction(
             "message": "Corrected code generated and validated successfully.",
         }
 
-    def _build_correction_prompt(
-        self,
-        file_path: str,
-        code: str,
-        violations: list[dict[str, Any]],
-        module_context: ModuleContext,
-        goal: str,
-        syntax_only: bool,
-        repo_root: Path,
-    ) -> str:
-        """
-        Build appropriate correction prompt based on violation type.
-        """
-        if syntax_only:
-            # For syntax errors: be strict about NOT rewriting
-            base_prompt = (
-                "You are CORE's syntax repair agent.\n\n"
-                "The code below has ONLY syntax errors. Your job is to fix the syntax "
-                "while preserving ALL logic and structure.\n\n"
-                f"File: {file_path}\n\n"
-                "SYNTAX ERRORS:\n"
-                f"{json.dumps(violations, indent=2)}\n\n"
-                "CODE TO FIX:\n"
-                f"{code}\n\n"
-                "CRITICAL: Fix ONLY the syntax errors listed above. "
-                "Do NOT rewrite or restructure the code. "
-                "Do NOT add or remove any logic or tests.\n\n"
-                "Output the corrected code:"
-            )
-        else:
-            # For structural/logic errors: allow more freedom
-            base_prompt = (
-                "You are CORE's self-correction agent.\n\n"
-                "A recent code generation attempt failed validation.\n"
-                "Please analyze the violations and fix the code below.\n\n"
-                f"File: {file_path}\n\n"
-                "[[violations]]\n"
-                f"{json.dumps(violations, indent=2)}\n"
-                "[[/violations]]\n\n"
-                "[[code]]\n"
-                f"{code.strip()}\n"
-                "[[/code]]\n\n"
-                "Module context:\n"
-                f"- Module: {module_context.module_name}\n"
-                f"- Import path: {module_context.import_path}\n"
-                f"- Goal: {goal}\n\n"
-                "CRITICAL INSTRUCTIONS:\n"
-                "1. Fix ALL violations listed above\n"
-                "2. Ensure the code is syntactically valid Python\n"
-                "3. Pay special attention to docstring quotes - use MATCHING triple quotes\n"
-                "4. NEVER mix quote types in a single docstring\n"
-                "5. Output the COMPLETE corrected code\n\n"
-                "Provide the corrected code now:"
-            )
-
-        # Process through prompt pipeline
-        pipeline = PromptPipeline(repo_path=repo_root)
-        return pipeline.process(base_prompt)
-
     def _extract_corrected_code(self, llm_output: str) -> str | None:
         """
         Extract code from LLM response using multiple strategies.
@@ -194,19 +140,16 @@ def _extract_corrected_code(self, llm_output: str) -> str | None:
         2. Markdown code fences ```python...```
         3. Raw Python code
         """
-        # Strategy 1: Write blocks
         write_blocks = parse_write_blocks(llm_output)
         if write_blocks:
             logger.info("Extracted correction from write block")
             return next(iter(write_blocks.values()))
 
-        # Strategy 2: Markdown code fences
         code = self.code_extractor.extract(llm_output)
         if code:
             logger.info("Extracted correction from markdown code fence")
             return code
 
-        # Strategy 3: Raw Python
         stripped = llm_output.strip()
         if stripped.startswith(("import ", "from ", "def ", "class ", "@", "#")):
             logger.info("Extracted correction from raw response")
diff --git a/src/will/self_healing/test_generation/single_test_fixer.py b/src/will/self_healing/test_generation/single_test_fixer.py
@@ -2,14 +2,15 @@
 
 """
 Single Test Fixer - Refined A3 Orchestrator.
+HEALED: fix_test uses PromptModel.invoke() — ai.prompt.model_required compliant.
 """
 
 from __future__ import annotations
 
 from pathlib import Path
 
+from shared.ai.prompt_model import PromptModel
 from shared.logger import getLogger
-from will.orchestration.prompt_pipeline import PromptPipeline
 
 from .failure_parser import TestFailureParser
 from .test_extractor import TestExtractor
@@ -27,10 +28,8 @@ def __init__(self, cognitive_service, file_handler, repo_root, max_attempts=3):
         self.max_attempts = max_attempts
         self.repo_root = repo_root
 
-        # Specialists
         self.parser = TestFailureParser()
         self.extractor = TestExtractor(file_handler, repo_root)
-        self.pipeline = PromptPipeline(repo_path=repo_root)
 
     # ID: 8adb4bee-9216-47a3-9d96-ec9714bb5daf
     async def fix_test(
@@ -45,15 +44,22 @@ async def fix_test(
         if not test_code:
             return {"status": "error", "error": "Source extraction failed"}
 
+        model = PromptModel.load("single_test_fixer")
+        client = await self.cognitive.aget_client_for_role("Coder")
+
         for attempt in range(self.max_attempts):
             logger.info(
                 "🤖 Fix Attempt %d/%d for %s", attempt + 1, self.max_attempts, test_name
             )
 
-            prompt = self._build_prompt(test_name, test_code, failure_info)
-            client = await self.cognitive.aget_client_for_role("Coder")
-            response = await client.make_request_async(
-                self.pipeline.process(prompt), user_id="test_fixer"
+            response = await model.invoke(
+                context={
+                    "test_name": test_name,
+                    "failure_type": failure_info.get("failure_type", ""),
+                    "test_code": test_code,
+                },
+                client=client,
+                user_id="test_fixer",
             )
 
             fixed_code = self._extract_code(response)
@@ -64,9 +70,6 @@ async def fix_test(
 
         return {"status": "failed"}
 
-    def _build_prompt(self, name: str, code: str, info: dict) -> str:
-        return f"Fix this failing test: {name}\nError: {info.get('failure_type')}\nCode:\n{code}"
-
     def _extract_code(self, response: str) -> str | None:
         """Simple extraction logic helper."""
         if "```python" in response:

Original file line number	Diff line number	Diff line change
`@@ -1,6 +1,6 @@`
`1`	`1`	`{`
`2`		`- "audit_id": "ca070e3b-8f65-4c90-9a39-8c7f1cdd6cbb",`
`3`		`- "timestamp": "2026-03-10T12:36:34Z",`
	`2`	`+ "audit_id": "e0985eff-9204-4ee9-b9a1-ae0070de4869",`
	`3`	`+ "timestamp": "2026-03-10T13:17:04Z",`
`4`	`4`	`"passed": false,`
`5`	`5`	`"findings_count": 140,`
`6`	`6`	`"executed_rules": [`
Original file line number	Diff line number	Diff line change
`@@ -1,4 +1,4 @@`
`1`	`1`	`{`
`2`		`- "generated_at": "2026-03-10T12:36:34Z",`
	`2`	`+ "generated_at": "2026-03-10T13:17:04Z",`
`3`	`3`	`"items": []`
`4`	`4`	`}`