Clean up nested duplicate: v2/v2/engine/synthesis.py

v2/v2/engine/synthesis.py

@@ -1,149 +0,0 @@
-"""Synthesis chip — the only place Rivet calls the model.
-
-Everything upstream in the DAG is evidence gathering; everything
-downstream is verification. The prompt is assembled from:
-
-  - the BDI beliefs relevant to this intent (constraints first)
-  - upstream artifacts (real source excerpts, migration/security reports)
-  - Pharos-routed knowledge packs (KV-injected on the transformers
-    backend, system-context on Ollama)
-  - the conversation history for this session
-
-The chip never sees raw context files — beliefs and artifacts are the
-interface. If it isn't in the BDI or an artifact, Rivet doesn't claim it.
-"""
-
-import json
-
-from kintsugi_core import (
-    BaseSkillChip,
-    BDIStore,
-    EFEWeights,
-    SkillCapability,
-    SkillContext,
-    SkillDomain,
-    SkillRequest,
-    SkillResponse,
-)
-
-RIVET_SYSTEM = """You are Rivet, a senior engineer embedded with the \
-Multiverse Campus team.
-
-## Non-negotiable rules
-1. Never suggest a destructive migration (DROP, TRUNCATE, in-place type \
-change, RENAME). Staging and prod share the database. If asked for one, \
-give the additive multi-step alternative instead — and never print the \
-destructive statement, not even as a "don't do this" example.
-2. Every code suggestion states: what it changes, what it could break, \
-and what tests verify it.
-3. If you have not read the relevant source (check the SOURCE EVIDENCE \
-section), say you are reasoning from architecture, not source.
-4. Auth changes get an explicit callout: "This touches authentication. \
-Review with security before merging."
-5. Flag known audit findings proactively when the question walks into one.
-6. You are a colleague, not the lead. Suggest, don't decree.
-"""
-
-
-def _format_beliefs(bdi: BDIStore, belief_ids: list) -> str:
-    lines = []
-    for bid in belief_ids:
-        b = bdi.get_belief(bid)
-        if b is not None:
-            lines.append(f"- ({b.confidence:.2f}) {b.content}")
-    return "\n".join(lines) if lines else "(none loaded)"
-
-
-def _format_analysis(analysis: dict) -> str:
-    if not analysis or not analysis.get("files"):
-        notes = "; ".join(analysis.get("notes", [])) if analysis else ""
-        return f"No source files were read for this request. {notes}".strip()
-    parts = []
-    for f in analysis["files"]:
-        header = f"### {f['path']}"
-        if f.get("git_status"):
-            header += f"  (git: {f['git_status']} — uncommitted changes!)"
-        parts.append(f"{header}\n```\n{f['excerpt']}\n```")
-        if f.get("recent_history"):
-            parts.append(f"Recent commits touching this file:\n{f['recent_history']}")
-    return "\n\n".join(parts)
-
-
-def _format_report(name: str, report: dict) -> str:
-    if not report:
-        return ""
-    return f"## {name}\n```json\n{json.dumps(report, indent=2, default=str)[:4000]}\n```"
-
-
-class SynthesisChip(BaseSkillChip):
-    name = "synthesis"
-    description = "Generate the draft answer from evidence + beliefs + packs"
-    version = "2.0.0"
-    domain = SkillDomain.GENERAL
-    efe_weights = EFEWeights()
-    capabilities = [SkillCapability.EXTERNAL_API]
-
-    def __init__(self, model_client, bdi: BDIStore, pharos_router=None,
-                 max_tokens: int = 1536):
-        super().__init__()
-        self.model = model_client
-        self.bdi = bdi
-        self.pharos = pharos_router
-        self.max_tokens = max_tokens
-
-    async def handle(self, request: SkillRequest,
-                     context: SkillContext) -> SkillResponse:
-        question = context.metadata.get("question", request.raw_input)
-        session = context.metadata.get("session")
-        belief_ids = context.metadata.get("belief_ids", [])
-
-        # Pharos: route the question to knowledge packs.
-        knowledge, pack_names = "", []
-        if self.pharos is not None:
-            routed = self.pharos.route(question)
-            knowledge = routed.knowledge_text
-            pack_names = routed.pack_names
-            if session and pack_names:
-                for p in pack_names:
-                    session.record_evidence("pharos_pack", p, self.name)
-
-        prompt_parts = ["# ORGANIZATIONAL BELIEFS (BDI)\n"
-                        + _format_beliefs(self.bdi, belief_ids)]
-
-        analysis = request.parameters.get("analysis") or {}
-        prompt_parts.append("# SOURCE EVIDENCE\n" + _format_analysis(analysis))
-
-        for key, title in (
-            ("migration_report", "MIGRATION SAFETY REPORT"),
-            ("security_report", "SECURITY REVIEW REPORT"),
-        ):
-            block = _format_report(title, request.parameters.get(key) or {})
-            if block:
-                prompt_parts.append(block)
-
-        if session and session.history:
-            recent = session.history[-6:]
-            convo = "\n".join(f"{t['role']}: {t['content'][:400]}" for t in recent)
-            prompt_parts.append(f"# CONVERSATION SO FAR\n{convo}")
-
-        prompt_parts.append(f"# QUESTION\n{question}")
-        prompt = "\n\n".join(prompt_parts)
-
-        reply = self.model.generate(
-            prompt, system=RIVET_SYSTEM, knowledge=knowledge,
-            max_tokens=self.max_tokens,
-        )
-        if not reply.ok:
-            return SkillResponse(
-                content=f"model call failed: {reply.error}", success=False,
-                data={"text": "", "error": reply.error},
-            )
-        return SkillResponse(
-            content="draft generated", success=True,
-            data={
-                "text": reply.text,
-                "backend": reply.backend,
-                "knowledge_injected": reply.knowledge_injected,
-                "packs_used": pack_names,
-            },
-        )