/**
 * atomic-tools — Node-side LLM-visible atomic tools (Task #156).
 *
 * These are the planner-facing decompositions of the previously coarse
 * `summarize_literature_bucket` and `query_opentargets` composites. The
 * coarse composites stay registered as `composition_alias` in the graph
 * (so legacy callers and saved chats keep working) but the planner now
 * sees the longer atomic chain instead.
 *
 * Each handler:
 *   - Conforms to the inputSchema / outputSchema declared on the
 *     corresponding `tool_nodes` row in `tool-graph-seed.ts`.
 *   - Is purely a function of its declared input — no reaching into
 *     a sibling step's hidden state. If a step needs something a prior
 *     step had, the contract on the `feeds` edge carries it.
 *   - Wraps itself in `runAtomicStep` so each call accumulates an
 *     evidence row (consumed by #157 seam-health).
 *
 * Python-owned atomic steps (validation / fulltext / task / drug joins)
 * are NOT exposed here — they remain graph-only labels until the
 * research-engine bridge gains atomic endpoints (#163). Their alias
 * composites continue to satisfy callers in the meantime.
 */
import type { ToolDef } from "./tools";
import {
  recordInvocation,
  resolveNodeForDirectReference,
} from "../lib/tool-graph";
import { logger } from "../lib/logger";

const OPENTARGETS_BASE = "https://api.platform.opentargets.org/api/v4/graphql";
const FETCH_TIMEOUT_MS = 15_000;

// --- shared helpers ---------------------------------------------------------

async function runAtomicStep<T>(
  nodeName: string,
  argsSummary: Record<string, unknown> | null,
  fn: () => Promise<T>,
): Promise<T> {
  const start = Date.now();
  // Pre-dispatch deprecation pre-check (#159). Mirrors the same hook
  // in src/mcp/tools.ts runAtomicStep — throws a structured error
  // referring to `replacedBy` when the node is deprecated. Resolver
  // failure is best-effort; only the deprecation case blocks dispatch.
  let resolved: Awaited<ReturnType<typeof resolveNodeForDirectReference>> = null;
  try {
    resolved = await resolveNodeForDirectReference(nodeName);
  } catch (err) {
    logger.debug(
      { err, nodeName },
      "atomic-tools runAtomicStep deprecation pre-resolve failed",
    );
  }
  if (resolved && resolved.deprecated) {
    logger.warn(
      {
        nodeName: resolved.nodeName,
        replacedBy: resolved.replacedBy,
        kind: "tool_dispatch_deprecated",
      },
      "tool dispatch: deprecated node invoked by direct reference — refusing dispatch",
    );
    const err = new Error(
      `tool '${resolved.nodeName}' is deprecated; use '${resolved.replacedBy ?? "(no replacement set)"}' instead`,
    ) as Error & {
      code: string;
      nodeName: string;
      replacedBy: string | null;
    };
    err.code = "TOOL_DEPRECATED";
    err.nodeName = resolved.nodeName;
    err.replacedBy = resolved.replacedBy;
    throw err;
  }
  try {
    const result = await fn();
    void recordInvocation({
      nodeName,
      ok: true,
      argsSummary,
      resultPreview: result,
      durationMs: Date.now() - start,
    }).catch(() => undefined);
    return result;
  } catch (err) {
    void recordInvocation({
      nodeName,
      ok: false,
      argsSummary,
      resultPreview: null,
      errorCode: err instanceof Error ? err.name : "error",
      durationMs: Date.now() - start,
    }).catch(() => undefined);
    throw err;
  }
}

async function postJson<T>(url: string, body: unknown): Promise<T> {
  const ctl = new AbortController();
  const timer = setTimeout(() => ctl.abort(), FETCH_TIMEOUT_MS);
  try {
    const res = await fetch(url, {
      method: "POST",
      headers: {
        "Content-Type": "application/json",
        Accept: "application/json",
        "User-Agent": "DoAtlas/1.0 (research workbench)",
      },
      body: JSON.stringify(body),
      signal: ctl.signal,
    });
    if (!res.ok) throw new Error(`HTTP ${res.status} from ${url}`);
    return (await res.json()) as T;
  } finally {
    clearTimeout(timer);
  }
}

// --- summarize_literature_bucket atomic decomposition -----------------------

const selectPapersForBucket: ToolDef = {
  schema: {
    name: "select_papers_for_bucket",
    description:
      "Atomic step 1/3 of summarize_literature_bucket: resolve a bucket_key to its bucket_id and supporting paper_ids. Single read against the persisted causal network (PostgresCausalNetwork) with a JSONL fallback for buckets that haven't been ingested yet. Use this to enumerate the papers in a bucket before per-paper extraction.",
    parameters: {
      type: "object",
      properties: {
        bucket_key: {
          type: "string",
          description:
            "Either a bucket_id (e.g. 'B:...') or a composite bucket_key from the legacy JSONL store.",
        },
      },
      required: ["bucket_key"],
    },
  },
  async invoke(args) {
    const bucket_key = String(args?.bucket_key || "").trim();
    if (!bucket_key) return { error: "bucket_key is required" };
    return runAtomicStep("select_papers_for_bucket", { bucket_key }, async () => {
      const { causalGetBucket } = await import("../lib/causal-store");
      const { getBucketByKey, ensureLoaded } = await import(
        "../lib/research-data"
      );
      try {
        await ensureLoaded();
      } catch {
        // JSONL fixtures absent — fall through to the persisted store.
      }
      const pg = await causalGetBucket(bucket_key);
      if (pg) {
        return {
          bucket_id: pg.bucket_id,
          bucket_key: pg.bucket_key,
          paper_ids: pg.paper_ids,
          supporting_edges: pg.supporting_edges,
        };
      }
      const local = getBucketByKey(bucket_key);
      if (local) {
        return {
          bucket_id: local.bucket_key,
          bucket_key: {
            kappa_pi: local.population_bucket,
            X: local.x_norm,
            Y: local.y_norm,
            tau_hat: local.time_index,
            ctype: local.equation_type,
            kappa_mu: `${local.measure_type}:${local.measure_scale}`,
          },
          paper_ids: [],
          supporting_edges: local.edge_count,
        };
      }
      return { error: "Bucket not found", bucket_key };
    });
  },
};

const extractPaperSummary: ToolDef = {
  schema: {
    name: "extract_paper_summary",
    description:
      "Atomic step 2/3 of summarize_literature_bucket: for each paper_id in the bucket, read its supporting causal-edge rows from the persisted store. Returns the per-paper evidence array. Pure function of (bucket_id, paper_ids).",
    parameters: {
      type: "object",
      properties: {
        bucket_id: { type: "string" },
        paper_ids: { type: "array", items: { type: "string" } },
      },
      required: ["bucket_id", "paper_ids"],
    },
  },
  async invoke(args) {
    const bucket_id = String(args?.bucket_id || "").trim();
    const paper_ids = Array.isArray(args?.paper_ids)
      ? (args.paper_ids as unknown[]).map(String).slice(0, 200)
      : [];
    if (!bucket_id) return { error: "bucket_id is required" };
    return runAtomicStep(
      "extract_paper_summary",
      { bucket_id, paper_count: paper_ids.length },
      async () => {
        const { causalEdgesForPaper } = await import("../lib/causal-store");
        const paper_evidence: Array<{ paper_id: string; edges: unknown[] }> = [];
        for (const pid of paper_ids) {
          try {
            const edges = await causalEdgesForPaper(pid);
            paper_evidence.push({ paper_id: pid, edges: edges ?? [] });
          } catch (err) {
            logger.debug({ err, pid }, "extract_paper_summary: per-paper read failed");
            paper_evidence.push({ paper_id: pid, edges: [] });
          }
        }
        return { bucket_id, paper_ids, paper_evidence };
      },
    );
  },
};

const aggregateBucketSummary: ToolDef = {
  schema: {
    name: "aggregate_bucket_summary",
    description:
      "Atomic step 3/3 of summarize_literature_bucket: combine the per-paper evidence into the bucket-level pooled estimate (θ̂, CI, method, I²). Reads the persisted bucket row to retrieve the canonical pooled estimate; falls back to a counts-only summary when the bucket has not been ingested yet.",
    parameters: {
      type: "object",
      properties: {
        bucket_id: { type: "string" },
        paper_ids: { type: "array", items: { type: "string" } },
        paper_evidence: { type: "array" },
      },
      required: ["bucket_id", "paper_ids"],
    },
  },
  async invoke(args) {
    const bucket_id = String(args?.bucket_id || "").trim();
    const paper_ids = Array.isArray(args?.paper_ids)
      ? (args.paper_ids as unknown[]).map(String)
      : [];
    if (!bucket_id) return { error: "bucket_id is required" };
    return runAtomicStep(
      "aggregate_bucket_summary",
      { bucket_id, paper_count: paper_ids.length },
      async () => {
        const { causalGetBucket } = await import("../lib/causal-store");
        const pg = await causalGetBucket(bucket_id);
        if (pg) {
          return {
            bucket_id: pg.bucket_id,
            supporting_edges: pg.supporting_edges,
            status: pg.status,
            pooled_estimate: pg.pooled_estimate,
          };
        }
        return {
          bucket_id,
          supporting_edges: paper_ids.length,
          status: "review_required",
          pooled_estimate: null,
          note: "No pooled estimate available — bucket has not been ingested into the persisted causal network yet.",
        };
      },
    );
  },
};

// --- query_opentargets atomic decomposition --------------------------------

const OT_FIND_QUERY =
  `query($q: String!) { search(queryString: $q, entityNames: ["target"]) { hits { id name entity } } }`;
const OT_ASSOC_QUERY = `query($id: String!, $size: Int!) {
  target(ensemblId: $id) {
    id
    approvedSymbol
    approvedName
    associatedDiseases(page: { index: 0, size: $size }) {
      count
      rows {
        score
        datasourceScores { id score }
        disease { id name therapeuticAreas { id name } }
      }
    }
  }
}`;

const opentargetsFindTargetId: ToolDef = {
  schema: {
    name: "opentargets_find_target_id",
    description:
      "Atomic step 1/2 of query_opentargets: one Open Targets GraphQL `search` request that resolves an HGNC gene symbol to an Ensembl target id. Returns null when no target matches.",
    parameters: {
      type: "object",
      properties: {
        gene_symbol: { type: "string" },
      },
      required: ["gene_symbol"],
    },
  },
  async invoke(args) {
    const g = String(args?.gene_symbol || "").trim();
    if (!g) return { error: "gene_symbol is required" };
    return runAtomicStep("opentargets_find_target_id", { gene_symbol: g }, async () => {
      try {
        const lookup = await postJson<{
          data?: { search?: { hits?: Array<{ id: string; name: string }> } };
        }>(OPENTARGETS_BASE, {
          query: OT_FIND_QUERY,
          variables: { q: g },
        });
        const hit = lookup.data?.search?.hits?.[0];
        if (!hit) return { error: `No target found for gene ${g}` };
        return { ensembl_id: hit.id, name: hit.name };
      } catch (err) {
        return { error: err instanceof Error ? err.message : String(err) };
      }
    });
  },
};

const opentargetsGetAssociations: ToolDef = {
  schema: {
    name: "opentargets_get_target_associations",
    description:
      "Atomic step 2/2 of query_opentargets: one Open Targets GraphQL request that fetches target↔disease associations for a known Ensembl id. Pair with opentargets_find_target_id when starting from a gene symbol.",
    parameters: {
      type: "object",
      properties: {
        ensembl_id: { type: "string" },
        size: { type: "integer", minimum: 1, maximum: 25, default: 10 },
      },
      required: ["ensembl_id"],
    },
  },
  async invoke(args) {
    const id = String(args?.ensembl_id || "").trim();
    const size = Math.max(1, Math.min(25, Number(args?.size) || 10));
    if (!id) return { error: "ensembl_id is required" };
    return runAtomicStep(
      "opentargets_get_target_associations",
      { ensembl_id: id, size },
      async () => {
        try {
          const resp = await postJson<{
            data?: {
              target?: {
                id: string;
                approvedSymbol: string;
                approvedName: string;
                associatedDiseases?: {
                  count: number;
                  rows: Array<{
                    score: number;
                    datasourceScores?: Array<{ id: string; score: number }>;
                    disease: { id: string; name: string };
                  }>;
                };
              };
            };
          }>(OPENTARGETS_BASE, {
            query: OT_ASSOC_QUERY,
            variables: { id, size },
          });
          const t = resp.data?.target;
          if (!t) return { error: "Failed to fetch associations" };
          return {
            ensembl_id: t.id,
            approvedSymbol: t.approvedSymbol,
            approvedName: t.approvedName,
            diseases: (t.associatedDiseases?.rows || []).map((r) => ({
              id: r.disease.id,
              name: r.disease.name,
              score: r.score,
              datasources: r.datasourceScores?.length ?? 0,
              url: `https://platform.opentargets.org/disease/${r.disease.id}`,
            })),
          };
        } catch (err) {
          return { error: err instanceof Error ? err.message : String(err) };
        }
      },
    );
  },
};

// --- create_research_task atom 1/3 (Node-side input validator) -------------

const TASK_MODES = new Set([
  "target_discovery",
  "target_ranking",
  "evidence_review",
  "fulltext_upgrade",
  "candidate_compare",
]);

const validateTaskInputs: ToolDef = {
  schema: {
    name: "validate_task_inputs",
    description:
      "Atomic step 1/3 of create_research_task: validate a ResearchTaskSpec against the canonical schema before any side effect. Pure function — no I/O. Returns {validated, warnings}; on failure returns {error}. Use this to pre-flight a task spec before persisting it.",
    parameters: {
      type: "object",
      properties: {
        task_mode: { type: "string" },
        disease: { type: "string" },
        drug: { type: "string" },
        target: { type: "string" },
        mechanism: { type: "string" },
        evidence_preference: {
          type: "string",
          enum: ["any", "human_only", "prefer_human"],
        },
        notes: { type: "string" },
      },
      required: ["task_mode"],
    },
  },
  async invoke(args) {
    const task_mode = String(args?.task_mode || "").trim();
    if (!TASK_MODES.has(task_mode)) {
      return {
        error: `task_mode must be one of ${Array.from(TASK_MODES).join(", ")}`,
      };
    }
    return runAtomicStep("validate_task_inputs", { task_mode }, async () => {
      const validated: Record<string, unknown> = { task_mode };
      const warnings: string[] = [];
      for (const k of [
        "disease",
        "drug",
        "target",
        "mechanism",
        "evidence_preference",
        "notes",
      ]) {
        const v = args?.[k];
        if (typeof v === "string" && v.trim()) validated[k] = v.trim();
      }
      if (
        (task_mode === "target_discovery" || task_mode === "evidence_review") &&
        !validated.disease
      ) {
        warnings.push(
          "task_mode '" + task_mode + "' typically expects a disease label",
        );
      }
      if (task_mode === "candidate_compare" && !validated.drug) {
        warnings.push(
          "task_mode 'candidate_compare' typically expects a drug field",
        );
      }
      return { validated, warnings };
    });
  },
};

export const ATOMIC_TOOLS: ToolDef[] = [
  selectPapersForBucket,
  extractPaperSummary,
  aggregateBucketSummary,
  opentargetsFindTargetId,
  opentargetsGetAssociations,
  validateTaskInputs,
];