/**
 * OpenRouter provider — OpenAI-compatible chat completions.
 *
 * Exports:
 *   sendOnce()        — non-streaming, single call (no tools)
 *   streamWithTools() — streaming + tool-call loop (Pattern C)
 *
 * The tool-call loop runs locally:
 *   1. Call model with messages + tools, stream=true.
 *   2. Read SSE deltas: text → emit `text_delta`; tool_calls → buffer args by id.
 *   3. When finish_reason='tool_calls': execute handlers locally, push results
 *      back as tool messages, call model again. Repeat until finish='stop'.
 *   4. When done: emit `done`.
 *
 * Free models (May 2026):
 *   deepseek/deepseek-v4-flash:free            — primary, solid tool calling
 *   nvidia/nemotron-3-super-120b-a12b:free     — fallback
 */
import type { AGUIEvent } from "./agui";
import { TOOL_DEFINITIONS, TOOL_HANDLERS, type ToolHandlerContext } from "./tools";

const PRIMARY = process.env.OPENROUTER_MODEL || "deepseek/deepseek-v4-flash:free";
const FALLBACK = process.env.OPENROUTER_FALLBACK_MODEL || "nvidia/nemotron-3-super-120b-a12b:free";
const ENDPOINT = "https://openrouter.ai/api/v1/chat/completions";

type OAMsg =
  | { role: "system" | "user"; content: string }
  | { role: "assistant"; content?: string | null; tool_calls?: OAToolCall[] }
  | { role: "tool"; content: string; tool_call_id: string; name?: string };

interface OAToolCall {
  id: string;
  type: "function";
  function: { name: string; arguments: string };
}

interface OADelta {
  role?: string;
  content?: string;
  tool_calls?: Array<{
    index: number;
    id?: string;
    type?: string;
    function?: { name?: string; arguments?: string };
  }>;
}

interface OAStreamChunk {
  choices?: Array<{
    delta?: OADelta;
    finish_reason?: string | null;
    message?: { role: string; content?: string | null; tool_calls?: OAToolCall[] };
  }>;
  usage?: { prompt_tokens?: number; completion_tokens?: number; total_tokens?: number };
  model?: string;
  error?: { message?: string };
}

function headers() {
  const apiKey = process.env.OPENROUTER_API_KEY;
  if (!apiKey) throw new Error("OPENROUTER_API_KEY not set");
  return {
    "Authorization": `Bearer ${apiKey}`,
    "Content-Type": "application/json",
    "HTTP-Referer": process.env.NEXT_PUBLIC_SITE_URL || "https://disclosure.top",
    "X-Title": "The Disclosure Bureau",
  };
}

export interface SendOnceReq {
  system: string;
  messages: Array<{ role: "user" | "assistant" | "system"; content: string }>;
  maxTokens?: number;
}

/** Non-streaming single shot — used by claude-code fallback path and tests. */
export async function sendOnce(req: SendOnceReq, model = PRIMARY): Promise<{
  content: string;
  model: string;
  tokensIn?: number;
  tokensOut?: number;
}> {
  const body = {
    model,
    messages: [
      { role: "system", content: req.system },
      ...req.messages.slice(-20),
    ],
    max_tokens: req.maxTokens ?? 1024,
  };
  const res = await fetch(ENDPOINT, {
    method: "POST",
    headers: headers(),
    body: JSON.stringify(body),
  });
  if (!res.ok) {
    const txt = await res.text();
    const err = new Error(`openrouter HTTP ${res.status}: ${txt.slice(0, 300)}`);
    if (res.status === 429 || res.status === 402) {
      (err as Error & { isRateLimit?: boolean }).isRateLimit = true;
    }
    throw err;
  }
  const data = await res.json();
  if (data.error) throw new Error(`openrouter error: ${data.error.message}`);
  return {
    content: data.choices?.[0]?.message?.content ?? "",
    model: data.model ?? model,
    tokensIn: data.usage?.prompt_tokens,
    tokensOut: data.usage?.completion_tokens,
  };
}

/* ─── Pattern C: streaming + tool-call loop ─────────────────────────────── */

export interface StreamRequest {
  system: string;
  history: Array<{ role: "user" | "assistant"; content: string }>;
  userTurn: string;
  ctx: ToolHandlerContext;
  maxTurns?: number; // max tool-call loop iterations
}

export interface StreamCallbacks {
  emit: (ev: AGUIEvent) => void;
}

/**
 * Stream with tool-call loop. Returns the final assistant content (assembled
 * across deltas + after all tool calls resolved) plus token usage.
 *
 * The caller is responsible for closing the SSE stream after this resolves.
 */
export async function streamWithTools(
  req: StreamRequest,
  cb: StreamCallbacks,
): Promise<{
  content: string;
  model: string;
  tokensIn: number;
  tokensOut: number;
  toolCalls: Array<{ name: string; args: Record<string, unknown>; result: unknown }>;
  artifacts: import("./agui").Artifact[];
}> {
  const maxTurns = req.maxTurns ?? 5;
  // Collect artifacts silently — do NOT emit them to the SSE stream while
  // tools are running. We only know which ones are "relevant" after the
  // model has written its final prose, by matching [[doc-id/p007#cNNNN]]
  // citations in the text. Whatever isn't cited gets dropped to keep the
  // chat UI focused on the actual answer.
  const collectedArtifacts: import("./agui").Artifact[] = [];
  const originalEmit = cb.emit;
  cb = {
    emit: (ev) => {
      if (ev.type === "artifact") {
        collectedArtifacts.push(ev.artifact);
        return; // suppressed — emitted later after filtering
      }
      originalEmit(ev);
    },
  };
  const messages: OAMsg[] = [
    { role: "system", content: req.system },
    ...req.history.map((m): OAMsg => ({
      role: m.role,
      content: m.content,
    })),
    { role: "user", content: req.userTurn },
  ];

  let assembledText = "";
  let totalIn = 0;
  let totalOut = 0;
  let modelUsed = PRIMARY;
  const toolTrace: Array<{ name: string; args: Record<string, unknown>; result: unknown }> = [];

  for (let turn = 0; turn < maxTurns; turn++) {
    // Run one round.
    let model = PRIMARY;
    let res: Response;
    try {
      res = await openrouterStreamCall(messages, model);
    } catch (e) {
      if ((e as Error & { isRateLimit?: boolean }).isRateLimit) {
        model = FALLBACK;
        res = await openrouterStreamCall(messages, model);
      } else throw e;
    }
    modelUsed = model;

    if (!res.body) throw new Error("openrouter: no response body");
    const { roundText, finishReason, toolCalls, usage } = await readSSE(res.body, cb);
    assembledText += roundText;
    totalIn += usage?.prompt_tokens ?? 0;
    totalOut += usage?.completion_tokens ?? 0;

    if (finishReason === "tool_calls" && toolCalls.length > 0) {
      // Append the assistant's tool-call turn to message history
      messages.push({
        role: "assistant",
        content: roundText || null,
        tool_calls: toolCalls,
      });
      // Execute each tool locally
      for (const tc of toolCalls) {
        let argsObj: Record<string, unknown> = {};
        try { argsObj = JSON.parse(tc.function.arguments || "{}"); }
        catch { /* malformed — pass empty */ }
        cb.emit({ type: "tool_start", id: tc.id, name: tc.function.name, args: argsObj });
        const handler = TOOL_HANDLERS[tc.function.name];
        const t0 = Date.now();
        let result: unknown;
        // Per-tool artifact sink: bridges typed artifacts produced by the
        // handler into the SSE stream as `artifact` events.
        const ctxWithSink: ToolHandlerContext = {
          ...req.ctx,
          emitArtifact: (artifact) => cb.emit({ type: "artifact", artifact }),
        };
        try {
          if (!handler) throw new Error(`unknown tool: ${tc.function.name}`);
          result = await handler(argsObj, ctxWithSink);
        } catch (e) {
          result = { error: e instanceof Error ? e.message : String(e) };
        }
        const dt = Date.now() - t0;
        cb.emit({ type: "tool_result", id: tc.id, result, durationMs: dt });
        toolTrace.push({ name: tc.function.name, args: argsObj, result });

        // Surface navigate_to as a UI event the frontend can render as a button
        if (tc.function.name === "navigate_to") {
          const target = String(argsObj.target ?? "");
          const label = String(argsObj.label ?? target);
          if (target.startsWith("/")) {
            cb.emit({ type: "navigate", target, label });
          }
        }

        // Append the tool result for the model
        messages.push({
          role: "tool",
          tool_call_id: tc.id,
          name: tc.function.name,
          content: JSON.stringify(result).slice(0, 8000),
        });
      }
      // Continue loop — model will see tool results and produce next turn
      continue;
    }

    // No tool calls → done
    break;
  }

  // Forced synthesis: free-tier models often exhaust the tool-call budget
  // without ever producing prose, returning content_len=0. If the loop ended
  // with empty text but the model did call tools, force ONE more turn without
  // tools so the model must answer in plain text.
  if (!assembledText.trim() && toolTrace.length > 0) {
    cb.emit({
      type: "text_delta",
      delta: "",
    });
    messages.push({
      role: "user",
      content:
        "Com base nas ferramentas que você acabou de chamar e nos resultados acima, " +
        "responda agora ao usuário EM TEXTO (3-8 frases), em português brasileiro. " +
        "Cite os chunks no formato [[doc-id/p007#c0042]]. Não chame mais nenhuma ferramenta.",
    });
    try {
      const res = await openrouterStreamCall(messages, modelUsed, { withTools: false });
      if (res.body) {
        const final = await readSSE(res.body, cb);
        assembledText += final.roundText;
        totalIn += final.usage?.prompt_tokens ?? 0;
        totalOut += final.usage?.completion_tokens ?? 0;
      }
    } catch (e) {
      cb.emit({ type: "error", message: `synthesis failed: ${e instanceof Error ? e.message : String(e)}` });
    }
  }

  // Filter artifacts to only those actually cited in the assistant's prose.
  // Citation grammar: [[doc-id]], [[doc-id/p007]], [[doc-id#c0042]],
  // [[doc-id/p007#c0042]]. The chunk anchor (cNNNN) is the strongest signal.
  const citedChunks = new Set<string>();
  const citedDocs = new Set<string>();
  const wikiLinkRe = /\[\[([^\]|]+?)(?:\|[^\]]+)?\]\]/g;
  let m: RegExpExecArray | null;
  while ((m = wikiLinkRe.exec(assembledText)) !== null) {
    const target = m[1].trim();
    const chunkMatch = target.match(/(c\d{4})$/i);
    if (chunkMatch) citedChunks.add(chunkMatch[1].toLowerCase());
    // Doc id is whatever comes before the first `/` or `#`
    const docMatch = target.match(/^([A-Za-z0-9._-]+)/);
    if (docMatch) citedDocs.add(docMatch[1]);
  }

  const relevantArtifacts = collectedArtifacts.filter((a) => {
    if (a.kind === "citation") {
      return citedChunks.has(a.chunk_id.toLowerCase()) ||
             (citedDocs.has(a.doc_id) && citedChunks.size === 0);
    }
    if (a.kind === "crop_image") {
      if (a.chunk_id && citedChunks.has(a.chunk_id.toLowerCase())) return true;
      return false;
    }
    // Entity / case / hypothesis / nav cards have no chunk reference — keep
    // them all; they are rarely emitted by hybrid_search anyway.
    return true;
  });

  // Now emit the filtered set so the UI renders only the relevant cards.
  // De-dupe by kind+key so a citation and its crop_image both fire but no
  // duplicate citations of the same chunk_id appear.
  const seen = new Set<string>();
  for (const a of relevantArtifacts) {
    const key =
      a.kind === "citation" ? `cit:${a.chunk_id}` :
      a.kind === "crop_image" ? `crop:${a.chunk_id ?? a.src}` :
      `${a.kind}:${JSON.stringify(a)}`;
    if (seen.has(key)) continue;
    seen.add(key);
    originalEmit({ type: "artifact", artifact: a });
  }

  return {
    content: assembledText,
    model: modelUsed,
    tokensIn: totalIn,
    tokensOut: totalOut,
    toolCalls: toolTrace,
    artifacts: relevantArtifacts,
  };
}

async function openrouterStreamCall(
  messages: OAMsg[],
  model: string,
  opts: { withTools?: boolean } = {},
): Promise<Response> {
  const withTools = opts.withTools !== false;
  const body: Record<string, unknown> = {
    model,
    messages,
    stream: true,
    max_tokens: 1024,
  };
  if (withTools) {
    body.tools = TOOL_DEFINITIONS;
    body.tool_choice = "auto";
  }
  const res = await fetch(ENDPOINT, {
    method: "POST",
    headers: headers(),
    body: JSON.stringify(body),
  });
  if (!res.ok) {
    const txt = await res.text();
    const err = new Error(`openrouter HTTP ${res.status}: ${txt.slice(0, 300)}`);
    if (res.status === 429 || res.status === 402) {
      (err as Error & { isRateLimit?: boolean }).isRateLimit = true;
    }
    throw err;
  }
  return res;
}

/**
 * Read OpenRouter SSE stream. Emits text_delta events via cb.emit. Returns
 * assembled text, finish_reason, accumulated tool_calls, and usage.
 */
async function readSSE(
  body: ReadableStream<Uint8Array>,
  cb: StreamCallbacks,
): Promise<{
  roundText: string;
  finishReason: string | null;
  toolCalls: OAToolCall[];
  usage?: { prompt_tokens?: number; completion_tokens?: number };
}> {
  const reader = body.getReader();
  const decoder = new TextDecoder();
  let buffer = "";
  let roundText = "";
  let finishReason: string | null = null;
  // tool_calls arrive as deltas across many chunks; accumulate by index.
  const toolBufs: Record<number, { id: string; name: string; args: string }> = {};
  let usage: { prompt_tokens?: number; completion_tokens?: number } | undefined;

  for (;;) {
    const { value, done } = await reader.read();
    if (done) break;
    buffer += decoder.decode(value, { stream: true });

    // SSE messages are separated by \n\n
    let idx: number;
    while ((idx = buffer.indexOf("\n\n")) !== -1) {
      const raw = buffer.slice(0, idx);
      buffer = buffer.slice(idx + 2);

      // Each message may have multiple lines; we care about "data: ..."
      for (const line of raw.split("\n")) {
        if (!line.startsWith("data: ")) continue;
        const payload = line.slice(6).trim();
        if (payload === "[DONE]") {
          return { roundText, finishReason, toolCalls: collectToolCalls(toolBufs), usage };
        }
        let chunk: OAStreamChunk;
        try { chunk = JSON.parse(payload); }
        catch { continue; }
        if (chunk.error) throw new Error(`openrouter stream error: ${chunk.error.message}`);
        if (chunk.usage) usage = chunk.usage;

        const choice = chunk.choices?.[0];
        if (!choice) continue;
        const d = choice.delta ?? {};
        if (typeof d.content === "string" && d.content) {
          roundText += d.content;
          cb.emit({ type: "text_delta", delta: d.content });
        }
        if (Array.isArray(d.tool_calls)) {
          for (const tc of d.tool_calls) {
            const slot = (toolBufs[tc.index] ??= { id: "", name: "", args: "" });
            if (tc.id) slot.id = tc.id;
            if (tc.function?.name) slot.name = tc.function.name;
            if (tc.function?.arguments) slot.args += tc.function.arguments;
          }
        }
        if (choice.finish_reason) finishReason = choice.finish_reason;
      }
    }
  }
  return { roundText, finishReason, toolCalls: collectToolCalls(toolBufs), usage };
}

function collectToolCalls(bufs: Record<number, { id: string; name: string; args: string }>): OAToolCall[] {
  return Object.values(bufs)
    .filter((b) => b.id && b.name)
    .map((b) => ({
      id: b.id,
      type: "function" as const,
      function: { name: b.name, arguments: b.args || "{}" },
    }));
}