import {
  askDocDoe,
  generateBrainDeepChapter,
  generateBrainExamAnswer,
  generateBrainFlashcards,
  generateBrainLastNightPlan,
  generateBrainNotes,
  generateBrainPyqAnalysis,
  generateBrainQuiz,
  generateBrainVisualLesson,
  generateStudyPath,
} from "@/lib/api/brain";
import type { ApiDocument, BrainGeneratePayload } from "@/lib/api/types";
import { buildStructuredStudyResponse, shouldUseStructuredStudyResponse } from "@/lib/phase3-learning";
import type { StudyIntent } from "@/lib/study-intents";
import { askModeForIntent, type StudyBrainContext } from "./study-brain-context";
import type { StudyCard, StudyCardMeta } from "./types";

export type RunStudyGenerationInput = {
  intent: StudyIntent;
  prompt: string;
  topic?: string | null;
  sourceIds: string[];
  selectedDocuments: ApiDocument[];
  brainContext?: StudyBrainContext;
  /**
   * When true, source IDs are stripped before calling the API.
   * Use for "general_answer" mode where the user asked a topic
   * question without explicitly requesting their uploaded material.
   */
  generalMode?: boolean;
};

function revisionTimeLeftForPrompt(prompt: string) {
  const value = prompt.toLowerCase();
  if (/\b(30\s*min|half\s*hour)\b/.test(value)) return "30_minutes";
  if (/\b(1\s*hour|one\s*hour|60\s*min)\b/.test(value)) return "1_hour";
  if (/\b(2\s*hours?|two\s*hours?)\b/.test(value)) return "2_hours";
  if (/\b(3\s*hours?|three\s*hours?)\b/.test(value)) return "3_hours";
  if (/\b(5\s*hours?|five\s*hours?|half\s*day)\b/.test(value)) return "5_hours";
  if (/\b(tonight|one\s+night|overnight|cram|last\s+night)\b/.test(value)) return "tonight";
  if (/\b(tomorrow|next\s+day|1\s*day|one\s*day)\b/.test(value)) return "tomorrow";
  return "tonight";
}

function generationPayload(
  generationTopic: string,
  sourceIds: string[],
  brainContext?: StudyBrainContext,
  extra: Partial<BrainGeneratePayload> = {},
): BrainGeneratePayload {
  return {
    topic: generationTopic,
    source_id: sourceIds[0] ?? null,
    source_ids: sourceIds,
    subject: brainContext?.subject ?? null,
    study_profile_id: brainContext?.studyProfileId ?? null,
    level: brainContext?.level ?? null,
    language_preference: brainContext?.languagePreference ?? null,
    ...extra,
  };
}

const GENERAL_EVIDENCE_LABEL = "No source attached - general answer";

export function metaFromResponse(response: {
  trust_note?: string | null;
  evidence_label?: string | null;
  is_fallback?: boolean;
  suggested_actions?: string[];
  citations?: unknown[];
}, sourceIds: string[] = []): StudyCardMeta {
  const trustNote = response.trust_note ?? null;
  const evidenceLabel = response.evidence_label ?? null;
  const citations = Array.isArray(response.citations) ? response.citations : [];
  const looksSourceBacked = evidenceLabel ? /uploaded|source|material|paper/i.test(evidenceLabel) : false;
  const saysNoSource = trustNote ? /no source attached|not source-grounded|generic/i.test(trustNote) : false;
  const shouldUseGeneralLabel = sourceIds.length === 0 && citations.length === 0 && (saysNoSource || looksSourceBacked);

  return {
    trustNote,
    evidenceLabel: shouldUseGeneralLabel ? GENERAL_EVIDENCE_LABEL : evidenceLabel,
    isFallback: Boolean(response.is_fallback),
    suggestedActions: response.suggested_actions ?? [],
  };
}

export async function runStudyGeneration({
  intent,
  prompt,
  topic,
  sourceIds: rawSourceIds,
  selectedDocuments,
  brainContext,
  generalMode = false,
}: RunStudyGenerationInput): Promise<StudyCard> {
  const sourceIds = generalMode ? [] : rawSourceIds;
  const generationTopic = topic?.trim() || prompt;

  if (sourceIds.length === 0 && shouldUseStructuredStudyResponse(prompt, intent)) {
    const data = buildStructuredStudyResponse(prompt);
    return {
      kind: "structured_study_response",
      data,
      topic: data.topic || generationTopic,
      meta: {
        trustNote: "Frontend fallback. Backend structured chapter contract is still a TODO.",
        evidenceLabel: "No source attached - Study Chat fallback",
        isFallback: true,
      },
    };
  }

  if (intent === "analyze_pyq" || intent === "predict_questions") {
    const response = await generateBrainPyqAnalysis(
      generationPayload(generationTopic, sourceIds, brainContext, {
        subject: selectedDocuments[0]?.subject ?? brainContext?.subject ?? null,
        options: { raw_text: prompt },
      }),
    );
    return {
      kind: "pyq_analysis",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "generate_notes" || intent === "show_formulas") {
    const response = await generateBrainNotes(
      generationPayload(generationTopic, sourceIds, brainContext, {
        options: { mode: intent === "show_formulas" ? "formulas" : "smart_notes" },
      }),
    );
    return {
      kind: "notes",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "generate_quiz") {
    const response = await generateBrainQuiz(
      generationPayload(generationTopic, sourceIds, brainContext, {
        options: { num_questions: 8 },
      }),
    );
    return {
      kind: "quiz",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "generate_flashcards") {
    const response = await generateBrainFlashcards(
      generationPayload(generationTopic, sourceIds, brainContext, {
        options: { card_count: 10 },
      }),
    );
    return {
      kind: "flashcards",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "generate_exam_answer") {
    const response = await generateBrainExamAnswer(
      generationPayload(generationTopic, sourceIds, brainContext),
    );
    return {
      kind: "exam_answer",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "create_revision_plan") {
    const response = await generateBrainLastNightPlan(
      generationPayload(generationTopic, sourceIds, brainContext, {
        time_left: revisionTimeLeftForPrompt(prompt),
      }),
    );
    return {
      kind: "revision_plan",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "continue_learning") {
    const response = await generateStudyPath({
      raw_text: prompt,
      source_id: sourceIds[0] ?? null,
      source_ids: sourceIds,
      subject: brainContext?.subject ?? selectedDocuments[0]?.subject ?? null,
      topic: generationTopic,
      goal: "School exam tuition path",
      time_left: "next exam",
      use_my_profile: true,
      level: brainContext?.level ?? null,
      language_preference: brainContext?.languagePreference ?? null,
    });
    return {
      kind: "study_path",
      data: response,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "create_video_plan" || intent === "render_video") {
    const response = await generateBrainVisualLesson(
      generationPayload(generationTopic, sourceIds, brainContext, {
        options: { raw_text: prompt, mode: "visual_lesson" },
      }),
    );
    return {
      kind: "visual_lesson",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  if (intent === "teach_topic" || intent === "ask_doubt" || intent === "explain_source" || intent === "summarize_source" || intent === "use_syllabus_chapter") {
    const response = await generateBrainDeepChapter(
      generationPayload(generationTopic, sourceIds, brainContext, {
        options: { raw_text: prompt },
      }),
    );
    return {
      kind: "deep_chapter",
      data: response.output,
      topic: response.topic || generationTopic,
      meta: metaFromResponse(response, sourceIds),
    };
  }

  const response = await askDocDoe({
    question: prompt,
    source_id: sourceIds[0] ?? null,
    source_ids: sourceIds,
    mode: askModeForIntent(intent, prompt),
    level: brainContext?.level ?? null,
    language_preference: brainContext?.languagePreference ?? null,
    study_profile_id: brainContext?.studyProfileId ?? null,
  });

  return {
    kind: "explanation",
    data: response,
    topic: generationTopic,
    intent,
    meta: metaFromResponse(response, sourceIds),
  };
}