feat: token count implement

This commit is contained in:
2026-03-17 12:07:56 -03:00
parent 41279585f6
commit be699ad6ab
44 changed files with 9032 additions and 167 deletions
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-- Question Bank: Centralized repository for reusable questions
-- Supports multiple question types, audio generation, and multi-tenant organization
-- Question types supported by the platform
CREATE TYPE question_bank_type AS ENUM (
'multiple-choice', -- Multiple choice with single/multiple correct answers
'true-false', -- True/False questions
'short-answer', -- Short text answer
'essay', -- Long form text answer
'matching', -- Match pairs
'ordering', -- Order items correctly
'fill-in-the-blanks', -- Fill in missing words
'audio-response', -- Record audio answer
'hotspot', -- Click on image area
'code-lab' -- Code exercise
);
-- Question Bank table
CREATE TABLE question_bank (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
organization_id UUID NOT NULL REFERENCES organizations(id) ON DELETE CASCADE,
-- Question content
question_text TEXT NOT NULL,
question_type question_bank_type NOT NULL,
-- Answers and options (structure depends on question_type)
options JSONB, -- Array of options for multiple-choice/true-false
correct_answer JSONB, -- Correct answer(s) - format varies by type
explanation TEXT, -- Explanation shown after answering (AI generated or manual)
-- Audio support (Bark TTS)
audio_url TEXT, -- URL to generated audio file
audio_text TEXT, -- Text used for audio generation (may differ from question_text)
audio_status VARCHAR(50) DEFAULT 'pending', -- pending, generating, ready, failed
audio_metadata JSONB, -- Bark generation parameters
-- Media support
media_url TEXT, -- Image/video URL for hotspot or context questions
media_type VARCHAR(50), -- image, video
-- Metadata
points INTEGER NOT NULL DEFAULT 1,
difficulty VARCHAR(20) DEFAULT 'medium', -- easy, medium, hard
tags TEXT[], -- For searching and categorization
skill_assessed VARCHAR(20), -- reading, listening, speaking, writing
-- Source tracking
source VARCHAR(50) DEFAULT 'manual', -- manual, ai-generated, imported-mysql, imported-csv
source_metadata JSONB, -- Original source data (e.g., MySQL question ID)
imported_mysql_id INTEGER, -- Original MySQL question ID to prevent re-import
imported_mysql_course_id INTEGER, -- Original MySQL course ID
-- Usage tracking
usage_count INTEGER DEFAULT 0, -- How many times used in templates/courses
last_used_at TIMESTAMPTZ,
-- Status
is_active BOOLEAN DEFAULT true,
is_archived BOOLEAN DEFAULT false,
-- Audit
created_by UUID REFERENCES users(id) ON DELETE SET NULL,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
updated_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
-- Constraints
CONSTRAINT question_bank_points_positive CHECK (points > 0)
);
-- Indexes for performance
CREATE INDEX idx_question_bank_org ON question_bank(organization_id);
CREATE INDEX idx_question_bank_type ON question_bank(question_type);
CREATE INDEX idx_question_bank_difficulty ON question_bank(difficulty);
CREATE INDEX idx_question_bank_tags ON question_bank USING GIN(tags);
CREATE INDEX idx_question_bank_source ON question_bank(source);
CREATE INDEX idx_question_bank_active ON question_bank(is_active) WHERE is_active = true;
CREATE INDEX idx_question_bank_search ON question_bank USING GIN(to_tsvector('english', question_text));
-- Question Bank Categories (optional organization)
CREATE TABLE question_bank_categories (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
organization_id UUID NOT NULL REFERENCES organizations(id) ON DELETE CASCADE,
name VARCHAR(100) NOT NULL,
parent_id UUID REFERENCES question_bank_categories(id) ON DELETE CASCADE,
description TEXT,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
UNIQUE(organization_id, name)
);
-- Link questions to categories
CREATE TABLE question_bank_question_categories (
question_id UUID NOT NULL REFERENCES question_bank(id) ON DELETE CASCADE,
category_id UUID NOT NULL REFERENCES question_bank_categories(id) ON DELETE CASCADE,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
PRIMARY KEY (question_id, category_id)
);
-- Question Bank Usage History (track where questions are used)
CREATE TABLE question_bank_usage (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
question_id UUID NOT NULL REFERENCES question_bank(id) ON DELETE CASCADE,
used_in_type VARCHAR(50) NOT NULL, -- template, lesson, quiz
used_in_id UUID NOT NULL, -- ID of the template/lesson/quiz
organization_id UUID NOT NULL,
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW(),
created_by UUID REFERENCES users(id) ON DELETE SET NULL
);
CREATE INDEX idx_question_bank_usage_question ON question_bank_usage(question_id);
CREATE INDEX idx_question_bank_usage_used_in ON question_bank_usage(used_in_type, used_in_id);
-- Trigger to update updated_at
CREATE TRIGGER trg_question_bank_updated_at
BEFORE UPDATE ON question_bank
FOR EACH ROW
EXECUTE FUNCTION update_test_templates_updated_at(); -- Reuse existing function
-- Function to increment usage count
CREATE OR REPLACE FUNCTION increment_question_usage(p_question_id UUID, p_used_in_type VARCHAR, p_used_in_id UUID, p_org_id UUID, p_user_id UUID)
RETURNS VOID AS $$
BEGIN
-- Update usage count
UPDATE question_bank
SET usage_count = usage_count + 1,
last_used_at = NOW()
WHERE id = p_question_id;
-- Log usage
INSERT INTO question_bank_usage (question_id, used_in_type, used_in_id, organization_id, created_by)
VALUES (p_question_id, p_used_in_type, p_used_in_id, p_org_id, p_user_id);
END;
$$ LANGUAGE plpgsql;
-- Function to import question from MySQL
CREATE OR REPLACE FUNCTION import_question_from_mysql(
p_org_id UUID,
p_user_id UUID,
p_question_text TEXT,
p_question_type question_bank_type,
p_options JSONB,
p_correct_answer JSONB,
p_source_metadata JSONB
)
RETURNS UUID AS $$
DECLARE
v_question_id UUID;
BEGIN
INSERT INTO question_bank (
organization_id, created_by, question_text, question_type,
options, correct_answer, source, source_metadata,
audio_status, is_active
)
VALUES (
p_org_id, p_user_id, p_question_text, p_question_type,
p_options, p_correct_answer, 'imported-mysql', p_source_metadata,
'pending', true
)
RETURNING id INTO v_question_id;
RETURN v_question_id;
END;
$$ LANGUAGE plpgsql;
-- Comments
COMMENT ON TABLE question_bank IS 'Centralized repository for reusable questions across the organization';
COMMENT ON COLUMN question_bank.question_type IS 'Type of question: multiple-choice, true-false, short-answer, essay, matching, ordering, fill-in-the-blanks, audio-response, hotspot, code-lab';
COMMENT ON COLUMN question_bank.audio_url IS 'URL to Bark-generated audio file for text-to-speech';
COMMENT ON COLUMN question_bank.audio_status IS 'Status of audio generation: pending, generating, ready, failed';
COMMENT ON COLUMN question_bank.source IS 'Origin: manual (created by user), ai-generated, imported-mysql, imported-csv';
COMMENT ON COLUMN question_bank.source_metadata IS 'Original source data, e.g., {mysql_table: "bancopreguntas", idPregunta: 123, idCursos: 456}';
COMMENT ON TABLE question_bank_usage IS 'Tracks where each question is used (templates, lessons, quizzes)';
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-- AI Usage Logs: Track token consumption per user for billing and limits
CREATE TABLE ai_usage_logs (
id UUID PRIMARY KEY DEFAULT gen_random_uuid(),
user_id UUID NOT NULL REFERENCES users(id) ON DELETE CASCADE,
organization_id UUID NOT NULL REFERENCES organizations(id) ON DELETE CASCADE,
-- Token counts
tokens_used INTEGER NOT NULL DEFAULT 0,
input_tokens INTEGER NOT NULL DEFAULT 0,
output_tokens INTEGER NOT NULL DEFAULT 0,
-- Request metadata
endpoint VARCHAR(255), -- e.g., "/lessons/generate-quiz"
model VARCHAR(100), -- e.g., "llama3.2:3b", "gpt-4o"
request_type VARCHAR(50), -- "transcription", "quiz-generation", "chat", "summary"
request_metadata JSONB, -- Additional context about the request
-- Cost estimation (optional, can be calculated later)
estimated_cost_usd NUMERIC(10, 6),
-- Timestamps
created_at TIMESTAMPTZ NOT NULL DEFAULT NOW()
);
-- Indexes for performance
CREATE INDEX idx_ai_usage_user ON ai_usage_logs(user_id);
CREATE INDEX idx_ai_usage_org ON ai_usage_logs(organization_id);
CREATE INDEX idx_ai_usage_created ON ai_usage_logs(created_at);
CREATE INDEX idx_ai_usage_endpoint ON ai_usage_logs(endpoint);
CREATE INDEX idx_ai_usage_type ON ai_usage_logs(request_type);
-- Function to log AI usage
CREATE OR REPLACE FUNCTION log_ai_usage(
p_user_id UUID,
p_org_id UUID,
p_tokens INTEGER,
p_input_tokens INTEGER,
p_output_tokens INTEGER,
p_endpoint VARCHAR,
p_model VARCHAR,
p_request_type VARCHAR,
p_metadata JSONB
)
RETURNS UUID AS $$
DECLARE
v_log_id UUID;
v_cost NUMERIC(10, 6);
BEGIN
-- Calculate estimated cost (OpenAI-like pricing)
v_cost := (p_input_tokens::NUMERIC * 0.000001) + (p_output_tokens::NUMERIC * 0.000003);
INSERT INTO ai_usage_logs (
user_id, organization_id, tokens_used, input_tokens, output_tokens,
endpoint, model, request_type, request_metadata, estimated_cost_usd
)
VALUES (
p_user_id, p_org_id, p_tokens, p_input_tokens, p_output_tokens,
p_endpoint, p_model, p_request_type, p_metadata, v_cost
)
RETURNING id INTO v_log_id;
RETURN v_log_id;
END;
$$ LANGUAGE plpgsql;
-- Daily aggregation view for reporting
CREATE VIEW ai_usage_daily AS
SELECT
DATE(created_at) as usage_date,
user_id,
organization_id,
request_type,
SUM(tokens_used) as total_tokens,
SUM(input_tokens) as total_input,
SUM(output_tokens) as total_output,
COUNT(*) as request_count,
SUM(estimated_cost_usd) as total_cost
FROM ai_usage_logs
GROUP BY DATE(created_at), user_id, organization_id, request_type;
-- Comments
COMMENT ON TABLE ai_usage_logs IS 'Tracks AI token usage per user for billing, limits, and analytics';
COMMENT ON COLUMN ai_usage_logs.tokens_used IS 'Total tokens (input + output)';
COMMENT ON COLUMN ai_usage_logs.input_tokens IS 'Tokens in the prompt/request';
COMMENT ON COLUMN ai_usage_logs.output_tokens IS 'Tokens in the AI response';
COMMENT ON COLUMN ai_usage_logs.estimated_cost_usd IS 'Estimated cost based on OpenAI-like pricing';