AI Prompt Manager

AI Prompt Manager

Capabilities

• Create new AI prompt templates with proper structure
• Generate prompt versions with variable substitution
• Set up feature bindings (vendor/​model/​environment)
• Validate prompt syntax and output schemas
• Configure AI pricing and usage tracking

Database Schema Reference

AI Prompt Tables

ai_prompt_templates (task, name, description)
ai_prompt_versions (template_id, version, system_prompt, user_prompt_template, output_schema, model_hints, status)
ai_prompt_bindings (task, env, prompt_version_id, enabled)

AI Feature Tables

ai_features (key, description)
ai_feature_bindings (feature_key, env, ai_vendor, ai_model, param_overrides, is_active)
ai_pricing (ai_vendor, ai_model, input_usd_per_1k, output_usd_per_1k)
ai_usage_logs (user_id, feature, ai_vendor, ai_model, tokens, cost_usd, status)

Usage Examples

Example 1: Create New AI Feature

User: "Add a new AI feature for verse comparison"

Assistant:

-- 1. Create feature
INSERT INTO bible_schema.ai_features (key, description)
VALUES ('compare_verses', 'Compare and analyze differences between Bible verses');

-- 2. Create prompt template
INSERT INTO bible_schema.ai_prompt_templates (task, name, description)
VALUES (
  'compare_verses',
  'Verse Comparison',
  'Analyzes theological and textual differences between verses'
);

-- 3. Create prompt version
INSERT INTO bible_schema.ai_prompt_versions (
  template_id,
  version,
  system_prompt,
  user_prompt_template,
  output_schema,
  model_hints,
  status
) VALUES (
  (SELECT id FROM bible_schema.ai_prompt_templates WHERE task = 'compare_verses'),
  1,
  'You are a Bible scholar assistant. Compare verses and explain their theological significance.',
  'Compare these verses: {{verse1}} and {{verse2}}. Explain the key differences and similarities.',
  '{"type": "object", "properties": {"differences": {"type": "array"}, "similarities": {"type": "array"}, "theological_significance": {"type": "string"}}}',
  '{"model": "google/​gemini-2.5-flash"}',
  'published'
);

-- 4. Bind to environment
INSERT INTO bible_schema.ai_prompt_bindings (task, env, prompt_version_id, enabled)
VALUES (
  'compare_verses',
  'prod',
  (SELECT id FROM bible_schema.ai_prompt_versions WHERE template_id = (SELECT id FROM bible_schema.ai_prompt_templates WHERE task = 'compare_verses') AND version = 1),
  true
);

-- 5. Configure feature binding
INSERT INTO bible_schema.ai_feature_bindings (
  feature_key,
  env,
  ai_vendor,
  ai_model,
  param_overrides,
  is_active
) VALUES (
  'compare_verses',
  'prod',
  'lovable',
  'google/​gemini-2.5-flash',
  '{"temperature": 0.7, "max_tokens": 1000}',
  true
);

Example 2: Update Existing Prompt

User: "Create a new version of the translate_search_term prompt"

Assistant:

-- Create new version (version 2)
INSERT INTO bible_schema.ai_prompt_versions (
  template_id,
  version,
  system_prompt,
  user_prompt_template,
  output_schema,
  status
) VALUES (
  (SELECT id FROM bible_schema.ai_prompt_templates WHERE task = 'translate_search_term'),
  2,
  'You are a Finnish-English Bible translation expert. Provide accurate theological term translations.',
  'Translate the term "{{term}}" from {{source_language}} to {{target_language}}. Focus on Biblical context. Return JSON: {"main": "primary translation", "synonyms": ["alt1", "alt2"]}',
  '{"type": "object", "properties": {"main": {"type": "string"}, "synonyms": {"type": "array", "items": {"type": "string"}}}}',
  'draft'
);

-- Test the new version in dev environment
UPDATE bible_schema.ai_prompt_bindings
SET prompt_version_id = (
  SELECT id FROM bible_schema.ai_prompt_versions
  WHERE template_id = (SELECT id FROM bible_schema.ai_prompt_templates WHERE task = 'translate_search_term')
  AND version = 2
)
WHERE task = 'translate_search_term' AND env = 'dev';

-- After testing, publish and promote to prod
UPDATE bible_schema.ai_prompt_versions
SET status = 'published'
WHERE template_id = (SELECT id FROM bible_schema.ai_prompt_templates WHERE task = 'translate_search_term')
AND version = 2;

UPDATE bible_schema.ai_prompt_bindings
SET prompt_version_id = (SELECT id FROM bible_schema.ai_prompt_versions WHERE template_id = (SELECT id FROM bible_schema.ai_prompt_templates WHERE task = 'translate_search_term') AND version = 2)
WHERE task = 'translate_search_term' AND env = 'prod';

Example 3: Configure AI Provider

User: "Switch to Anthropic Claude for summaries in production"

Assistant:

-- Update feature binding
UPDATE bible_schema.ai_feature_bindings
SET
  ai_vendor = 'anthropic',
  ai_model = 'claude-3-5-sonnet-20241022',
  param_overrides = '{"max_tokens": 2048, "temperature": 0.7}'
WHERE feature_key = 'ai_summary' AND env = 'prod';

-- Ensure pricing is set
INSERT INTO bible_schema.ai_pricing (ai_vendor, ai_model, input_usd_per_1k, output_usd_per_1k)
VALUES ('anthropic', 'claude-3-5-sonnet-20241022', 0.003, 0.015)
ON CONFLICT (ai_vendor, ai_model) DO UPDATE
SET input_usd_per_1k = 0.003, output_usd_per_1k = 0.015;

Prompt Variable Substitution

Use {{variable}} syntax in prompts:

// System prompt
"You are a {{role}} assistant. Translate from {{source_language}} to {{target_language}}."

// User prompt template
"Translate: {{term}}"

// Edge Function usage
const prompt = await getPrompt('translate_search_term', {
  role: 'theological translation',
  term: 'armo',
  source_language: 'Finnish',
  target_language: 'English'
}, 'prod');

Supported AI Providers

Model Parameter Guidelines

Newer Models (GPT-5, O3, O4)

• Use max_completion_tokens (not max_tokens)
• No temperature parameter
• Example: {"max_completion_tokens": 1000}

Legacy Models (GPT-4o, Gemini)

• Use max_tokens
• Support temperature
• Example: {"max_tokens": 1000, "temperature": 0.7}

Environment Strategy

1. dev - Experimental prompts and features
2. stage - Testing before production
3. prod - Live user-facing features

Always test in dev → stage → prod progression.

Prompt Best Practices

1. Clear instructions - Be specific about the task
2. JSON output - Define explicit output schema
3. Variable names - Use descriptive {{variable}} names
4. Examples - Include examples in system prompt when possible
5. Context - Provide enough context for accurate responses
6. Token limits - Set appropriate max_tokens for the task
7. Temperature - Lower (0.3-0.5) for factual, higher (0.7-0.9) for creative

Cost Optimization

1. Use cheaper models (gemini-2.5-flash) for simple tasks
2. Cache AI responses in term_translations table
3. Set reasonable max_tokens limits
4. Monitor usage in ai_usage_logs
5. Use fallback prompts for critical features

Testing AI Features

Use the Admin AI page → Testaus tab:

1. Select feature
2. Input test variables
3. Review response, tokens, cost
4. Iterate on prompt if needed

Related Documentation

• See Docs/​06-AI-ARCHITECTURE.md for AI system details
• See Docs/​07-ADMIN-GUIDE.md for Admin AI page usage