Implement Azure OpenAI vector embeddings for Romanian Bible

- Add pgvector support with bible_passages table for vector search
- Create Python ingestion script for Azure OpenAI embed-3 embeddings
- Implement hybrid search combining vector similarity and full-text search
- Update AI chat to use vector search with Azure OpenAI gpt-4o
- Add floating chat component with Material UI design
- Import complete Romanian Bible (FIDELA) with 30K+ verses
- Add vector search library for semantic Bible search
- Create multi-language implementation plan for future expansion

🤖 Generated with [Claude Code](https://claude.ai/code)

Co-Authored-By: Claude <noreply@anthropic.com>

lib/vector-search.ts

@@ -0,0 +1,140 @@
+import { Pool } from 'pg'
+
+const pool = new Pool({
+  connectionString: process.env.DATABASE_URL,
+})
+
+export interface BibleVerse {
+  id: string
+  ref: string
+  book: string
+  chapter: number
+  verse: number
+  text_raw: string
+  similarity?: number
+  combined_score?: number
+}
+
+export async function getEmbedding(text: string): Promise<number[]> {
+  const response = await fetch(
+    `${process.env.AZURE_OPENAI_ENDPOINT}/openai/deployments/${process.env.AZURE_OPENAI_EMBED_DEPLOYMENT}/embeddings?api-version=${process.env.AZURE_OPENAI_API_VERSION}`,
+    {
+      method: 'POST',
+      headers: {
+        'api-key': process.env.AZURE_OPENAI_KEY!,
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        input: [text],
+      }),
+    }
+  )
+
+  if (!response.ok) {
+    throw new Error(`Embedding API error: ${response.status}`)
+  }
+
+  const data = await response.json()
+  return data.data[0].embedding
+}
+
+export async function searchBibleSemantic(
+  query: string,
+  limit: number = 10
+): Promise<BibleVerse[]> {
+  try {
+    const queryEmbedding = await getEmbedding(query)
+
+    const client = await pool.connect()
+    try {
+      const result = await client.query(
+        `
+        SELECT ref, book, chapter, verse, text_raw,
+               1 - (embedding <=> $1) AS similarity
+        FROM bible_passages
+        WHERE embedding IS NOT NULL
+        ORDER BY embedding <=> $1
+        LIMIT $2
+        `,
+        [JSON.stringify(queryEmbedding), limit]
+      )
+
+      return result.rows
+    } finally {
+      client.release()
+    }
+  } catch (error) {
+    console.error('Error in semantic search:', error)
+    throw error
+  }
+}
+
+export async function searchBibleHybrid(
+  query: string,
+  limit: number = 10
+): Promise<BibleVerse[]> {
+  try {
+    const queryEmbedding = await getEmbedding(query)
+
+    const client = await pool.connect()
+    try {
+      const result = await client.query(
+        `
+        WITH vector_search AS (
+          SELECT id, 1 - (embedding <=> $1) AS vector_sim
+          FROM bible_passages
+          WHERE embedding IS NOT NULL
+          ORDER BY embedding <=> $1
+          LIMIT 100
+        ),
+        text_search AS (
+          SELECT id, ts_rank(tsv, plainto_tsquery('romanian', $3)) AS text_rank
+          FROM bible_passages
+          WHERE tsv @@ plainto_tsquery('romanian', $3)
+        )
+        SELECT bp.ref, bp.book, bp.chapter, bp.verse, bp.text_raw,
+               COALESCE(vs.vector_sim, 0) * 0.7 + COALESCE(ts.text_rank, 0) * 0.3 AS combined_score
+        FROM bible_passages bp
+        LEFT JOIN vector_search vs ON vs.id = bp.id
+        LEFT JOIN text_search ts ON ts.id = bp.id
+        WHERE vs.id IS NOT NULL OR ts.id IS NOT NULL
+        ORDER BY combined_score DESC
+        LIMIT $2
+        `,
+        [JSON.stringify(queryEmbedding), limit, query]
+      )
+
+      return result.rows
+    } finally {
+      client.release()
+    }
+  } catch (error) {
+    console.error('Error in hybrid search:', error)
+    throw error
+  }
+}
+
+export async function getContextVerses(
+  book: string,
+  chapter: number,
+  verse: number,
+  contextSize: number = 2
+): Promise<BibleVerse[]> {
+  const client = await pool.connect()
+  try {
+    const result = await client.query(
+      `
+      SELECT ref, book, chapter, verse, text_raw
+      FROM bible_passages
+      WHERE book = $1 AND chapter = $2
+      AND verse BETWEEN $3 AND $4
+      ORDER BY verse
+      `,
+      [book, chapter, verse - contextSize, verse + contextSize]
+    )
+
+    return result.rows
+  } finally {
+    client.release()
+  }
+}