optimclaw/src/db/libsql/workspace.rs

//! Workspace-related WorkspaceStore implementation for LibSqlBackend.

use std::collections::HashMap;

use async_trait::async_trait;
use libsql::params;
use uuid::Uuid;

use super::{
    LibSqlBackend, fmt_ts, get_i64, get_opt_text, get_opt_ts, get_text, get_ts,
    row_to_memory_document,
};
use crate::db::WorkspaceStore;
use crate::error::WorkspaceError;
use crate::workspace::{
    MemoryChunk, MemoryDocument, RankedResult, SearchConfig, SearchResult, WorkspaceEntry,
    fuse_results,
};

use chrono::Utc;

#[async_trait]
impl WorkspaceStore for LibSqlBackend {
    async fn get_document_by_path(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
        path: &str,
    ) -> Result<MemoryDocument, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let agent_id_str = agent_id.map(|id| id.to_string());
        let mut rows = conn
            .query(
                r#"
                SELECT id, user_id, agent_id, path, content,
                       created_at, updated_at, metadata
                FROM memory_documents
                WHERE user_id = ?1 AND agent_id IS ?2 AND path = ?3
                "#,
                params![user_id, agent_id_str.as_deref(), path],
            )
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?;

        match rows
            .next()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })? {
            Some(row) => Ok(row_to_memory_document(&row)),
            None => Err(WorkspaceError::DocumentNotFound {
                doc_type: path.to_string(),
                user_id: user_id.to_string(),
            }),
        }
    }

    async fn get_document_by_id(&self, id: Uuid) -> Result<MemoryDocument, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let mut rows = conn
            .query(
                r#"
                SELECT id, user_id, agent_id, path, content,
                       created_at, updated_at, metadata
                FROM memory_documents WHERE id = ?1
                "#,
                params![id.to_string()],
            )
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?;

        match rows
            .next()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })? {
            Some(row) => Ok(row_to_memory_document(&row)),
            None => Err(WorkspaceError::DocumentNotFound {
                doc_type: "unknown".to_string(),
                user_id: "unknown".to_string(),
            }),
        }
    }

    async fn get_or_create_document_by_path(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
        path: &str,
    ) -> Result<MemoryDocument, WorkspaceError> {
        // Try get
        match self.get_document_by_path(user_id, agent_id, path).await {
            Ok(doc) => return Ok(doc),
            Err(WorkspaceError::DocumentNotFound { .. }) => {}
            Err(e) => return Err(e),
        }

        // Create
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let id = Uuid::new_v4();
        let agent_id_str = agent_id.map(|id| id.to_string());
        conn.execute(
            r#"
                INSERT INTO memory_documents (id, user_id, agent_id, path, content, metadata)
                VALUES (?1, ?2, ?3, ?4, '', '{}')
                ON CONFLICT (user_id, agent_id, path) DO NOTHING
                "#,
            params![id.to_string(), user_id, agent_id_str.as_deref(), path],
        )
        .await
        .map_err(|e| WorkspaceError::SearchFailed {
            reason: format!("Insert failed: {}", e),
        })?;

        self.get_document_by_path(user_id, agent_id, path).await
    }

    async fn update_document(&self, id: Uuid, content: &str) -> Result<(), WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let now = fmt_ts(&Utc::now());
        conn.execute(
            "UPDATE memory_documents SET content = ?2, updated_at = ?3 WHERE id = ?1",
            params![id.to_string(), content, now],
        )
        .await
        .map_err(|e| WorkspaceError::SearchFailed {
            reason: format!("Update failed: {}", e),
        })?;
        Ok(())
    }

    async fn delete_document_by_path(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
        path: &str,
    ) -> Result<(), WorkspaceError> {
        let doc = self.get_document_by_path(user_id, agent_id, path).await?;
        self.delete_chunks(doc.id).await?;

        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let agent_id_str = agent_id.map(|id| id.to_string());
        conn.execute(
            "DELETE FROM memory_documents WHERE user_id = ?1 AND agent_id IS ?2 AND path = ?3",
            params![user_id, agent_id_str.as_deref(), path],
        )
        .await
        .map_err(|e| WorkspaceError::SearchFailed {
            reason: format!("Delete failed: {}", e),
        })?;
        Ok(())
    }

    async fn list_directory(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
        directory: &str,
    ) -> Result<Vec<WorkspaceEntry>, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let dir = if !directory.is_empty() && !directory.ends_with('/') {
            format!("{}/", directory)
        } else {
            directory.to_string()
        };

        let agent_id_str = agent_id.map(|id| id.to_string());
        let pattern = if dir.is_empty() {
            "%".to_string()
        } else {
            format!("{}%", dir)
        };

        let mut rows = conn
            .query(
                r#"
                SELECT path, updated_at, substr(content, 1, 200) as content_preview
                FROM memory_documents
                WHERE user_id = ?1 AND agent_id IS ?2
                  AND (?3 = '%' OR path LIKE ?3)
                ORDER BY path
                "#,
                params![user_id, agent_id_str.as_deref(), pattern],
            )
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("List directory failed: {}", e),
            })?;

        let mut entries_map: HashMap<String, WorkspaceEntry> = HashMap::new();

        while let Some(row) = rows
            .next()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?
        {
            let full_path = get_text(&row, 0);
            let updated_at = get_opt_ts(&row, 1);
            let content_preview = get_opt_text(&row, 2);

            let relative = if dir.is_empty() {
                &full_path
            } else if let Some(stripped) = full_path.strip_prefix(&dir) {
                stripped
            } else {
                continue;
            };

            let child_name = if let Some(slash_pos) = relative.find('/') {
                &relative[..slash_pos]
            } else {
                relative
            };

            if child_name.is_empty() {
                continue;
            }

            let is_dir = relative.contains('/');
            let entry_path = if dir.is_empty() {
                child_name.to_string()
            } else {
                format!("{}{}", dir, child_name)
            };

            entries_map
                .entry(child_name.to_string())
                .and_modify(|e| {
                    if is_dir {
                        e.is_directory = true;
                        e.content_preview = None;
                    }
                    if let (Some(existing), Some(new)) = (&e.updated_at, &updated_at)
                        && new > existing
                    {
                        e.updated_at = Some(*new);
                    }
                })
                .or_insert(WorkspaceEntry {
                    path: entry_path,
                    is_directory: is_dir,
                    updated_at,
                    content_preview: if is_dir { None } else { content_preview },
                });
        }

        let mut entries: Vec<WorkspaceEntry> = entries_map.into_values().collect();
        entries.sort_by(|a, b| a.path.cmp(&b.path));
        Ok(entries)
    }

    async fn list_all_paths(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
    ) -> Result<Vec<String>, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let agent_id_str = agent_id.map(|id| id.to_string());
        let mut rows = conn
            .query(
                "SELECT path FROM memory_documents WHERE user_id = ?1 AND agent_id IS ?2 ORDER BY path",
                params![user_id, agent_id_str.as_deref()],
            )
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("List paths failed: {}", e),
            })?;

        let mut paths = Vec::new();
        while let Some(row) = rows
            .next()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?
        {
            paths.push(get_text(&row, 0));
        }
        Ok(paths)
    }

    async fn list_documents(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
    ) -> Result<Vec<MemoryDocument>, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let agent_id_str = agent_id.map(|id| id.to_string());
        let mut rows = conn
            .query(
                r#"
                SELECT id, user_id, agent_id, path, content,
                       created_at, updated_at, metadata
                FROM memory_documents
                WHERE user_id = ?1 AND agent_id IS ?2
                ORDER BY updated_at DESC
                "#,
                params![user_id, agent_id_str.as_deref()],
            )
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?;

        let mut docs = Vec::new();
        while let Some(row) = rows
            .next()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?
        {
            docs.push(row_to_memory_document(&row));
        }
        Ok(docs)
    }

    async fn delete_chunks(&self, document_id: Uuid) -> Result<(), WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::ChunkingFailed {
                reason: e.to_string(),
            })?;
        conn.execute(
            "DELETE FROM memory_chunks WHERE document_id = ?1",
            params![document_id.to_string()],
        )
        .await
        .map_err(|e| WorkspaceError::ChunkingFailed {
            reason: format!("Delete failed: {}", e),
        })?;
        Ok(())
    }

    async fn insert_chunk(
        &self,
        document_id: Uuid,
        chunk_index: i32,
        content: &str,
        embedding: Option<&[f32]>,
    ) -> Result<Uuid, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::ChunkingFailed {
                reason: e.to_string(),
            })?;
        let id = Uuid::new_v4();
        let embedding_blob = embedding.map(|e| {
            let bytes: Vec<u8> = e.iter().flat_map(|f| f.to_le_bytes()).collect();
            bytes
        });

        conn.execute(
            r#"
                INSERT INTO memory_chunks (id, document_id, chunk_index, content, embedding)
                VALUES (?1, ?2, ?3, ?4, ?5)
                "#,
            params![
                id.to_string(),
                document_id.to_string(),
                chunk_index as i64,
                content,
                embedding_blob.map(libsql::Value::Blob),
            ],
        )
        .await
        .map_err(|e| WorkspaceError::ChunkingFailed {
            reason: format!("Insert failed: {}", e),
        })?;
        Ok(id)
    }

    async fn update_chunk_embedding(
        &self,
        chunk_id: Uuid,
        embedding: &[f32],
    ) -> Result<(), WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::EmbeddingFailed {
                reason: e.to_string(),
            })?;
        let bytes: Vec<u8> = embedding.iter().flat_map(|f| f.to_le_bytes()).collect();

        conn.execute(
            "UPDATE memory_chunks SET embedding = ?2 WHERE id = ?1",
            params![chunk_id.to_string(), libsql::Value::Blob(bytes)],
        )
        .await
        .map_err(|e| WorkspaceError::EmbeddingFailed {
            reason: format!("Update failed: {}", e),
        })?;
        Ok(())
    }

    async fn get_chunks_without_embeddings(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
        limit: usize,
    ) -> Result<Vec<MemoryChunk>, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let agent_id_str = agent_id.map(|id| id.to_string());
        let mut rows = conn
            .query(
                r#"
                SELECT c.id, c.document_id, c.chunk_index, c.content, c.created_at
                FROM memory_chunks c
                JOIN memory_documents d ON d.id = c.document_id
                WHERE d.user_id = ?1 AND d.agent_id IS ?2
                  AND c.embedding IS NULL
                LIMIT ?3
                "#,
                params![user_id, agent_id_str.as_deref(), limit as i64],
            )
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?;

        let mut chunks = Vec::new();
        while let Some(row) = rows
            .next()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: format!("Query failed: {}", e),
            })?
        {
            chunks.push(MemoryChunk {
                id: get_text(&row, 0).parse().unwrap_or_default(),
                document_id: get_text(&row, 1).parse().unwrap_or_default(),
                chunk_index: get_i64(&row, 2) as i32,
                content: get_text(&row, 3),
                embedding: None,
                created_at: get_ts(&row, 4),
            });
        }
        Ok(chunks)
    }

    async fn hybrid_search(
        &self,
        user_id: &str,
        agent_id: Option<Uuid>,
        query: &str,
        embedding: Option<&[f32]>,
        config: &SearchConfig,
    ) -> Result<Vec<SearchResult>, WorkspaceError> {
        let conn = self
            .connect()
            .await
            .map_err(|e| WorkspaceError::SearchFailed {
                reason: e.to_string(),
            })?;
        let agent_id_str = agent_id.map(|id| id.to_string());
        let pre_limit = config.pre_fusion_limit as i64;

        let fts_results = if config.use_fts {
            let mut rows = conn
                .query(
                    r#"
                    SELECT c.id, c.document_id, d.path, c.content
                    FROM memory_chunks_fts fts
                    JOIN memory_chunks c ON c._rowid = fts.rowid
                    JOIN memory_documents d ON d.id = c.document_id
                    WHERE d.user_id = ?1 AND d.agent_id IS ?2
                      AND memory_chunks_fts MATCH ?3
                    ORDER BY rank
                    LIMIT ?4
                    "#,
                    params![user_id, agent_id_str.as_deref(), query, pre_limit],
                )
                .await
                .map_err(|e| WorkspaceError::SearchFailed {
                    reason: format!("FTS query failed: {}", e),
                })?;

            let mut results = Vec::new();
            while let Some(row) = rows
                .next()
                .await
                .map_err(|e| WorkspaceError::SearchFailed {
                    reason: format!("FTS row fetch failed: {}", e),
                })?
            {
                results.push(RankedResult {
                    chunk_id: get_text(&row, 0).parse().unwrap_or_default(),
                    document_id: get_text(&row, 1).parse().unwrap_or_default(),
                    document_path: get_text(&row, 2),
                    content: get_text(&row, 3),
                    rank: results.len() as u32 + 1,
                });
            }
            results
        } else {
            Vec::new()
        };

        let vector_results = if let (true, Some(emb)) = (config.use_vector, embedding) {
            let vector_json = format!(
                "[{}]",
                emb.iter()
                    .map(|f| f.to_string())
                    .collect::<Vec<_>>()
                    .join(",")
            );

            // vector_top_k requires a libsql_vector_idx index. After the V9
            // migration the index is dropped (to support flexible embedding
            // dimensions), so this query may fail. Fall back to FTS-only.
            match conn
                .query(
                    r#"
                    SELECT c.id, c.document_id, d.path, c.content
                    FROM vector_top_k('idx_memory_chunks_embedding', vector(?1), ?2) AS top_k
                    JOIN memory_chunks c ON c._rowid = top_k.id
                    JOIN memory_documents d ON d.id = c.document_id
                    WHERE d.user_id = ?3 AND d.agent_id IS ?4
                    "#,
                    params![vector_json, pre_limit, user_id, agent_id_str.as_deref()],
                )
                .await
            {
                Ok(mut rows) => {
                    let mut results = Vec::new();
                    while let Some(row) =
                        rows.next()
                            .await
                            .map_err(|e| WorkspaceError::SearchFailed {
                                reason: format!("Vector row fetch failed: {}", e),
                            })?
                    {
                        results.push(RankedResult {
                            chunk_id: get_text(&row, 0).parse().unwrap_or_default(),
                            document_id: get_text(&row, 1).parse().unwrap_or_default(),
                            document_path: get_text(&row, 2),
                            content: get_text(&row, 3),
                            rank: results.len() as u32 + 1,
                        });
                    }
                    results
                }
                Err(e) => {
                    tracing::debug!(
                        "Vector index query failed (expected after V9 migration), \
                         falling back to FTS-only: {e}"
                    );
                    Vec::new()
                }
            }
        } else {
            Vec::new()
        };

        if embedding.is_some() && !config.use_vector {
            tracing::warn!(
                "Embedding provided but vector search is disabled in config; using FTS-only results"
            );
        }

        Ok(fuse_results(fts_results, vector_results, config))
    }
}