918 lines
32 KiB
Rust
918 lines
32 KiB
Rust
use std::sync::Arc;
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use serde_json::json;
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use crate::agent_events::{ToolCall, ToolDefinition, ToolResult};
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use crate::connection::AppState;
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use crate::db::vector_driver;
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use crate::models::connection::DatabaseType;
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use crate::query::QueryExecutionOptions;
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use crate::query_execution_sql::{build_explain_sql, supports_explain_plan, supports_sql_query, ExplainSqlOptions};
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use crate::sql_risk::SqlRisk;
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use crate::types::QueryResult;
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/// Maximum number of tables returned by list_tables tool.
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const LIST_TABLES_LIMIT: usize = 200;
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/// Maximum number of rows returned by execute_query tool.
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const EXECUTE_QUERY_LIMIT: usize = 50;
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/// Maximum number of rows returned by get_sample_data tool.
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const SAMPLE_DATA_LIMIT: usize = 20;
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/// Maximum number of rows returned by browse_collection tool.
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const BROWSE_COLLECTION_LIMIT: usize = 20;
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/// Absolute maximum rows any query tool may request.
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const MAX_ALLOWED_ROWS: usize = 100;
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#[derive(Debug, Clone, Copy, Default, PartialEq, Eq)]
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pub struct AgentSqlPermissions {
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pub allow_writes: bool,
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pub allow_dangerous: bool,
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}
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fn sql_risk_allowed(risk: SqlRisk, permissions: AgentSqlPermissions) -> bool {
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match risk {
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SqlRisk::ReadOnly => true,
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SqlRisk::Write => permissions.allow_writes,
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SqlRisk::Ddl => permissions.allow_dangerous,
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SqlRisk::Transaction => false,
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}
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}
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/// Returns true for vector database types (Qdrant, Milvus, Weaviate, ChromaDb).
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/// If modifying this, also update VECTOR_DB_TYPES in apps/desktop/src/lib/ai.ts.
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pub fn is_vector_db(db_type: DatabaseType) -> bool {
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matches!(db_type, DatabaseType::Qdrant | DatabaseType::Milvus | DatabaseType::Weaviate | DatabaseType::ChromaDb)
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}
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/// Get read-only tool definitions for the given database type.
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/// Returns vector tools for vector DBs, SQL tools otherwise.
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pub fn read_only_tools(db_type: DatabaseType) -> Vec<ToolDefinition> {
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if is_vector_db(db_type) {
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vec![list_collections_tool()]
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} else {
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vec![list_tables_tool(), get_columns_tool()]
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}
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}
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/// Get all available tool definitions for the given database type.
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/// Includes read-only tools plus execute_query, get_sample_data, and
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/// explain_query for database types that support them.
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pub fn all_tools(db_type: DatabaseType, sql_permissions: AgentSqlPermissions) -> Vec<ToolDefinition> {
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if is_vector_db(db_type) {
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return vec![list_collections_tool(), browse_collection_tool()];
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}
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let mut tools = vec![list_tables_tool(), get_columns_tool()];
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if supports_sql_query(db_type) {
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tools.push(execute_query_tool(sql_permissions));
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tools.push(get_sample_data_tool());
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}
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if supports_explain_plan(Some(db_type)) {
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tools.push(explain_query_tool());
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}
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tools
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}
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/// list_tables tool definition.
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fn list_tables_tool() -> ToolDefinition {
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ToolDefinition {
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name: "list_tables",
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description: "List all tables and views in the current database. Returns table names, types, and comments.",
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parameters: json!({
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"type": "object",
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"properties": {
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"schema": {
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"type": "string",
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"description": "Schema name to list tables from (optional, defaults to current database)"
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}
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},
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"required": []
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}),
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read_only: true,
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parallel_ok: true,
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}
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}
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/// get_columns tool definition.
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fn get_columns_tool() -> ToolDefinition {
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ToolDefinition {
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name: "get_columns",
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description:
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"Get column definitions for a table: names, types, primary keys, nullable, defaults, and comments. \
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Use this when the user asks about table structure, column details, or field information — \
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even if some schema context was provided, this tool returns the authoritative and complete column list.",
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parameters: json!({
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"type": "object",
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"properties": {
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"table": {
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"type": "string",
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"description": "Table name to get columns for"
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},
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"schema": {
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"type": "string",
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"description": "Schema name (optional, defaults to current database)"
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}
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},
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"required": ["table"]
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}),
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read_only: true,
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// get_columns runs sequentially: concurrent metadata queries can exhaust
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// single-connection drivers (e.g. DuckDB), causing cascading tool errors.
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parallel_ok: false,
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}
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}
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/// execute_query tool definition.
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fn execute_query_tool(sql_permissions: AgentSqlPermissions) -> ToolDefinition {
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let description = if sql_permissions.allow_dangerous {
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"Execute SQL after the user explicitly confirmed this operation. Read queries, writes, and DDL are allowed for this run."
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} else if sql_permissions.allow_writes {
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"Execute SQL after the user explicitly confirmed this operation. Read queries and non-DDL writes are allowed for this run."
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} else {
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"Execute a read-only SQL query and return results (max 50 rows). Only SELECT, WITH, SHOW, DESCRIBE, EXPLAIN statements are allowed. Write operations (INSERT/UPDATE/DELETE/DDL) are blocked."
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};
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ToolDefinition {
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name: "execute_query",
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description,
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parameters: json!({
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"type": "object",
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"properties": {
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"sql": {
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"type": "string",
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"description": "The SQL query to execute"
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},
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"limit": {
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"type": "number",
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"description": "Max rows to return (default 50, max 100)"
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}
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},
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"required": ["sql"]
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}),
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read_only: true,
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parallel_ok: false,
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}
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}
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/// get_sample_data tool definition.
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fn get_sample_data_tool() -> ToolDefinition {
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ToolDefinition {
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name: "get_sample_data",
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description: "Get sample rows from a table to understand its data. Returns up to 20 rows.",
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parameters: json!({
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"type": "object",
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"properties": {
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"table": {
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"type": "string",
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"description": "Table name"
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},
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"schema": {
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"type": "string",
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"description": "Schema name (optional)"
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},
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"limit": {
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"type": "number",
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"description": "Max rows (default 20)"
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}
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},
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"required": ["table"]
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}),
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read_only: true,
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parallel_ok: true,
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}
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}
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/// explain_query tool definition (Phase 3).
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fn explain_query_tool() -> ToolDefinition {
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ToolDefinition {
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name: "explain_query",
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description: "Get the execution plan for a SQL query using EXPLAIN. \
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Shows how the database will execute the query (scan type, indexes, cost). \
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Only read-only queries (SELECT, WITH, SHOW, DESCRIBE, EXPLAIN) are allowed. \
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Use this to analyze query performance and suggest index optimizations.",
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parameters: json!({
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"type": "object",
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"properties": {
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"sql": {
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"type": "string",
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"description": "The SQL query to explain (must be read-only)"
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}
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},
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"required": ["sql"]
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}),
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read_only: true,
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parallel_ok: true,
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}
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}
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/// list_collections tool definition (vector databases).
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fn list_collections_tool() -> ToolDefinition {
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ToolDefinition {
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name: "list_collections",
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description: "List all collections in the current vector database. Returns collection names and dimensions.",
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parameters: json!({
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"type": "object",
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"properties": {},
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"required": []
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}),
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read_only: true,
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parallel_ok: true,
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}
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}
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/// browse_collection tool definition (vector databases).
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fn browse_collection_tool() -> ToolDefinition {
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ToolDefinition {
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name: "browse_collection",
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description: "Browse documents in a collection. Returns up to 20 items with payload/metadata (vectors excluded for compactness). For ChromaDB, use the collection id (UUID from list_collections) instead of the collection name.",
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parameters: json!({
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"type": "object",
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"properties": {
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"collection": {
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"type": "string",
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"description": "Collection name"
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},
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"limit": {
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"type": "number",
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"description": "Max items to return (default 20, max 100)"
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}
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},
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"required": ["collection"]
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}),
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read_only: true,
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parallel_ok: true,
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}
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}
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/// Execute a tool call and return the result.
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pub async fn execute_tool(
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tool_call: &ToolCall,
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state: &Arc<AppState>,
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connection_id: &str,
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database: &str,
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db_type: &DatabaseType,
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sql_permissions: AgentSqlPermissions,
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) -> ToolResult {
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let result = match tool_call.name.as_str() {
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"list_tables" => execute_list_tables(tool_call, state, connection_id, database, db_type).await,
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"get_columns" => execute_get_columns(tool_call, state, connection_id, database, db_type).await,
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"execute_query" => {
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execute_execute_query(tool_call, state, connection_id, database, db_type, sql_permissions).await
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}
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"get_sample_data" => execute_get_sample_data(tool_call, state, connection_id, database, db_type).await,
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"list_collections" => execute_list_collections(tool_call, state, connection_id, database, db_type).await,
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"browse_collection" => execute_browse_collection(tool_call, state, connection_id, database, db_type).await,
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"explain_query" => {
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let (text_result, explain_data) =
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execute_explain_query(tool_call, state, connection_id, database, db_type).await;
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match text_result {
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Ok(content) => {
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return ToolResult {
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tool_call_id: tool_call.id.clone(),
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tool_name: tool_call.name.clone(),
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content,
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is_error: false,
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explain_data,
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};
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}
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Err(err) => {
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return ToolResult {
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tool_call_id: tool_call.id.clone(),
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tool_name: tool_call.name.clone(),
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content: format!("Error: {err}"),
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is_error: true,
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explain_data: None,
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};
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}
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}
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}
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_ => Err(format!("Unknown tool: {}", tool_call.name)),
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};
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match result {
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Ok(content) => ToolResult {
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tool_call_id: tool_call.id.clone(),
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tool_name: tool_call.name.clone(),
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content,
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is_error: false,
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explain_data: None,
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},
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Err(err) => ToolResult {
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tool_call_id: tool_call.id.clone(),
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tool_name: tool_call.name.clone(),
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content: format!("Error: {err}"),
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is_error: true,
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explain_data: None,
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},
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}
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}
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async fn execute_list_tables(
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tool_call: &ToolCall,
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state: &Arc<AppState>,
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connection_id: &str,
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database: &str,
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_db_type: &DatabaseType,
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) -> Result<String, String> {
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let schema = tool_call.arguments.get("schema").and_then(|v| v.as_str()).unwrap_or("").to_string();
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// Request one extra to detect whether more tables exist beyond the limit.
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let tables = crate::schema::list_tables_core(
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state,
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connection_id,
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database,
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&schema,
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None,
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Some(LIST_TABLES_LIMIT + 1),
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None,
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None,
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)
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.await
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.map_err(|e| format!("Failed to list tables: {e}"))?;
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let total = tables.len();
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let truncated = total > LIST_TABLES_LIMIT;
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let mut lines = Vec::new();
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let display_count = if truncated { LIST_TABLES_LIMIT } else { total };
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for table in tables.iter().take(display_count) {
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let mut line = format!("- {} ({})", table.name, table.table_type);
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if let Some(comment) = &table.comment {
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let trimmed = comment.trim();
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if !trimmed.is_empty() {
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line.push_str(&format!(" -- {}", trimmed));
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}
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}
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lines.push(line);
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}
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if truncated {
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lines.push(format!("... (showing {LIST_TABLES_LIMIT} of {total} tables)"));
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}
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if lines.is_empty() {
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return Ok("No tables found in this database/schema.".to_string());
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}
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Ok(lines.join("\n"))
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}
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async fn execute_get_columns(
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tool_call: &ToolCall,
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state: &Arc<AppState>,
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connection_id: &str,
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database: &str,
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_db_type: &DatabaseType,
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) -> Result<String, String> {
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let table = tool_call
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.arguments
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.get("table")
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.and_then(|v| v.as_str())
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.ok_or("Missing required parameter: table")?
|
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.trim()
|
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.to_string();
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|
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if table.is_empty() {
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return Err("Table name cannot be empty".to_string());
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}
|
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if table.len() > 256 {
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return Err(format!("Table name too long: {} characters (max 256)", table.len()));
|
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}
|
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// Reject names with characters that are unlikely to be valid identifiers
|
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if table.contains(';') || table.contains('\'') || table.contains('"') || table.contains('\\') {
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return Err(format!("Table name contains invalid characters: '{}'", table));
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}
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let schema = tool_call.arguments.get("schema").and_then(|v| v.as_str()).unwrap_or("").to_string();
|
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|
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let columns = crate::schema::get_columns_core(state, connection_id, database, &schema, &table)
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.await
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.map_err(|e| format!("Failed to get columns for {table}: {e}"))?;
|
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|
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if columns.is_empty() {
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return Ok(format!("No columns found for table '{table}'."));
|
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}
|
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|
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let mut lines = Vec::new();
|
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lines.push(format!("Columns of {table}:"));
|
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for col in &columns {
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let mut flags: Vec<String> = Vec::new();
|
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if col.is_primary_key {
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flags.push("PK".to_string());
|
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}
|
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if col.is_nullable {
|
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flags.push("nullable".to_string());
|
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} else {
|
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flags.push("NOT NULL".to_string());
|
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}
|
||
if let Some(default) = &col.column_default {
|
||
if !default.is_empty() {
|
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flags.push(format!("default {default}"));
|
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}
|
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}
|
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if let Some(extra) = &col.extra {
|
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if !extra.is_empty() {
|
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flags.push(extra.clone());
|
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}
|
||
}
|
||
|
||
let flags_str = if flags.is_empty() { String::new() } else { format!(" ({})", flags.join(", ")) };
|
||
|
||
let comment_str = col
|
||
.comment
|
||
.as_ref()
|
||
.filter(|c| !c.trim().is_empty())
|
||
.map(|c| format!(" -- {}", c.trim()))
|
||
.unwrap_or_default();
|
||
|
||
lines.push(format!(" - {}: {}{}{}", col.name, col.data_type, flags_str, comment_str));
|
||
}
|
||
|
||
Ok(lines.join("\n"))
|
||
}
|
||
|
||
/// Execute a read-only SQL query via the execute_query tool.
|
||
async fn execute_execute_query(
|
||
tool_call: &ToolCall,
|
||
state: &Arc<AppState>,
|
||
connection_id: &str,
|
||
database: &str,
|
||
db_type: &DatabaseType,
|
||
sql_permissions: AgentSqlPermissions,
|
||
) -> Result<String, String> {
|
||
let sql = tool_call.arguments.get("sql").and_then(|v| v.as_str()).ok_or("Missing required parameter: sql")?.trim();
|
||
|
||
if sql.is_empty() {
|
||
return Err("SQL query cannot be empty".to_string());
|
||
}
|
||
|
||
let limit = tool_call
|
||
.arguments
|
||
.get("limit")
|
||
.and_then(|v| v.as_u64())
|
||
.map(|l| (l as usize).min(MAX_ALLOWED_ROWS))
|
||
.unwrap_or(EXECUTE_QUERY_LIMIT);
|
||
|
||
// Classify SQL risk using the concrete database dialect.
|
||
let risk = crate::sql_risk::classify_sql_risk_for_database(sql, *db_type)?;
|
||
let connection_config = state.configs.read().await.get(connection_id).cloned();
|
||
if let Some(config) = connection_config {
|
||
if risk != SqlRisk::ReadOnly && crate::production_safety::targets_production_database(&config, database, sql) {
|
||
return Err("Blocked: AI agents cannot execute writes or DDL on a production database. Return the SQL for the user to review and execute manually in DBX.".to_string());
|
||
}
|
||
}
|
||
if !sql_risk_allowed(risk, sql_permissions) {
|
||
if risk == SqlRisk::Transaction {
|
||
return Err("Blocked: transaction control statements are not available to the AI agent.".to_string());
|
||
}
|
||
return Err(format!(
|
||
"Blocked: {} statement detected. Ask the user to confirm the proposed database change before executing it.",
|
||
risk
|
||
));
|
||
}
|
||
|
||
// Execute query using existing infrastructure
|
||
let options = QueryExecutionOptions { max_rows: Some(limit), timeout_secs: Some(30), ..Default::default() };
|
||
let result =
|
||
crate::query::execute_sql_statement_with_options(state, connection_id, database, sql, None, None, options)
|
||
.await?;
|
||
|
||
format_query_result_as_text(&result, limit)
|
||
}
|
||
|
||
/// Format a QueryResult as a Markdown table for LLM consumption.
|
||
fn format_query_result_as_text(result: &QueryResult, limit: usize) -> Result<String, String> {
|
||
if result.rows.is_empty() {
|
||
return Ok("Query returned 0 rows.".to_string());
|
||
}
|
||
|
||
let mut lines = Vec::new();
|
||
|
||
// Header row
|
||
lines.push(format!("| {} |", result.columns.join(" | ")));
|
||
// Separator row
|
||
lines.push(format!("|{}|", result.columns.iter().map(|_| "---").collect::<Vec<_>>().join("|")));
|
||
|
||
// Data rows
|
||
for row in &result.rows {
|
||
let cells: Vec<String> = row
|
||
.iter()
|
||
.map(|v| match v {
|
||
serde_json::Value::Null => "NULL".to_string(),
|
||
serde_json::Value::String(s) => {
|
||
// Truncate long strings to keep result compact
|
||
if s.len() > 200 {
|
||
let truncated: String =
|
||
s.char_indices().take_while(|(i, _)| *i < 200).map(|(_, c)| c).collect();
|
||
format!("{}...", truncated)
|
||
} else {
|
||
s.clone()
|
||
}
|
||
}
|
||
other => other.to_string(),
|
||
})
|
||
.collect();
|
||
lines.push(format!("| {} |", cells.join(" | ")));
|
||
}
|
||
|
||
// Truncation notice
|
||
if result.truncated || result.rows.len() >= limit {
|
||
lines.push(format!("... (showing {} rows, result may be truncated)", result.rows.len()));
|
||
}
|
||
|
||
// Stats line
|
||
lines.push(format!("({} rows, {}ms)", result.rows.len(), result.execution_time_ms));
|
||
|
||
Ok(lines.join("\n"))
|
||
}
|
||
|
||
/// Get sample data from a table via the get_sample_data tool.
|
||
async fn execute_get_sample_data(
|
||
tool_call: &ToolCall,
|
||
state: &Arc<AppState>,
|
||
connection_id: &str,
|
||
database: &str,
|
||
db_type: &DatabaseType,
|
||
) -> Result<String, String> {
|
||
let table =
|
||
tool_call.arguments.get("table").and_then(|v| v.as_str()).ok_or("Missing required parameter: table")?.trim();
|
||
|
||
if table.is_empty() {
|
||
return Err("Table name cannot be empty".to_string());
|
||
}
|
||
if table.contains(';') || table.contains('\'') || table.contains('"') || table.contains('\\') {
|
||
return Err(format!("Table name contains invalid characters: '{}'", table));
|
||
}
|
||
|
||
let schema = tool_call.arguments.get("schema").and_then(|v| v.as_str());
|
||
let limit = tool_call
|
||
.arguments
|
||
.get("limit")
|
||
.and_then(|v| v.as_u64())
|
||
.map(|l| (l as usize).min(MAX_ALLOWED_ROWS))
|
||
.unwrap_or(SAMPLE_DATA_LIMIT);
|
||
|
||
// Build SELECT * FROM table LIMIT N
|
||
let schema_prefix = schema.filter(|s| !s.is_empty()).map(|s| format!("\"{}\".", s)).unwrap_or_default();
|
||
let sql = format!("SELECT * FROM {}\"{}\" LIMIT {}", schema_prefix, table, limit);
|
||
|
||
// Delegate to execute_execute_query with a synthetic tool call
|
||
let synthetic_call = ToolCall {
|
||
id: tool_call.id.clone(),
|
||
name: "execute_query".to_string(),
|
||
arguments: serde_json::json!({ "sql": sql, "limit": limit }),
|
||
};
|
||
execute_execute_query(&synthetic_call, state, connection_id, database, db_type, AgentSqlPermissions::default())
|
||
.await
|
||
}
|
||
|
||
/// Execute an EXPLAIN query via the explain_query tool.
|
||
/// Returns (text_for_llm, optional_explain_data_for_frontend).
|
||
async fn execute_explain_query(
|
||
tool_call: &ToolCall,
|
||
state: &Arc<AppState>,
|
||
connection_id: &str,
|
||
database: &str,
|
||
db_type: &DatabaseType,
|
||
) -> (Result<String, String>, Option<serde_json::Value>) {
|
||
let sql = match tool_call.arguments.get("sql").and_then(|v| v.as_str()) {
|
||
Some(s) => s.trim(),
|
||
None => return (Err("Missing required parameter: sql".to_string()), None),
|
||
};
|
||
|
||
if sql.is_empty() {
|
||
return (Err("SQL query cannot be empty".to_string()), None);
|
||
}
|
||
|
||
// Classify SQL risk – only ReadOnly queries can be explained
|
||
let risk = match crate::sql_risk::classify_sql_risk_for_database(sql, *db_type) {
|
||
Ok(r) => r,
|
||
Err(e) => return (Err(e), None),
|
||
};
|
||
match risk {
|
||
SqlRisk::ReadOnly => { /* proceed */ }
|
||
_ => {
|
||
return (
|
||
Err(format!(
|
||
"Blocked: {} statement detected. Only read-only queries (SELECT, SHOW, DESCRIBE, EXPLAIN) can be analyzed.",
|
||
risk
|
||
)),
|
||
None,
|
||
);
|
||
}
|
||
}
|
||
|
||
if *db_type == DatabaseType::Oracle {
|
||
return match crate::agent_explain::get_agent_explain_info_core(
|
||
state,
|
||
connection_id,
|
||
Some(database),
|
||
None,
|
||
sql,
|
||
Some("explain"),
|
||
)
|
||
.await
|
||
{
|
||
Ok(plan) => (Ok(plan.clone()), Some(serde_json::Value::String(plan))),
|
||
Err(error) => (Err(error), None),
|
||
};
|
||
}
|
||
|
||
// Build the database-specific EXPLAIN SQL
|
||
let explain_result =
|
||
build_explain_sql(ExplainSqlOptions { database_type: Some(*db_type), format: None, sql: sql.to_string() });
|
||
|
||
let explain_sql = match (explain_result.ok, explain_result.sql) {
|
||
(true, Some(sql)) => sql,
|
||
(true, None) => return (Err("EXPLAIN SQL is empty".to_string()), None),
|
||
(false, _) => {
|
||
let reason = explain_result.reason.unwrap_or_else(|| "unknown".to_string());
|
||
return (Err(format!("Cannot explain this query: {}. The database type may not support EXPLAIN, or the query may be unsafe.", reason)), None);
|
||
}
|
||
};
|
||
|
||
// Execute the EXPLAIN query
|
||
let options = QueryExecutionOptions { max_rows: Some(100), timeout_secs: Some(30), ..Default::default() };
|
||
let result = match crate::query::execute_sql_statement_with_options(
|
||
state,
|
||
connection_id,
|
||
database,
|
||
&explain_sql,
|
||
None,
|
||
None,
|
||
options,
|
||
)
|
||
.await
|
||
{
|
||
Ok(r) => r,
|
||
Err(e) => return (Err(e), None),
|
||
};
|
||
|
||
// Serialize the raw QueryResult for the frontend ExplainPlanViewer
|
||
let explain_data = serde_json::to_value(&result).ok();
|
||
let text = match format_query_result_as_text(&result, 100) {
|
||
Ok(t) => t,
|
||
Err(e) => return (Err(e), None),
|
||
};
|
||
|
||
(Ok(text), explain_data)
|
||
}
|
||
|
||
/// Execute list_collections tool (vector databases).
|
||
async fn execute_list_collections(
|
||
_tool_call: &ToolCall,
|
||
state: &Arc<AppState>,
|
||
connection_id: &str,
|
||
database: &str,
|
||
_db_type: &DatabaseType,
|
||
) -> Result<String, String> {
|
||
let collections = crate::schema::list_vector_collections_core(state, connection_id, database)
|
||
.await
|
||
.map_err(|e| format!("Failed to list collections: {e}"))?;
|
||
|
||
if collections.is_empty() {
|
||
return Ok("No collections found.".to_string());
|
||
}
|
||
|
||
let mut lines: Vec<String> = collections
|
||
.iter()
|
||
.map(|c| {
|
||
let mut line = format!("- {} (COLLECTION)", c.name);
|
||
if let Some(dim) = c.dimension {
|
||
line.push_str(&format!(" -- {}d", dim));
|
||
}
|
||
line.push_str(&format!(" [id: {}]", c.id));
|
||
line
|
||
})
|
||
.collect();
|
||
|
||
if lines.len() > LIST_TABLES_LIMIT {
|
||
lines.truncate(LIST_TABLES_LIMIT);
|
||
lines.push(format!("... (showing {LIST_TABLES_LIMIT} of {} collections)", collections.len()));
|
||
}
|
||
|
||
Ok(lines.join("\n"))
|
||
}
|
||
|
||
/// Execute browse_collection tool (vector databases).
|
||
/// Generates a database-specific REST query and executes it.
|
||
async fn execute_browse_collection(
|
||
tool_call: &ToolCall,
|
||
state: &Arc<AppState>,
|
||
connection_id: &str,
|
||
database: &str,
|
||
db_type: &DatabaseType,
|
||
) -> Result<String, String> {
|
||
let collection = tool_call
|
||
.arguments
|
||
.get("collection")
|
||
.and_then(|v| v.as_str())
|
||
.ok_or("Missing required parameter: collection")?
|
||
.trim();
|
||
|
||
if collection.is_empty() {
|
||
return Err("Collection name cannot be empty".to_string());
|
||
}
|
||
|
||
let limit = tool_call
|
||
.arguments
|
||
.get("limit")
|
||
.and_then(|v| v.as_u64())
|
||
.map(|l| (l as usize).min(MAX_ALLOWED_ROWS))
|
||
.unwrap_or(BROWSE_COLLECTION_LIMIT);
|
||
|
||
// ChromaDB requires UUID in URL path, not collection name.
|
||
// If the collection param is already a UUID (from list_collections output), use it directly.
|
||
let collection_id = if *db_type == DatabaseType::ChromaDb && !is_uuid(collection) {
|
||
resolve_chroma_collection_uuid(state, connection_id, database, collection).await?
|
||
} else {
|
||
collection.to_string()
|
||
};
|
||
|
||
let query = build_browse_query(db_type, &collection_id, database, limit)?;
|
||
|
||
let options = QueryExecutionOptions { max_rows: Some(limit), timeout_secs: Some(30), ..Default::default() };
|
||
let result =
|
||
crate::query::execute_sql_statement_with_options(state, connection_id, database, &query, None, None, options)
|
||
.await?;
|
||
|
||
format_query_result_as_text(&result, limit)
|
||
}
|
||
|
||
/// Build a browse query for the given vector database type.
|
||
/// Intentionally omits offset/pagination — Agent browse only fetches the first N items.
|
||
fn build_browse_query(
|
||
db_type: &DatabaseType,
|
||
collection: &str,
|
||
database: &str,
|
||
limit: usize,
|
||
) -> Result<String, String> {
|
||
let collection = collection.trim();
|
||
if collection.is_empty() {
|
||
return Err("Collection name cannot be empty".to_string());
|
||
}
|
||
let limit = limit.max(1) as u64;
|
||
|
||
match db_type {
|
||
DatabaseType::Qdrant => Ok(format!(
|
||
"POST /collections/{}/points/scroll\n{}",
|
||
vector_driver::path_segment(collection),
|
||
serde_json::json!({ "limit": limit, "with_payload": true, "with_vector": false })
|
||
)),
|
||
// Milvus v2 omitting outputFields defaults to returning only scalar fields (no vectors).
|
||
DatabaseType::Milvus => Ok(format!(
|
||
"POST /v2/vectordb/entities/query\n{}",
|
||
serde_json::json!({
|
||
"dbName": if database.is_empty() { "default" } else { database },
|
||
"collectionName": collection,
|
||
"filter": "", "limit": limit
|
||
})
|
||
)),
|
||
DatabaseType::Weaviate => {
|
||
Ok(format!("GET /v1/objects?class={}&limit={}", vector_driver::query_value(collection), limit))
|
||
}
|
||
// TODO: ChromaDB Cloud 支持自定义租户和数据库，当前只实现了本地部署
|
||
// （固定 default_tenant / default_database），后续支持云服务时需改为可配置。
|
||
DatabaseType::ChromaDb => Ok(format!(
|
||
"POST /api/v2/tenants/default_tenant/databases/default_database/collections/{}/get\n{}",
|
||
collection,
|
||
serde_json::json!({ "limit": limit, "include": ["documents", "metadatas"] })
|
||
)),
|
||
_ => Err(format!("Unsupported database type: {:?}", db_type)),
|
||
}
|
||
}
|
||
|
||
/// Check if a string looks like a UUID (simple check — 36 chars with 4 hyphens).
|
||
fn is_uuid(s: &str) -> bool {
|
||
s.len() == 36
|
||
&& s.chars().filter(|&c| c == '-').count() == 4
|
||
&& s.chars().all(|c| c.is_ascii_hexdigit() || c == '-')
|
||
}
|
||
|
||
/// Resolve a ChromaDB collection name to its UUID by listing all collections.
|
||
async fn resolve_chroma_collection_uuid(
|
||
state: &Arc<AppState>,
|
||
connection_id: &str,
|
||
database: &str,
|
||
name: &str,
|
||
) -> Result<String, String> {
|
||
let collections = crate::schema::list_vector_collections_core(state, connection_id, database).await?;
|
||
collections
|
||
.into_iter()
|
||
.find(|c| c.name == name)
|
||
.map(|c| c.id)
|
||
.ok_or_else(|| format!("Collection '{name}' not found"))
|
||
}
|
||
|
||
#[cfg(test)]
|
||
mod tests {
|
||
use super::*;
|
||
|
||
#[test]
|
||
fn vector_read_only_tools_do_not_include_collection_browsing() {
|
||
let tools = read_only_tools(DatabaseType::Qdrant);
|
||
let names: Vec<&str> = tools.iter().map(|tool| tool.name).collect();
|
||
|
||
assert_eq!(names, vec!["list_collections"]);
|
||
}
|
||
|
||
#[test]
|
||
fn vector_agent_tools_include_collection_browsing() {
|
||
let tools = all_tools(DatabaseType::Qdrant, AgentSqlPermissions::default());
|
||
let names: Vec<&str> = tools.iter().map(|tool| tool.name).collect();
|
||
|
||
assert_eq!(names, vec!["list_collections", "browse_collection"]);
|
||
}
|
||
|
||
#[test]
|
||
fn confirmed_sql_permissions_update_execute_query_contract() {
|
||
let tools = all_tools(DatabaseType::Mysql, AgentSqlPermissions { allow_writes: true, allow_dangerous: true });
|
||
let execute_query = tools.iter().find(|tool| tool.name == "execute_query").unwrap();
|
||
|
||
assert!(execute_query.description.contains("explicitly confirmed"));
|
||
assert!(execute_query.description.contains("DDL"));
|
||
}
|
||
|
||
#[test]
|
||
fn sql_permissions_keep_writes_blocked_until_confirmation() {
|
||
assert!(!sql_risk_allowed(SqlRisk::Write, AgentSqlPermissions::default()));
|
||
assert!(!sql_risk_allowed(SqlRisk::Ddl, AgentSqlPermissions::default()));
|
||
assert!(sql_risk_allowed(SqlRisk::Ddl, AgentSqlPermissions { allow_writes: true, allow_dangerous: true }));
|
||
assert!(!sql_risk_allowed(
|
||
SqlRisk::Transaction,
|
||
AgentSqlPermissions { allow_writes: true, allow_dangerous: true }
|
||
));
|
||
}
|
||
|
||
#[test]
|
||
fn oracle_agent_tools_include_explain_query() {
|
||
let tools = all_tools(DatabaseType::Oracle, AgentSqlPermissions::default());
|
||
let names: Vec<&str> = tools.iter().map(|tool| tool.name).collect();
|
||
|
||
assert!(names.contains(&"explain_query"));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_qdrant() {
|
||
let q = build_browse_query(&DatabaseType::Qdrant, "articles", "", 10).unwrap();
|
||
assert!(q.starts_with("POST /collections/articles/points/scroll"));
|
||
assert!(q.contains("\"limit\":10"));
|
||
assert!(q.contains("\"with_payload\":true"));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_qdrant_encodes_url_chars() {
|
||
let q = build_browse_query(&DatabaseType::Qdrant, "my collection", "", 10).unwrap();
|
||
assert!(q.starts_with("POST /collections/my%20collection/points/scroll"));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_milvus() {
|
||
let q = build_browse_query(&DatabaseType::Milvus, "articles", "custom_db", 20).unwrap();
|
||
assert!(q.starts_with("POST /v2/vectordb/entities/query"));
|
||
assert!(q.contains("\"dbName\":\"custom_db\""));
|
||
assert!(q.contains("\"collectionName\":\"articles\""));
|
||
assert!(q.contains("\"limit\":20"));
|
||
assert!(!q.contains("outputFields"));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_milvus_default_db() {
|
||
let q = build_browse_query(&DatabaseType::Milvus, "articles", "", 10).unwrap();
|
||
assert!(q.contains("\"dbName\":\"default\""));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_weaviate() {
|
||
let q = build_browse_query(&DatabaseType::Weaviate, "Articles", "", 5).unwrap();
|
||
assert_eq!(q, "GET /v1/objects?class=Articles&limit=5");
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_weaviate_encodes_query_param() {
|
||
let q = build_browse_query(&DatabaseType::Weaviate, "A&B", "", 5).unwrap();
|
||
assert!(q.contains("class=A%26B"));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_chromadb() {
|
||
let q = build_browse_query(&DatabaseType::ChromaDb, "uuid-123", "", 15).unwrap();
|
||
assert!(
|
||
q.starts_with("POST /api/v2/tenants/default_tenant/databases/default_database/collections/uuid-123/get")
|
||
);
|
||
assert!(q.contains("\"limit\":15"));
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_rejects_empty_collection() {
|
||
let result = build_browse_query(&DatabaseType::Qdrant, " ", "", 10);
|
||
assert!(result.is_err());
|
||
}
|
||
|
||
#[test]
|
||
fn build_browse_query_rejects_unsupported_type() {
|
||
let result = build_browse_query(&DatabaseType::Postgres, "articles", "", 10);
|
||
assert!(result.is_err());
|
||
}
|
||
}
|