diff --git a/integrations/agents/.env.example b/agents/sql2memgraph/.env.example similarity index 69% rename from integrations/agents/.env.example rename to agents/sql2memgraph/.env.example index 25b7b02..67422d6 100644 --- a/integrations/agents/.env.example +++ b/agents/sql2memgraph/.env.example @@ -1,6 +1,12 @@ # OpenAI API Configuration OPENAI_API_KEY=your_actual_openai_api_key +# Migration Defaults (can be overridden via CLI flags) +SQL2MG_MODE=automatic +SQL2MG_STRATEGY=deterministic +SQL2MG_META_POLICY=auto +SQL2MG_LOG_LEVEL=INFO + # MySQL Database Configuration MYSQL_HOST=host.docker.internal MYSQL_USER=root diff --git a/agents/sql2memgraph/PROMPT.md b/agents/sql2memgraph/PROMPT.md new file mode 100644 index 0000000..373c4ea --- /dev/null +++ b/agents/sql2memgraph/PROMPT.md @@ -0,0 +1,90 @@ +# SQL → Memgraph Migration Agent Prompt + +## TL;DR + +You are working inside the `agents/sql2memgraph` package, a UV-managed Python project that turns relational schemas (MySQL/PostgreSQL) into Memgraph graph schemas and data. The primary entry point is `main.py`, which wires configuration, environment validation, database analyzers, and the HyGM graph-modeling subsystem. Changes usually touch: + +- `core/` — Orchestrates the migration workflow (`migration_agent.py`) and HyGM graph modeling (`hygm/`). +- `database/` — Connectors and analyzers for the source RDBMSs. +- `query_generation/` — Cypher generation helpers. +- `utils/` — Environment setup, connection probes, and CLI helpers. + +Always maintain the CLI experience (`main.py`) and respect the line-length < 79 char lint rule. + +## Tech Stack & Tooling + +- Python 3.10+, managed with [uv](https://github.com/astral-sh/uv). +- Memgraph as the target graph database (Bolt connection). +- Optional LLM features powered by OpenAI (LangChain / LangGraph patterns inside `core/hygm`). +- Testing: `pytest` under `tests/` (integration heavy, uses mocks for DB analyzers). + +## Core Concepts + +- **HyGM (Hypothetical Graph Modeling)** lives in `core/hygm/hygm.py` and exposes modeling modes via `ModelingMode`: + - `AUTOMATIC` – one-shot graph generation. + - `INCREMENTAL` – table-by-table confirmation flow with an optional refinement + loop after processing all tables. +- **GraphModelingStrategy**: `DETERMINISTIC` (rule-based) and `LLM_POWERED` (needs an LLM+API key). +- **SQLToMemgraphAgent** (`core/migration_agent.py`) coordinates schema analysis, HyGM modeling, query generation, execution, and validation. +- **Database analyzers** in `database/` introspect MySQL/PostgreSQL schemas and emit a normalized metadata structure consumed by HyGM. +- **Query generation** in `query_generation/` converts the graph model + metadata into Cypher migrations, indexes, and constraints. +- **Database data interfaces** in `database/models.py` define the canonical `TableInfo`, `ColumnInfo`, `RelationshipInfo`, and `DatabaseStructure` data classes. These objects flow from analyzers into HyGM via the `to_hygm_format()` helpers, ensuring consistent schema metadata for every modeling mode. +- **Graph schema structures** in `core/hygm/models/graph_models.py` (e.g., `GraphModel`, `GraphNode`, `GraphRelationship`) capture the in-memory graph representation HyGM produces and later serializes to schema format. +- **LLM structured output models** in `core/hygm/models/llm_models.py` (`LLMGraphModel`, `LLMGraphNode`, `LLMGraphRelationship`) describe the contract for AI-generated schemas and include `to_graph_model()` utilities to convert LLM responses into the standard `GraphModel` objects. +- The `GraphModel` serialization format matches the canonical spec in `core/schema/spec.json`, so any changes to the schema data classes should be mirrored against that document. +- Source tracking helpers in `core/hygm/models/sources.py` annotate nodes, relationships, properties, indexes, and constraints with origin metadata. Preserve these when modifying `GraphModel` so downstream migrations retain the link back to the originating tables or user-applied changes. + +## Entry Points & CLI Flow + +- Run with `uv run main.py` (banner, env checks, connection probes, then the migration workflow). +- CLI prompts include: + - Graph modeling mode (automatic / incremental with interactive refinement). + - Modeling strategy (deterministic / AI-powered). + - Confirmation dialogs during automatic or incremental flows. + - Post-session prompts that let users launch the interactive refinement loop + after reviewing every table in an incremental run. +- Environment validation happens before migration; failures raise `MigrationEnvironmentError` or `DatabaseConnectionError` from `utils/`. + +## Configuration & Environment + +- `.env` (or env vars) must provide: + - `SOURCE_DB_*` (host, port, name, user, password, type [`mysql|postgresql`]). + - `MEMGRAPH_*` connection details. + - `OPENAI_API_KEY` for LLM features; omit or leave empty to disable LLM strategy. +- Memgraph must run with `--schema-info-enabled=true` for schema validation. + +## Testing & Validation + +- Install deps: `uv sync` (or `uv pip install -e .`). +- Run targeted tests: `uv run python -m pytest tests/test_integration.py -v`. +- Keep graph-modeling logic covered via integration tests; they rely on mocked analyzers. +- Observe linting: adhere to 79-character lines and existing logging conventions (`logging` module). + +## Development Tips + +- Update `PROMPT.md` when project layout or workflows change. +- Prefer existing abstractions: use `SQLToMemgraphAgent` methods, HyGM strategies/helpers, and database adapters. +- For new modeling flows, ensure `ModelingMode` and CLI choices stay in sync. +- Preserve user-facing prompts/emojis—they guide the interactive experience. +- When adding LLM-dependent features, guard them when API keys or clients are missing. +- Document new commands or config expectations in this prompt and `README.md` if user-facing. + +## Useful Commands + +```bash +# Sync dependencies +uv sync + +# Run the CLI +uv run main.py + +# Run tests +uv run python -m pytest tests -v +``` + +## When Generating Code + +- Mention which files you change and why, referencing modules above. +- Explain how to rerun the CLI or relevant tests after modifications. +- Provide small follow-up suggestions if more validation is needed. +- Keep output concise but cover context so the next agent run has everything it needs. diff --git a/integrations/agents/README.md b/agents/sql2memgraph/README.md similarity index 51% rename from integrations/agents/README.md rename to agents/sql2memgraph/README.md index 35f5155..86fdfc9 100644 --- a/integrations/agents/README.md +++ b/agents/sql2memgraph/README.md @@ -10,7 +10,9 @@ This package provides a sophisticated migration agent that: - **Generates optimal graph models** - Uses AI to create node and relationship structures - **Creates indexes and constraints** - Ensures performance and data integrity - **Handles complex relationships** - Converts foreign keys to graph relationships -- **Interactive refinement** - Allows users to review and adjust the graph model +- **Incremental refinement** - Review each table, adjust the model + immediately, then enter the interactive refinement loop once all tables + are processed - **Comprehensive validation** - Verifies migration results and data integrity ## Installation @@ -35,38 +37,61 @@ The agent will guide you through: 1. Environment setup and database connections 2. Graph modeling strategy selection -3. Interactive or automatic migration mode +3. Automatic or incremental migration mode 4. Complete migration workflow with progress tracking +> **Incremental review:** The LLM now drafts the entire graph model in a single +> shot and then walks you through table-level changes detected since the last +> migration. You only need to approve (or tweak) the differences that matter. + +You can also preconfigure the workflow using CLI flags or environment variables: + +```bash +uv run main --mode incremental --strategy llm --meta-graph reset --log-level DEBUG +``` + +| Option | Environment | Description | +| -------------------------------- | -------------------- | ------------------------------------------------------------- | +| `--mode {automatic,incremental}` | `SQL2MG_MODE` | Selects automatic or incremental modeling flow. | +| `--strategy {deterministic,llm}` | `SQL2MG_STRATEGY` | Chooses deterministic or LLM-powered HyGM strategy. | +| `--meta-graph {auto,skip,reset}` | `SQL2MG_META_POLICY` | Controls how stored meta graph data is used (default `auto`). | +| `--log-level LEVEL` | `SQL2MG_LOG_LEVEL` | Sets logging verbosity (`DEBUG`, `INFO`, etc.). | + ## Configuration Set up your environment variables in `.env`: ```bash -# Source Database (MySQL/PostgreSQL) -SOURCE_DB_HOST=localhost -SOURCE_DB_PORT=3306 -SOURCE_DB_NAME=your_database -SOURCE_DB_USER=username -SOURCE_DB_PASSWORD=password -SOURCE_DB_TYPE=mysql # or postgresql +# MySQL Database (primary source) +MYSQL_HOST=localhost +MYSQL_PORT=3306 +MYSQL_DATABASE=sakila +MYSQL_USER=username +MYSQL_PASSWORD=password # Memgraph Database -MEMGRAPH_HOST=localhost -MEMGRAPH_PORT=7687 -MEMGRAPH_USER= +MEMGRAPH_URL=bolt://localhost:7687 +MEMGRAPH_USERNAME= MEMGRAPH_PASSWORD= +MEMGRAPH_DATABASE=memgraph # OpenAI (for LLM-powered features) OPENAI_API_KEY=your_openai_key + +# Optional migration defaults (override CLI prompts) +SQL2MG_MODE=automatic +SQL2MG_STRATEGY=deterministic +SQL2MG_META_POLICY=auto +SQL2MG_LOG_LEVEL=INFO ``` Make sure that Memgraph is started with the `--schema-info-enabled=true`, since agent uses the schema information from Memgraph `SHOW SCHEMA INFO`. # Arhitecture +``` core/hygm/ -├── hygm.py # Main orchestrator class +├── hygm.py # Main orchestrator class ├── models/ # Data models and structures │ ├── graph_models.py # Core graph representation │ ├── llm_models.py # LLM-specific models @@ -76,3 +101,4 @@ core/hygm/ ├── base.py # Abstract interface ├── deterministic.py # Rule-based modeling └── llm.py # AI-powered modeling +``` diff --git a/integrations/agents/__init__.py b/agents/sql2memgraph/__init__.py similarity index 91% rename from integrations/agents/__init__.py rename to agents/sql2memgraph/__init__.py index 97ab013..6dba05e 100644 --- a/integrations/agents/__init__.py +++ b/agents/sql2memgraph/__init__.py @@ -17,13 +17,14 @@ ```python from agents.core import SQLToMemgraphAgent, HyGM +from agents.core.hygm import ModelingMode from agents.utils import setup_and_validate_environment # Setup environment mysql_config, memgraph_config = setup_and_validate_environment() # Create migration agent -agent = SQLToMemgraphAgent(interactive_graph_modeling=False) +agent = SQLToMemgraphAgent(modeling_mode=ModelingMode.AUTOMATIC) # Run migration result = agent.migrate(mysql_config, memgraph_config) diff --git a/integrations/agents/core/__init__.py b/agents/sql2memgraph/core/__init__.py similarity index 100% rename from integrations/agents/core/__init__.py rename to agents/sql2memgraph/core/__init__.py diff --git a/integrations/agents/core/hygm/__init__.py b/agents/sql2memgraph/core/hygm/__init__.py similarity index 100% rename from integrations/agents/core/hygm/__init__.py rename to agents/sql2memgraph/core/hygm/__init__.py diff --git a/integrations/agents/core/hygm/hygm.py b/agents/sql2memgraph/core/hygm/hygm.py similarity index 68% rename from integrations/agents/core/hygm/hygm.py rename to agents/sql2memgraph/core/hygm/hygm.py index f7d5a5b..d1ce7cb 100644 --- a/integrations/agents/core/hygm/hygm.py +++ b/agents/sql2memgraph/core/hygm/hygm.py @@ -1,17 +1,19 @@ +# flake8: noqa """ Main HyGM (Hypothetical Graph Modeling) class. This is the primary interface for the modular HyGM system. """ + +import copy import uuid import logging from enum import Enum -from typing import Dict, Any, Optional, List, TYPE_CHECKING +from typing import Dict, Any, Optional, List, Tuple, TYPE_CHECKING if TYPE_CHECKING: - from .models.graph_models import GraphModel + from .models.graph_models import GraphModel, GraphNode, GraphRelationship from .models.operations import ModelModifications - from .models.user_operations import UserOperationHistory try: from .strategies import ( @@ -20,7 +22,6 @@ LLMStrategy, ) from .validation import GraphSchemaValidator - from .models.user_operations import UserOperationHistory except ImportError: from core.hygm.strategies import ( BaseModelingStrategy, @@ -28,33 +29,26 @@ LLMStrategy, ) from core.hygm.validation import GraphSchemaValidator - from core.hygm.models.user_operations import UserOperationHistory - -logger = logging.getLogger(__name__) - -import copy -import logging -from enum import Enum -from typing import Dict, Any, Optional, List, TYPE_CHECKING - -if TYPE_CHECKING: - from .models.graph_models import GraphModel - from .models.operations import ModelModifications try: - from .strategies import ( - BaseModelingStrategy, - DeterministicStrategy, - LLMStrategy, + from ..utils.meta_graph import ( + node_key as meta_node_key, + summarize_node as meta_summarize_node, + relationship_key as meta_relationship_key, + summarize_relationship as meta_summarize_relationship, ) - from .validation import GraphSchemaValidator except ImportError: - from core.hygm.strategies import ( - BaseModelingStrategy, - DeterministicStrategy, - LLMStrategy, + from core.utils.meta_graph import ( # type: ignore + node_key as meta_node_key, + summarize_node as meta_summarize_node, + relationship_key as meta_relationship_key, + summarize_relationship as meta_summarize_relationship, ) - from core.hygm.validation import GraphSchemaValidator + +try: + from .models.user_operations import UserOperationHistory +except ImportError: + from core.hygm.models.user_operations import UserOperationHistory logger = logging.getLogger(__name__) @@ -63,7 +57,7 @@ class ModelingMode(Enum): """Modeling modes for HyGM.""" AUTOMATIC = "automatic" - INTERACTIVE = "interactive" + INCREMENTAL = "incremental" class GraphModelingStrategy(Enum): @@ -78,7 +72,8 @@ class HyGM: Main Hypothetical Graph Modeling class. Uses different strategies to create intelligent graph models from - relational schemas. Supports both automatic and interactive modes. + relational schemas. Supports automatic generation or incremental + refinement with user feedback. """ def __init__( @@ -86,13 +81,14 @@ def __init__( llm=None, mode: ModelingMode = ModelingMode.AUTOMATIC, strategy: GraphModelingStrategy = GraphModelingStrategy.DETERMINISTIC, + existing_meta_graph: Optional[Dict[str, Any]] = None, ): """ Initialize HyGM with modeling configuration. Args: llm: LLM instance for AI-powered modeling (optional) - mode: AUTOMATIC or INTERACTIVE modeling mode + mode: AUTOMATIC or INCREMENTAL modeling mode strategy: DETERMINISTIC or LLM_POWERED strategy """ self.llm = llm @@ -105,6 +101,7 @@ def __init__( # User operation tracking self.user_operation_history: Optional["UserOperationHistory"] = None self.session_id = str(uuid.uuid4()) + self.existing_meta_graph = existing_meta_graph or {} def create_graph_model( self, @@ -128,9 +125,9 @@ def create_graph_model( logger.info("Creating graph model using %s strategy...", used_strategy.value) - # Check if interactive mode is enabled - if self.mode == ModelingMode.INTERACTIVE: - return self._interactive_modeling( + # Check if incremental mode is enabled + if self.mode == ModelingMode.INCREMENTAL: + return self._incremental_modeling( database_structure, domain_context, used_strategy ) @@ -167,64 +164,654 @@ def _get_strategy_instance( return self._strategy_cache[strategy] - def _interactive_modeling( + def _interactive_refinement_loop( + self, + model: "GraphModel", + strategy: GraphModelingStrategy, + ) -> "GraphModel": + """ + Interactive refinement loop for the incremental modeling flow. + + Allows users to inspect the aggregated graph model, provide feedback, + and iteratively refine nodes, relationships, indexes, and constraints + using the natural-language modification helpers. + """ + logger.info("Entering interactive refinement loop for incremental modeling") + + self.current_graph_model = model + if self.iteration_count == 0: + self.iteration_count = 1 + + while True: + self._display_current_model(model) + + user_choice = self._get_refinement_choice() + + if user_choice == "accept": + logger.info("Combined model accepted by user") + break + if user_choice == "modify": + logger.info("Modifying combined model interactively...") + model = self._modify_model_interactively(model, strategy) + self.current_graph_model = model + continue + if user_choice == "validate": + logger.info("Validating combined model on user request") + model = self._perform_manual_validation(model, strategy) + self.current_graph_model = model + + return model + + def _table_review_decision( + self, + table_name: str, + table_model: "GraphModel", + ) -> Tuple[bool, List[str], str]: + """Determine whether a table needs user review based on metadata.""" + if not self.existing_meta_graph: + return True, ["No stored migration metadata"], "" + + node_summaries = self.existing_meta_graph.get("node_summaries", {}) or {} + rel_summaries = self.existing_meta_graph.get("relationship_summaries", {}) or {} + existing_counts = self.existing_meta_graph.get("table_counts", {}) or {} + + current_counts: Dict[str, Any] = {} + if isinstance(self.database_structure, dict): + current_counts = self.database_structure.get("table_counts", {}) or {} + + change_reasons: List[str] = [] + produced_node_keys = set() + produced_rel_keys = set() + + new_count = current_counts.get(table_name) + old_count = existing_counts.get(table_name) + if new_count is not None and old_count is not None and new_count != old_count: + if new_count > old_count: + change_reasons.append("Row count increased since last migration") + else: + change_reasons.append("Row count decreased since last migration") + + for node_def in getattr(table_model, "nodes", []): + key = meta_node_key(node_def) + produced_node_keys.add(key) + summary = meta_summarize_node(node_def) + stored = node_summaries.get(key) + display_name = summary.get("source") or key.replace("source::", "") + + if not stored: + change_reasons.append(f"New node definition for {display_name}") + continue + + if summary.get("properties") != stored.get("properties", []): + change_reasons.append(f"Properties changed for {display_name}") + if summary.get("id_field") != stored.get("id_field"): + change_reasons.append(f"Identifier field changed for {display_name}") + if summary.get("mapping") != stored.get("mapping", {}): + change_reasons.append(f"Mapping changed for {display_name}") + + stored_node_keys = { + key + for key, summary in node_summaries.items() + if summary.get("source") == table_name + } + missing_nodes = stored_node_keys - produced_node_keys + if missing_nodes: + change_reasons.append("Existing node definition removed from model") + + for rel_def in getattr(table_model, "edges", []): + key = meta_relationship_key(rel_def) + produced_rel_keys.add(key) + summary = meta_summarize_relationship(rel_def) + if table_name not in { + summary.get("start_table"), + summary.get("end_table"), + summary.get("join_table"), + }: + continue + + stored = rel_summaries.get(key) + rel_name = summary.get("edge_type") or key + + if not stored: + change_reasons.append(f"New relationship {rel_name}") + continue + + if summary.get("mapping") != stored.get("mapping", {}): + change_reasons.append(f"Relationship mapping changed for {rel_name}") + if summary.get("start") != stored.get("start", []): + change_reasons.append( + f"Relationship start labels changed for {rel_name}" + ) + if summary.get("end") != stored.get("end", []): + change_reasons.append(f"Relationship end labels changed for {rel_name}") + + stored_rel_keys = { + key + for key, summary in rel_summaries.items() + if table_name + in { + summary.get("start_table"), + summary.get("end_table"), + summary.get("join_table"), + } + } + missing_rels = stored_rel_keys - produced_rel_keys + if missing_rels: + change_reasons.append("Existing relationship removed from model") + + if change_reasons: + return True, change_reasons, "" + + if new_count is not None: + skip_message = f"Metadata unchanged (rows: {new_count})" + else: + skip_message = "Metadata unchanged" + + return False, [], skip_message + + def _incremental_modeling( self, database_structure: Dict[str, Any], domain_context: Optional[str] = None, strategy: GraphModelingStrategy = GraphModelingStrategy.DETERMINISTIC, ) -> "GraphModel": """ - Interactive modeling process with user feedback. + Incremental modeling process with table-by-table confirmation. - This method provides an interactive terminal interface for users - to iteratively refine the graph model. + This method processes each table individually, showing the user + what node will be created and asking for confirmation before + proceeding to the next table. """ - logger.info("Starting interactive modeling session...") + logger.info("Starting incremental modeling session...") - # Create initial model using the specified strategy + # Get the strategy instance strategy_instance = self._get_strategy_instance(strategy) - current_model = strategy_instance.create_model( - database_structure, domain_context + + # Generate a complete draft model once using the selected strategy + logger.info( + "Generating full graph model before incremental review using %s strategy", + strategy.value, ) - self.current_graph_model = current_model - self.iteration_count = 1 + full_model = strategy_instance.create_model(database_structure, domain_context) + self.current_graph_model = full_model - # Interactive refinement loop - while True: - self._display_current_model(current_model) + # Initialize an empty graph model to build incrementally + from .models.graph_models import GraphModel - user_choice = self._get_user_choice() + incremental_model = GraphModel( + nodes=[], edges=[], node_indexes=[], node_constraints=[] + ) - if user_choice == "accept": - logger.info("Model accepted by user") - break - elif user_choice == "modify": - logger.info("Starting interactive model modification...") - current_model = self._modify_model_interactively( - current_model, strategy + # Extract tables from database structure + tables = database_structure.get("tables", {}) + if not tables: + print("❌ No tables found in database structure") + return incremental_model + + self._print_banner("INCREMENTAL MODELING SESSION") + print("\n🧠 Generated a draft graph model for the entire database.") + print( + "We will now review tables with detected changes so you can " + "approve or adjust them one by one.\n" + ) + + table_models = self._build_table_model_map(full_model, tables) + + processed_tables = [] + skipped_tables = [] + auto_accepted_tables: List[Tuple[str, str]] = [] + + # Process each table individually + for table_name, table_info in tables.items(): + print("=" * 60) + print(f"PROCESSING TABLE: {table_name}") + print("=" * 60) + try: + table_model = table_models.get(table_name) + if table_model is None: + table_model = GraphModel( + nodes=[], + edges=[], + node_indexes=[], + node_constraints=[], + ) + + ( + needs_review, + change_reasons, + skip_message, + ) = self._table_review_decision(table_name, table_model) + + if not needs_review: + self._merge_table_model_into_incremental( + incremental_model, table_model + ) + processed_tables.append(table_name) + message = skip_message or "No changes detected" + print(f"🤖 Auto-accepted {table_name}: {message}") + auto_accepted_tables.append((table_name, message)) + continue + + if change_reasons: + print("⚠️ Changes detected:") + for reason in change_reasons: + print(f" - {reason}") + + self._display_table_details_and_proposals( + table_name, + table_info, + table_model, ) - self.iteration_count += 1 - elif user_choice == "regenerate": - logger.info("Regenerating model with same strategy...") - # Regenerate with the same strategy - current_model = strategy_instance.create_model( - database_structure, domain_context + + # Get user decision + user_choice = self._get_incremental_choice(table_name) + + if user_choice == "accept": + # Add this table's nodes to the incremental model + self._merge_table_model_into_incremental( + incremental_model, table_model + ) + processed_tables.append(table_name) + print(f"✅ Added {table_name} to the graph model") + # Refinement is now offered after the full session summary. + elif user_choice == "skip": + skipped_tables.append(table_name) + print(f"⏭️ Skipped {table_name}") + elif user_choice == "modify": + # Allow user to modify the proposed node + modified_model = self._modify_table_node_interactively( + table_model, table_name + ) + self._merge_table_model_into_incremental( + incremental_model, modified_model + ) + processed_tables.append(table_name) + print(f"✅ Added modified {table_name} to the graph model") + # Refinement is now offered after the full session summary. + elif user_choice == "finish": + print("🏁 Finishing incremental modeling session...") + break + + except Exception as e: + logger.error("Error processing table %s: %s", table_name, e) + print(f"❌ Error processing {table_name}: {e}") + continue + + # Final summary + self._merge_source_less_elements(incremental_model, full_model) + self._print_banner("INCREMENTAL MODELING SUMMARY") + print(f"✅ Processed tables: {len(processed_tables)}") + if processed_tables: + print(f" {', '.join(processed_tables)}") + + if auto_accepted_tables: + print(f"🤖 Auto-accepted tables: {len(auto_accepted_tables)}") + auto_details = [ + f"{name}{f' ({msg})' if msg else ''}" + for name, msg in auto_accepted_tables + ] + print(f" {', '.join(auto_details)}") + + if skipped_tables: + print(f"⏭️ Skipped tables: {len(skipped_tables)}") + print(f" {', '.join(skipped_tables)}") + + print("\n📊 Final model statistics:") + print(f" Nodes: {len(incremental_model.nodes)}") + print(f" Relationships: {len(incremental_model.edges)}") + print(f" Indexes: {len(incremental_model.node_indexes)}") + print(f" Constraints: {len(incremental_model.node_constraints)}") + + review_choice = self._get_user_input_choice( + "\nWould you like to review and refine the combined model?\n" + "1. Finish with the incremental result\n" + "2. Enter the interactive refinement loop\n" + "\nSelect option (1-2) or press Enter to finish: ", + {"1": "finish", "2": "review", "": "finish"}, + "finish", + ) + + if review_choice == "review": + logger.info( + "Switching from incremental flow to interactive refinement", + ) + incremental_model = self._interactive_refinement_loop( + incremental_model, + strategy, + ) + + self.current_graph_model = incremental_model + return incremental_model + + def _display_table_details_and_proposals( + self, + table_name: str, + table_info: Dict[str, Any], + table_model: "GraphModel", + ) -> None: + """Display table information and proposed graph elements.""" + print(f"\n📋 TABLE: {table_name}") + + # Show table columns + columns = table_info.get("schema") or table_info.get("columns", []) + if columns: + if isinstance(columns, dict): + items = columns.items() + else: + items = [ + ( + col.get("field") or col.get("name"), + { + "type": col.get("type") or col.get("data_type"), + "null": col.get("null"), + }, + ) + for col in columns + ] + + print(f" Columns ({len(columns)}):") + for col_name, col_info in items: + if not col_name: + continue + col_type = col_info.get("type", "unknown") + nullable_flag = col_info.get("null") + is_nullable = nullable_flag not in {"NO", False, "false", 0} + nullable = " (nullable)" if is_nullable else "" + print(f" - {col_name}: {col_type}{nullable}") + + # Show primary keys + primary_keys = table_info.get("primary_keys", []) + if primary_keys: + print(f" Primary Keys: {', '.join(primary_keys)}") + + # Show proposed node(s) + print("\n🎯 PROPOSED NODE(S):") + proposed_nodes = table_model.nodes + if proposed_nodes: + for i, node in enumerate(proposed_nodes, 1): + labels = " | ".join(node.labels) + properties = [p.key for p in node.properties] + print(f" {i}. Node Labels: {labels}") + print(f" Properties: {properties}") + else: + print(" ❌ No nodes proposed for this table") + + # Show proposed relationships related to this table + relationships = table_model.edges + print("\n🔗 PROPOSED RELATIONSHIPS:") + if relationships: + for i, relationship in enumerate(relationships, 1): + start_labels = " | ".join(relationship.start_node_labels) + end_labels = " | ".join(relationship.end_node_labels) + props = [p.key for p in relationship.properties] + print( + f" {i}. ({start_labels})-[:{relationship.edge_type}]->({end_labels})" ) - self.iteration_count += 1 - elif user_choice == "switch_strategy": - logger.info("Switching modeling strategy...") - # Switch between strategies - new_strategy = self._switch_strategy(strategy) - if new_strategy != strategy: - strategy_instance = self._get_strategy_instance(new_strategy) - current_model = strategy_instance.create_model( - database_structure, domain_context + if props: + print(f" Properties: {props}") + else: + print(" ❌ No relationships proposed for this table") + + def _get_incremental_choice(self, table_name: str) -> str: + """Get user choice for incremental modeling.""" + print(f"\nWhat would you like to do with table '{table_name}'?") + print("1. Accept - Add this node to the graph model") + print("2. Skip - Skip this table for now") + print("3. Modify - Modify the proposed node before adding") + print("4. Finish - Stop incremental modeling and return current model") + + choices = { + "1": "accept", + "2": "skip", + "3": "modify", + "4": "finish", + } + return self._get_user_input_choice( + f"\nEnter your choice for {table_name} (1-4): ", choices, "accept" + ) + + def _merge_table_model_into_incremental( + self, incremental_model: "GraphModel", table_model: "GraphModel" + ) -> None: + """Merge a single table's model into the incremental model.""" + # Add nodes (avoid duplicates based on labels) + existing_node_labels = { + tuple(sorted(node.labels)) for node in incremental_model.nodes + } + + for node in table_model.nodes: + node_labels_tuple = tuple(sorted(node.labels)) + if node_labels_tuple not in existing_node_labels: + incremental_model.nodes.append(node) + existing_node_labels.add(node_labels_tuple) + + # Add edges (avoid duplicates) + existing_edges = { + ( + edge.edge_type, + tuple(edge.start_node_labels), + tuple(edge.end_node_labels), + ) + for edge in incremental_model.edges + } + + for edge in table_model.edges: + edge_key = ( + edge.edge_type, + tuple(edge.start_node_labels), + tuple(edge.end_node_labels), + ) + if edge_key not in existing_edges: + incremental_model.edges.append(edge) + existing_edges.add(edge_key) + + # Add indexes + incremental_model.node_indexes.extend(table_model.node_indexes) + + # Add constraints + incremental_model.node_constraints.extend(table_model.node_constraints) + + def _build_table_model_map( + self, + full_model: "GraphModel", + tables: Dict[str, Any], + ) -> Dict[str, "GraphModel"]: + """Build lightweight sub-models per table from the complete model.""" + from .models.graph_models import GraphModel + + table_models: Dict[str, GraphModel] = {} + for table_name in tables.keys(): + table_nodes = [ + copy.deepcopy(node) + for node in full_model.nodes + if self._node_matches_table(node, table_name) + ] + + table_edges = [ + copy.deepcopy(edge) + for edge in full_model.edges + if self._relationship_matches_table(edge, table_name) + ] + + node_label_keys = {tuple(sorted(node.labels)) for node in table_nodes} + + table_indexes = [ + copy.deepcopy(index) + for index in full_model.node_indexes + if index.labels and tuple(sorted(index.labels)) in node_label_keys + ] + + table_constraints = [ + copy.deepcopy(constraint) + for constraint in full_model.node_constraints + if constraint.labels + and tuple(sorted(constraint.labels)) in node_label_keys + ] + + table_models[table_name] = GraphModel( + nodes=table_nodes, + edges=table_edges, + node_indexes=table_indexes, + node_constraints=table_constraints, + ) + + return table_models + + def _node_matches_table(self, node: "GraphNode", table_name: str) -> bool: + """Return True if a node traces back to the specified table.""" + source = getattr(node, "source", None) + if not source: + return False + + source_name = getattr(source, "name", None) + if isinstance(source_name, str) and source_name.lower() == table_name.lower(): + return True + + mapping = getattr(source, "mapping", {}) or {} + for key in ("table", "source", "source_table", "primary_table"): + value = mapping.get(key) + if isinstance(value, str) and value.lower() == table_name.lower(): + return True + + for value in mapping.values(): + if isinstance(value, str) and value.lower() == table_name.lower(): + return True + + labels = getattr(node, "labels", []) or [] + for label in labels: + if isinstance(label, str) and table_name.lower() in label.lower(): + return True + + return False + + def _relationship_matches_table( + self, relationship: "GraphRelationship", table_name: str + ) -> bool: + """Return True if a relationship is associated with the table.""" + source = getattr(relationship, "source", None) + mapping = getattr(source, "mapping", {}) or {} + + if source: + source_name = getattr(source, "name", None) + if ( + isinstance(source_name, str) + and source_name.lower() == table_name.lower() + ): + return True + + for key in ( + "from_table", + "to_table", + "join_table", + "through_table", + "source", + ): + value = mapping.get(key) + if isinstance(value, str) and value.lower() == table_name.lower(): + return True + + for value in mapping.values(): + if isinstance(value, str) and value.lower() == table_name.lower(): + return True + + # Fallback to matching on label names when mapping metadata is unavailable + combined_labels = list(relationship.start_node_labels) + list( + relationship.end_node_labels + ) + for label in combined_labels: + if isinstance(label, str) and table_name.lower() in label.lower(): + return True + + return False + + def _merge_source_less_elements( + self, + incremental_model: "GraphModel", + full_model: "GraphModel", + ) -> None: + """Add global elements that don't belong to a specific table.""" + if not full_model: + return + + from .models.graph_models import GraphModel + + anonymous_nodes = [ + copy.deepcopy(node) + for node in full_model.nodes + if getattr(node, "source", None) is None + ] + anonymous_edges = [ + copy.deepcopy(edge) + for edge in full_model.edges + if getattr(edge, "source", None) is None + ] + + if not anonymous_nodes and not anonymous_edges: + return + + placeholder_model = GraphModel( + nodes=anonymous_nodes, + edges=anonymous_edges, + node_indexes=[], + node_constraints=[], + ) + + self._merge_table_model_into_incremental(incremental_model, placeholder_model) + + def _modify_table_node_interactively( + self, table_model: "GraphModel", table_name: str + ) -> "GraphModel": + """Allow user to modify the proposed node for a table.""" + print(f"\n🔧 MODIFYING NODE FOR TABLE: {table_name}") + print("You can use natural language to modify the proposed node.") + print("Examples:") + print(" - Change the label from 'User' to 'Person'") + print(" - Remove the 'email' property") + print(" - Add a 'full_name' property") + + if not self.llm: + print("❌ LLM not available for natural language modifications.") + print("Returning original model.") + return table_model + + while True: + try: + user_input = input( + f"\nDescribe changes for {table_name} " f"(or 'done' to finish): " + ).strip() + + if user_input.lower() == "done": + break + elif not user_input: + print("Please describe the change you'd like to make.") + continue + + # Use existing natural language parsing + operations = self._parse_natural_language_to_operations( + user_input, table_model + ) + + if operations: + print(f"✅ Understood: {operations.reasoning}") + table_model = self._apply_operations_to_model( + table_model, operations ) - strategy = new_strategy - self.iteration_count += 1 - self.current_graph_model = current_model - return current_model + # Show updated model + print(f"\n📋 UPDATED NODE FOR {table_name}:") + for node in table_model.nodes: + labels = " | ".join(node.labels) + properties = [p.key for p in node.properties] + print(f" Labels: {labels}") + print(f" Properties: {properties}") + else: + print("❌ I didn't understand that command. " "Please try again.") + + except (EOFError, KeyboardInterrupt): + print(f"\nFinished modifying {table_name}") + break + + return table_model def _print_banner(self, title: str, width: int = 60) -> None: """Print a formatted banner with title.""" @@ -261,7 +848,10 @@ def _display_current_model(self, model: "GraphModel") -> None: print(f" {i}. {constraint.type.upper()}: {labels}.{props}") def _get_user_input_choice( - self, prompt: str, choices: Dict[str, str], default_action: str = "accept" + self, + prompt: str, + choices: Dict[str, str], + default_action: str = "accept", ) -> str: """Get validated user input from multiple choices. @@ -303,6 +893,22 @@ def _get_user_choice(self) -> str: "\nEnter your choice (1-4): ", choices, "accept" ) + def _get_refinement_choice(self) -> str: + """Get user choice while refining the combined graph model.""" + print("\nWhat would you like to do with the combined graph model?") + print("1. Accept and continue") + print("2. Modify the model using natural language commands") + print("3. Run graph schema validation") + + choices = { + "1": "accept", + "2": "modify", + "3": "validate", + } + return self._get_user_input_choice( + "\nEnter your choice (1-3): ", choices, "accept" + ) + def _switch_strategy( self, current_strategy: GraphModelingStrategy ) -> GraphModelingStrategy: @@ -539,7 +1145,10 @@ def _apply_operations_to_model( f"{op.old_property} → {op.new_property}" ) modified_model = self._apply_rename_property( - modified_model, op.node_label, op.old_property, op.new_property + modified_model, + op.node_label, + op.old_property, + op.new_property, ) elif op.operation_type == "drop_property": print(f" - Drop property: {op.node_label}.{op.property_name}") @@ -601,7 +1210,10 @@ def _apply_operations_to_model( elif op.operation_type == "add_node": print(f" - Add node: {op.node_label}") modified_model = self._apply_add_node( - modified_model, op.node_label, op.properties, op.source_table + modified_model, + op.node_label, + op.properties, + op.source_table, ) elif op.operation_type == "drop_node": print(f" - Drop node: {op.node_label}") @@ -623,6 +1235,30 @@ def _apply_operations_to_model( return modified_model + def _perform_manual_validation( + self, + model: "GraphModel", + strategy: GraphModelingStrategy, + ) -> "GraphModel": + """Run validation on demand without additional user operations.""" + try: + from .models.operations import ModelModifications + except ImportError: + from core.hygm.models.operations import ModelModifications + + dummy_operations = ModelModifications( + operations=[], + reasoning="Interactive refinement validation request", + ) + + return self._validate_and_improve_model( + model=model, + strategy=strategy, + operations=dummy_operations, + database_structure=self.database_structure or {}, + mode="interactive", + ) + def _apply_change_node_label( self, model: "GraphModel", old_label: str, new_label: str ) -> "GraphModel": @@ -669,7 +1305,11 @@ def _apply_change_node_label( return model def _apply_rename_property( - self, model: "GraphModel", node_label: str, old_property: str, new_property: str + self, + model: "GraphModel", + node_label: str, + old_property: str, + new_property: str, ) -> "GraphModel": """Apply rename property operation.""" for node in model.nodes: @@ -856,11 +1496,17 @@ def _apply_add_node( print(f" ⚠️ Node {node_label} already exists, skipping") return model - # Create node source + # Create node source metadata + source_name = source_table or node_label.lower() node_source = NodeSource( - origin="user_request", - table=source_table or node_label.lower(), - created_by="interactive_modification", + type="manual", + name=source_name, + location=source_name, + mapping={ + "labels": [node_label], + "properties": properties, + "created_by": "interactive_modification", + }, ) # Create properties @@ -920,8 +1566,8 @@ def _apply_add_relationship( properties: List[str], ) -> "GraphModel": """Apply add relationship operation.""" - from .models.graph_models import GraphEdge, GraphProperty - from .models.sources import PropertySource, EdgeSource + from .models.graph_models import GraphRelationship, GraphProperty + from .models.sources import PropertySource, RelationshipSource # Check if relationship already exists for edge in model.edges: @@ -937,10 +1583,17 @@ def _apply_add_relationship( ) return model - # Create edge source - edge_source = EdgeSource( - origin="user_request", - created_by="interactive_modification", + # Create edge source metadata + edge_source = RelationshipSource( + type="manual", + name=relationship_name, + location=relationship_name.lower(), + mapping={ + "start_node": start_node_label, + "end_node": end_node_label, + "properties": properties, + "created_by": "interactive_modification", + }, ) # Create properties @@ -952,7 +1605,7 @@ def _apply_add_relationship( edge_properties.append(GraphProperty(key=prop_name, source=prop_source)) # Create new relationship - new_edge = GraphEdge( + new_edge = GraphRelationship( edge_type=relationship_name, start_node_labels=[start_node_label], end_node_labels=[end_node_label], @@ -986,7 +1639,8 @@ def _validate_and_improve_automatic_llm_model( from .models.operations import ModelModifications dummy_operations = ModelModifications( - operations=[], reasoning="Automatic validation improvement iteration" + operations=[], + reasoning="Automatic validation improvement iteration", ) return self._validate_and_improve_model( @@ -1105,9 +1759,11 @@ def _validate_and_improve_model( "Validation iteration %d: %s (Coverage: %.1f%%)", improvement_count + 1, "PASSED" if validation_result.success else "FAILED", - validation_result.metrics.coverage_percentage - if validation_result.metrics - else 0, + ( + validation_result.metrics.coverage_percentage + if validation_result.metrics + else 0 + ), ) else: # Detailed display for interactive mode @@ -1436,7 +2092,10 @@ def _prepare_validation_context_for_llm( return "\n".join(context_parts) def _regenerate_model_with_llm_fixes( - self, current_model: "GraphModel", validation_context: str, validation_result + self, + current_model: "GraphModel", + validation_context: str, + validation_result, ) -> Optional["GraphModel"]: """Use LLM to regenerate an improved model based on validation.""" if not self.llm or not self.database_structure: @@ -1487,7 +2146,10 @@ def _regenerate_model_with_llm_fixes( return None def _prepare_improvement_context( - self, current_model: "GraphModel", validation_result, validation_context: str + self, + current_model: "GraphModel", + validation_result, + validation_context: str, ) -> str: """Prepare comprehensive context for LLM model improvement.""" context_parts = [] diff --git a/integrations/agents/core/hygm/models/__init__.py b/agents/sql2memgraph/core/hygm/models/__init__.py similarity index 100% rename from integrations/agents/core/hygm/models/__init__.py rename to agents/sql2memgraph/core/hygm/models/__init__.py diff --git a/integrations/agents/core/hygm/models/graph_models.py b/agents/sql2memgraph/core/hygm/models/graph_models.py similarity index 100% rename from integrations/agents/core/hygm/models/graph_models.py rename to agents/sql2memgraph/core/hygm/models/graph_models.py diff --git a/integrations/agents/core/hygm/models/llm_models.py b/agents/sql2memgraph/core/hygm/models/llm_models.py similarity index 100% rename from integrations/agents/core/hygm/models/llm_models.py rename to agents/sql2memgraph/core/hygm/models/llm_models.py diff --git a/integrations/agents/core/hygm/models/operations.py b/agents/sql2memgraph/core/hygm/models/operations.py similarity index 100% rename from integrations/agents/core/hygm/models/operations.py rename to agents/sql2memgraph/core/hygm/models/operations.py diff --git a/integrations/agents/core/hygm/models/sources.py b/agents/sql2memgraph/core/hygm/models/sources.py similarity index 100% rename from integrations/agents/core/hygm/models/sources.py rename to agents/sql2memgraph/core/hygm/models/sources.py diff --git a/integrations/agents/core/hygm/models/user_operations.py b/agents/sql2memgraph/core/hygm/models/user_operations.py similarity index 100% rename from integrations/agents/core/hygm/models/user_operations.py rename to agents/sql2memgraph/core/hygm/models/user_operations.py diff --git a/integrations/agents/core/hygm/strategies/__init__.py b/agents/sql2memgraph/core/hygm/strategies/__init__.py similarity index 100% rename from integrations/agents/core/hygm/strategies/__init__.py rename to agents/sql2memgraph/core/hygm/strategies/__init__.py diff --git a/integrations/agents/core/hygm/strategies/base.py b/agents/sql2memgraph/core/hygm/strategies/base.py similarity index 100% rename from integrations/agents/core/hygm/strategies/base.py rename to agents/sql2memgraph/core/hygm/strategies/base.py diff --git a/integrations/agents/core/hygm/strategies/deterministic.py b/agents/sql2memgraph/core/hygm/strategies/deterministic.py similarity index 100% rename from integrations/agents/core/hygm/strategies/deterministic.py rename to agents/sql2memgraph/core/hygm/strategies/deterministic.py diff --git a/integrations/agents/core/hygm/strategies/llm.py b/agents/sql2memgraph/core/hygm/strategies/llm.py similarity index 100% rename from integrations/agents/core/hygm/strategies/llm.py rename to agents/sql2memgraph/core/hygm/strategies/llm.py diff --git a/integrations/agents/core/hygm/validation/__init__.py b/agents/sql2memgraph/core/hygm/validation/__init__.py similarity index 100% rename from integrations/agents/core/hygm/validation/__init__.py rename to agents/sql2memgraph/core/hygm/validation/__init__.py diff --git a/integrations/agents/core/hygm/validation/base.py b/agents/sql2memgraph/core/hygm/validation/base.py similarity index 100% rename from integrations/agents/core/hygm/validation/base.py rename to agents/sql2memgraph/core/hygm/validation/base.py diff --git a/integrations/agents/core/hygm/validation/graph_schema_validator.py b/agents/sql2memgraph/core/hygm/validation/graph_schema_validator.py similarity index 100% rename from integrations/agents/core/hygm/validation/graph_schema_validator.py rename to agents/sql2memgraph/core/hygm/validation/graph_schema_validator.py diff --git a/integrations/agents/core/hygm/validation/memgraph_data_validator.py b/agents/sql2memgraph/core/hygm/validation/memgraph_data_validator.py similarity index 100% rename from integrations/agents/core/hygm/validation/memgraph_data_validator.py rename to agents/sql2memgraph/core/hygm/validation/memgraph_data_validator.py diff --git a/integrations/agents/core/migration_agent.py b/agents/sql2memgraph/core/migration_agent.py similarity index 51% rename from integrations/agents/core/migration_agent.py rename to agents/sql2memgraph/core/migration_agent.py index 63a3edd..b9b7947 100644 --- a/integrations/agents/core/migration_agent.py +++ b/agents/sql2memgraph/core/migration_agent.py @@ -1,3 +1,4 @@ +# flake8: noqa """ SQL Database to Memgraph Migration Agent @@ -5,11 +6,11 @@ and migrates data to Memgraph using LangGraph workflow. """ -import os -import sys +import hashlib +import json import logging -from time import sleep -from typing import Dict, List, Any, TypedDict, Optional +import sys +from typing import Dict, List, Any, TypedDict, Optional, cast from pathlib import Path # Add parent directories to path for imports @@ -17,15 +18,24 @@ sys.path.append(str(Path(__file__).parent.parent / "langchain-memgraph")) sys.path.append(str(Path(__file__).parent.parent)) # Add agents root to path -from langgraph.graph import StateGraph, END -from langchain_openai import ChatOpenAI -from dotenv import load_dotenv - -from query_generation.cypher_generator import CypherGenerator -from core.hygm import HyGM, ModelingMode, GraphModelingStrategy -from core.hygm.validation import validate_memgraph_data -from memgraph_toolbox.api.memgraph import Memgraph -from database.factory import DatabaseAnalyzerFactory +from langgraph.graph import StateGraph, END # noqa: E402 +from langchain_openai import ChatOpenAI # noqa: E402 +from langchain_core.runnables.config import RunnableConfig # noqa: E402 +from dotenv import load_dotenv # noqa: E402 + +from query_generation.cypher_generator import CypherGenerator # noqa: E402 +from core.hygm import HyGM, ModelingMode, GraphModelingStrategy # noqa: E402 +from core.hygm.validation import validate_memgraph_data # noqa: E402 +from memgraph_toolbox.api.memgraph import Memgraph # noqa: E402 +from database.factory import DatabaseAnalyzerFactory # noqa: E402 +from core.utils.meta_graph import ( # noqa: E402 + node_key as meta_node_key, + relationship_key as meta_relationship_key, + summarize_node as meta_summarize_node, + summarize_relationship as meta_summarize_relationship, + summarize_nodes as meta_summarize_nodes, + summarize_relationships as meta_summarize_relationships, +) # Load environment variables load_dotenv() @@ -37,7 +47,7 @@ class MigrationState(TypedDict): """State for the migration workflow.""" source_db_config: Dict[str, str] - memgraph_config: Dict[str, str] + memgraph_config: Optional[Dict[str, str]] database_structure: Dict[str, Any] graph_model: Any # HyGM GraphModel object migration_queries: List[str] @@ -48,6 +58,7 @@ class MigrationState(TypedDict): created_indexes: List[str] created_constraints: List[str] validation_report: Dict[str, Any] # Post-migration validation results + existing_meta_graph: Optional[Dict[str, Any]] class SQLToMemgraphAgent: @@ -56,30 +67,40 @@ class SQLToMemgraphAgent: def __init__( self, modeling_mode: ModelingMode = ModelingMode.AUTOMATIC, - graph_modeling_strategy: GraphModelingStrategy = GraphModelingStrategy.DETERMINISTIC, + graph_modeling_strategy: GraphModelingStrategy = ( + GraphModelingStrategy.DETERMINISTIC + ), + meta_graph_policy: str = "auto", ): """Initialize the migration agent. Args: modeling_mode: Graph modeling mode - AUTOMATIC: Generate graph model automatically (default) - - INTERACTIVE: Allow user to modify and refine graph model + - INCREMENTAL: Review tables and refine the model interactively graph_modeling_strategy: Strategy for graph model creation - DETERMINISTIC: Rule-based graph creation (default) - LLM_POWERED: LLM generates the graph model """ - - openai_api_key = os.getenv("OPENAI_API_KEY") - - self.llm = ChatOpenAI( - model="gpt-4o-mini", temperature=0.1, api_key=openai_api_key - ) + self.llm = ChatOpenAI(model="gpt-4o-mini", temperature=0.1) self.database_analyzer = None self.cypher_generator = CypherGenerator() self.modeling_mode = modeling_mode self.graph_modeling_strategy = graph_modeling_strategy + policy = (meta_graph_policy or "auto").lower() + if policy not in {"auto", "skip", "reset"}: + logger.warning( + "Unknown meta graph policy '%s'; defaulting to auto", + meta_graph_policy, + ) + policy = "auto" + self.meta_graph_policy = policy - self.memgraph_client = None + self.memgraph_client: Optional[Memgraph] = None + self._existing_meta_graph: Optional[Dict[str, Any]] = None + self._current_graph_model: Optional[Any] = None + self._ingestion_plan: Dict[str, Any] = {} + self._source_signature: Dict[str, str] = {} # Build the workflow graph self.workflow = self._build_workflow() @@ -95,31 +116,312 @@ def _get_db_config_for_migrate(self, db_config: Dict[str, str]) -> str: migrate_host = "host.docker.internal" return f"""{{ - user: '{db_config['user']}', - password: '{db_config['password']}', + user: '{db_config["user"]}', + password: '{db_config["password"]}', host: '{migrate_host}', - database: '{db_config['database']}' + database: '{db_config["database"]}' }}""" + def _compute_source_signature( + self, + state: MigrationState, + ) -> Dict[str, str]: + """Create a deterministic signature for the source database.""" + config = state.get("source_db_config", {}) + structure = state.get("database_structure", {}) + host = config.get("host", "") + database = config.get("database", "") + db_type = ( + structure.get("database_type") or config.get("database_type") or "mysql" + ) + signature = { + "host": host, + "database": database, + "type": db_type, + } + self._source_signature = signature + return signature + + def _node_key(self, node: Any) -> str: + """Generate a stable key for a graph node definition.""" + return meta_node_key(node) + + def _relationship_key(self, rel: Any) -> str: + """Generate a stable key for a graph relationship.""" + return meta_relationship_key(rel) + + def _summarize_node(self, node: Any) -> Dict[str, Any]: + """Create a JSON-serializable summary for a node definition.""" + return meta_summarize_node(node) + + def _summarize_relationship(self, rel: Any) -> Dict[str, Any]: + """Create a JSON-serializable summary for a relationship.""" + return meta_summarize_relationship(rel) + + def _graph_model_schema(self, model: Any) -> Dict[str, Any]: + """Convert a graph model to schema format if possible.""" + if hasattr(model, "to_schema_format"): + return model.to_schema_format() + return {} + + def _graph_model_hash(self, schema: Dict[str, Any]) -> str: + """Compute a stable hash for a schema dictionary.""" + schema_json = json.dumps(schema, sort_keys=True) + return hashlib.sha256(schema_json.encode("utf-8")).hexdigest() + + def _build_node_summaries(self, model: Any) -> Dict[str, Any]: + """Build summaries for all nodes in a model.""" + return meta_summarize_nodes(getattr(model, "nodes", [])) + + def _build_relationship_summaries(self, model: Any) -> Dict[str, Any]: + """Build summaries for all relationships in a model.""" + return meta_summarize_relationships(getattr(model, "edges", [])) + + def _load_existing_meta_graph(self, state: MigrationState) -> None: + """Read stored migration metadata from Memgraph if available.""" + if not self.memgraph_client: + return + + signature = self._compute_source_signature(state) + query = ( + "MATCH (meta:MigrationAgent {source_host: $host, " + "source_database: $database, source_type: $type}) " + "RETURN meta LIMIT 1" + ) + result = self.memgraph_client.query( + query, + { + "host": signature["host"], + "database": signature["database"], + "type": signature["type"], + }, + ) + + if result: + meta = result[0].get("meta", {}) + node_data = meta.get("node_summaries") or "{}" + rel_data = meta.get("relationship_summaries") or "{}" + table_counts = meta.get("table_counts") or "{}" + self._existing_meta_graph = { + "model_hash": meta.get("model_hash"), + "node_summaries": json.loads(node_data), + "relationship_summaries": json.loads(rel_data), + "table_counts": json.loads(table_counts), + } + state["existing_meta_graph"] = self._existing_meta_graph + logger.info( + "Loaded existing migration metadata for %s/%s", + signature["host"], + signature["database"], + ) + else: + self._existing_meta_graph = None + state["existing_meta_graph"] = None + logger.info( + "No existing migration metadata found for %s/%s", + signature["host"], + signature["database"], + ) + + def _calculate_ingestion_plan( + self, + graph_model: Any, + structure: Dict[str, Any], + ) -> Dict[str, Any]: + """Determine which nodes and relationships need migration.""" + plan = { + "nodes": set(), + "relationships": set(), + "node_reasons": {}, + "relationship_reasons": {}, + } + + table_counts = structure.get("table_counts", {}) or {} + existing = self._existing_meta_graph or {} + existing_nodes = existing.get("node_summaries", {}) or {} + existing_rels = existing.get("relationship_summaries", {}) or {} + existing_counts = existing.get("table_counts", {}) or {} + + node_keys_by_source: Dict[str, str] = {} + label_keys: Dict[str, str] = {} + + for node in getattr(graph_model, "nodes", []): + key = self._node_key(node) + summary = self._summarize_node(node) + source_name = summary.get("source") + if source_name: + node_keys_by_source[source_name] = key + label_key = "|".join(sorted(summary.get("labels", []))) + label_keys[label_key] = key + + reasons: List[str] = [] + stored = existing_nodes.get(key) + if not stored: + reasons.append("new node definition") + else: + if summary["properties"] != stored.get("properties", []): + reasons.append("properties changed") + if summary["id_field"] != stored.get("id_field"): + reasons.append("identifier changed") + + table_name = summary.get("source") + if table_name: + new_count = table_counts.get(table_name) + old_count = existing_counts.get(table_name) + if new_count is not None: + if old_count is None: + reasons.append("table count unavailable previously") + elif new_count != old_count: + if new_count > old_count: + reasons.append("source data increased") + else: + reasons.append("source data changed") + + if reasons or not existing_nodes: + plan["nodes"].add(key) + plan["node_reasons"][key] = reasons or ["initial migration"] + + for rel in getattr(graph_model, "edges", []): + key = self._relationship_key(rel) + summary = self._summarize_relationship(rel) + reasons: List[str] = [] + stored = existing_rels.get(key) + if not stored: + reasons.append("new relationship definition") + else: + if summary["mapping"] != stored.get("mapping", {}): + reasons.append("mapping changed") + if summary["start"] != stored.get("start", []): + reasons.append("start labels changed") + if summary["end"] != stored.get("end", []): + reasons.append("end labels changed") + + start_key = None + end_key = None + start_table = summary.get("start_table") + end_table = summary.get("end_table") + if start_table and start_table in node_keys_by_source: + start_key = node_keys_by_source[start_table] + if end_table and end_table in node_keys_by_source: + end_key = node_keys_by_source[end_table] + if not start_key: + label = "|".join(summary.get("start", [])) + start_key = label_keys.get(label) + if not end_key: + label = "|".join(summary.get("end", [])) + end_key = label_keys.get(label) + + dependent_update = False + if start_key and start_key in plan["nodes"]: + dependent_update = True + if end_key and end_key in plan["nodes"]: + dependent_update = True + if dependent_update and "dependent node update" not in reasons: + reasons.append("dependent node update") + + if reasons or not existing_rels: + plan["relationships"].add(key) + plan["relationship_reasons"][key] = reasons or ["initial migration"] + + self._ingestion_plan = plan + return plan + + def _store_meta_graph(self, state: MigrationState) -> None: + """Persist the current graph model metadata to Memgraph.""" + if not self.memgraph_client: + return + + graph_model = state.get("graph_model") + if not graph_model: + return + + structure = state.get("database_structure", {}) + schema = self._graph_model_schema(graph_model) + node_summaries = self._build_node_summaries(graph_model) + rel_summaries = self._build_relationship_summaries(graph_model) + table_counts = structure.get("table_counts", {}) or {} + + model_hash = self._graph_model_hash(schema) + signature = self._source_signature or self._compute_source_signature(state) + + query = ( + "MERGE (meta:MigrationAgent {source_host: $host, " + "source_database: $database, source_type: $type}) " + "SET meta.last_migrated_at = datetime(), " + "meta.model_hash = $model_hash, " + "meta.schema = $schema, " + "meta.node_summaries = $node_summaries, " + "meta.relationship_summaries = $relationship_summaries, " + "meta.table_counts = $table_counts" + ) + + self.memgraph_client.query( + query, + { + "host": signature.get("host", ""), + "database": signature.get("database", ""), + "type": signature.get("type", ""), + "model_hash": model_hash, + "schema": json.dumps(schema, sort_keys=True), + "node_summaries": json.dumps(node_summaries, sort_keys=True), + "relationship_summaries": json.dumps( + rel_summaries, + sort_keys=True, + ), + "table_counts": json.dumps(table_counts, sort_keys=True), + }, + ) + + logger.info( + "Stored migration metadata for %s/%s", + signature.get("host", ""), + signature.get("database", ""), + ) + def _build_workflow(self) -> StateGraph: - """Build the LangGraph workflow with improved separation of concerns.""" + """Build the LangGraph workflow with clear separation of concerns.""" workflow = StateGraph(MigrationState) # Add nodes - refactored for better modularity workflow.add_node( - "connect_and_analyze_schema", self._connect_and_analyze_schema + "connect_and_analyze_schema", + self._connect_and_analyze_schema, + ) + workflow.add_node( + "create_graph_model", + self._create_graph_model, + ) + workflow.add_node( + "create_indexes", + self._create_indexes, + ) + workflow.add_node( + "generate_cypher_queries", + self._generate_cypher_queries, + ) + workflow.add_node( + "prepare_target_database", + self._prepare_target_database, + ) + workflow.add_node( + "execute_data_migration", + self._execute_data_migration, + ) + workflow.add_node( + "validate_post_migration", + self._validate_post_migration, ) - workflow.add_node("create_graph_model", self._create_graph_model) - workflow.add_node("create_indexes", self._create_indexes) - workflow.add_node("generate_cypher_queries", self._generate_cypher_queries) - workflow.add_node("prepare_target_database", self._prepare_target_database) - workflow.add_node("execute_data_migration", self._execute_data_migration) - workflow.add_node("validate_post_migration", self._validate_post_migration) # Add conditional edges for better error handling - workflow.add_edge("connect_and_analyze_schema", "create_graph_model") - workflow.add_edge("create_graph_model", "prepare_target_database") - workflow.add_edge("prepare_target_database", "create_indexes") + workflow.add_edge( + "connect_and_analyze_schema", + "prepare_target_database", + ) + workflow.add_edge( + "prepare_target_database", + "create_graph_model", + ) + workflow.add_edge("create_graph_model", "create_indexes") workflow.add_edge("create_indexes", "generate_cypher_queries") workflow.add_edge("generate_cypher_queries", "execute_data_migration") workflow.add_edge("execute_data_migration", "validate_post_migration") @@ -131,8 +433,11 @@ def _build_workflow(self) -> StateGraph: # Return the workflow (not compiled) so caller can add checkpointer return workflow - def _connect_and_analyze_schema(self, state: MigrationState) -> MigrationState: - """Connect to source database and prepare basic connection info for HyGM.""" + def _connect_and_analyze_schema( + self, + state: MigrationState, + ) -> MigrationState: + """Connect to source database and prepare info for HyGM.""" logger.info("Preparing database connection for HyGM analysis...") try: @@ -169,8 +474,11 @@ def _create_graph_model(self, state: MigrationState) -> MigrationState: hygm_data = state["database_structure"] # Log the modeling mode being used - if self.modeling_mode == ModelingMode.INTERACTIVE: - logger.info("Using interactive graph modeling mode") + if self.modeling_mode == ModelingMode.INCREMENTAL: + logger.info( + "Using incremental graph modeling mode with an " + "end-of-session interactive refinement option" + ) else: logger.info("Using automatic graph modeling mode") @@ -179,6 +487,7 @@ def _create_graph_model(self, state: MigrationState) -> MigrationState: llm=self.llm, mode=self.modeling_mode, strategy=self.graph_modeling_strategy, + existing_meta_graph=state.get("existing_meta_graph"), ) # Log the strategy being used @@ -187,7 +496,8 @@ def _create_graph_model(self, state: MigrationState) -> MigrationState: # Generate graph model using new unified interface graph_model = graph_modeler.create_graph_model( - hygm_data, domain_context="Database migration to graph database" + hygm_data, + domain_context="Database migration to graph database", ) # Store the graph model in state @@ -208,18 +518,33 @@ def _create_graph_model(self, state: MigrationState) -> MigrationState: return state - def _prepare_target_database(self, state: MigrationState) -> MigrationState: + def _prepare_target_database( + self, + state: MigrationState, + ) -> MigrationState: """Prepare the target Memgraph database for migration.""" logger.info("Preparing target database for migration...") try: # Initialize Memgraph connection - config = state["memgraph_config"] + config_value = state.get("memgraph_config") + if not config_value: + raise Exception("Memgraph configuration is required") + config = cast(Dict[str, str], config_value) + + url = config.get("url") + if not url: + raise Exception("Memgraph configuration must include 'url'") + + username = config.get("username") or "" + password = config.get("password") or "" + database = config.get("database") or "memgraph" + self.memgraph_client = Memgraph( - url=config.get("url"), - username=config.get("username"), - password=config.get("password"), - database=config.get("database"), + url=url, + username=username, + password=password, + database=database, ) # Test Memgraph connection @@ -227,18 +552,29 @@ def _prepare_target_database(self, state: MigrationState) -> MigrationState: self.memgraph_client.query(test_query) logger.info("Memgraph connection established successfully") - # Clear the database first to avoid constraint violations - try: - logger.info("Clearing existing data from Memgraph...") - self.memgraph_client.query("STORAGE MODE IN_MEMORY_ANALYTICAL;") - sleep(1) - self.memgraph_client.query("DROP GRAPH") - sleep(5) - self.memgraph_client.query("STORAGE MODE IN_MEMORY_TRANSACTIONAL;") - sleep(1) - logger.info("Database cleared successfully") - except Exception as e: - logger.warning(f"Database clearing failed (might be empty): {e}") + # Load existing meta graph to plan incremental ingestion + policy = getattr(self, "meta_graph_policy", "auto") + if policy == "skip": + logger.info("Meta graph loading skipped by configuration") + self._existing_meta_graph = None + state["existing_meta_graph"] = None + else: + self._load_existing_meta_graph(state) + if self._existing_meta_graph: + if policy == "reset": + logger.info( + "Existing migration metadata ignored due to reset policy", + ) + self._existing_meta_graph = None + state["existing_meta_graph"] = None + else: + logger.info( + "Existing migration metadata detected; data will be merged", + ) + else: + logger.info( + "No migration metadata found; treating this as an initial run", + ) state["current_step"] = "Target database prepared successfully" @@ -254,12 +590,16 @@ def _execute_data_migration(self, state: MigrationState) -> MigrationState: logger.info("Executing data migration...") try: + memgraph_client = self.memgraph_client + if not memgraph_client: + raise Exception("Memgraph client is not initialized") + queries = state["migration_queries"] # Execute all migration queries sequentially successful_queries = 0 for i, query in enumerate(queries): - # Skip empty queries, but don't skip queries that contain comments + # Skip empty queries but keep comment-only blocks for context query_lines = [line.strip() for line in query.strip().split("\n")] non_comment_lines = [ line for line in query_lines if line and not line.startswith("//") @@ -267,13 +607,17 @@ def _execute_data_migration(self, state: MigrationState) -> MigrationState: if non_comment_lines: # Has actual Cypher code try: - logger.info(f"Executing query {i+1}/{len(queries)}...") - self.memgraph_client.query(query) + logger.info( + "Executing query %d/%d...", + i + 1, + len(queries), + ) + memgraph_client.query(query) successful_queries += 1 # Log progress for node creation queries if "CREATE (n:" in query: - # Extract table name from query comment or FROM clause + # Extract table name from comment or FROM clause table_name = None if "FROM " in query: try: @@ -294,7 +638,7 @@ def _execute_data_migration(self, state: MigrationState) -> MigrationState: logger.info("Successfully created relationships") except Exception as e: - logger.error(f"Failed to execute query {i+1}: {e}") + logger.error(f"Failed to execute query {i + 1}: {e}") logger.error(f"Query: {query[:100]}...") state["errors"].append(f"Query execution failed: {e}") @@ -321,13 +665,14 @@ def _execute_queries_with_logging( """Execute queries with consistent logging and error handling.""" for query in queries: try: - logger.info(f"Creating {query_type}: %s", query) + logger.info("Creating %s: %s", query_type, query) memgraph_client.query(query) success_list.append(query) except Exception as e: # Some queries might already exist, log but continue logger.warning( - f"{query_type.capitalize()} creation {warning_prefix}: %s", e + f"{query_type.capitalize()} creation {warning_prefix}: %s", + e, ) def _handle_step_error( @@ -348,7 +693,7 @@ def _handle_step_error( def _create_indexes(self, state: MigrationState) -> MigrationState: """Create indexes and constraints in Memgraph before migration.""" - logger.info("Creating indexes and constraints from HyGM graph model...") + logger.info("Creating HyGM indexes and constraints...") try: # Use the existing Memgraph connection from prepare_target_database @@ -413,89 +758,139 @@ def _create_indexes(self, state: MigrationState) -> MigrationState: return state - def _generate_cypher_queries(self, state: MigrationState) -> MigrationState: - """Generate Cypher queries based on HyGM graph model recommendations.""" + def _generate_cypher_queries( + self, + state: MigrationState, + ) -> MigrationState: + """Generate merge-based Cypher queries using the ingestion plan.""" logger.info("Generating Cypher queries based on HyGM graph model...") try: source_db_config = state["source_db_config"] - - # Get the HyGM graph model (required) graph_model = state.get("graph_model") if not graph_model: raise Exception("HyGM graph model is required for migration") - # Store graph model in instance for use by helper methods self._current_graph_model = graph_model - queries = [] - # Create database connection config for migrate module - db_config_str = self._get_db_config_for_migrate(source_db_config) + structure = state.get("database_structure", {}) + plan = self._calculate_ingestion_plan(graph_model, structure) + nodes_to_migrate = plan["nodes"] + relationships_to_migrate = plan["relationships"] - # Generate node creation queries based on HyGM recommendations - logger.info( - f"Creating nodes based on {len(graph_model.nodes)} HyGM node definitions" - ) + if not nodes_to_migrate and not relationships_to_migrate: + logger.info( + "Schema and table counts already match stored metadata; " + "no migration queries generated" + ) + state["migration_queries"] = [] + state["current_step"] = "No new data to migrate" + return state + + for node_key in sorted(nodes_to_migrate): + reasons = plan["node_reasons"].get(node_key, []) + reason_text = ", ".join(reasons) if reasons else "initial migration" + logger.info("Node plan %s → %s", node_key, reason_text) + + for rel_key in sorted(relationships_to_migrate): + reasons = plan["relationship_reasons"].get(rel_key, []) + reason_text = ", ".join(reasons) if reasons else "initial migration" + logger.info("Relationship plan %s → %s", rel_key, reason_text) + + queries: List[str] = [] + db_config_str = self._get_db_config_for_migrate(source_db_config) for node_def in graph_model.nodes: - source_table = node_def.source.name if node_def.source else "unknown" + node_key = self._node_key(node_def) + if nodes_to_migrate and node_key not in nodes_to_migrate: + continue + + source = getattr(node_def, "source", None) + source_table = getattr(source, "name", None) or "unknown" node_label = node_def.primary_label - # Extract property names from HyGM GraphProperty objects properties = [ prop.key if hasattr(prop, "key") else str(prop) - for prop in node_def.properties + for prop in getattr(node_def, "properties", []) ] - # Use validated properties from HyGM graph model - if properties: - properties_str = ", ".join(properties) - node_query = f""" -// Create {node_label} nodes from {source_table} table (HyGM optimized) -CALL migrate.mysql('SELECT {properties_str} FROM {source_table}', - {db_config_str}) -YIELD row -CREATE (n:{node_label}) -SET n += row;""" - queries.append(node_query) - logger.info( - f"Added node creation for {node_label} with " - f"{len(properties)} properties" + node_mapping = getattr(source, "mapping", {}) if source else {} + id_field = node_mapping.get("id_field") + if not id_field and properties: + id_field = properties[0] + + if id_field and id_field not in properties: + properties.append(id_field) + + if not id_field: + logger.warning( + "Skipping node %s: identifier field missing", + node_label, ) - else: + continue + + if not properties: logger.warning( - f"No properties found for node {node_label} " - f"from table {source_table}" + "No properties found for node %s from table %s", + node_label, + source_table, ) + continue + + properties_str = ", ".join(properties) + node_query = f""" +// Merge {node_label} nodes from {source_table} table (HyGM optimized) +CALL migrate.mysql( + 'SELECT {properties_str} FROM {source_table}', + {db_config_str} +) +YIELD row +MERGE (n:{node_label} {{{id_field}: row.{id_field}}}) +SET n += row;""" + queries.append(node_query) + logger.info("Prepared merge query for %s", node_label) - # Generate relationship creation queries based on HyGM recommendations logger.info( - f"Creating relationships based on {len(graph_model.edges)} HyGM relationship definitions" + "Preparing relationship queries for %d definitions", + len(graph_model.edges), ) for rel_def in graph_model.edges: + rel_key = self._relationship_key(rel_def) + if relationships_to_migrate and rel_key not in relationships_to_migrate: + continue + rel_query = self._generate_hygm_relationship_query( rel_def, db_config_str ) if rel_query: queries.append(rel_query) - logger.info(f"Added relationship creation: {rel_def.edge_type}") + logger.info( + "Prepared merge query for relationship %s", + rel_def.edge_type, + ) state["migration_queries"] = queries - state["current_step"] = "Cypher queries generated using HyGM graph model" + state["current_step"] = "Migration queries prepared" - logger.info( - f"Generated {len(queries)} migration queries based on HyGM recommendations" - ) + logger.info("Generated %d migration queries", len(queries)) except Exception as e: logger.error(f"Error generating HyGM-based Cypher queries: {e}") - return self._handle_step_error(state, "generating cypher queries", e) + return self._handle_step_error( + state, + "generating cypher queries", + e, + ) return state - def _generate_hygm_relationship_query(self, rel_def, mysql_config_str: str) -> str: - """Generate relationship query based on HyGM relationship definition.""" + def _generate_hygm_relationship_query( + self, + rel_def, + mysql_config_str: str, + ) -> str: + """Create relationship query from HyGM definition.""" try: if not rel_def.source or not rel_def.source.mapping: @@ -517,12 +912,17 @@ def _generate_hygm_relationship_query(self, rel_def, mysql_config_str: str) -> s rel_name, rel_def, source_info, mysql_config_str ) else: - logger.warning(f"Unsupported relationship type: {rel_def.source.type}") + logger.warning( + "Unsupported relationship type: %s", + rel_def.source.type, + ) return "" except Exception as e: logger.error( - "Error generating relationship query for %s: %s", rel_def.edge_type, e + "Error generating relationship query for %s: %s", + rel_def.edge_type, + e, ) return "" @@ -533,46 +933,55 @@ def _generate_one_to_many_hygm_query( source_info: Dict[str, Any], mysql_config_str: str, ) -> str: - """Generate one-to-many relationship query using HyGM source information.""" + """Generate one-to-many relationship query from HyGM mapping.""" - # All mapping information should come from HyGM source - start_node = source_info.get("start_node", "") # e.g., "address.city_id" - end_node = source_info.get("end_node", "") # e.g., "city.city_id" - from_pk = source_info.get("from_pk") # Primary key provided by HyGM + start_node = source_info.get("start_node", "") + end_node = source_info.get("end_node", "") + from_pk = source_info.get("from_pk") if not start_node or not end_node: logger.error("Missing relationship information for %s", rel_name) raise Exception( - f"HyGM must provide complete relationship mapping for {rel_name}" + "HyGM must provide complete relationship mapping for " f"{rel_name}" ) - # Parse the table.column format try: from_table, fk_column = start_node.split(".", 1) to_table, to_column = end_node.split(".", 1) except ValueError: - logger.error("Invalid mapping format for %s: %s", rel_name, source_info) + logger.error( + "Invalid mapping format for %s: %s", + rel_name, + source_info, + ) raise Exception( f"HyGM must provide valid relationship mapping for {rel_name}" ) - # HyGM should provide the primary key information if not from_pk: raise Exception(f"HyGM must provide primary key information for {rel_name}") - # Get node labels from the relationship definition from_label = ( rel_def.start_node_labels[0] if rel_def.start_node_labels else from_table ) to_label = rel_def.end_node_labels[0] if rel_def.end_node_labels else to_table + select_sql = ( + f"SELECT {from_pk}, {fk_column} " + f"FROM {from_table} " + f"WHERE {fk_column} IS NOT NULL" + ) + query = f""" -// Create {rel_name} relationships (HyGM: {from_label} -> {to_label}) -CALL migrate.mysql('SELECT {from_pk}, {fk_column} FROM {from_table} WHERE {fk_column} IS NOT NULL', {mysql_config_str}) +// Merge {rel_name} relationships (HyGM: {from_label} -> {to_label}) +CALL migrate.mysql( + '{select_sql}', + {mysql_config_str} +) YIELD row MATCH (from_node:{from_label} {{{from_pk}: row.{from_pk}}}) MATCH (to_node:{to_label} {{{to_column}: row.{fk_column}}}) -CREATE (from_node)-[:{rel_name}]->(to_node);""" +MERGE (from_node)-[:{rel_name}]->(to_node);""" return query @@ -583,42 +992,49 @@ def _generate_many_to_many_hygm_query( source_info: Dict[str, Any], mysql_config_str: str, ) -> str: - """Generate many-to-many relationship query using HyGM source information.""" + """Generate many-to-many relationship query from HyGM mapping.""" - # All many-to-many join table information should come from HyGM source join_table = source_info.get("join_table") from_table = source_info.get("from_table") to_table = source_info.get("to_table") - from_fk = source_info.get("join_from_column") # FK in many-to-many join table - to_fk = source_info.get("join_to_column") # FK in many-to-many join table - from_pk = source_info.get("from_column") # PK in source table - to_pk = source_info.get("to_column") # PK in target table + from_fk = source_info.get("join_from_column") + to_fk = source_info.get("join_to_column") + from_pk = source_info.get("from_column") + to_pk = source_info.get("to_column") if not all([join_table, from_table, to_table, from_fk, to_fk, from_pk, to_pk]): logger.error( - "Missing many-to-many relationship information for %s", rel_name + "Missing many-to-many relationship information for %s", + rel_name, ) raise Exception( - f"HyGM must provide complete many-to-many mapping for {rel_name}" + "HyGM must provide complete many-to-many mapping for " f"{rel_name}" ) - # Get node labels from the relationship definition from_label = ( rel_def.start_node_labels[0] if rel_def.start_node_labels else from_table ) to_label = rel_def.end_node_labels[0] if rel_def.end_node_labels else to_table + select_sql = f"SELECT {from_fk}, {to_fk} " f"FROM {join_table}" + query = f""" -// Create {rel_name} relationships via {join_table} +// Merge {rel_name} relationships via {join_table} // (HyGM: {from_label} <-> {to_label}) -CALL migrate.mysql('SELECT {from_fk}, {to_fk} FROM {join_table}', {mysql_config_str}) +CALL migrate.mysql( + '{select_sql}', + {mysql_config_str} +) YIELD row MATCH (from:{from_label} {{{from_pk}: row.{from_fk}}}) MATCH (to:{to_label} {{{to_pk}: row.{to_fk}}}) -CREATE (from)-[:{rel_name}]->(to);""" +MERGE (from)-[:{rel_name}]->(to);""" return query - def _validate_post_migration(self, state: MigrationState) -> MigrationState: + def _validate_post_migration( + self, + state: MigrationState, + ) -> MigrationState: """Validate post-migration results using HyGM schema comparison.""" logger.info("Running post-migration validation...") @@ -651,7 +1067,7 @@ def _validate_post_migration(self, state: MigrationState) -> MigrationState: expected_nodes = 0 table_counts = structure.get("table_counts", {}) - # If selected_tables is not set, use all entity tables that were migrated + # Default to all migrated tables when nothing specific is selected selected_tables = structure.get("selected_tables", []) if not selected_tables: # Use entity tables (exclude views and system tables) @@ -668,7 +1084,7 @@ def _validate_post_migration(self, state: MigrationState) -> MigrationState: "selected_tables": selected_tables, } - # Run post-migration validation using existing connection with data counts + # Run validation using existing connection and data counts logger.info("Executing post-migration validation...") validation_result = validate_memgraph_data( expected_model=graph_model, @@ -723,6 +1139,9 @@ def _validate_post_migration(self, state: MigrationState) -> MigrationState: state["current_step"] = "Post-migration validation completed" + if not state["errors"]: + self._store_meta_graph(state) + except Exception as e: logger.error(f"Error during post-migration validation: {e}") state["errors"].append(f"Post-migration validation failed: {e}") @@ -756,23 +1175,29 @@ def migrate( created_indexes=[], created_constraints=[], validation_report={}, + existing_meta_graph=None, ) try: - # For automatic graph modeling mode, compile workflow without checkpointer + # Automatic mode compiles workflow without a checkpointer if self.modeling_mode == ModelingMode.AUTOMATIC: compiled_workflow = self.workflow.compile() final_state = compiled_workflow.invoke(initial_state) else: - # For interactive graph modeling mode, import and use checkpointer + # Incremental mode enables a persistent checkpointer from langgraph.checkpoint.memory import MemorySaver memory = MemorySaver() compiled_workflow = self.workflow.compile(checkpointer=memory) # Provide required configuration for checkpointer - config = {"configurable": {"thread_id": "migration_thread_1"}} - final_state = compiled_workflow.invoke(initial_state, config=config) + config: RunnableConfig = { + "configurable": {"thread_id": "migration_thread_1"} + } + final_state = compiled_workflow.invoke( + initial_state, + config=config, + ) # Cleanup connections if self.database_analyzer: diff --git a/integrations/agents/core/schema/spec.json b/agents/sql2memgraph/core/schema/spec.json similarity index 100% rename from integrations/agents/core/schema/spec.json rename to agents/sql2memgraph/core/schema/spec.json diff --git a/agents/sql2memgraph/core/utils/meta_graph.py b/agents/sql2memgraph/core/utils/meta_graph.py new file mode 100644 index 0000000..5e26a71 --- /dev/null +++ b/agents/sql2memgraph/core/utils/meta_graph.py @@ -0,0 +1,108 @@ +"""Shared helpers for HyGM meta graph summaries and keys.""" + +from __future__ import annotations + +from typing import Any, Dict, List + + +def node_key(node: Any) -> str: + """Generate a stable key for a graph node definition.""" + source = getattr(node, "source", None) + source_name = getattr(source, "name", None) + if source_name: + return f"source::{source_name}" + labels = sorted(getattr(node, "labels", [])) + return "labels::" + "|".join(labels) + + +def relationship_key(rel: Any) -> str: + """Generate a stable key for a graph relationship.""" + source = getattr(rel, "source", None) + source_name = getattr(source, "name", None) + if source_name: + return f"source::{source_name}" + edge_type = getattr(rel, "edge_type", "") + start = "|".join(sorted(getattr(rel, "start_node_labels", []))) + end = "|".join(sorted(getattr(rel, "end_node_labels", []))) + return f"edge::{edge_type}:{start}->{end}" + + +def summarize_node(node: Any) -> Dict[str, Any]: + """Create a JSON-serializable summary for a node definition.""" + properties = sorted( + {prop.key for prop in getattr(node, "properties", []) if hasattr(prop, "key")} + ) + node_source = getattr(node, "source", None) + mapping: Dict[str, Any] = {} + source_name = None + id_field = None + if node_source: + mapping = dict(getattr(node_source, "mapping", {}) or {}) + source_name = getattr(node_source, "name", None) + id_field = mapping.get("id_field") + return { + "labels": sorted(getattr(node, "labels", [])), + "properties": properties, + "id_field": id_field, + "source": source_name, + "mapping": mapping, + } + + +def summarize_relationship(rel: Any) -> Dict[str, Any]: + """Create a JSON-serializable summary for a relationship.""" + rel_source = getattr(rel, "source", None) + mapping: Dict[str, Any] = {} + source_name = None + source_type = None + if rel_source: + mapping = dict(getattr(rel_source, "mapping", {}) or {}) + source_name = getattr(rel_source, "name", None) + source_type = getattr(rel_source, "type", None) + start_labels = sorted(getattr(rel, "start_node_labels", [])) + end_labels = sorted(getattr(rel, "end_node_labels", [])) + start_table = mapping.get("from_table") + end_table = mapping.get("to_table") + if not start_table and mapping.get("start_node"): + start_table = str(mapping["start_node"]).split(".")[0] + if not end_table and mapping.get("end_node"): + end_table = str(mapping["end_node"]).split(".")[0] + return { + "edge_type": getattr(rel, "edge_type", ""), + "start": start_labels, + "end": end_labels, + "source": source_name, + "source_type": source_type, + "mapping": mapping, + "start_table": start_table, + "end_table": end_table, + "join_table": mapping.get("join_table"), + } + + +def summarize_nodes(nodes: List[Any]) -> Dict[str, Dict[str, Any]]: + """Build summaries for all provided nodes.""" + summaries: Dict[str, Dict[str, Any]] = {} + for node in nodes: + summaries[node_key(node)] = summarize_node(node) + return summaries + + +def summarize_relationships( + relationships: List[Any], +) -> Dict[str, Dict[str, Any]]: + """Build summaries for all provided relationships.""" + summaries: Dict[str, Dict[str, Any]] = {} + for relationship in relationships: + summaries[relationship_key(relationship)] = summarize_relationship(relationship) + return summaries + + +__all__ = [ + "node_key", + "relationship_key", + "summarize_node", + "summarize_relationship", + "summarize_nodes", + "summarize_relationships", +] diff --git a/integrations/agents/database/__init__.py b/agents/sql2memgraph/database/__init__.py similarity index 100% rename from integrations/agents/database/__init__.py rename to agents/sql2memgraph/database/__init__.py diff --git a/integrations/agents/database/adapters/__init__.py b/agents/sql2memgraph/database/adapters/__init__.py similarity index 100% rename from integrations/agents/database/adapters/__init__.py rename to agents/sql2memgraph/database/adapters/__init__.py diff --git a/integrations/agents/database/adapters/memgraph.py b/agents/sql2memgraph/database/adapters/memgraph.py similarity index 100% rename from integrations/agents/database/adapters/memgraph.py rename to agents/sql2memgraph/database/adapters/memgraph.py diff --git a/integrations/agents/database/adapters/mysql.py b/agents/sql2memgraph/database/adapters/mysql.py similarity index 100% rename from integrations/agents/database/adapters/mysql.py rename to agents/sql2memgraph/database/adapters/mysql.py diff --git a/integrations/agents/database/adapters/postgresql.py b/agents/sql2memgraph/database/adapters/postgresql.py similarity index 100% rename from integrations/agents/database/adapters/postgresql.py rename to agents/sql2memgraph/database/adapters/postgresql.py diff --git a/integrations/agents/database/analyzer.py b/agents/sql2memgraph/database/analyzer.py similarity index 100% rename from integrations/agents/database/analyzer.py rename to agents/sql2memgraph/database/analyzer.py diff --git a/integrations/agents/database/factory.py b/agents/sql2memgraph/database/factory.py similarity index 100% rename from integrations/agents/database/factory.py rename to agents/sql2memgraph/database/factory.py diff --git a/integrations/agents/database/models.py b/agents/sql2memgraph/database/models.py similarity index 100% rename from integrations/agents/database/models.py rename to agents/sql2memgraph/database/models.py diff --git a/integrations/agents/examples/__init__.py b/agents/sql2memgraph/examples/__init__.py similarity index 100% rename from integrations/agents/examples/__init__.py rename to agents/sql2memgraph/examples/__init__.py diff --git a/integrations/agents/examples/basic_migration.py b/agents/sql2memgraph/examples/basic_migration.py similarity index 100% rename from integrations/agents/examples/basic_migration.py rename to agents/sql2memgraph/examples/basic_migration.py diff --git a/integrations/agents/examples/constraint_operations_example.py b/agents/sql2memgraph/examples/constraint_operations_example.py similarity index 100% rename from integrations/agents/examples/constraint_operations_example.py rename to agents/sql2memgraph/examples/constraint_operations_example.py diff --git a/integrations/agents/main.py b/agents/sql2memgraph/main.py similarity index 66% rename from integrations/agents/main.py rename to agents/sql2memgraph/main.py index 1cd8b2b..9f4eb63 100644 --- a/integrations/agents/main.py +++ b/agents/sql2memgraph/main.py @@ -1,4 +1,5 @@ #!/usr/bin/env python3 +# flake8: noqa """ SQL Database to Memgraph Migration Agent - Main Entry Point @@ -6,15 +7,17 @@ Run with: uv run main.py """ +import argparse import logging +import os import sys -from typing import Dict, Any +from typing import Dict, Any, Optional from pathlib import Path # Add current directory to Python path for absolute imports sys.path.insert(0, str(Path(__file__).parent)) -from utils import ( +from utils import ( # noqa: E402 MigrationEnvironmentError, DatabaseConnectionError, setup_and_validate_environment, @@ -22,16 +25,130 @@ print_environment_help, print_troubleshooting_help, ) -from core import SQLToMemgraphAgent -from core.hygm import GraphModelingStrategy, ModelingMode +from core import SQLToMemgraphAgent # noqa: E402 +from core.hygm import GraphModelingStrategy, ModelingMode # noqa: E402 # Configure logging logging.basicConfig( - level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s" + level=logging.INFO, + format="%(asctime)s - %(name)s - %(levelname)s - %(message)s", ) logger = logging.getLogger(__name__) +MODE_CHOICES = { + "automatic": ModelingMode.AUTOMATIC, + "incremental": ModelingMode.INCREMENTAL, +} + +STRATEGY_CHOICES = { + "deterministic": GraphModelingStrategy.DETERMINISTIC, + "llm": GraphModelingStrategy.LLM_POWERED, + "llm_powered": GraphModelingStrategy.LLM_POWERED, +} + +META_GRAPH_POLICIES = {"auto", "skip", "reset"} + +LOG_LEVEL_CHOICES = ["CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG", "NOTSET"] + + +def _lower_env(name: str) -> Optional[str]: + value = os.getenv(name) + return value.lower() if value else None + + +def _upper_env(name: str) -> Optional[str]: + value = os.getenv(name) + return value.upper() if value else None + + +def parse_cli_args(argv: Optional[list[str]] = None) -> argparse.Namespace: + """Parse command-line arguments for the migration agent.""" + + env_mode = _lower_env("SQL2MG_MODE") + env_strategy = _lower_env("SQL2MG_STRATEGY") + env_meta_policy = _lower_env("SQL2MG_META_POLICY") + env_log_level = _upper_env("SQL2MG_LOG_LEVEL") + + parser = argparse.ArgumentParser( + description="SQL database to Memgraph migration agent", + ) + + parser.add_argument( + "--mode", + choices=sorted(MODE_CHOICES.keys()), + default=env_mode, + type=str.lower, + help="Graph modeling mode (automatic|incremental). Overrides SQL2MG_MODE.", + ) + + parser.add_argument( + "--strategy", + choices=["deterministic", "llm"], + default=env_strategy, + type=str.lower, + help="Graph modeling strategy (deterministic|llm). Overrides SQL2MG_STRATEGY.", + ) + + parser.add_argument( + "--meta-graph", + choices=sorted(META_GRAPH_POLICIES), + default=env_meta_policy, + type=str.lower, + help=( + "Meta graph policy: auto (default), skip stored metadata, or reset to " + "ignore previous migrations. Overrides SQL2MG_META_POLICY." + ), + ) + + parser.add_argument( + "--log-level", + choices=LOG_LEVEL_CHOICES, + default=env_log_level, + type=str.upper, + help="Logging level for the agent. Overrides SQL2MG_LOG_LEVEL.", + ) + + return parser.parse_args(argv) + + +def _configure_log_level(level_name: Optional[str]) -> None: + """Configure global logging level if provided.""" + + if not level_name: + return + + numeric_level = getattr(logging, level_name.upper(), None) + if not isinstance(numeric_level, int): + logger.warning("Unknown log level '%s'; falling back to INFO", level_name) + numeric_level = logging.INFO + + logging.getLogger().setLevel(numeric_level) + for handler in logging.getLogger().handlers: + handler.setLevel(numeric_level) + logger.setLevel(numeric_level) + + +def _resolve_mode(cli_mode: Optional[str]) -> Optional[ModelingMode]: + if not cli_mode: + return None + resolved = MODE_CHOICES.get(cli_mode) + if not resolved: + logger.warning("Unrecognised mode '%s'; falling back to prompt", cli_mode) + return resolved + + +def _resolve_strategy(cli_strategy: Optional[str]) -> Optional[GraphModelingStrategy]: + if not cli_strategy: + return None + resolved = STRATEGY_CHOICES.get(cli_strategy) + if not resolved: + logger.warning( + "Unrecognised strategy '%s'; falling back to prompt", + cli_strategy, + ) + return resolved + def print_banner() -> None: """Print application banner.""" @@ -51,9 +168,8 @@ def get_graph_modeling_mode() -> ModelingMode: """ print("Graph modeling mode:") print() - print(" 1. Interactive - Generate graph model with user feedback") - print() - print(" 2. Automatic - Generate graph model automatically without user feedback") + print(" 1. Automatic - Generate graph model without prompts") + print(" 2. Incremental - Review each table with end-of-session refinement") print() while True: @@ -63,9 +179,9 @@ def get_graph_modeling_mode() -> ModelingMode: return ModelingMode.AUTOMATIC # Default to automatic if choice == "1": - return ModelingMode.INTERACTIVE # Interactive + return ModelingMode.AUTOMATIC elif choice == "2": - return ModelingMode.AUTOMATIC # Automatic + return ModelingMode.INCREMENTAL else: print("Invalid choice. Please select 1-2.") except ValueError: @@ -110,6 +226,7 @@ def run_migration( memgraph_config: Dict[str, Any], modeling_mode: ModelingMode, graph_modeling_strategy: GraphModelingStrategy, + meta_graph_policy: str, ) -> Dict[str, Any]: """ Run the migration with the specified configuration. @@ -117,17 +234,19 @@ def run_migration( Args: source_db_config: Source database connection configuration memgraph_config: Memgraph connection configuration - modeling_mode: Graph modeling mode (interactive or automatic) - graph_modeling_strategy: Strategy for graph model creation + modeling_mode: Graph modeling mode (automatic or incremental) + graph_modeling_strategy: Strategy for graph model creation + meta_graph_policy: Meta graph handling policy (auto|skip|reset) Returns: Migration result dictionary """ print("🔧 Creating migration agent...") - mode_name = ( - "interactive" if modeling_mode == ModelingMode.INTERACTIVE else "automatic" - ) + if modeling_mode == ModelingMode.INCREMENTAL: + mode_name = "incremental" + else: + mode_name = "automatic" strategy_name = graph_modeling_strategy.value print(f"🎯 Graph modeling: {mode_name} with {strategy_name} strategy") print() @@ -136,6 +255,7 @@ def run_migration( agent = SQLToMemgraphAgent( modeling_mode=modeling_mode, graph_modeling_strategy=graph_modeling_strategy, + meta_graph_policy=meta_graph_policy, ) print("🚀 Starting migration workflow...") @@ -148,10 +268,10 @@ def run_migration( print(" 6. ✅ Verify the migration results") print() - # Handle interactive vs automatic mode - if modeling_mode == ModelingMode.INTERACTIVE: - print("🔄 Interactive mode: You'll be prompted to review and refine") - print(" the graph model") + # Handle incremental vs automatic mode + if modeling_mode == ModelingMode.INCREMENTAL: + print("🔄 Incremental mode: Review LLM-generated graph changes table by table") + print(" then approve or tweak differences before refining the model") print() # Run the migration with the user's chosen settings @@ -286,8 +406,12 @@ def print_migration_results(result: Dict[str, Any]) -> None: print("=" * 60) -def main() -> None: +def main(argv: Optional[list[str]] = None) -> None: """Main entry point for the migration agent.""" + args = parse_cli_args(argv) + + _configure_log_level(args.log_level) + print_banner() try: @@ -304,12 +428,26 @@ def main() -> None: print() # Get user preferences - graph_interactive = get_graph_modeling_mode() - graph_strategy = get_graph_modeling_strategy() + graph_mode = _resolve_mode(args.mode) or get_graph_modeling_mode() + graph_strategy = ( + _resolve_strategy(args.strategy) or get_graph_modeling_strategy() + ) + + meta_graph_policy = (args.meta_graph or "auto").lower() + if meta_graph_policy not in META_GRAPH_POLICIES: + logger.warning( + "Unrecognised meta graph policy '%s'; defaulting to auto", + meta_graph_policy, + ) + meta_graph_policy = "auto" # Run migration result = run_migration( - source_db_config, memgraph_config, graph_interactive, graph_strategy + source_db_config, + memgraph_config, + graph_mode, + graph_strategy, + meta_graph_policy, ) # Display results diff --git a/integrations/agents/pyproject.toml b/agents/sql2memgraph/pyproject.toml similarity index 100% rename from integrations/agents/pyproject.toml rename to agents/sql2memgraph/pyproject.toml diff --git a/integrations/agents/query_generation/__init__.py b/agents/sql2memgraph/query_generation/__init__.py similarity index 100% rename from integrations/agents/query_generation/__init__.py rename to agents/sql2memgraph/query_generation/__init__.py diff --git a/integrations/agents/query_generation/cypher_generator.py b/agents/sql2memgraph/query_generation/cypher_generator.py similarity index 100% rename from integrations/agents/query_generation/cypher_generator.py rename to agents/sql2memgraph/query_generation/cypher_generator.py diff --git a/integrations/agents/query_generation/schema_utilities.py b/agents/sql2memgraph/query_generation/schema_utilities.py similarity index 100% rename from integrations/agents/query_generation/schema_utilities.py rename to agents/sql2memgraph/query_generation/schema_utilities.py diff --git a/integrations/agents/tests/__init__.py b/agents/sql2memgraph/tests/__init__.py similarity index 100% rename from integrations/agents/tests/__init__.py rename to agents/sql2memgraph/tests/__init__.py diff --git a/integrations/agents/tests/test_integration.py b/agents/sql2memgraph/tests/test_integration.py similarity index 100% rename from integrations/agents/tests/test_integration.py rename to agents/sql2memgraph/tests/test_integration.py diff --git a/integrations/agents/utils/__init__.py b/agents/sql2memgraph/utils/__init__.py similarity index 100% rename from integrations/agents/utils/__init__.py rename to agents/sql2memgraph/utils/__init__.py diff --git a/integrations/agents/utils/config.py b/agents/sql2memgraph/utils/config.py similarity index 100% rename from integrations/agents/utils/config.py rename to agents/sql2memgraph/utils/config.py diff --git a/integrations/agents/utils/environment.py b/agents/sql2memgraph/utils/environment.py similarity index 100% rename from integrations/agents/utils/environment.py rename to agents/sql2memgraph/utils/environment.py diff --git a/agents/sql2memgraph/uv.lock b/agents/sql2memgraph/uv.lock new file mode 100644 index 0000000..2b0deb0 --- /dev/null +++ b/agents/sql2memgraph/uv.lock @@ -0,0 +1,4131 @@ +version = 1 +revision = 1 +requires-python = ">=3.10" +resolution-markers = [ + "python_full_version >= '3.13'", + "python_full_version == '3.12.*'", + "python_full_version == '3.11.*'", + "python_full_version < '3.11'", +] + +[[package]] +name = "agents" +version = "0.1.0" +source = { editable = "." } +dependencies = [ + { name = "langchain" }, + { name = "langchain-core" }, + { name = "langchain-openai" }, + { name = "langgraph" }, + { name = "memgraph-toolbox" }, + { name = "mysql-connector-python" }, + { name = "neo4j" }, + { name = "openai" }, + { name = "pydantic" }, + { name = "pymysql" }, + { name = "python-dotenv" }, + { name = "sqlalchemy" }, +] + +[package.dev-dependencies] +dev = [ + { name = "pytest" }, +] + +[package.metadata] +requires-dist = [ + { name = "langchain", specifier = ">=0.3.0" }, + { name = "langchain-core", specifier = ">=0.3.0" }, + { name = "langchain-openai", specifier = ">=0.2.0" }, + { name = "langgraph", specifier = ">=0.2.0" }, + { name = "memgraph-toolbox", specifier = ">=0.1.4" }, + { name = "mysql-connector-python", specifier = ">=9.0.0" }, + { name = "neo4j", specifier = ">=5.0.0" }, + { name = "openai", specifier = ">=1.0.0" }, + { name = "pydantic", specifier = ">=2.0.0" }, + { name = "pymysql", specifier = ">=1.1.0" }, + { name = "python-dotenv", specifier = ">=1.0.0" }, + { name = "sqlalchemy", specifier = ">=2.0.0" }, +] + +[package.metadata.requires-dev] +dev = [{ name = "pytest", specifier = ">=8.3.5" }] + +[[package]] +name = "aiohappyeyeballs" +version = "2.6.1" +source = { registry = 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