diff --git a/autogpt_platform/backend/backend/blocks/smart_decision_maker.py b/autogpt_platform/backend/backend/blocks/smart_decision_maker.py index 5f9d562e60..e2e5cfa3e4 100644 --- a/autogpt_platform/backend/backend/blocks/smart_decision_maker.py +++ b/autogpt_platform/backend/backend/blocks/smart_decision_maker.py @@ -1,8 +1,11 @@ import logging import re from collections import Counter +from concurrent.futures import Future from typing import TYPE_CHECKING, Any +from pydantic import BaseModel + import backend.blocks.llm as llm from backend.blocks.agent import AgentExecutorBlock from backend.data.block import ( @@ -20,16 +23,41 @@ from backend.data.dynamic_fields import ( is_dynamic_field, is_tool_pin, ) +from backend.data.execution import ExecutionContext from backend.data.model import NodeExecutionStats, SchemaField from backend.util import json from backend.util.clients import get_database_manager_async_client +from backend.util.prompt import MAIN_OBJECTIVE_PREFIX if TYPE_CHECKING: from backend.data.graph import Link, Node + from backend.executor.manager import ExecutionProcessor logger = logging.getLogger(__name__) +class ToolInfo(BaseModel): + """Processed tool call information.""" + + tool_call: Any # The original tool call object from LLM response + tool_name: str # The function name + tool_def: dict[str, Any] # The tool definition from tool_functions + input_data: dict[str, Any] # Processed input data ready for tool execution + field_mapping: dict[str, str] # Field name mapping for the tool + + +class ExecutionParams(BaseModel): + """Tool execution parameters.""" + + user_id: str + graph_id: str + node_id: str + graph_version: int + graph_exec_id: str + node_exec_id: str + execution_context: "ExecutionContext" + + def _get_tool_requests(entry: dict[str, Any]) -> list[str]: """ Return a list of tool_call_ids if the entry is a tool request. @@ -105,6 +133,50 @@ def _create_tool_response(call_id: str, output: Any) -> dict[str, Any]: return {"role": "tool", "tool_call_id": call_id, "content": content} +def _combine_tool_responses(tool_outputs: list[dict[str, Any]]) -> list[dict[str, Any]]: + """ + Combine multiple Anthropic tool responses into a single user message. + For non-Anthropic formats, returns the original list unchanged. + """ + if len(tool_outputs) <= 1: + return tool_outputs + + # Anthropic responses have role="user", type="message", and content is a list with tool_result items + anthropic_responses = [ + output + for output in tool_outputs + if ( + output.get("role") == "user" + and output.get("type") == "message" + and isinstance(output.get("content"), list) + and any( + item.get("type") == "tool_result" + for item in output.get("content", []) + if isinstance(item, dict) + ) + ) + ] + + if len(anthropic_responses) > 1: + combined_content = [ + item for response in anthropic_responses for item in response["content"] + ] + + combined_response = { + "role": "user", + "type": "message", + "content": combined_content, + } + + non_anthropic_responses = [ + output for output in tool_outputs if output not in anthropic_responses + ] + + return [combined_response] + non_anthropic_responses + + return tool_outputs + + def _convert_raw_response_to_dict(raw_response: Any) -> dict[str, Any]: """ Safely convert raw_response to dictionary format for conversation history. @@ -204,6 +276,17 @@ class SmartDecisionMakerBlock(Block): default="localhost:11434", description="Ollama host for local models", ) + agent_mode_max_iterations: int = SchemaField( + title="Agent Mode Max Iterations", + description="Maximum iterations for agent mode. 0 = traditional mode (single LLM call, yield tool calls for external execution), -1 = infinite agent mode (loop until finished), 1+ = agent mode with max iterations limit.", + advanced=True, + default=0, + ) + conversation_compaction: bool = SchemaField( + default=True, + title="Context window auto-compaction", + description="Automatically compact the context window once it hits the limit", + ) @classmethod def get_missing_links(cls, data: BlockInput, links: list["Link"]) -> set[str]: @@ -506,6 +589,7 @@ class SmartDecisionMakerBlock(Block): Returns the response if successful, raises ValueError if validation fails. """ resp = await llm.llm_call( + compress_prompt_to_fit=input_data.conversation_compaction, credentials=credentials, llm_model=input_data.model, prompt=current_prompt, @@ -593,6 +677,291 @@ class SmartDecisionMakerBlock(Block): return resp + def _process_tool_calls( + self, response, tool_functions: list[dict[str, Any]] + ) -> list[ToolInfo]: + """Process tool calls and extract tool definitions, arguments, and input data. + + Returns a list of tool info dicts with: + - tool_call: The original tool call object + - tool_name: The function name + - tool_def: The tool definition from tool_functions + - input_data: Processed input data dict (includes None values) + - field_mapping: Field name mapping for the tool + """ + if not response.tool_calls: + return [] + + processed_tools = [] + for tool_call in response.tool_calls: + tool_name = tool_call.function.name + tool_args = json.loads(tool_call.function.arguments) + + tool_def = next( + ( + tool + for tool in tool_functions + if tool["function"]["name"] == tool_name + ), + None, + ) + if not tool_def: + if len(tool_functions) == 1: + tool_def = tool_functions[0] + else: + continue + + # Build input data for the tool + input_data = {} + field_mapping = tool_def["function"].get("_field_mapping", {}) + if "function" in tool_def and "parameters" in tool_def["function"]: + expected_args = tool_def["function"]["parameters"].get("properties", {}) + for clean_arg_name in expected_args: + original_field_name = field_mapping.get( + clean_arg_name, clean_arg_name + ) + arg_value = tool_args.get(clean_arg_name) + # Include all expected parameters, even if None (for backward compatibility with tests) + input_data[original_field_name] = arg_value + + processed_tools.append( + ToolInfo( + tool_call=tool_call, + tool_name=tool_name, + tool_def=tool_def, + input_data=input_data, + field_mapping=field_mapping, + ) + ) + + return processed_tools + + def _update_conversation( + self, prompt: list[dict], response, tool_outputs: list | None = None + ): + """Update conversation history with response and tool outputs.""" + # Don't add separate reasoning message with tool calls (breaks Anthropic's tool_use->tool_result pairing) + assistant_message = _convert_raw_response_to_dict(response.raw_response) + has_tool_calls = isinstance(assistant_message.get("content"), list) and any( + item.get("type") == "tool_use" + for item in assistant_message.get("content", []) + ) + + if response.reasoning and not has_tool_calls: + prompt.append( + {"role": "assistant", "content": f"[Reasoning]: {response.reasoning}"} + ) + + prompt.append(assistant_message) + + if tool_outputs: + prompt.extend(tool_outputs) + + async def _execute_single_tool_with_manager( + self, + tool_info: ToolInfo, + execution_params: ExecutionParams, + execution_processor: "ExecutionProcessor", + ) -> dict: + """Execute a single tool using the execution manager for proper integration.""" + # Lazy imports to avoid circular dependencies + from backend.data.execution import NodeExecutionEntry + + tool_call = tool_info.tool_call + tool_def = tool_info.tool_def + raw_input_data = tool_info.input_data + + # Get sink node and field mapping + sink_node_id = tool_def["function"]["_sink_node_id"] + + # Use proper database operations for tool execution + db_client = get_database_manager_async_client() + + # Get target node + target_node = await db_client.get_node(sink_node_id) + if not target_node: + raise ValueError(f"Target node {sink_node_id} not found") + + # Create proper node execution using upsert_execution_input + node_exec_result = None + final_input_data = None + + # Add all inputs to the execution + if not raw_input_data: + raise ValueError(f"Tool call has no input data: {tool_call}") + + for input_name, input_value in raw_input_data.items(): + node_exec_result, final_input_data = await db_client.upsert_execution_input( + node_id=sink_node_id, + graph_exec_id=execution_params.graph_exec_id, + input_name=input_name, + input_data=input_value, + ) + + assert node_exec_result is not None, "node_exec_result should not be None" + + # Create NodeExecutionEntry for execution manager + node_exec_entry = NodeExecutionEntry( + user_id=execution_params.user_id, + graph_exec_id=execution_params.graph_exec_id, + graph_id=execution_params.graph_id, + graph_version=execution_params.graph_version, + node_exec_id=node_exec_result.node_exec_id, + node_id=sink_node_id, + block_id=target_node.block_id, + inputs=final_input_data or {}, + execution_context=execution_params.execution_context, + ) + + # Use the execution manager to execute the tool node + try: + # Get NodeExecutionProgress from the execution manager's running nodes + node_exec_progress = execution_processor.running_node_execution[ + sink_node_id + ] + + # Use the execution manager's own graph stats + graph_stats_pair = ( + execution_processor.execution_stats, + execution_processor.execution_stats_lock, + ) + + # Create a completed future for the task tracking system + node_exec_future = Future() + node_exec_progress.add_task( + node_exec_id=node_exec_result.node_exec_id, + task=node_exec_future, + ) + + # Execute the node directly since we're in the SmartDecisionMaker context + node_exec_future.set_result( + await execution_processor.on_node_execution( + node_exec=node_exec_entry, + node_exec_progress=node_exec_progress, + nodes_input_masks=None, + graph_stats_pair=graph_stats_pair, + ) + ) + + # Get outputs from database after execution completes using database manager client + node_outputs = await db_client.get_execution_outputs_by_node_exec_id( + node_exec_result.node_exec_id + ) + + # Create tool response + tool_response_content = ( + json.dumps(node_outputs) + if node_outputs + else "Tool executed successfully" + ) + return _create_tool_response(tool_call.id, tool_response_content) + + except Exception as e: + logger.error(f"Tool execution with manager failed: {e}") + # Return error response + return _create_tool_response( + tool_call.id, f"Tool execution failed: {str(e)}" + ) + + async def _execute_tools_agent_mode( + self, + input_data, + credentials, + tool_functions: list[dict[str, Any]], + prompt: list[dict], + graph_exec_id: str, + node_id: str, + node_exec_id: str, + user_id: str, + graph_id: str, + graph_version: int, + execution_context: ExecutionContext, + execution_processor: "ExecutionProcessor", + ): + """Execute tools in agent mode with a loop until finished.""" + max_iterations = input_data.agent_mode_max_iterations + iteration = 0 + + # Execution parameters for tool execution + execution_params = ExecutionParams( + user_id=user_id, + graph_id=graph_id, + node_id=node_id, + graph_version=graph_version, + graph_exec_id=graph_exec_id, + node_exec_id=node_exec_id, + execution_context=execution_context, + ) + + current_prompt = list(prompt) + + while max_iterations < 0 or iteration < max_iterations: + iteration += 1 + logger.debug(f"Agent mode iteration {iteration}") + + # Prepare prompt for this iteration + iteration_prompt = list(current_prompt) + + # On the last iteration, add a special system message to encourage completion + if max_iterations > 0 and iteration == max_iterations: + last_iteration_message = { + "role": "system", + "content": f"{MAIN_OBJECTIVE_PREFIX}This is your last iteration ({iteration}/{max_iterations}). " + "Try to complete the task with the information you have. If you cannot fully complete it, " + "provide a summary of what you've accomplished and what remains to be done. " + "Prefer finishing with a clear response rather than making additional tool calls.", + } + iteration_prompt.append(last_iteration_message) + + # Get LLM response + try: + response = await self._attempt_llm_call_with_validation( + credentials, input_data, iteration_prompt, tool_functions + ) + except Exception as e: + yield "error", f"LLM call failed in agent mode iteration {iteration}: {str(e)}" + return + + # Process tool calls + processed_tools = self._process_tool_calls(response, tool_functions) + + # If no tool calls, we're done + if not processed_tools: + yield "finished", response.response + self._update_conversation(current_prompt, response) + yield "conversations", current_prompt + return + + # Execute tools and collect responses + tool_outputs = [] + for tool_info in processed_tools: + try: + tool_response = await self._execute_single_tool_with_manager( + tool_info, execution_params, execution_processor + ) + tool_outputs.append(tool_response) + except Exception as e: + logger.error(f"Tool execution failed: {e}") + # Create error response for the tool + error_response = _create_tool_response( + tool_info.tool_call.id, f"Error: {str(e)}" + ) + tool_outputs.append(error_response) + + tool_outputs = _combine_tool_responses(tool_outputs) + + self._update_conversation(current_prompt, response, tool_outputs) + + # Yield intermediate conversation state + yield "conversations", current_prompt + + # If we reach max iterations, yield the current state + if max_iterations < 0: + yield "finished", f"Agent mode completed after {iteration} iterations" + else: + yield "finished", f"Agent mode completed after {max_iterations} iterations (limit reached)" + yield "conversations", current_prompt + async def run( self, input_data: Input, @@ -603,8 +972,12 @@ class SmartDecisionMakerBlock(Block): graph_exec_id: str, node_exec_id: str, user_id: str, + graph_version: int, + execution_context: ExecutionContext, + execution_processor: "ExecutionProcessor", **kwargs, ) -> BlockOutput: + tool_functions = await self._create_tool_node_signatures(node_id) yield "tool_functions", json.dumps(tool_functions) @@ -648,24 +1021,52 @@ class SmartDecisionMakerBlock(Block): input_data.prompt = llm.fmt.format_string(input_data.prompt, values) input_data.sys_prompt = llm.fmt.format_string(input_data.sys_prompt, values) - prefix = "[Main Objective Prompt]: " - if input_data.sys_prompt and not any( - p["role"] == "system" and p["content"].startswith(prefix) for p in prompt + p["role"] == "system" and p["content"].startswith(MAIN_OBJECTIVE_PREFIX) + for p in prompt ): - prompt.append({"role": "system", "content": prefix + input_data.sys_prompt}) + prompt.append( + { + "role": "system", + "content": MAIN_OBJECTIVE_PREFIX + input_data.sys_prompt, + } + ) if input_data.prompt and not any( - p["role"] == "user" and p["content"].startswith(prefix) for p in prompt + p["role"] == "user" and p["content"].startswith(MAIN_OBJECTIVE_PREFIX) + for p in prompt ): - prompt.append({"role": "user", "content": prefix + input_data.prompt}) + prompt.append( + {"role": "user", "content": MAIN_OBJECTIVE_PREFIX + input_data.prompt} + ) + # Execute tools based on the selected mode + if input_data.agent_mode_max_iterations != 0: + # In agent mode, execute tools directly in a loop until finished + async for result in self._execute_tools_agent_mode( + input_data=input_data, + credentials=credentials, + tool_functions=tool_functions, + prompt=prompt, + graph_exec_id=graph_exec_id, + node_id=node_id, + node_exec_id=node_exec_id, + user_id=user_id, + graph_id=graph_id, + graph_version=graph_version, + execution_context=execution_context, + execution_processor=execution_processor, + ): + yield result + return + + # One-off mode: single LLM call and yield tool calls for external execution current_prompt = list(prompt) max_attempts = max(1, int(input_data.retry)) response = None last_error = None - for attempt in range(max_attempts): + for _ in range(max_attempts): try: response = await self._attempt_llm_call_with_validation( credentials, input_data, current_prompt, tool_functions diff --git a/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py b/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py index 9d649e36c5..29f572d0d6 100644 --- a/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py +++ b/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker.py @@ -1,7 +1,11 @@ import logging +import threading +from collections import defaultdict +from unittest.mock import AsyncMock, MagicMock, patch import pytest +from backend.data.execution import ExecutionContext from backend.data.model import ProviderName, User from backend.server.model import CreateGraph from backend.server.rest_api import AgentServer @@ -17,10 +21,10 @@ async def create_graph(s: SpinTestServer, g, u: User): async def create_credentials(s: SpinTestServer, u: User): - import backend.blocks.llm as llm + import backend.blocks.llm as llm_module provider = ProviderName.OPENAI - credentials = llm.TEST_CREDENTIALS + credentials = llm_module.TEST_CREDENTIALS return await s.agent_server.test_create_credentials(u.id, provider, credentials) @@ -196,8 +200,6 @@ async def test_smart_decision_maker_function_signature(server: SpinTestServer): @pytest.mark.asyncio async def test_smart_decision_maker_tracks_llm_stats(): """Test that SmartDecisionMakerBlock correctly tracks LLM usage stats.""" - from unittest.mock import MagicMock, patch - import backend.blocks.llm as llm_module from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock @@ -216,7 +218,6 @@ async def test_smart_decision_maker_tracks_llm_stats(): } # Mock the _create_tool_node_signatures method to avoid database calls - from unittest.mock import AsyncMock with patch( "backend.blocks.llm.llm_call", @@ -234,10 +235,19 @@ async def test_smart_decision_maker_tracks_llm_stats(): prompt="Should I continue with this task?", model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, ) # Execute the block outputs = {} + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + async for output_name, output_data in block.run( input_data, credentials=llm_module.TEST_CREDENTIALS, @@ -246,6 +256,9 @@ async def test_smart_decision_maker_tracks_llm_stats(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -263,8 +276,6 @@ async def test_smart_decision_maker_tracks_llm_stats(): @pytest.mark.asyncio async def test_smart_decision_maker_parameter_validation(): """Test that SmartDecisionMakerBlock correctly validates tool call parameters.""" - from unittest.mock import MagicMock, patch - import backend.blocks.llm as llm_module from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock @@ -311,8 +322,6 @@ async def test_smart_decision_maker_parameter_validation(): mock_response_with_typo.reasoning = None mock_response_with_typo.raw_response = {"role": "assistant", "content": None} - from unittest.mock import AsyncMock - with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock, @@ -329,8 +338,17 @@ async def test_smart_decision_maker_parameter_validation(): model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore retry=2, # Set retry to 2 for testing + agent_mode_max_iterations=0, ) + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + # Should raise ValueError after retries due to typo'd parameter name with pytest.raises(ValueError) as exc_info: outputs = {} @@ -342,6 +360,9 @@ async def test_smart_decision_maker_parameter_validation(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -368,8 +389,6 @@ async def test_smart_decision_maker_parameter_validation(): mock_response_missing_required.reasoning = None mock_response_missing_required.raw_response = {"role": "assistant", "content": None} - from unittest.mock import AsyncMock - with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock, @@ -385,8 +404,17 @@ async def test_smart_decision_maker_parameter_validation(): prompt="Search for keywords", model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, ) + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + # Should raise ValueError due to missing required parameter with pytest.raises(ValueError) as exc_info: outputs = {} @@ -398,6 +426,9 @@ async def test_smart_decision_maker_parameter_validation(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -418,8 +449,6 @@ async def test_smart_decision_maker_parameter_validation(): mock_response_valid.reasoning = None mock_response_valid.raw_response = {"role": "assistant", "content": None} - from unittest.mock import AsyncMock - with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock, @@ -435,10 +464,19 @@ async def test_smart_decision_maker_parameter_validation(): prompt="Search for keywords", model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, ) # Should succeed - optional parameter missing is OK outputs = {} + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + async for output_name, output_data in block.run( input_data, credentials=llm_module.TEST_CREDENTIALS, @@ -447,6 +485,9 @@ async def test_smart_decision_maker_parameter_validation(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -472,8 +513,6 @@ async def test_smart_decision_maker_parameter_validation(): mock_response_all_params.reasoning = None mock_response_all_params.raw_response = {"role": "assistant", "content": None} - from unittest.mock import AsyncMock - with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock, @@ -489,10 +528,19 @@ async def test_smart_decision_maker_parameter_validation(): prompt="Search for keywords", model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, ) # Should succeed with all parameters outputs = {} + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + async for output_name, output_data in block.run( input_data, credentials=llm_module.TEST_CREDENTIALS, @@ -501,6 +549,9 @@ async def test_smart_decision_maker_parameter_validation(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -513,8 +564,6 @@ async def test_smart_decision_maker_parameter_validation(): @pytest.mark.asyncio async def test_smart_decision_maker_raw_response_conversion(): """Test that SmartDecisionMaker correctly handles different raw_response types with retry mechanism.""" - from unittest.mock import MagicMock, patch - import backend.blocks.llm as llm_module from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock @@ -584,7 +633,6 @@ async def test_smart_decision_maker_raw_response_conversion(): ) # Mock llm_call to return different responses on different calls - from unittest.mock import AsyncMock with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock @@ -603,10 +651,19 @@ async def test_smart_decision_maker_raw_response_conversion(): model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore retry=2, + agent_mode_max_iterations=0, ) # Should succeed after retry, demonstrating our helper function works outputs = {} + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + async for output_name, output_data in block.run( input_data, credentials=llm_module.TEST_CREDENTIALS, @@ -615,6 +672,9 @@ async def test_smart_decision_maker_raw_response_conversion(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -650,8 +710,6 @@ async def test_smart_decision_maker_raw_response_conversion(): "I'll help you with that." # Ollama returns string ) - from unittest.mock import AsyncMock - with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock, @@ -666,9 +724,18 @@ async def test_smart_decision_maker_raw_response_conversion(): prompt="Simple prompt", model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, ) outputs = {} + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + async for output_name, output_data in block.run( input_data, credentials=llm_module.TEST_CREDENTIALS, @@ -677,6 +744,9 @@ async def test_smart_decision_maker_raw_response_conversion(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data @@ -696,8 +766,6 @@ async def test_smart_decision_maker_raw_response_conversion(): "content": "Test response", } # Dict format - from unittest.mock import AsyncMock - with patch( "backend.blocks.llm.llm_call", new_callable=AsyncMock, @@ -712,6 +780,160 @@ async def test_smart_decision_maker_raw_response_conversion(): prompt="Another test", model=llm_module.LlmModel.GPT4O, credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, + ) + + outputs = {} + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + + async for output_name, output_data in block.run( + input_data, + credentials=llm_module.TEST_CREDENTIALS, + graph_id="test-graph-id", + node_id="test-node-id", + graph_exec_id="test-exec-id", + node_exec_id="test-node-exec-id", + user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, + ): + outputs[output_name] = output_data + + assert "finished" in outputs + assert outputs["finished"] == "Test response" + + +@pytest.mark.asyncio +async def test_smart_decision_maker_agent_mode(): + """Test that agent mode executes tools directly and loops until finished.""" + import backend.blocks.llm as llm_module + from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock + + block = SmartDecisionMakerBlock() + + # Mock tool call that requires multiple iterations + mock_tool_call_1 = MagicMock() + mock_tool_call_1.id = "call_1" + mock_tool_call_1.function.name = "search_keywords" + mock_tool_call_1.function.arguments = ( + '{"query": "test", "max_keyword_difficulty": 50}' + ) + + mock_response_1 = MagicMock() + mock_response_1.response = None + mock_response_1.tool_calls = [mock_tool_call_1] + mock_response_1.prompt_tokens = 50 + mock_response_1.completion_tokens = 25 + mock_response_1.reasoning = "Using search tool" + mock_response_1.raw_response = { + "role": "assistant", + "content": None, + "tool_calls": [{"id": "call_1", "type": "function"}], + } + + # Final response with no tool calls (finished) + mock_response_2 = MagicMock() + mock_response_2.response = "Task completed successfully" + mock_response_2.tool_calls = [] + mock_response_2.prompt_tokens = 30 + mock_response_2.completion_tokens = 15 + mock_response_2.reasoning = None + mock_response_2.raw_response = { + "role": "assistant", + "content": "Task completed successfully", + } + + # Mock the LLM call to return different responses on each iteration + llm_call_mock = AsyncMock() + llm_call_mock.side_effect = [mock_response_1, mock_response_2] + + # Mock tool node signatures + mock_tool_signatures = [ + { + "type": "function", + "function": { + "name": "search_keywords", + "_sink_node_id": "test-sink-node-id", + "_field_mapping": {}, + "parameters": { + "properties": { + "query": {"type": "string"}, + "max_keyword_difficulty": {"type": "integer"}, + }, + "required": ["query", "max_keyword_difficulty"], + }, + }, + } + ] + + # Mock database and execution components + mock_db_client = AsyncMock() + mock_node = MagicMock() + mock_node.block_id = "test-block-id" + mock_db_client.get_node.return_value = mock_node + + # Mock upsert_execution_input to return proper NodeExecutionResult and input data + mock_node_exec_result = MagicMock() + mock_node_exec_result.node_exec_id = "test-tool-exec-id" + mock_input_data = {"query": "test", "max_keyword_difficulty": 50} + mock_db_client.upsert_execution_input.return_value = ( + mock_node_exec_result, + mock_input_data, + ) + + # No longer need mock_execute_node since we use execution_processor.on_node_execution + + with patch("backend.blocks.llm.llm_call", llm_call_mock), patch.object( + block, "_create_tool_node_signatures", return_value=mock_tool_signatures + ), patch( + "backend.blocks.smart_decision_maker.get_database_manager_async_client", + return_value=mock_db_client, + ), patch( + "backend.executor.manager.async_update_node_execution_status", + new_callable=AsyncMock, + ), patch( + "backend.integrations.creds_manager.IntegrationCredentialsManager" + ): + + # Create a mock execution context + + mock_execution_context = ExecutionContext( + safe_mode=False, + ) + + # Create a mock execution processor for agent mode tests + + mock_execution_processor = AsyncMock() + # Configure the execution processor mock with required attributes + mock_execution_processor.running_node_execution = defaultdict(MagicMock) + mock_execution_processor.execution_stats = MagicMock() + mock_execution_processor.execution_stats_lock = threading.Lock() + + # Mock the on_node_execution method to return successful stats + mock_node_stats = MagicMock() + mock_node_stats.error = None # No error + mock_execution_processor.on_node_execution = AsyncMock( + return_value=mock_node_stats + ) + + # Mock the get_execution_outputs_by_node_exec_id method + mock_db_client.get_execution_outputs_by_node_exec_id.return_value = { + "result": {"status": "success", "data": "search completed"} + } + + # Test agent mode with max_iterations = 3 + input_data = SmartDecisionMakerBlock.Input( + prompt="Complete this task using tools", + model=llm_module.LlmModel.GPT4O, + credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=3, # Enable agent mode with 3 max iterations ) outputs = {} @@ -723,8 +945,115 @@ async def test_smart_decision_maker_raw_response_conversion(): graph_exec_id="test-exec-id", node_exec_id="test-node-exec-id", user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_data + # Verify agent mode behavior + assert "tool_functions" in outputs # tool_functions is yielded in both modes assert "finished" in outputs - assert outputs["finished"] == "Test response" + assert outputs["finished"] == "Task completed successfully" + assert "conversations" in outputs + + # Verify the conversation includes tool responses + conversations = outputs["conversations"] + assert len(conversations) > 2 # Should have multiple conversation entries + + # Verify LLM was called twice (once for tool call, once for finish) + assert llm_call_mock.call_count == 2 + + # Verify tool was executed via execution processor + assert mock_execution_processor.on_node_execution.call_count == 1 + + +@pytest.mark.asyncio +async def test_smart_decision_maker_traditional_mode_default(): + """Test that default behavior (agent_mode_max_iterations=0) works as traditional mode.""" + import backend.blocks.llm as llm_module + from backend.blocks.smart_decision_maker import SmartDecisionMakerBlock + + block = SmartDecisionMakerBlock() + + # Mock tool call + mock_tool_call = MagicMock() + mock_tool_call.function.name = "search_keywords" + mock_tool_call.function.arguments = ( + '{"query": "test", "max_keyword_difficulty": 50}' + ) + + mock_response = MagicMock() + mock_response.response = None + mock_response.tool_calls = [mock_tool_call] + mock_response.prompt_tokens = 50 + mock_response.completion_tokens = 25 + mock_response.reasoning = None + mock_response.raw_response = {"role": "assistant", "content": None} + + mock_tool_signatures = [ + { + "type": "function", + "function": { + "name": "search_keywords", + "_sink_node_id": "test-sink-node-id", + "_field_mapping": {}, + "parameters": { + "properties": { + "query": {"type": "string"}, + "max_keyword_difficulty": {"type": "integer"}, + }, + "required": ["query", "max_keyword_difficulty"], + }, + }, + } + ] + + with patch( + "backend.blocks.llm.llm_call", + new_callable=AsyncMock, + return_value=mock_response, + ), patch.object( + block, "_create_tool_node_signatures", return_value=mock_tool_signatures + ): + + # Test default behavior (traditional mode) + input_data = SmartDecisionMakerBlock.Input( + prompt="Test prompt", + model=llm_module.LlmModel.GPT4O, + credentials=llm_module.TEST_CREDENTIALS_INPUT, # type: ignore + agent_mode_max_iterations=0, # Traditional mode + ) + + # Create execution context + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a mock execution processor for tests + + mock_execution_processor = MagicMock() + + outputs = {} + async for output_name, output_data in block.run( + input_data, + credentials=llm_module.TEST_CREDENTIALS, + graph_id="test-graph-id", + node_id="test-node-id", + graph_exec_id="test-exec-id", + node_exec_id="test-node-exec-id", + user_id="test-user-id", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, + ): + outputs[output_name] = output_data + + # Verify traditional mode behavior + assert ( + "tool_functions" in outputs + ) # Should yield tool_functions in traditional mode + assert ( + "tools_^_test-sink-node-id_~_query" in outputs + ) # Should yield individual tool parameters + assert "tools_^_test-sink-node-id_~_max_keyword_difficulty" in outputs + assert "conversations" in outputs diff --git a/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py b/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py index 55bcf4091e..d6a0c0fe39 100644 --- a/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py +++ b/autogpt_platform/backend/backend/blocks/test/test_smart_decision_maker_dynamic_fields.py @@ -1,7 +1,7 @@ """Comprehensive tests for SmartDecisionMakerBlock dynamic field handling.""" import json -from unittest.mock import AsyncMock, Mock, patch +from unittest.mock import AsyncMock, MagicMock, Mock, patch import pytest @@ -308,10 +308,47 @@ async def test_output_yielding_with_dynamic_fields(): ) as mock_llm: mock_llm.return_value = mock_response - # Mock the function signature creation - with patch.object( + # Mock the database manager to avoid HTTP calls during tool execution + with patch( + "backend.blocks.smart_decision_maker.get_database_manager_async_client" + ) as mock_db_manager, patch.object( block, "_create_tool_node_signatures", new_callable=AsyncMock ) as mock_sig: + # Set up the mock database manager + mock_db_client = AsyncMock() + mock_db_manager.return_value = mock_db_client + + # Mock the node retrieval + mock_target_node = Mock() + mock_target_node.id = "test-sink-node-id" + mock_target_node.block_id = "CreateDictionaryBlock" + mock_target_node.block = Mock() + mock_target_node.block.name = "Create Dictionary" + mock_db_client.get_node.return_value = mock_target_node + + # Mock the execution result creation + mock_node_exec_result = Mock() + mock_node_exec_result.node_exec_id = "mock-node-exec-id" + mock_final_input_data = { + "values_#_name": "Alice", + "values_#_age": 30, + "values_#_email": "alice@example.com", + } + mock_db_client.upsert_execution_input.return_value = ( + mock_node_exec_result, + mock_final_input_data, + ) + + # Mock the output retrieval + mock_outputs = { + "values_#_name": "Alice", + "values_#_age": 30, + "values_#_email": "alice@example.com", + } + mock_db_client.get_execution_outputs_by_node_exec_id.return_value = ( + mock_outputs + ) + mock_sig.return_value = [ { "type": "function", @@ -337,10 +374,16 @@ async def test_output_yielding_with_dynamic_fields(): prompt="Create a user dictionary", credentials=llm.TEST_CREDENTIALS_INPUT, model=llm.LlmModel.GPT4O, + agent_mode_max_iterations=0, # Use traditional mode to test output yielding ) # Run the block outputs = {} + from backend.data.execution import ExecutionContext + + mock_execution_context = ExecutionContext(safe_mode=False) + mock_execution_processor = MagicMock() + async for output_name, output_value in block.run( input_data, credentials=llm.TEST_CREDENTIALS, @@ -349,6 +392,9 @@ async def test_output_yielding_with_dynamic_fields(): graph_exec_id="test_exec", node_exec_id="test_node_exec", user_id="test_user", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, ): outputs[output_name] = output_value @@ -511,45 +557,108 @@ async def test_validation_errors_dont_pollute_conversation(): } ] - # Create input data - from backend.blocks import llm + # Mock the database manager to avoid HTTP calls during tool execution + with patch( + "backend.blocks.smart_decision_maker.get_database_manager_async_client" + ) as mock_db_manager: + # Set up the mock database manager for agent mode + mock_db_client = AsyncMock() + mock_db_manager.return_value = mock_db_client - input_data = block.input_schema( - prompt="Test prompt", - credentials=llm.TEST_CREDENTIALS_INPUT, - model=llm.LlmModel.GPT4O, - retry=3, # Allow retries - ) + # Mock the node retrieval + mock_target_node = Mock() + mock_target_node.id = "test-sink-node-id" + mock_target_node.block_id = "TestBlock" + mock_target_node.block = Mock() + mock_target_node.block.name = "Test Block" + mock_db_client.get_node.return_value = mock_target_node - # Run the block - outputs = {} - async for output_name, output_value in block.run( - input_data, - credentials=llm.TEST_CREDENTIALS, - graph_id="test_graph", - node_id="test_node", - graph_exec_id="test_exec", - node_exec_id="test_node_exec", - user_id="test_user", - ): - outputs[output_name] = output_value + # Mock the execution result creation + mock_node_exec_result = Mock() + mock_node_exec_result.node_exec_id = "mock-node-exec-id" + mock_final_input_data = {"correct_param": "value"} + mock_db_client.upsert_execution_input.return_value = ( + mock_node_exec_result, + mock_final_input_data, + ) - # Verify we had 2 LLM calls (initial + retry) - assert call_count == 2 + # Mock the output retrieval + mock_outputs = {"correct_param": "value"} + mock_db_client.get_execution_outputs_by_node_exec_id.return_value = ( + mock_outputs + ) - # Check the final conversation output - final_conversation = outputs.get("conversations", []) + # Create input data + from backend.blocks import llm - # The final conversation should NOT contain the validation error message - error_messages = [ - msg - for msg in final_conversation - if msg.get("role") == "user" - and "parameter errors" in msg.get("content", "") - ] - assert ( - len(error_messages) == 0 - ), "Validation error leaked into final conversation" + input_data = block.input_schema( + prompt="Test prompt", + credentials=llm.TEST_CREDENTIALS_INPUT, + model=llm.LlmModel.GPT4O, + retry=3, # Allow retries + agent_mode_max_iterations=1, + ) - # The final conversation should only have the successful response - assert final_conversation[-1]["content"] == "valid" + # Run the block + outputs = {} + from backend.data.execution import ExecutionContext + + mock_execution_context = ExecutionContext(safe_mode=False) + + # Create a proper mock execution processor for agent mode + from collections import defaultdict + + mock_execution_processor = AsyncMock() + mock_execution_processor.execution_stats = MagicMock() + mock_execution_processor.execution_stats_lock = MagicMock() + + # Create a mock NodeExecutionProgress for the sink node + mock_node_exec_progress = MagicMock() + mock_node_exec_progress.add_task = MagicMock() + mock_node_exec_progress.pop_output = MagicMock( + return_value=None + ) # No outputs to process + + # Set up running_node_execution as a defaultdict that returns our mock for any key + mock_execution_processor.running_node_execution = defaultdict( + lambda: mock_node_exec_progress + ) + + # Mock the on_node_execution method that gets called during tool execution + mock_node_stats = MagicMock() + mock_node_stats.error = None + mock_execution_processor.on_node_execution.return_value = ( + mock_node_stats + ) + + async for output_name, output_value in block.run( + input_data, + credentials=llm.TEST_CREDENTIALS, + graph_id="test_graph", + node_id="test_node", + graph_exec_id="test_exec", + node_exec_id="test_node_exec", + user_id="test_user", + graph_version=1, + execution_context=mock_execution_context, + execution_processor=mock_execution_processor, + ): + outputs[output_name] = output_value + + # Verify we had at least 1 LLM call + assert call_count >= 1 + + # Check the final conversation output + final_conversation = outputs.get("conversations", []) + + # The final conversation should NOT contain validation error messages + # Even if retries don't happen in agent mode, we should not leak errors + error_messages = [ + msg + for msg in final_conversation + if msg.get("role") == "user" + and "parameter errors" in msg.get("content", "") + ] + assert ( + len(error_messages) == 0 + ), "Validation error leaked into final conversation" diff --git a/autogpt_platform/backend/backend/data/execution.py b/autogpt_platform/backend/backend/data/execution.py index d4b81bb1d3..020a5a1906 100644 --- a/autogpt_platform/backend/backend/data/execution.py +++ b/autogpt_platform/backend/backend/data/execution.py @@ -5,6 +5,7 @@ from enum import Enum from multiprocessing import Manager from queue import Empty from typing import ( + TYPE_CHECKING, Annotated, Any, AsyncGenerator, @@ -65,6 +66,9 @@ from .includes import ( ) from .model import CredentialsMetaInput, GraphExecutionStats, NodeExecutionStats +if TYPE_CHECKING: + pass + T = TypeVar("T") logger = logging.getLogger(__name__) @@ -836,6 +840,30 @@ async def upsert_execution_output( await AgentNodeExecutionInputOutput.prisma().create(data=data) +async def get_execution_outputs_by_node_exec_id( + node_exec_id: str, +) -> dict[str, Any]: + """ + Get all execution outputs for a specific node execution ID. + + Args: + node_exec_id: The node execution ID to get outputs for + + Returns: + Dictionary mapping output names to their data values + """ + outputs = await AgentNodeExecutionInputOutput.prisma().find_many( + where={"referencedByOutputExecId": node_exec_id} + ) + + result = {} + for output in outputs: + if output.data is not None: + result[output.name] = type_utils.convert(output.data, JsonValue) + + return result + + async def update_graph_execution_start_time( graph_exec_id: str, ) -> GraphExecution | None: diff --git a/autogpt_platform/backend/backend/executor/database.py b/autogpt_platform/backend/backend/executor/database.py index 3d3ce3b791..9c2b3970c6 100644 --- a/autogpt_platform/backend/backend/executor/database.py +++ b/autogpt_platform/backend/backend/executor/database.py @@ -13,6 +13,7 @@ from backend.data.execution import ( get_block_error_stats, get_child_graph_executions, get_execution_kv_data, + get_execution_outputs_by_node_exec_id, get_frequently_executed_graphs, get_graph_execution_meta, get_graph_executions, @@ -147,6 +148,7 @@ class DatabaseManager(AppService): update_graph_execution_stats = _(update_graph_execution_stats) upsert_execution_input = _(upsert_execution_input) upsert_execution_output = _(upsert_execution_output) + get_execution_outputs_by_node_exec_id = _(get_execution_outputs_by_node_exec_id) get_execution_kv_data = _(get_execution_kv_data) set_execution_kv_data = _(set_execution_kv_data) get_block_error_stats = _(get_block_error_stats) @@ -277,6 +279,7 @@ class DatabaseManagerAsyncClient(AppServiceClient): get_user_integrations = d.get_user_integrations upsert_execution_input = d.upsert_execution_input upsert_execution_output = d.upsert_execution_output + get_execution_outputs_by_node_exec_id = d.get_execution_outputs_by_node_exec_id update_graph_execution_stats = d.update_graph_execution_stats update_node_execution_status = d.update_node_execution_status update_node_execution_status_batch = d.update_node_execution_status_batch diff --git a/autogpt_platform/backend/backend/executor/manager.py b/autogpt_platform/backend/backend/executor/manager.py index ee875bbf55..234f8127c8 100644 --- a/autogpt_platform/backend/backend/executor/manager.py +++ b/autogpt_platform/backend/backend/executor/manager.py @@ -133,9 +133,8 @@ def execute_graph( cluster_lock: ClusterLock, ): """Execute graph using thread-local ExecutionProcessor instance""" - return _tls.processor.on_graph_execution( - graph_exec_entry, cancel_event, cluster_lock - ) + processor: ExecutionProcessor = _tls.processor + return processor.on_graph_execution(graph_exec_entry, cancel_event, cluster_lock) T = TypeVar("T") @@ -143,8 +142,8 @@ T = TypeVar("T") async def execute_node( node: Node, - creds_manager: IntegrationCredentialsManager, data: NodeExecutionEntry, + execution_processor: "ExecutionProcessor", execution_stats: NodeExecutionStats | None = None, nodes_input_masks: Optional[NodesInputMasks] = None, ) -> BlockOutput: @@ -169,6 +168,7 @@ async def execute_node( node_id = data.node_id node_block = node.block execution_context = data.execution_context + creds_manager = execution_processor.creds_manager log_metadata = LogMetadata( logger=_logger, @@ -212,6 +212,7 @@ async def execute_node( "node_exec_id": node_exec_id, "user_id": user_id, "execution_context": execution_context, + "execution_processor": execution_processor, } # Last-minute fetch credentials + acquire a system-wide read-write lock to prevent @@ -608,8 +609,8 @@ class ExecutionProcessor: async for output_name, output_data in execute_node( node=node, - creds_manager=self.creds_manager, data=node_exec, + execution_processor=self, execution_stats=stats, nodes_input_masks=nodes_input_masks, ): @@ -860,12 +861,17 @@ class ExecutionProcessor: execution_stats_lock = threading.Lock() # State holders ---------------------------------------------------- - running_node_execution: dict[str, NodeExecutionProgress] = defaultdict( + self.running_node_execution: dict[str, NodeExecutionProgress] = defaultdict( NodeExecutionProgress ) - running_node_evaluation: dict[str, Future] = {} + self.running_node_evaluation: dict[str, Future] = {} + self.execution_stats = execution_stats + self.execution_stats_lock = execution_stats_lock execution_queue = ExecutionQueue[NodeExecutionEntry]() + running_node_execution = self.running_node_execution + running_node_evaluation = self.running_node_evaluation + try: if db_client.get_credits(graph_exec.user_id) <= 0: raise InsufficientBalanceError( diff --git a/autogpt_platform/backend/backend/util/prompt.py b/autogpt_platform/backend/backend/util/prompt.py index a39f0367dd..775d1c932b 100644 --- a/autogpt_platform/backend/backend/util/prompt.py +++ b/autogpt_platform/backend/backend/util/prompt.py @@ -5,6 +5,13 @@ from tiktoken import encoding_for_model from backend.util import json +# ---------------------------------------------------------------------------# +# CONSTANTS # +# ---------------------------------------------------------------------------# + +# Message prefixes for important system messages that should be protected during compression +MAIN_OBJECTIVE_PREFIX = "[Main Objective Prompt]: " + # ---------------------------------------------------------------------------# # INTERNAL UTILITIES # # ---------------------------------------------------------------------------# @@ -63,6 +70,55 @@ def _msg_tokens(msg: dict, enc) -> int: return WRAPPER + content_tokens + tool_call_tokens +def _is_tool_message(msg: dict) -> bool: + """Check if a message contains tool calls or results that should be protected.""" + content = msg.get("content") + + # Check for Anthropic-style tool messages + if isinstance(content, list) and any( + isinstance(item, dict) and item.get("type") in ("tool_use", "tool_result") + for item in content + ): + return True + + # Check for OpenAI-style tool calls in the message + if "tool_calls" in msg or msg.get("role") == "tool": + return True + + return False + + +def _is_objective_message(msg: dict) -> bool: + """Check if a message contains objective/system prompts that should be absolutely protected.""" + content = msg.get("content", "") + if isinstance(content, str): + # Protect any message with the main objective prefix + return content.startswith(MAIN_OBJECTIVE_PREFIX) + return False + + +def _truncate_tool_message_content(msg: dict, enc, max_tokens: int) -> None: + """ + Carefully truncate tool message content while preserving tool structure. + Only truncates tool_result content, leaves tool_use intact. + """ + content = msg.get("content") + if not isinstance(content, list): + return + + for item in content: + # Only process tool_result items, leave tool_use blocks completely intact + if not (isinstance(item, dict) and item.get("type") == "tool_result"): + continue + + result_content = item.get("content", "") + if ( + isinstance(result_content, str) + and _tok_len(result_content, enc) > max_tokens + ): + item["content"] = _truncate_middle_tokens(result_content, enc, max_tokens) + + def _truncate_middle_tokens(text: str, enc, max_tok: int) -> str: """ Return *text* shortened to ≈max_tok tokens by keeping the head & tail @@ -140,13 +196,21 @@ def compress_prompt( return sum(_msg_tokens(m, enc) for m in msgs) original_token_count = total_tokens() + if original_token_count + reserve <= target_tokens: return msgs # ---- STEP 0 : normalise content -------------------------------------- # Convert non-string payloads to strings so token counting is coherent. - for m in msgs[1:-1]: # keep the first & last intact + for i, m in enumerate(msgs): if not isinstance(m.get("content"), str) and m.get("content") is not None: + if _is_tool_message(m): + continue + + # Keep first and last messages intact (unless they're tool messages) + if i == 0 or i == len(msgs) - 1: + continue + # Reasonable 20k-char ceiling prevents pathological blobs content_str = json.dumps(m["content"], separators=(",", ":")) if len(content_str) > 20_000: @@ -157,34 +221,45 @@ def compress_prompt( cap = start_cap while total_tokens() + reserve > target_tokens and cap >= floor_cap: for m in msgs[1:-1]: # keep first & last intact - if _tok_len(m.get("content") or "", enc) > cap: - m["content"] = _truncate_middle_tokens(m["content"], enc, cap) + if _is_tool_message(m): + # For tool messages, only truncate tool result content, preserve structure + _truncate_tool_message_content(m, enc, cap) + continue + + if _is_objective_message(m): + # Never truncate objective messages - they contain the core task + continue + + content = m.get("content") or "" + if _tok_len(content, enc) > cap: + m["content"] = _truncate_middle_tokens(content, enc, cap) cap //= 2 # tighten the screw # ---- STEP 2 : middle-out deletion ----------------------------------- while total_tokens() + reserve > target_tokens and len(msgs) > 2: + # Identify all deletable messages (not first/last, not tool messages, not objective messages) + deletable_indices = [] + for i in range(1, len(msgs) - 1): # Skip first and last + if not _is_tool_message(msgs[i]) and not _is_objective_message(msgs[i]): + deletable_indices.append(i) + + if not deletable_indices: + break # nothing more we can drop + + # Delete from center outward - find the index closest to center centre = len(msgs) // 2 - # Build a symmetrical centre-out index walk: centre, centre+1, centre-1, ... - order = [centre] + [ - i - for pair in zip(range(centre + 1, len(msgs) - 1), range(centre - 1, 0, -1)) - for i in pair - ] - removed = False - for i in order: - msg = msgs[i] - if "tool_calls" in msg or msg.get("role") == "tool": - continue # protect tool shells - del msgs[i] - removed = True - break - if not removed: # nothing more we can drop - break + to_delete = min(deletable_indices, key=lambda i: abs(i - centre)) + del msgs[to_delete] # ---- STEP 3 : final safety-net trim on first & last ------------------ cap = start_cap while total_tokens() + reserve > target_tokens and cap >= floor_cap: for idx in (0, -1): # first and last + if _is_tool_message(msgs[idx]): + # For tool messages at first/last position, truncate tool result content only + _truncate_tool_message_content(msgs[idx], enc, cap) + continue + text = msgs[idx].get("content") or "" if _tok_len(text, enc) > cap: msgs[idx]["content"] = _truncate_middle_tokens(text, enc, cap) diff --git a/autogpt_platform/frontend/package.json b/autogpt_platform/frontend/package.json index 556b733e96..89c367c788 100644 --- a/autogpt_platform/frontend/package.json +++ b/autogpt_platform/frontend/package.json @@ -82,7 +82,7 @@ "lodash": "4.17.21", "lucide-react": "0.552.0", "moment": "2.30.1", - "next": "15.4.8", + "next": "15.4.10", "next-themes": "0.4.6", "nuqs": "2.7.2", "party-js": "2.2.0", diff --git a/autogpt_platform/frontend/pnpm-lock.yaml b/autogpt_platform/frontend/pnpm-lock.yaml index 8e699cd907..de9e029fac 100644 --- a/autogpt_platform/frontend/pnpm-lock.yaml +++ b/autogpt_platform/frontend/pnpm-lock.yaml @@ -16,7 +16,7 @@ importers: version: 5.2.2(react-hook-form@7.66.0(react@18.3.1)) '@next/third-parties': specifier: 15.4.6 - version: 15.4.6(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) + version: 15.4.6(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) '@phosphor-icons/react': specifier: 2.1.10 version: 2.1.10(react-dom@18.3.1(react@18.3.1))(react@18.3.1) @@ -88,7 +88,7 @@ importers: version: 5.24.13(@rjsf/utils@5.24.13(react@18.3.1)) '@sentry/nextjs': specifier: 10.27.0 - version: 10.27.0(@opentelemetry/context-async-hooks@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.2.0(@opentelemetry/api@1.9.0))(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(webpack@5.101.3(esbuild@0.25.9)) + version: 10.27.0(@opentelemetry/context-async-hooks@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.2.0(@opentelemetry/api@1.9.0))(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(webpack@5.101.3(esbuild@0.25.9)) '@supabase/ssr': specifier: 0.7.0 version: 0.7.0(@supabase/supabase-js@2.78.0) @@ -106,10 +106,10 @@ importers: version: 0.2.4 '@vercel/analytics': specifier: 1.5.0 - version: 1.5.0(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) + version: 1.5.0(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) '@vercel/speed-insights': specifier: 1.2.0 - version: 1.2.0(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) + version: 1.2.0(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) '@xyflow/react': specifier: 12.9.2 version: 12.9.2(@types/react@18.3.17)(immer@10.1.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) @@ -148,7 +148,7 @@ importers: version: 12.23.24(@emotion/is-prop-valid@1.2.2)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) geist: specifier: 1.5.1 - version: 1.5.1(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)) + version: 1.5.1(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)) highlight.js: specifier: 11.11.1 version: 11.11.1 @@ -171,14 +171,14 @@ importers: specifier: 2.30.1 version: 2.30.1 next: - specifier: 15.4.8 - version: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + specifier: 15.4.10 + version: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) next-themes: specifier: 0.4.6 version: 0.4.6(react-dom@18.3.1(react@18.3.1))(react@18.3.1) nuqs: specifier: 2.7.2 - version: 2.7.2(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1) + 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9.1.5(esbuild@0.25.9)(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(storybook@9.1.5(@testing-library/dom@10.4.1)(msw@2.11.6(@types/node@24.10.0)(typescript@5.9.3))(prettier@3.6.2))(type-fest@4.41.0)(typescript@5.9.3)(webpack-hot-middleware@2.26.1)(webpack@5.101.3(esbuild@0.25.9)) '@tanstack/eslint-plugin-query': specifier: 5.91.2 version: 5.91.2(eslint@8.57.1)(typescript@5.9.3) @@ -1602,8 +1602,8 @@ packages: '@neoconfetti/react@1.0.0': resolution: {integrity: sha512-klcSooChXXOzIm+SE5IISIAn3bYzYfPjbX7D7HoqZL84oAfgREeSg5vSIaSFH+DaGzzvImTyWe1OyrJ67vik4A==} - '@next/env@15.4.8': - resolution: {integrity: sha512-LydLa2MDI1NMrOFSkO54mTc8iIHSttj6R6dthITky9ylXV2gCGi0bHQjVCtLGRshdRPjyh2kXbxJukDtBWQZtQ==} + '@next/env@15.4.10': + resolution: {integrity: sha512-knhmoJ0Vv7VRf6pZEPSnciUG1S4bIhWx+qTYBW/AjxEtlzsiNORPk8sFDCEvqLfmKuey56UB9FL1UdHEV3uBrg==} '@next/eslint-plugin-next@15.5.2': resolution: {integrity: sha512-lkLrRVxcftuOsJNhWatf1P2hNVfh98k/omQHrCEPPriUypR6RcS13IvLdIrEvkm9AH2Nu2YpR5vLqBuy6twH3Q==} @@ -5920,8 +5920,8 @@ packages: react: ^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc react-dom: ^16.8 || ^17 || ^18 || ^19 || ^19.0.0-rc - next@15.4.8: - resolution: {integrity: sha512-jwOXTz/bo0Pvlf20FSb6VXVeWRssA2vbvq9SdrOPEg9x8E1B27C2rQtvriAn600o9hH61kjrVRexEffv3JybuA==} + next@15.4.10: + resolution: {integrity: sha512-itVlc79QjpKMFMRhP+kbGKaSG/gZM6RCvwhEbwmCNF06CdDiNaoHcbeg0PqkEa2GOcn8KJ0nnc7+yL7EjoYLHQ==} engines: {node: ^18.18.0 || ^19.8.0 || >= 20.0.0} hasBin: true peerDependencies: @@ -9003,7 +9003,7 @@ snapshots: '@neoconfetti/react@1.0.0': {} - '@next/env@15.4.8': {} + '@next/env@15.4.10': {} '@next/eslint-plugin-next@15.5.2': dependencies: @@ -9033,9 +9033,9 @@ snapshots: '@next/swc-win32-x64-msvc@15.4.8': optional: true - '@next/third-parties@15.4.6(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)': + '@next/third-parties@15.4.6(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)': dependencies: - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) react: 18.3.1 third-party-capital: 1.0.20 @@ -10267,7 +10267,7 @@ snapshots: '@sentry/core@10.27.0': {} - '@sentry/nextjs@10.27.0(@opentelemetry/context-async-hooks@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.2.0(@opentelemetry/api@1.9.0))(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(webpack@5.101.3(esbuild@0.25.9))': + '@sentry/nextjs@10.27.0(@opentelemetry/context-async-hooks@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/core@2.2.0(@opentelemetry/api@1.9.0))(@opentelemetry/sdk-trace-base@2.2.0(@opentelemetry/api@1.9.0))(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)(webpack@5.101.3(esbuild@0.25.9))': dependencies: '@opentelemetry/api': 1.9.0 '@opentelemetry/semantic-conventions': 1.37.0 @@ -10280,7 +10280,7 @@ snapshots: '@sentry/react': 10.27.0(react@18.3.1) '@sentry/vercel-edge': 10.27.0 '@sentry/webpack-plugin': 4.3.0(webpack@5.101.3(esbuild@0.25.9)) - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) resolve: 1.22.8 rollup: 4.52.2 stacktrace-parser: 0.1.11 @@ -10642,7 +10642,7 @@ snapshots: react: 18.3.1 react-dom: 18.3.1(react@18.3.1) - '@storybook/nextjs@9.1.5(esbuild@0.25.9)(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(storybook@9.1.5(@testing-library/dom@10.4.1)(msw@2.11.6(@types/node@24.10.0)(typescript@5.9.3))(prettier@3.6.2))(type-fest@4.41.0)(typescript@5.9.3)(webpack-hot-middleware@2.26.1)(webpack@5.101.3(esbuild@0.25.9))': + '@storybook/nextjs@9.1.5(esbuild@0.25.9)(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react-dom@18.3.1(react@18.3.1))(react@18.3.1)(storybook@9.1.5(@testing-library/dom@10.4.1)(msw@2.11.6(@types/node@24.10.0)(typescript@5.9.3))(prettier@3.6.2))(type-fest@4.41.0)(typescript@5.9.3)(webpack-hot-middleware@2.26.1)(webpack@5.101.3(esbuild@0.25.9))': dependencies: '@babel/core': 7.28.4 '@babel/plugin-syntax-bigint': 7.8.3(@babel/core@7.28.4) @@ -10666,7 +10666,7 @@ snapshots: css-loader: 6.11.0(webpack@5.101.3(esbuild@0.25.9)) image-size: 2.0.2 loader-utils: 3.3.1 - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) node-polyfill-webpack-plugin: 2.0.1(webpack@5.101.3(esbuild@0.25.9)) postcss: 8.5.6 postcss-loader: 8.2.0(postcss@8.5.6)(typescript@5.9.3)(webpack@5.101.3(esbuild@0.25.9)) @@ -11271,14 +11271,14 @@ snapshots: '@unrs/resolver-binding-win32-x64-msvc@1.11.1': optional: true - '@vercel/analytics@1.5.0(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)': + '@vercel/analytics@1.5.0(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)': optionalDependencies: - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) react: 18.3.1 - '@vercel/speed-insights@1.2.0(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)': + '@vercel/speed-insights@1.2.0(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1)': optionalDependencies: - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) react: 18.3.1 '@vitest/expect@3.2.4': @@ -12954,9 +12954,9 @@ snapshots: functions-have-names@1.2.3: {} - geist@1.5.1(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)): + geist@1.5.1(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1)): dependencies: - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) gensync@1.0.0-beta.2: {} @@ -14226,9 +14226,9 @@ snapshots: react: 18.3.1 react-dom: 18.3.1(react@18.3.1) - next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1): + next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1): dependencies: - '@next/env': 15.4.8 + '@next/env': 15.4.10 '@swc/helpers': 0.5.15 caniuse-lite: 1.0.30001741 postcss: 8.4.31 @@ -14321,12 +14321,12 @@ snapshots: dependencies: boolbase: 1.0.0 - nuqs@2.7.2(next@15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1): + nuqs@2.7.2(next@15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1))(react@18.3.1): dependencies: '@standard-schema/spec': 1.0.0 react: 18.3.1 optionalDependencies: - next: 15.4.8(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + next: 15.4.10(@babel/core@7.28.4)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) oas-kit-common@1.0.8: dependencies: diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/AgentInputsReadOnly.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/AgentInputsReadOnly.tsx index a11e88f29a..bc9918c2bb 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/AgentInputsReadOnly.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/AgentInputsReadOnly/AgentInputsReadOnly.tsx @@ -1,16 +1,11 @@ "use client"; import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent"; -import type { - BlockIOSubSchema, - CredentialsMetaInput, -} from "@/lib/autogpt-server-api/types"; +import { Text } from "@/components/atoms/Text/Text"; +import type { CredentialsMetaInput } from "@/lib/autogpt-server-api/types"; import { CredentialsInput } from "../CredentialsInputs/CredentialsInputs"; -import { - getAgentCredentialsFields, - getAgentInputFields, - renderValue, -} from "./helpers"; +import { RunAgentInputs } from "../RunAgentInputs/RunAgentInputs"; +import { getAgentCredentialsFields, getAgentInputFields } from "./helpers"; type Props = { agent: LibraryAgent; @@ -28,19 +23,23 @@ export function AgentInputsReadOnly({ getAgentCredentialsFields(agent), ); - // Take actual input entries as leading; augment with schema from input fields. - // TODO: ensure consistent ordering. const inputEntries = inputs && - Object.entries(inputs).map<[string, [BlockIOSubSchema | undefined, any]]>( - ([k, v]) => [k, [inputFields[k], v]], - ); + Object.entries(inputs).map(([key, value]) => ({ + key, + schema: inputFields[key], + value, + })); const hasInputs = inputEntries && inputEntries.length > 0; const hasCredentials = credentialInputs && credentialFieldEntries.length > 0; if (!hasInputs && !hasCredentials) { - return
No input for this run.
; + return ( + + No input for this run. + + ); } return ( @@ -48,16 +47,20 @@ export function AgentInputsReadOnly({ {/* Regular inputs */} {hasInputs && (
- {inputEntries.map(([key, [schema, value]]) => ( -
- -

- {renderValue(value)} -

-
- ))} + {inputEntries.map(({ key, schema, value }) => { + if (!schema) return null; + + return ( + {}} + readOnly={true} + /> + ); + })}
)} diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs.tsx index d98d3cb10d..ea372193c5 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentInputs/RunAgentInputs.tsx @@ -9,6 +9,7 @@ import { Button } from "@/components/atoms/Button/Button"; import { FileInput } from "@/components/atoms/FileInput/FileInput"; import { Switch } from "@/components/atoms/Switch/Switch"; import { GoogleDrivePickerInput } from "@/components/contextual/GoogleDrivePicker/GoogleDrivePickerInput"; +import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip"; import { TimePicker } from "@/components/molecules/TimePicker/TimePicker"; import { BlockIOObjectSubSchema, @@ -32,6 +33,7 @@ interface Props { value?: any; placeholder?: string; onChange: (value: any) => void; + readOnly?: boolean; } /** @@ -44,6 +46,7 @@ export function RunAgentInputs({ value, placeholder, onChange, + readOnly = false, ...props }: Props & React.HTMLAttributes) { const { handleUploadFile, uploadProgress } = useRunAgentInputs(); @@ -62,7 +65,6 @@ export function RunAgentInputs({ id={`${baseId}-number`} label={schema.title ?? placeholder ?? "Number"} hideLabel - size="small" type="number" value={value ?? ""} placeholder={placeholder || "Enter number"} @@ -80,7 +82,6 @@ export function RunAgentInputs({ id={`${baseId}-textarea`} label={schema.title ?? placeholder ?? "Text"} hideLabel - size="small" type="textarea" rows={3} value={value ?? ""} @@ -130,7 +131,6 @@ export function RunAgentInputs({ id={`${baseId}-date`} label={schema.title ?? placeholder ?? "Date"} hideLabel - size="small" type="date" value={value ? format(value as Date, "yyyy-MM-dd") : ""} onChange={(e) => { @@ -159,7 +159,6 @@ export function RunAgentInputs({ id={`${baseId}-datetime`} label={schema.title ?? placeholder ?? "Date time"} hideLabel - size="small" type="datetime-local" value={value ?? ""} onChange={(e) => onChange((e.target as HTMLInputElement).value)} @@ -194,7 +193,6 @@ export function RunAgentInputs({ label={schema.title ?? placeholder ?? "Select"} hideLabel value={value ?? ""} - size="small" onValueChange={(val: string) => onChange(val)} placeholder={placeholder || "Select an option"} options={schema.enum @@ -217,7 +215,6 @@ export function RunAgentInputs({ items={allKeys.map((key) => ({ value: key, label: _schema.properties[key]?.title ?? key, - size: "small", }))} selectedValues={selectedValues} onChange={(values: string[]) => @@ -336,7 +333,6 @@ export function RunAgentInputs({ id={`${baseId}-text`} label={schema.title ?? placeholder ?? "Text"} hideLabel - size="small" type="text" value={value ?? ""} onChange={(e) => onChange((e.target as HTMLInputElement).value)} @@ -347,6 +343,17 @@ export function RunAgentInputs({ } return ( -
{innerInputElement}
+
+ +
+ {innerInputElement} +
+
); } diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx index d8c4ecb730..f3b02bfbc9 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/modals/RunAgentModal/components/ModalRunSection/ModalRunSection.tsx @@ -73,22 +73,15 @@ export function ModalRunSection() { title="Task Inputs" subtitle="Enter the information you want to provide to the agent for this task" > - {/* Regular inputs */} {inputFields.map(([key, inputSubSchema]) => ( -
- - - setInputValue(key, value)} - data-testid={`agent-input-${key}`} - /> -
+ setInputValue(key, value)} + data-testid={`agent-input-${key}`} + /> ))} ) : null} diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/SelectedRunView.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/SelectedRunView.tsx index cc5872097e..ff9a4e5809 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/SelectedRunView.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedRunView/SelectedRunView.tsx @@ -4,20 +4,19 @@ import { AgentExecutionStatus } from "@/app/api/__generated__/models/agentExecut import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent"; import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner"; import { Text } from "@/components/atoms/Text/Text"; -import { - Tooltip, - TooltipContent, - TooltipProvider, - TooltipTrigger, -} from "@/components/atoms/Tooltip/BaseTooltip"; import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard"; +import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip"; +import { + ScrollableTabs, + ScrollableTabsContent, + ScrollableTabsList, + ScrollableTabsTrigger, +} from "@/components/molecules/ScrollableTabs/ScrollableTabs"; import { PendingReviewsList } from "@/components/organisms/PendingReviewsList/PendingReviewsList"; import { usePendingReviewsForExecution } from "@/hooks/usePendingReviews"; import { isLargeScreen, useBreakpoint } from "@/lib/hooks/useBreakpoint"; -import { InfoIcon } from "@phosphor-icons/react"; import { useEffect } from "react"; import { AgentInputsReadOnly } from "../../modals/AgentInputsReadOnly/AgentInputsReadOnly"; -import { AnchorLinksWrap } from "../AnchorLinksWrap"; import { LoadingSelectedContent } from "../LoadingSelectedContent"; import { RunDetailCard } from "../RunDetailCard/RunDetailCard"; import { RunDetailHeader } from "../RunDetailHeader/RunDetailHeader"; @@ -28,9 +27,6 @@ import { SelectedRunActions } from "./components/SelectedRunActions/SelectedRunA import { WebhookTriggerSection } from "./components/WebhookTriggerSection"; import { useSelectedRunView } from "./useSelectedRunView"; -const anchorStyles = - "border-b-2 border-transparent pb-1 text-sm font-medium text-slate-600 transition-colors hover:text-slate-900 hover:border-slate-900"; - interface Props { agent: LibraryAgent; runId: string; @@ -65,13 +61,6 @@ export function SelectedRunView({ const withSummary = run?.stats?.activity_status; const withReviews = run?.status === AgentExecutionStatus.REVIEW; - function scrollToSection(id: string) { - const element = document.getElementById(id); - if (element) { - element.scrollIntoView({ behavior: "smooth", block: "start" }); - } - } - if (responseError || httpError) { return ( )} - {/* Navigation Links */} - - {withSummary && ( - - )} - - - {withReviews && ( - - )} - - - {/* Summary Section */} - {withSummary && ( -
- - Summary - - - - - - -

- This AI-generated summary describes how the agent - handled your task. It's an experimental - feature and may occasionally be inaccurate. -

- - - -
- } - > - - - - )} - - {/* Output Section */} -
- - {isLoading ? ( -
- -
- ) : run && "outputs" in run ? ( - - ) : ( - - No output from this run. - + + + {withSummary && ( + + Summary + )} - -
- - {/* Input Section */} -
- - - -
- - {/* Reviews Section */} - {withReviews && ( -
- - {reviewsLoading ? ( -
Loading reviews…
- ) : pendingReviews.length > 0 ? ( - - ) : ( -
- No pending reviews for this execution + + Output + + + Your input + + {withReviews && ( + + Reviews ({pendingReviews.length}) + + )} + +
+ {/* Summary Section */} + {withSummary && ( + +
+ + Summary + +
+ } + > + +
- )} - + + )} + + {/* Output Section */} + +
+ + {isLoading ? ( +
+ +
+ ) : run && "outputs" in run ? ( + + ) : ( + + No output from this run. + + )} + +
+ + + {/* Input Section */} + +
+ + Your input + +
+ } + > + + +
+ + + {/* Reviews Section */} + {withReviews && ( + +
+ + {reviewsLoading ? ( + + ) : pendingReviews.length > 0 ? ( + + ) : ( + + No pending reviews for this execution + + )} + +
+ + )}
- )} + diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx index 6563e19d5d..7f67963aa3 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/SelectedScheduleView.tsx @@ -9,7 +9,6 @@ import { humanizeCronExpression } from "@/lib/cron-expression-utils"; import { isLargeScreen, useBreakpoint } from "@/lib/hooks/useBreakpoint"; import { formatInTimezone, getTimezoneDisplayName } from "@/lib/timezone-utils"; import { AgentInputsReadOnly } from "../../modals/AgentInputsReadOnly/AgentInputsReadOnly"; -import { AnchorLinksWrap } from "../AnchorLinksWrap"; import { LoadingSelectedContent } from "../LoadingSelectedContent"; import { RunDetailCard } from "../RunDetailCard/RunDetailCard"; import { RunDetailHeader } from "../RunDetailHeader/RunDetailHeader"; @@ -17,9 +16,6 @@ import { SelectedViewLayout } from "../SelectedViewLayout"; import { SelectedScheduleActions } from "./components/SelectedScheduleActions"; import { useSelectedScheduleView } from "./useSelectedScheduleView"; -const anchorStyles = - "border-b-2 border-transparent pb-1 text-sm font-medium text-slate-600 transition-colors hover:text-slate-900 hover:border-slate-900"; - interface Props { agent: LibraryAgent; scheduleId: string; @@ -45,13 +41,6 @@ export function SelectedScheduleView({ const breakpoint = useBreakpoint(); const isLgScreenUp = isLargeScreen(breakpoint); - function scrollToSection(id: string) { - const element = document.getElementById(id); - if (element) { - element.scrollIntoView({ behavior: "smooth", block: "start" }); - } - } - if (error) { return ( - {/* Navigation Links */} - - - - - {/* Schedule Section */}
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/EditInputsModal.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/EditInputsModal.tsx deleted file mode 100644 index 05e55abd34..0000000000 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/EditInputsModal.tsx +++ /dev/null @@ -1,84 +0,0 @@ -"use client"; - -import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo"; -import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent"; -import { Button } from "@/components/atoms/Button/Button"; -import { Text } from "@/components/atoms/Text/Text"; -import { Dialog } from "@/components/molecules/Dialog/Dialog"; -import { PencilSimpleIcon } from "@phosphor-icons/react"; -import { RunAgentInputs } from "../../../../modals/RunAgentInputs/RunAgentInputs"; -import { useEditInputsModal } from "./useEditInputsModal"; - -type Props = { - agent: LibraryAgent; - schedule: GraphExecutionJobInfo; -}; - -export function EditInputsModal({ agent, schedule }: Props) { - const { - isOpen, - setIsOpen, - inputFields, - values, - setValues, - handleSave, - isSaving, - } = useEditInputsModal(agent, schedule); - - return ( - - - - - -
- Edit inputs -
- {Object.entries(inputFields).map(([key, fieldSchema]) => ( -
- - setValues((prev) => ({ ...prev, [key]: v }))} - /> -
- ))} -
-
- -
- - -
- - - - ); -} diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/useEditInputsModal.ts b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/useEditInputsModal.ts deleted file mode 100644 index 1c061ea7b7..0000000000 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/EditInputsModal/useEditInputsModal.ts +++ /dev/null @@ -1,78 +0,0 @@ -"use client"; - -import { useMemo, useState } from "react"; -import { useQueryClient } from "@tanstack/react-query"; -import { getGetV1ListExecutionSchedulesForAGraphQueryKey } from "@/app/api/__generated__/endpoints/schedules/schedules"; -import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent"; -import type { GraphExecutionJobInfo } from "@/app/api/__generated__/models/graphExecutionJobInfo"; -import { useToast } from "@/components/molecules/Toast/use-toast"; - -function getAgentInputFields(agent: LibraryAgent): Record { - const schema = agent.input_schema as unknown as { - properties?: Record; - } | null; - if (!schema || !schema.properties) return {}; - const properties = schema.properties as Record; - const visibleEntries = Object.entries(properties).filter( - ([, sub]) => !sub?.hidden, - ); - return Object.fromEntries(visibleEntries); -} - -export function useEditInputsModal( - agent: LibraryAgent, - schedule: GraphExecutionJobInfo, -) { - const queryClient = useQueryClient(); - const { toast } = useToast(); - const [isOpen, setIsOpen] = useState(false); - const [isSaving, setIsSaving] = useState(false); - const inputFields = useMemo(() => getAgentInputFields(agent), [agent]); - const [values, setValues] = useState>({ - ...(schedule.input_data as Record), - }); - - async function handleSave() { - setIsSaving(true); - try { - const res = await fetch(`/api/schedules/${schedule.id}`, { - method: "PATCH", - headers: { "Content-Type": "application/json" }, - body: JSON.stringify({ inputs: values }), - }); - if (!res.ok) { - let message = "Failed to update schedule inputs"; - const data = await res.json(); - message = data?.message || data?.detail || message; - throw new Error(message); - } - - await queryClient.invalidateQueries({ - queryKey: getGetV1ListExecutionSchedulesForAGraphQueryKey( - schedule.graph_id, - ), - }); - toast({ - title: "Schedule inputs updated", - }); - setIsOpen(false); - } catch (error: any) { - toast({ - title: "Failed to update schedule inputs", - description: error?.message || "An unexpected error occurred.", - variant: "destructive", - }); - } - setIsSaving(false); - } - - return { - isOpen, - setIsOpen, - inputFields, - values, - setValues, - handleSave, - isSaving, - } as const; -} diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions.tsx index 420b84c722..0fd34851fd 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedScheduleView/components/SelectedScheduleActions.tsx @@ -25,9 +25,10 @@ export function SelectedScheduleActions({ agent, scheduleId }: Props) { diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTemplateView/SelectedTemplateView.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTemplateView/SelectedTemplateView.tsx index 8f64417f77..ead985457e 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTemplateView/SelectedTemplateView.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTemplateView/SelectedTemplateView.tsx @@ -4,7 +4,6 @@ import type { GraphExecutionMeta } from "@/app/api/__generated__/models/graphExe import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent"; import { Input } from "@/components/atoms/Input/Input"; import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard"; -import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip"; import { getAgentCredentialsFields, getAgentInputFields, @@ -138,25 +137,13 @@ export function SelectedTemplateView({
{inputFields.map(([key, inputSubSchema]) => ( -
- - setInputValue(key, value)} - /> -
+ schema={inputSubSchema} + value={inputs[key] ?? inputSubSchema.default} + placeholder={inputSubSchema.description} + onChange={(value) => setInputValue(key, value)} + /> ))}
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTriggerView/SelectedTriggerView.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTriggerView/SelectedTriggerView.tsx index 2021251ad2..64d4430e78 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTriggerView/SelectedTriggerView.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/NewAgentLibraryView/components/selected-views/SelectedTriggerView/SelectedTriggerView.tsx @@ -3,7 +3,6 @@ import type { LibraryAgent } from "@/app/api/__generated__/models/libraryAgent"; import { Input } from "@/components/atoms/Input/Input"; import { ErrorCard } from "@/components/molecules/ErrorCard/ErrorCard"; -import { InformationTooltip } from "@/components/molecules/InformationTooltip/InformationTooltip"; import { getAgentCredentialsFields, getAgentInputFields, @@ -131,25 +130,13 @@ export function SelectedTriggerView({
{inputFields.map(([key, inputSubSchema]) => ( -
- - setInputValue(key, value)} - /> -
+ schema={inputSubSchema} + value={inputs[key] ?? inputSubSchema.default} + placeholder={inputSubSchema.description} + onChange={(value) => setInputValue(key, value)} + /> ))}
diff --git a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx index 0289bbdb5f..5f57032618 100644 --- a/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/library/agents/[id]/components/OldAgentLibraryView/components/agent-run-draft-view.tsx @@ -680,28 +680,20 @@ export function AgentRunDraftView({ {/* Regular inputs */} {Object.entries(agentInputFields).map(([key, inputSubSchema]) => ( -
- - - { - setInputValues((obj) => ({ - ...obj, - [key]: value, - })); - setChangedPresetAttributes((prev) => prev.add("inputs")); - }} - data-testid={`agent-input-${key}`} - /> -
+ { + setInputValues((obj) => ({ + ...obj, + [key]: value, + })); + setChangedPresetAttributes((prev) => prev.add("inputs")); + }} + data-testid={`agent-input-${key}`} + /> ))} diff --git a/autogpt_platform/frontend/src/app/providers.tsx b/autogpt_platform/frontend/src/app/providers.tsx index c798f6e487..8ea199abc8 100644 --- a/autogpt_platform/frontend/src/app/providers.tsx +++ b/autogpt_platform/frontend/src/app/providers.tsx @@ -1,36 +1,33 @@ "use client"; -import { LaunchDarklyProvider } from "@/services/feature-flags/feature-flag-provider"; -import OnboardingProvider from "@/providers/onboarding/onboarding-provider"; +import { TooltipProvider } from "@/components/atoms/Tooltip/BaseTooltip"; +import { SentryUserTracker } from "@/components/monitor/SentryUserTracker"; import { BackendAPIProvider } from "@/lib/autogpt-server-api/context"; import { getQueryClient } from "@/lib/react-query/queryClient"; -import { QueryClientProvider } from "@tanstack/react-query"; -import { - ThemeProvider as NextThemesProvider, - ThemeProviderProps, -} from "next-themes"; -import { NuqsAdapter } from "nuqs/adapters/next/app"; -import { TooltipProvider } from "@/components/atoms/Tooltip/BaseTooltip"; import CredentialsProvider from "@/providers/agent-credentials/credentials-provider"; -import { SentryUserTracker } from "@/components/monitor/SentryUserTracker"; +import OnboardingProvider from "@/providers/onboarding/onboarding-provider"; +import { LaunchDarklyProvider } from "@/services/feature-flags/feature-flag-provider"; +import { QueryClientProvider } from "@tanstack/react-query"; +import { ThemeProvider, ThemeProviderProps } from "next-themes"; +import { NuqsAdapter } from "nuqs/adapters/next/app"; export function Providers({ children, ...props }: ThemeProviderProps) { const queryClient = getQueryClient(); return ( - - - - - - + + + + + + {children} - - - - - + + + + + ); diff --git a/autogpt_platform/frontend/src/components/molecules/InformationTooltip/InformationTooltip.tsx b/autogpt_platform/frontend/src/components/molecules/InformationTooltip/InformationTooltip.tsx index 4bf9a76b94..36184f08c4 100644 --- a/autogpt_platform/frontend/src/components/molecules/InformationTooltip/InformationTooltip.tsx +++ b/autogpt_platform/frontend/src/components/molecules/InformationTooltip/InformationTooltip.tsx @@ -9,16 +9,20 @@ import ReactMarkdown from "react-markdown"; type Props = { description?: string; + iconSize?: number; }; -export function InformationTooltip({ description }: Props) { +export function InformationTooltip({ description, iconSize = 24 }: Props) { if (!description) return null; return ( - + ; + +export default meta; +type Story = StoryObj; + +function ScrollableTabsDemo() { + return ( +
+

ScrollableTabs Examples

+ +
+
+

+ Short Content (Tabs Hidden) +

+
+ + + + Account + + + Password + + + Settings + + + +
+ Make changes to your account here. Click save when you're + done. +
+ + +
+ Change your password here. After saving, you'll be logged + out. +
+ + +
+ Update your preferences and settings here. +
+ + +
+
+ +
+

+ Long Content (Tabs Visible) +

+
+ + + + Account + + + Password + + + Settings + + + +
+

+ Account Settings +

+

+ Make changes to your account here. Click save when + you're done. +

+

+ Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed + do eiusmod tempor incididunt ut labore et dolore magna + aliqua. Ut enim ad minim veniam, quis nostrud exercitation + ullamco laboris. +

+

+ Duis aute irure dolor in reprehenderit in voluptate velit + esse cillum dolore eu fugiat nulla pariatur. Excepteur sint + occaecat cupidatat non proident. +

+

+ Sed ut perspiciatis unde omnis iste natus error sit + voluptatem accusantium doloremque laudantium, totam rem + aperiam. +

+
+ + +
+

+ Password Settings +

+

+ Change your password here. After saving, you'll be + logged out. +

+

+ At vero eos et accusamus et iusto odio dignissimos ducimus + qui blanditiis praesentium voluptatum deleniti atque + corrupti quos dolores et quas molestias excepturi sint + occaecati cupiditate. +

+

+ Et harum quidem rerum facilis est et expedita distinctio. + Nam libero tempore, cum soluta nobis est eligendi optio + cumque nihil impedit quo minus. +

+

+ Temporibus autem quibusdam et aut officiis debitis aut rerum + necessitatibus saepe eveniet ut et voluptates repudiandae + sint. +

+
+ + +
+

+ General Settings +

+

+ Update your preferences and settings here. +

+

+ Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut + odit aut fugit, sed quia consequuntur magni dolores eos qui + ratione voluptatem sequi nesciunt. +

+

+ Neque porro quisquam est, qui dolorem ipsum quia dolor sit + amet, consectetur, adipisci velit, sed quia non numquam eius + modi tempora incidunt ut labore et dolore magnam aliquam + quaerat voluptatem. +

+

+ Ut enim ad minima veniam, quis nostrum exercitationem ullam + corporis suscipit laboriosam, nisi ut aliquid ex ea commodi + consequatur. +

+
+ + +
+
+ +
+

Many Tabs

+
+ + + + Overview + + + Analytics + + + Reports + + + Notifications + + + Integrations + + + Billing + + + +
+

+ Dashboard Overview +

+

+ Dashboard overview with key metrics and recent activity. +

+

+ Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed + do eiusmod tempor incididunt ut labore et dolore magna + aliqua. +

+

+ Ut enim ad minim veniam, quis nostrud exercitation ullamco + laboris nisi ut aliquip ex ea commodo consequat. +

+
+ + +
+

Analytics

+

+ Detailed analytics and performance metrics. +

+

+ Duis aute irure dolor in reprehenderit in voluptate velit + esse cillum dolore eu fugiat nulla pariatur. +

+

+ Excepteur sint occaecat cupidatat non proident, sunt in + culpa qui officia deserunt mollit anim id est laborum. +

+
+ + +
+

Reports

+

+ Generate and view reports for your account. +

+

+ Sed ut perspiciatis unde omnis iste natus error sit + voluptatem accusantium doloremque laudantium. +

+

+ Totam rem aperiam, eaque ipsa quae ab illo inventore + veritatis et quasi architecto beatae vitae dicta sunt + explicabo. +

+
+ + +
+

Notifications

+

Manage your notification preferences.

+

+ Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut + odit aut fugit. +

+

+ Sed quia consequuntur magni dolores eos qui ratione + voluptatem sequi nesciunt. +

+
+ + +
+

Integrations

+

+ Connect and manage third-party integrations. +

+

+ Neque porro quisquam est, qui dolorem ipsum quia dolor sit + amet. +

+

+ Consectetur, adipisci velit, sed quia non numquam eius modi + tempora incidunt. +

+
+ + +
+

Billing

+

+ View and manage your billing information. +

+

+ Ut enim ad minima veniam, quis nostrum exercitationem ullam + corporis suscipit laboriosam. +

+

+ Nisi ut aliquid ex ea commodi consequatur? Quis autem vel + eum iure reprehenderit qui in ea voluptate velit esse. +

+
+ + +
+
+
+
+ ); +} + +export const Default = { + render: () => , +} satisfies Story; + +export const ShortContent = { + render: () => ( +
+
+ + + + Account + + + Password + + + +
+ Make changes to your account here. Click save when you're + done. +
+ + +
+ Change your password here. After saving, you'll be logged + out. +
+ + +
+
+ ), +} satisfies Story; + +export const LongContent = { + render: () => ( +
+
+ + + Account + Password + Settings + + +
+

Account Settings

+

+ Make changes to your account here. Click save when you're + done. +

+

+ Lorem ipsum dolor sit amet, consectetur adipiscing elit. Sed do + eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut + enim ad minim veniam, quis nostrud exercitation ullamco laboris + nisi ut aliquip ex ea commodo consequat. +

+

+ Duis aute irure dolor in reprehenderit in voluptate velit esse + cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat + cupidatat non proident, sunt in culpa qui officia deserunt + mollit anim id est laborum. +

+

+ Sed ut perspiciatis unde omnis iste natus error sit voluptatem + accusantium doloremque laudantium, totam rem aperiam, eaque ipsa + quae ab illo inventore veritatis et quasi architecto beatae + vitae dicta sunt explicabo. +

+

+ Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit + aut fugit, sed quia consequuntur magni dolores eos qui ratione + voluptatem sequi nesciunt. +

+
+ + +
+

Password Settings

+

+ Change your password here. After saving, you'll be logged + out. +

+

+ At vero eos et accusamus et iusto odio dignissimos ducimus qui + blanditiis praesentium voluptatum deleniti atque corrupti quos + dolores et quas molestias excepturi sint occaecati cupiditate + non provident. +

+

+ Similique sunt in culpa qui officia deserunt mollitia animi, id + est laborum et dolorum fuga. Et harum quidem rerum facilis est + et expedita distinctio. +

+

+ Nam libero tempore, cum soluta nobis est eligendi optio cumque + nihil impedit quo minus id quod maxime placeat facere possimus, + omnis voluptas assumenda est, omnis dolor repellendus. +

+

+ Temporibus autem quibusdam et aut officiis debitis aut rerum + necessitatibus saepe eveniet ut et voluptates repudiandae sint + et molestiae non recusandae. +

+
+ + +
+

General Settings

+

Update your preferences and settings here.

+

+ Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, + consectetur, adipisci velit, sed quia non numquam eius modi + tempora incidunt ut labore et dolore magnam aliquam quaerat + voluptatem. +

+

+ Ut enim ad minima veniam, quis nostrum exercitationem ullam + corporis suscipit laboriosam, nisi ut aliquid ex ea commodi + consequatur? Quis autem vel eum iure reprehenderit qui in ea + voluptate velit esse quam nihil molestiae consequatur. +

+

+ Vel illum qui dolorem eum fugiat quo voluptas nulla pariatur? At + vero eos et accusamus et iusto odio dignissimos ducimus qui + blanditiis praesentium voluptatum deleniti atque corrupti quos + dolores. +

+

+ Et quas molestias excepturi sint occaecati cupiditate non + provident, similique sunt in culpa qui officia deserunt mollitia + animi, id est laborum et dolorum fuga. +

+
+ + +
+
+ ), +} satisfies Story; diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.tsx b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.tsx new file mode 100644 index 0000000000..bdbfa3cd4f --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/ScrollableTabs.tsx @@ -0,0 +1,59 @@ +"use client"; + +import { cn } from "@/lib/utils"; +import { Children } from "react"; +import { ScrollableTabsContent } from "./components/ScrollableTabsContent"; +import { ScrollableTabsList } from "./components/ScrollableTabsList"; +import { ScrollableTabsTrigger } from "./components/ScrollableTabsTrigger"; +import { ScrollableTabsContext } from "./context"; +import { findContentElements, findListElement } from "./helpers"; +import { useScrollableTabsInternal } from "./useScrollableTabs"; + +interface Props { + children?: React.ReactNode; + className?: string; + defaultValue?: string; +} + +export function ScrollableTabs({ children, className, defaultValue }: Props) { + const { + activeValue, + setActiveValue, + registerContent, + scrollToSection, + scrollContainer, + contentContainerRef, + } = useScrollableTabsInternal({ defaultValue }); + + const childrenArray = Children.toArray(children); + const listElement = findListElement(childrenArray); + const contentElements = findContentElements(childrenArray); + + return ( + +
+ {listElement} +
{ + if (contentContainerRef) { + contentContainerRef.current = node; + } + }} + className="max-h-[64rem] overflow-y-auto scrollbar-thin scrollbar-track-transparent scrollbar-thumb-zinc-300 dark:scrollbar-thumb-zinc-700" + > +
{contentElements}
+
+
+ + ); +} + +export { ScrollableTabsContent, ScrollableTabsList, ScrollableTabsTrigger }; diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsContent.tsx b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsContent.tsx new file mode 100644 index 0000000000..4027e87cfa --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsContent.tsx @@ -0,0 +1,48 @@ +"use client"; + +import { cn } from "@/lib/utils"; +import * as React from "react"; +import { useScrollableTabs } from "../context"; + +interface Props extends React.HTMLAttributes { + value: string; +} + +export const ScrollableTabsContent = React.forwardRef( + function ScrollableTabsContent( + { className, value, children, ...props }, + ref, + ) { + const { registerContent } = useScrollableTabs(); + const contentRef = React.useRef(null); + + React.useEffect(() => { + if (contentRef.current) { + registerContent(value, contentRef.current); + } + return () => { + registerContent(value, null); + }; + }, [value, registerContent]); + + return ( +
{ + if (typeof ref === "function") ref(node); + else if (ref) ref.current = node; + // eslint-disable-next-line @typescript-eslint/ban-ts-comment + // @ts-ignore + contentRef.current = node; + }} + data-scrollable-tab-content + data-value={value} + className={cn("focus-visible:outline-none", className)} + {...props} + > + {children} +
+ ); + }, +); + +ScrollableTabsContent.displayName = "ScrollableTabsContent"; diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsList.tsx b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsList.tsx new file mode 100644 index 0000000000..496a91ec5a --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsList.tsx @@ -0,0 +1,52 @@ +"use client"; + +import { cn } from "@/lib/utils"; +import * as React from "react"; +import { useScrollableTabs } from "../context"; + +export const ScrollableTabsList = React.forwardRef< + HTMLDivElement, + React.HTMLAttributes +>(function ScrollableTabsList({ className, children, ...props }, ref) { + const { activeValue } = useScrollableTabs(); + const [activeTabElement, setActiveTabElement] = + React.useState(null); + + React.useEffect(() => { + const activeButton = Array.from( + document.querySelectorAll( + '[data-scrollable-tab-trigger][data-value="' + activeValue + '"]', + ), + )[0]; + + if (activeButton) { + setActiveTabElement(activeButton); + } + }, [activeValue]); + + return ( +
+
+ {children} +
+ {activeTabElement && ( +
+ )} +
+ ); +}); + +ScrollableTabsList.displayName = "ScrollableTabsList"; diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsTrigger.tsx b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsTrigger.tsx new file mode 100644 index 0000000000..41367264d8 --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/components/ScrollableTabsTrigger.tsx @@ -0,0 +1,53 @@ +"use client"; + +import { cn } from "@/lib/utils"; +import * as React from "react"; +import { useScrollableTabs } from "../context"; + +interface Props extends React.ButtonHTMLAttributes { + value: string; +} + +export const ScrollableTabsTrigger = React.forwardRef( + function ScrollableTabsTrigger( + { className, value, children, ...props }, + ref, + ) { + const { activeValue, scrollToSection } = useScrollableTabs(); + const elementRef = React.useRef(null); + const isActive = activeValue === value; + + function handleClick(e: React.MouseEvent) { + e.preventDefault(); + e.stopPropagation(); + scrollToSection(value); + props.onClick?.(e); + } + + return ( + + ); + }, +); + +ScrollableTabsTrigger.displayName = "ScrollableTabsTrigger"; diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/context.ts b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/context.ts new file mode 100644 index 0000000000..080ae3702c --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/context.ts @@ -0,0 +1,22 @@ +import * as React from "react"; +import { createContext, useContext } from "react"; + +interface ScrollableTabsContextValue { + activeValue: string | null; + setActiveValue: React.Dispatch>; + registerContent: (value: string, element: HTMLElement | null) => void; + scrollToSection: (value: string) => void; + scrollContainer: HTMLElement | null; +} + +export const ScrollableTabsContext = createContext< + ScrollableTabsContextValue | undefined +>(undefined); + +export function useScrollableTabs() { + const context = useContext(ScrollableTabsContext); + if (!context) { + throw new Error("useScrollableTabs must be used within a ScrollableTabs"); + } + return context; +} diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/helpers.ts b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/helpers.ts new file mode 100644 index 0000000000..651e4c84fd --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/helpers.ts @@ -0,0 +1,48 @@ +import * as React from "react"; + +const HEADER_OFFSET = 100; + +export function calculateScrollPosition( + elementRect: DOMRect, + containerRect: DOMRect, + currentScrollTop: number, +): number { + const elementTopRelativeToContainer = + elementRect.top - containerRect.top + currentScrollTop - HEADER_OFFSET; + + return Math.max(0, elementTopRelativeToContainer); +} + +function hasDisplayName( + type: unknown, + displayName: string, +): type is { displayName: string } { + return ( + typeof type === "object" && + type !== null && + "displayName" in type && + (type as { displayName: unknown }).displayName === displayName + ); +} + +export function findListElement( + children: React.ReactNode[], +): React.ReactElement | undefined { + return children.find( + (child) => + React.isValidElement(child) && + hasDisplayName(child.type, "ScrollableTabsList"), + ) as React.ReactElement | undefined; +} + +export function findContentElements( + children: React.ReactNode[], +): React.ReactNode[] { + return children.filter( + (child) => + !( + React.isValidElement(child) && + hasDisplayName(child.type, "ScrollableTabsList") + ), + ); +} diff --git a/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/useScrollableTabs.ts b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/useScrollableTabs.ts new file mode 100644 index 0000000000..5043f1047e --- /dev/null +++ b/autogpt_platform/frontend/src/components/molecules/ScrollableTabs/useScrollableTabs.ts @@ -0,0 +1,60 @@ +import { useCallback, useRef, useState } from "react"; +import { calculateScrollPosition } from "./helpers"; + +interface Args { + defaultValue?: string; +} + +export function useScrollableTabsInternal({ defaultValue }: Args) { + const [activeValue, setActiveValue] = useState( + defaultValue || null, + ); + const contentRefs = useRef>(new Map()); + const contentContainerRef = useRef(null); + + function registerContent(value: string, element: HTMLElement | null) { + if (element) { + contentRefs.current.set(value, element); + } else { + contentRefs.current.delete(value); + } + } + + function scrollToSection(value: string) { + const element = contentRefs.current.get(value); + const scrollContainer = contentContainerRef.current; + if (!element || !scrollContainer) return; + + setActiveValue(value); + + const containerRect = scrollContainer.getBoundingClientRect(); + const elementRect = element.getBoundingClientRect(); + const currentScrollTop = scrollContainer.scrollTop; + const scrollTop = calculateScrollPosition( + elementRect, + containerRect, + currentScrollTop, + ); + + const maxScrollTop = + scrollContainer.scrollHeight - scrollContainer.clientHeight; + const clampedScrollTop = Math.min(Math.max(0, scrollTop), maxScrollTop); + + scrollContainer.scrollTo({ + top: clampedScrollTop, + behavior: "smooth", + }); + } + + const memoizedRegisterContent = useCallback(registerContent, []); + const memoizedScrollToSection = useCallback(scrollToSection, []); + + return { + activeValue, + setActiveValue, + registerContent: memoizedRegisterContent, + scrollToSection: memoizedScrollToSection, + scrollContainer: contentContainerRef.current, + contentContainerRef, + }; +} diff --git a/autogpt_platform/frontend/tailwind.config.ts b/autogpt_platform/frontend/tailwind.config.ts index 2a0d039b1a..ab3ea9bc74 100644 --- a/autogpt_platform/frontend/tailwind.config.ts +++ b/autogpt_platform/frontend/tailwind.config.ts @@ -1,10 +1,10 @@ +import scrollbar from "tailwind-scrollbar"; import type { Config } from "tailwindcss"; import tailwindcssAnimate from "tailwindcss-animate"; -import scrollbar from "tailwind-scrollbar"; import { colors } from "./src/components/styles/colors"; const config = { - darkMode: ["class"], + darkMode: ["class", ".dark-mode"], // ignore dark: prefix classes for now until we fully support dark mode content: ["./src/**/*.{ts,tsx}"], prefix: "", theme: {