diff --git a/.github/workflows/claude-ci-failure-auto-fix.yml b/.github/workflows/claude-ci-failure-auto-fix.yml index 070a4acd14..ab07c8ae10 100644 --- a/.github/workflows/claude-ci-failure-auto-fix.yml +++ b/.github/workflows/claude-ci-failure-auto-fix.yml @@ -22,7 +22,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: ref: ${{ github.event.workflow_run.head_branch }} fetch-depth: 0 diff --git a/.github/workflows/claude-dependabot.yml b/.github/workflows/claude-dependabot.yml index 6dbe068c3d..da37df6de7 100644 --- a/.github/workflows/claude-dependabot.yml +++ b/.github/workflows/claude-dependabot.yml @@ -30,7 +30,7 @@ jobs: actions: read # Required for CI access steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 1 diff --git a/.github/workflows/claude.yml b/.github/workflows/claude.yml index 8e165b823e..ee901fe5d4 100644 --- a/.github/workflows/claude.yml +++ b/.github/workflows/claude.yml @@ -40,7 +40,7 @@ jobs: actions: read # Required for CI access steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 1 diff --git a/.github/workflows/codeql.yml b/.github/workflows/codeql.yml index a6c36ed86c..966243323c 100644 --- a/.github/workflows/codeql.yml +++ b/.github/workflows/codeql.yml @@ -58,7 +58,7 @@ jobs: # your codebase is analyzed, see https://docs.github.com/en/code-security/code-scanning/creating-an-advanced-setup-for-code-scanning/codeql-code-scanning-for-compiled-languages steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 # Initializes the CodeQL tools for scanning. - name: Initialize CodeQL diff --git a/.github/workflows/copilot-setup-steps.yml b/.github/workflows/copilot-setup-steps.yml index eae6eea5d2..dad99cb8d9 100644 --- a/.github/workflows/copilot-setup-steps.yml +++ b/.github/workflows/copilot-setup-steps.yml @@ -27,7 +27,7 @@ jobs: # If you do not check out your code, Copilot will do this for you. steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 0 submodules: true diff --git a/.github/workflows/docs-block-sync.yml b/.github/workflows/docs-block-sync.yml index 4977877b19..32f205019f 100644 --- a/.github/workflows/docs-block-sync.yml +++ b/.github/workflows/docs-block-sync.yml @@ -23,7 +23,7 @@ jobs: steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 1 diff --git a/.github/workflows/docs-claude-review.yml b/.github/workflows/docs-claude-review.yml index 1643fe1c49..ca2788b387 100644 --- a/.github/workflows/docs-claude-review.yml +++ b/.github/workflows/docs-claude-review.yml @@ -23,7 +23,7 @@ jobs: steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 0 diff --git a/.github/workflows/docs-enhance.yml b/.github/workflows/docs-enhance.yml index 4baa882cd1..52607fa5df 100644 --- a/.github/workflows/docs-enhance.yml +++ b/.github/workflows/docs-enhance.yml @@ -28,7 +28,7 @@ jobs: steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 1 diff --git a/.github/workflows/platform-autogpt-deploy-dev.yaml b/.github/workflows/platform-autogpt-deploy-dev.yaml index 6e1e23d3eb..b415fb1b7b 100644 --- a/.github/workflows/platform-autogpt-deploy-dev.yaml +++ b/.github/workflows/platform-autogpt-deploy-dev.yaml @@ -25,7 +25,7 @@ jobs: steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: ref: ${{ github.event.inputs.git_ref || github.ref_name }} @@ -52,7 +52,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Trigger deploy workflow - uses: peter-evans/repository-dispatch@v3 + uses: peter-evans/repository-dispatch@v4 with: token: ${{ secrets.DEPLOY_TOKEN }} repository: Significant-Gravitas/AutoGPT_cloud_infrastructure diff --git a/.github/workflows/platform-autogpt-deploy-prod.yml b/.github/workflows/platform-autogpt-deploy-prod.yml index 4d7c16d710..e0c524d8d2 100644 --- a/.github/workflows/platform-autogpt-deploy-prod.yml +++ b/.github/workflows/platform-autogpt-deploy-prod.yml @@ -17,7 +17,7 @@ jobs: steps: - name: Checkout code - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: ref: ${{ github.ref_name || 'master' }} @@ -45,7 +45,7 @@ jobs: runs-on: ubuntu-latest steps: - name: Trigger deploy workflow - uses: peter-evans/repository-dispatch@v3 + uses: peter-evans/repository-dispatch@v4 with: token: ${{ secrets.DEPLOY_TOKEN }} repository: Significant-Gravitas/AutoGPT_cloud_infrastructure diff --git a/.github/workflows/platform-backend-ci.yml b/.github/workflows/platform-backend-ci.yml index a301477ecf..1f0c6da3dd 100644 --- a/.github/workflows/platform-backend-ci.yml +++ b/.github/workflows/platform-backend-ci.yml @@ -68,7 +68,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 0 submodules: true diff --git a/.github/workflows/platform-dev-deploy-event-dispatcher.yml b/.github/workflows/platform-dev-deploy-event-dispatcher.yml index b5324b7c2c..1a581c55c2 100644 --- a/.github/workflows/platform-dev-deploy-event-dispatcher.yml +++ b/.github/workflows/platform-dev-deploy-event-dispatcher.yml @@ -82,7 +82,7 @@ jobs: - name: Dispatch Deploy Event if: steps.check_status.outputs.should_deploy == 'true' - uses: peter-evans/repository-dispatch@v3 + uses: peter-evans/repository-dispatch@v4 with: token: ${{ secrets.DISPATCH_TOKEN }} repository: Significant-Gravitas/AutoGPT_cloud_infrastructure @@ -110,7 +110,7 @@ jobs: - name: Dispatch Undeploy Event (from comment) if: steps.check_status.outputs.should_undeploy == 'true' - uses: peter-evans/repository-dispatch@v3 + uses: peter-evans/repository-dispatch@v4 with: token: ${{ secrets.DISPATCH_TOKEN }} repository: Significant-Gravitas/AutoGPT_cloud_infrastructure @@ -168,7 +168,7 @@ jobs: github.event_name == 'pull_request' && github.event.action == 'closed' && steps.check_pr_close.outputs.should_undeploy == 'true' - uses: peter-evans/repository-dispatch@v3 + uses: peter-evans/repository-dispatch@v4 with: token: ${{ secrets.DISPATCH_TOKEN }} repository: Significant-Gravitas/AutoGPT_cloud_infrastructure diff --git a/.github/workflows/platform-frontend-ci.yml b/.github/workflows/platform-frontend-ci.yml index 669a775934..6410daae9f 100644 --- a/.github/workflows/platform-frontend-ci.yml +++ b/.github/workflows/platform-frontend-ci.yml @@ -31,7 +31,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 - name: Check for component changes uses: dorny/paths-filter@v3 @@ -71,7 +71,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 - name: Set up Node.js uses: actions/setup-node@v6 @@ -107,7 +107,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: fetch-depth: 0 @@ -148,7 +148,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: submodules: recursive @@ -277,7 +277,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: submodules: recursive diff --git a/.github/workflows/platform-fullstack-ci.yml b/.github/workflows/platform-fullstack-ci.yml index 67be0ae939..b4724245dc 100644 --- a/.github/workflows/platform-fullstack-ci.yml +++ b/.github/workflows/platform-fullstack-ci.yml @@ -29,7 +29,7 @@ jobs: steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 - name: Set up Node.js uses: actions/setup-node@v6 @@ -56,14 +56,14 @@ jobs: run: pnpm install --frozen-lockfile types: - runs-on: ubuntu-latest + runs-on: big-boi needs: setup strategy: fail-fast: false steps: - name: Checkout repository - uses: actions/checkout@v4 + uses: actions/checkout@v6 with: submodules: recursive @@ -85,7 +85,7 @@ jobs: - name: Run docker compose run: | - docker compose -f ../docker-compose.yml --profile local --profile deps_backend up -d + docker compose -f ../docker-compose.yml --profile local up -d deps_backend - 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extras = ["toml"]} pluggy = ">=1.2" -pytest = ">=6.2.5" +pytest = ">=7" [package.extras] -testing = ["fields", "hunter", "process-tests", "pytest-xdist", "virtualenv"] +testing = ["process-tests", "pytest-xdist", "virtualenv"] [[package]] name = "pytest-mock" @@ -2545,7 +2563,7 @@ description = "A lil' TOML parser" optional = false python-versions = ">=3.8" groups = ["dev"] -markers = "python_version == \"3.10\"" +markers = "python_version < \"3.11\"" files = [ {file = "tomli-2.2.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:678e4fa69e4575eb77d103de3df8a895e1591b48e740211bd1067378c69e8249"}, {file = "tomli-2.2.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:023aa114dd824ade0100497eb2318602af309e5a55595f76b626d6d9f3b7b0a6"}, @@ -2893,4 +2911,4 @@ type = ["pytest-mypy"] [metadata] lock-version = "2.1" python-versions = ">=3.10,<4.0" -content-hash = "b7ac335a86aa44c3d7d2802298818b389a6f1286e3e9b7b0edb2ff06377cecaf" +content-hash = "40eae94995dc0a388fa832ed4af9b6137f28d5b5ced3aaea70d5f91d4d9a179d" diff --git a/autogpt_platform/autogpt_libs/pyproject.toml b/autogpt_platform/autogpt_libs/pyproject.toml index 9b2bcb8fbe..8deb4d2169 100644 --- a/autogpt_platform/autogpt_libs/pyproject.toml +++ b/autogpt_platform/autogpt_libs/pyproject.toml @@ -26,7 +26,7 @@ pyright = "^1.1.408" pytest = "^8.4.1" pytest-asyncio = "^1.3.0" pytest-mock = "^3.15.1" -pytest-cov = "^6.2.1" +pytest-cov = "^7.0.0" ruff = "^0.15.0" [build-system] diff --git a/autogpt_platform/backend/backend/api/features/chat/config.py b/autogpt_platform/backend/backend/api/features/chat/config.py index 0b37e42df8..808692f97f 100644 --- a/autogpt_platform/backend/backend/api/features/chat/config.py +++ b/autogpt_platform/backend/backend/api/features/chat/config.py @@ -93,6 +93,12 @@ class ChatConfig(BaseSettings): description="Name of the prompt in Langfuse to fetch", ) + # Extended thinking configuration for Claude models + thinking_enabled: bool = Field( + default=True, + description="Enable adaptive thinking for Claude models via OpenRouter", + ) + @field_validator("api_key", mode="before") @classmethod def get_api_key(cls, v): diff --git a/autogpt_platform/backend/backend/api/features/chat/db.py b/autogpt_platform/backend/backend/api/features/chat/db.py index d34b4e5b07..303ea0a698 100644 --- a/autogpt_platform/backend/backend/api/features/chat/db.py +++ b/autogpt_platform/backend/backend/api/features/chat/db.py @@ -45,10 +45,7 @@ async def create_chat_session( successfulAgentRuns=SafeJson({}), successfulAgentSchedules=SafeJson({}), ) - return await PrismaChatSession.prisma().create( - data=data, - include={"Messages": True}, - ) + return await PrismaChatSession.prisma().create(data=data) async def update_chat_session( diff --git a/autogpt_platform/backend/backend/api/features/chat/model.py b/autogpt_platform/backend/backend/api/features/chat/model.py index 7318ef88d7..35418f174f 100644 --- a/autogpt_platform/backend/backend/api/features/chat/model.py +++ b/autogpt_platform/backend/backend/api/features/chat/model.py @@ -2,7 +2,7 @@ import asyncio import logging import uuid from datetime import UTC, datetime -from typing import Any +from typing import Any, cast from weakref import WeakValueDictionary from openai.types.chat import ( @@ -104,6 +104,26 @@ class ChatSession(BaseModel): successful_agent_runs: dict[str, int] = {} successful_agent_schedules: dict[str, int] = {} + def add_tool_call_to_current_turn(self, tool_call: dict) -> None: + """Attach a tool_call to the current turn's assistant message. + + Searches backwards for the most recent assistant message (stopping at + any user message boundary). If found, appends the tool_call to it. + Otherwise creates a new assistant message with the tool_call. + """ + for msg in reversed(self.messages): + if msg.role == "user": + break + if msg.role == "assistant": + if not msg.tool_calls: + msg.tool_calls = [] + msg.tool_calls.append(tool_call) + return + + self.messages.append( + ChatMessage(role="assistant", content="", tool_calls=[tool_call]) + ) + @staticmethod def new(user_id: str) -> "ChatSession": return ChatSession( @@ -172,6 +192,47 @@ class ChatSession(BaseModel): successful_agent_schedules=successful_agent_schedules, ) + @staticmethod + def _merge_consecutive_assistant_messages( + messages: list[ChatCompletionMessageParam], + ) -> list[ChatCompletionMessageParam]: + """Merge consecutive assistant messages into single messages. + + Long-running tool flows can create split assistant messages: one with + text content and another with tool_calls. Anthropic's API requires + tool_result blocks to reference a tool_use in the immediately preceding + assistant message, so these splits cause 400 errors via OpenRouter. + """ + if len(messages) < 2: + return messages + + result: list[ChatCompletionMessageParam] = [messages[0]] + for msg in messages[1:]: + prev = result[-1] + if prev.get("role") != "assistant" or msg.get("role") != "assistant": + result.append(msg) + continue + + prev = cast(ChatCompletionAssistantMessageParam, prev) + curr = cast(ChatCompletionAssistantMessageParam, msg) + + curr_content = curr.get("content") or "" + if curr_content: + prev_content = prev.get("content") or "" + prev["content"] = ( + f"{prev_content}\n{curr_content}" if prev_content else curr_content + ) + + curr_tool_calls = curr.get("tool_calls") + if curr_tool_calls: + prev_tool_calls = prev.get("tool_calls") + prev["tool_calls"] = ( + list(prev_tool_calls) + list(curr_tool_calls) + if prev_tool_calls + else list(curr_tool_calls) + ) + return result + def to_openai_messages(self) -> list[ChatCompletionMessageParam]: messages = [] for message in self.messages: @@ -258,7 +319,7 @@ class ChatSession(BaseModel): name=message.name or "", ) ) - return messages + return self._merge_consecutive_assistant_messages(messages) async def _get_session_from_cache(session_id: str) -> ChatSession | None: diff --git a/autogpt_platform/backend/backend/api/features/chat/model_test.py b/autogpt_platform/backend/backend/api/features/chat/model_test.py index c230b00f9c..239137844d 100644 --- a/autogpt_platform/backend/backend/api/features/chat/model_test.py +++ b/autogpt_platform/backend/backend/api/features/chat/model_test.py @@ -1,4 +1,16 @@ +from typing import cast + import pytest +from openai.types.chat import ( + ChatCompletionAssistantMessageParam, + ChatCompletionMessageParam, + ChatCompletionToolMessageParam, + ChatCompletionUserMessageParam, +) +from openai.types.chat.chat_completion_message_tool_call_param import ( + ChatCompletionMessageToolCallParam, + Function, +) from .model import ( ChatMessage, @@ -117,3 +129,205 @@ async def test_chatsession_db_storage(setup_test_user, test_user_id): loaded.tool_calls is not None ), f"Tool calls missing for {orig.role} message" assert len(orig.tool_calls) == len(loaded.tool_calls) + + +# --------------------------------------------------------------------------- # +# _merge_consecutive_assistant_messages # +# --------------------------------------------------------------------------- # + +_tc = ChatCompletionMessageToolCallParam( + id="tc1", type="function", function=Function(name="do_stuff", arguments="{}") +) +_tc2 = ChatCompletionMessageToolCallParam( + id="tc2", type="function", function=Function(name="other", arguments="{}") +) + + +def test_merge_noop_when_no_consecutive_assistants(): + """Messages without consecutive assistants are returned unchanged.""" + msgs = [ + ChatCompletionUserMessageParam(role="user", content="hi"), + ChatCompletionAssistantMessageParam(role="assistant", content="hello"), + ChatCompletionUserMessageParam(role="user", content="bye"), + ] + merged = ChatSession._merge_consecutive_assistant_messages(msgs) + assert len(merged) == 3 + assert [m["role"] for m in merged] == ["user", "assistant", "user"] + + +def test_merge_splits_text_and_tool_calls(): + """The exact bug scenario: text-only assistant followed by tool_calls-only assistant.""" + msgs = [ + ChatCompletionUserMessageParam(role="user", content="build agent"), + ChatCompletionAssistantMessageParam( + role="assistant", content="Let me build that" + ), + ChatCompletionAssistantMessageParam( + role="assistant", content="", tool_calls=[_tc] + ), + ChatCompletionToolMessageParam(role="tool", content="ok", tool_call_id="tc1"), + ] + merged = ChatSession._merge_consecutive_assistant_messages(msgs) + + assert len(merged) == 3 + assert merged[0]["role"] == "user" + assert merged[2]["role"] == "tool" + a = cast(ChatCompletionAssistantMessageParam, merged[1]) + assert a["role"] == "assistant" + assert a.get("content") == "Let me build that" + assert a.get("tool_calls") == [_tc] + + +def test_merge_combines_tool_calls_from_both(): + """Both consecutive assistants have tool_calls — they get merged.""" + msgs: list[ChatCompletionAssistantMessageParam] = [ + ChatCompletionAssistantMessageParam( + role="assistant", content="text", tool_calls=[_tc] + ), + ChatCompletionAssistantMessageParam( + role="assistant", content="", tool_calls=[_tc2] + ), + ] + merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type] + + assert len(merged) == 1 + a = cast(ChatCompletionAssistantMessageParam, merged[0]) + assert a.get("tool_calls") == [_tc, _tc2] + assert a.get("content") == "text" + + +def test_merge_three_consecutive_assistants(): + """Three consecutive assistants collapse into one.""" + msgs: list[ChatCompletionAssistantMessageParam] = [ + ChatCompletionAssistantMessageParam(role="assistant", content="a"), + ChatCompletionAssistantMessageParam(role="assistant", content="b"), + ChatCompletionAssistantMessageParam( + role="assistant", content="", tool_calls=[_tc] + ), + ] + merged = ChatSession._merge_consecutive_assistant_messages(msgs) # type: ignore[arg-type] + + assert len(merged) == 1 + a = cast(ChatCompletionAssistantMessageParam, merged[0]) + assert a.get("content") == "a\nb" + assert a.get("tool_calls") == [_tc] + + +def test_merge_empty_and_single_message(): + """Edge cases: empty list and single message.""" + assert ChatSession._merge_consecutive_assistant_messages([]) == [] + + single: list[ChatCompletionMessageParam] = [ + ChatCompletionUserMessageParam(role="user", content="hi") + ] + assert ChatSession._merge_consecutive_assistant_messages(single) == single + + +# --------------------------------------------------------------------------- # +# add_tool_call_to_current_turn # +# --------------------------------------------------------------------------- # + +_raw_tc = { + "id": "tc1", + "type": "function", + "function": {"name": "f", "arguments": "{}"}, +} +_raw_tc2 = { + "id": "tc2", + "type": "function", + "function": {"name": "g", "arguments": "{}"}, +} + + +def test_add_tool_call_appends_to_existing_assistant(): + """When the last assistant is from the current turn, tool_call is added to it.""" + session = ChatSession.new(user_id="u") + session.messages = [ + ChatMessage(role="user", content="hi"), + ChatMessage(role="assistant", content="working on it"), + ] + session.add_tool_call_to_current_turn(_raw_tc) + + assert len(session.messages) == 2 # no new message created + assert session.messages[1].tool_calls == [_raw_tc] + + +def test_add_tool_call_creates_assistant_when_none_exists(): + """When there's no current-turn assistant, a new one is created.""" + session = ChatSession.new(user_id="u") + session.messages = [ + ChatMessage(role="user", content="hi"), + ] + session.add_tool_call_to_current_turn(_raw_tc) + + assert len(session.messages) == 2 + assert session.messages[1].role == "assistant" + assert session.messages[1].tool_calls == [_raw_tc] + + +def test_add_tool_call_does_not_cross_user_boundary(): + """A user message acts as a boundary — previous assistant is not modified.""" + session = ChatSession.new(user_id="u") + session.messages = [ + ChatMessage(role="assistant", content="old turn"), + ChatMessage(role="user", content="new message"), + ] + session.add_tool_call_to_current_turn(_raw_tc) + + assert len(session.messages) == 3 # new assistant was created + assert session.messages[0].tool_calls is None # old assistant untouched + assert session.messages[2].role == "assistant" + assert session.messages[2].tool_calls == [_raw_tc] + + +def test_add_tool_call_multiple_times(): + """Multiple long-running tool calls accumulate on the same assistant.""" + session = ChatSession.new(user_id="u") + session.messages = [ + ChatMessage(role="user", content="hi"), + ChatMessage(role="assistant", content="doing stuff"), + ] + session.add_tool_call_to_current_turn(_raw_tc) + # Simulate a pending tool result in between (like _yield_tool_call does) + session.messages.append( + ChatMessage(role="tool", content="pending", tool_call_id="tc1") + ) + session.add_tool_call_to_current_turn(_raw_tc2) + + assert len(session.messages) == 3 # user, assistant, tool — no extra assistant + assert session.messages[1].tool_calls == [_raw_tc, _raw_tc2] + + +def test_to_openai_messages_merges_split_assistants(): + """End-to-end: session with split assistants produces valid OpenAI messages.""" + session = ChatSession.new(user_id="u") + session.messages = [ + ChatMessage(role="user", content="build agent"), + ChatMessage(role="assistant", content="Let me build that"), + ChatMessage( + role="assistant", + content="", + tool_calls=[ + { + "id": "tc1", + "type": "function", + "function": {"name": "create_agent", "arguments": "{}"}, + } + ], + ), + ChatMessage(role="tool", content="done", tool_call_id="tc1"), + ChatMessage(role="assistant", content="Saved!"), + ChatMessage(role="user", content="show me an example run"), + ] + openai_msgs = session.to_openai_messages() + + # The two consecutive assistants at index 1,2 should be merged + roles = [m["role"] for m in openai_msgs] + assert roles == ["user", "assistant", "tool", "assistant", "user"] + + # The merged assistant should have both content and tool_calls + merged = cast(ChatCompletionAssistantMessageParam, openai_msgs[1]) + assert merged.get("content") == "Let me build that" + tc_list = merged.get("tool_calls") + assert tc_list is not None and len(list(tc_list)) == 1 + assert list(tc_list)[0]["id"] == "tc1" diff --git a/autogpt_platform/backend/backend/api/features/chat/response_model.py b/autogpt_platform/backend/backend/api/features/chat/response_model.py index f627a42fcc..8ea0c1f97a 100644 --- a/autogpt_platform/backend/backend/api/features/chat/response_model.py +++ b/autogpt_platform/backend/backend/api/features/chat/response_model.py @@ -10,6 +10,8 @@ from typing import Any from pydantic import BaseModel, Field +from backend.util.json import dumps as json_dumps + class ResponseType(str, Enum): """Types of streaming responses following AI SDK protocol.""" @@ -18,6 +20,10 @@ class ResponseType(str, Enum): START = "start" FINISH = "finish" + # Step lifecycle (one LLM API call within a message) + START_STEP = "start-step" + FINISH_STEP = "finish-step" + # Text streaming TEXT_START = "text-start" TEXT_DELTA = "text-delta" @@ -57,6 +63,16 @@ class StreamStart(StreamBaseResponse): description="Task ID for SSE reconnection. Clients can reconnect using GET /tasks/{taskId}/stream", ) + def to_sse(self) -> str: + """Convert to SSE format, excluding non-protocol fields like taskId.""" + import json + + data: dict[str, Any] = { + "type": self.type.value, + "messageId": self.messageId, + } + return f"data: {json.dumps(data)}\n\n" + class StreamFinish(StreamBaseResponse): """End of message/stream.""" @@ -64,6 +80,26 @@ class StreamFinish(StreamBaseResponse): type: ResponseType = ResponseType.FINISH +class StreamStartStep(StreamBaseResponse): + """Start of a step (one LLM API call within a message). + + The AI SDK uses this to add a step-start boundary to message.parts, + enabling visual separation between multiple LLM calls in a single message. + """ + + type: ResponseType = ResponseType.START_STEP + + +class StreamFinishStep(StreamBaseResponse): + """End of a step (one LLM API call within a message). + + The AI SDK uses this to reset activeTextParts and activeReasoningParts, + so the next LLM call in a tool-call continuation starts with clean state. + """ + + type: ResponseType = ResponseType.FINISH_STEP + + # ========== Text Streaming ========== @@ -117,7 +153,7 @@ class StreamToolOutputAvailable(StreamBaseResponse): type: ResponseType = ResponseType.TOOL_OUTPUT_AVAILABLE toolCallId: str = Field(..., description="Tool call ID this responds to") output: str | dict[str, Any] = Field(..., description="Tool execution output") - # Additional fields for internal use (not part of AI SDK spec but useful) + # Keep these for internal backend use toolName: str | None = Field( default=None, description="Name of the tool that was executed" ) @@ -125,6 +161,17 @@ class StreamToolOutputAvailable(StreamBaseResponse): default=True, description="Whether the tool execution succeeded" ) + def to_sse(self) -> str: + """Convert to SSE format, excluding non-spec fields.""" + import json + + data = { + "type": self.type.value, + "toolCallId": self.toolCallId, + "output": self.output, + } + return f"data: {json.dumps(data)}\n\n" + # ========== Other ========== @@ -148,6 +195,18 @@ class StreamError(StreamBaseResponse): default=None, description="Additional error details" ) + def to_sse(self) -> str: + """Convert to SSE format, only emitting fields required by AI SDK protocol. + + The AI SDK uses z.strictObject({type, errorText}) which rejects + any extra fields like `code` or `details`. + """ + data = { + "type": self.type.value, + "errorText": self.errorText, + } + return f"data: {json_dumps(data)}\n\n" + class StreamHeartbeat(StreamBaseResponse): """Heartbeat to keep SSE connection alive during long-running operations. diff --git a/autogpt_platform/backend/backend/api/features/chat/routes.py b/autogpt_platform/backend/backend/api/features/chat/routes.py index 3e731d86ac..c6f37569b7 100644 --- a/autogpt_platform/backend/backend/api/features/chat/routes.py +++ b/autogpt_platform/backend/backend/api/features/chat/routes.py @@ -6,7 +6,7 @@ from collections.abc import AsyncGenerator from typing import Annotated from autogpt_libs import auth -from fastapi import APIRouter, Depends, Header, HTTPException, Query, Security +from fastapi import APIRouter, Depends, Header, HTTPException, Query, Response, Security from fastapi.responses import StreamingResponse from pydantic import BaseModel @@ -17,7 +17,29 @@ from . import stream_registry from .completion_handler import process_operation_failure, process_operation_success from .config import ChatConfig from .model import ChatSession, create_chat_session, get_chat_session, get_user_sessions -from .response_model import StreamFinish, StreamHeartbeat, StreamStart +from .response_model import StreamFinish, StreamHeartbeat +from .tools.models import ( + AgentDetailsResponse, + AgentOutputResponse, + AgentPreviewResponse, + AgentSavedResponse, + AgentsFoundResponse, + BlockListResponse, + BlockOutputResponse, + ClarificationNeededResponse, + DocPageResponse, + DocSearchResultsResponse, + ErrorResponse, + ExecutionStartedResponse, + InputValidationErrorResponse, + NeedLoginResponse, + NoResultsResponse, + OperationInProgressResponse, + OperationPendingResponse, + OperationStartedResponse, + SetupRequirementsResponse, + UnderstandingUpdatedResponse, +) config = ChatConfig() @@ -266,12 +288,36 @@ async def stream_chat_post( """ import asyncio + import time + + stream_start_time = time.perf_counter() + log_meta = {"component": "ChatStream", "session_id": session_id} + if user_id: + log_meta["user_id"] = user_id + + logger.info( + f"[TIMING] stream_chat_post STARTED, session={session_id}, " + f"user={user_id}, message_len={len(request.message)}", + extra={"json_fields": log_meta}, + ) session = await _validate_and_get_session(session_id, user_id) + logger.info( + f"[TIMING] session validated in {(time.perf_counter() - stream_start_time)*1000:.1f}ms", + extra={ + "json_fields": { + **log_meta, + "duration_ms": (time.perf_counter() - stream_start_time) * 1000, + } + }, + ) # Create a task in the stream registry for reconnection support task_id = str(uuid_module.uuid4()) operation_id = str(uuid_module.uuid4()) + log_meta["task_id"] = task_id + + task_create_start = time.perf_counter() await stream_registry.create_task( task_id=task_id, session_id=session_id, @@ -280,14 +326,28 @@ async def stream_chat_post( tool_name="chat", operation_id=operation_id, ) + logger.info( + f"[TIMING] create_task completed in {(time.perf_counter() - task_create_start)*1000:.1f}ms", + extra={ + "json_fields": { + **log_meta, + "duration_ms": (time.perf_counter() - task_create_start) * 1000, + } + }, + ) # Background task that runs the AI generation independently of SSE connection async def run_ai_generation(): - try: - # Emit a start event with task_id for reconnection - start_chunk = StreamStart(messageId=task_id, taskId=task_id) - await stream_registry.publish_chunk(task_id, start_chunk) + import time as time_module + gen_start_time = time_module.perf_counter() + logger.info( + f"[TIMING] run_ai_generation STARTED, task={task_id}, session={session_id}, user={user_id}", + extra={"json_fields": log_meta}, + ) + first_chunk_time, ttfc = None, None + chunk_count = 0 + try: async for chunk in chat_service.stream_chat_completion( session_id, request.message, @@ -295,25 +355,79 @@ async def stream_chat_post( user_id=user_id, session=session, # Pass pre-fetched session to avoid double-fetch context=request.context, + _task_id=task_id, # Pass task_id so service emits start with taskId for reconnection ): + chunk_count += 1 + if first_chunk_time is None: + first_chunk_time = time_module.perf_counter() + ttfc = first_chunk_time - gen_start_time + logger.info( + f"[TIMING] FIRST AI CHUNK at {ttfc:.2f}s, type={type(chunk).__name__}", + extra={ + "json_fields": { + **log_meta, + "chunk_type": type(chunk).__name__, + "time_to_first_chunk_ms": ttfc * 1000, + } + }, + ) # Write to Redis (subscribers will receive via XREAD) await stream_registry.publish_chunk(task_id, chunk) - # Mark task as completed + gen_end_time = time_module.perf_counter() + total_time = (gen_end_time - gen_start_time) * 1000 + logger.info( + f"[TIMING] run_ai_generation FINISHED in {total_time/1000:.1f}s; " + f"task={task_id}, session={session_id}, " + f"ttfc={ttfc or -1:.2f}s, n_chunks={chunk_count}", + extra={ + "json_fields": { + **log_meta, + "total_time_ms": total_time, + "time_to_first_chunk_ms": ( + ttfc * 1000 if ttfc is not None else None + ), + "n_chunks": chunk_count, + } + }, + ) await stream_registry.mark_task_completed(task_id, "completed") except Exception as e: + elapsed = time_module.perf_counter() - gen_start_time logger.error( - f"Error in background AI generation for session {session_id}: {e}" + f"[TIMING] run_ai_generation ERROR after {elapsed:.2f}s: {e}", + extra={ + "json_fields": { + **log_meta, + "elapsed_ms": elapsed * 1000, + "error": str(e), + } + }, ) await stream_registry.mark_task_completed(task_id, "failed") # Start the AI generation in a background task bg_task = asyncio.create_task(run_ai_generation()) await stream_registry.set_task_asyncio_task(task_id, bg_task) + setup_time = (time.perf_counter() - stream_start_time) * 1000 + logger.info( + f"[TIMING] Background task started, setup={setup_time:.1f}ms", + extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}}, + ) # SSE endpoint that subscribes to the task's stream async def event_generator() -> AsyncGenerator[str, None]: + import time as time_module + + event_gen_start = time_module.perf_counter() + logger.info( + f"[TIMING] event_generator STARTED, task={task_id}, session={session_id}, " + f"user={user_id}", + extra={"json_fields": log_meta}, + ) subscriber_queue = None + first_chunk_yielded = False + chunks_yielded = 0 try: # Subscribe to the task stream (this replays existing messages + live updates) subscriber_queue = await stream_registry.subscribe_to_task( @@ -328,22 +442,70 @@ async def stream_chat_post( return # Read from the subscriber queue and yield to SSE + logger.info( + "[TIMING] Starting to read from subscriber_queue", + extra={"json_fields": log_meta}, + ) while True: try: chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0) + chunks_yielded += 1 + + if not first_chunk_yielded: + first_chunk_yielded = True + elapsed = time_module.perf_counter() - event_gen_start + logger.info( + f"[TIMING] FIRST CHUNK from queue at {elapsed:.2f}s, " + f"type={type(chunk).__name__}", + extra={ + "json_fields": { + **log_meta, + "chunk_type": type(chunk).__name__, + "elapsed_ms": elapsed * 1000, + } + }, + ) + yield chunk.to_sse() # Check for finish signal if isinstance(chunk, StreamFinish): + total_time = time_module.perf_counter() - event_gen_start + logger.info( + f"[TIMING] StreamFinish received in {total_time:.2f}s; " + f"n_chunks={chunks_yielded}", + extra={ + "json_fields": { + **log_meta, + "chunks_yielded": chunks_yielded, + "total_time_ms": total_time * 1000, + } + }, + ) break except asyncio.TimeoutError: - # Send heartbeat to keep connection alive yield StreamHeartbeat().to_sse() except GeneratorExit: + logger.info( + f"[TIMING] GeneratorExit (client disconnected), chunks={chunks_yielded}", + extra={ + "json_fields": { + **log_meta, + "chunks_yielded": chunks_yielded, + "reason": "client_disconnect", + } + }, + ) pass # Client disconnected - background task continues except Exception as e: - logger.error(f"Error in SSE stream for task {task_id}: {e}") + elapsed = (time_module.perf_counter() - event_gen_start) * 1000 + logger.error( + f"[TIMING] event_generator ERROR after {elapsed:.1f}ms: {e}", + extra={ + "json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)} + }, + ) finally: # Unsubscribe when client disconnects or stream ends to prevent resource leak if subscriber_queue is not None: @@ -357,6 +519,18 @@ async def stream_chat_post( exc_info=True, ) # AI SDK protocol termination - always yield even if unsubscribe fails + total_time = time_module.perf_counter() - event_gen_start + logger.info( + f"[TIMING] event_generator FINISHED in {total_time:.2f}s; " + f"task={task_id}, session={session_id}, n_chunks={chunks_yielded}", + extra={ + "json_fields": { + **log_meta, + "total_time_ms": total_time * 1000, + "chunks_yielded": chunks_yielded, + } + }, + ) yield "data: [DONE]\n\n" return StreamingResponse( @@ -374,63 +548,90 @@ async def stream_chat_post( @router.get( "/sessions/{session_id}/stream", ) -async def stream_chat_get( +async def resume_session_stream( session_id: str, - message: Annotated[str, Query(min_length=1, max_length=10000)], user_id: str | None = Depends(auth.get_user_id), - is_user_message: bool = Query(default=True), ): """ - Stream chat responses for a session (GET - legacy endpoint). + Resume an active stream for a session. - Streams the AI/completion responses in real time over Server-Sent Events (SSE), including: - - Text fragments as they are generated - - Tool call UI elements (if invoked) - - Tool execution results + Called by the AI SDK's ``useChat(resume: true)`` on page load. + Checks for an active (in-progress) task on the session and either replays + the full SSE stream or returns 204 No Content if nothing is running. Args: - session_id: The chat session identifier to associate with the streamed messages. - message: The user's new message to process. + session_id: The chat session identifier. user_id: Optional authenticated user ID. - is_user_message: Whether the message is a user message. - Returns: - StreamingResponse: SSE-formatted response chunks. + Returns: + StreamingResponse (SSE) when an active stream exists, + or 204 No Content when there is nothing to resume. """ - session = await _validate_and_get_session(session_id, user_id) + import asyncio + + active_task, _last_id = await stream_registry.get_active_task_for_session( + session_id, user_id + ) + + if not active_task: + return Response(status_code=204) + + subscriber_queue = await stream_registry.subscribe_to_task( + task_id=active_task.task_id, + user_id=user_id, + last_message_id="0-0", # Full replay so useChat rebuilds the message + ) + + if subscriber_queue is None: + return Response(status_code=204) async def event_generator() -> AsyncGenerator[str, None]: chunk_count = 0 first_chunk_type: str | None = None - async for chunk in chat_service.stream_chat_completion( - session_id, - message, - is_user_message=is_user_message, - user_id=user_id, - session=session, # Pass pre-fetched session to avoid double-fetch - ): - if chunk_count < 3: - logger.info( - "Chat stream chunk", - extra={ - "session_id": session_id, - "chunk_type": str(chunk.type), - }, + try: + while True: + try: + chunk = await asyncio.wait_for(subscriber_queue.get(), timeout=30.0) + if chunk_count < 3: + logger.info( + "Resume stream chunk", + extra={ + "session_id": session_id, + "chunk_type": str(chunk.type), + }, + ) + if not first_chunk_type: + first_chunk_type = str(chunk.type) + chunk_count += 1 + yield chunk.to_sse() + + if isinstance(chunk, StreamFinish): + break + except asyncio.TimeoutError: + yield StreamHeartbeat().to_sse() + except GeneratorExit: + pass + except Exception as e: + logger.error(f"Error in resume stream for session {session_id}: {e}") + finally: + try: + await stream_registry.unsubscribe_from_task( + active_task.task_id, subscriber_queue ) - if not first_chunk_type: - first_chunk_type = str(chunk.type) - chunk_count += 1 - yield chunk.to_sse() - logger.info( - "Chat stream completed", - extra={ - "session_id": session_id, - "chunk_count": chunk_count, - "first_chunk_type": first_chunk_type, - }, - ) - # AI SDK protocol termination - yield "data: [DONE]\n\n" + except Exception as unsub_err: + logger.error( + f"Error unsubscribing from task {active_task.task_id}: {unsub_err}", + exc_info=True, + ) + logger.info( + "Resume stream completed", + extra={ + "session_id": session_id, + "n_chunks": chunk_count, + "first_chunk_type": first_chunk_type, + }, + ) + yield "data: [DONE]\n\n" return StreamingResponse( event_generator(), @@ -438,8 +639,8 @@ async def stream_chat_get( headers={ "Cache-Control": "no-cache", "Connection": "keep-alive", - "X-Accel-Buffering": "no", # Disable nginx buffering - "x-vercel-ai-ui-message-stream": "v1", # AI SDK protocol header + "X-Accel-Buffering": "no", + "x-vercel-ai-ui-message-stream": "v1", }, ) @@ -751,3 +952,42 @@ async def health_check() -> dict: "service": "chat", "version": "0.1.0", } + + +# ========== Schema Export (for OpenAPI / Orval codegen) ========== + +ToolResponseUnion = ( + AgentsFoundResponse + | NoResultsResponse + | AgentDetailsResponse + | SetupRequirementsResponse + | ExecutionStartedResponse + | NeedLoginResponse + | ErrorResponse + | InputValidationErrorResponse + | AgentOutputResponse + | UnderstandingUpdatedResponse + | AgentPreviewResponse + | AgentSavedResponse + | ClarificationNeededResponse + | BlockListResponse + | BlockOutputResponse + | DocSearchResultsResponse + | DocPageResponse + | OperationStartedResponse + | OperationPendingResponse + | OperationInProgressResponse +) + + +@router.get( + "/schema/tool-responses", + response_model=ToolResponseUnion, + include_in_schema=True, + summary="[Dummy] Tool response type export for codegen", + description="This endpoint is not meant to be called. It exists solely to " + "expose tool response models in the OpenAPI schema for frontend codegen.", +) +async def _tool_response_schema() -> ToolResponseUnion: # type: ignore[return] + """Never called at runtime. Exists only so Orval generates TS types.""" + raise HTTPException(status_code=501, detail="Schema-only endpoint") diff --git a/autogpt_platform/backend/backend/api/features/chat/service.py b/autogpt_platform/backend/backend/api/features/chat/service.py index 06da6bdf2b..193566ea01 100644 --- a/autogpt_platform/backend/backend/api/features/chat/service.py +++ b/autogpt_platform/backend/backend/api/features/chat/service.py @@ -52,8 +52,10 @@ from .response_model import ( StreamBaseResponse, StreamError, StreamFinish, + StreamFinishStep, StreamHeartbeat, StreamStart, + StreamStartStep, StreamTextDelta, StreamTextEnd, StreamTextStart, @@ -351,6 +353,10 @@ async def stream_chat_completion( retry_count: int = 0, session: ChatSession | None = None, context: dict[str, str] | None = None, # {url: str, content: str} + _continuation_message_id: ( + str | None + ) = None, # Internal: reuse message ID for tool call continuations + _task_id: str | None = None, # Internal: task ID for SSE reconnection support ) -> AsyncGenerator[StreamBaseResponse, None]: """Main entry point for streaming chat completions with database handling. @@ -371,21 +377,45 @@ async def stream_chat_completion( ValueError: If max_context_messages is exceeded """ + completion_start = time.monotonic() + + # Build log metadata for structured logging + log_meta = {"component": "ChatService", "session_id": session_id} + if user_id: + log_meta["user_id"] = user_id + logger.info( - f"Streaming chat completion for session {session_id} for message {message} and user id {user_id}. Message is user message: {is_user_message}" + f"[TIMING] stream_chat_completion STARTED, session={session_id}, user={user_id}, " + f"message_len={len(message) if message else 0}, is_user={is_user_message}", + extra={ + "json_fields": { + **log_meta, + "message_len": len(message) if message else 0, + "is_user_message": is_user_message, + } + }, ) # Only fetch from Redis if session not provided (initial call) if session is None: + fetch_start = time.monotonic() session = await get_chat_session(session_id, user_id) + fetch_time = (time.monotonic() - fetch_start) * 1000 logger.info( - f"Fetched session from Redis: {session.session_id if session else 'None'}, " - f"message_count={len(session.messages) if session else 0}" + f"[TIMING] get_chat_session took {fetch_time:.1f}ms, " + f"n_messages={len(session.messages) if session else 0}", + extra={ + "json_fields": { + **log_meta, + "duration_ms": fetch_time, + "n_messages": len(session.messages) if session else 0, + } + }, ) else: logger.info( - f"Using provided session object: {session.session_id}, " - f"message_count={len(session.messages)}" + f"[TIMING] Using provided session, messages={len(session.messages)}", + extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}}, ) if not session: @@ -406,17 +436,25 @@ async def stream_chat_completion( # Track user message in PostHog if is_user_message: + posthog_start = time.monotonic() track_user_message( user_id=user_id, session_id=session_id, message_length=len(message), ) + posthog_time = (time.monotonic() - posthog_start) * 1000 + logger.info( + f"[TIMING] track_user_message took {posthog_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": posthog_time}}, + ) - logger.info( - f"Upserting session: {session.session_id} with user id {session.user_id}, " - f"message_count={len(session.messages)}" - ) + upsert_start = time.monotonic() session = await upsert_chat_session(session) + upsert_time = (time.monotonic() - upsert_start) * 1000 + logger.info( + f"[TIMING] upsert_chat_session took {upsert_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": upsert_time}}, + ) assert session, "Session not found" # Generate title for new sessions on first user message (non-blocking) @@ -454,7 +492,13 @@ async def stream_chat_completion( asyncio.create_task(_update_title()) # Build system prompt with business understanding + prompt_start = time.monotonic() system_prompt, understanding = await _build_system_prompt(user_id) + prompt_time = (time.monotonic() - prompt_start) * 1000 + logger.info( + f"[TIMING] _build_system_prompt took {prompt_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": prompt_time}}, + ) # Initialize variables for streaming assistant_response = ChatMessage( @@ -479,13 +523,27 @@ async def stream_chat_completion( # Generate unique IDs for AI SDK protocol import uuid as uuid_module - message_id = str(uuid_module.uuid4()) + is_continuation = _continuation_message_id is not None + message_id = _continuation_message_id or str(uuid_module.uuid4()) text_block_id = str(uuid_module.uuid4()) - # Yield message start - yield StreamStart(messageId=message_id) + # Only yield message start for the initial call, not for continuations. + setup_time = (time.monotonic() - completion_start) * 1000 + logger.info( + f"[TIMING] Setup complete, yielding StreamStart at {setup_time:.1f}ms", + extra={"json_fields": {**log_meta, "setup_time_ms": setup_time}}, + ) + if not is_continuation: + yield StreamStart(messageId=message_id, taskId=_task_id) + + # Emit start-step before each LLM call (AI SDK uses this to add step boundaries) + yield StreamStartStep() try: + logger.info( + "[TIMING] Calling _stream_chat_chunks", + extra={"json_fields": log_meta}, + ) async for chunk in _stream_chat_chunks( session=session, tools=tools, @@ -585,6 +643,10 @@ async def stream_chat_completion( ) yield chunk elif isinstance(chunk, StreamFinish): + if has_done_tool_call: + # Tool calls happened — close the step but don't send message-level finish. + # The continuation will open a new step, and finish will come at the end. + yield StreamFinishStep() if not has_done_tool_call: # Emit text-end before finish if we received text but haven't closed it if has_received_text and not text_streaming_ended: @@ -616,6 +678,8 @@ async def stream_chat_completion( has_saved_assistant_message = True has_yielded_end = True + # Emit finish-step before finish (resets AI SDK text/reasoning state) + yield StreamFinishStep() yield chunk elif isinstance(chunk, StreamError): has_yielded_error = True @@ -665,6 +729,10 @@ async def stream_chat_completion( logger.info( f"Retryable error encountered. Attempt {retry_count + 1}/{config.max_retries}" ) + # Close the current step before retrying so the recursive call's + # StreamStartStep doesn't produce unbalanced step events. + if not has_yielded_end: + yield StreamFinishStep() should_retry = True else: # Non-retryable error or max retries exceeded @@ -700,6 +768,7 @@ async def stream_chat_completion( error_response = StreamError(errorText=error_message) yield error_response if not has_yielded_end: + yield StreamFinishStep() yield StreamFinish() return @@ -714,6 +783,8 @@ async def stream_chat_completion( retry_count=retry_count + 1, session=session, context=context, + _continuation_message_id=message_id, # Reuse message ID since start was already sent + _task_id=_task_id, ): yield chunk return # Exit after retry to avoid double-saving in finally block @@ -729,9 +800,13 @@ async def stream_chat_completion( # Build the messages list in the correct order messages_to_save: list[ChatMessage] = [] - # Add assistant message with tool_calls if any + # Add assistant message with tool_calls if any. + # Use extend (not assign) to preserve tool_calls already added by + # _yield_tool_call for long-running tools. if accumulated_tool_calls: - assistant_response.tool_calls = accumulated_tool_calls + if not assistant_response.tool_calls: + assistant_response.tool_calls = [] + assistant_response.tool_calls.extend(accumulated_tool_calls) logger.info( f"Added {len(accumulated_tool_calls)} tool calls to assistant message" ) @@ -783,6 +858,8 @@ async def stream_chat_completion( session=session, # Pass session object to avoid Redis refetch context=context, tool_call_response=str(tool_response_messages), + _continuation_message_id=message_id, # Reuse message ID to avoid duplicates + _task_id=_task_id, ): yield chunk @@ -893,9 +970,21 @@ async def _stream_chat_chunks( SSE formatted JSON response objects """ + import time as time_module + + stream_chunks_start = time_module.perf_counter() model = config.model - logger.info("Starting pure chat stream") + # Build log metadata for structured logging + log_meta = {"component": "ChatService", "session_id": session.session_id} + if session.user_id: + log_meta["user_id"] = session.user_id + + logger.info( + f"[TIMING] _stream_chat_chunks STARTED, session={session.session_id}, " + f"user={session.user_id}, n_messages={len(session.messages)}", + extra={"json_fields": {**log_meta, "n_messages": len(session.messages)}}, + ) messages = session.to_openai_messages() if system_prompt: @@ -906,12 +995,18 @@ async def _stream_chat_chunks( messages = [system_message] + messages # Apply context window management + context_start = time_module.perf_counter() context_result = await _manage_context_window( messages=messages, model=model, api_key=config.api_key, base_url=config.base_url, ) + context_time = (time_module.perf_counter() - context_start) * 1000 + logger.info( + f"[TIMING] _manage_context_window took {context_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": context_time}}, + ) if context_result.error: if "System prompt dropped" in context_result.error: @@ -946,9 +1041,19 @@ async def _stream_chat_chunks( while retry_count <= MAX_RETRIES: try: + elapsed = (time_module.perf_counter() - stream_chunks_start) * 1000 + retry_info = ( + f" (retry {retry_count}/{MAX_RETRIES})" if retry_count > 0 else "" + ) logger.info( - f"Creating OpenAI chat completion stream..." - f"{f' (retry {retry_count}/{MAX_RETRIES})' if retry_count > 0 else ''}" + f"[TIMING] Creating OpenAI stream at {elapsed:.1f}ms{retry_info}", + extra={ + "json_fields": { + **log_meta, + "elapsed_ms": elapsed, + "retry_count": retry_count, + } + }, ) # Build extra_body for OpenRouter tracing and PostHog analytics @@ -965,6 +1070,11 @@ async def _stream_chat_chunks( :128 ] # OpenRouter limit + # Enable adaptive thinking for Anthropic models via OpenRouter + if config.thinking_enabled and "anthropic" in model.lower(): + extra_body["reasoning"] = {"enabled": True} + + api_call_start = time_module.perf_counter() stream = await client.chat.completions.create( model=model, messages=cast(list[ChatCompletionMessageParam], messages), @@ -974,6 +1084,11 @@ async def _stream_chat_chunks( stream_options=ChatCompletionStreamOptionsParam(include_usage=True), extra_body=extra_body, ) + api_init_time = (time_module.perf_counter() - api_call_start) * 1000 + logger.info( + f"[TIMING] OpenAI stream object returned in {api_init_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": api_init_time}}, + ) # Variables to accumulate tool calls tool_calls: list[dict[str, Any]] = [] @@ -984,10 +1099,13 @@ async def _stream_chat_chunks( # Track if we've started the text block text_started = False + first_content_chunk = True + chunk_count = 0 # Process the stream chunk: ChatCompletionChunk async for chunk in stream: + chunk_count += 1 if chunk.usage: yield StreamUsage( promptTokens=chunk.usage.prompt_tokens, @@ -1010,6 +1128,23 @@ async def _stream_chat_chunks( if not text_started and text_block_id: yield StreamTextStart(id=text_block_id) text_started = True + # Log timing for first content chunk + if first_content_chunk: + first_content_chunk = False + ttfc = ( + time_module.perf_counter() - api_call_start + ) * 1000 + logger.info( + f"[TIMING] FIRST CONTENT CHUNK at {ttfc:.1f}ms " + f"(since API call), n_chunks={chunk_count}", + extra={ + "json_fields": { + **log_meta, + "time_to_first_chunk_ms": ttfc, + "n_chunks": chunk_count, + } + }, + ) # Stream the text delta text_response = StreamTextDelta( id=text_block_id or "", @@ -1066,7 +1201,21 @@ async def _stream_chat_chunks( toolName=tool_calls[idx]["function"]["name"], ) emitted_start_for_idx.add(idx) - logger.info(f"Stream complete. Finish reason: {finish_reason}") + stream_duration = time_module.perf_counter() - api_call_start + logger.info( + f"[TIMING] OpenAI stream COMPLETE, finish_reason={finish_reason}, " + f"duration={stream_duration:.2f}s, " + f"n_chunks={chunk_count}, n_tool_calls={len(tool_calls)}", + extra={ + "json_fields": { + **log_meta, + "stream_duration_ms": stream_duration * 1000, + "finish_reason": finish_reason, + "n_chunks": chunk_count, + "n_tool_calls": len(tool_calls), + } + }, + ) # Yield all accumulated tool calls after the stream is complete # This ensures all tool call arguments have been fully received @@ -1086,6 +1235,12 @@ async def _stream_chat_chunks( # Re-raise to trigger retry logic in the parent function raise + total_time = (time_module.perf_counter() - stream_chunks_start) * 1000 + logger.info( + f"[TIMING] _stream_chat_chunks COMPLETED in {total_time/1000:.1f}s; " + f"session={session.session_id}, user={session.user_id}", + extra={"json_fields": {**log_meta, "total_time_ms": total_time}}, + ) yield StreamFinish() return except Exception as e: @@ -1253,13 +1408,9 @@ async def _yield_tool_call( operation_id=operation_id, ) - # Save assistant message with tool_call FIRST (required by LLM) - assistant_message = ChatMessage( - role="assistant", - content="", - tool_calls=[tool_calls[yield_idx]], - ) - session.messages.append(assistant_message) + # Attach the tool_call to the current turn's assistant message + # (or create one if this is a tool-only response with no text). + session.add_tool_call_to_current_turn(tool_calls[yield_idx]) # Then save pending tool result pending_message = ChatMessage( @@ -1565,6 +1716,7 @@ async def _execute_long_running_tool_with_streaming( task_id, StreamError(errorText=str(e)), ) + await stream_registry.publish_chunk(task_id, StreamFinishStep()) await stream_registry.publish_chunk(task_id, StreamFinish()) await _update_pending_operation( @@ -1681,6 +1833,10 @@ async def _generate_llm_continuation( if session_id: extra_body["session_id"] = session_id[:128] + # Enable adaptive thinking for Anthropic models via OpenRouter + if config.thinking_enabled and "anthropic" in config.model.lower(): + extra_body["reasoning"] = {"enabled": True} + retry_count = 0 last_error: Exception | None = None response = None @@ -1811,6 +1967,10 @@ async def _generate_llm_continuation_with_streaming( if session_id: extra_body["session_id"] = session_id[:128] + # Enable adaptive thinking for Anthropic models via OpenRouter + if config.thinking_enabled and "anthropic" in config.model.lower(): + extra_body["reasoning"] = {"enabled": True} + # Make streaming LLM call (no tools - just text response) from typing import cast @@ -1822,6 +1982,7 @@ async def _generate_llm_continuation_with_streaming( # Publish start event await stream_registry.publish_chunk(task_id, StreamStart(messageId=message_id)) + await stream_registry.publish_chunk(task_id, StreamStartStep()) await stream_registry.publish_chunk(task_id, StreamTextStart(id=text_block_id)) # Stream the response @@ -1845,6 +2006,7 @@ async def _generate_llm_continuation_with_streaming( # Publish end events await stream_registry.publish_chunk(task_id, StreamTextEnd(id=text_block_id)) + await stream_registry.publish_chunk(task_id, StreamFinishStep()) if assistant_content: # Reload session from DB to avoid race condition with user messages @@ -1886,4 +2048,5 @@ async def _generate_llm_continuation_with_streaming( task_id, StreamError(errorText=f"Failed to generate response: {e}"), ) + await stream_registry.publish_chunk(task_id, StreamFinishStep()) await stream_registry.publish_chunk(task_id, StreamFinish()) diff --git a/autogpt_platform/backend/backend/api/features/chat/stream_registry.py b/autogpt_platform/backend/backend/api/features/chat/stream_registry.py index 88a5023e2b..abc34b1fc9 100644 --- a/autogpt_platform/backend/backend/api/features/chat/stream_registry.py +++ b/autogpt_platform/backend/backend/api/features/chat/stream_registry.py @@ -104,6 +104,24 @@ async def create_task( Returns: The created ActiveTask instance (metadata only) """ + import time + + start_time = time.perf_counter() + + # Build log metadata for structured logging + log_meta = { + "component": "StreamRegistry", + "task_id": task_id, + "session_id": session_id, + } + if user_id: + log_meta["user_id"] = user_id + + logger.info( + f"[TIMING] create_task STARTED, task={task_id}, session={session_id}, user={user_id}", + extra={"json_fields": log_meta}, + ) + task = ActiveTask( task_id=task_id, session_id=session_id, @@ -114,10 +132,18 @@ async def create_task( ) # Store metadata in Redis + redis_start = time.perf_counter() redis = await get_redis_async() + redis_time = (time.perf_counter() - redis_start) * 1000 + logger.info( + f"[TIMING] get_redis_async took {redis_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": redis_time}}, + ) + meta_key = _get_task_meta_key(task_id) op_key = _get_operation_mapping_key(operation_id) + hset_start = time.perf_counter() await redis.hset( # type: ignore[misc] meta_key, mapping={ @@ -131,12 +157,22 @@ async def create_task( "created_at": task.created_at.isoformat(), }, ) + hset_time = (time.perf_counter() - hset_start) * 1000 + logger.info( + f"[TIMING] redis.hset took {hset_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": hset_time}}, + ) + await redis.expire(meta_key, config.stream_ttl) # Create operation_id -> task_id mapping for webhook lookups await redis.set(op_key, task_id, ex=config.stream_ttl) - logger.debug(f"Created task {task_id} for session {session_id}") + total_time = (time.perf_counter() - start_time) * 1000 + logger.info( + f"[TIMING] create_task COMPLETED in {total_time:.1f}ms; task={task_id}, session={session_id}", + extra={"json_fields": {**log_meta, "total_time_ms": total_time}}, + ) return task @@ -156,26 +192,60 @@ async def publish_chunk( Returns: The Redis Stream message ID """ + import time + + start_time = time.perf_counter() + chunk_type = type(chunk).__name__ chunk_json = chunk.model_dump_json() message_id = "0-0" + # Build log metadata + log_meta = { + "component": "StreamRegistry", + "task_id": task_id, + "chunk_type": chunk_type, + } + try: redis = await get_redis_async() stream_key = _get_task_stream_key(task_id) # Write to Redis Stream for persistence and real-time delivery + xadd_start = time.perf_counter() raw_id = await redis.xadd( stream_key, {"data": chunk_json}, maxlen=config.stream_max_length, ) + xadd_time = (time.perf_counter() - xadd_start) * 1000 message_id = raw_id if isinstance(raw_id, str) else raw_id.decode() # Set TTL on stream to match task metadata TTL await redis.expire(stream_key, config.stream_ttl) + + total_time = (time.perf_counter() - start_time) * 1000 + # Only log timing for significant chunks or slow operations + if ( + chunk_type + in ("StreamStart", "StreamFinish", "StreamTextStart", "StreamTextEnd") + or total_time > 50 + ): + logger.info( + f"[TIMING] publish_chunk {chunk_type} in {total_time:.1f}ms (xadd={xadd_time:.1f}ms)", + extra={ + "json_fields": { + **log_meta, + "total_time_ms": total_time, + "xadd_time_ms": xadd_time, + "message_id": message_id, + } + }, + ) except Exception as e: + elapsed = (time.perf_counter() - start_time) * 1000 logger.error( - f"Failed to publish chunk for task {task_id}: {e}", + f"[TIMING] Failed to publish chunk {chunk_type} after {elapsed:.1f}ms: {e}", + extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}}, exc_info=True, ) @@ -200,24 +270,61 @@ async def subscribe_to_task( An asyncio Queue that will receive stream chunks, or None if task not found or user doesn't have access """ + import time + + start_time = time.perf_counter() + + # Build log metadata + log_meta = {"component": "StreamRegistry", "task_id": task_id} + if user_id: + log_meta["user_id"] = user_id + + logger.info( + f"[TIMING] subscribe_to_task STARTED, task={task_id}, user={user_id}, last_msg={last_message_id}", + extra={"json_fields": {**log_meta, "last_message_id": last_message_id}}, + ) + + redis_start = time.perf_counter() redis = await get_redis_async() meta_key = _get_task_meta_key(task_id) meta: dict[Any, Any] = await redis.hgetall(meta_key) # type: ignore[misc] + hgetall_time = (time.perf_counter() - redis_start) * 1000 + logger.info( + f"[TIMING] Redis hgetall took {hgetall_time:.1f}ms", + extra={"json_fields": {**log_meta, "duration_ms": hgetall_time}}, + ) if not meta: - logger.debug(f"Task {task_id} not found in Redis") + elapsed = (time.perf_counter() - start_time) * 1000 + logger.info( + f"[TIMING] Task not found in Redis after {elapsed:.1f}ms", + extra={ + "json_fields": { + **log_meta, + "elapsed_ms": elapsed, + "reason": "task_not_found", + } + }, + ) return None # Note: Redis client uses decode_responses=True, so keys are strings task_status = meta.get("status", "") task_user_id = meta.get("user_id", "") or None + log_meta["session_id"] = meta.get("session_id", "") # Validate ownership - if task has an owner, requester must match if task_user_id: if user_id != task_user_id: logger.warning( - f"User {user_id} denied access to task {task_id} " - f"owned by {task_user_id}" + f"[TIMING] Access denied: user {user_id} tried to access task owned by {task_user_id}", + extra={ + "json_fields": { + **log_meta, + "task_owner": task_user_id, + "reason": "access_denied", + } + }, ) return None @@ -225,7 +332,19 @@ async def subscribe_to_task( stream_key = _get_task_stream_key(task_id) # Step 1: Replay messages from Redis Stream + xread_start = time.perf_counter() messages = await redis.xread({stream_key: last_message_id}, block=0, count=1000) + xread_time = (time.perf_counter() - xread_start) * 1000 + logger.info( + f"[TIMING] Redis xread (replay) took {xread_time:.1f}ms, status={task_status}", + extra={ + "json_fields": { + **log_meta, + "duration_ms": xread_time, + "task_status": task_status, + } + }, + ) replayed_count = 0 replay_last_id = last_message_id @@ -244,19 +363,48 @@ async def subscribe_to_task( except Exception as e: logger.warning(f"Failed to replay message: {e}") - logger.debug(f"Task {task_id}: replayed {replayed_count} messages") + logger.info( + f"[TIMING] Replayed {replayed_count} messages, last_id={replay_last_id}", + extra={ + "json_fields": { + **log_meta, + "n_messages_replayed": replayed_count, + "replay_last_id": replay_last_id, + } + }, + ) # Step 2: If task is still running, start stream listener for live updates if task_status == "running": + logger.info( + "[TIMING] Task still running, starting _stream_listener", + extra={"json_fields": {**log_meta, "task_status": task_status}}, + ) listener_task = asyncio.create_task( - _stream_listener(task_id, subscriber_queue, replay_last_id) + _stream_listener(task_id, subscriber_queue, replay_last_id, log_meta) ) # Track listener task for cleanup on unsubscribe _listener_tasks[id(subscriber_queue)] = (task_id, listener_task) else: # Task is completed/failed - add finish marker + logger.info( + f"[TIMING] Task already {task_status}, adding StreamFinish", + extra={"json_fields": {**log_meta, "task_status": task_status}}, + ) await subscriber_queue.put(StreamFinish()) + total_time = (time.perf_counter() - start_time) * 1000 + logger.info( + f"[TIMING] subscribe_to_task COMPLETED in {total_time:.1f}ms; task={task_id}, " + f"n_messages_replayed={replayed_count}", + extra={ + "json_fields": { + **log_meta, + "total_time_ms": total_time, + "n_messages_replayed": replayed_count, + } + }, + ) return subscriber_queue @@ -264,6 +412,7 @@ async def _stream_listener( task_id: str, subscriber_queue: asyncio.Queue[StreamBaseResponse], last_replayed_id: str, + log_meta: dict | None = None, ) -> None: """Listen to Redis Stream for new messages using blocking XREAD. @@ -274,10 +423,27 @@ async def _stream_listener( task_id: Task ID to listen for subscriber_queue: Queue to deliver messages to last_replayed_id: Last message ID from replay (continue from here) + log_meta: Structured logging metadata """ + import time + + start_time = time.perf_counter() + + # Use provided log_meta or build minimal one + if log_meta is None: + log_meta = {"component": "StreamRegistry", "task_id": task_id} + + logger.info( + f"[TIMING] _stream_listener STARTED, task={task_id}, last_id={last_replayed_id}", + extra={"json_fields": {**log_meta, "last_replayed_id": last_replayed_id}}, + ) + queue_id = id(subscriber_queue) # Track the last successfully delivered message ID for recovery hints last_delivered_id = last_replayed_id + messages_delivered = 0 + first_message_time = None + xread_count = 0 try: redis = await get_redis_async() @@ -287,9 +453,39 @@ async def _stream_listener( while True: # Block for up to 30 seconds waiting for new messages # This allows periodic checking if task is still running + xread_start = time.perf_counter() + xread_count += 1 messages = await redis.xread( {stream_key: current_id}, block=30000, count=100 ) + xread_time = (time.perf_counter() - xread_start) * 1000 + + if messages: + msg_count = sum(len(msgs) for _, msgs in messages) + logger.info( + f"[TIMING] xread #{xread_count} returned {msg_count} messages in {xread_time:.1f}ms", + extra={ + "json_fields": { + **log_meta, + "xread_count": xread_count, + "n_messages": msg_count, + "duration_ms": xread_time, + } + }, + ) + elif xread_time > 1000: + # Only log timeouts (30s blocking) + logger.info( + f"[TIMING] xread #{xread_count} timeout after {xread_time:.1f}ms", + extra={ + "json_fields": { + **log_meta, + "xread_count": xread_count, + "duration_ms": xread_time, + "reason": "timeout", + } + }, + ) if not messages: # Timeout - check if task is still running @@ -326,10 +522,30 @@ async def _stream_listener( ) # Update last delivered ID on successful delivery last_delivered_id = current_id + messages_delivered += 1 + if first_message_time is None: + first_message_time = time.perf_counter() + elapsed = (first_message_time - start_time) * 1000 + logger.info( + f"[TIMING] FIRST live message at {elapsed:.1f}ms, type={type(chunk).__name__}", + extra={ + "json_fields": { + **log_meta, + "elapsed_ms": elapsed, + "chunk_type": type(chunk).__name__, + } + }, + ) except asyncio.TimeoutError: logger.warning( - f"Subscriber queue full for task {task_id}, " - f"message delivery timed out after {QUEUE_PUT_TIMEOUT}s" + f"[TIMING] Subscriber queue full, delivery timed out after {QUEUE_PUT_TIMEOUT}s", + extra={ + "json_fields": { + **log_meta, + "timeout_s": QUEUE_PUT_TIMEOUT, + "reason": "queue_full", + } + }, ) # Send overflow error with recovery info try: @@ -351,15 +567,44 @@ async def _stream_listener( # Stop listening on finish if isinstance(chunk, StreamFinish): + total_time = (time.perf_counter() - start_time) * 1000 + logger.info( + f"[TIMING] StreamFinish received in {total_time/1000:.1f}s; delivered={messages_delivered}", + extra={ + "json_fields": { + **log_meta, + "total_time_ms": total_time, + "messages_delivered": messages_delivered, + } + }, + ) return except Exception as e: - logger.warning(f"Error processing stream message: {e}") + logger.warning( + f"Error processing stream message: {e}", + extra={"json_fields": {**log_meta, "error": str(e)}}, + ) except asyncio.CancelledError: - logger.debug(f"Stream listener cancelled for task {task_id}") + elapsed = (time.perf_counter() - start_time) * 1000 + logger.info( + f"[TIMING] _stream_listener CANCELLED after {elapsed:.1f}ms, delivered={messages_delivered}", + extra={ + "json_fields": { + **log_meta, + "elapsed_ms": elapsed, + "messages_delivered": messages_delivered, + "reason": "cancelled", + } + }, + ) raise # Re-raise to propagate cancellation except Exception as e: - logger.error(f"Stream listener error for task {task_id}: {e}") + elapsed = (time.perf_counter() - start_time) * 1000 + logger.error( + f"[TIMING] _stream_listener ERROR after {elapsed:.1f}ms: {e}", + extra={"json_fields": {**log_meta, "elapsed_ms": elapsed, "error": str(e)}}, + ) # On error, send finish to unblock subscriber try: await asyncio.wait_for( @@ -368,10 +613,24 @@ async def _stream_listener( ) except (asyncio.TimeoutError, asyncio.QueueFull): logger.warning( - f"Could not deliver finish event for task {task_id} after error" + "Could not deliver finish event after error", + extra={"json_fields": log_meta}, ) finally: # Clean up listener task mapping on exit + total_time = (time.perf_counter() - start_time) * 1000 + logger.info( + f"[TIMING] _stream_listener FINISHED in {total_time/1000:.1f}s; task={task_id}, " + f"delivered={messages_delivered}, xread_count={xread_count}", + extra={ + "json_fields": { + **log_meta, + "total_time_ms": total_time, + "messages_delivered": messages_delivered, + "xread_count": xread_count, + } + }, + ) _listener_tasks.pop(queue_id, None) @@ -598,8 +857,10 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None: ResponseType, StreamError, StreamFinish, + StreamFinishStep, StreamHeartbeat, StreamStart, + StreamStartStep, StreamTextDelta, StreamTextEnd, StreamTextStart, @@ -613,6 +874,8 @@ def _reconstruct_chunk(chunk_data: dict) -> StreamBaseResponse | None: type_to_class: dict[str, type[StreamBaseResponse]] = { ResponseType.START.value: StreamStart, ResponseType.FINISH.value: StreamFinish, + ResponseType.START_STEP.value: StreamStartStep, + ResponseType.FINISH_STEP.value: StreamFinishStep, ResponseType.TEXT_START.value: StreamTextStart, ResponseType.TEXT_DELTA.value: StreamTextDelta, ResponseType.TEXT_END.value: StreamTextEnd, diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py b/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py new file mode 100644 index 0000000000..cf53605ac0 --- /dev/null +++ b/autogpt_platform/backend/backend/api/features/chat/tools/helpers.py @@ -0,0 +1,29 @@ +"""Shared helpers for chat tools.""" + +from typing import Any + + +def get_inputs_from_schema( + input_schema: dict[str, Any], + exclude_fields: set[str] | None = None, +) -> list[dict[str, Any]]: + """Extract input field info from JSON schema.""" + if not isinstance(input_schema, dict): + return [] + + exclude = exclude_fields or set() + properties = input_schema.get("properties", {}) + required = set(input_schema.get("required", [])) + + return [ + { + "name": name, + "title": schema.get("title", name), + "type": schema.get("type", "string"), + "description": schema.get("description", ""), + "required": name in required, + "default": schema.get("default"), + } + for name, schema in properties.items() + if name not in exclude + ] diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py index 73d4cf81f2..a9f19bcf62 100644 --- a/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py +++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py @@ -24,6 +24,7 @@ from backend.util.timezone_utils import ( ) from .base import BaseTool +from .helpers import get_inputs_from_schema from .models import ( AgentDetails, AgentDetailsResponse, @@ -261,7 +262,7 @@ class RunAgentTool(BaseTool): ), requirements={ "credentials": requirements_creds_list, - "inputs": self._get_inputs_list(graph.input_schema), + "inputs": get_inputs_from_schema(graph.input_schema), "execution_modes": self._get_execution_modes(graph), }, ), @@ -369,22 +370,6 @@ class RunAgentTool(BaseTool): session_id=session_id, ) - def _get_inputs_list(self, input_schema: dict[str, Any]) -> list[dict[str, Any]]: - """Extract inputs list from schema.""" - inputs_list = [] - if isinstance(input_schema, dict) and "properties" in input_schema: - for field_name, field_schema in input_schema["properties"].items(): - inputs_list.append( - { - "name": field_name, - "title": field_schema.get("title", field_name), - "type": field_schema.get("type", "string"), - "description": field_schema.get("description", ""), - "required": field_name in input_schema.get("required", []), - } - ) - return inputs_list - def _get_execution_modes(self, graph: GraphModel) -> list[str]: """Get available execution modes for the graph.""" trigger_info = graph.trigger_setup_info @@ -398,7 +383,7 @@ class RunAgentTool(BaseTool): suffix: str, ) -> str: """Build a message describing available inputs for an agent.""" - inputs_list = self._get_inputs_list(graph.input_schema) + inputs_list = get_inputs_from_schema(graph.input_schema) required_names = [i["name"] for i in inputs_list if i["required"]] optional_names = [i["name"] for i in inputs_list if not i["required"]] diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py b/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py index 590f81ff23..fc4a470fdd 100644 --- a/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py +++ b/autogpt_platform/backend/backend/api/features/chat/tools/run_block.py @@ -12,14 +12,15 @@ from backend.api.features.chat.tools.find_block import ( COPILOT_EXCLUDED_BLOCK_IDS, COPILOT_EXCLUDED_BLOCK_TYPES, ) -from backend.data.block import get_block +from backend.data.block import AnyBlockSchema, get_block from backend.data.execution import ExecutionContext -from backend.data.model import CredentialsMetaInput +from backend.data.model import CredentialsFieldInfo, CredentialsMetaInput from backend.data.workspace import get_or_create_workspace from backend.integrations.creds_manager import IntegrationCredentialsManager from backend.util.exceptions import BlockError from .base import BaseTool +from .helpers import get_inputs_from_schema from .models import ( BlockOutputResponse, ErrorResponse, @@ -28,7 +29,10 @@ from .models import ( ToolResponseBase, UserReadiness, ) -from .utils import build_missing_credentials_from_field_info +from .utils import ( + build_missing_credentials_from_field_info, + match_credentials_to_requirements, +) logger = logging.getLogger(__name__) @@ -77,91 +81,6 @@ class RunBlockTool(BaseTool): def requires_auth(self) -> bool: return True - async def _check_block_credentials( - self, - user_id: str, - block: Any, - input_data: dict[str, Any] | None = None, - ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]: - """ - Check if user has required credentials for a block. - - Args: - user_id: User ID - block: Block to check credentials for - input_data: Input data for the block (used to determine provider via discriminator) - - Returns: - tuple[matched_credentials, missing_credentials] - """ - matched_credentials: dict[str, CredentialsMetaInput] = {} - missing_credentials: list[CredentialsMetaInput] = [] - input_data = input_data or {} - - # Get credential field info from block's input schema - credentials_fields_info = block.input_schema.get_credentials_fields_info() - - if not credentials_fields_info: - return matched_credentials, missing_credentials - - # Get user's available credentials - creds_manager = IntegrationCredentialsManager() - available_creds = await creds_manager.store.get_all_creds(user_id) - - for field_name, field_info in credentials_fields_info.items(): - effective_field_info = field_info - if field_info.discriminator and field_info.discriminator_mapping: - # Get discriminator from input, falling back to schema default - discriminator_value = input_data.get(field_info.discriminator) - if discriminator_value is None: - field = block.input_schema.model_fields.get( - field_info.discriminator - ) - if field and field.default is not PydanticUndefined: - discriminator_value = field.default - - if ( - discriminator_value - and discriminator_value in field_info.discriminator_mapping - ): - effective_field_info = field_info.discriminate(discriminator_value) - logger.debug( - f"Discriminated provider for {field_name}: " - f"{discriminator_value} -> {effective_field_info.provider}" - ) - - matching_cred = next( - ( - cred - for cred in available_creds - if cred.provider in effective_field_info.provider - and cred.type in effective_field_info.supported_types - ), - None, - ) - - if matching_cred: - matched_credentials[field_name] = CredentialsMetaInput( - id=matching_cred.id, - provider=matching_cred.provider, # type: ignore - type=matching_cred.type, - title=matching_cred.title, - ) - else: - # Create a placeholder for the missing credential - provider = next(iter(effective_field_info.provider), "unknown") - cred_type = next(iter(effective_field_info.supported_types), "api_key") - missing_credentials.append( - CredentialsMetaInput( - id=field_name, - provider=provider, # type: ignore - type=cred_type, # type: ignore - title=field_name.replace("_", " ").title(), - ) - ) - - return matched_credentials, missing_credentials - async def _execute( self, user_id: str | None, @@ -232,8 +151,8 @@ class RunBlockTool(BaseTool): logger.info(f"Executing block {block.name} ({block_id}) for user {user_id}") creds_manager = IntegrationCredentialsManager() - matched_credentials, missing_credentials = await self._check_block_credentials( - user_id, block, input_data + matched_credentials, missing_credentials = ( + await self._resolve_block_credentials(user_id, block, input_data) ) if missing_credentials: @@ -362,29 +281,75 @@ class RunBlockTool(BaseTool): session_id=session_id, ) - def _get_inputs_list(self, block: Any) -> list[dict[str, Any]]: + async def _resolve_block_credentials( + self, + user_id: str, + block: AnyBlockSchema, + input_data: dict[str, Any] | None = None, + ) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]: + """ + Resolve credentials for a block by matching user's available credentials. + + Args: + user_id: User ID + block: Block to resolve credentials for + input_data: Input data for the block (used to determine provider via discriminator) + + Returns: + tuple of (matched_credentials, missing_credentials) - matched credentials + are used for block execution, missing ones indicate setup requirements. + """ + input_data = input_data or {} + requirements = self._resolve_discriminated_credentials(block, input_data) + + if not requirements: + return {}, [] + + return await match_credentials_to_requirements(user_id, requirements) + + def _get_inputs_list(self, block: AnyBlockSchema) -> list[dict[str, Any]]: """Extract non-credential inputs from block schema.""" - inputs_list = [] schema = block.input_schema.jsonschema() - properties = schema.get("properties", {}) - required_fields = set(schema.get("required", [])) - - # Get credential field names to exclude credentials_fields = set(block.input_schema.get_credentials_fields().keys()) + return get_inputs_from_schema(schema, exclude_fields=credentials_fields) - for field_name, field_schema in properties.items(): - # Skip credential fields - if field_name in credentials_fields: - continue + def _resolve_discriminated_credentials( + self, + block: AnyBlockSchema, + input_data: dict[str, Any], + ) -> dict[str, CredentialsFieldInfo]: + """Resolve credential requirements, applying discriminator logic where needed.""" + credentials_fields_info = block.input_schema.get_credentials_fields_info() + if not credentials_fields_info: + return {} - inputs_list.append( - { - "name": field_name, - "title": field_schema.get("title", field_name), - "type": field_schema.get("type", "string"), - "description": field_schema.get("description", ""), - "required": field_name in required_fields, - } - ) + resolved: dict[str, CredentialsFieldInfo] = {} - return inputs_list + for field_name, field_info in credentials_fields_info.items(): + effective_field_info = field_info + + if field_info.discriminator and field_info.discriminator_mapping: + discriminator_value = input_data.get(field_info.discriminator) + if discriminator_value is None: + field = block.input_schema.model_fields.get( + field_info.discriminator + ) + if field and field.default is not PydanticUndefined: + discriminator_value = field.default + + if ( + discriminator_value + and discriminator_value in field_info.discriminator_mapping + ): + effective_field_info = field_info.discriminate(discriminator_value) + # For host-scoped credentials, add the discriminator value + # (e.g., URL) so _credential_is_for_host can match it + effective_field_info.discriminator_values.add(discriminator_value) + logger.debug( + f"Discriminated provider for {field_name}: " + f"{discriminator_value} -> {effective_field_info.provider}" + ) + + resolved[field_name] = effective_field_info + + return resolved diff --git a/autogpt_platform/backend/backend/api/features/chat/tools/utils.py b/autogpt_platform/backend/backend/api/features/chat/tools/utils.py index cda0914809..80a842bf36 100644 --- a/autogpt_platform/backend/backend/api/features/chat/tools/utils.py +++ b/autogpt_platform/backend/backend/api/features/chat/tools/utils.py @@ -8,6 +8,7 @@ from backend.api.features.library import model as library_model from backend.api.features.store import db as store_db from backend.data.graph import GraphModel from backend.data.model import ( + Credentials, CredentialsFieldInfo, CredentialsMetaInput, HostScopedCredentials, @@ -223,6 +224,99 @@ async def get_or_create_library_agent( return library_agents[0] +async def match_credentials_to_requirements( + user_id: str, + requirements: dict[str, CredentialsFieldInfo], +) -> tuple[dict[str, CredentialsMetaInput], list[CredentialsMetaInput]]: + """ + Match user's credentials against a dictionary of credential requirements. + + This is the core matching logic shared by both graph and block credential matching. + """ + matched: dict[str, CredentialsMetaInput] = {} + missing: list[CredentialsMetaInput] = [] + + if not requirements: + return matched, missing + + available_creds = await get_user_credentials(user_id) + + for field_name, field_info in requirements.items(): + matching_cred = find_matching_credential(available_creds, field_info) + + if matching_cred: + try: + matched[field_name] = create_credential_meta_from_match(matching_cred) + except Exception as e: + logger.error( + f"Failed to create CredentialsMetaInput for field '{field_name}': " + f"provider={matching_cred.provider}, type={matching_cred.type}, " + f"credential_id={matching_cred.id}", + exc_info=True, + ) + provider = next(iter(field_info.provider), "unknown") + cred_type = next(iter(field_info.supported_types), "api_key") + missing.append( + CredentialsMetaInput( + id=field_name, + provider=provider, # type: ignore + type=cred_type, # type: ignore + title=f"{field_name} (validation failed: {e})", + ) + ) + else: + provider = next(iter(field_info.provider), "unknown") + cred_type = next(iter(field_info.supported_types), "api_key") + missing.append( + CredentialsMetaInput( + id=field_name, + provider=provider, # type: ignore + type=cred_type, # type: ignore + title=field_name.replace("_", " ").title(), + ) + ) + + return matched, missing + + +async def get_user_credentials(user_id: str) -> list[Credentials]: + """Get all available credentials for a user.""" + creds_manager = IntegrationCredentialsManager() + return await creds_manager.store.get_all_creds(user_id) + + +def find_matching_credential( + available_creds: list[Credentials], + field_info: CredentialsFieldInfo, +) -> Credentials | None: + """Find a credential that matches the required provider, type, scopes, and host.""" + for cred in available_creds: + if cred.provider not in field_info.provider: + continue + if cred.type not in field_info.supported_types: + continue + if cred.type == "oauth2" and not _credential_has_required_scopes( + cred, field_info + ): + continue + if cred.type == "host_scoped" and not _credential_is_for_host(cred, field_info): + continue + return cred + return None + + +def create_credential_meta_from_match( + matching_cred: Credentials, +) -> CredentialsMetaInput: + """Create a CredentialsMetaInput from a matched credential.""" + return CredentialsMetaInput( + id=matching_cred.id, + provider=matching_cred.provider, # type: ignore + type=matching_cred.type, + title=matching_cred.title, + ) + + async def match_user_credentials_to_graph( user_id: str, graph: GraphModel, @@ -331,8 +425,6 @@ def _credential_has_required_scopes( # If no scopes are required, any credential matches if not requirements.required_scopes: return True - - # Check that credential scopes are a superset of required scopes return set(credential.scopes).issuperset(requirements.required_scopes) diff --git a/autogpt_platform/backend/backend/api/features/store/hybrid_search.py b/autogpt_platform/backend/backend/api/features/store/hybrid_search.py index e1b8f402c8..b10bfbcc06 100644 --- a/autogpt_platform/backend/backend/api/features/store/hybrid_search.py +++ b/autogpt_platform/backend/backend/api/features/store/hybrid_search.py @@ -8,6 +8,7 @@ Includes BM25 reranking for improved lexical relevance. import logging import re +import time from dataclasses import dataclass from typing import Any, Literal @@ -362,7 +363,11 @@ async def unified_hybrid_search( LIMIT {limit_param} OFFSET {offset_param} """ - results = await query_raw_with_schema(sql_query, *params) + try: + results = await query_raw_with_schema(sql_query, *params) + except Exception as e: + await _log_vector_error_diagnostics(e) + raise total = results[0]["total_count"] if results else 0 # Apply BM25 reranking @@ -686,7 +691,11 @@ async def hybrid_search( LIMIT {limit_param} OFFSET {offset_param} """ - results = await query_raw_with_schema(sql_query, *params) + try: + results = await query_raw_with_schema(sql_query, *params) + except Exception as e: + await _log_vector_error_diagnostics(e) + raise total = results[0]["total_count"] if results else 0 @@ -718,6 +727,87 @@ async def hybrid_search_simple( return await hybrid_search(query=query, page=page, page_size=page_size) +# ============================================================================ +# Diagnostics +# ============================================================================ + +# Rate limit: only log vector error diagnostics once per this interval +_VECTOR_DIAG_INTERVAL_SECONDS = 60 +_last_vector_diag_time: float = 0 + + +async def _log_vector_error_diagnostics(error: Exception) -> None: + """Log diagnostic info when 'type vector does not exist' error occurs. + + Note: Diagnostic queries use query_raw_with_schema which may run on a different + pooled connection than the one that failed. Session-level search_path can differ, + so these diagnostics show cluster-wide state, not necessarily the failed session. + + Includes rate limiting to avoid log spam - only logs once per minute. + Caller should re-raise the error after calling this function. + """ + global _last_vector_diag_time + + # Check if this is the vector type error + error_str = str(error).lower() + if not ( + "type" in error_str and "vector" in error_str and "does not exist" in error_str + ): + return + + # Rate limit: only log once per interval + now = time.time() + if now - _last_vector_diag_time < _VECTOR_DIAG_INTERVAL_SECONDS: + return + _last_vector_diag_time = now + + try: + diagnostics: dict[str, object] = {} + + try: + search_path_result = await query_raw_with_schema("SHOW search_path") + diagnostics["search_path"] = search_path_result + except Exception as e: + diagnostics["search_path"] = f"Error: {e}" + + try: + schema_result = await query_raw_with_schema("SELECT current_schema()") + diagnostics["current_schema"] = schema_result + except Exception as e: + diagnostics["current_schema"] = f"Error: {e}" + + try: + user_result = await query_raw_with_schema( + "SELECT current_user, session_user, current_database()" + ) + diagnostics["user_info"] = user_result + except Exception as e: + diagnostics["user_info"] = f"Error: {e}" + + try: + # Check pgvector extension installation (cluster-wide, stable info) + ext_result = await query_raw_with_schema( + "SELECT extname, extversion, nspname as schema " + "FROM pg_extension e " + "JOIN pg_namespace n ON e.extnamespace = n.oid " + "WHERE extname = 'vector'" + ) + diagnostics["pgvector_extension"] = ext_result + except Exception as e: + diagnostics["pgvector_extension"] = f"Error: {e}" + + logger.error( + f"Vector type error diagnostics:\n" + f" Error: {error}\n" + f" search_path: {diagnostics.get('search_path')}\n" + f" current_schema: {diagnostics.get('current_schema')}\n" + f" user_info: {diagnostics.get('user_info')}\n" + f" pgvector_extension: {diagnostics.get('pgvector_extension')}" + ) + except Exception as diag_error: + logger.error(f"Failed to collect vector error diagnostics: {diag_error}") + + # Backward compatibility alias - HybridSearchWeights maps to StoreAgentSearchWeights # for existing code that expects the popularity parameter HybridSearchWeights = StoreAgentSearchWeights diff --git a/autogpt_platform/backend/backend/blocks/human_in_the_loop.py b/autogpt_platform/backend/backend/blocks/human_in_the_loop.py index 568ac4b33f..d31f90ec81 100644 --- a/autogpt_platform/backend/backend/blocks/human_in_the_loop.py +++ b/autogpt_platform/backend/backend/blocks/human_in_the_loop.py @@ -21,43 +21,71 @@ logger = logging.getLogger(__name__) class HumanInTheLoopBlock(Block): """ - This block pauses execution and waits for human approval or modification of the data. + Pauses execution and waits for human approval or rejection of the data. - When executed, it creates a pending review entry and sets the node execution status - to REVIEW. The execution will remain paused until a human user either: - - Approves the data (with or without modifications) - - Rejects the data + When executed, this block creates a pending review entry and sets the node execution + status to REVIEW. The execution remains paused until a human user either approves + or rejects the data. - This is useful for workflows that require human validation or intervention before - proceeding to the next steps. + **How it works:** + - The input data is presented to a human reviewer + - The reviewer can approve or reject (and optionally modify the data if editable) + - On approval: the data flows out through the `approved_data` output pin + - On rejection: the data flows out through the `rejected_data` output pin + + **Important:** The output pins yield the actual data itself, NOT status strings. + The approval/rejection decision determines WHICH output pin fires, not the value. + You do NOT need to compare the output to "APPROVED" or "REJECTED" - simply connect + downstream blocks to the appropriate output pin for each case. + + **Example usage:** + - Connect `approved_data` → next step in your workflow (data was approved) + - Connect `rejected_data` → error handling or notification (data was rejected) """ class Input(BlockSchemaInput): - data: Any = SchemaField(description="The data to be reviewed by a human user") + data: Any = SchemaField( + description="The data to be reviewed by a human user. " + "This exact data will be passed through to either approved_data or " + "rejected_data output based on the reviewer's decision." + ) name: str = SchemaField( - description="A descriptive name for what this data represents", + description="A descriptive name for what this data represents. " + "This helps the reviewer understand what they are reviewing.", ) editable: bool = SchemaField( - description="Whether the human reviewer can edit the data", + description="Whether the human reviewer can edit the data before " + "approving or rejecting it", default=True, advanced=True, ) class Output(BlockSchemaOutput): approved_data: Any = SchemaField( - description="The data when approved (may be modified by reviewer)" + description="Outputs the input data when the reviewer APPROVES it. " + "The value is the actual data itself (not a status string like 'APPROVED'). " + "If the reviewer edited the data, this contains the modified version. " + "Connect downstream blocks here for the 'approved' workflow path." ) rejected_data: Any = SchemaField( - description="The data when rejected (may be modified by reviewer)" + description="Outputs the input data when the reviewer REJECTS it. " + "The value is the actual data itself (not a status string like 'REJECTED'). " + "If the reviewer edited the data, this contains the modified version. " + "Connect downstream blocks here for the 'rejected' workflow path." ) review_message: str = SchemaField( - description="Any message provided by the reviewer", default="" + description="Optional message provided by the reviewer explaining their " + "decision. Only outputs when the reviewer provides a message; " + "this pin does not fire if no message was given.", + default="", ) def __init__(self): super().__init__( id="8b2a7b3c-6e9d-4a5f-8c1b-2e3f4a5b6c7d", - description="Pause execution and wait for human approval or modification of data", + description="Pause execution for human review. Data flows through " + "approved_data or rejected_data output based on the reviewer's decision. " + "Outputs contain the actual data, not status strings.", categories={BlockCategory.BASIC}, input_schema=HumanInTheLoopBlock.Input, output_schema=HumanInTheLoopBlock.Output, diff --git a/autogpt_platform/backend/backend/data/graph.py b/autogpt_platform/backend/backend/data/graph.py index 0dc3eea887..2433a5d270 100644 --- a/autogpt_platform/backend/backend/data/graph.py +++ b/autogpt_platform/backend/backend/data/graph.py @@ -743,6 +743,11 @@ class GraphModel(Graph, GraphMeta): # For invalid blocks, we still raise immediately as this is a structural issue raise ValueError(f"Invalid block {node.block_id} for node #{node.id}") + if block.disabled: + raise ValueError( + f"Block {node.block_id} is disabled and cannot be used in graphs" + ) + node_input_mask = ( nodes_input_masks.get(node.id, {}) if nodes_input_masks else {} ) diff --git a/autogpt_platform/backend/backend/data/rabbitmq.py b/autogpt_platform/backend/backend/data/rabbitmq.py index bdf2090083..524e21748a 100644 --- a/autogpt_platform/backend/backend/data/rabbitmq.py +++ b/autogpt_platform/backend/backend/data/rabbitmq.py @@ -1,3 +1,4 @@ +import asyncio import logging from abc import ABC, abstractmethod from enum import Enum @@ -225,6 +226,10 @@ class SyncRabbitMQ(RabbitMQBase): class AsyncRabbitMQ(RabbitMQBase): """Asynchronous RabbitMQ client""" + def __init__(self, config: RabbitMQConfig): + super().__init__(config) + self._reconnect_lock: asyncio.Lock | None = None + @property def is_connected(self) -> bool: return bool(self._connection and not self._connection.is_closed) @@ -235,7 +240,17 @@ class AsyncRabbitMQ(RabbitMQBase): @conn_retry("AsyncRabbitMQ", "Acquiring async connection") async def connect(self): - if self.is_connected: + if self.is_connected and self._channel and not self._channel.is_closed: + return + + if ( + self.is_connected + and self._connection + and (self._channel is None or self._channel.is_closed) + ): + self._channel = await self._connection.channel() + await self._channel.set_qos(prefetch_count=1) + await self.declare_infrastructure() return self._connection = await aio_pika.connect_robust( @@ -291,24 +306,46 @@ class AsyncRabbitMQ(RabbitMQBase): exchange, routing_key=queue.routing_key or queue.name ) - @func_retry - async def publish_message( + @property + def _lock(self) -> asyncio.Lock: + if self._reconnect_lock is None: + self._reconnect_lock = asyncio.Lock() + return self._reconnect_lock + + async def _ensure_channel(self) -> aio_pika.abc.AbstractChannel: + """Get a valid channel, reconnecting if the current one is stale. + + Uses a lock to prevent concurrent reconnection attempts from racing. + """ + if self.is_ready: + return self._channel # type: ignore # is_ready guarantees non-None + + async with self._lock: + # Double-check after acquiring lock + if self.is_ready: + return self._channel # type: ignore + + self._channel = None + await self.connect() + + if self._channel is None: + raise RuntimeError("Channel should be established after connect") + + return self._channel + + async def _publish_once( self, routing_key: str, message: str, exchange: Optional[Exchange] = None, persistent: bool = True, ) -> None: - if not self.is_ready: - await self.connect() - - if self._channel is None: - raise RuntimeError("Channel should be established after connect") + channel = await self._ensure_channel() if exchange: - exchange_obj = await self._channel.get_exchange(exchange.name) + exchange_obj = await channel.get_exchange(exchange.name) else: - exchange_obj = self._channel.default_exchange + exchange_obj = channel.default_exchange await exchange_obj.publish( aio_pika.Message( @@ -322,9 +359,23 @@ class AsyncRabbitMQ(RabbitMQBase): routing_key=routing_key, ) + @func_retry + async def publish_message( + self, + routing_key: str, + message: str, + exchange: Optional[Exchange] = None, + persistent: bool = True, + ) -> None: + try: + await self._publish_once(routing_key, message, exchange, persistent) + except aio_pika.exceptions.ChannelInvalidStateError: + logger.warning( + "RabbitMQ channel invalid, forcing reconnect and retrying publish" + ) + async with self._lock: + self._channel = None + await self._publish_once(routing_key, message, exchange, persistent) + async def get_channel(self) -> aio_pika.abc.AbstractChannel: - if not self.is_ready: - await self.connect() - if self._channel is None: - raise RuntimeError("Channel should be established after connect") - return self._channel + return await self._ensure_channel() diff --git a/autogpt_platform/backend/backend/executor/manager.py b/autogpt_platform/backend/backend/executor/manager.py index 8362dae828..7304653811 100644 --- a/autogpt_platform/backend/backend/executor/manager.py +++ b/autogpt_platform/backend/backend/executor/manager.py @@ -213,6 +213,9 @@ async def execute_node( block_name=node_block.name, ) + if node_block.disabled: + raise ValueError(f"Block {node_block.id} is disabled and cannot be executed") + # Sanity check: validate the execution input. input_data, error = validate_exec(node, data.inputs, resolve_input=False) if input_data is None: diff --git a/autogpt_platform/backend/backend/util/prompt.py b/autogpt_platform/backend/backend/util/prompt.py index 5f904bbc8a..3ec25dd61b 100644 --- a/autogpt_platform/backend/backend/util/prompt.py +++ b/autogpt_platform/backend/backend/util/prompt.py @@ -364,6 +364,44 @@ def _remove_orphan_tool_responses( return result +def validate_and_remove_orphan_tool_responses( + messages: list[dict], + log_warning: bool = True, +) -> list[dict]: + """ + Validate tool_call/tool_response pairs and remove orphaned responses. + + Scans messages in order, tracking all tool_call IDs. Any tool response + referencing an ID not seen in a preceding message is considered orphaned + and removed. This prevents API errors like Anthropic's "unexpected tool_use_id". + + Args: + messages: List of messages to validate (OpenAI or Anthropic format) + log_warning: Whether to log a warning when orphans are found + + Returns: + A new list with orphaned tool responses removed + """ + available_ids: set[str] = set() + orphan_ids: set[str] = set() + + for msg in messages: + available_ids |= _extract_tool_call_ids_from_message(msg) + for resp_id in _extract_tool_response_ids_from_message(msg): + if resp_id not in available_ids: + orphan_ids.add(resp_id) + + if not orphan_ids: + return messages + + if log_warning: + logger.warning( + f"Removing {len(orphan_ids)} orphan tool response(s): {orphan_ids}" + ) + + return _remove_orphan_tool_responses(messages, orphan_ids) + + def _ensure_tool_pairs_intact( recent_messages: list[dict], all_messages: list[dict], @@ -723,6 +761,13 @@ async def compress_context( # Filter out any None values that may have been introduced final_msgs: list[dict] = [m for m in msgs if m is not None] + + # ---- STEP 6: Final tool-pair validation --------------------------------- + # After all compression steps, verify that every tool response has a + # matching tool_call in a preceding assistant message. Remove orphans + # to prevent API errors (e.g., Anthropic's "unexpected tool_use_id"). + final_msgs = validate_and_remove_orphan_tool_responses(final_msgs) + final_count = sum(_msg_tokens(m, enc) for m in final_msgs) error = None if final_count + reserve > target_tokens: diff --git a/autogpt_platform/backend/poetry.lock b/autogpt_platform/backend/poetry.lock index 425b8d555a..53b5030da6 100644 --- a/autogpt_platform/backend/poetry.lock +++ b/autogpt_platform/backend/poetry.lock @@ -46,14 +46,14 @@ pycares = ">=4.9.0,<5" [[package]] name = "aiofiles" -version = "24.1.0" +version = "25.1.0" description = "File support for asyncio." optional = false -python-versions = ">=3.8" +python-versions = ">=3.9" groups = ["main"] files = [ - {file = "aiofiles-24.1.0-py3-none-any.whl", hash = "sha256:b4ec55f4195e3eb5d7abd1bf7e061763e864dd4954231fb8539a0ef8bb8260e5"}, - {file = "aiofiles-24.1.0.tar.gz", hash = "sha256:22a075c9e5a3810f0c2e48f3008c94d68c65d763b9b03857924c99e57355166c"}, + {file = "aiofiles-25.1.0-py3-none-any.whl", hash = "sha256:abe311e527c862958650f9438e859c1fa7568a141b22abcd015e120e86a85695"}, + {file = "aiofiles-25.1.0.tar.gz", hash = "sha256:a8d728f0a29de45dc521f18f07297428d56992a742f0cd2701ba86e44d23d5b2"}, ] [[package]] @@ -1382,14 +1382,14 @@ tzdata = "*" [[package]] name = "fastapi" -version = "0.128.5" +version = "0.128.6" description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production" optional = false python-versions = ">=3.9" groups = ["main"] files = [ - {file = "fastapi-0.128.5-py3-none-any.whl", hash = "sha256:bceec0de8aa6564599c5bcc0593b0d287703562c848271fca8546fd2c87bf4dd"}, - {file = "fastapi-0.128.5.tar.gz", hash = "sha256:a7173579fc162d6471e3c6fbd9a4b7610c7a3b367bcacf6c4f90d5d022cab711"}, + {file = "fastapi-0.128.6-py3-none-any.whl", hash = "sha256:bb1c1ef87d6086a7132d0ab60869d6f1ee67283b20fbf84ec0003bd335099509"}, + {file = "fastapi-0.128.6.tar.gz", hash = "sha256:0cb3946557e792d731b26a42b04912f16367e3c3135ea8290f620e234f2b604f"}, ] [package.dependencies] @@ -3078,14 +3078,14 @@ type = ["pygobject-stubs", "pytest-mypy (>=1.0.1)", "shtab", "types-pywin32"] [[package]] name = "langfuse" -version = "3.13.0" +version = "3.14.1" description = "A client library for accessing langfuse" optional = false python-versions = "<4.0,>=3.10" groups = ["main"] files = [ - {file = "langfuse-3.13.0-py3-none-any.whl", hash = "sha256:71912ddac1cc831a65df895eae538a556f564c094ae51473e747426e9ded1a9d"}, - {file = "langfuse-3.13.0.tar.gz", hash = "sha256:dacea8111ca4442e97dbfec4f8d676cf9709b35357a26e468f8887b95de0012f"}, + {file = "langfuse-3.14.1-py3-none-any.whl", hash = "sha256:17bed605dbfc9947cbd1738a715f6d27c1b80b6da9f2946586171958fa5820d0"}, + {file = "langfuse-3.14.1.tar.gz", hash = "sha256:404a6104cd29353d7829aa417ec46565b04917e5599afdda96c5b0865f4bc991"}, ] [package.dependencies] @@ -8440,4 +8440,4 @@ cffi = ["cffi (>=1.17,<2.0) ; platform_python_implementation != \"PyPy\" and pyt [metadata] lock-version = "2.1" python-versions = ">=3.10,<3.14" -content-hash = "14686ee0e2dc446a75d0db145b08dc410dc31c357e25085bb0f9b0174711c4b1" +content-hash = "c06e96ad49388ba7a46786e9ea55ea2c1a57408e15613237b4bee40a592a12af" diff --git a/autogpt_platform/backend/pyproject.toml b/autogpt_platform/backend/pyproject.toml index 677b73b468..317663ee98 100644 --- a/autogpt_platform/backend/pyproject.toml +++ b/autogpt_platform/backend/pyproject.toml @@ -21,7 +21,7 @@ cryptography = "^46.0" discord-py = "^2.5.2" e2b-code-interpreter = "^1.5.2" elevenlabs = "^1.50.0" -fastapi = "^0.128.5" +fastapi = "^0.128.6" feedparser = "^6.0.11" flake8 = "^7.3.0" google-api-python-client = "^2.177.0" @@ -34,7 +34,7 @@ html2text = "^2024.2.26" jinja2 = "^3.1.6" jsonref = "^1.1.0" jsonschema = "^4.25.0" -langfuse = "^3.11.0" +langfuse = "^3.14.1" launchdarkly-server-sdk = "^9.14.1" mem0ai = "^0.1.115" moviepy = "^2.1.2" @@ -76,7 +76,7 @@ yt-dlp = "2025.12.08" zerobouncesdk = "^1.1.2" # NOTE: please insert new dependencies in their alphabetical location pytest-snapshot = "^0.9.0" -aiofiles = "^24.1.0" +aiofiles = "^25.1.0" tiktoken = "^0.12.0" aioclamd = "^1.0.0" setuptools = "^80.9.0" diff --git a/autogpt_platform/frontend/Dockerfile b/autogpt_platform/frontend/Dockerfile index 2b120af5e1..ab2708f1f9 100644 --- a/autogpt_platform/frontend/Dockerfile +++ b/autogpt_platform/frontend/Dockerfile @@ -25,8 +25,12 @@ RUN if [ -f .env.production ]; then \ cp .env.default .env; \ fi RUN pnpm run generate:api +# Disable source-map generation in Docker builds to halve webpack memory usage. +# Source maps are only useful when SENTRY_AUTH_TOKEN is set (Vercel deploys); +# the Docker image never uploads them, so generating them just wastes RAM. +ENV NEXT_PUBLIC_SOURCEMAPS="false" # In CI, we want NEXT_PUBLIC_PW_TEST=true during build so Next.js inlines it -RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=4096" pnpm build; else NODE_OPTIONS="--max-old-space-size=4096" pnpm build; fi +RUN if [ "$NEXT_PUBLIC_PW_TEST" = "true" ]; then NEXT_PUBLIC_PW_TEST=true NODE_OPTIONS="--max-old-space-size=8192" pnpm build; else NODE_OPTIONS="--max-old-space-size=8192" pnpm build; fi # Prod stage - based on NextJS reference Dockerfile https://github.com/vercel/next.js/blob/64271354533ed16da51be5dce85f0dbd15f17517/examples/with-docker/Dockerfile FROM node:21-alpine AS prod diff --git a/autogpt_platform/frontend/next.config.mjs b/autogpt_platform/frontend/next.config.mjs index bb4410039d..9bb5983801 100644 --- a/autogpt_platform/frontend/next.config.mjs +++ b/autogpt_platform/frontend/next.config.mjs @@ -1,8 +1,12 @@ import { withSentryConfig } from "@sentry/nextjs"; +// Allow Docker builds to skip source-map generation (halves memory usage). +// Defaults to true so Vercel/local builds are unaffected. +const enableSourceMaps = process.env.NEXT_PUBLIC_SOURCEMAPS !== "false"; + /** @type {import('next').NextConfig} */ const nextConfig = { - productionBrowserSourceMaps: true, + productionBrowserSourceMaps: enableSourceMaps, // Externalize OpenTelemetry packages to fix Turbopack HMR issues serverExternalPackages: [ "@opentelemetry/instrumentation", @@ -14,9 +18,37 @@ const nextConfig = { serverActions: { bodySizeLimit: "256mb", }, - // Increase body size limit for API routes (file uploads) - 256MB to match backend limit - proxyClientMaxBodySize: "256mb", middlewareClientMaxBodySize: "256mb", + // Limit parallel webpack workers to reduce peak memory during builds. + cpus: 2, + }, + // Work around cssnano "Invalid array length" bug in Next.js's bundled + // cssnano-simple comment parser when processing very large CSS chunks. + // CSS is still bundled correctly; gzip handles most of the size savings anyway. + webpack: (config, { dev }) => { + if (!dev) { + // Next.js adds CssMinimizerPlugin internally (after user config), so we + // can't filter it from config.plugins. Instead, intercept the webpack + // compilation hooks and replace the buggy plugin's tap with a no-op. + config.plugins.push({ + apply(compiler) { + compiler.hooks.compilation.tap( + "DisableCssMinimizer", + (compilation) => { + compilation.hooks.processAssets.intercept({ + register: (tap) => { + if (tap.name === "CssMinimizerPlugin") { + return { ...tap, fn: async () => {} }; + } + return tap; + }, + }); + }, + ); + }, + }); + } + return config; }, images: { domains: [ @@ -54,9 +86,16 @@ const nextConfig = { transpilePackages: ["geist"], }; -const isDevelopmentBuild = process.env.NODE_ENV !== "production"; +// Only run the Sentry webpack plugin when we can actually upload source maps +// (i.e. on Vercel with SENTRY_AUTH_TOKEN set). The Sentry *runtime* SDK +// (imported in app code) still captures errors without the plugin. +// Skipping the plugin saves ~1 GB of peak memory during `next build`. +const skipSentryPlugin = + process.env.NODE_ENV !== "production" || + !enableSourceMaps || + !process.env.SENTRY_AUTH_TOKEN; -export default isDevelopmentBuild +export default skipSentryPlugin ? nextConfig : withSentryConfig(nextConfig, { // For all available options, see: @@ -96,7 +135,7 @@ export default isDevelopmentBuild // This helps Sentry with sourcemaps... https://docs.sentry.io/platforms/javascript/guides/nextjs/sourcemaps/ sourcemaps: { - disable: false, + disable: !enableSourceMaps, assets: [".next/**/*.js", ".next/**/*.js.map"], ignore: ["**/node_modules/**"], deleteSourcemapsAfterUpload: false, // Source is public anyway :) diff --git a/autogpt_platform/frontend/package.json b/autogpt_platform/frontend/package.json index e8c9871a72..5988e59c90 100644 --- a/autogpt_platform/frontend/package.json +++ b/autogpt_platform/frontend/package.json @@ -7,7 +7,7 @@ }, "scripts": { "dev": "pnpm run generate:api:force && next dev --turbo", - "build": "next build", + "build": "cross-env NODE_OPTIONS=--max-old-space-size=16384 next build", "start": "next start", "start:standalone": "cd .next/standalone && node server.js", "lint": "next lint && prettier --check .", @@ -30,6 +30,7 @@ "defaults" ], "dependencies": { + "@ai-sdk/react": "3.0.61", "@faker-js/faker": "10.0.0", "@hookform/resolvers": "5.2.2", "@next/third-parties": "15.4.6", @@ -60,6 +61,10 @@ "@rjsf/utils": "6.1.2", "@rjsf/validator-ajv8": "6.1.2", "@sentry/nextjs": "10.27.0", + "@streamdown/cjk": "1.0.1", + "@streamdown/code": "1.0.1", + "@streamdown/math": "1.0.1", + "@streamdown/mermaid": "1.0.1", "@supabase/ssr": "0.7.0", "@supabase/supabase-js": "2.78.0", "@tanstack/react-query": "5.90.6", @@ -68,6 +73,7 @@ "@vercel/analytics": "1.5.0", "@vercel/speed-insights": "1.2.0", "@xyflow/react": "12.9.2", + "ai": "6.0.59", "boring-avatars": "1.11.2", "class-variance-authority": "0.7.1", "clsx": "2.1.1", @@ -87,7 +93,6 @@ "launchdarkly-react-client-sdk": "3.9.0", "lodash": "4.17.21", "lucide-react": "0.552.0", - "moment": "2.30.1", "next": "15.4.10", "next-themes": "0.4.6", "nuqs": "2.7.2", @@ -112,9 +117,11 @@ "remark-math": "6.0.0", "shepherd.js": "14.5.1", "sonner": "2.0.7", + "streamdown": "2.1.0", "tailwind-merge": "2.6.0", "tailwind-scrollbar": "3.1.0", "tailwindcss-animate": "1.0.7", + "use-stick-to-bottom": "1.1.2", "uuid": "11.1.0", "vaul": "1.1.2", "zod": "3.25.76", @@ -172,7 +179,8 @@ }, "pnpm": { "overrides": { - "@opentelemetry/instrumentation": "0.209.0" + "@opentelemetry/instrumentation": "0.209.0", + "lodash-es": "4.17.23" } }, "packageManager": "pnpm@10.20.0+sha512.cf9998222162dd85864d0a8102e7892e7ba4ceadebbf5a31f9c2fce48dfce317a9c53b9f6464d1ef9042cba2e02ae02a9f7c143a2b438cd93c91840f0192b9dd" diff --git a/autogpt_platform/frontend/pnpm-lock.yaml b/autogpt_platform/frontend/pnpm-lock.yaml index 377a298564..468e2f312d 100644 --- a/autogpt_platform/frontend/pnpm-lock.yaml +++ b/autogpt_platform/frontend/pnpm-lock.yaml @@ -6,11 +6,15 @@ settings: overrides: '@opentelemetry/instrumentation': 0.209.0 + lodash-es: 4.17.23 importers: .: dependencies: + '@ai-sdk/react': + specifier: 3.0.61 + version: 3.0.61(react@18.3.1)(zod@3.25.76) '@faker-js/faker': specifier: 10.0.0 version: 10.0.0 @@ -101,6 +105,18 @@ importers: '@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@15.4.10(@babel/core@7.28.5)(@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@5.104.1(esbuild@0.25.12)) + '@streamdown/cjk': + specifier: 1.0.1 + version: 1.0.1(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(react@18.3.1)(unified@11.0.5) + '@streamdown/code': + specifier: 1.0.1 + version: 1.0.1(react@18.3.1) + '@streamdown/math': + specifier: 1.0.1 + version: 1.0.1(react@18.3.1) + '@streamdown/mermaid': + specifier: 1.0.1 + version: 1.0.1(react@18.3.1) '@supabase/ssr': specifier: 0.7.0 version: 0.7.0(@supabase/supabase-js@2.78.0) @@ -125,6 +141,9 @@ importers: '@xyflow/react': specifier: 12.9.2 version: 12.9.2(@types/react@18.3.17)(immer@11.1.3)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + ai: + specifier: 6.0.59 + version: 6.0.59(zod@3.25.76) boring-avatars: specifier: 1.11.2 version: 1.11.2 @@ -182,9 +201,6 @@ importers: lucide-react: specifier: 0.552.0 version: 0.552.0(react@18.3.1) - moment: - specifier: 2.30.1 - version: 2.30.1 next: specifier: 15.4.10 version: 15.4.10(@babel/core@7.28.5)(@opentelemetry/api@1.9.0)(@playwright/test@1.56.1)(react-dom@18.3.1(react@18.3.1))(react@18.3.1) @@ -257,6 +273,9 @@ importers: sonner: specifier: 2.0.7 version: 2.0.7(react-dom@18.3.1(react@18.3.1))(react@18.3.1) + streamdown: + specifier: 2.1.0 + version: 2.1.0(react@18.3.1) tailwind-merge: specifier: 2.6.0 version: 2.6.0 @@ -266,6 +285,9 @@ importers: tailwindcss-animate: specifier: 1.0.7 version: 1.0.7(tailwindcss@3.4.17) + use-stick-to-bottom: + specifier: 1.1.2 + version: 1.1.2(react@18.3.1) uuid: specifier: 11.1.0 version: 11.1.0 @@ -417,10 +439,35 @@ packages: '@adobe/css-tools@4.4.4': resolution: {integrity: sha512-Elp+iwUx5rN5+Y8xLt5/GRoG20WGoDCQ/1Fb+1LiGtvwbDavuSk0jhD/eZdckHAuzcDzccnkv+rEjyWfRx18gg==} + '@ai-sdk/gateway@3.0.27': + resolution: {integrity: sha512-Pr+ApS9k6/jcR3kNltJNxo60OdYvnVU4DeRhzVtxUAYTXCHx4qO+qTMG9nNRn+El1acJnNRA//Su47srjXkT/w==} + engines: {node: '>=18'} + peerDependencies: + zod: ^3.25.76 || ^4.1.8 + + '@ai-sdk/provider-utils@4.0.10': + resolution: {integrity: sha512-VeDAiCH+ZK8Xs4hb9Cw7pHlujWNL52RKe8TExOkrw6Ir1AmfajBZTb9XUdKOZO08RwQElIKA8+Ltm+Gqfo8djQ==} + engines: {node: '>=18'} + peerDependencies: + zod: ^3.25.76 || ^4.1.8 + + '@ai-sdk/provider@3.0.5': + resolution: {integrity: sha512-2Xmoq6DBJqmSl80U6V9z5jJSJP7ehaJJQMy2iFUqTay06wdCqTnPVBBQbtEL8RCChenL+q5DC5H5WzU3vV3v8w==} + engines: {node: '>=18'} + + '@ai-sdk/react@3.0.61': + resolution: {integrity: sha512-vCjZBnY2+TawFBXamSKt6elAt9n1MXMfcjSd9DSgT9peCJN27qNGVSXgaGNh/B3cUgeOktFfhB2GVmIqOjvmLQ==} + engines: {node: '>=18'} + peerDependencies: + react: ^18 || ~19.0.1 || ~19.1.2 || ^19.2.1 + '@alloc/quick-lru@5.2.0': resolution: {integrity: sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==} engines: {node: '>=10'} + '@antfu/install-pkg@1.1.0': + resolution: {integrity: sha512-MGQsmw10ZyI+EJo45CdSER4zEb+p31LpDAFp2Z3gkSd1yqVZGi0Ebx++YTEMonJy4oChEMLsxZ64j8FH6sSqtQ==} + '@apidevtools/json-schema-ref-parser@14.0.1': resolution: {integrity: sha512-Oc96zvmxx1fqoSEdUmfmvvb59/KDOnUoJ7s2t7bISyAn0XEz57LCCw8k2Y4Pf3mwKaZLMciESALORLgfe2frCw==} engines: {node: '>= 16'} @@ -1032,6 +1079,24 @@ packages: resolution: {integrity: 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4.17.23 + + chevrotain@11.0.3: + dependencies: + '@chevrotain/cst-dts-gen': 11.0.3 + '@chevrotain/gast': 11.0.3 + '@chevrotain/regexp-to-ast': 11.0.3 + '@chevrotain/types': 11.0.3 + '@chevrotain/utils': 11.0.3 + lodash-es: 4.17.23 + chokidar@3.6.0: dependencies: anymatch: 3.1.3 @@ -12491,6 +13208,8 @@ snapshots: commander@4.1.1: {} + commander@7.2.0: {} + commander@8.3.0: {} common-path-prefix@3.0.0: {} @@ -12510,6 +13229,8 @@ snapshots: tree-kill: 1.2.2 yargs: 17.7.2 + confbox@0.1.8: {} + console-browserify@1.2.0: {} constants-browserify@1.0.0: {} @@ -12530,6 +13251,14 @@ snapshots: core-util-is@1.0.3: {} + cose-base@1.0.3: + dependencies: + layout-base: 1.0.2 + + cose-base@2.2.0: + dependencies: + layout-base: 2.0.1 + cosmiconfig@7.1.0: dependencies: '@types/parse-json': 4.0.2 @@ -12638,12 +13367,50 @@ snapshots: csstype@3.2.3: {} + cytoscape-cose-bilkent@4.1.0(cytoscape@3.33.1): + dependencies: + cose-base: 1.0.3 + cytoscape: 3.33.1 + + cytoscape-fcose@2.2.0(cytoscape@3.33.1): + dependencies: + cose-base: 2.2.0 + cytoscape: 3.33.1 + + cytoscape@3.33.1: {} + + d3-array@2.12.1: + dependencies: + internmap: 1.0.1 + d3-array@3.2.4: dependencies: internmap: 2.0.3 + d3-axis@3.0.0: {} + + d3-brush@3.0.0: + dependencies: + d3-dispatch: 3.0.1 + d3-drag: 3.0.0 + d3-interpolate: 3.0.1 + d3-selection: 3.0.0 + d3-transition: 3.0.1(d3-selection@3.0.0) + + d3-chord@3.0.1: + dependencies: + d3-path: 3.1.0 + d3-color@3.1.0: {} + d3-contour@4.0.2: + dependencies: + d3-array: 3.2.4 + + d3-delaunay@6.0.4: + dependencies: + delaunator: 5.0.1 + d3-dispatch@3.0.1: {} d3-drag@3.0.0: @@ -12651,16 +13418,56 @@ snapshots: d3-dispatch: 3.0.1 d3-selection: 3.0.0 + d3-dsv@3.0.1: + dependencies: + commander: 7.2.0 + iconv-lite: 0.6.3 + rw: 1.3.3 + d3-ease@3.0.1: {} + d3-fetch@3.0.1: + dependencies: + d3-dsv: 3.0.1 + + d3-force@3.0.0: + dependencies: + d3-dispatch: 3.0.1 + d3-quadtree: 3.0.1 + d3-timer: 3.0.1 + d3-format@3.1.0: {} + d3-geo@3.1.1: + dependencies: + d3-array: 3.2.4 + + d3-hierarchy@3.1.2: {} + d3-interpolate@3.0.1: dependencies: d3-color: 3.1.0 + d3-path@1.0.9: {} + d3-path@3.1.0: {} + d3-polygon@3.0.1: {} + + d3-quadtree@3.0.1: {} + + d3-random@3.0.1: {} + + d3-sankey@0.12.3: + dependencies: + d3-array: 2.12.1 + d3-shape: 1.3.7 + + d3-scale-chromatic@3.1.0: + dependencies: + d3-color: 3.1.0 + d3-interpolate: 3.0.1 + d3-scale@4.0.2: dependencies: d3-array: 3.2.4 @@ -12671,6 +13478,10 @@ snapshots: d3-selection@3.0.0: {} + d3-shape@1.3.7: + dependencies: + d3-path: 1.0.9 + d3-shape@3.2.0: dependencies: d3-path: 3.1.0 @@ -12702,6 +13513,44 @@ snapshots: d3-selection: 3.0.0 d3-transition: 3.0.1(d3-selection@3.0.0) + d3@7.9.0: + dependencies: + d3-array: 3.2.4 + d3-axis: 3.0.0 + d3-brush: 3.0.0 + d3-chord: 3.0.1 + d3-color: 3.1.0 + d3-contour: 4.0.2 + d3-delaunay: 6.0.4 + d3-dispatch: 3.0.1 + d3-drag: 3.0.0 + d3-dsv: 3.0.1 + d3-ease: 3.0.1 + d3-fetch: 3.0.1 + d3-force: 3.0.0 + d3-format: 3.1.0 + d3-geo: 3.1.1 + d3-hierarchy: 3.1.2 + d3-interpolate: 3.0.1 + d3-path: 3.1.0 + d3-polygon: 3.0.1 + d3-quadtree: 3.0.1 + d3-random: 3.0.1 + d3-scale: 4.0.2 + d3-scale-chromatic: 3.1.0 + d3-selection: 3.0.0 + d3-shape: 3.2.0 + d3-time: 3.1.0 + d3-time-format: 4.1.0 + d3-timer: 3.0.1 + d3-transition: 3.0.1(d3-selection@3.0.0) + d3-zoom: 3.0.0 + + dagre-d3-es@7.0.13: + dependencies: + d3: 7.9.0 + lodash-es: 4.17.23 + damerau-levenshtein@1.0.8: {} data-urls@6.0.1: @@ -12732,6 +13581,8 @@ snapshots: date-fns@4.1.0: {} + dayjs@1.11.19: {} + debug@3.2.7: dependencies: ms: 2.1.3 @@ -12773,6 +13624,10 @@ snapshots: has-property-descriptors: 1.0.2 object-keys: 1.1.1 + delaunator@5.0.1: + dependencies: + robust-predicates: 3.0.2 + dependency-graph@0.11.0: {} dequal@2.0.3: {} @@ -13347,6 +14202,8 @@ snapshots: events@3.3.0: {} + eventsource-parser@3.0.6: {} + evp_bytestokey@1.0.3: dependencies: md5.js: 1.3.5 @@ -13553,6 +14410,8 @@ snapshots: get-caller-file@2.0.5: {} + get-east-asian-width@1.4.0: {} + get-intrinsic@1.3.0: dependencies: call-bind-apply-helpers: 1.0.2 @@ -13643,6 +14502,8 @@ snapshots: graphql@16.12.0: {} + hachure-fill@0.5.2: {} + happy-dom@20.3.4: dependencies: '@types/node': 24.10.0 @@ -13739,6 +14600,42 @@ snapshots: dependencies: '@types/hast': 3.0.4 + hast-util-raw@9.1.0: + dependencies: + '@types/hast': 3.0.4 + '@types/unist': 3.0.3 + '@ungap/structured-clone': 1.3.0 + hast-util-from-parse5: 8.0.3 + hast-util-to-parse5: 8.0.1 + html-void-elements: 3.0.0 + mdast-util-to-hast: 13.2.1 + parse5: 7.3.0 + unist-util-position: 5.0.0 + unist-util-visit: 5.0.0 + vfile: 6.0.3 + web-namespaces: 2.0.1 + zwitch: 2.0.4 + + hast-util-sanitize@5.0.2: + dependencies: + '@types/hast': 3.0.4 + '@ungap/structured-clone': 1.3.0 + unist-util-position: 5.0.0 + + hast-util-to-html@9.0.5: + dependencies: + '@types/hast': 3.0.4 + '@types/unist': 3.0.3 + ccount: 2.0.1 + comma-separated-tokens: 2.0.3 + hast-util-whitespace: 3.0.0 + html-void-elements: 3.0.0 + mdast-util-to-hast: 13.2.1 + property-information: 7.1.0 + space-separated-tokens: 2.0.2 + stringify-entities: 4.0.4 + zwitch: 2.0.4 + hast-util-to-jsx-runtime@2.3.6: dependencies: '@types/estree': 1.0.8 @@ -13759,6 +14656,16 @@ snapshots: transitivePeerDependencies: - supports-color + hast-util-to-parse5@8.0.1: + dependencies: + '@types/hast': 3.0.4 + comma-separated-tokens: 2.0.3 + devlop: 1.1.0 + property-information: 7.1.0 + space-separated-tokens: 2.0.2 + web-namespaces: 2.0.1 + zwitch: 2.0.4 + hast-util-to-string@3.0.1: dependencies: '@types/hast': 3.0.4 @@ -13819,6 +14726,8 @@ snapshots: html-url-attributes@3.0.1: {} + html-void-elements@3.0.0: {} + html-webpack-plugin@5.6.5(webpack@5.104.1(esbuild@0.25.12)): dependencies: '@types/html-minifier-terser': 6.1.0 @@ -13865,6 +14774,10 @@ snapshots: human-signals@2.1.0: {} + iconv-lite@0.6.3: + dependencies: + safer-buffer: 2.1.2 + icss-utils@5.1.0(postcss@8.5.6): dependencies: postcss: 8.5.6 @@ -13916,6 +14829,8 @@ snapshots: hasown: 2.0.2 side-channel: 1.1.0 + internmap@1.0.1: {} + internmap@2.0.3: {} is-alphabetical@2.0.1: {} @@ -14164,6 +15079,8 @@ snapshots: json-schema-traverse@1.0.0: {} + json-schema@0.4.0: {} + json-stable-stringify-without-jsonify@1.0.1: {} json5@1.0.2: @@ -14207,10 +15124,24 @@ snapshots: dependencies: commander: 8.3.0 + katex@0.16.28: + dependencies: + commander: 8.3.0 + keyv@4.5.4: dependencies: json-buffer: 3.0.1 + khroma@2.1.0: {} + + langium@3.3.1: + dependencies: + chevrotain: 11.0.3 + chevrotain-allstar: 0.3.1(chevrotain@11.0.3) + vscode-languageserver: 9.0.1 + vscode-languageserver-textdocument: 1.0.12 + vscode-uri: 3.0.8 + language-subtag-registry@0.3.23: {} language-tags@1.0.9: @@ -14236,6 +15167,10 @@ snapshots: react: 18.3.1 react-dom: 18.3.1(react@18.3.1) + layout-base@1.0.2: {} + + layout-base@2.0.1: {} + leven@3.1.0: {} levn@0.4.1: @@ -14273,7 +15208,7 @@ snapshots: dependencies: p-locate: 6.0.0 - lodash-es@4.17.22: {} + lodash-es@4.17.23: {} lodash.camelcase@4.3.0: {} @@ -14363,6 +15298,10 @@ snapshots: optionalDependencies: react: 18.3.1 + marked@16.4.2: {} + + marked@17.0.1: {} + math-intrinsics@1.1.0: {} md5.js@1.3.5: @@ -14549,6 +15488,29 @@ snapshots: merge2@1.4.1: {} + mermaid@11.12.2: + dependencies: + '@braintree/sanitize-url': 7.1.2 + '@iconify/utils': 3.1.0 + '@mermaid-js/parser': 0.6.3 + '@types/d3': 7.4.3 + cytoscape: 3.33.1 + cytoscape-cose-bilkent: 4.1.0(cytoscape@3.33.1) + cytoscape-fcose: 2.2.0(cytoscape@3.33.1) + d3: 7.9.0 + d3-sankey: 0.12.3 + dagre-d3-es: 7.0.13 + dayjs: 1.11.19 + dompurify: 3.3.1 + katex: 0.16.25 + khroma: 2.1.0 + lodash-es: 4.17.23 + marked: 16.4.2 + roughjs: 4.6.6 + stylis: 4.3.6 + ts-dedent: 2.2.0 + uuid: 11.1.0 + micromark-core-commonmark@2.0.3: dependencies: decode-named-character-reference: 1.2.0 @@ -14568,6 +15530,38 @@ snapshots: micromark-util-symbol: 2.0.1 micromark-util-types: 2.0.2 + micromark-extension-cjk-friendly-gfm-strikethrough@1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2): + dependencies: + devlop: 1.1.0 + get-east-asian-width: 1.4.0 + micromark: 4.0.2 + micromark-extension-cjk-friendly-util: 2.1.1(micromark-util-types@2.0.2) + micromark-util-character: 2.1.1 + micromark-util-chunked: 2.0.1 + micromark-util-resolve-all: 2.0.1 + micromark-util-symbol: 2.0.1 + optionalDependencies: + micromark-util-types: 2.0.2 + + micromark-extension-cjk-friendly-util@2.1.1(micromark-util-types@2.0.2): + dependencies: + get-east-asian-width: 1.4.0 + micromark-util-character: 2.1.1 + micromark-util-symbol: 2.0.1 + optionalDependencies: + micromark-util-types: 2.0.2 + + micromark-extension-cjk-friendly@1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2): + dependencies: + devlop: 1.1.0 + micromark: 4.0.2 + micromark-extension-cjk-friendly-util: 2.1.1(micromark-util-types@2.0.2) + micromark-util-chunked: 2.0.1 + micromark-util-resolve-all: 2.0.1 + micromark-util-symbol: 2.0.1 + optionalDependencies: + micromark-util-types: 2.0.2 + micromark-extension-gfm-autolink-literal@2.1.0: dependencies: micromark-util-character: 2.1.1 @@ -14790,9 +15784,14 @@ snapshots: minipass@7.1.2: {} - module-details-from-path@1.0.4: {} + mlly@1.8.0: + dependencies: + acorn: 8.15.0 + pathe: 2.0.3 + pkg-types: 1.3.1 + ufo: 1.6.3 - moment@2.30.1: {} + module-details-from-path@1.0.4: {} motion-dom@12.24.8: dependencies: @@ -15049,6 +16048,14 @@ snapshots: dependencies: mimic-fn: 2.1.0 + oniguruma-parser@0.12.1: {} + + oniguruma-to-es@4.3.4: + dependencies: + oniguruma-parser: 0.12.1 + regex: 6.1.0 + regex-recursion: 6.0.2 + open@8.4.2: dependencies: define-lazy-prop: 2.0.0 @@ -15143,6 +16150,8 @@ snapshots: package-json-from-dist@1.0.1: {} + package-manager-detector@1.6.0: {} + pako@1.0.11: {} param-case@3.0.4: @@ -15197,6 +16206,8 @@ snapshots: path-browserify@1.0.1: {} + path-data-parser@0.1.0: {} + path-exists@4.0.0: {} path-exists@5.0.0: {} @@ -15259,6 +16270,12 @@ snapshots: dependencies: find-up: 6.3.0 + pkg-types@1.3.1: + dependencies: + confbox: 0.1.8 + mlly: 1.8.0 + pathe: 2.0.3 + playwright-core@1.56.1: {} playwright@1.56.1: @@ -15267,6 +16284,13 @@ snapshots: optionalDependencies: fsevents: 2.3.2 + points-on-curve@0.2.0: {} + + points-on-path@0.2.1: + dependencies: + path-data-parser: 0.1.0 + points-on-curve: 0.2.0 + pony-cause@1.1.1: {} possible-typed-array-names@1.1.0: {} @@ -15693,6 +16717,16 @@ snapshots: regex-parser@2.3.1: {} + regex-recursion@6.0.2: + dependencies: + regex-utilities: 2.3.0 + + regex-utilities@2.3.0: {} + + regex@6.1.0: + dependencies: + regex-utilities: 2.3.0 + regexp.prototype.flags@1.5.4: dependencies: call-bind: 1.0.8 @@ -15726,6 +16760,10 @@ snapshots: unified: 11.0.5 unist-util-visit: 5.0.0 + rehype-harden@1.1.7: + dependencies: + unist-util-visit: 5.0.0 + rehype-highlight@7.0.2: dependencies: '@types/hast': 3.0.4 @@ -15744,6 +16782,17 @@ snapshots: unist-util-visit-parents: 6.0.2 vfile: 6.0.3 + rehype-raw@7.0.0: + dependencies: + '@types/hast': 3.0.4 + hast-util-raw: 9.1.0 + vfile: 6.0.3 + + rehype-sanitize@6.0.0: + dependencies: + '@types/hast': 3.0.4 + hast-util-sanitize: 5.0.2 + rehype-slug@6.0.0: dependencies: '@types/hast': 3.0.4 @@ -15754,6 +16803,26 @@ snapshots: relateurl@0.2.7: {} + remark-cjk-friendly-gfm-strikethrough@1.2.3(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(unified@11.0.5): + dependencies: + micromark-extension-cjk-friendly-gfm-strikethrough: 1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2) + unified: 11.0.5 + optionalDependencies: + '@types/mdast': 4.0.4 + transitivePeerDependencies: + - micromark + - micromark-util-types + + remark-cjk-friendly@1.2.3(@types/mdast@4.0.4)(micromark-util-types@2.0.2)(micromark@4.0.2)(unified@11.0.5): + dependencies: + micromark-extension-cjk-friendly: 1.2.3(micromark-util-types@2.0.2)(micromark@4.0.2) + unified: 11.0.5 + optionalDependencies: + '@types/mdast': 4.0.4 + transitivePeerDependencies: + - micromark + - micromark-util-types + remark-gfm@4.0.1: dependencies: '@types/mdast': 4.0.4 @@ -15797,6 +16866,8 @@ snapshots: mdast-util-to-markdown: 2.1.2 unified: 11.0.5 + remend@1.1.0: {} + renderkid@3.0.0: dependencies: css-select: 4.3.0 @@ -15861,6 +16932,8 @@ snapshots: hash-base: 3.1.2 inherits: 2.0.4 + robust-predicates@3.0.2: {} + rollup@4.55.1: dependencies: '@types/estree': 1.0.8 @@ -15892,10 +16965,19 @@ snapshots: '@rollup/rollup-win32-x64-msvc': 4.55.1 fsevents: 2.3.3 + roughjs@4.6.6: + dependencies: + hachure-fill: 0.5.2 + path-data-parser: 0.1.0 + points-on-curve: 0.2.0 + points-on-path: 0.2.1 + run-parallel@1.2.0: dependencies: queue-microtask: 1.2.3 + rw@1.3.3: {} + rxjs@7.8.2: dependencies: tslib: 2.8.1 @@ -15925,6 +17007,8 @@ snapshots: safe-stable-stringify@1.1.1: {} + safer-buffer@2.1.2: {} + sass-loader@16.0.6(webpack@5.104.1(esbuild@0.25.12)): dependencies: neo-async: 2.6.2 @@ -16037,6 +17121,17 @@ snapshots: '@scarf/scarf': 1.4.0 deepmerge-ts: 7.1.5 + shiki@3.21.0: + dependencies: + '@shikijs/core': 3.21.0 + '@shikijs/engine-javascript': 3.21.0 + '@shikijs/engine-oniguruma': 3.21.0 + '@shikijs/langs': 3.21.0 + '@shikijs/themes': 3.21.0 + '@shikijs/types': 3.21.0 + '@shikijs/vscode-textmate': 10.0.2 + '@types/hast': 3.0.4 + should-equal@2.0.0: dependencies: should-type: 1.4.0 @@ -16176,6 +17271,26 @@ snapshots: readable-stream: 3.6.2 xtend: 4.0.2 + streamdown@2.1.0(react@18.3.1): + dependencies: + clsx: 2.1.1 + hast-util-to-jsx-runtime: 2.3.6 + html-url-attributes: 3.0.1 + marked: 17.0.1 + react: 18.3.1 + rehype-harden: 1.1.7 + rehype-raw: 7.0.0 + rehype-sanitize: 6.0.0 + remark-gfm: 4.0.1 + remark-parse: 11.0.0 + remark-rehype: 11.1.2 + remend: 1.1.0 + tailwind-merge: 3.4.0 + unified: 11.0.5 + unist-util-visit: 5.0.0 + transitivePeerDependencies: + - supports-color + strict-event-emitter@0.5.1: {} string-argv@0.3.2: {} @@ -16301,6 +17416,8 @@ snapshots: optionalDependencies: '@babel/core': 7.28.5 + stylis@4.3.6: {} + sucrase@3.35.1: dependencies: '@jridgewell/gen-mapping': 0.3.13 @@ -16337,11 +17454,19 @@ snapshots: transitivePeerDependencies: - encoding + swr@2.3.8(react@18.3.1): + dependencies: + dequal: 2.0.3 + react: 18.3.1 + use-sync-external-store: 1.6.0(react@18.3.1) + symbol-tree@3.2.4: optional: true tailwind-merge@2.6.0: {} + tailwind-merge@3.4.0: {} + tailwind-scrollbar@3.1.0(tailwindcss@3.4.17): dependencies: tailwindcss: 3.4.17 @@ -16409,6 +17534,8 @@ snapshots: third-party-capital@1.0.20: {} + throttleit@2.1.0: {} + timers-browserify@2.0.12: dependencies: setimmediate: 1.0.5 @@ -16571,6 +17698,8 @@ snapshots: uc.micro@2.1.0: {} + ufo@1.6.3: {} + unbox-primitive@1.1.0: dependencies: call-bound: 1.0.4 @@ -16708,6 +17837,10 @@ snapshots: optionalDependencies: '@types/react': 18.3.17 + use-stick-to-bottom@1.1.2(react@18.3.1): + dependencies: + react: 18.3.1 + use-sync-external-store@1.6.0(react@18.3.1): dependencies: react: 18.3.1 @@ -16843,6 +17976,23 @@ snapshots: vm-browserify@1.1.2: {} + vscode-jsonrpc@8.2.0: {} + + vscode-languageserver-protocol@3.17.5: + dependencies: + vscode-jsonrpc: 8.2.0 + vscode-languageserver-types: 3.17.5 + + vscode-languageserver-textdocument@1.0.12: {} + + vscode-languageserver-types@3.17.5: {} + + vscode-languageserver@9.0.1: + dependencies: + vscode-languageserver-protocol: 3.17.5 + + vscode-uri@3.0.8: {} + w3c-xmlserializer@5.0.0: dependencies: xml-name-validator: 5.0.0 diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts index ab1af16584..e98d240215 100644 --- a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts +++ b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/BlockMenuSearchBar/useBlockMenuSearchBar.ts @@ -1,4 +1,4 @@ -import { debounce } from "lodash"; +import debounce from "lodash/debounce"; import { useCallback, useEffect, useRef, useState } from "react"; import { useBlockMenuStore } from "../../../../stores/blockMenuStore"; import { getQueryClient } from "@/lib/react-query/queryClient"; diff --git a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx index 0f953394e6..bee0b85721 100644 --- a/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/build/components/NewControlPanel/NewBlockMenu/HorizontalScroll.tsx @@ -70,10 +70,10 @@ export const HorizontalScroll: React.FC = ({ {children} {canScrollLeft && ( -
+
)} {canScrollRight && ( -
+
)} {canScrollLeft && (
+ ); + } + + return ( + + {!isMobile && } +
+ {isMobile && } +
+ +
+
+ {isMobile && ( + + )} + + ); +} diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx new file mode 100644 index 0000000000..5074741095 --- /dev/null +++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatContainer/ChatContainer.tsx @@ -0,0 +1,74 @@ +"use client"; +import { ChatInput } from "@/app/(platform)/copilot/components/ChatInput/ChatInput"; +import { UIDataTypes, UIMessage, UITools } from "ai"; +import { LayoutGroup, motion } from "framer-motion"; +import { ChatMessagesContainer } from "../ChatMessagesContainer/ChatMessagesContainer"; +import { CopilotChatActionsProvider } from "../CopilotChatActionsProvider/CopilotChatActionsProvider"; +import { EmptySession } from "../EmptySession/EmptySession"; + +export interface ChatContainerProps { + messages: UIMessage[]; + status: string; + error: Error | undefined; + sessionId: string | null; + isLoadingSession: boolean; + isCreatingSession: boolean; + onCreateSession: () => void | Promise; + onSend: (message: string) => void | Promise; + onStop: () => void; +} +export const ChatContainer = ({ + messages, + status, + error, + sessionId, + isLoadingSession, + isCreatingSession, + onCreateSession, + onSend, + onStop, +}: ChatContainerProps) => { + const inputLayoutId = "copilot-2-chat-input"; + + return ( + + +
+ {sessionId ? ( +
+ + +
+ + +
+ ) : ( + + )} +
+ + + ); +}; diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx similarity index 93% rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx index bac004f6ed..af44232a4a 100644 --- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/ChatInput.tsx +++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/ChatInput.tsx @@ -6,17 +6,19 @@ import { MicrophoneIcon, StopIcon, } from "@phosphor-icons/react"; +import { ChangeEvent, useCallback } from "react"; import { RecordingIndicator } from "./components/RecordingIndicator"; import { useChatInput } from "./useChatInput"; import { useVoiceRecording } from "./useVoiceRecording"; export interface Props { - onSend: (message: string) => void; + onSend: (message: string) => void | Promise; disabled?: boolean; isStreaming?: boolean; onStop?: () => void; placeholder?: string; className?: string; + inputId?: string; } export function ChatInput({ @@ -26,14 +28,14 @@ export function ChatInput({ onStop, placeholder = "Type your message...", className, + inputId = "chat-input", }: Props) { - const inputId = "chat-input"; const { value, setValue, handleKeyDown: baseHandleKeyDown, handleSubmit, - handleChange, + handleChange: baseHandleChange, hasMultipleLines, } = useChatInput({ onSend, @@ -60,6 +62,15 @@ export function ChatInput({ inputId, }); + // Block text changes when recording + const handleChange = useCallback( + (e: ChangeEvent) => { + if (isRecording) return; + baseHandleChange(e); + }, + [isRecording, baseHandleChange], + ); + return (
diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/AudioWaveform.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/AudioWaveform.tsx similarity index 100% rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/AudioWaveform.tsx rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/AudioWaveform.tsx diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/RecordingIndicator.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/RecordingIndicator.tsx similarity index 100% rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/components/RecordingIndicator.tsx rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/components/RecordingIndicator.tsx diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/helpers.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/helpers.ts similarity index 100% rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/helpers.ts rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/helpers.ts diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts similarity index 83% rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts index a053e6080f..64b39c3817 100644 --- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useChatInput.ts +++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useChatInput.ts @@ -21,6 +21,7 @@ export function useChatInput({ }: Args) { const [value, setValue] = useState(""); const [hasMultipleLines, setHasMultipleLines] = useState(false); + const [isSending, setIsSending] = useState(false); useEffect( function focusOnMount() { @@ -100,34 +101,40 @@ export function useChatInput({ } }, [value, maxRows, inputId]); - const handleSend = () => { - if (disabled || !value.trim()) return; - onSend(value.trim()); - setValue(""); - setHasMultipleLines(false); - const textarea = document.getElementById(inputId) as HTMLTextAreaElement; - const wrapper = document.getElementById( - `${inputId}-wrapper`, - ) as HTMLDivElement; - if (textarea) { - textarea.style.height = "auto"; + async function handleSend() { + if (disabled || isSending || !value.trim()) return; + + setIsSending(true); + try { + await onSend(value.trim()); + setValue(""); + setHasMultipleLines(false); + const textarea = document.getElementById(inputId) as HTMLTextAreaElement; + const wrapper = document.getElementById( + `${inputId}-wrapper`, + ) as HTMLDivElement; + if (textarea) { + textarea.style.height = "auto"; + } + if (wrapper) { + wrapper.style.height = ""; + wrapper.style.maxHeight = ""; + } + } finally { + setIsSending(false); } - if (wrapper) { - wrapper.style.height = ""; - wrapper.style.maxHeight = ""; - } - }; + } function handleKeyDown(event: KeyboardEvent) { if (event.key === "Enter" && !event.shiftKey) { event.preventDefault(); - handleSend(); + void handleSend(); } } function handleSubmit(e: FormEvent) { e.preventDefault(); - handleSend(); + void handleSend(); } function handleChange(e: ChangeEvent) { @@ -142,5 +149,6 @@ export function useChatInput({ handleSubmit, handleChange, hasMultipleLines, + isSending, }; } diff --git a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts similarity index 86% rename from autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts rename to autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts index 4fd500d96a..0f9ee51736 100644 --- a/autogpt_platform/frontend/src/components/contextual/Chat/components/ChatInput/useVoiceRecording.ts +++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatInput/useVoiceRecording.ts @@ -38,9 +38,13 @@ export function useVoiceRecording({ const streamRef = useRef(null); const isRecordingRef = useRef(false); - const isSupported = - typeof window !== "undefined" && - !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia); + const [isSupported, setIsSupported] = useState(false); + + useEffect(() => { + setIsSupported( + !!(navigator.mediaDevices && navigator.mediaDevices.getUserMedia), + ); + }, []); const clearTimer = useCallback(() => { if (timerRef.current) { @@ -214,17 +218,33 @@ export function useVoiceRecording({ const handleKeyDown = useCallback( (event: KeyboardEvent) => { - if (event.key === " " && !value.trim() && !isTranscribing) { + // Allow space to toggle recording (start when empty, stop when recording) + if (event.key === " " && !isTranscribing) { + if (isRecordingRef.current) { + // Stop recording on space + event.preventDefault(); + stopRecording(); + return; + } else if (!value.trim()) { + // Start recording on space when input is empty + event.preventDefault(); + void startRecording(); + return; + } + } + // Block all key events when recording (except space handled above) + if (isRecordingRef.current) { event.preventDefault(); - toggleRecording(); return; } baseHandleKeyDown(event); }, - [value, isTranscribing, toggleRecording, baseHandleKeyDown], + [value, isTranscribing, stopRecording, startRecording, baseHandleKeyDown], ); const showMicButton = isSupported; + // Don't include isRecording in disabled state - we need key events to work + // Text input is blocked via handleKeyDown instead const isInputDisabled = disabled || isStreaming || isTranscribing; // Cleanup on unmount diff --git a/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx new file mode 100644 index 0000000000..fbe1c03d1d --- /dev/null +++ b/autogpt_platform/frontend/src/app/(platform)/copilot/components/ChatMessagesContainer/ChatMessagesContainer.tsx @@ -0,0 +1,294 @@ +import { getGetWorkspaceDownloadFileByIdUrl } from "@/app/api/__generated__/endpoints/workspace/workspace"; +import { + Conversation, + ConversationContent, + ConversationScrollButton, +} from "@/components/ai-elements/conversation"; +import { + Message, + MessageContent, + MessageResponse, +} from "@/components/ai-elements/message"; +import { LoadingSpinner } from "@/components/atoms/LoadingSpinner/LoadingSpinner"; +import { toast } from "@/components/molecules/Toast/use-toast"; +import { ToolUIPart, UIDataTypes, UIMessage, UITools } from "ai"; +import { useEffect, useRef, useState } from "react"; +import { CreateAgentTool } from "../../tools/CreateAgent/CreateAgent"; +import { EditAgentTool } from "../../tools/EditAgent/EditAgent"; +import { FindAgentsTool } from "../../tools/FindAgents/FindAgents"; +import { FindBlocksTool } from "../../tools/FindBlocks/FindBlocks"; +import { RunAgentTool } from "../../tools/RunAgent/RunAgent"; +import { RunBlockTool } from "../../tools/RunBlock/RunBlock"; +import { SearchDocsTool } from "../../tools/SearchDocs/SearchDocs"; +import { ViewAgentOutputTool } from "../../tools/ViewAgentOutput/ViewAgentOutput"; + +// --------------------------------------------------------------------------- +// Workspace media support +// --------------------------------------------------------------------------- + +/** + * Resolve workspace:// URLs in markdown text to proxy download URLs. + * Detects MIME type from the hash fragment (e.g. workspace://id#video/mp4) + * and prefixes the alt text with "video:" so the custom img component can + * render a