fix: skip binary file if stat fails to prevent OOM

If the stat command fails (file deleted, permissions issue, etc.),
we now skip the file rather than proceeding to read it with an
unknown size. This prevents potential OOM crashes from large files
where size verification failed.

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:

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"

autogpt_platform/backend/backend/api/features/chat/service.py

@@ -800,9 +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"
             )
@@ -1404,13 +1408,9 @@ async def _yield_tool_call(
                 operation_id=operation_id,
             )
 
-            # Save assistant message with tool_call FIRST (required by LLM)
+            # Attach the tool_call to the current turn's assistant message
-            assistant_message = ChatMessage(
+            # (or create one if this is a tool-only response with no text).
-                role="assistant",
+            session.add_tool_call_to_current_turn(tool_calls[yield_idx])
-                content="",
-                tool_calls=[tool_calls[yield_idx]],
-            )
-            session.messages.append(assistant_message)
 
             # Then save pending tool result
             pending_message = ChatMessage(

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/dummy.py

@@ -1,152 +0,0 @@
-"""Dummy Agent Generator for testing.
-
-Returns mock responses matching the format expected from the external service.
-Enable via AGENTGENERATOR_USE_DUMMY=true in settings.
-
-WARNING: This is for testing only. Do not use in production.
-"""
-
-import logging
-import uuid
-from typing import Any
-
-logger = logging.getLogger(__name__)
-
-# Dummy decomposition result (instructions type)
-DUMMY_DECOMPOSITION_RESULT: dict[str, Any] = {
-    "type": "instructions",
-    "steps": [
-        {
-            "description": "Get input from user",
-            "action": "input",
-            "block_name": "AgentInputBlock",
-        },
-        {
-            "description": "Process the input",
-            "action": "process",
-            "block_name": "TextFormatterBlock",
-        },
-        {
-            "description": "Return output to user",
-            "action": "output",
-            "block_name": "AgentOutputBlock",
-        },
-    ],
-}
-
-# Block IDs from backend/blocks/io.py
-AGENT_INPUT_BLOCK_ID = "c0a8e994-ebf1-4a9c-a4d8-89d09c86741b"
-AGENT_OUTPUT_BLOCK_ID = "363ae599-353e-4804-937e-b2ee3cef3da4"
-
-
-def _generate_dummy_agent_json() -> dict[str, Any]:
-    """Generate a minimal valid agent JSON for testing."""
-    input_node_id = str(uuid.uuid4())
-    output_node_id = str(uuid.uuid4())
-
-    return {
-        "id": str(uuid.uuid4()),
-        "version": 1,
-        "is_active": True,
-        "name": "Dummy Test Agent",
-        "description": "A dummy agent generated for testing purposes",
-        "nodes": [
-            {
-                "id": input_node_id,
-                "block_id": AGENT_INPUT_BLOCK_ID,
-                "input_default": {
-                    "name": "input",
-                    "title": "Input",
-                    "description": "Enter your input",
-                    "placeholder_values": [],
-                },
-                "metadata": {"position": {"x": 0, "y": 0}},
-            },
-            {
-                "id": output_node_id,
-                "block_id": AGENT_OUTPUT_BLOCK_ID,
-                "input_default": {
-                    "name": "output",
-                    "title": "Output",
-                    "description": "Agent output",
-                    "format": "{output}",
-                },
-                "metadata": {"position": {"x": 400, "y": 0}},
-            },
-        ],
-        "links": [
-            {
-                "id": str(uuid.uuid4()),
-                "source_id": input_node_id,
-                "sink_id": output_node_id,
-                "source_name": "result",
-                "sink_name": "value",
-                "is_static": False,
-            },
-        ],
-    }
-
-
-async def decompose_goal_dummy(
-    description: str,
-    context: str = "",
-    library_agents: list[dict[str, Any]] | None = None,
-) -> dict[str, Any]:
-    """Return dummy decomposition result."""
-    logger.info("Using dummy agent generator for decompose_goal")
-    return DUMMY_DECOMPOSITION_RESULT.copy()
-
-
-async def generate_agent_dummy(
-    instructions: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
-) -> dict[str, Any]:
-    """Return dummy agent JSON."""
-    logger.info("Using dummy agent generator for generate_agent")
-    return _generate_dummy_agent_json()
-
-
-async def generate_agent_patch_dummy(
-    update_request: str,
-    current_agent: dict[str, Any],
-    library_agents: list[dict[str, Any]] | None = None,
-    operation_id: str | None = None,
-    task_id: str | None = None,
-) -> dict[str, Any]:
-    """Return dummy patched agent (returns the current agent with updated description)."""
-    logger.info("Using dummy agent generator for generate_agent_patch")
-    patched = current_agent.copy()
-    patched["description"] = (
-        f"{current_agent.get('description', '')} (updated: {update_request})"
-    )
-    return patched
-
-
-async def customize_template_dummy(
-    template_agent: dict[str, Any],
-    modification_request: str,
-    context: str = "",
-) -> dict[str, Any]:
-    """Return dummy customized template (returns template with updated description)."""
-    logger.info("Using dummy agent generator for customize_template")
-    customized = template_agent.copy()
-    customized["description"] = (
-        f"{template_agent.get('description', '')} (customized: {modification_request})"
-    )
-    return customized
-
-
-async def get_blocks_dummy() -> list[dict[str, Any]]:
-    """Return dummy blocks list."""
-    logger.info("Using dummy agent generator for get_blocks")
-    return [
-        {"id": AGENT_INPUT_BLOCK_ID, "name": "AgentInputBlock"},
-        {"id": AGENT_OUTPUT_BLOCK_ID, "name": "AgentOutputBlock"},
-    ]
-
-
-async def health_check_dummy() -> bool:
-    """Always returns healthy for dummy service."""
-    return True

autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/service.py

@@ -12,19 +12,8 @@ import httpx
 
 from backend.util.settings import Settings
 
-from .dummy import (
-    customize_template_dummy,
-    decompose_goal_dummy,
-    generate_agent_dummy,
-    generate_agent_patch_dummy,
-    get_blocks_dummy,
-    health_check_dummy,
-)
-
 logger = logging.getLogger(__name__)
 
-_dummy_mode_warned = False
-
 
 def _create_error_response(
     error_message: str,
@@ -101,26 +90,10 @@ def _get_settings() -> Settings:
     return _settings
 
 
-def _is_dummy_mode() -> bool:
-    """Check if dummy mode is enabled for testing."""
-    global _dummy_mode_warned
-    settings = _get_settings()
-    is_dummy = bool(settings.config.agentgenerator_use_dummy)
-    if is_dummy and not _dummy_mode_warned:
-        logger.warning(
-            "Agent Generator running in DUMMY MODE - returning mock responses. "
-            "Do not use in production!"
-        )
-        _dummy_mode_warned = True
-    return is_dummy
-
-
 def is_external_service_configured() -> bool:
-    """Check if external Agent Generator service is configured (or dummy mode)."""
+    """Check if external Agent Generator service is configured."""
     settings = _get_settings()
-    return bool(settings.config.agentgenerator_host) or bool(
+    return bool(settings.config.agentgenerator_host)
-        settings.config.agentgenerator_use_dummy
-    )
 
 
 def _get_base_url() -> str:
@@ -164,9 +137,6 @@ async def decompose_goal_external(
         - {"type": "error", "error": "...", "error_type": "..."} on error
         Or None on unexpected error
     """
-    if _is_dummy_mode():
-        return await decompose_goal_dummy(description, context, library_agents)
-
     client = _get_client()
 
     if context:
@@ -256,11 +226,6 @@ async def generate_agent_external(
     Returns:
         Agent JSON dict, {"status": "accepted"} for async, or error dict {"type": "error", ...} on error
     """
-    if _is_dummy_mode():
-        return await generate_agent_dummy(
-            instructions, library_agents, operation_id, task_id
-        )
-
     client = _get_client()
 
     # Build request payload
@@ -332,11 +297,6 @@ async def generate_agent_patch_external(
     Returns:
         Updated agent JSON, clarifying questions dict, {"status": "accepted"} for async, or error dict on error
     """
-    if _is_dummy_mode():
-        return await generate_agent_patch_dummy(
-            update_request, current_agent, library_agents, operation_id, task_id
-        )
-
     client = _get_client()
 
     # Build request payload
@@ -423,11 +383,6 @@ async def customize_template_external(
     Returns:
         Customized agent JSON, clarifying questions dict, or error dict on error
     """
-    if _is_dummy_mode():
-        return await customize_template_dummy(
-            template_agent, modification_request, context
-        )
-
     client = _get_client()
 
     request = modification_request
@@ -490,9 +445,6 @@ async def get_blocks_external() -> list[dict[str, Any]] | None:
     Returns:
         List of block info dicts or None on error
     """
-    if _is_dummy_mode():
-        return await get_blocks_dummy()
-
     client = _get_client()
 
     try:
@@ -526,9 +478,6 @@ async def health_check() -> bool:
     if not is_external_service_configured():
         return False
 
-    if _is_dummy_mode():
-        return await health_check_dummy()
-
     client = _get_client()
 
     try:

autogpt_platform/backend/backend/blocks/claude_code.py

@@ -1,4 +1,6 @@
+import base64
 import json
+import logging
 import shlex
 import uuid
 from typing import Literal, Optional
@@ -21,6 +23,11 @@ from backend.data.model import (
 )
 from backend.integrations.providers import ProviderName
 
+logger = logging.getLogger(__name__)
+
+# Maximum size for binary files to extract (50MB)
+MAX_BINARY_FILE_SIZE = 50 * 1024 * 1024
+
 
 class ClaudeCodeExecutionError(Exception):
     """Exception raised when Claude Code execution fails.
@@ -180,7 +187,9 @@ class ClaudeCodeBlock(Block):
         path: str
         relative_path: str  # Path relative to working directory (for GitHub, etc.)
         name: str
-        content: str
+        content: str  # Text content for text files, empty string for binary files
+        is_binary: bool = False  # True if this is a binary file
+        content_base64: Optional[str] = None  # Base64-encoded content for binary files
 
     class Output(BlockSchemaOutput):
         response: str = SchemaField(
@@ -188,8 +197,11 @@ class ClaudeCodeBlock(Block):
         )
         files: list["ClaudeCodeBlock.FileOutput"] = SchemaField(
             description=(
-                "List of text files created/modified by Claude Code during this execution. "
+                "List of files created/modified by Claude Code during this execution. "
-                "Each file has 'path', 'relative_path', 'name', and 'content' fields."
+                "Each file has 'path', 'relative_path', 'name', 'content', 'is_binary', "
+                "and 'content_base64' fields. For text files, 'content' contains the text "
+                "and 'is_binary' is False. For binary files (PDFs, images, etc.), "
+                "'is_binary' is True and 'content_base64' contains the base64-encoded data."
             )
         )
         conversation_history: str = SchemaField(
@@ -252,6 +264,8 @@ class ClaudeCodeBlock(Block):
                             "relative_path": "index.html",
                             "name": "index.html",
                             "content": "<html>Hello World</html>",
+                            "is_binary": False,
+                            "content_base64": None,
                         }
                     ],
                 ),
@@ -272,6 +286,8 @@ class ClaudeCodeBlock(Block):
                             relative_path="index.html",
                             name="index.html",
                             content="<html>Hello World</html>",
+                            is_binary=False,
+                            content_base64=None,
                         )
                     ],  # files
                     "User: Create a hello world HTML file\n"
@@ -531,7 +547,6 @@ class ClaudeCodeBlock(Block):
             ".env",
             ".gitignore",
             ".dockerfile",
-            "Dockerfile",
             ".vue",
             ".svelte",
             ".astro",
@@ -540,6 +555,44 @@ class ClaudeCodeBlock(Block):
             ".tex",
             ".csv",
             ".log",
+            ".svg",  # SVG is XML-based text
+        }
+
+        # Binary file extensions we can read and base64-encode
+        binary_extensions = {
+            # Images
+            ".png",
+            ".jpg",
+            ".jpeg",
+            ".gif",
+            ".webp",
+            ".ico",
+            ".bmp",
+            ".tiff",
+            ".tif",
+            # Documents
+            ".pdf",
+            # Archives (useful for downloads)
+            ".zip",
+            ".tar",
+            ".gz",
+            ".7z",
+            # Audio/Video (if small enough)
+            ".mp3",
+            ".wav",
+            ".mp4",
+            ".webm",
+            # Other binary formats
+            ".woff",
+            ".woff2",
+            ".ttf",
+            ".otf",
+            ".eot",
+            ".bin",
+            ".exe",
+            ".dll",
+            ".so",
+            ".dylib",
         }
 
         try:
@@ -564,10 +617,26 @@ class ClaudeCodeBlock(Block):
                     if not file_path:
                         continue
 
-                    # Check if it's a text file we can read
+                    # Check if it's a text file we can read (case-insensitive)
+                    file_path_lower = file_path.lower()
                     is_text = any(
-                        file_path.endswith(ext) for ext in text_extensions
+                        file_path_lower.endswith(ext) for ext in text_extensions
-                    ) or file_path.endswith("Dockerfile")
+                    ) or file_path_lower.endswith("dockerfile")
+
+                    # Check if it's a binary file we should extract
+                    is_binary = any(
+                        file_path_lower.endswith(ext) for ext in binary_extensions
+                    )
+
+                    # Helper to extract filename and relative path
+                    def get_file_info(path: str, work_dir: str) -> tuple[str, str]:
+                        name = path.split("/")[-1]
+                        rel_path = path
+                        if path.startswith(work_dir):
+                            rel_path = path[len(work_dir) :]
+                            if rel_path.startswith("/"):
+                                rel_path = rel_path[1:]
+                        return name, rel_path
 
                     if is_text:
                         try:
@@ -576,32 +645,75 @@ class ClaudeCodeBlock(Block):
                             if isinstance(content, bytes):
                                 content = content.decode("utf-8", errors="replace")
 
-                            # Extract filename from path
+                            file_name, relative_path = get_file_info(
-                            file_name = file_path.split("/")[-1]
+                                file_path, working_directory
-
+                            )
-                            # Calculate relative path by stripping working directory
-                            relative_path = file_path
-                            if file_path.startswith(working_directory):
-                                relative_path = file_path[len(working_directory) :]
-                                # Remove leading slash if present
-                                if relative_path.startswith("/"):
-                                    relative_path = relative_path[1:]
-
                             files.append(
                                 ClaudeCodeBlock.FileOutput(
                                     path=file_path,
                                     relative_path=relative_path,
                                     name=file_name,
                                     content=content,
+                                    is_binary=False,
+                                    content_base64=None,
                                 )
                             )
-                        except Exception:
+                        except Exception as e:
-                            # Skip files that can't be read
+                            logger.warning(f"Failed to read text file {file_path}: {e}")
-                            pass
+                    elif is_binary:
+                        try:
+                            # Check file size before reading to avoid OOM
+                            stat_result = await sandbox.commands.run(
+                                f"stat -c %s {shlex.quote(file_path)} 2>/dev/null"
+                            )
+                            if (
+                                stat_result.exit_code != 0
+                                or not stat_result.stdout
+                            ):
+                                logger.warning(
+                                    f"Skipping binary file {file_path}: "
+                                    f"could not determine file size"
+                                )
+                                continue
+                            file_size = int(stat_result.stdout.strip())
+                            if file_size > MAX_BINARY_FILE_SIZE:
+                                logger.warning(
+                                    f"Skipping binary file {file_path}: "
+                                    f"size {file_size} exceeds limit "
+                                    f"{MAX_BINARY_FILE_SIZE}"
+                                )
+                                continue
 
-        except Exception:
+                            # Read binary file as bytes using format="bytes"
-            # If file extraction fails, return empty results
+                            content_bytes = await sandbox.files.read(
-            pass
+                                file_path, format="bytes"
+                            )
+
+                            # Base64 encode the binary content
+                            content_b64 = base64.b64encode(content_bytes).decode(
+                                "ascii"
+                            )
+
+                            file_name, relative_path = get_file_info(
+                                file_path, working_directory
+                            )
+                            files.append(
+                                ClaudeCodeBlock.FileOutput(
+                                    path=file_path,
+                                    relative_path=relative_path,
+                                    name=file_name,
+                                    content="",  # Empty for binary files
+                                    is_binary=True,
+                                    content_base64=content_b64,
+                                )
+                            )
+                        except Exception as e:
+                            logger.warning(
+                                f"Failed to read binary file {file_path}: {e}"
+                            )
+
+        except Exception as e:
+            logger.warning(f"File extraction failed: {e}")
 
         return files
 

autogpt_platform/backend/backend/util/settings.py

@@ -368,10 +368,6 @@ class Config(UpdateTrackingModel["Config"], BaseSettings):
         default=600,
         description="The timeout in seconds for Agent Generator service requests (includes retries for rate limits)",
     )
-    agentgenerator_use_dummy: bool = Field(
-        default=False,
-        description="Use dummy agent generator responses for testing (bypasses external service)",
-    )
 
     enable_example_blocks: bool = Field(
         default=False,

docs/integrations/block-integrations/claude_code.md

@@ -16,7 +16,7 @@ When activated, the block:
    - Install dependencies (npm, pip, etc.)
    - Run terminal commands
    - Build and test applications
-5. Extracts all text files created/modified during execution
+5. Extracts all text and binary files created/modified during execution
 6. Returns the response and files, optionally keeping the sandbox alive for follow-up tasks
 
 The block supports conversation continuation through three mechanisms:
@@ -42,7 +42,7 @@ The block supports conversation continuation through three mechanisms:
 | Output | Description |
 |--------|-------------|
 | Response | The output/response from Claude Code execution |
-| Files | List of text files created/modified during execution. Each file includes path, relative_path, name, and content fields |
+| Files | List of files created/modified during execution. Each file includes path, relative_path, name, content, is_binary, and content_base64 fields. For text files, content contains the text and is_binary is False. For binary files (PDFs, images, etc.), is_binary is True and content_base64 contains the base64-encoded data |
 | Conversation History | Full conversation history including this turn. Use to restore context on a fresh sandbox |
 | Session ID | Session ID for this conversation. Pass back with sandbox_id to continue the conversation |
 | Sandbox ID | ID of the sandbox instance (null if disposed). Pass back with session_id to continue the conversation |

docs/integrations/block-integrations/llm.md

@@ -535,7 +535,7 @@ When activated, the block:
 2. Installs the latest version of Claude Code in the sandbox
 3. Optionally runs setup commands to prepare the environment
 4. Executes your prompt using Claude Code, which can create/edit files, install dependencies, run terminal commands, and build applications
-5. Extracts all text files created/modified during execution
+5. Extracts all text and binary files created/modified during execution
 6. Returns the response and files, optionally keeping the sandbox alive for follow-up tasks
 
 The block supports conversation continuation through three mechanisms:
@@ -563,7 +563,7 @@ The block supports conversation continuation through three mechanisms:
 |--------|-------------|------|
 | error | Error message if execution failed | str |
 | response | The output/response from Claude Code execution | str |
-| files | List of text files created/modified by Claude Code during this execution. Each file has 'path', 'relative_path', 'name', and 'content' fields. | List[FileOutput] |
+| files | List of files created/modified by Claude Code during this execution. Each file has 'path', 'relative_path', 'name', 'content', 'is_binary', and 'content_base64' fields. For text files, 'content' contains the text and 'is_binary' is False. For binary files (PDFs, images, etc.), 'is_binary' is True and 'content_base64' contains the base64-encoded data. | List[FileOutput] |
 | conversation_history | Full conversation history including this turn. Pass this to conversation_history input to continue on a fresh sandbox if the previous sandbox timed out. | str |
 | session_id | Session ID for this conversation. Pass this back along with sandbox_id to continue the conversation. | str |
 | sandbox_id | ID of the sandbox instance. Pass this back along with session_id to continue the conversation. This is None if dispose_sandbox was True (sandbox was disposed). | str |