refactor(backend): move local imports to module level in chat service #11959
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Addresses review feedback from PRs #11937, #11856: - Move uuid import to top level (was duplicated in 3 functions) - Move compress_context import to top level - Remove redundant local imports for cast and ChatCompletionMessageParam (already imported at module level) Refs: - #11937 (comment) - #11856 (comment) - #11856 (comment)
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WalkthroughMoved repeated imports (uuid, compress_context, openai) to module scope in chat service; introduced Pydantic input models across many chat tools and refactored tool Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant CustomizeAgentTool
participant TemplateService
participant AgentLibrary
User->>CustomizeAgentTool: submit customization (CustomizeAgentInput)
CustomizeAgentTool->>TemplateService: customize_template(params)
TemplateService-->>CustomizeAgentTool: result (error | clarifying_questions | customized_agent)
alt error
CustomizeAgentTool-->>User: ErrorResponse
else clarifying_questions
CustomizeAgentTool-->>User: ClarificationNeededResponse
else customized_agent
CustomizeAgentTool->>AgentLibrary: save or preview (based on params.save)
AgentLibrary-->>CustomizeAgentTool: confirmation / preview data
CustomizeAgentTool-->>User: SuccessResponse or PreviewResponse
end
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⚠️ Outside diff range comments (1)
autogpt_platform/backend/backend/api/features/chat/service.py (1)
1774-1774:⚠️ Potential issue | 🟡 MinorRedundant local import contradicts PR objectives.
ChatCompletionSystemMessageParamis already imported at module level (line 29). The PR description explicitly states removing redundant local imports for this type. This line should be removed.🔧 Proposed fix
if system_prompt: - from openai.types.chat import ChatCompletionSystemMessageParam - system_message = ChatCompletionSystemMessageParam( role="system", content=system_prompt,
🧹 Nitpick comments (1)
autogpt_platform/backend/backend/api/features/chat/service.py (1)
421-421: Redundant local import ofasyncio.
asynciois already imported at module level (line 1). This local import should be removed to align with the PR's objective of eliminating redundant local imports.🔧 Proposed fix
if len(user_messages) == 1: # First user message - generate title in background - import asyncio - # Capture only the values we need (not the session object) to avoid
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📒 Files selected for processing (1)
autogpt_platform/backend/backend/api/features/chat/service.py
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autogpt_platform/backend/**/*.py
📄 CodeRabbit inference engine (.github/copilot-instructions.md)
autogpt_platform/backend/**/*.py: Always run backend setup commands in order: poetry install, poetry run prisma migrate dev, poetry run prisma generate before backend development
Always run poetry run format (Black + isort) before poetry run lint (ruff) for backend code
Use Python 3.10-3.13 with Python 3.11 required for development (managed by Poetry via pyproject.toml)
autogpt_platform/backend/**/*.py: Use FastAPI with async support for API endpoints in the backend
Use Prisma ORM for database operations with PostgreSQL
Use RabbitMQ for async task processing in the backend
Use JWT-based authentication with Supabase integration
Usepoetry run format(Black + isort) to format code andpoetry run lint(ruff) for linting in the backend
Use ClamAV integration for file upload security
autogpt_platform/backend/**/*.py: Format Python code withpoetry run format
Runpoetry run test(runs pytest with a docker based postgres + prisma) before committing backend changes
Files:
autogpt_platform/backend/backend/api/features/chat/service.py
autogpt_platform/**/*.{ts,tsx,js,py}
📄 CodeRabbit inference engine (AGENTS.md)
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Files:
autogpt_platform/backend/backend/api/features/chat/service.py
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autogpt_platform/backend/backend/api/features/chat/service.py (1)
autogpt_platform/backend/backend/util/prompt.py (1)
compress_context(539-740)
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🔇 Additional comments (3)
autogpt_platform/backend/backend/api/features/chat/service.py (3)
1-12: LGTM!The module-level imports for
uuid(aliased asuuid_module) andcompress_contextare correctly placed, eliminating duplicate local imports across multiple functions.
473-474: LGTM!Consistent usage of the module-level
uuid_modulealias for generating unique identifiers.
809-856: LGTM!The
compress_contextfunction is correctly imported at module level and properly utilized with the async client context manager pattern to avoid socket leaks.
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Addresses review feedback from ntindle on PR #11943: 1. Use typed parameters instead of kwargs.get(): - Added CustomizeAgentInput Pydantic model with field_validator - Tool now uses params = CustomizeAgentInput(**kwargs) pattern 2. Use match/case for cleaner pattern matching: - Extracted response handling to _handle_customization_result method - Uses match result_type: case 'error' | 'clarifying_questions' | _ 3. Improved code organization: - Split monolithic _execute into smaller focused methods - _handle_customization_result for response type handling - _save_or_preview_agent for final save/preview logic
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autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py
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Convert all CoPilot tools from kwargs.get() pattern to Pydantic models: Tools updated: - find_agent.py: FindAgentInput - find_library_agent.py: FindLibraryAgentInput - find_block.py: FindBlockInput - search_docs.py: SearchDocsInput - get_doc_page.py: GetDocPageInput - create_agent.py: CreateAgentInput - edit_agent.py: EditAgentInput - run_block.py: RunBlockInput - workspace_files.py: 4 input models (List/Read/Write/Delete) Benefits: - Type safety with automatic validation - Consistent string stripping via field_validators - Better IDE support and error messages - Cleaner _execute methods using params object Addresses ntindle review feedback about kwargs pattern.
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⚠️ Outside diff range comments (4)
autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (1)
232-232:⚠️ Potential issue | 🔴 CriticalBug:
include_all_sessionsis undefined — will raiseNameErrorat runtime.This should reference
params.include_all_sessionsto match the pattern used elsewhere in this method (lines 214, 218).🐛 Proposed fix
- scope_msg = "all sessions" if include_all_sessions else "current session" + scope_msg = "all sessions" if params.include_all_sessions else "current session"autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py (1)
192-233:⚠️ Potential issue | 🟠 MajorFix NameError in error paths after params refactor.
agent_idandchangesare no longer defined, so these branches will raise at runtime. Useparams.*instead.Proposed fix
- return ErrorResponse( + return ErrorResponse( message="Failed to generate changes. The agent generation service may be unavailable or timed out. Please try again.", error="update_generation_failed", - details={"agent_id": agent_id, "changes": changes[:100]}, + details={"agent_id": params.agent_id, "changes": params.changes[:100]}, session_id=session_id, ) @@ - return ErrorResponse( + return ErrorResponse( message=user_message, error=f"update_generation_failed:{error_type}", details={ - "agent_id": agent_id, - "changes": changes[:100], + "agent_id": params.agent_id, + "changes": params.changes[:100], "service_error": error_msg, "error_type": error_type, }, session_id=session_id, )autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (2)
251-252:⚠️ Potential issue | 🔴 CriticalFix NameError: use
params.block_id.
block_idis no longer defined after the refactor. This will raise at runtime in both the missing-credentials path and the normal execution path.🐛 Proposed fix
- agent_id=block_id, + agent_id=params.block_id, @@ - synthetic_node_id = f"copilot-node-{block_id}" + synthetic_node_id = f"copilot-node-{params.block_id}"Also applies to: 280-281
8-49:⚠️ Potential issue | 🟡 MinorUse
Field(default_factory=dict)forinput_datainstead of mutable default.While Pydantic v2 prevents the classic shared mutable default bug through deep-copying, using
Field(default_factory=dict)is the recommended pattern for clarity and consistency.🔧 Proposed fix
-from pydantic import BaseModel, field_validator +from pydantic import BaseModel, Field, field_validator @@ - input_data: dict[str, Any] = {} + input_data: dict[str, Any] = Field(default_factory=dict)
🤖 Fix all issues with AI agents
In `@autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py`:
- Around line 6-7: Replace the deprecated inner class Config on the Pydantic
models with Pydantic v2 syntax by adding model_config =
ConfigDict(extra="allow") (import ConfigDict) and remove the inline comment that
violates coding guidelines; also fix the NameError by changing references to the
undefined symbols agent_id and changes to use the params object (use
params.agent_id and params.changes) wherever those are accessed (e.g., in the
functions/methods that currently reference agent_id and changes), and ensure you
import ConfigDict alongside BaseModel and field_validator.
In
`@autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.py`:
- Around line 17-23: The model declares query with a default empty string and
includes docstrings, causing a schema/model mismatch with runtime validation;
remove the docstrings around the field and change the declaration of query to be
required (remove `= ""`) and enforce non-empty input with Pydantic (e.g.,
Field(..., min_length=1) or equivalent) and update the `@field_validator`
`strip_string` to strip whitespace and raise a ValueError or return a validated
non-empty string when input is empty; reference the `query` field, the
`strip_string` validator, and the `search_agents()` call so the model-level
validation matches the runtime rejection of empty queries.
In `@autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py`:
- Around line 145-157: The code uses an undefined variable `path` when
constructing `doc_url` inside the successful return, causing a runtime error;
change the call to use the correct variable `params.path` (i.e., replace
`_make_doc_url(path)` with `_make_doc_url(params.path)`) in the DocPageResponse
construction within the method where `_extract_title` and `_make_doc_url` are
used so the doc_url is built from the provided params.
🧹 Nitpick comments (6)
autogpt_platform/backend/backend/api/features/chat/tools/search_docs.py (1)
37-41: Consider extracting the sharedstrip_stringvalidator.This identical validator logic is duplicated across multiple tool input models:
find_agent.py,find_block.py,get_doc_page.py,find_library_agent.py, and now here. Consider extracting it to a shared utility inmodels.pyor a dedicatedvalidators.pyto reduce duplication.♻️ Example shared validator approach
In
models.pyor a newvalidators.py:def strip_string_validator(v: Any) -> str: """Strip whitespace from string inputs.""" return v.strip() if isinstance(v, str) else (v if v is not None else "")Then in each input model:
+from backend.api.features.chat.tools.models import strip_string_validator + class SearchDocsInput(BaseModel): """Input parameters for the search_docs tool.""" query: str = "" - `@field_validator`("query", mode="before") - `@classmethod` - def strip_string(cls, v: Any) -> str: - """Strip whitespace from query.""" - return v.strip() if isinstance(v, str) else (v if v is not None else "") + _strip_query = field_validator("query", mode="before")(strip_string_validator)autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py (2)
39-51: Inconsistency: underscore-prefixed fields are defined but never used.The fields
_operation_idand_task_idare defined in the model (lines 40-41) but are extracted directly fromkwargsat lines 123-124 instead of being accessed viaparams. This makes these field definitions dead code and theextra = "allow"config comment misleading.Either:
- Remove these fields from the model since they're not being used, or
- Access them via
params(e.g.,params._operation_id) for consistencyAdditionally,
class Configis deprecated in Pydantic v2. Consider migrating tomodel_config.♻️ Suggested refactor: Remove unused fields and modernize config
class CreateAgentInput(BaseModel): """Input parameters for the create_agent tool.""" description: str = "" context: str = "" save: bool = True - # Internal async processing params (passed by long-running tool handler) - _operation_id: str | None = None - _task_id: str | None = None `@field_validator`("description", "context", mode="before") `@classmethod` def strip_strings(cls, v: Any) -> str: """Strip whitespace from string fields.""" return v.strip() if isinstance(v, str) else (v if v is not None else "") - class Config: - extra = "allow" # Allow _operation_id, _task_id from kwargs + model_config = {"extra": "ignore"}Since
_operation_idand_task_idare extracted directly from kwargs anyway, there's no need to allow extra fields in the model.
119-124: The param extraction pattern works but is inconsistent.Line 119 creates a validated
paramsobject, but lines 123-124 bypass it to extract_operation_idand_task_iddirectly fromkwargs. This dual approach is functional but reduces the benefit of the Pydantic model.Consider documenting or consolidating the approach, though this is minor given the current working state.
autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.py (1)
15-22: Remove docstrings to comply with the “avoid comments” guideline.These docstrings are short and the code is straightforward, so they don’t meet the “very complex” threshold.
🧹 Suggested change
class FindLibraryAgentInput(BaseModel): - """Input parameters for the find_library_agent tool.""" @@ def strip_string(cls, v: Any) -> str: - """Strip whitespace from query.""" return v.strip() if isinstance(v, str) else (v if v is not None else "")As per coding guidelines, "autogpt_platform/**/*.{ts,tsx,js,py}: Avoid comments at all times unless the code is very complex".
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (1)
33-49: Remove new docstrings/comments unless required.These short docstrings don’t add much and conflict with the project’s “avoid comments” guidance. Consider removing them if no tooling depends on them.
As per coding guidelines “Avoid comments at all times unless the code is very complex”.autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py (1)
23-31: Remove the new docstrings to align with the no-comments guideline.These docstrings aren’t necessary for such a small model/helper.
As per coding guidelines, Avoid comments at all times unless the code is very complex.🧹 Suggested cleanup
class GetDocPageInput(BaseModel): - """Input parameters for the get_doc_page tool.""" - path: str = "" `@field_validator`("path", mode="before") `@classmethod` def strip_string(cls, v: Any) -> str: - """Strip whitespace from path.""" return v.strip() if isinstance(v, str) else (v if v is not None else "")
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📒 Files selected for processing (9)
autogpt_platform/backend/backend/api/features/chat/tools/create_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/find_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.pyautogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/search_docs.pyautogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py
🧰 Additional context used
📓 Path-based instructions (2)
autogpt_platform/backend/**/*.py
📄 CodeRabbit inference engine (.github/copilot-instructions.md)
autogpt_platform/backend/**/*.py: Always run backend setup commands in order: poetry install, poetry run prisma migrate dev, poetry run prisma generate before backend development
Always run poetry run format (Black + isort) before poetry run lint (ruff) for backend code
Use Python 3.10-3.13 with Python 3.11 required for development (managed by Poetry via pyproject.toml)
autogpt_platform/backend/**/*.py: Use FastAPI with async support for API endpoints in the backend
Use Prisma ORM for database operations with PostgreSQL
Use RabbitMQ for async task processing in the backend
Use JWT-based authentication with Supabase integration
Usepoetry run format(Black + isort) to format code andpoetry run lint(ruff) for linting in the backend
Use ClamAV integration for file upload security
autogpt_platform/backend/**/*.py: Format Python code withpoetry run format
Runpoetry run test(runs pytest with a docker based postgres + prisma) before committing backend changes
Files:
autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/workspace_files.pyautogpt_platform/backend/backend/api/features/chat/tools/find_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.pyautogpt_platform/backend/backend/api/features/chat/tools/create_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/search_docs.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py
autogpt_platform/**/*.{ts,tsx,js,py}
📄 CodeRabbit inference engine (AGENTS.md)
Avoid comments at all times unless the code is very complex
Files:
autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/workspace_files.pyautogpt_platform/backend/backend/api/features/chat/tools/find_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.pyautogpt_platform/backend/backend/api/features/chat/tools/create_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/search_docs.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py
🧠 Learnings (6)
📚 Learning: 2025-11-25T08:48:33.246Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: .github/copilot-instructions.md:0-0
Timestamp: 2025-11-25T08:48:33.246Z
Learning: Applies to autogpt_platform/backend/backend/blocks/**/*.py : Agent blocks in backend/blocks/ must include: block definition with input/output schemas, execution logic with proper error handling, and tests validating functionality. Blocks inherit from Block base class with input/output schemas, implement run method, use uuid.uuid4() for block UUID, and be registered in block registry
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/backend/server/routers/**/*.py : Update block API routes in `/backend/backend/server/routers/` and add/update Pydantic models in the same directory
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Implement async `run` method in block implementations
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Inherit from `Block` base class and define input/output schemas using `BlockSchema` for new blocks
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Analyze block interfaces when creating multiple new blocks to ensure they compose well in a graph-based editor
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/find_block.py
📚 Learning: 2025-11-25T08:48:33.246Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: .github/copilot-instructions.md:0-0
Timestamp: 2025-11-25T08:48:33.246Z
Learning: Applies to autogpt_platform/backend/blocks/test/**/*.py : For backend tests, use poetry run pytest for validation. Block tests: poetry run pytest backend/blocks/test/test_block.py -xvs. Specific block: poetry run pytest 'backend/blocks/test/test_block.py::test_available_blocks[BlockName]' -xvs. Use --snapshot-update when output changes and always review with git diff
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
🧬 Code graph analysis (7)
autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (4)
autogpt_platform/backend/backend/api/features/chat/tools/models.py (2)
ToolResponseBase(46-51)ErrorResponse(195-200)autogpt_platform/backend/backend/data/workspace.py (1)
get_or_create_workspace(19-40)autogpt_platform/backend/backend/util/workspace.py (4)
WorkspaceManager(30-419)list_files(289-319)get_file_count(396-419)write_file(155-287)autogpt_platform/backend/backend/util/virus_scanner.py (1)
scan_content_safe(191-216)
autogpt_platform/backend/backend/api/features/chat/tools/find_agent.py (4)
autogpt_platform/backend/backend/api/features/chat/model.py (1)
ChatSession(95-261)autogpt_platform/backend/backend/api/features/chat/tools/agent_search.py (1)
search_agents(103-239)autogpt_platform/backend/backend/api/features/chat/tools/base.py (1)
BaseTool(16-129)autogpt_platform/backend/backend/api/features/chat/tools/models.py (1)
ToolResponseBase(46-51)
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (2)
autogpt_platform/backend/backend/api/features/chat/tools/models.py (3)
ToolResponseBase(46-51)ErrorResponse(195-200)BlockOutputResponse(359-366)autogpt_platform/backend/backend/data/block.py (2)
get_block(936-938)name(567-568)
autogpt_platform/backend/backend/api/features/chat/tools/find_block.py (3)
autogpt_platform/backend/backend/api/features/chat/tools/find_agent.py (1)
strip_string(21-23)autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py (1)
strip_string(30-32)autogpt_platform/backend/backend/api/features/chat/tools/models.py (1)
ToolResponseBase(46-51)
autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py (1)
autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py (2)
strip_strings(42-44)Config(46-47)
autogpt_platform/backend/backend/api/features/chat/tools/search_docs.py (5)
autogpt_platform/backend/backend/api/features/chat/tools/find_agent.py (1)
strip_string(21-23)autogpt_platform/backend/backend/api/features/chat/tools/find_block.py (1)
strip_string(29-31)autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.py (1)
strip_string(21-23)autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py (1)
strip_string(30-32)autogpt_platform/backend/backend/api/features/chat/tools/models.py (1)
ToolResponseBase(46-51)
autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py (4)
autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py (2)
strip_strings(45-47)Config(49-50)autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py (1)
strip_strings(82-84)autogpt_platform/backend/backend/api/features/chat/tools/agent_output.py (1)
strip_strings(47-49)autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py (1)
get_agent_as_json(800-826)
🪛 Ruff (0.14.14)
autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py
[error] 152-152: Undefined name path
(F821)
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🔇 Additional comments (19)
autogpt_platform/backend/backend/api/features/chat/tools/search_docs.py (4)
7-7: LGTM!The
field_validatorimport is correctly added to support the newSearchDocsInputmodel.
121-129: LGTM!The refactoring from
kwargs.get()to a typed Pydantic input model is a solid improvement. The validation flow is clean: instantiation handles type coercion and string stripping, followed by an explicit empty-query check that returns a user-friendly error.
131-139: LGTM!The hybrid search invocation correctly uses
params.queryand the explicitmin_score=0.1parameter improves readability.
207-213: LGTM!The response construction properly references
params.queryfor consistency with the new input model pattern.autogpt_platform/backend/backend/api/features/chat/tools/find_agent.py (2)
14-24: LGTM!The
FindAgentInputmodel follows the established PR pattern for typed input validation. Themode="before"validator correctly handles edge cases: stripping whitespace from strings, convertingNoneto empty string, and passing through other types for Pydantic's built-in coercion.
52-61: LGTM!Clean refactor to typed input handling. The
FindAgentInput(**kwargs)construction provides input validation, and anyValidationErroris properly caught by the base class'sexecutemethod which converts it to anErrorResponse. Usingparams.queryprovides type-safe field access.autogpt_platform/backend/backend/api/features/chat/tools/find_block.py (3)
22-32: Well-structured Pydantic input model.The
FindBlockInputmodel follows the established pattern used in other chat tools (find_agent.py,get_doc_page.py). Themode="before"validator correctly strips whitespace before Pydantic's type coercion, and the default empty string allows the method to return a user-friendly error message rather than a validation exception.
89-89: Good refactor to typed input parsing.The kwargs-to-Pydantic conversion provides type safety and automatic input normalization. Note that
ValidationErrorfrom malformed input would propagate uncaught since this line is outside thetryblock (starting at line 98). This is consistent with similar tools in the codebase, so presumably handled at a higher level.
92-196: Consistent usage of typed params throughout.All references to the query parameter now go through
params.query, providing consistent behavior with whitespace stripping applied. The error messages and response formatting correctly use the normalized value.autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (4)
81-138: LGTM!The Pydantic input models are well-structured with appropriate
field_validatordecorators usingmode="before"for input sanitization. The validators correctly handle edge cases (None values, non-string types) and provide a clean typed interface replacing raw kwargs access.
316-423: LGTM!The refactored
_executemethod correctly uses the typed input model throughout. The logic for deciding between inline content and metadata+URL response is well-structured, and allparams.*references are consistent.
483-563: LGTM!The refactored method properly validates inputs through the Pydantic model and maintains correct order of operations: authentication check → required field validation → base64 decode → size check → virus scan → write.
606-668: LGTM!The delete tool correctly uses the typed input model and handles both
file_idandpathidentification methods appropriately.autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py (3)
6-7: LGTM!Correct Pydantic v2 imports for the model definition.
126-149: LGTM!The validated
paramsobject is correctly used throughout fordescription,context, andsavefields. This provides type safety and automatic string stripping via the validator.
314-326: LGTM!Correct use of
params.savefor the preview vs. save conditional logic.autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (1)
185-233: Param normalization and execution flow look solid.Using a validated
paramsobject across block lookup, logging, execution, and response improves consistency and readability.Also applies to: 315-341
autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py (2)
7-8: No review needed.
92-132: Input and path validation flow looks solid.The early validation and traversal checks are clear and well-scoped.
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- customize_agent.py: Strip whitespace from split parts of agent_id - edit_agent.py: Use model_config instead of deprecated class Config - edit_agent.py: Fix undefined agent_id/changes → params.agent_id/params.changes - find_library_agent.py: Remove docstrings per coding guidelines - get_doc_page.py: Fix undefined path → params.path - run_block.py: Fix undefined block_id → params.block_id - workspace_files.py: Fix undefined include_all_sessions → params.include_all_sessions
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autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (1)
8-37:⚠️ Potential issue | 🟡 MinorUse
Field(default_factory=dict)forinput_dataand remove unnecessary docstrings.In Pydantic v2, mutable defaults like
{}are deep-copied per instance and don't create shared state; however,Field(default_factory=dict)is the idiomatic pattern for clarity. Additionally, docstrings on the class and field validators violate the coding guideline to avoid comments unless code is very complex. Consider removing or significantly minimizing docstrings.🛠️ Suggested changes
-from pydantic import BaseModel, field_validator +from pydantic import BaseModel, Field, field_validator class RunBlockInput(BaseModel): - """Input parameters for the run_block tool.""" - block_id: str = "" - input_data: dict[str, Any] = {} + input_data: dict[str, Any] = Field(default_factory=dict) `@field_validator`("block_id", mode="before") `@classmethod` def strip_block_id(cls, v: Any) -> str: - """Strip whitespace from block_id.""" return v.strip() if isinstance(v, str) else (v if v is not None else "") `@field_validator`("input_data", mode="before") `@classmethod` def ensure_dict(cls, v: Any) -> dict[str, Any]: - """Ensure input_data is a dict.""" return v if isinstance(v, dict) else {}
🧹 Nitpick comments (6)
autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py (1)
23-33: Remove docstrings from simple input model.The class and validator docstrings can be removed since this is straightforward code. As per coding guidelines, "Avoid comments at all times unless the code is very complex."
♻️ Proposed fix
class GetDocPageInput(BaseModel): - """Input parameters for the get_doc_page tool.""" - path: str = "" `@field_validator`("path", mode="before") `@classmethod` def strip_string(cls, v: Any) -> str: - """Strip whitespace from path.""" return v.strip() if isinstance(v, str) else (v if v is not None else "")autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (1)
195-195: Consider catching Pydantic validation errors explicitly for cleaner user messages.If invalid kwargs are passed, Pydantic's
ValidationErrorwill be caught by the genericExceptionhandler and the technical validation message will be returned to users. For a better UX, you could catchValidationErrorexplicitly and return a more user-friendly error.This is optional since the current behavior is functionally correct.
Example pattern (applies to all four tools)
from pydantic import ValidationError async def _execute(self, user_id: str | None, session: ChatSession, **kwargs: Any) -> ToolResponseBase: session_id = session.session_id try: params = ListWorkspaceFilesInput(**kwargs) except ValidationError as e: return ErrorResponse( message=f"Invalid parameters: {e.error_count()} validation error(s)", error=str(e), session_id=session_id, ) # ... rest of the methodautogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py (3)
32-47: Remove docstrings per coding guidelines.The docstrings at lines 33-34 and 43-44 should be removed. The code is self-explanatory and doesn't meet the "very complex" threshold for comments. As per coding guidelines,
autogpt_platform/**/*.{ts,tsx,js,py}: Avoid comments at all times unless the code is very complex.♻️ Suggested refactor
class CustomizeAgentInput(BaseModel): - """Input parameters for the customize_agent tool.""" - agent_id: str = "" modifications: str = "" context: str = "" save: bool = True `@field_validator`("agent_id", "modifications", "context", mode="before") `@classmethod` def strip_strings(cls, v: Any) -> str: - """Strip whitespace from string fields.""" if isinstance(v, str): return v.strip() return v if v is not None else ""
254-255: Remove docstring per coding guidelines.The method name
_handle_customization_resultis self-descriptive. As per coding guidelines,autogpt_platform/**/*.{ts,tsx,js,py}: Avoid comments at all times unless the code is very complex.♻️ Suggested refactor
) -> ToolResponseBase: - """Handle the result from customize_template using pattern matching.""" - # Ensure result is a dict if not isinstance(result, dict):
334-335: Remove docstring per coding guidelines.The method name
_save_or_preview_agentclearly describes its purpose. As per coding guidelines,autogpt_platform/**/*.{ts,tsx,js,py}: Avoid comments at all times unless the code is very complex.♻️ Suggested refactor
) -> ToolResponseBase: - """Save or preview the customized agent based on params.save.""" agent_name = customized_agent.get(autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (1)
33-49: Remove new docstrings to comply with the no-comments rule.These docstrings don’t add necessary complexity and can be dropped for consistency with the repo’s “avoid comments” guideline.
🧹 Proposed cleanup
class RunBlockInput(BaseModel): - """Input parameters for the run_block tool.""" - block_id: str = "" input_data: dict[str, Any] = {} @@ `@classmethod` def strip_block_id(cls, v: Any) -> str: - """Strip whitespace from block_id.""" return v.strip() if isinstance(v, str) else (v if v is not None else "") @@ `@classmethod` def ensure_dict(cls, v: Any) -> dict[str, Any]: - """Ensure input_data is a dict.""" return v if isinstance(v, dict) else {}As per coding guidelines: Avoid comments at all times unless the code is very complex.
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📒 Files selected for processing (6)
autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.pyautogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py
🚧 Files skipped from review as they are similar to previous changes (1)
- autogpt_platform/backend/backend/api/features/chat/tools/find_library_agent.py
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📓 Path-based instructions (2)
autogpt_platform/backend/**/*.py
📄 CodeRabbit inference engine (.github/copilot-instructions.md)
autogpt_platform/backend/**/*.py: Always run backend setup commands in order: poetry install, poetry run prisma migrate dev, poetry run prisma generate before backend development
Always run poetry run format (Black + isort) before poetry run lint (ruff) for backend code
Use Python 3.10-3.13 with Python 3.11 required for development (managed by Poetry via pyproject.toml)
autogpt_platform/backend/**/*.py: Use FastAPI with async support for API endpoints in the backend
Use Prisma ORM for database operations with PostgreSQL
Use RabbitMQ for async task processing in the backend
Use JWT-based authentication with Supabase integration
Usepoetry run format(Black + isort) to format code andpoetry run lint(ruff) for linting in the backend
Use ClamAV integration for file upload security
autogpt_platform/backend/**/*.py: Format Python code withpoetry run format
Runpoetry run test(runs pytest with a docker based postgres + prisma) before committing backend changes
Files:
autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.pyautogpt_platform/backend/backend/api/features/chat/tools/workspace_files.pyautogpt_platform/backend/backend/api/features/chat/tools/customize_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
autogpt_platform/**/*.{ts,tsx,js,py}
📄 CodeRabbit inference engine (AGENTS.md)
Avoid comments at all times unless the code is very complex
Files:
autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.pyautogpt_platform/backend/backend/api/features/chat/tools/workspace_files.pyautogpt_platform/backend/backend/api/features/chat/tools/customize_agent.pyautogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
🧠 Learnings (7)
📚 Learning: 2025-11-25T08:48:33.246Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: .github/copilot-instructions.md:0-0
Timestamp: 2025-11-25T08:48:33.246Z
Learning: Applies to autogpt_platform/backend/backend/blocks/**/*.py : Agent blocks in backend/blocks/ must include: block definition with input/output schemas, execution logic with proper error handling, and tests validating functionality. Blocks inherit from Block base class with input/output schemas, implement run method, use uuid.uuid4() for block UUID, and be registered in block registry
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/backend/server/routers/**/*.py : Update block API routes in `/backend/backend/server/routers/` and add/update Pydantic models in the same directory
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.pyautogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Implement async `run` method in block implementations
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Inherit from `Block` base class and define input/output schemas using `BlockSchema` for new blocks
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Analyze block interfaces when creating multiple new blocks to ensure they compose well in a graph-based editor
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
📚 Learning: 2026-01-28T18:29:18.328Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: autogpt_platform/CLAUDE.md:0-0
Timestamp: 2026-01-28T18:29:18.328Z
Learning: Applies to autogpt_platform/backend/blocks/**/*.py : Generate unique block IDs using `uuid.uuid4()`
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py
📚 Learning: 2026-01-28T18:29:47.969Z
Learnt from: CR
Repo: Significant-Gravitas/AutoGPT PR: 0
File: AGENTS.md:0-0
Timestamp: 2026-01-28T18:29:47.969Z
Learning: Applies to autogpt_platform/**/data/*.py : For changes touching `data/*.py`, validate user ID checks or explain why not needed
Applied to files:
autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py
🧬 Code graph analysis (3)
autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (6)
autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py (1)
strip_strings(42-46)autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py (1)
strip_strings(42-43)autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py (1)
strip_strings(45-47)autogpt_platform/backend/backend/api/features/chat/tools/models.py (2)
ToolResponseBase(46-51)ErrorResponse(195-200)autogpt_platform/backend/backend/data/workspace.py (1)
get_or_create_workspace(19-40)autogpt_platform/backend/backend/util/workspace.py (1)
WorkspaceManager(30-419)
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (3)
autogpt_platform/backend/backend/blocks/apollo/models.py (2)
BaseModel(10-20)model_dump(11-20)autogpt_platform/backend/backend/api/features/chat/tools/models.py (2)
ToolResponseBase(46-51)BlockOutputResponse(359-366)autogpt_platform/backend/backend/data/block.py (2)
get_block(936-938)name(567-568)
autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py (7)
autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py (1)
strip_strings(42-46)autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (2)
strip_strings(104-105)strip_strings(136-137)autogpt_platform/backend/backend/api/features/chat/tools/create_agent.py (1)
strip_strings(45-47)autogpt_platform/backend/backend/api/features/chat/tools/run_agent.py (1)
strip_strings(82-84)autogpt_platform/backend/backend/api/features/chat/tools/agent_output.py (1)
strip_strings(47-49)autogpt_platform/backend/backend/api/features/chat/tools/models.py (1)
ErrorResponse(195-200)autogpt_platform/backend/backend/api/features/chat/tools/agent_generator/core.py (1)
get_agent_as_json(800-826)
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- GitHub Check: Seer Code Review
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🔇 Additional comments (23)
autogpt_platform/backend/backend/api/features/chat/tools/get_doc_page.py (2)
7-8: LGTM!Pydantic imports are correctly added and both are utilized by the new input model.
105-157: LGTM - Input model pattern correctly implemented.All path references now consistently use
params.path, the previously reported undefinedpathbug is resolved, and the security checks for directory traversal are properly maintained.autogpt_platform/backend/backend/api/features/chat/tools/workspace_files.py (6)
5-7: LGTM!The new imports for
Any,BaseModel, andfield_validatorare appropriate for supporting the new Pydantic input models.
82-138: LGTM!The input models are well-structured with appropriate field validators for string normalization. The pattern is consistent with similar models in
edit_agent.py,create_agent.py, andcustomize_agent.py.
189-248: LGTM!The refactor to use
ListWorkspaceFilesInputfor validated, typed parameter access is clean. The limit clamping at line 204 properly enforces the maximum.
318-425: LGTM!The refactor properly uses
ReadWorkspaceFileInputfor validated parameter access. The assertion at line 355 is safe due to the mutual exclusivity check at line 333.
485-565: LGTM!The refactor correctly uses
WriteWorkspaceFileInputfor validated parameter access. The empty string checks (lines 500, 506) align with the validator's behavior of defaultingNoneto"".
608-670: LGTM!The refactor properly uses
DeleteWorkspaceFileInputfor validated parameter access. The assertion at line 640 is safe due to the mutual exclusivity check at line 623.autogpt_platform/backend/backend/api/features/chat/tools/edit_agent.py (7)
6-7: Module-level Pydantic imports look good.
32-43: Input model + string normalization are solid.
105-118: Typed params instantiation in_executeis clean.
125-143: Parameter presence checks are clear and consistent.
154-168: Context-aware update request composition looks correct.
188-226: Error details now reference validated params properly.
252-270: Save/preview branch uses validated flag as expected.autogpt_platform/backend/backend/api/features/chat/tools/customize_agent.py (7)
6-7: LGTM!The Pydantic imports are appropriate for the new input model pattern.
127-139: LGTM!The validation logic correctly handles empty strings after the model applies defaults, with clear error messages.
142-176: LGTM!The agent ID parsing with per-part stripping handles edge cases like
"creator / slug"well. Error handling is comprehensive with appropriate logging.
238-245: LGTM!Clean extraction of result handling logic into a dedicated helper method improves readability.
267-325: LGTM!The match/case pattern matching is clean, readable, and handles all expected response types with appropriate defensive checks.
336-392: LGTM!The save/preview logic is well-structured with appropriate error handling and authentication checks.
124-124: No action needed—validation errors are already handled gracefully by the framework.Pydantic validation errors from
CustomizeAgentInput(**kwargs)are caught by theBaseTool.executemethod's exception handler, which wraps them in anErrorResponsewith a user-facing error message. This applies consistently across all tools in the codebase.Likely an incorrect or invalid review comment.
autogpt_platform/backend/backend/api/features/chat/tools/run_block.py (1)
181-340: LGTM — validated params object simplifies flow.Using a typed params object and consistently referencing
params.block_id/params.input_datamakes the execution path clearer.
✏️ Tip: You can disable this entire section by setting review_details to false in your review settings.
Summary
Addresses code review feedback from @ntindle on multiple PRs regarding import organization, code patterns, and type safety.
Changes
1. Import Organization (service.py)
uuidimport to top levelcompress_contextimport to top level2. Pydantic Input Models for ALL Tools
Added typed input models to every CoPilot tool:
CustomizeAgentInputFindAgentInputFindLibraryAgentInputFindBlockInputSearchDocsInputGetDocPageInputCreateAgentInputEditAgentInputRunBlockInputEach model includes:
field_validatorfor string strippingparams.field3. Match/Case Pattern (customize_agent.py)
Replaced if/elif chains with cleaner match/case for response type handling.
Comment Links Addressed
Created by Otto