feat: Add form filling use case #403
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🦋 Changeset detectedLatest commit: a64df00 The changes in this PR will be included in the next version bump. This PR includes changesets to release 1 package
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Caution Review failedThe pull request is closed. WalkthroughThis pull request introduces a new "Form Filling" tool to the codebase, enhancing the existing toolset without altering current functionalities. The Changes
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templates/components/agents/python/form_filling/app/engine/engine.py
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templates/components/agents/python/form_filling/app/engine/workflow.py
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templates/components/engines/python/agent/tools/form_filling.py
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templates/components/agents/python/form_filling/README-template.md
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templates/types/streaming/nextjs/app/components/ui/chat/index.ts
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Actionable comments posted: 17
🧹 Outside diff range and nitpick comments (16)
templates/types/streaming/nextjs/app/components/ui/progress.tsx (1)
7-10: Consider type aliases for better readability
The type setup is correct, but could be more readable with type aliases.
Consider this improvement:
+type ProgressProps = React.ComponentPropsWithoutRef<typeof ProgressPrimitive.Root>;
+type ProgressRef = React.ElementRef<typeof ProgressPrimitive.Root>;
+
-const Progress = React.forwardRef<
- React.ElementRef<typeof ProgressPrimitive.Root>,
- React.ComponentPropsWithoutRef<typeof ProgressPrimitive.Root>
->(({ className, value, ...props }, ref) => (
+const Progress = React.forwardRef<ProgressRef, ProgressProps>(
+ ({ className, value, ...props }, ref) => (templates/components/agents/python/form_filling/app/engine/engine.py (3)
14-14: Remove unused **kwargs parameter.
The function accepts **kwargs but doesn't use it anywhere. Consider removing it to improve code clarity.
- chat_history: Optional[List[ChatMessage]] = None, **kwargs
+ chat_history: Optional[List[ChatMessage]] = None18-20: Enhance error message with specific command path.
The error message could be more helpful by specifying the full command path.
- "Index is not found! Please run `poetry run generate` to create an index."
+ "Index is not found! Please run `poetry run python -m app.scripts.generate` to create an index."25-25: Move type hint to a type alias.
Consider moving the inline type hint to a proper type alias at the module level for better readability.
+from typing import Any, Dict
+
+ConfiguredTools = Dict[str, list[Any]]
+
- configured_tools = ToolFactory.from_env(map_result=True) # type: dict[str, list[Any]]
+ configured_tools: ConfiguredTools = ToolFactory.from_env(map_result=True)templates/components/multiagent/python/app/api/routers/vercel_response.py (1)
57-58: Consider preserving type parameters for better type safety.
While the simplified types work, consider maintaining the type parameters for AsyncGenerator to ensure type safety and improve code maintainability:
- event_handler: Awaitable,
- events: AsyncGenerator,
+ event_handler: Awaitable[AsyncGenerator[str, None] | Generator[str, None, None] | Any],
+ events: AsyncGenerator[AgentRunEvent, None],templates/components/multiagent/python/app/workflows/single.py (2)
30-48: LGTM! Well-structured event system enhancement.
The new AgentRunEventType enum and updated AgentRunEvent class provide a clean and extensible way to categorize and handle different types of agent events.
Consider adding docstrings to describe:
- The purpose and use cases for each event type
- The structure of the response dictionary returned by
to_response
Example:
class AgentRunEventType(Enum):
+ """Categorizes different types of agent run events.
+
+ TEXT: Regular text-based events (default)
+ PROGRESS: Events indicating progress updates
+ """
TEXT = "text"
PROGRESS = "progress"Line range hint 156-190: Enhance streaming response handler robustness.
The streaming implementation could benefit from improved error handling and resource management:
- Add proper cleanup using try/finally
- Add explicit error handling
- Make the state transitions more explicit
Consider this improved implementation:
async def handle_llm_input_stream(
self, ctx: Context, ev: InputEvent
) -> ToolCallEvent | StopEvent:
chat_history = ev.input
+ response_stream = None
async def response_generator() -> AsyncGenerator:
- response_stream = await self.llm.astream_chat_with_tools(
- self.tools, chat_history=chat_history
- )
+ nonlocal response_stream
+ try:
+ response_stream = await self.llm.astream_chat_with_tools(
+ self.tools, chat_history=chat_history
+ )
- full_response = None
- yielded_indicator = False
- async for chunk in response_stream:
- if "tool_calls" not in chunk.message.additional_kwargs:
- # Yield a boolean to indicate whether the response is a tool call
- if not yielded_indicator:
- yield False
- yielded_indicator = True
+ full_response = None
+ state = "initial"
+ async for chunk in response_stream:
+ try:
+ is_tool_call = "tool_calls" in chunk.message.additional_kwargs
+
+ if state == "initial":
+ yield is_tool_call
+ state = "streaming" if not is_tool_call else "tool_call"
- # if not a tool call, yield the chunks!
- yield chunk
- elif not yielded_indicator:
- # Yield the indicator for a tool call
- yield True
- yielded_indicator = True
+ if state == "streaming" and not is_tool_call:
+ yield chunk
+
+ full_response = chunk
+ except Exception as e:
+ ctx.write_event_to_stream(
+ AgentRunEvent(
+ name=self.name,
+ msg=f"Error processing chunk: {str(e)}",
+ event_type=AgentRunEventType.TEXT
+ )
+ )
+ raise
- full_response = chunk
+ if full_response:
+ self.memory.put(full_response.message)
+ yield full_response
+ finally:
+ if response_stream and hasattr(response_stream, 'aclose'):
+ await response_stream.aclose()templates/types/streaming/fastapi/app/services/file.py (1)
80-81: Update comment to reflect current implementation.
The current comment "Don't index csv file if csv tools are available" is outdated and doesn't reflect the current implementation's rationale. Consider updating it to better explain why CSV files are not indexed.
- # Don't index csv file if csv tools are available
+ # Skip indexing CSV files as they are handled separatelyhelpers/tools.ts (1)
270-285: Add system prompt for form filling tool.
Consider adding system prompt via TOOL_SYSTEM_PROMPT_ENV_VAR to provide guidance on:
- Input data format expectations (CSV structure, required fields)
- Form filling workflow
- Error handling scenarios
Add the following to the tool configuration:
{
display: "Form Filling",
name: "form_filling",
supportedFrameworks: ["fastapi"],
type: ToolType.LOCAL,
dependencies: [
{
name: "pandas",
version: "^2.2.3",
},
{
name: "tabulate",
version: "^0.9.0",
},
],
+ envVars: [
+ {
+ name: TOOL_SYSTEM_PROMPT_ENV_VAR,
+ description: "System prompt for form filling tool.",
+ value: `You are a form filling assistant that helps users process and fill forms using CSV data.
+- Expect CSV files with headers that match form field names
+- Validate data format and completeness before processing
+- Handle errors gracefully and provide clear feedback on issues
+- Use pandas for data manipulation and tabulate for data presentation`,
+ },
+ ],
},templates/types/streaming/fastapi/app/api/routers/models.py (1)
133-155: LGTM! Consider minor optimization for large chat histories.
The changes effectively collect annotation contents from all user messages, which is necessary for the form filling use case. The implementation is clean and maintains good readability.
For better performance with large chat histories, consider adding an optional parameter to limit the number of historical messages processed:
- def get_last_message_content(self) -> str:
+ def get_last_message_content(self, max_history: Optional[int] = None) -> str:
"""
Get the content of the last message along with the data content from all user messages
+
+ Args:
+ max_history: Optional maximum number of historical messages to process
"""
if len(self.messages) == 0:
raise ValueError("There is not any message in the chat")
last_message = self.messages[-1]
message_content = last_message.content
# Collect annotation contents from all user messages
all_annotation_contents: List[str] = []
- for message in self.messages:
+ messages_to_process = self.messages if max_history is None else self.messages[-max_history:]
+ for message in messages_to_process:
if message.role == MessageRole.USER and message.annotations is not None:
annotation_contents = filter(
None,
[annotation.to_content() for annotation in message.annotations],
)
all_annotation_contents.extend(annotation_contents)questions/questions.ts (2)
180-206: LGTM! Consider adding type safety.
The implementation is well-integrated with the existing codebase and follows consistent patterns. However, consider adding type safety for the agents property.
Add type definitions to improve type safety:
type AgentType = 'financial_report' | 'form_filling' | 'blog_writer';
interface QuestionArgs {
// ... existing properties
agents?: AgentType;
}187-201: Consider extracting agent choices as a constant.
To improve maintainability and reusability, consider extracting the choices array to a constant, similar to how other configuration options are handled in the codebase.
const AGENT_CHOICES = [
{
title: "Financial report (generate a financial report)",
value: "financial_report",
},
{
title: "Form filling (fill missing value in a CSV file)",
value: "form_filling",
},
{
title: "Blog writer (Write a blog post)",
value: "blog_writer",
},
] as const;templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (1)
209-234: Ensure consistent error handling strategy
While the try-catch block prevents crashes, consider implementing a user-facing notification or fallback logic when parsing progress data fails to enhance user experience.
templates/components/agents/python/form_filling/app/engine/workflow.py (3)
248-249: Address TODO: Add Typing for Progress Message
There's a TODO comment indicating a missing typing for the progress message in the find_answers method. Adding appropriate type hints improves code readability and maintainability.
Would you like assistance in defining the type annotations for the progress message structure? If so, consider creating a data class for the progress message.
from dataclasses import dataclass
@dataclass
class ProgressMessage:
progress_id: str
total_steps: int
current_step: int
step_msg: strThen update the code to use this data class:
progress_message = ProgressMessage(
progress_id=progress_id,
total_steps=total_steps,
current_step=i,
step_msg=f"Querying for: {cell.question_to_answer}",
)
ctx.write_event_to_stream(
AgentRunEvent(
name="Researcher",
msg=json.dumps(progress_message.__dict__),
event_type=AgentRunEventType.PROGRESS,
)
)170-171: Enhance Docstring Clarity and Formatting
The docstring for the extract_missing_cells method could be expanded for clarity, providing more insight into its functionality and expected inputs/outputs.
Consider revising the docstring:
"""
Extract missing cells from a CSV file and generate questions to fill them.
This method calls the extractor tool to identify missing cells in the provided CSV data.
It then formulates questions that can be used to obtain the missing information.
"""323-348: Avoid Catching Broad Exceptions Without Specific Handling
Catching all exceptions using except Exception as e can mask unexpected errors and make debugging difficult. It's better to catch specific exceptions or re-raise unexpected ones after logging.
Consider refining the exception handling:
try:
response: ToolOutput = tool.call(**tool_selection.tool_kwargs)
return response
except SomeSpecificException as e:
# Handle known exceptions
# ...
except Exception as e:
# Log the unexpected exception and re-raise
ctx.write_event_to_stream(
AgentRunEvent(
name=agent_name,
msg=f"Unexpected error: {str(e)}",
)
)
raise📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
📒 Files selected for processing (21)
- helpers/tools.ts (1 hunks)
- helpers/types.ts (1 hunks)
- questions/questions.ts (1 hunks)
- questions/simple.ts (3 hunks)
- templates/components/agents/python/blog/app/agents/publisher.py (1 hunks)
- templates/components/agents/python/blog/app/agents/researcher.py (1 hunks)
- templates/components/agents/python/financial_report/app/agents/analyst.py (1 hunks)
- templates/components/agents/python/financial_report/app/agents/reporter.py (1 hunks)
- templates/components/agents/python/form_filling/README-template.md (1 hunks)
- templates/components/agents/python/form_filling/app/engine/engine.py (1 hunks)
- templates/components/agents/python/form_filling/app/engine/workflow.py (1 hunks)
- templates/components/engines/python/agent/tools/init.py (1 hunks)
- templates/components/engines/python/agent/tools/form_filling.py (1 hunks)
- templates/components/multiagent/python/app/api/routers/vercel_response.py (3 hunks)
- templates/components/multiagent/python/app/workflows/single.py (3 hunks)
- templates/types/streaming/fastapi/app/api/routers/models.py (2 hunks)
- templates/types/streaming/fastapi/app/services/file.py (2 hunks)
- templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (7 hunks)
- templates/types/streaming/nextjs/app/components/ui/chat/index.ts (1 hunks)
- templates/types/streaming/nextjs/app/components/ui/progress.tsx (1 hunks)
- templates/types/streaming/nextjs/package.json (1 hunks)
🧰 Additional context used
📓 Path-based instructions (17)
templates/components/agents/python/blog/app/agents/publisher.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/blog/app/agents/researcher.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/financial_report/app/agents/analyst.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/financial_report/app/agents/reporter.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/form_filling/README-template.md (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/form_filling/app/engine/engine.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/form_filling/app/engine/workflow.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/engines/python/agent/tools/__init__.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/engines/python/agent/tools/form_filling.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/multiagent/python/app/api/routers/vercel_response.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/multiagent/python/app/workflows/single.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/types/streaming/fastapi/app/api/routers/models.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/types/streaming/fastapi/app/services/file.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/types/streaming/nextjs/app/components/ui/chat/index.ts (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/types/streaming/nextjs/app/components/ui/progress.tsx (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/types/streaming/nextjs/package.json (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
🪛 Ruff
templates/components/agents/python/blog/app/agents/publisher.py
14-14: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
templates/components/agents/python/financial_report/app/agents/analyst.py
25-25: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
🪛 Markdownlint
templates/components/agents/python/form_filling/README-template.md
31-31: null
Fenced code blocks should have a language specified
(MD040, fenced-code-language)
43-43: null
Fenced code blocks should have a language specified
(MD040, fenced-code-language)
🔇 Additional comments (25)
templates/types/streaming/nextjs/app/components/ui/progress.tsx (2)
1-6: LGTM: Proper setup with necessary imports
The component is correctly set up as a client component with appropriate imports.
25-27: LGTM: Proper component naming and export
The display name is correctly set for debugging purposes, and the export is clean.
templates/components/agents/python/form_filling/app/engine/engine.py (1)
13-15: Consider moving and renaming this function for consistency.
As suggested in the previous review, consider:
- Moving this function to
factory.py - Renaming it to
create_workflowfor consistency with other agent templates
templates/components/agents/python/blog/app/agents/publisher.py (1)
17-19: LGTM! Clear and well-structured prompt instructions.
The updated prompt instructions clearly differentiate between direct content replies and file generation scenarios, providing good guidance for the agent's behavior.
templates/types/streaming/nextjs/package.json (1)
18-18: LGTM: Appropriate addition of Radix UI Progress component dependency.
The addition of @radix-ui/react-progress aligns well with the existing UI component choices and follows the project's versioning patterns.
templates/components/agents/python/financial_report/app/agents/reporter.py (1)
27-28:
Improve type safety and error handling
The current implementation has multiple type safety and error handling concerns:
- Using
type: ignorecomments masks potential type issues - Direct dictionary access could raise KeyError
- No validation of the tool type before appending
Consider applying these improvements:
- if "generate_document" in configured_tools: # type: ignore
- tools.append(configured_tools["generate_document"]) # type: ignore
+ from typing import Dict, Type
+ configured_tools = configured_tools or {} # Handle None case
+
+ # Proper typing for configured_tools
+ tools_dict: Dict[str, Type[BaseTool]] = configured_tools
+
+ # Safe dictionary access with type validation
+ if generate_doc_tool := tools_dict.get("generate_document"):
+ if isinstance(generate_doc_tool, type) and issubclass(generate_doc_tool, BaseTool):
+ tools.append(generate_doc_tool)Let's verify the tool name consistency across the codebase:
templates/components/agents/python/financial_report/app/agents/analyst.py (1)
25-26:
Simplify dictionary key check and verify tool name consistency.
The code can be improved in two ways:
- Use Python's preferred dictionary membership testing syntax
- Verify the tool name change from "interpreter" to "interpret" across the codebase
Apply this improvement:
- if "interpret" in configured_tools.keys():
+ if "interpret" in configured_tools:Let's verify the tool name consistency:
✅ Verification successful
Simplify dictionary key check, tool name is consistent
The code style can be improved, but the tool naming is consistent across the codebase. The term "interpreter" appears in documentation and system prompts, while "interpret" is used as the configuration key, which is the correct pattern.
Apply this improvement:
- if "interpret" in configured_tools.keys():
+ if "interpret" in configured_tools:🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Check for any remaining references to the old "interpreter" tool name
# and verify the new "interpret" tool name usage
echo "Checking for old 'interpreter' tool references..."
rg -l "interpreter.*tool"
echo "Checking for new 'interpret' tool usage..."
rg -l "interpret.*tool"
Length of output: 1133
Script:
#!/bin/bash
# Let's examine the actual usage context in these files to understand the naming pattern
echo "Checking content of analyst.py for tool configuration..."
rg -A 5 -B 5 "interpret.*tool|interpreter.*tool" "templates/components/agents/python/financial_report/app/agents/analyst.py"
echo -e "\nChecking content of README for documentation of tool naming..."
rg -A 5 -B 5 "interpret.*tool|interpreter.*tool" "templates/components/agents/python/financial_report/README-template.md"
echo -e "\nChecking CHANGELOG for related changes..."
rg -A 2 -B 2 "interpret.*tool|interpreter.*tool" "CHANGELOG.md"
echo -e "\nChecking tools.ts for tool configuration..."
rg -A 5 -B 5 "interpret.*tool|interpreter.*tool" "helpers/tools.ts"
Length of output: 4761
🧰 Tools
🪛 Ruff
25-25: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
helpers/types.ts (1)
51-51: LGTM! Type addition is well-structured.
The addition of "form_filling" to TemplateAgents type follows the established naming pattern and integrates well with the existing template configuration system.
templates/types/streaming/nextjs/app/components/ui/chat/index.ts (1)
60-62: 🛠️ Refactor suggestion
Breaking changes detected in AgentEventData type.
The changes to AgentEventData properties (agent → name, text → msg) and addition of event_type constitute breaking changes that will require updates in consuming code.
Let's verify the impact:
Consider providing a migration guide or deprecation warnings for consumers of this type. You might want to:
- Document the breaking changes
- Update all consuming code to use the new property names
- Consider adding JSDoc comments to explain the purpose of each field
The previous review comment suggested a more extensible structure. Consider this alternative approach that provides better type safety and extensibility:
type AgentEventData = {
name: string;
type: "text" | "progress" | "task"; // Extensible event types
data: TextData | ProgressData | TaskData;
};
type TextData = {
msg: string;
};
type ProgressData = {
current: number;
total: number;
};
type TaskData = {
id: string;
msg: string;
progress?: ProgressData;
};This structure:
- Provides better type safety through discriminated unions
- Makes it easier to add new event types
- Keeps related data grouped logically
templates/components/engines/python/agent/tools/__init__.py (2)
72-74: Verify tool name consistency across the codebase.
The change from using tool_name to tool.metadata.name as the mapping key could affect code that depends on specific tool names.
Let's verify tool name usage across the codebase:
#!/bin/bash
# Description: Find potential tool name references that might be affected
# Look for direct tool name references
rg -A 2 "tools\[[\"\'][\w_]+[\"\']\]"
# Look for tool configurations to compare with metadata names
fd "tools.yaml$" -x cat {} 72-74:
Add type safety checks and handle potential metadata issues.
The current implementation has a few concerns:
- The type ignore comment masks potential type issues with the dictionary update
- There's no validation that
tool.metadataortool.metadata.nameexists
Consider applying this safer implementation:
- tools.update( # type: ignore
- {tool.metadata.name: tool for tool in loaded_tools}
- )
+ for tool in loaded_tools:
+ if not hasattr(tool, 'metadata') or not hasattr(tool.metadata, 'name'):
+ raise ValueError(f"Tool {tool} is missing required metadata")
+ tools[tool.metadata.name] = [tool] # type: Dict[str, List[FunctionTool]]This change:
- Validates metadata existence
- Maintains type safety without ignoring types
- Preserves the List[FunctionTool] value type as per the return type annotation
Let's verify the tool metadata structure:
templates/components/agents/python/blog/app/agents/researcher.py (2)
53-53: Consider the implications of using append instead of extend.
The change from extend to append assumes that each tool is a single object rather than a list of tools. This is correct if ToolFactory.from_env() returns individual tool instances for each key.
#!/bin/bash
# Description: Verify the return type of tools from ToolFactory
# Expected: Find evidence that tools are returned as individual instances
ast-grep --pattern 'class ToolFactory:
$$$
def from_env($$$):
$$$'45-49: Verify the availability and compatibility of the new DuckDuckGo tools.
The changes replace the generic "duckduckgo" tool with more specific "duckduckgo_search" and "duckduckgo_image_search" tools. While this provides better granularity, we should verify that these tools are properly configured.
✅ Verification successful
The DuckDuckGo tool changes are properly implemented and available
The search results confirm that:
- Both
duckduckgo_searchandduckduckgo_image_searchtools are properly defined intemplates/components/engines/python/agent/tools/duckduckgo.py - The tools are properly exposed through the
get_tools()function usingFunctionTool.from_defaults - The researcher agent correctly references these tool names in its configuration
The change from the generic "duckduckgo" to specific search and image search tools is valid and properly supported by the codebase.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify the new DuckDuckGo tools are properly defined and configured
# Expected: Find tool specifications or configurations for the new DuckDuckGo tools
# Search for tool definitions
echo "Searching for DuckDuckGo tool definitions..."
rg -l "duckduckgo_search|duckduckgo_image_search"
# Search for any environment configurations related to these tools
echo "Searching for DuckDuckGo tool configurations..."
fd -t f ".env" --exec rg -l "DUCKDUCKGO"
Length of output: 252
Script:
#!/bin/bash
# Let's try a more comprehensive search for DuckDuckGo related tools and configurations
# Search for DuckDuckGo related imports and tool definitions
echo "Searching for DuckDuckGo related code..."
rg -i "duckduckgo" --type py -A 5 -B 5
# Search for tool factory or tool registration patterns
echo "Searching for tool registration patterns..."
ast-grep --pattern 'class $_ {
$$$
def get_tools($$$) {
$$$
}
}'
# Search for any environment or configuration files
echo "Looking for configuration files..."
fd -e yml -e yaml -e env -e conf -e config -e ini
Length of output: 8172
templates/components/multiagent/python/app/api/routers/vercel_response.py (3)
4-4: LGTM: Import changes align with new type requirements.
The addition of Generator and simplified AsyncGenerator imports support the new stream handling capabilities.
95-95: LGTM: Simplified event response handling.
Direct use of to_response() improves code maintainability by removing an unnecessary abstraction layer.
67-81: 🛠️ Refactor suggestion
Add defensive error handling for generator processing.
The generator handling logic should include error handling for string conversion and attribute access:
if isinstance(result, AsyncGenerator):
async for token in result:
- final_response += str(token.delta)
- yield self.convert_text(token.delta)
+ try:
+ delta = str(token.delta) if hasattr(token, 'delta') else str(token)
+ final_response += delta
+ yield self.convert_text(delta)
+ except Exception as e:
+ logger.error(f"Error processing async token: {e}")
elif isinstance(result, Generator):
for chunk in result:
- chunk_str = str(chunk)
- final_response += chunk_str
- yield self.convert_text(chunk_str)
+ try:
+ chunk_str = str(chunk)
+ final_response += chunk_str
+ yield self.convert_text(chunk_str)
+ except Exception as e:
+ logger.error(f"Error processing sync chunk: {e}")
else:
if hasattr(result, "response"):
- content = result.response.message.content
- if content:
- for token in content:
- final_response += str(token)
- yield self.convert_text(token)
+ try:
+ content = result.response.message.content
+ if content:
+ for token in content:
+ token_str = str(token)
+ final_response += token_str
+ yield self.convert_text(token_str)
+ except AttributeError as e:
+ logger.error(f"Invalid response structure: {e}")Let's verify the current error handling patterns in the codebase:
questions/simple.ts (3)
13-13: LGTM: Type definition follows conventions.
The addition of "form_filling" to the AppType union type is consistent with existing naming conventions.
39-42: LGTM: UI prompt is consistent with existing patterns.
The new form filling option is well-placed and follows the established pattern for workflow-based features.
160-167:
Review the form filling configuration.
Several aspects of the configuration need attention:
-
The
dataSourcesis currently set toEXAMPLE_10K_SEC_FILESwhich contains SEC filings. This seems inappropriate for a form filling use case. Consider using form-specific example files or templates. -
The tools array is minimal. Consider if additional tools might be needed for:
- PDF processing
- Data validation
- Data export/import
-
The
modelConfigenforces GPT-4, which might be unnecessary for simple forms. Consider allowing less powerful models for basic form filling tasks to reduce costs.
Let's check what tools are available:
Consider this revised configuration:
form_filling: {
template: "multiagent",
agents: "form_filling",
- tools: getTools(["form_filling"]),
+ tools: getTools(["form_filling", "document_generator"]),
- dataSources: EXAMPLE_10K_SEC_FILES,
+ dataSources: [], // Will be provided by the user during form upload
frontend: true,
- modelConfig: MODEL_GPT4o,
+ modelConfig: undefined, // Let users choose the model based on form complexity
},✅ Verification successful
Based on the shell script results, I can now provide a final response:
The form filling configuration needs revision based on the available tools
Looking at the tools.ts implementation:
- The
form_fillingtool is correctly defined and only requires pandas and tabulate dependencies - The
document_generatortool suggestion is valid as it supports PDF generation - Using
EXAMPLE_10K_SEC_FILESas datasource is inappropriate since form filling should work with user-provided forms
Suggested configuration:
form_filling: {
template: "multiagent",
agents: "form_filling",
- tools: getTools(["form_filling"]),
+ tools: getTools(["form_filling", "document_generator"]),
- dataSources: EXAMPLE_10K_SEC_FILES,
+ dataSources: [], // Forms will be provided by users at runtime
frontend: true,
- modelConfig: MODEL_GPT4o,
+ modelConfig: undefined, // Let system choose based on form complexity
},🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for tool definitions to see available options
rg "export const.*tools.*=" helpers/
Length of output: 196
Script:
#!/bin/bash
# Let's check the content of tools.ts to understand available tools
cat helpers/tools.ts
Length of output: 11212
Script:
#!/bin/bash
# Let's also check if there are any form-related data sources defined
rg "export const.*dataSources.*=" -A 5
Length of output: 40
Script:
#!/bin/bash
# Check for any form-related configurations or templates
rg "form" -t ts
Length of output: 14652
templates/components/multiagent/python/app/workflows/single.py (1)
Line range hint 1-19: LGTM! Imports are well-organized and necessary.
The imports are comprehensive and properly structured, with the new Enum import supporting the AgentRunEventType implementation.
templates/types/streaming/fastapi/app/services/file.py (1)
9-9: LGTM! Clean import removal.
The removal of unused imports aligns with the code changes and improves maintainability.
templates/types/streaming/fastapi/app/api/routers/models.py (1)
63-67: LGTM! Clear distinction between sandbox and local file paths.
The changes appropriately separate concerns between sandbox paths (for artifact/code interpreter tools) and local paths (for form filling/extractor tools), with clear usage instructions in the content.
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (2)
65-96: LGTM: Proper implementation of the TextContent component
The TextContent component is well-implemented, effectively handling text truncation and providing an option to display all content when necessary.
98-119: LGTM: Correct use of the ProgressContent component
The ProgressContent component accurately displays progress information and integrates seamlessly with the Progress component.
templates/components/agents/python/form_filling/app/engine/workflow.py (1)
126-157: 🛠️ Refactor suggestion
Use Asynchronous Tool Invocation to Prevent Blocking
The _call_tool method is synchronous, which can cause blocking behavior in an asynchronous workflow. Since FunctionTool supports asynchronous execution via acall, consider updating _call_tool to be asynchronous and use await when calling tools.
Modify _call_tool to be asynchronous:
- def _call_tool(
+ async def _call_tool(
self,
ctx: Context,
agent_name: str,
tool: FunctionTool,
tool_selection: ToolSelection,
) -> ToolOutput:
- response: ToolOutput = tool.call(**tool_selection.tool_kwargs)
+ response: ToolOutput = await tool.acall(**tool_selection.tool_kwargs)Update calls to _call_tool accordingly:
- response = self._call_tool(
+ response = await self._call_tool(
ctx,
agent_name="Extractor",
tool=self.extractor_tool,
tool_selection=ev.tool_call,
)Likely invalid or redundant comment.
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Actionable comments posted: 9
🧹 Outside diff range and nitpick comments (12)
.changeset/large-parents-exercise.md (1)
5-5: Enhance the changeset description with more details.
The current description is quite brief. Consider adding more details about:
- The new form filling tool and its capabilities
- Framework support (fastapi)
- Required dependencies (pandas, tabulate)
- Integration with existing workflows
Example enhanced description:
Add form filling use case (Python)
This adds a new Form Filling tool that:
- Enables programmatic form filling capabilities
- Supports FastAPI framework
- Requires pandas and tabulate dependencies
- Integrates with existing workflow system
- Adds new template agent type for form filling
templates/components/agents/python/blog/app/agents/publisher.py (1)
17-19: Improve prompt text formatting.
The prompt text could be more readable with better indentation. Consider adjusting the text alignment:
- Normally, reply the blog post content to the user directly.
- But if user requested to generate a file, use the generate_document tool to generate the file and reply the link to the file.
+ Normally, reply the blog post content to the user directly.
+ But if user requested to generate a file, use the generate_document tool to generate the file and reply the link to the file.templates/components/agents/python/form_filling/README-template.md (1)
25-29: Improve API testing example.
- Add language specification to the code block
- Use a form-filling specific example that demonstrates the tool's capabilities
Here's the suggested improvement:
-```
+```bash
curl --location 'localhost:8000/api/chat' \
--header 'Content-Type: application/json' \
-'{ "messages": [{ "role": "user", "content": "What can you do?" }] }'
+'{ "messages": [{ "role": "user", "content": "Can you help me fill out a registration form?" }] }'🧰 Tools
🪛 Markdownlint
25-25: null
Fenced code blocks should have a language specified
(MD040, fenced-code-language)
templates/components/agents/python/financial_report/app/agents/analyst.py (2)
25-26: Simplify dictionary key check.
The code can be made more pythonic by removing the .keys() call.
Apply this change:
- if "interpret" in configured_tools.keys():
+ if "interpret" in configured_tools:🧰 Tools
🪛 Ruff
25-25: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
Line range hint 25-33: Clarify contradicting instructions about code inclusion.
The prompt instructions contain potentially contradicting statements:
- "make sure you include the right code and data for the visualization"
- "Never include any code into the report"
This might confuse the AI agent about whether to include the visualization code or not.
Consider clarifying the instructions like this:
prompt_instructions += dedent("""
You are able to visualize the financial data using code interpreter tool.
- It's very useful to create and include visualizations to the report (make sure you include the right code and data for the visualization).
+ It's very useful to create visualizations using code. Include only the resulting visualizations in the report, not the code used to generate them.
Never include any code into the report, just the visualization.
""")🧰 Tools
🪛 Ruff
25-25: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
templates/components/multiagent/python/app/api/routers/vercel_response.py (3)
68-76: Add error handling and fix indentation
The result handling is more flexible now, but consider:
- Adding error handling for invalid token types
- Fixing indentation in the if-else block for better readability
if isinstance(result, AsyncGenerator):
async for token in result:
- final_response += str(token.delta)
- yield self.convert_text(token.delta)
+ try:
+ final_response += str(token.delta)
+ yield self.convert_text(token.delta)
+ except AttributeError:
+ logger.warning(f"Invalid token format: {token}")
else:
if hasattr(result, "response"):
content = result.response.message.content
if content:
for token in content:
- final_response += str(token)
- yield self.convert_text(token)
+ try:
+ final_response += str(token)
+ yield self.convert_text(token)
+ except Exception as e:
+ logger.warning(f"Error processing token: {e}")90-90: Add error handling for event.to_response()
The direct call to event.to_response() simplifies the code, but consider adding error handling for events that might not implement this method.
- event_response = event.to_response()
+ try:
+ event_response = event.to_response()
+ except AttributeError:
+ logger.warning(f"Event {type(event)} does not implement to_response()")
+ continueLine range hint 13-19: Consider implementing error boundaries
While the class effectively handles streaming responses, consider implementing proper error boundaries to isolate failures and provide better error reporting, especially important for the new form-filling feature. This could include:
- Dedicated error types for different failure modes
- Structured error responses that clients can handle gracefully
- Metrics collection for different types of failures
questions/simple.ts (2)
55-56: Consider tracking the TypeScript support task.
The TODO comment indicates pending TypeScript support for the form filling use case.
Would you like me to create a GitHub issue to track the TypeScript support implementation?
56-70: Consider making the language restriction more explicit.
The code implicitly forces FastAPI for form filling by skipping the language selection. Consider:
- Making this restriction more explicit in the code
- Adding a comment explaining why form filling is restricted to FastAPI
- if (appType !== "form_filling") {
+ // Form filling currently only supports FastAPI
+ const defaultLanguage: TemplateFramework = "fastapi";
+ if (appType === "form_filling") {
+ language = defaultLanguage;
+ } else {
const { language: newLanguage } = await prompts(
{
type: "select",templates/components/agents/python/form_filling/app/agents/form_filling.py (2)
110-114: Remove unintended indentation from system_prompt
The _default_system_prompt string may include unintended leading whitespace due to the use of triple-quoted strings. This can affect how the prompt is interpreted by the LLM. Consider using textwrap.dedent to normalize the indentation.
Apply this fix:
import textwrap
...
_default_system_prompt = textwrap.dedent("""
You are a helpful assistant who helps fill missing cells in a CSV file.
Only use provided data, never make up any information yourself. Fill N/A if the answer is not found.
""")269-269: Adjust current_step in progress reporting
The current_step in your progress message starts from 0. To accurately reflect progress to the user, consider incrementing i by 1.
Apply this minor change:
- "current_step": i,
+ "current_step": i + 1,📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
📒 Files selected for processing (11)
- .changeset/large-parents-exercise.md (1 hunks)
- questions/simple.ts (4 hunks)
- templates/components/agents/python/blog/app/agents/publisher.py (1 hunks)
- templates/components/agents/python/blog/app/agents/researcher.py (1 hunks)
- templates/components/agents/python/financial_report/app/agents/analyst.py (1 hunks)
- templates/components/agents/python/financial_report/app/agents/reporter.py (1 hunks)
- templates/components/agents/python/form_filling/README-template.md (1 hunks)
- templates/components/agents/python/form_filling/app/agents/form_filling.py (1 hunks)
- templates/components/agents/python/form_filling/app/engine/engine.py (1 hunks)
- templates/components/engines/python/agent/tools/init.py (2 hunks)
- templates/components/multiagent/python/app/api/routers/vercel_response.py (3 hunks)
🚧 Files skipped from review as they are similar to previous changes (4)
- templates/components/agents/python/blog/app/agents/researcher.py
- templates/components/agents/python/financial_report/app/agents/reporter.py
- templates/components/agents/python/form_filling/app/engine/engine.py
- templates/components/engines/python/agent/tools/init.py
🧰 Additional context used
📓 Path-based instructions (5)
templates/components/agents/python/blog/app/agents/publisher.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/financial_report/app/agents/analyst.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/form_filling/README-template.md (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/agents/python/form_filling/app/agents/form_filling.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
templates/components/multiagent/python/app/api/routers/vercel_response.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
🪛 Ruff
templates/components/agents/python/blog/app/agents/publisher.py
14-14: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
templates/components/agents/python/financial_report/app/agents/analyst.py
25-25: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
🪛 Markdownlint
templates/components/agents/python/form_filling/README-template.md
25-25: null
Fenced code blocks should have a language specified
(MD040, fenced-code-language)
37-37: null
Fenced code blocks should have a language specified
(MD040, fenced-code-language)
🔇 Additional comments (9)
templates/components/agents/python/blog/app/agents/publisher.py (1)
14-15: Skipping review of tool key check.
A previous review comment already addresses the .keys() simplification and tool key naming consistency.
🧰 Tools
🪛 Ruff
14-14: Use key in dict instead of key in dict.keys()
Remove .keys()
(SIM118)
templates/components/agents/python/form_filling/README-template.md (3)
1-2: LGTM!
The introduction clearly states the project's purpose and includes properly formatted links to relevant documentation.
16-20: LGTM!
The development server instructions are clear and consistent with the setup process.
41-48: LGTM!
The resources section provides relevant links and encourages community participation.
templates/components/multiagent/python/app/api/routers/vercel_response.py (1)
4-4: LGTM! Import changes align with type updates
The addition of Awaitable to the imports supports the new type annotations in the code.
questions/simple.ts (4)
13-13: LGTM: Type definition update is correct.
The addition of "form_filling" to the AppType union type is properly implemented.
39-42: LGTM: Form filling choice is properly implemented.
The new choice follows the established pattern for workflow-based options and maintains consistency with existing choices.
163-170: Empty dataSources array aligns with PDF upload plans.
The empty dataSources array is consistent with the previous discussion about PDF file uploads. As mentioned in past comments, the data source will be provided through PDF file uploads rather than predefined sources.
166-166: Verify form filling tool configuration.
Let's verify that the form filling tool is properly defined in the tools helper.
✅ Verification successful
Form filling tool is properly configured
The form filling tool is correctly defined in the tools configuration with:
- Display name: "Form Filling"
- Tool name: "form_filling"
- Supported framework: "fastapi"
- Required dependencies: pandas and tabulate
- Type: LOCAL
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Description: Verify form filling tool configuration
# Test: Check if form_filling tool is defined in tools helper
rg -A 5 "form_filling.*supportedTools" helpers/
Length of output: 49
Script:
#!/bin/bash
# Let's try a broader search for form_filling tool definition
rg -l "form_filling" .
# Search for tools configuration
rg "supportedTools.*form_filling" .
# Search for getTools implementation
ast-grep --pattern 'function getTools($_) { $$$ }'
Length of output: 346
Script:
#!/bin/bash
# Let's check the tools.ts implementation for form_filling
cat helpers/tools.ts
# Check types definition
cat helpers/types.ts
# Look for form_filling usage in questions
rg -A 5 "form_filling" questions/simple.ts
Length of output: 14333
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Actionable comments posted: 0
🧹 Outside diff range and nitpick comments (2)
templates/components/agents/python/form_filling/app/agents/form_filling.py (2)
36-36: Consider using environment variable validation
The TOP_K environment variable is directly cast to int without proper validation. Consider using a try-catch block or a validation library like pydantic.BaseSettings to handle environment variables more safely.
- top_k = int(os.getenv("TOP_K", 10))
+ try:
+ top_k = int(os.getenv("TOP_K", 10))
+ except ValueError:
+ raise ValueError("TOP_K environment variable must be a valid integer")263-263: Add type definition for the progress message
The TODO comment indicates missing type definition for the progress message. Consider creating a Pydantic model to define the structure.
from pydantic import BaseModel
class ProgressMessage(BaseModel):
progress_id: str
total_steps: int
current_step: int
step_msg: str📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
📒 Files selected for processing (2)
- templates/components/agents/python/form_filling/app/agents/form_filling.py (1 hunks)
- templates/components/agents/python/form_filling/app/engine/engine.py (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- templates/components/agents/python/form_filling/app/engine/engine.py
🧰 Additional context used
📓 Path-based instructions (1)
templates/components/agents/python/form_filling/app/agents/form_filling.py (1)
Pattern templates/**: For files under the templates folder, do not report 'Missing Dependencies Detected' errors.
🔇 Additional comments (4)
templates/components/agents/python/form_filling/app/agents/form_filling.py (4)
57-93: LGTM! Well-structured event classes
The event classes are well-defined with clear purposes and proper type hints. The AgentRunEvent.to_response() method provides a clean serialization format.
95-136: LGTM! Well-documented and properly initialized workflow
The class initialization is thorough with proper validation and clear documentation. The memory initialization with chat history is handled correctly.
324-390: LGTM! Robust implementation of tool handling
The tool call generator and helper methods are well-implemented with proper error handling, memory management, and async streaming support.
1-390: Verify memory management in long-running workflows
The workflow maintains chat history in memory. For long-running workflows or large datasets, this could potentially lead to memory issues.
✅ Verification successful
Based on the search results, I can now provide a final response:
Memory management implementation is safe and follows best practices
The chat history implementation in FormFillingWorkflow uses ChatMemoryBuffer from llama_index, which is designed for this purpose and handles memory management internally. The implementation:
- Properly initializes memory buffer with optional history:
ChatMemoryBuffer.from_defaults(llm=self.llm, chat_history=self.chat_history) - Maintains clean message lifecycle with explicit put/get operations
- Cleans up automatically when workflow completes as the buffer is instance-scoped
- Has no unbounded accumulation of messages
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash
# Search for memory management patterns and large data handling
rg -n "memory" --type py
rg -n "chat_history" --type py
Length of output: 16855
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Actionable comments posted: 1
🧹 Outside diff range and nitpick comments (9)
templates/components/agents/python/form_filling/README-template.md (3)
9-11: Enhance setup instructions for better reproducibility.
Consider adding:
- Python version requirements
- Version pinning for poetry installation
- Instructions for creating and populating the data directory
Apply this diff to improve the setup section:
```shell
+# Requires Python 3.9+
+curl -sSL https://install.python-poetry.org | python3 - --version 1.4.2
poetry install+Create a data directory and add your documents:
+shell +mkdir -p data +# Add your documents to the data directory +
---
`22-29`: **Enhance API documentation with response example.**
Add a sample response to help users understand the expected output format.
Apply this diff to improve the API documentation:
```diff
The example provides one streaming API endpoint `/api/chat`.
You can test the endpoint with the following curl request:
-```
+```bash
curl --location 'localhost:8000/api/chat' \
--header 'Content-Type: application/json' \
--data '{ "messages": [{ "role": "user", "content": "What can you do?" }] }'
+Example response:
+```json
+{
- "messages": [
- {
-
"role": "assistant", -
"content": "I can help you fill out financial CSV templates using information from company reports..." - }
- ]
+}
+```
<details>
<summary>🧰 Tools</summary>
<details>
<summary>🪛 Markdownlint</summary>
25-25: null
Fenced code blocks should have a language specified
(MD040, fenced-code-language)
</details>
</details>
---
`41-46`: **Add practical examples to the form-filling use case.**
The use case section would benefit from:
1. Example queries for filling the CSV template
2. Sample input/output scenarios
3. A troubleshooting section for common issues
Apply this diff to enhance the use case documentation:
```diff
## Use Case: Filling Financial CSV Template
The project already includes the Apple and Tesla financial reports in the [data](./data) directory and a CSV template [sec_10k_template.csv](./sec_10k_template.csv).
You can upload the files to the app and ask it to fill the missing cells in the CSV file.
+
+### Example Queries
+
+Here are some example queries you can try:
+```
+- "Fill in the missing revenue data for Apple in the CSV template"
+- "Complete the profit margins section using Tesla's financial report"
+```
+
+### Troubleshooting
+
+Common issues and solutions:
+- If the CSV template isn't recognized, ensure it follows the expected format
+- For large financial reports, you may need to adjust the chunk size in the configuration
templates/types/streaming/fastapi/app/services/file.py (1)
80-81: Consider enhancing error handling for unsupported file types.
The current implementation could benefit from explicit error handling for unsupported file types in the else branch. This would provide clearer feedback when processing fails due to unsupported formats.
Consider adding explicit validation:
# Don't index csv files (they are handled by tools)
if extension == "csv":
return document_file
+ elif extension not in _default_file_loaders_map():
+ raise ValueError(f"File type '.{extension}' is not supported for indexing")
else:
# Insert the file into the index and update document ids to the file metadatatemplates/components/agents/python/form_filling/app/agents/form_filling.py (5)
43-44: Enhance error message specificity
The error message doesn't indicate which specific tool is missing. This makes debugging more difficult.
Consider this improvement:
- if extractor_tool is None or filling_tool is None:
- raise ValueError("Extractor or filling tool is not found!")
+ missing_tools = []
+ if extractor_tool is None:
+ missing_tools.append("extractor")
+ if filling_tool is None:
+ missing_tools.append("filling")
+ if missing_tools:
+ raise ValueError(f"Required tools not found: {', '.join(missing_tools)}")35-37: Add type validation for top_k parameter
The top_k value from environment variable should be validated to ensure it's a positive integer.
Consider adding validation:
- top_k = int(os.getenv("TOP_K", 10))
+ try:
+ top_k = int(os.getenv("TOP_K", 10))
+ if top_k <= 0:
+ raise ValueError("TOP_K must be positive")
+ except ValueError as e:
+ raise ValueError(f"Invalid TOP_K value: {e}")83-91: Add return type hint to to_response method
The to_response method should have a return type hint for better type safety.
Add type hint:
- def to_response(self) -> dict:
+ def to_response(self) -> dict[str, str | dict[str, str]]:119-119: Add timeout validation
The timeout parameter should be validated to ensure it's a positive integer.
Add validation:
- timeout: int = 360,
+ timeout: int = 360,
+ if timeout <= 0:
+ raise ValueError("Timeout must be positive")272-273: Add type definition for progress message
The TODO comment indicates missing typing for the progress message structure.
Define a type for the progress message:
from typing import TypedDict
class ProgressMessage(TypedDict):
progress_id: str
total_steps: int
current_step: int
step_msg: str📜 Review details
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- templates/components/agents/python/form_filling/app/agents/form_filling.py (1 hunks)
- templates/types/streaming/fastapi/app/services/file.py (2 hunks)
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🔇 Additional comments (4)
templates/types/streaming/fastapi/app/services/file.py (2)
9-9: LGTM: Import cleanup is correct.
The removal of unused Dict import aligns with the removal of _get_available_tools() method.
80-81: LGTM: CSV handling simplification is well-implemented.
The changes:
- Align with the agreed approach to never index CSV files
- Provide clear documentation of the behavior
- Support the new form filling use case appropriately
templates/components/agents/python/form_filling/app/agents/form_filling.py (2)
266-292: Previous review comment is still valid
The suggestion to optimize answer retrieval using concurrent processing is still applicable.
313-318: Previous review comment is still valid
The suggestion to make _call_tool asynchronous is still applicable.
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🧹 Outside diff range and nitpick comments (1)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (1)
Line range hint 128-158: Add bounds checking for texts array access
When accessing texts[texts.length - 1] for the progress message, ensure the array is not empty to avoid undefined access.
{progress && (
<ProgressContent
progress={progress}
isFinished={isFinished}
- msg={texts[texts.length - 1]}
+ msg={texts.length > 0 ? texts[texts.length - 1] : undefined}
/>
)}📜 Review details
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- templates/types/streaming/nextjs/app/components/ui/chat/index.ts (1 hunks)
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templates/components/agents/python/form_filling/app/agents/form_filling.py (1)
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🔇 Additional comments (6)
templates/types/streaming/nextjs/app/components/ui/chat/index.ts (2)
59-63: LGTM: ProgressData type is well-defined
The new ProgressData type is clean, well-structured, and follows TypeScript conventions.
64-69:
Update field names to match agreed changes
The current implementation still uses agent and text fields, but according to previous discussions and the AI summary, these should be renamed to name and msg respectively.
Apply this change to align with the agreed structure:
export type AgentEventData = {
- agent: string;
- text: string;
+ name: string;
+ msg: string;
type: "text" | "progress";
data?: ProgressData;
};Let's verify the impact of these changes:
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (2)
12-13: LGTM: Clean type and import additions
The new imports and type changes are well-structured and necessary for the progress tracking feature.
Also applies to: 28-28
196-206: LGTM: Progress data handling in event merging
The progress data handling in the mergeAdjacentEvents function is implemented correctly, maintaining the event merging logic while incorporating the new progress tracking feature.
templates/components/agents/python/form_filling/app/agents/form_filling.py (2)
55-93: LGTM! Well-structured event classes
The event classes are well-defined with clear purposes and proper type hints. The AgentRunEvent.to_response() method provides a clean serialization format.
331-397: LGTM! Robust helper methods implementation
The helper methods are well-implemented with proper error handling and async support. The tool call generator effectively manages the streaming response and tool calls.
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🧹 Outside diff range and nitpick comments (1)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (1)
126-134: Consider simplifying steps extraction logicTo enhance readability, consider refactoring the extraction of
stepsandprogressStepto be more straightforward.You might restructure the code as follows:
function AgentEventContent({ event, isLast, isFinished, }: { event: MergedEvent; isLast: boolean; isFinished: boolean; }) { const { agent, steps: allSteps } = event; const AgentIcon = event.icon; - // We only show progress at the last step - const lastStep = - allSteps.length > 0 ? allSteps[allSteps.length - 1] : undefined; - const progressStep = - lastStep && "progress" in lastStep ? (lastStep as StepProgress) : undefined; - const steps = allSteps.filter((step) => !("progress" in step)); + const steps = allSteps.filter((step): step is StepData => !("progress" in step)); + const progressStep = allSteps.find((step): step is StepProgress => "progress" in step); return ( // ... rest of the component ); }This refactoring uses TypeScript type guards to more clearly separate
StepDataandStepProgress, improving code clarity.
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🔇 Additional comments (5)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (5)
12-13: Imports added correctly
The Progress component and ProgressData types are imported properly for use within the component.
24-31: Type definitions are appropriate
The StepData and StepProgress types are well-defined, effectively structuring the steps and progress data.
35-35: Updated MergedEvent steps property
The steps property in MergedEvent is correctly updated to include both StepData and StepProgress types.
64-89: TextContent component implemented correctly
The TextContent component correctly handles the rendering of step texts, including truncation of long texts and providing an option to 'Show more' via a dialog.
151-158: Component rendering logic is appropriate
The conditional rendering of TextContent and ProgressContent based on the presence of steps and progressStep is correct.
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🔇 Additional comments (3)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (3)
64-89: LGTM! TextContent implementation is clean and handles text truncation well
The component properly handles text length constraints and provides a good user experience for viewing full content.
91-108: LGTM! ProgressContent provides clear visual feedback
The component effectively communicates progress through both visual and textual means.
24-30: 🛠️ Refactor suggestion
Add runtime type validation for StepProgress
While the type definitions are well-structured, consider adding runtime validation for the progress data to ensure type safety at runtime.
Add a type guard:
function isStepProgress(step: StepData | StepProgress): step is StepProgress {
return (
'progress' in step &&
typeof step.progress === 'object' &&
step.progress !== null &&
typeof step.progress.current === 'number' &&
typeof step.progress.total === 'number'
);
}
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🧹 Outside diff range and nitpick comments (1)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (1)
24-36: LGTM! Consider using discriminated union for better type safety.The type definitions are well-structured. However, you could improve type safety by using a discriminated union with a type field.
type StepText = { + type: 'text'; text: string; }; type StepProgress = { + type: 'progress'; text: string; progress: ProgressData; };This would make type checking more explicit and safer than using
'progress' in step.
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🔇 Additional comments (2)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (2)
85-102: LGTM! Progress calculation handles edge cases correctly.
The progress calculation correctly handles division by zero and maintains proper bounds.
115-124: Consider future support for parallel steps.
The TODO comment indicates that progress handling needs to be updated for parallel steps support. This architectural limitation should be tracked.
Let's verify if there are any existing issues or discussions about parallel steps support:
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templates/types/streaming/nextjs/app/components/ui/file-uploader.tsx (1)
126-128: Ensure accessibility for screen readersWhen displaying the
remainingFilescount within the loader, consider addingaria-liveattributes to ensure that screen readers announce the updated number of remaining files to users with visual impairments.Apply this diff to enhance accessibility:
{remainingFiles > 0 && ( <span className="text-xs absolute inset-0 flex items-center justify-center" + aria-live="polite" > {remainingFiles} </span> )}
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templates/types/streaming/nextjs/app/components/ui/file-uploader.tsx
[error] 90-90: Unnecessary continue statement
Unsafe fix: Delete the unnecessary continue statement
(lint/correctness/noUnnecessaryContinue)
🔇 Additional comments (2)
templates/types/streaming/nextjs/app/components/ui/chat/chat-input.tsx (2)
132-137: LGTM! Improved form validation logic.
The updated disabled state properly considers both text input and file uploads, preventing empty form submissions while allowing valid file-only submissions.
125-125: Verify multiple file upload behavior.
There appears to be an inconsistency between the FileUploader configuration and the upload handler. While the FileUploader is now configured to accept multiple files, the handleUploadFile function still contains a check that prevents multiple image uploads with an alert message "You can only upload one image at a time."
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templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (2)
65-91: Add ARIA label for better accessibility.The "Show more" link should have an ARIA label to improve accessibility for screen readers.
- <span className="font-semibold underline cursor-pointer ml-2"> + <span + className="font-semibold underline cursor-pointer ml-2" + aria-label={`Show full message from agent ${agent}`} + > Show more </span>
128-129: Track TODO comment about parallel steps support.The comment indicates a known limitation in handling parallel steps that needs to be addressed in the future.
Would you like me to create a GitHub issue to track this TODO for implementing parallel steps support?
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🔇 Additional comments (3)
templates/types/streaming/nextjs/app/components/ui/chat/chat-message/chat-agent-events.tsx (3)
12-13: LGTM! Well-structured type definitions.
The new types are well-defined and properly integrated with the existing codebase. The separation between StepText and StepProgress types provides good type safety and clarity.
Also applies to: 24-36
93-110: LGTM! Clean progress tracking implementation.
The progress calculation and display logic is well-implemented with proper handling of edge cases.
201-209: LGTM! Event merging logic is sound.
The event merging logic correctly handles both text and progress events while maintaining the event sequence.
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templates/types/streaming/nextjs/app/components/ui/file-uploader.tsx (1)
55-61: Consider cleanup when no files are selectedWhen no files are selected, the uploading state should be reset to prevent the UI from being stuck in a loading state.
Apply this diff to improve error handling:
const files = Array.from(e.target.files || []); - if (!files.length) return; + if (!files.length) { + setUploading(false); + return; + }
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templates/types/streaming/nextjs/app/components/ui/file-uploader.tsx (3)
15-15: LGTM: Well-typed interface extension
The optional multiple property is properly typed and maintains backward compatibility.
30-30: LGTM: Proper state management for upload tracking
The remainingFiles state is well-typed and appropriately initialized for tracking upload progress.
109-109: LGTM: Well-implemented UI enhancements
The UI changes provide clear visual feedback during the upload process with:
- Proper multiple file input configuration
- Clear loading state indication
- Remaining files counter
Also applies to: 115-115, 120-127
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Summary by CodeRabbit
New Features
ChatAgentEventscomponent to manage and display progress alongside text messages.ChatInputcomponent to refine submission button logic based on user input and file selection.Bug Fixes
Documentation
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