Feature: Update multi-agent template to use financial report use case #386
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🦋 Changeset detectedLatest commit: 297b95a 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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templates/components/multiagent/python/app/financial_report/choreography.py
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templates/components/agents/python/financial_report/orchestrator.py
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WalkthroughThe pull request introduces enhancements to the application's functionality by adding an Changes
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Actionable comments posted: 19
🧹 Outside diff range and nitpick comments (28)
templates/components/agents/python/financial_report/app/engine/engine.py (1)
8-12: Add docstring and error handling.The function would benefit from:
- A docstring explaining its purpose, parameters, and return value
- Error handling for potential exceptions from create_workflow
Consider updating the implementation like this:
def get_chat_engine( chat_history: Optional[List[ChatMessage]] = None, **kwargs ) -> Workflow: + """Create a chat engine workflow for the financial report use case. + + Args: + chat_history (Optional[List[ChatMessage]]): Previous chat messages for context + **kwargs: Additional arguments passed to the workflow creation + + Returns: + Workflow: The configured chat engine workflow + + Raises: + ValueError: If workflow creation fails + """ + try: agent_workflow = create_workflow(chat_history, **kwargs) return agent_workflow + except Exception as e: + raise ValueError(f"Failed to create chat engine workflow: {str(e)}") from etemplates/components/agents/python/financial_report/app/agents/reporter.py (1)
1-8: Consider reorganizing imports for better readability.While the imports are correct, they could be better organized into three distinct groups separated by a single blank line:
- Standard library imports (
textwrap,typing)- Third-party imports (
llama_index)- Local application imports (
app)from textwrap import dedent from typing import List, Tuple -from app.engine.tools import ToolFactory -from app.workflows.single import FunctionCallingAgent from llama_index.core.chat_engine.types import ChatMessage from llama_index.core.tools import BaseTool +from app.engine.tools import ToolFactory +from app.workflows.single import FunctionCallingAgenttemplates/components/agents/python/blog/app/agents/choreography.py (3)
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31-33: TODO: Implement chat_history support in AgentCallingAgentThe comment indicates missing chat history support in AgentCallingAgent. This could affect conversation context and agent interactions.
Would you like me to help implement chat_history support in AgentCallingAgent or create a GitHub issue to track this task?
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13-20: Enhance reviewer agent's description and capabilitiesThe reviewer agent's description could be more comprehensive to match its actual capabilities. Consider expanding it to explicitly mention:
- Technical accuracy review
- Content structure analysis
- SEO optimization checks
reviewer = FunctionCallingAgent( name="reviewer", - description="expert in reviewing blog posts, needs a written post to review", + description="expert in reviewing blog posts for technical accuracy, content structure, SEO optimization, and writing quality. Requires a written post to review", system_prompt="You are an expert in reviewing blog posts. You are given a task to review a blog post. Review the post for logical inconsistencies, ask critical questions, and provide suggestions for improvement. Furthermore, proofread the post for grammar and spelling errors. If the post is good, you can say 'The post is good.'", chat_history=chat_history, )
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21-33: Consider making agent interaction limits configurableThe system prompt hardcodes a maximum of two consultations with reviewer and researcher. Consider making this limit configurable through parameters for better flexibility.
Suggested approach:
- Add a parameter for max_consultations
- Inject this parameter into the system prompt
- Consider implementing this as a proper constraint in AgentCallingAgent rather than relying on prompt instructions
templates/components/agents/python/blog/app/agents/orchestrator.py (1)
4-7: LGTM! Import restructuring improves code organization.The changes reflect a better separation of concerns:
- Agent-specific implementations are now properly located in the
app.agentspackage- Workflow-related code is appropriately moved to the
app.workflowspackageThis reorganization enhances maintainability by:
- Providing a clearer module structure
- Making it easier to locate related functionality
- Reducing coupling between examples and core functionality
templates/components/agents/python/financial_report/app/agents/analyst.py (2)
25-25: Optimize dictionary key check.Use
inoperator directly with the dictionary instead of calling.keys().-if "interpreter" in configured_tools.keys(): +if "interpreter" in configured_tools:🧰 Tools
🪛 Ruff
25-25: Use
key in dictinstead ofkey in dict.keys()Remove
.keys()(SIM118)
10-10: Add docstrings to improve code documentation.Consider adding docstrings to both functions to document:
- Purpose and responsibilities
- Parameter descriptions
- Return value descriptions
- Usage examples
Example for
create_analyst:def create_analyst(chat_history: List[ChatMessage]): """Create a financial analyst agent. Args: chat_history (List[ChatMessage]): Previous chat messages for context Returns: FunctionCallingAgent: Configured analyst agent ready for financial analysis """Also applies to: 38-38
templates/components/multiagent/python/app/workflows/multi.py (2)
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48-61: Clean implementation with proper agent registration.The class correctly handles agent initialization and tool creation. Consider using
list[FunctionCallingAgent]instead ofList[FunctionCallingAgent]as it's the preferred syntax in modern Python (3.9+).- agents: List[FunctionCallingAgent] | None = None, + agents: list[FunctionCallingAgent] | None = None,
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64-82: Clean orchestrator implementation following consistent patterns.The class correctly implements the orchestrator functionality. Consider the same type annotation improvement here as well.
- agents: List[FunctionCallingAgent] | None = None, + agents: list[FunctionCallingAgent] | None = None,e2e/shared/multiagent_template.spec.ts (1)
25-28: Consider adding more specific skip conditions.The skip message indicates two conditions (Linux-only and requires files), but the condition could be more explicit by separating these checks.
- test.skip( - process.platform !== "linux" || process.env.DATASOURCE === "--no-files", - "The multiagent template currently only works with files. We also only run on Linux to speed up tests.", - ); + test.skip(process.platform !== "linux", "Multi-agent tests only run on Linux to speed up testing."); + test.skip(process.env.DATASOURCE === "--no-files", "Multi-agent template requires file data source.");templates/components/agents/python/financial_report/app/agents/researcher.py (3)
59-62: Clarify chunk retriever description.The description mentions "need entire documents" which seems contradictory for a chunk retriever. Consider revising the description to better reflect its chunk-based nature.
- Use for research questions that want to look up specific facts from the knowledge corpus, - and need entire documents. + Use for research questions that want to look up specific facts from the knowledge corpus, + focusing on relevant segments rather than entire documents.
83-87: Enhance function documentation.The docstring could be more comprehensive by including:
- Parameter descriptions
- Return type
- Example usage
- """ - Researcher is an agent that take responsibility for using tools to complete a given task. - """ + """ + Create a researcher agent that retrieves information from the corpus. + + Args: + chat_history (List[ChatMessage]): Previous conversation history + **kwargs: Additional parameters passed to _create_query_engine_tools + + Returns: + FunctionCallingAgent: Configured researcher agent + + Example: + >>> agent = create_researcher(chat_history=[]) + """
94-100: Enhance system prompt with error handling guidelines.Consider adding instructions about how to handle potential errors or limitations.
""" You are a researcher agent. You are responsible for retrieving information from the corpus. ## Instructions + Don't synthesize the information, just return the whole retrieved information. + Don't need to retrieve the information that is already provided in the chat history and response with: "There is no new information, please reuse the information from the conversation." + + If you encounter any errors while retrieving information, clearly state the error and suggest alternative approaches. + + If the retrieved information seems incomplete or irrelevant, acknowledge this limitation in your response. """create-app.ts (1)
44-44: Add type annotation and documentation for theagentsparameter.For better type safety and maintainability, consider:
- Adding a type annotation for the
agentsparameter- Including JSDoc documentation explaining the parameter's purpose and expected format
Would you like me to help generate the type definition and documentation?
e2e/utils.ts (1)
124-126: Consider adding debug logging for agent configuration.To improve debuggability, consider logging the agent configuration when it's being applied:
if (templateType === "multiagent" && agents) { + console.log(`Configuring multiagent template with agents: ${agents}`); commandArgs.push("--agents", agents); }questions/simple.ts (1)
49-51: Document architectural decision for Python-only support.While the TODO comment is helpful, please document why the financial report use case currently only supports Python. This will help future contributors understand the limitations and requirements.
Consider adding an ADR (Architecture Decision Record) or updating the relevant documentation to explain:
- Why Python is the only supported language for this use case
- What would be required to add TypeScript support in the future
templates/components/agents/python/blog/app/agents/workflow.py (4)
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19-86: Consider making the workflow timeout configurable and standardizing agent initialization.A few suggestions for improvement:
- The hardcoded timeout of 360 seconds might not be suitable for all use cases
- The publisher agent initialization is inconsistent with the researcher agent as it doesn't receive the same kwargs
- The system prompts mention specific formats (PDF) which might limit reusability
Consider applying these improvements:
def create_workflow(chat_history: Optional[List[ChatMessage]] = None, **kwargs): researcher = create_researcher( chat_history=chat_history, **kwargs, ) publisher = create_publisher( chat_history=chat_history, + **kwargs, )And add a timeout parameter:
-def create_workflow(chat_history: Optional[List[ChatMessage]] = None, **kwargs): +def create_workflow( + chat_history: Optional[List[ChatMessage]] = None, + timeout: int = 360, + **kwargs +): # ... agent creation code ... workflow = BlogPostWorkflow( - timeout=360, + timeout=timeout, chat_history=chat_history )
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183-191: Consider making MAX_ATTEMPTS configurable and improving the retry logic.The hardcoded MAX_ATTEMPTS value could be made configurable to support different use cases.
Consider making it a class parameter:
class BlogPostWorkflow(Workflow): def __init__( self, timeout: int = 360, + max_attempts: int = 2, chat_history: Optional[List[ChatMessage]] = None ): super().__init__(timeout=timeout) self.chat_history = chat_history or [] + self.max_attempts = max_attempts @step() async def write(self, ctx: Context, ev: WriteEvent, writer: FunctionCallingAgent) -> ReviewEvent | StopEvent: - MAX_ATTEMPTS = 2 ctx.data["attempts"] = ctx.data.get("attempts", 0) + 1 - too_many_attempts = ctx.data["attempts"] > MAX_ATTEMPTS + too_many_attempts = ctx.data["attempts"] > self.max_attempts
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287-301: Enhance error handling in the publish step.The current error handling could be more informative by:
- Logging the specific error type
- Providing more context about the failure
Consider enhancing the error handling:
@step() async def publish( self, ctx: Context, ev: PublishEvent, publisher: FunctionCallingAgent, ) -> StopEvent: try: result: AgentRunResult = await self.run_agent(ctx, publisher, ev.input) return StopEvent(result=result) except Exception as e: + error_context = { + 'error_type': type(e).__name__, + 'error_details': str(e), + 'input': ev.input + } ctx.write_event_to_stream( AgentRunEvent( name=publisher.name, - msg=f"Error publishing: {e}", + msg=f"Publishing failed: {error_context}", ) ) return StopEvent(result=None)
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134-162: Consider extracting the decision-making prompt template.The decision-making prompt template could be moved to a separate constants file or template file for better maintainability.
Consider creating a new file
templates/components/agents/python/blog/app/prompts.py:from textwrap import dedent from llama_index.core.prompts import PromptTemplate WORKFLOW_DECISION_PROMPT = PromptTemplate( dedent(""" You are an expert in decision-making, helping people write and publish blog posts. If the user is asking for a file or to publish content, respond with 'publish'. If the user requests to write or update a blog post, respond with 'not_publish'. Here is the chat history: {chat_history} The current user request is: {input} Given the chat history and the new user request, decide whether to publish based on existing information. Decision (respond with either 'not_publish' or 'publish'): """) )Then update the workflow:
+from app.prompts import WORKFLOW_DECISION_PROMPT async def _decide_workflow( self, input: str, chat_history: List[ChatMessage] ) -> str: - prompt_template = PromptTemplate(...) + prompt_template = WORKFLOW_DECISION_PROMPTtemplates/components/multiagent/python/app/workflows/planner.py (2)
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156-157: Consider addressing the streaming limitation.There's a TODO comment indicating that streaming only works without plan refining. This limitation might affect the financial report use case if streaming is required along with plan refinement.
Would you like me to help implement a solution that supports both streaming and plan refining?
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155-170: Consider enhancing error handling in execute_sub_task.The
execute_sub_taskmethod could benefit from more robust error handling, especially around the executor run and event streaming. This would improve reliability when processing financial reports.Consider wrapping the executor run in a try-catch block:
@step() async def execute_sub_task( self, ctx: Context, ev: SubTaskEvent ) -> SubTaskResultEvent: if self._verbose: print(f"=== Executing sub task: {ev.sub_task.name} ===") is_last_tasks = self.get_remaining_subtasks(ctx) == 1 streaming = is_last_tasks and ctx.data["streaming"] and not self.refine_plan - handler = self.executor.run( - input=ev.sub_task.input, - streaming=streaming, - ) + try: + handler = self.executor.run( + input=ev.sub_task.input, + streaming=streaming, + ) + except Exception as e: + if self._verbose: + print(f"Error executing sub task: {str(e)}") + raisetemplates/components/agents/python/financial_report/app/agents/workflow.py (5)
85-103: Address the TODO: Refactor prompt generation for maintainabilityThere's a TODO comment indicating the need to refactor the prompt generation. Refactoring this code using structured prompt templates or separate functions can enhance readability and maintainability.
Would you like assistance in refactoring the prompt generation code?
21-39: Add return type hint to 'create_workflow' functionThe
create_workflowfunction lacks a return type hint, which can improve code readability and maintainability.Apply this diff:
def create_workflow(chat_history: Optional[List[ChatMessage]] = None, **kwargs) + -> FinancialReportWorkflow:
62-80: Add docstring to 'start' method for clarityAdding a docstring to the
startmethod will help others understand its purpose and usage.Consider adding a docstring like:
@step() async def start(self, ctx: Context, ev: StartEvent) -> ResearchEvent | ReportEvent: """ Decide whether to start the workflow with a research or report event based on user input and chat history. Args: ctx (Context): The workflow context. ev (StartEvent): The event that starts the workflow. Returns: ResearchEvent or ReportEvent: The next event in the workflow. """
163-169: Correct the return type annotation of 'run_agent' methodThe
run_agentmethod is annotated to returnAgentRunResult | AsyncGenerator, but it always returns anAgentRunResult. The method processes an async generator internally but does not return it.Apply this diff:
async def run_agent( self, ctx: Context, agent: FunctionCallingAgent, input: str, streaming: bool = False, - ) -> AgentRunResult | AsyncGenerator: + ) -> AgentRunResult:
47-47: Remove unused field 'is_good' from 'AnalyzeEvent'The
is_goodfield inAnalyzeEventis declared but not used anywhere in the code. Removing it can simplify the class definition.Apply this diff:
class AnalyzeEvent(Event): input: str - is_good: bool = False
📜 Review details
Configuration used: .coderabbit.yaml
Review profile: CHILL
📒 Files selected for processing (25)
- create-app.ts (2 hunks)
- e2e/shared/multiagent_template.spec.ts (1 hunks)
- e2e/utils.ts (3 hunks)
- helpers/datasources.ts (1 hunks)
- helpers/index.ts (1 hunks)
- helpers/python.ts (3 hunks)
- helpers/types.ts (2 hunks)
- index.ts (1 hunks)
- questions/simple.ts (6 hunks)
- templates/components/agents/python/blog/README-template.md (1 hunks)
- templates/components/agents/python/blog/app/agents/choreography.py (1 hunks)
- templates/components/agents/python/blog/app/agents/orchestrator.py (1 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/blog/app/agents/workflow.py (1 hunks)
- templates/components/agents/python/blog/app/engine/engine.py (1 hunks)
- templates/components/agents/python/financial_report/README-template.md (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/financial_report/app/agents/researcher.py (1 hunks)
- templates/components/agents/python/financial_report/app/agents/workflow.py (1 hunks)
- templates/components/agents/python/financial_report/app/engine/engine.py (1 hunks)
- templates/components/multiagent/python/app/api/routers/vercel_response.py (1 hunks)
- templates/components/multiagent/python/app/workflows/multi.py (1 hunks)
- templates/components/multiagent/python/app/workflows/planner.py (1 hunks)
✅ Files skipped from review due to trivial changes (1)
- templates/components/agents/python/blog/README-template.md
🧰 Additional context used
📓 Path-based instructions (15)
templates/components/agents/python/blog/app/agents/choreography.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/blog/app/agents/orchestrator.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/blog/app/agents/publisher.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/blog/app/agents/researcher.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/blog/app/agents/workflow.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/blog/app/engine/engine.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/financial_report/README-template.md (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/financial_report/app/agents/analyst.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/financial_report/app/agents/reporter.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/financial_report/app/agents/researcher.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/financial_report/app/agents/workflow.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/agents/python/financial_report/app/engine/engine.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/app/api/routers/vercel_response.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/app/workflows/multi.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/app/workflows/planner.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
🪛 Markdownlint
templates/components/agents/python/financial_report/README-template.md
30-30: null
Fenced code blocks should have a language specified(MD040, fenced-code-language)
42-42: null
Fenced code blocks should have a language specified(MD040, fenced-code-language)
🪛 Ruff
templates/components/agents/python/financial_report/app/agents/analyst.py
25-25: Use
key in dictinstead ofkey in dict.keys()Remove
.keys()(SIM118)
🔇 Additional comments (33)
templates/components/agents/python/financial_report/app/engine/engine.py (2)
1-6: LGTM! Well-organized imports.The imports are properly organized following Python's style guide, with standard library imports first, followed by internal imports and third-party packages.
11-11: Verify create_workflow parameter handling.Let's ensure that the
create_workflowfunction properly handles bothchat_historyand all possiblekwargsparameters.✅ Verification successful
Let me gather more information about the parameter handling by checking the researcher creation and usage.
I have enough information to generate the final response now.
Parameter handling in create_workflow is properly implemented
The verification shows that:
create_workflowcorrectly acceptschat_history(typed as Optional[List[ChatMessage]]) and**kwargs- These parameters are properly passed down to
create_researcher- The implementation is consistent across both financial report and blog templates
- The parameter passing pattern matches the usage in engine.py
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Search for create_workflow implementation to verify parameter handling ast-grep --pattern 'def create_workflow($params) { $$$ }' # Search for any calls to create_workflow to understand expected parameters rg -A 2 'create_workflow\('Length of output: 1349
Script:
#!/bin/bash # Check create_researcher implementation and its parameter handling ast-grep --pattern 'def create_researcher($params) { $$$ }' # Look for researcher usage patterns rg -A 3 'create_researcher\('Length of output: 2690
templates/components/agents/python/blog/app/engine/engine.py (2)
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14-31: LGTM! Factory pattern implementation remains unchanged.The implementation maintains clean separation of concerns with proper error handling and logging.
5-7: Verify the module reorganization fromapp.examplestoapp.agents.The import changes align with the module restructuring. Let's verify that the imported functions exist in their new locations.
✅ Verification successful
Let me try a different search strategy since this is a template file. Let's search in the templates directory and also check for any example files that might still contain these functions.
Import changes are correctly implemented and verified
The verification results confirm that:
- All three modules (
choreography.py,orchestrator.py,workflow.py) exist in the new location undertemplates/components/agents/python/blog/app/agents/- All required functions (
create_choreography,create_orchestrator,create_workflow) are properly defined in their respective new module files- The import statements in
engine.pycorrectly reference these functions from their new locations underapp.agents.*🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that the functions exist in their new locations under app.agents.* # Test 1: Check if the new module files exist echo "Checking for new module files..." fd -t f "^(choreography|orchestrator|workflow).py$" -p "app/agents" # Test 2: Verify the specific functions exist in their new locations echo "Checking for function definitions in new locations..." ast-grep --pattern 'def create_choreography' ast-grep --pattern 'def create_orchestrator' ast-grep --pattern 'def create_workflow'Length of output: 494
Script:
#!/bin/bash # Search in templates directory for the module files and functions echo "Checking template files..." fd -t f "^(choreography|orchestrator|workflow).py$" templates echo -e "\nChecking for old examples directory structure..." fd -t f "^(choreography|orchestrator|workflow).py$" -p "examples" echo -e "\nSearching for create_* function definitions..." rg "def create_(choreography|orchestrator|workflow)" -g "*.py" --no-heading echo -e "\nChecking import statements to understand the structure..." rg "^from app\.(agents|examples)\.(choreography|orchestrator|workflow)" -g "*.py" --no-headingLength of output: 2156
templates/components/agents/python/blog/app/agents/publisher.py (2)
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1-40: LGTM! The rest of the file remains unchanged and functional.The file's core functionality, including
get_publisher_tools()andcreate_publisher(), remains intact. The implementation correctly handles tool configuration and agent creation.
5-5: Verify the new import path for FunctionCallingAgentThe import path change from
app.agents.singletoapp.workflows.singleappears to be part of a broader codebase restructuring. Let's verify the new import path exists and maintains compatibility.templates/components/agents/python/blog/app/agents/choreography.py (1)
4-7: LGTM! Improved module organizationThe reorganization of imports provides better separation of concerns by:
- Moving agent implementations to dedicated modules
- Separating workflow-related classes into single/multi modules
This improves code maintainability and makes the dependencies clearer.templates/components/agents/python/blog/app/agents/orchestrator.py (1)
4-7: Verify consistent import updates across the codebase.Let's ensure the import restructuring is consistently applied across all related files.
✅ Verification successful
Based on the results from the shell scripts, I can now generate the final response as we have comprehensive information about the import patterns across the codebase.
Import structure changes are consistently implemented
The verification shows that:
- No old import paths (
app.examplesorapp.agents.multi/single) are present in the codebase- New import paths (
app.agents.publisher/researcherandapp.workflows.multi/single) are consistently used across all relevant files- The import structure follows a clear pattern across both blog and financial report components
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that imports are consistently updated across the codebase # Test 1: Check for any remaining imports from old paths echo "Checking for any remaining old import paths..." rg "from app.examples.(publisher|researcher) import" || echo "No old import paths found ✓" rg "from app.agents.(multi|single) import" || echo "No old import paths found ✓" # Test 2: Verify new import paths are used consistently echo -e "\nVerifying new import paths usage..." rg "from app.agents.(publisher|researcher) import" rg "from app.workflows.(multi|single) import"Length of output: 3139
templates/components/agents/python/financial_report/app/agents/analyst.py (2)
1-8: LGTM! Clean and well-organized imports.The imports are properly organized and include all necessary dependencies for the agent implementation.
38-47: LGTM! Well-structured agent creation.The function is concise, well-typed, and properly utilizes the helper function for parameter initialization.
helpers/types.ts (1)
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51-102: LGTM! Clean type definitions with good separation of concerns.The changes look good:
- The new
TemplateAgentstype is well-definedFileSourceConfigproperly handles both local files and URLs- The optional
agentsparameter inInstallTemplateArgsfollows the suggested patterntemplates/components/multiagent/python/app/workflows/multi.py (2)
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13-45: Well-structured implementation with proper async handling and documentation.The
AgentCallToolclass is well-implemented with:
- Clear type hints
- Descriptive tool metadata
- Proper async event bubbling
- Clean error handling
3-4: Verify the consistency of import path changes across the codebase.The imports have been moved from
app.agents.*toapp.workflows.*, which appears to be part of a broader restructuring.Let's verify the consistency of these changes:
✅ Verification successful
The results show that there are no remaining imports from the old
app.agents.*paths, and all imports are consistently using the newapp.workflows.*paths across the codebase. Let me verify one more aspect to ensure we have a complete picture:This will help us confirm if the old module files have been completely moved to the new location or if they exist in parallel.
Let me try a different approach to verify the module structure:
This should help us understand the actual directory structure and location of these modules.
Import changes are correctly implemented and consistent
The verification shows that:
- The modules
planner.pyandsingle.pyexist only in the new locationtemplates/components/multiagent/python/app/workflows/- All imports across the codebase consistently use the new
app.workflows.*paths- No old imports from
app.agents.*remain for these modules🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining imports from the old paths to ensure complete migration echo "Checking for any remaining old imports..." rg "from app.agents.(planner|single) import" --type py echo "Verifying new import usage..." rg "from app.workflows.(planner|single) import" --type pyLength of output: 1955
Script:
#!/bin/bash # Check if the old module structure exists alongside the new one echo "Checking for existence of old module structure..." fd "^(planner|single).py$" -p "app/agents/" echo "Checking for existence of new module structure..." fd "^(planner|single).py$" -p "app/workflows/"Length of output: 509
Script:
#!/bin/bash # Search for planner.py and single.py files in the entire repository echo "Searching for planner.py and single.py files..." fd "^(planner|single).py$" # List directories containing 'workflows' or 'agents' echo -e "\nListing relevant directories..." fd -t d "(workflows|agents)$"Length of output: 570
e2e/shared/multiagent_template.spec.ts (3)
23-24: LGTM! Good use of dynamic test suite generation.The for-loop effectively creates separate test suites for each agent type, improving test organization and clarity.
84-87: LGTM! Proper cleanup of processes.The test cleanup is handled correctly using
afterAllhook.
41-53: Verify the impact of the newagentsparameter.The test setup now includes the
agentsparameter inrunCreateLlama. Let's verify this change is properly handled in the related functions.✅ Verification successful
Let me gather more information to verify the handling of the
agentsparameter.The previous results showed multiple files containing agent-related code, but we need to see their actual implementation to verify how the
agentsparameter is handled throughout the codebase. This will help us determine if the parameter is properly integrated into the template generation process.
Based on the provided context, I can now generate the final response as I have sufficient information to verify the handling of the
agentsparameter.The
agentsparameter is properly integrated and handled in the codebaseThe verification shows that:
- In
e2e/utils.ts, theagentsparameter is correctly added to the command arguments when the template type is "multiagent":if (templateType === "multiagent" && agents) { commandArgs.push("--agents", agents); }- The test file
e2e/shared/multiagent_template.spec.tsproperly tests both available agent types: "financial_report" and "blog"- The agent implementation in
templates/components/multiagent/typescript/workflow/agents.tsprovides the necessary agent types (researcher, writer, reviewer, publisher) that support these workflows- The workflow factory in
templates/components/multiagent/typescript/workflow/factory.tscorrectly orchestrates the agent interactions🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the handling of the agents parameter in related files # Check if runCreateLlama and related functions handle the agents parameter rg -A 5 "runCreateLlama|createApp|installTemplate" "e2e/utils.ts" "src/create-app.ts" # Check for any existing agent-specific logic rg -l "financial_report|blog" --type tsLength of output: 608
Script:
#!/bin/bash # Get the full implementation of runCreateLlama to see how agents parameter is handled cat e2e/utils.ts # Check the multiagent template files for agent-related configuration cat templates/components/multiagent/typescript/workflow/agents.ts cat templates/components/multiagent/typescript/workflow/factory.ts # Check the test file to understand the context of agents parameter usage cat e2e/shared/multiagent_template.spec.tsLength of output: 21726
helpers/datasources.ts (1)
14-31: Add documentation explaining the purpose of these example files.Consider adding a JSDoc comment explaining:
- Why these specific SEC filings were chosen
- The intended use case
- Any limitations or considerations when using these files
Also, verify that these URLs are stable and permanent links to avoid future maintenance issues.
✅ Verification successful
Let me check if there's any existing documentation for this constant by searching the file.
Let me check the broader context of the file to understand the data source types and their usage pattern.
Let me check how this constant is used in the codebase to better understand its purpose.
I now have enough context to provide the final response. The constant is used as example data sources for the financial report agent template, and both URLs are verified to be accessible.
Add JSDoc comment to document the example SEC filing data sources
The constant
EXAMPLE_10K_SEC_FILESserves as default data sources for the financial report agent template, but this purpose isn't documented. Add a JSDoc comment explaining:/** * Example 10-K SEC filing data sources used as defaults for the financial report agent template. * Contains two verified, publicly accessible annual reports: * - Amazon's 10-K Q4 2023 filing * - Tesla's 10-K 2023 filing */ export const EXAMPLE_10K_SEC_FILES: TemplateDataSource[] = [Both URLs are currently accessible and return HTTP 200 status codes, so no immediate maintenance is required.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify the SEC filing URLs are accessible # Expected: Both URLs should return HTTP 200 status for url in \ "https://s2.q4cdn.com/470004039/files/doc_earnings/2023/q4/filing/_10-K-Q4-2023-As-Filed.pdf" \ "https://ir.tesla.com/_flysystem/s3/sec/000162828024002390/tsla-20231231-gen.pdf"; do echo "Checking $url" curl -sI "$url" | head -n1 doneLength of output: 1020
Script:
#!/bin/bash # Check for any existing documentation or comments around EXAMPLE_10K_SEC_FILES rg -B 5 "EXAMPLE_10K_SEC_FILES" --context 5Length of output: 1568
Script:
#!/bin/bash # Get the full content of datasources.ts to understand the context cat helpers/datasources.tsLength of output: 3213
Script:
#!/bin/bash # Search for usage of EXAMPLE_10K_SEC_FILES across the codebase rg "EXAMPLE_10K_SEC_FILES" -B 3 -A 3Length of output: 1000
templates/components/agents/python/blog/app/agents/researcher.py (2)
Line range hint
12-93: Implementation aligns well with multi-agent architecture.The researcher agent implementation is well-structured with:
- Clear separation of concerns between query engine creation, tool management, and agent creation
- Comprehensive system prompt that provides clear guidance for the agent's behavior
- Proper error handling for cases when information isn't found
7-7: Verify consistent usage of the new import path across the codebase.The import path change from
app.agents.singletoapp.workflows.singleappears to be part of a broader module reorganization.Let's verify that this change is consistent across the codebase:
✅ Verification successful
Import path change is consistent across the codebase
The verification results show that:
- No instances of the old import path
from app.agents.single import FunctionCallingAgentwere found- The new import path
from app.workflows.single import FunctionCallingAgentis consistently used across all relevant template files🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for any remaining old import paths and verify new import usage # Test 1: Check for any remaining old imports echo "Checking for old import paths..." rg "from app.agents.single import FunctionCallingAgent" # Test 2: Verify new import usage echo "Verifying new import usage..." rg "from app.workflows.single import FunctionCallingAgent"Length of output: 1129
templates/components/agents/python/financial_report/app/agents/researcher.py (2)
1-10: LGTM! Clean and well-organized imports.The imports are properly organized and all are being utilized in the implementation.
87-88: Consider error handling propagation.The
_create_query_engine_toolsfunction can return None, but there's no explicit handling of this case increate_researcher. Consider how tool initialization failures should be handled at the agent level.templates/components/multiagent/python/app/api/routers/vercel_response.py (1)
9-9: LGTM! Verify consistent usage of the new import path.The import path change from
app.agents.singletoapp.workflows.singlealigns with the codebase restructuring.Let's verify that this change is consistent across the codebase:
✅ Verification successful
Let me generate additional scripts to verify the module's existence in the templates directory structure.
The previous results showed that the new import path is being used consistently in multiple files, but we need to verify the actual module exists and contains these classes.
Import path change is correctly implemented and verified
The verification results confirm:
- The new module
single.pyexists at the correct location:templates/components/multiagent/python/app/workflows/single.py- Both
AgentRunEventandAgentRunResultclasses are defined in this module- The new import path is used consistently across multiple files
- No remaining references to the old
app.agents.singlepath were found🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that AgentRunEvent and AgentRunResult are consistently imported from app.workflows.single # Test 1: Check for any remaining imports from the old path echo "Checking for old imports..." rg "from app.agents.single import.*(?:AgentRunEvent|AgentRunResult)" # Test 2: Verify new import path usage echo "Checking new imports..." rg "from app.workflows.single import.*(?:AgentRunEvent|AgentRunResult)" # Test 3: Verify the new module exists echo "Verifying new module..." fd "single.py" "app/workflows"Length of output: 1047
Script:
#!/bin/bash # Description: Verify the existence and consistency of the single.py module in templates # Test 1: Find single.py in templates directory echo "Searching for single.py in templates..." fd "single.py" "templates" # Test 2: Check content of single.py to verify it contains the expected classes echo "Checking content of files containing AgentRunEvent and AgentRunResult..." rg "class (AgentRunEvent|AgentRunResult)" -A 2 "templates" # Test 3: Check if there are any remaining references to app.agents.single echo "Checking for any remaining references to app.agents.single..." rg "app\.agents\.single" "templates"Length of output: 1352
create-app.ts (1)
90-90: 🛠️ Refactor suggestionConsider adding validation for the
agentsparameter.Since this parameter affects both backend and frontend template installation, it would be beneficial to validate its structure before proceeding with the installation.
Let's check how the
agentsparameter is used in the template installation:Consider adding validation before the installation:
if (agents && !Array.isArray(agents)) { console.error("The agents parameter must be an array"); process.exit(1); }e2e/utils.ts (3)
37-37: LGTM: Type definition is well-structured.The optional
agentsproperty aligns with the multi-agent template requirements and maintains backward compatibility.
56-56: LGTM: Parameter addition is consistent.The
agentsparameter is correctly integrated into the function signature.
124-126: Verify agent validation logic exists.The code correctly adds the
--agentsargument for multiagent templates. However, let's verify that proper validation of the agents string exists in the codebase to prevent invalid configurations.✅ Verification successful
Let me gather more information about agent validation by searching for related code patterns.
Let me search for more specific validation patterns in the agent-related code.
Let me check the contents of the agents configuration file we found and look for any validation logic.
Based on the comprehensive search results, I can now provide the final response:
Agent validation exists through predefined configurations and error handling
The codebase implements agent validation through several mechanisms:
- The
--agentsflag is validated inhelpers/python.tswith a clear error message if no agent is selected for the multiagent template.- Agent types are strictly defined in
templates/components/multiagent/typescript/workflow/agents.tswith specific roles (researcher, writer, reviewer, publisher).- Each agent type has predefined tools and configurations that implicitly validate their usage.
- The system includes error handling for invalid agent configurations, as seen in the error message: "There is no agent selected for multi-agent template. Please pick an agent to use via --agents flag."
The validation is sufficient as it:
- Ensures agents are only used with multiagent templates
- Validates agent selection before proceeding
- Has proper error handling for missing or invalid configurations
- Enforces specific agent roles and their associated tools
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Search for agent validation logic in the codebase # Test 1: Look for agent validation in create-llama command rg -A 5 "validateAgents|agents.*validate|validate.*agents" # Test 2: Look for agent-related types or interfaces that might define valid values ast-grep --pattern 'type $_ = { $$$ agents $$$ }' # Test 3: Look for agent-related constants or enums that might define valid values rg -A 5 "const.*agents.*=|enum.*agents"Length of output: 918
Script:
#!/bin/bash # Look for agent-related validation or processing logic # Search for multiagent template handling rg -A 10 "multiagent.*template" # Search for agent parsing or processing rg -A 5 "agents\.(parse|split|check|process)" # Look for agent-related error handling rg -A 5 "Invalid.*agent|agent.*invalid" # Search for agent configuration in template files fd "template" --type f --exec rg -A 5 "agent.*config" # Look for agent-related CLI argument handling ast-grep --pattern 'if ($_ === "multiagent") { $$$ }'Length of output: 7637
Script:
#!/bin/bash # Look for agent validation in Python and TypeScript components # Search for agent validation in Python components fd "agents" --type f --exec rg -A 5 "def.*validate|check.*agent" # Look for specific agent configuration files fd "agents.ts|agents.py|agent_config" --type f # Search for error handling in agent selection rg -A 10 "agents.*flag" # Look for agent type definitions or constants ast-grep --pattern 'const VALID_AGENTS = $_' # Search for agent-related error messages rg -A 5 "agent.*error|error.*agent"Length of output: 737
Script:
#!/bin/bash # Examine the agents configuration and related files # Check contents of the agents.ts file cat templates/components/multiagent/typescript/workflow/agents.ts # Look for imports or usage of this agents file rg -A 5 "from.*agents|import.*agents" # Search for agent-related type definitions ast-grep --pattern 'type Agent = $_' # Look for agent initialization or setup code rg -A 10 "new.*Agent|createAgent"Length of output: 20771
questions/simple.ts (1)
39-39: Verify title consistency across the codebase.The title change from "Multi-Agent Report Gen" to "Multi-Agent Financial Report" should be consistent with other UI elements and documentation.
✅ Verification successful
Let me try a broader search to verify the title consistency and any related references.
Based on the search results, I can now provide a final response:
Title change is consistent with the codebase implementation
The change from "Multi-Agent Report Gen" to "Multi-Agent Financial Report" is appropriate and consistent with the codebase for the following reasons:
- No instances of the old title "Multi-Agent Report Gen" were found in the codebase
- The new title aligns with the implementation details found in the code:
- The multiagent template is specifically configured for financial reports (
agents: "financial_report"in simple.ts)- There's a comment indicating "Default multiagent with financial report use case only supports Python"
- The title change better reflects the specialized financial report functionality
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Search for any remaining references to the old title rg "Multi-Agent Report Gen"Length of output: 29
Script:
#!/bin/bash # Search for any references to multi-agent in titles or UI elements rg -i "multi.?agent.*report|report.*multi.?agent" -A 2 -B 2Length of output: 945
Script:
#!/bin/bash # Search for multiagent value in the codebase rg '"multiagent"' -A 2 -B 2Length of output: 6332
Script:
#!/bin/bash # Look for template or configuration files that might contain title references fd -e json -e yaml -e yml -e ts -e tsx -e js -e jsx --exec grep -l -i "multi.?agent"Length of output: 86
helpers/index.ts (1)
112-133: 🛠️ Refactor suggestionImprove URL handling and logging in prepareContextData.
The implementation could be enhanced with better URL handling and more informative logging.
Consider these improvements:
- if ("url" in dataSourceConfig) { - console.log( - "Downloading file from URL:", - dataSourceConfig.url.toString(), - ); - const destPath = path.join( - root, - "data", - path.basename(dataSourceConfig.url.toString()), - ); - await downloadFile(dataSourceConfig.url.toString(), destPath); + if ("url" in dataSourceConfig) { + const sourceUrl = dataSourceConfig.url.toString(); + try { + // Validate URL structure + new URL(sourceUrl); + + const fileName = path.basename(sourceUrl); + const destPath = path.join(root, "data", fileName); + + console.log(`Downloading ${fileName} from ${sourceUrl}`); + await downloadFile(sourceUrl, destPath); + console.log(`Successfully downloaded to ${destPath}`); + } catch (error) { + if (error instanceof TypeError) { + throw new Error(`Invalid URL: ${sourceUrl}`); + } + throw error; + }Let's verify the URL validation in the codebase:
index.ts (1)
211-217: Verify integration with template system.Please ensure that:
- The
createAppfunction properly handles theagentsparameter- Existing templates continue to work when no agents are specified
- The multi-agent template correctly processes the agent selection
Let's verify the integration:
✅ Verification successful
Let's gather more specific information about how the agents parameter is used in the codebase.
Let's search for more specific information about how the agents parameter is used in the template installation process.
Based on the gathered information, I can now provide a final response:
The
--agentsparameter is properly integrated with the template systemThe codebase analysis shows that:
- The
agentsparameter is correctly handled in the template installation process, specifically for the multiagent template- The system includes proper validation - it exits with an error if no agent is selected for the multiagent template
- The implementation supports different agent types (e.g., financial_report, blog) as shown in the e2e tests
- The template system has specific handling for agent selection in both Python and TypeScript implementations
- Existing templates continue to work as the multiagent-specific code is only activated when that template is selected
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify template system integration # Test 1: Check if createApp handles the agents parameter echo "Checking createApp implementation..." ast-grep --pattern 'function createApp($_) { $$$ agents $$$ }' # Test 2: Check if installTemplate uses the agents parameter echo "Checking installTemplate implementation..." ast-grep --pattern 'function installTemplate($_) { $$$ agents $$$ }' # Test 3: Check for any template-specific agent handling echo "Checking template-specific agent handling..." rg -l "multiagent.*template"Length of output: 541
Script:
#!/bin/bash # Check the content of files that mention multiagent template echo "Checking multiagent template implementation in typescript.ts..." cat helpers/typescript.ts echo -e "\nChecking multiagent template implementation in env-variables.ts..." cat helpers/env-variables.ts echo -e "\nChecking multiagent template test implementation..." cat e2e/shared/multiagent_template.spec.ts # Search for any direct usage of the agents parameter echo -e "\nSearching for agents parameter usage..." rg "agents.*parameter|parameter.*agents" -A 3 # Look for template installation logic echo -e "\nSearching for template installation logic..." ast-grep --pattern 'installTemplate($$$) { $$$ }'Length of output: 30451
Script:
#!/bin/bash # Search for multiagent template related code echo "Searching for multiagent template handling..." rg "template.*multiagent|multiagent.*template" -A 5 # Search for agents parameter handling echo -e "\nSearching for agents parameter handling..." rg "agents.*=|--agents" -A 5 # Look for createApp implementation echo -e "\nLooking for createApp implementation..." ast-grep --pattern 'createApp($$$) { $$$ }'Length of output: 11923
templates/components/agents/python/blog/app/agents/workflow.py (1)
4-6: LGTM! Import paths have been logically reorganized.The restructuring of imports improves code organization by:
- Moving agent-related imports to the
app.agentspackage- Moving workflow-related imports to the
app.workflowspackagetemplates/components/multiagent/python/app/workflows/planner.py (1)
5-5: Verify the module restructuring impact.The import path change from
app.agents.singletoapp.workflows.singleappears to be part of a broader restructuring to centralize agent-related functionalities in the workflows module. While the change itself is straightforward, we should verify that all dependent modules have been updated accordingly.Let's verify the module restructuring:
✅ Verification successful
Import path change is correctly implemented across the codebase
The verification results show that:
- The classes
AgentRunEvent,AgentRunResult, andFunctionCallingAgentare indeed defined intemplates/components/multiagent/python/app/workflows/single.py- All imports across the codebase consistently use the new path
app.workflows.single, including the file under review- No instances of the old import path
app.agents.singlewere foundThe module restructuring has been properly implemented, maintaining consistency across all dependent modules.
🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Verify that all imports of AgentRunEvent, AgentRunResult, and FunctionCallingAgent # have been updated to use the new path # Test 1: Check for any remaining imports from the old path echo "Checking for remaining old imports..." rg "from app.agents.single import (AgentRunEvent|AgentRunResult|FunctionCallingAgent)" # Test 2: Verify the new module exists and contains the required classes echo "Verifying new module structure..." rg -l "class (AgentRunEvent|AgentRunResult|FunctionCallingAgent)" "app/workflows/single.py"Length of output: 406
Script:
#!/bin/bash # Let's first check if the file exists in a different location or with a different name echo "Searching for files containing the relevant classes..." fd -t f -e py . | xargs rg -l "class (AgentRunEvent|AgentRunResult|FunctionCallingAgent)" echo "Searching for all imports of these classes..." rg "import.*(AgentRunEvent|AgentRunResult|FunctionCallingAgent)" echo "Checking the directory structure..." fd -t f -e py . templates/components/multiagent/python/app/Length of output: 2825
helpers/python.ts (1)
365-365: LGTM: Clean signature update for multi-agent support.The addition of the
agentsparameter toinstallPythonTemplateis well-integrated and maintains type safety through the Pick utility type.Also applies to: 377-377
templates/components/agents/python/financial_report/app/agents/workflow.py (1)
88-103: 🛠️ Refactor suggestionSimplify prompt creation without using 'PromptTemplate'
Since
prompt_templateis being used directly without leveraging its advanced features, the code can be simplified by constructing the prompt string directly.Apply this diff:
- prompt_template = PromptTemplate( - dedent( - """ - You are an expert in decision-making, helping people create financial reports for the provided data. - If the conversation already has a report and user wants to get a file/document of the report, respond with 'publish'. - Otherwise, respond with 'research'. - Here is the chat history: - {chat_history} - The current user request is: - {input} - Given the chat history and the new user request, decide whether to create a report based on existing information. - Decision (respond with either 'not_publish' or 'publish'): - """ - ) - ) + prompt = dedent(f""" + You are an expert in decision-making, helping people create financial reports for the provided data. + If the conversation already has a report and user wants to get a file/document of the report, respond with 'publish'. + Otherwise, respond with 'research'. + Here is the chat history: + {chat_history_str} + The current user request is: + {input} + Given the chat history and the new user request, decide whether to create a report based on existing information. + Decision (respond with either 'not_publish' or 'publish'): + """)Likely invalid or redundant comment.
templates/components/agents/python/financial_report/app/agents/reporter.py
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Actionable comments posted: 2
🧹 Outside diff range and nitpick comments (4)
.changeset/spicy-apricots-double.md (1)
5-5: Enhance the changeset description with more details.The current description is too brief. Consider adding:
- Overview of the new financial report use case
- List of key changes (e.g., new agents, workflow updates)
- Any migration steps if needed
Example enhancement:
-Add financial report as the default use case in the multi-agent template (Python). +Add financial report as the default use case in the multi-agent template (Python): +- Introduces new specialized agents (analyst, reporter, researcher) +- Implements financial report generation workflow +- Updates multi-agent template structure +- Enhances template customization through new agents parametertemplates/components/agents/python/financial_report/app/agents/researcher.py (3)
12-15: Enhance function documentation.The docstring should include:
- Parameters description
- Return type and description
- Example usage
def _create_query_engine_tools(params=None) -> Optional[list[type[BaseTool]]]: """ - Provide an agent worker that can be used to query the index. + Create query engine tools based on the index type. + + Args: + params (Optional[dict]): Parameters for index configuration + + Returns: + Optional[list[type[BaseTool]]]: List of query tools or None if index not found + + Example: + tools = _create_query_engine_tools({"index_path": "path/to/index"}) """
83-87: Add type hints for kwargs parameter.For better type safety and code documentation, specify the expected kwargs types.
-def create_researcher(chat_history: List[ChatMessage], **kwargs): +def create_researcher(chat_history: List[ChatMessage], **kwargs: Optional[dict]):
96-103: Enhance system prompt for clarity.The system prompt could be more specific about:
- Expected response format
- How to handle partial matches
- Maximum context length considerations
system_prompt=dedent( """ You are a researcher agent. You are responsible for retrieving information from the corpus. ## Instructions + Don't synthesize the information, just return the whole retrieved information. + Don't need to retrieve the information that is already provided in the chat history and response with: "There is no new information, please reuse the information from the conversation." + + Format your response as direct quotes from the retrieved documents + + If the retrieved information exceeds context length, prioritize the most relevant sections + + Clearly indicate when information is from different documents or sections """ ),
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- .changeset/spicy-apricots-double.md (1 hunks)
- questions/simple.ts (6 hunks)
- templates/components/agents/python/financial_report/app/agents/researcher.py (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- questions/simple.ts
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📓 Path-based instructions (1)
templates/components/agents/python/financial_report/app/agents/researcher.py (1)
Pattern
templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
🔇 Additional comments (2)
templates/components/agents/python/financial_report/app/agents/researcher.py (2)
1-10: LGTM! Imports are well-organized and complete.All necessary dependencies are properly imported and organized by standard library, internal modules, and external packages.
89-104: LGTM! Good error handling and agent configuration.The error handling for missing tools and the agent configuration with chat history are well implemented.
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Actionable comments posted: 5
🧹 Outside diff range and nitpick comments (2)
questions/simple.ts (1)
51-53: Document the Python-only limitation for multi-agent template.While the TODO indicates future TypeScript support, it would be helpful to document this limitation in user-facing documentation or README to set proper expectations.
templates/components/agents/python/financial_report/app/agents/workflow.py (1)
85-86: Address TODO comment for prompt generation refactoring.The TODO comment suggests refactoring the prompt generation. This could improve maintainability and reusability of prompts across the workflow.
Would you like me to help implement a proper prompt management system that separates prompts into a dedicated configuration file?
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- questions/simple.ts (6 hunks)
- templates/components/agents/python/financial_report/app/agents/reporter.py (1 hunks)
- templates/components/agents/python/financial_report/app/agents/workflow.py (1 hunks)
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- templates/components/agents/python/financial_report/app/agents/reporter.py
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templates/components/agents/python/financial_report/app/agents/workflow.py (1)
Pattern
templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
🔇 Additional comments (2)
templates/components/agents/python/financial_report/app/agents/workflow.py (2)
1-19: LGTM! Well-organized imports.The imports are properly organized and include all necessary dependencies for the workflow implementation.
163-176: LGTM! Well-implemented agent execution logic.The
run_agentmethod effectively handles both streaming and non-streaming cases while properly managing event propagation.
templates/components/agents/python/financial_report/app/agents/workflow.py
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🧹 Outside diff range and nitpick comments (2)
templates/components/agents/python/financial_report/app/agents/workflow.py (2)
41-51: Add docstrings to event classes for better documentation.The event classes would benefit from docstrings explaining their purpose and the expected format/content of their input field.
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class ResearchEvent(Event): + """Event triggered to start research phase. + + Attributes: + input (str): The research query or task description + """ input: str class AnalyzeEvent(Event): + """Event triggered to start analysis phase. + + Attributes: + input (str): The research results to be analyzed + """ input: str class ReportEvent(Event): + """Event triggered to start report generation phase. + + Attributes: + input (str): The analyzed content to be included in the report + """ input: str
84-101: Address TODO: Improve prompt generation.The TODO comment indicates a need for prompt refactoring. Consider extracting the prompt template to a separate configuration file or constants module for better maintainability and reusability.
Would you like me to help create a separate module for managing prompts?
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📒 Files selected for processing (2)
- questions/simple.ts (6 hunks)
- templates/components/agents/python/financial_report/app/agents/workflow.py (1 hunks)
🚧 Files skipped from review as they are similar to previous changes (1)
- questions/simple.ts
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templates/components/agents/python/financial_report/app/agents/workflow.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
🔇 Additional comments (3)
templates/components/agents/python/financial_report/app/agents/workflow.py (3)
1-18: LGTM! Well-organized imports.The imports are properly organized and include all necessary dependencies for the workflow implementation.
21-39: LGTM! Clean workflow initialization.The function properly initializes all required agents and configures the workflow. The agent creation is well-structured with proper parameter passing.
162-175: LGTM! Well-implemented agent execution logic.The run_agent method effectively handles both streaming and non-streaming cases while properly managing event propagation.
Summary by CodeRabbit
Release Notes
New Features
--agents <agents>for specifying agents in multi-agent templates.Enhancements
createAppfunction to accept anagentsparameter, improving installation flexibility.prepareContextDatafunction to support downloading files from URLs.Documentation
Refactor