feat: Use selected LlamaCloud index in multi-agent template #350
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🦋 Changeset detectedLatest commit: 407fa7b 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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WalkthroughThis pull request introduces a patch labeled "create-llama," enabling the use of selected LlamaCloud indices within a multi-agent template. Key modifications include the addition of parameters to various functions, allowing for enhanced configurability and integration of LlamaCloud services. The logging mechanism for LlamaCloud configuration has also been updated to use print statements instead of a logger. Overall, the changes focus on improving the flexibility and functionality of the multi-agent framework in relation to LlamaCloud. Changes
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Actionable comments posted: 3
🧹 Outside diff range and nitpick comments (7)
.changeset/witty-hotels-do.md (1)
1-5: LGTM! Consider enhancing the description slightly.The changeset looks good and aligns with the PR objectives. The patch version bump is appropriate for the described change.
Consider slightly expanding the description for more clarity. For example:
-Use selected LlamaCloud index in multi-agent template +Use selected LlamaCloud index in multi-agent template to enhance data integrationThis minor addition provides a bit more context about the purpose of the change.
templates/types/streaming/fastapi/app/api/routers/chat_config.py (1)
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1-45: Review overall logging strategy for consistency.The changes in this file suggest a shift from using the
loggerobject to
- Consistency: Ensure this change is applied consistently across the codebase if it's intentional.
- Log Management: Verify that this change doesn't negatively impact log collection, filtering, or analysis in your production environment.
- Error Handling: Confirm that critical error information isn't lost due to this change, especially in the except block.
Consider reviewing the project's logging strategy holistically. If print statements are preferred, document this decision and ensure it meets all logging requirements (e.g., log levels, formatting, integration with monitoring tools).
templates/components/multiagent/python/app/examples/choreography.py (2)
11-11: LGTM! Consider adding documentation for**kwargs.The addition of
**kwargsto the function signature enhances flexibility and aligns with the PR objectives. This change allows for passing additional arguments to thecreate_researcherfunction, improving the template's configurability.Consider adding a brief docstring to explain the purpose of
**kwargsand how it's used within the function. This would improve code readability and maintainability.
24-31: LGTM! Improved readability ofsystem_prompt.The reformatting of the
system_promptenhances code readability without altering its functionality. The use of a multi-line string withdedentis a good practice for maintaining clean and readable code.For consistency, consider applying similar formatting to other string literals in the file, such as the
system_promptfor therevieweragent. This would maintain a uniform style throughout the code.templates/components/multiagent/python/app/examples/orchestrator.py (1)
11-11: LGTM! Consider adding a docstring for clarity.The addition of
**kwargsto the function signature enhances flexibility and aligns with the PR objectives. This change allows for passing additional configuration options to thecreate_researcherfunction.Consider adding a docstring to explain the purpose of
**kwargsand any expected key-value pairs. This would improve the function's documentation and make it easier for other developers to use.def create_orchestrator(chat_history: Optional[List[ChatMessage]] = None, **kwargs): """ Create an orchestrator for multi-agent interactions. Args: chat_history (Optional[List[ChatMessage]]): The chat history to initialize agents with. **kwargs: Additional keyword arguments to be passed to the create_researcher function. Returns: AgentOrchestrator: An orchestrator instance with configured agents. """ # ... rest of the functiontemplates/components/multiagent/python/app/examples/workflow.py (1)
20-23: LGTM! Consider adding a docstring for clarity.The addition of
**kwargsto thecreate_workflowfunction and its usage increate_researcherimproves flexibility and aligns with the PR objective. This change allows for easier integration of LlamaCloud indices.Consider adding a docstring to explain the purpose of
**kwargs:def create_workflow(chat_history: Optional[List[ChatMessage]] = None, **kwargs): """ Create a workflow for blog post creation. Args: chat_history (Optional[List[ChatMessage]]): The chat history. **kwargs: Additional keyword arguments to be passed to the researcher. Returns: BlogPostWorkflow: The created workflow instance. """ # ... rest of the functiontemplates/components/multiagent/python/app/examples/researcher.py (1)
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63-83: Fix typos insystem_promptThere are typographical errors in the
system_promptwhere "->Though" should be "->Thought". Correcting these will improve the readability of the prompt.Apply this diff to correct the typos:
- ->Though: The main content is "history of the internet", while "write in English and publish in PDF format" is a requirement for other agents. + ->Thought: The main content is "history of the internet", while "write in English and publish in PDF format" is a requirement for other agents. ... - ->Though: User just asking for a format change, the previous content is still valid. + ->Thought: User is just asking for a format change; the previous content is still valid.
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📒 Files selected for processing (8)
- .changeset/witty-hotels-do.md (1 hunks)
- templates/components/multiagent/python/app/api/routers/chat.py (1 hunks)
- templates/components/multiagent/python/app/engine/engine.py (1 hunks)
- templates/components/multiagent/python/app/examples/choreography.py (2 hunks)
- templates/components/multiagent/python/app/examples/orchestrator.py (1 hunks)
- templates/components/multiagent/python/app/examples/researcher.py (4 hunks)
- templates/components/multiagent/python/app/examples/workflow.py (3 hunks)
- templates/types/streaming/fastapi/app/api/routers/chat_config.py (2 hunks)
🧰 Additional context used
📓 Path-based instructions (7)
templates/components/multiagent/python/app/api/routers/chat.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/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/examples/choreography.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/app/examples/orchestrator.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/app/examples/researcher.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/components/multiagent/python/app/examples/workflow.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.templates/types/streaming/fastapi/app/api/routers/chat_config.py (1)
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templates/**: For files under thetemplatesfolder, do not report 'Missing Dependencies Detected' errors.
🔇 Additional comments (15)
templates/components/multiagent/python/app/engine/engine.py (2)
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14-15: LGTM: Function signature update enhances flexibility.The addition of
**kwargsto the function signature is a good change. It allows for more flexibility in passing additional parameters to theget_chat_enginefunction, which aligns with the PR objective of using selected LlamaCloud indices.
21-21: Verify compatibility of called functions with**kwargs.The changes to pass
**kwargstocreate_choreography,create_orchestrator, andcreate_workfloware consistent and appropriate. However, it's important to ensure that these functions are capable of handling additional keyword arguments.To verify the compatibility, please run the following script:
This script will search for the function definitions and verify if they accept
**kwargs. If the functions are not found or don't accept**kwargs, you may need to update them to handle the additional arguments.Also applies to: 23-23, 25-25
templates/types/streaming/fastapi/app/api/routers/chat_config.py (2)
26-26: Consider using logger instead of print for consistency.The change from
logger.info()toprint()may impact log management and integration with existing logging infrastructure. While print statements are simpler, they lack the flexibility and features of a proper logging system (e.g., log levels, formatting, output redirection).Could you confirm if replacing logger with print is intentional? If not, consider reverting to using the logger:
- print("LlamaCloud is configured. Adding /config/llamacloud route.") + logger.info("LlamaCloud is configured. Adding /config/llamacloud route.")If this change is intentional, please ensure it aligns with the project's logging strategy.
45-45: Consistent use of print, but consider logger for better control.This change is consistent with the previous one, replacing
logger.debug()withprint(). However, it raises the same concerns about log management and control.If the previous change to print was unintentional, consider reverting this one as well:
- print("LlamaCloud is not configured. Skipping adding /config/llamacloud route.") + logger.debug("LlamaCloud is not configured. Skipping adding /config/llamacloud route.")If these changes are part of a deliberate shift in logging strategy, please ensure this aligns with the project's overall logging approach and requirements.
templates/components/multiagent/python/app/api/routers/chat.py (2)
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1-45: Summary of changes and recommendationsThe changes introduced in this file successfully implement the ability to use selected LlamaCloud index in the multi-agent template, aligning with the PR objectives. The modification to the
get_chat_enginecall allows for more flexible configuration through the newparamsargument.Key points:
- The changes are minimal and well-integrated into the existing code structure.
- Error handling and the overall function structure remain intact.
- The introduction of the
paramsvariable increases flexibility but requires additional attention to ensure robust implementation.Recommendations:
- Implement input validation for the
paramsdictionary.- Add documentation explaining the structure and purpose of
params.- Verify that the
get_chat_enginefunction in other parts of the codebase is prepared to handle the newparamsargument.Overall, the changes are approved with the suggested improvements for better code quality and maintainability.
31-32: Approve changes with suggestions for improvementThe changes align well with the PR objectives of using selected LlamaCloud index in the multi-agent template. The introduction of the
paramsvariable allows for more flexible configuration of the chat engine. However, I have a few suggestions to improve the code:
- Consider adding input validation for the
paramsdictionary to ensure it contains expected keys and value types.- Add documentation (preferably as a docstring) explaining the structure and purpose of the
paramsdictionary, including any required or optional keys.Here's a suggested improvement:
def validate_params(params: dict) -> dict: # Add validation logic here return params # In the chat function params = validate_params(data.data or {})Let's verify the impact of these changes on the rest of the codebase:
This will help us ensure that the changes are consistent with other parts of the codebase and that the
get_chat_enginefunction is prepared to handle the newparamsargument.✅ Verification successful
Changes Verified Successfully
The introduction of the
paramsparameter inget_chat_engineis consistent across all implementations and does not introduce any issues to the codebase.🏁 Scripts executed
The following scripts were executed for the analysis:
Script:
#!/bin/bash # Description: Check for other occurrences of get_chat_engine and potential impacts # Test 1: Search for other calls to get_chat_engine echo "Searching for other calls to get_chat_engine:" rg "get_chat_engine\(" --type py # Test 2: Check the implementation of get_chat_engine echo "Checking the implementation of get_chat_engine:" rg "def get_chat_engine" --type py -A 10Length of output: 4183
templates/components/multiagent/python/app/examples/choreography.py (2)
12-12: LGTM! Proper usage of**kwargs.The
**kwargsis correctly passed to thecreate_researcherfunction, allowing for flexible configuration of the researcher agent without modifying thecreate_choreographyfunction. This change aligns well with the PR objectives and enhances the template's adaptability.
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1-35: Overall, the changes look good and align with the PR objectives.The modifications to the
create_choreographyfunction enhance its flexibility and improve code readability. The addition of**kwargsallows for better integration with LlamaCloud services, as mentioned in the PR objectives. The reformatting of thesystem_promptimproves code maintainability.A few minor suggestions have been made to further improve documentation and consistency, but these are not critical issues. The changes are approved and ready for merging, pending any final adjustments based on the suggestions.
templates/components/multiagent/python/app/examples/orchestrator.py (3)
12-12: LGTM! Correct usage of**kwargs.The
**kwargsis correctly passed to thecreate_researcherfunction, allowing for flexible configuration of the researcher agent. This change is consistent with the function signature update and enhances the modularity of the code.
16-24: LGTM! Improved formatting for better readability.The reformatting of the
system_promptstrings for both thewriterandrevieweragents enhances code readability. The use of parentheses instead of a closing quote on a new line is a cleaner approach and consistent with Python best practices.Also applies to: 30-36
11-36: Overall LGTM! Changes enhance flexibility and readability.The modifications to the
create_orchestratorfunction successfully implement the PR objectives:
- The addition of
**kwargsto the function signature and its usage increate_researcherallow for the integration of selected LlamaCloud indices, enhancing configurability.- The reformatting of
system_promptstrings improves code readability.These changes maintain the original functionality while providing more flexibility for future extensions. The code structure remains clean and consistent with the rest of the file.
templates/components/multiagent/python/app/examples/workflow.py (2)
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131-146: LGTM! Improved readability.The reformatting of the string passed to
dedentenhances code readability without changing the logic. This change aligns with Python best practices for multi-line strings.
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1-265: Overall, the changes improve flexibility and readability.The modifications in this file successfully address the PR objective of using selected LlamaCloud index in the multi-agent template. The addition of
**kwargsin thecreate_workflowfunction enhances flexibility, while the reformatting of the string in_decide_workflowimproves readability.These changes contribute positively to the codebase without introducing any apparent issues or bugs. The multi-agent framework's integration with LlamaCloud services has been improved, aligning well with the PR's goals.
templates/components/multiagent/python/app/examples/researcher.py (2)
6-6: ImportIndexConfigfor index configurationThe addition of
IndexConfigto the import statement is appropriate, as it is used for configuring the index.
12-12: Addparamsparameter to_create_query_engine_toolIntroducing the
paramsparameter enhances the configurability of the query engine tool creation.
| @@ -48,16 +50,17 @@ def _get_research_tools() -> QueryEngineTool: | |||
| return tools | |||
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| def create_researcher(chat_history: List[ChatMessage]): | |||
| def create_researcher(chat_history: List[ChatMessage], **kwargs): | |||
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🛠️ Refactor suggestion
Add type annotations for **kwargs in create_researcher
Consider specifying the expected types within **kwargs for better code clarity and to assist developers in understanding what parameters can be passed.
| def _create_query_engine_tool(params=None) -> QueryEngineTool: | ||
| """ | ||
| Provide an agent worker that can be used to query the index. | ||
| """ | ||
| index = get_index() | ||
| # Add query tool if index exists | ||
| index_config = IndexConfig(**(params or {})) | ||
| index = get_index(index_config) |
There was a problem hiding this comment.
🛠️ Refactor suggestion
Specify type annotations for params
To improve code clarity and type safety, consider adding a type annotation to params. Since it's expected to be a dictionary of parameters, you could define it as Optional[Dict].
Apply this diff to add the type annotation:
-def _create_query_engine_tool(params=None) -> QueryEngineTool:
+def _create_query_engine_tool(params: Optional[Dict] = None) -> QueryEngineTool:📝 Committable suggestion
‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.
| def _create_query_engine_tool(params=None) -> QueryEngineTool: | |
| """ | |
| Provide an agent worker that can be used to query the index. | |
| """ | |
| index = get_index() | |
| # Add query tool if index exists | |
| index_config = IndexConfig(**(params or {})) | |
| index = get_index(index_config) | |
| def _create_query_engine_tool(params: Optional[Dict] = None) -> QueryEngineTool: | |
| """ | |
| Provide an agent worker that can be used to query the index. | |
| """ | |
| # Add query tool if index exists | |
| index_config = IndexConfig(**(params or {})) | |
| index = get_index(index_config) |
| @@ -31,13 +33,13 @@ | |||
| ) | |||
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| def _get_research_tools() -> QueryEngineTool: | |||
| def _get_research_tools(**kwargs) -> QueryEngineTool: | |||
There was a problem hiding this comment.
Correct return type annotation in _get_research_tools
The function returns a list of QueryEngineTools, but the return type annotation is -> QueryEngineTool. Update the return type to List[QueryEngineTool] for accuracy.
Apply this diff to fix the return type annotation:
-from typing import List
+from typing import List, Dict, Optional
-def _get_research_tools(**kwargs) -> QueryEngineTool:
+def _get_research_tools(**kwargs) -> List[QueryEngineTool]:Committable suggestion was skipped due to low confidence.
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New Features
Bug Fixes
Documentation