Multi agent example #15
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WalkthroughThe pull request introduces enhancements to the Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Orchestrator
participant KGAgent_Restaurant
participant KGAgent_Attraction
User->>Orchestrator: Ask for itinerary
Orchestrator->>KGAgent_Restaurant: Query for restaurant data
KGAgent_Restaurant-->>Orchestrator: Return restaurant data
Orchestrator->>KGAgent_Attraction: Query for attraction data
KGAgent_Attraction-->>Orchestrator: Return attraction data
Orchestrator-->>User: Provide itinerary suggestions
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Files selected for processing (2)
- README.md (2 hunks)
- examples/trip/demo_orchestrator_trip.ipynb (7 hunks)
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Markdownlint
README.md
204-204: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
451-451: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
498-498: null
Fenced code blocks should have a language specified(MD040, fenced-code-language)
Additional comments not posted (11)
examples/trip/demo_orchestrator_trip.ipynb (7)
9-21: Review of Import Statements and Environment SetupThe addition of new import statements (
vertexai,json.loads) and the consolidation of existing imports improve the readability and organization of the notebook. Placingload_dotenv()prominently is a good practice as it ensures environment variables are loaded before any dependent operations.
31-32: Markdown Explanation for Data ReadingThe new markdown cell provides a clear explanation of the subsequent code's purpose, which enhances the notebook's documentation and makes it more user-friendly.
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36-133: Streamlined Data Import FunctionThe reorganization of the
import_datafunction and the explicit loading of data into Knowledge Graphs improve the clarity and functionality of the code. It's good to see that data handling is being separated into a distinct function, which enhances modularity and readability.
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123-295: Ontology Creation and OrganizationMoving the initialization of
attractions_ontologyto a more logical position before its usage is a significant improvement. The detailed setup of entities and relations within the ontology is well-documented through the code, which aligns with best practices in code clarity and maintainability.
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310-337: Setup of Knowledge Graphs and AgentsThe instantiation of
KnowledgeGraphandKGAgentobjects is clear and follows the SDK's usage patterns. The introductions for agents are concise and relevant, which helps in understanding the role of each agent within the multi-agent system.
353-362: Orchestrator Initialization and QueryThe setup of the
Orchestratorand the registration of agents are correctly implemented. The query to the orchestrator is well-formed, and the explicit instruction not to ask further questions streamlines the interaction, fitting the use case of generating a quick itinerary.
374-397: Itinerary Output and PresentationThe detailed itinerary output is well-formatted and informative, providing a clear and engaging user experience. The use of bold and structured lists helps in making the itinerary easy to read and follow.
README.md (4)
180-202: Addition of Multi-Agent ExampleThe new section on multi-agent systems is comprehensive and well-structured. It provides a clear example of setting up the environment, importing data, and configuring agents, which significantly enhances the documentation.
204-283: Detailed Code Example for Data Import and Graph SetupThe detailed code example for importing data and setting up Knowledge Graphs is informative and practical. It effectively demonstrates how to populate graphs with data from JSON files, which is crucial for users to understand the SDK's capabilities.
Tools
Markdownlint
204-204: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
285-450: Ontology and Entity Setup ExampleThe detailed setup of ontologies and entities in the README is a valuable addition. It provides users with a clear understanding of how to define and use ontologies within the SDK, enhancing the educational value of the documentation.
452-497: Multi-Agent System Configuration and QueryingThe final section detailing the setup of the multi-agent system and the orchestrator is well-explained. The example query and the output provided give a practical demonstration of the system's capabilities, making it easier for users to replicate and adapt for their needs.
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Files selected for processing (1)
- README.md (1 hunks)
Additional context used
Markdownlint
README.md
205-205: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
452-452: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
499-499: null
Fenced code blocks should have a language specified(MD040, fenced-code-language)
Additional comments not posted (1)
README.md (1)
181-498: Comprehensive Review of Multi-Agent Example in README.mdThe addition of the "Multi Agent" section in the README.md file significantly enhances the documentation by providing a detailed example of setting up a multi-agent system using the GraphRAG-SDK-v2. This section includes code snippets that demonstrate the initialization of environment variables, the setup of the Vertex AI client, and the detailed steps to import data into Knowledge Graphs for restaurants and attractions.
Key Observations and Suggestions:
Code Clarity and Functionality:
- The code snippets are well-organized and provide a clear step-by-step guide to setting up the multi-agent system. This includes the definition of entities, relations, and the instantiation of
KGAgentobjects.- The use of
import_datafunction to load JSON data into the Knowledge Graphs is a practical example that users can easily adapt for their purposes.Documentation Quality:
- The explanations accompanying the code snippets are informative and enhance understanding. It's beneficial for users who are new to the concept of multi-agent systems in the context of Knowledge Graphs.
Syntax and Markdown Issues:
- There are minor markdown lint issues such as trailing punctuation in headings which should be corrected to adhere to markdown best practices.
- The fenced code block at the end of the document lacks a specified language, which should be added for better syntax highlighting and readability.
Potential Enhancements:
- While the documentation is comprehensive, adding a few more examples of querying the multi-agent system could provide further clarity and demonstrate additional capabilities of the system.
- Consider including a section on troubleshooting common issues that might arise when setting up or querying the multi-agent system.
Overall Assessment:
The changes made in the README.md file are substantial and improve the documentation significantly. They provide a clear and practical example of how to implement a multi-agent system using the GraphRAG-SDK-v2, which will be beneficial for users. The documentation is well-structured and informative, making it easier for users to understand and implement the described functionalities.Consider the enhancements mentioned above to further improve the documentation and examples provided.
Tools
Markdownlint
205-205: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
452-452: Punctuation: '.'
Trailing punctuation in heading(MD026, no-trailing-punctuation)
Changes:
Summary by CodeRabbit
New Features
Documentation
Bug Fixes