Add e commerce shopping assistant #675
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WalkthroughA new Jupyter notebook example, "E-commerce Shopping Assistant," has been added. It demonstrates building an AI agent-based system using PraisonAI Agents to help users find, compare, and decide on wireless earbuds under $100. The notebook includes setup, agent and task definition, system creation, execution, and result display. Changes
Sequence Diagram(s)sequenceDiagram
participant User
participant Notebook
participant PraisonAIAgents
participant EcommerceShoppingAgent
participant OpenAI API
participant DuckDuckGo Search
User->>Notebook: Provide OpenAI API key and run cells
Notebook->>PraisonAIAgents: Create system with agent and task
Notebook->>PraisonAIAgents: Run query for earbuds under $100
PraisonAIAgents->>EcommerceShoppingAgent: Assign shopping task
EcommerceShoppingAgent->>DuckDuckGo Search: Search for products
EcommerceShoppingAgent->>OpenAI API: Analyze and compare products
EcommerceShoppingAgent->>PraisonAIAgents: Return recommendations
PraisonAIAgents->>Notebook: Output formatted results
Notebook->>User: Display recommendations
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Summary of Changes
Hello @DhivyaBharathy-web, I'm Gemini Code Assist1! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!
This pull request introduces a new example Jupyter Notebook that showcases an AI-powered e-commerce shopping assistant. The assistant is designed to help users with product discovery, comparison, and decision-making by leveraging AI agents to research and synthesize information from online sources.
Highlights
- New E-commerce Shopping Assistant Notebook: Introduces a new Jupyter Notebook (
E_commerce_Shopping_Assistant.ipynb) that demonstrates how to build an AI-powered e-commerce shopping assistant. - AI Agent Implementation: The notebook sets up an
EcommerceShoppingAgentusingpraisonaiagentsto perform product comparisons, pricing insights, and personalized recommendations. - Dependency Integration: Shows the integration of
openaifor AI capabilities andduckduckgo_searchfor online research within the agent's workflow.
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Codecov ReportAll modified and coverable lines are covered by tests ✅
Additional details and impacted files@@ Coverage Diff @@
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Lines 2517 2517
Branches 357 357
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Partials 16 16
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Code Review
The pull request introduces an E-commerce Shopping Assistant Jupyter notebook with an AI agent for product comparison and recommendations. The notebook includes an interactive example for wireless earbuds search, providing structured output with pros, cons, and pricing. The review focuses on ensuring the query aligns with the notebook's intended functionality.
| "query = \"Find the best wireless earbuds under $100 with noise cancellation\"\n", | ||
| "output = assistant_system.start(input=query)\n", |
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The query lacks noise cancellation criteria, while the comment above cell 35 states that the query should include noise cancellation. This discrepancy should be addressed to align the query with the intended functionality.
query = "Find the best wireless earbuds under $100 with noise cancellation"
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Actionable comments posted: 2
🧹 Nitpick comments (1)
examples/cookbooks/E_commerce_Shopping_Assistant.ipynb (1)
94-100: Update to use modern OpenAI client initialization.The
openai.api_keyassignment on line 99 is deprecated in newer versions of the OpenAI library. Consider using the modern client initialization pattern.import os from getpass import getpass os.environ["OPENAI_API_KEY"] = getpass("Enter your OpenAI API key: ") -import openai -openai.api_key = os.getenv("OPENAI_API_KEY") +from openai import OpenAI +client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
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🔇 Additional comments (3)
examples/cookbooks/E_commerce_Shopping_Assistant.ipynb (3)
60-60: LGTM!The dependency installation correctly includes all necessary packages for the e-commerce shopping assistant functionality.
143-179: LGTM!The agent and task definitions are well-structured with clear instructions and expected outputs. The agent's role as an e-commerce shopping assistant is properly defined.
201-206: LGTM!The system configuration is appropriate with sequential processing for the single task and verbose mode enabled for better demonstration visibility.
| "query = \"Find the best wireless earbuds under $100 with noise cancellation\"\n", | ||
| "output = assistant_system.start(input=query)\n", | ||
| "\n", | ||
| "# 📄 Display Output\n", | ||
| "print(\"🛍️ Shopping Assistant Output:\\n\", output)\n" |
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🛠️ Refactor suggestion
Address query-task inconsistency and add error handling.
Two issues identified:
-
Query-task mismatch: The query specifically requests "noise cancellation" but the task description doesn't mention this requirement, and all recommended earbuds lack active noise cancellation.
-
Missing error handling: No error handling around the system execution could lead to unhandled exceptions.
-query = "Find the best wireless earbuds under $100 with noise cancellation"
+query = "Find the best wireless earbuds under $100"
-output = assistant_system.start(input=query)
+try:
+ output = assistant_system.start(input=query)
+except Exception as e:
+ print(f"Error executing assistant system: {e}")
+ output = "Unable to process request at this time."Alternatively, update the task description to specifically mention noise cancellation requirements if that's the intended functionality.
📝 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.
| "query = \"Find the best wireless earbuds under $100 with noise cancellation\"\n", | |
| "output = assistant_system.start(input=query)\n", | |
| "\n", | |
| "# 📄 Display Output\n", | |
| "print(\"🛍️ Shopping Assistant Output:\\n\", output)\n" | |
| # Update the query if you want to drop the noise-cancellation requirement | |
| query = "Find the best wireless earbuds under $100" | |
| # Add error handling around the assistant call | |
| try: | |
| output = assistant_system.start(input=query) | |
| except Exception as e: | |
| print(f"Error executing assistant system: {e}") | |
| output = "Unable to process request at this time." | |
| # 📄 Display Output | |
| print("🛍️ Shopping Assistant Output:\n", output) |
🤖 Prompt for AI Agents
In examples/cookbooks/E_commerce_Shopping_Assistant.ipynb around lines 539 to
543, the query requests earbuds with noise cancellation but the task description
and recommendations do not reflect this requirement, causing inconsistency.
Update the task description to explicitly include the noise cancellation feature
or modify the query to match the current task scope. Additionally, wrap the
assistant_system.start call in a try-except block to catch and handle potential
errors gracefully, preventing unhandled exceptions during execution.
User description
An AI assistant for e-commerce shoppers that provides product comparisons, reviews, pricing insights, and personalized recommendations.
PR Type
Enhancement
Description
Add E-commerce Shopping Assistant Jupyter notebook
Implement AI agent for product comparison and recommendations
Include interactive example for wireless earbuds search
Provide structured output with pros, cons, and pricing
Changes walkthrough 📝
E_commerce_Shopping_Assistant.ipynb
E-commerce Shopping Assistant notebook implementationexamples/cookbooks/E_commerce_Shopping_Assistant.ipynb
Summary by CodeRabbit