Add Gradio UI for Airbnb Booking Assistant#434
Conversation
- Introduced a new Gradio interface in `airbnb.mdx` and `ui.py` for searching and booking apartments on Airbnb. - Implemented the `search_airbnb` function to handle user queries and display results. - Enhanced user experience with a clear input prompt and structured output format.
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Caution Review failedThe pull request is closed. WalkthroughThe changes add a new Airbnb search feature using Gradio. Both the documentation and a new source module now define a Changes
Sequence Diagram(s)sequenceDiagram
participant U as User
participant G as Gradio Interface
participant F as search_airbnb Function
participant A as Agent
U->>G: Enter search query
G->>F: Call search_airbnb(query)
F->>A: Initialize Agent with Airbnb instructions
A-->>F: Return formatted results
F->>G: Provide output (Markdown format)
G->>U: Display Airbnb search results
Poem
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Hello @MervinPraison, 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!
Summary of Changes
This pull request introduces a Gradio UI for an Airbnb booking assistant. It adds a new interface in airbnb.mdx and ui.py that allows users to search and book apartments on Airbnb using a natural language query. The search_airbnb function is implemented to handle user input and display the search results in a markdown format.
Highlights
- New UI: Introduces a Gradio UI for searching and booking apartments on Airbnb.
- Function Implementation: Implements the
search_airbnbfunction to process user queries and display results. - Enhanced UX: Enhances user experience with a clear input prompt and structured output format.
Changelog
- docs/mcp/airbnb.mdx
- Added a Gradio UI section with a Python code snippet to demonstrate the Airbnb booking assistant.
- The UI includes a text input for user queries and a markdown output to display search results.
- The code uses the
praisonaiagentslibrary for agent and MCP functionalities andgradiofor the UI.
- src/praisonai-agents/ui.py
- Created a new file
ui.pycontaining the Gradio UI implementation for the Airbnb booking assistant. - The file includes the
search_airbnbfunction and the Gradio interface setup. - It uses the
AgentandMCPclasses from thepraisonaiagentslibrary and thegradiolibrary for the UI.
- Created a new file
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A user's wish, a booking's quest,
Gradio's UI, puts code to the test.
With agents smart, and queries clear,
Airbnb results, banish all fear.
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Code Review
This pull request introduces a Gradio UI for an Airbnb booking assistant, which is a great addition to the project. The code is well-structured and easy to understand. However, there are a few areas that could be improved to enhance maintainability and user experience.
Summary of Findings
- Error Handling: The code lacks explicit error handling. Consider adding error handling to gracefully manage potential issues during agent initialization or API calls.
- Configuration: The LLM and tool configurations are hardcoded. Consider making these configurable via environment variables or a configuration file.
- Code Duplication: The Gradio UI code is duplicated in
airbnb.mdxandui.py. Consider creating a reusable function or module to avoid duplication.
Merge Readiness
The pull request introduces a valuable feature, but it's not quite ready for merging. Addressing the error handling, configuration, and code duplication issues would significantly improve the code's quality and maintainability. I am unable to approve this pull request, and recommend that the author address the above points before merging.
| from praisonaiagents import Agent, MCP | ||
| import gradio as gr | ||
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| def search_airbnb(query): | ||
| agent = Agent( | ||
| instructions="You help book apartments on Airbnb.", | ||
| llm="gpt-4o-mini", | ||
| tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt") | ||
| ) | ||
| result = agent.start(query) | ||
| return f"## Airbnb Search Results\n\n{result}" | ||
|
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| demo = gr.Interface( | ||
| fn=search_airbnb, | ||
| inputs=gr.Textbox(placeholder="I want to book an apartment in Paris for 2 nights..."), | ||
| outputs=gr.Markdown(), | ||
| title="Airbnb Booking Assistant", | ||
| description="Enter your booking requirements below:" | ||
| ) | ||
|
|
||
| if __name__ == "__main__": | ||
| demo.launch() No newline at end of file |
There was a problem hiding this comment.
The Gradio UI code is duplicated in airbnb.mdx and ui.py. Consider creating a reusable function or module to avoid duplication and improve maintainability. You can define the search_airbnb function and Gradio interface in a separate module and import it into both files.
# In a new file, e.g., gradio_app.py:
# def create_gradio_app():
# from praisonaiagents import Agent, MCP
# import gradio as gr
#
# def search_airbnb(query):
# agent = Agent(
# instructions="You help book apartments on Airbnb.",
# llm="gpt-4o-mini",
# tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt")
# )
# result = agent.start(query)
# return f"## Airbnb Search Results\n\n{result}"
#
# demo = gr.Interface(
# fn=search_airbnb,
# inputs=gr.Textbox(placeholder="I want to book an apartment in Paris for 2 nights..."),
# outputs=gr.Markdown(),
# title="Airbnb Booking Assistant",
# description="Enter your booking requirements below:"
# )
# return demo
# if __name__ == "__main__":
# demo = create_gradio_app()
# demo.launch()
# Then, in both airbnb.mdx and ui.py:
# from gradio_app import create_gradio_app
# demo = create_gradio_app()
# if __name__ == "__main__":
# demo.launch()| def search_airbnb(query): | ||
| agent = Agent( | ||
| instructions="You help book apartments on Airbnb.", | ||
| llm="gpt-4o-mini", | ||
| tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt") | ||
| ) | ||
| result = agent.start(query) | ||
| return f"## Airbnb Search Results\n\n{result}" |
There was a problem hiding this comment.
Consider adding error handling to gracefully manage potential issues during agent initialization or API calls. For example, wrap the agent.start(query) call in a try...except block to catch exceptions and display an error message to the user.
try:
result = agent.start(query)
except Exception as e:
return f"## Airbnb Search Results\n\nError: {str(e)}"
return f"## Airbnb Search Results\n\n{result}"
| agent = Agent( | ||
| instructions="You help book apartments on Airbnb.", | ||
| llm="gpt-4o-mini", | ||
| tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt") |
There was a problem hiding this comment.
The LLM and tool configurations are hardcoded. Consider making these configurable via environment variables or a configuration file to allow users to easily change the settings without modifying the code.
llm = os.getenv("LLM_MODEL", "gpt-4o-mini")
tools_command = os.getenv("AIRBNB_MCP_COMMAND", "npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt")
agent = Agent(
instructions="You help book apartments on Airbnb.",
llm=llm,
tools=MCP(tools_command)
)
| def search_airbnb(query): | ||
| agent = Agent( | ||
| instructions="You help book apartments on Airbnb.", | ||
| llm="gpt-4o-mini", | ||
| tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt") | ||
| ) | ||
| result = agent.start(query) | ||
| return f"## Airbnb Search Results\n\n{result}" |
There was a problem hiding this comment.
Consider adding error handling to gracefully manage potential issues during agent initialization or API calls. For example, wrap the agent.start(query) call in a try...except block to catch exceptions and display an error message to the user.
try:
result = agent.start(query)
except Exception as e:
return f"## Airbnb Search Results\n\nError: {str(e)}"
return f"## Airbnb Search Results\n\n{result}"| agent = Agent( | ||
| instructions="You help book apartments on Airbnb.", | ||
| llm="gpt-4o-mini", | ||
| tools=MCP("npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt") |
There was a problem hiding this comment.
The LLM and tool configurations are hardcoded. Consider making these configurable via environment variables or a configuration file to allow users to easily change the settings without modifying the code.
llm = os.getenv("LLM_MODEL", "gpt-4o-mini")
tools_command = os.getenv("AIRBNB_MCP_COMMAND", "npx -y @openbnb/mcp-server-airbnb --ignore-robots-txt")
agent = Agent(
instructions="You help book apartments on Airbnb.",
llm=llm,
tools=MCP(tools_command)
)
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Add Gradio UI for Airbnb Booking Assistant
1 participant
airbnb.mdxandui.pyfor searching and booking apartments on Airbnb.search_airbnbfunction to handle user queries and display results.Summary by CodeRabbit