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Outfit Recommendation with Loop Example

This example demonstrates how to use the framework for outfit recommendation tasks with loop functionality. The example code can be found in the examples/step3_outfit_with_loop directory.

   cd examples/step3_outfit_with_loop

Overview

This example implements an interactive outfit recommendation workflow that uses a loop-based approach to refine recommendations based on user feedback. The workflow consists of the following key components:

  1. Initial Image Input

    • OutfitImageInput: Handles the upload and processing of the initial clothing item image
    • Serves as the starting point for the recommendation process

  2. Interactive QA Loop with Weather Integration

    • OutfitQA: Conducts an interactive Q&A session to gather context and preferences
    • Uses web search tool to fetch real-time weather data for the specified location
    • OutfitDecider: Evaluates if sufficient information has been collected based on:
      • User preferences
      • Current weather conditions
    • Uses DoWhileTask to continue the loop until adequate information is gathered
    • Loop terminates when OutfitDecider returns decision=true

  3. Final Recommendation

    • OutfitRecommendation: Generates the final outfit suggestions based on:
      • The initial uploaded image
      • Information collected during the Q&A loop
      • Current weather conditions from web search
      • Other context (occasion, preferences, etc.)

  4. Workflow Flow

    Start -> Image Input -> OutfitQA Loop (QA + Weather Search + Decision) -> Final Recommendation -> End

The workflow leverages Redis for state management and the Conductor server for workflow orchestration. This architecture enables:

  • Image-based outfit recommendations
  • Weather-aware outfit suggestions using real-time data
  • Interactive refinement through structured Q&A
  • Context-aware suggestions incorporating multiple factors
  • Persistent state management across the workflow

Prerequisites

  • Python 3.8+
  • Required packages installed (see requirements.txt)
  • Access to OpenAI API or compatible endpoint
  • Access to Bing API key for web search functionality to search real-time weather information for outfit recommendations (see configs/tools/websearch.yml)
  • Redis server running locally or remotely
  • Conductor server running locally or remotely

Configuration

The container.yaml file is a configuration file that manages dependencies and settings for different components of the system, including Conductor connections, Redis connections, and other service configurations. To set up your configuration:

  1. Generate the container.yaml file:

    python compile_container.py

    This will create a container.yaml file with default settings under examples/step3_outfit_with_loop.

  2. Configure your LLM settings in configs/llms/gpt.yml and configs/llms/text_res.yml:

    • Set your OpenAI API key or compatible endpoint through environment variable or by directly modifying the yml file
    export custom_openai_key="your_openai_api_key"
export custom_openai_endpoint="your_openai_endpoint"
    • Configure other model settings like temperature as needed through environment variable or by directly modifying the yml file

  3. Configure your Bing Search API key in configs/tools/websearch.yml:

    • Set your Bing API key through environment variable or by directly modifying the yml file
    export bing_api_key="your_bing_api_key"

  4. Update settings in the generated container.yaml:

    • Modify Redis connection settings:
      • Set the host, port and credentials for your Redis instance
      • Configure both redis_stream_client and redis_stm_client sections
    • Update the Conductor server URL under conductor_config section
    • Adjust any other component settings as needed

Running the Example

  1. Run the outfit recommendation workflow:

    For terminal/CLI usage:

    python run_cli.py

    For app/GUI usage:

    python run_app.py

Troubleshooting

If you encounter issues:

  • Verify Redis is running and accessible
  • Check your OpenAI API key and Bing API key are valid
  • Ensure all dependencies are installed correctly
  • Review logs for any error messages
  • Confirm Conductor server is running and accessible
  • Check Redis Stream client and Redis STM client configuration

Building the Example

Coming soon! This section will provide detailed instructions for building the step3_outfit_with_loop example step by step.