| --- |
| title: Transcript Analysis |
| emoji: 📝 |
| colorFrom: blue |
| colorTo: green |
| sdk: docker |
| app_port: 7860 |
| pinned: false |
| --- |
| |
| # ml-tech-assessment |
|
|
| ## Environment Setup |
|
|
| ### Using Conda (Recommended) |
|
|
| 1. Install Conda if you haven't already: |
| - Download and install [Miniconda](https://docs.conda.io/en/latest/miniconda.html) or [Anaconda](https://www.anaconda.com/products/distribution) |
|
|
| 2. Create and activate a new conda environment: |
| ```bash |
| conda create -n ml-assessment python=3.12 |
| conda activate ml-assessment |
| ``` |
|
|
| ## Installing Poetry and Dependencies |
|
|
| 1. Install Poetry using pip: |
| ```bash |
| pip install poetry |
| ``` |
|
|
| 2. Install project dependencies: |
| ```bash |
| poetry install |
| ``` |
|
|
| ## Environment Variables |
|
|
| 1. Create a `.env` file in the root directory of the project |
| 2. Add the OpenAI API key and optional model: |
|
|
| ```env |
| OPENAI_API_KEY=your-openai-api-key |
| OPENAI_MODEL=gpt-4o-2024-08-06 |
| ``` |
|
|
| ## Running Tests |
|
|
| To run the tests, make sure you have: |
| 1. Activated your virtual environment |
| 2. Installed all dependencies using Poetry |
| 3. Created and populated the `.env` file |
|
|
| Then run: |
| ```bash |
| pytest |
| ``` |
|
|
| For more detailed test output: |
| ```bash |
| pytest -v |
| ``` |
|
|
| For test coverage report: |
| ```bash |
| pytest --cov |
| ``` |
|
|
| ## Running the API |
|
|
| Start the FastAPI application with: |
|
|
| ```bash |
| poetry run uvicorn app.main:app --reload |
| ``` |
|
|
| If Poetry is not installed globally but dependencies are already installed in the local virtual environment, run: |
|
|
| ```bash |
| ./.venv/bin/uvicorn app.main:app --reload |
| ``` |
|
|
| Swagger documentation is available at: |
|
|
| ```text |
| http://127.0.0.1:8000/docs |
| ``` |
|
|
| The Gradio frontend is available at: |
|
|
| ```text |
| http://127.0.0.1:8000/ |
| ``` |
|
|
| Analyze one transcript: |
|
|
| ```bash |
| curl -G "http://127.0.0.1:8000/analyses" \ |
| --data-urlencode "transcript=Discuss the launch plan and assign next steps." |
| ``` |
|
|
| Retrieve a stored analysis: |
|
|
| ```bash |
| curl "http://127.0.0.1:8000/analyses/<analysis-id>" |
| ``` |
|
|
| Analyze multiple transcripts concurrently: |
|
|
| ```bash |
| curl -X POST "http://127.0.0.1:8000/analyses/batch" \ |
| -H "Content-Type: application/json" \ |
| -d '{"transcripts":["Discuss launch risks.","Review onboarding plan."]}' |
| ``` |
|
|
| Analysis results are stored in memory, so they reset when the API process restarts. |
|
|
| ## OpenAI Adapter Integration Test |
|
|
| The live OpenAI adapter test is skipped by default so local test runs do not require network access or credentials. To run it explicitly: |
|
|
| ```bash |
| RUN_OPENAI_INTEGRATION_TESTS=1 poetry run pytest tests/adapters/test_openai.py |
| ``` |
|
|
