diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 0000000000000000000000000000000000000000..7566d677dc0c4ad7c9c7bc6a176c6b7186e9c728 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,12 @@ +.git +.gitignore +**/__pycache__ +**/*.pyc +**/.pytest_cache +**/.mypy_cache +**/.ruff_cache +**/node_modules +**/dist +**/.env +**/.env.* +!openenv-polypharmacy/.env.example diff --git a/.gitattributes b/.gitattributes new file mode 100644 index 0000000000000000000000000000000000000000..a6344aac8c09253b3b630fb776ae94478aa0275b --- /dev/null +++ b/.gitattributes @@ -0,0 +1,35 @@ +*.7z filter=lfs diff=lfs merge=lfs -text +*.arrow filter=lfs diff=lfs merge=lfs -text +*.bin filter=lfs diff=lfs merge=lfs -text +*.bz2 filter=lfs diff=lfs merge=lfs -text +*.ckpt filter=lfs diff=lfs merge=lfs -text +*.ftz filter=lfs diff=lfs merge=lfs -text +*.gz filter=lfs diff=lfs merge=lfs -text +*.h5 filter=lfs diff=lfs merge=lfs -text +*.joblib filter=lfs diff=lfs merge=lfs -text +*.lfs.* filter=lfs diff=lfs merge=lfs -text +*.mlmodel filter=lfs diff=lfs merge=lfs -text +*.model filter=lfs diff=lfs merge=lfs -text +*.msgpack filter=lfs diff=lfs merge=lfs -text +*.npy filter=lfs diff=lfs merge=lfs -text +*.npz filter=lfs diff=lfs merge=lfs -text +*.onnx filter=lfs diff=lfs merge=lfs -text +*.ot filter=lfs diff=lfs merge=lfs -text +*.parquet filter=lfs diff=lfs merge=lfs -text +*.pb filter=lfs diff=lfs merge=lfs -text +*.pickle filter=lfs diff=lfs merge=lfs -text +*.pkl filter=lfs diff=lfs merge=lfs -text +*.pt filter=lfs diff=lfs merge=lfs -text +*.pth filter=lfs diff=lfs merge=lfs -text +*.rar filter=lfs diff=lfs merge=lfs -text +*.safetensors filter=lfs diff=lfs merge=lfs -text +saved_model/**/* filter=lfs diff=lfs merge=lfs -text +*.tar.* filter=lfs diff=lfs merge=lfs -text +*.tar filter=lfs diff=lfs merge=lfs -text +*.tflite filter=lfs diff=lfs merge=lfs -text +*.tgz filter=lfs diff=lfs merge=lfs -text +*.wasm filter=lfs diff=lfs merge=lfs -text +*.xz filter=lfs diff=lfs merge=lfs -text +*.zip filter=lfs diff=lfs merge=lfs -text +*.zst filter=lfs diff=lfs merge=lfs -text +*tfevents* filter=lfs diff=lfs merge=lfs -text diff --git a/.gitignore b/.gitignore index 0bb8010f237a644afe235484f689fc21c449cca4..a21ac13278960096fd010e674651b109be6c6cc4 100644 --- a/.gitignore +++ b/.gitignore @@ -1,3 +1,35 @@ +# --- Python --- venv/ +.venv/ +env/ +.env +.env.* +!openenv-polypharmacy/.env.example +*.py[cod] +__pycache__/ +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +.coverage +coverage.xml + +# --- Node / frontend --- +node_modules/ +**/node_modules/ +frontend/dist/ +**/dist/ +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* + +# --- Build / temp --- +*.log +*.tmp +*.swp .DS_Store -__pycache__/ \ No newline at end of file + +# --- Project-specific nested paths --- +openenv-polypharmacy/frontend/node_modules/ +openenv-polypharmacy/frontend/dist/ +openenv-polypharmacy/.pytest_cache/ diff --git a/.gitignore copy b/.gitignore copy new file mode 100644 index 0000000000000000000000000000000000000000..a21ac13278960096fd010e674651b109be6c6cc4 --- /dev/null +++ b/.gitignore copy @@ -0,0 +1,35 @@ +# --- Python --- +venv/ +.venv/ +env/ +.env +.env.* +!openenv-polypharmacy/.env.example +*.py[cod] +__pycache__/ +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +.coverage +coverage.xml + +# --- Node / frontend --- +node_modules/ +**/node_modules/ +frontend/dist/ +**/dist/ +npm-debug.log* +yarn-debug.log* +yarn-error.log* +pnpm-debug.log* + +# --- Build / temp --- +*.log +*.tmp +*.swp +.DS_Store + +# --- Project-specific nested paths --- +openenv-polypharmacy/frontend/node_modules/ +openenv-polypharmacy/frontend/dist/ +openenv-polypharmacy/.pytest_cache/ diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..10f199b9446b1375bce69953826c903f9ed43efe --- /dev/null +++ b/Dockerfile @@ -0,0 +1,39 @@ +FROM node:20-alpine AS frontend-builder +WORKDIR /app/frontend +COPY openenv-polypharmacy/frontend/package*.json ./ +RUN npm ci +COPY openenv-polypharmacy/frontend/ ./ +RUN npm run build + +FROM python:3.11-slim + +RUN apt-get update && \ + apt-get install -y --no-install-recommends build-essential curl && \ + rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +COPY openenv-polypharmacy/backend/requirements.txt /app/backend/requirements.txt +RUN pip install --no-cache-dir -r /app/backend/requirements.txt + +COPY openenv-polypharmacy/backend /app/backend +COPY openenv-polypharmacy/data /app/data +COPY openenv-polypharmacy/scripts /app/scripts +COPY openenv-polypharmacy/openenv.yaml /app/openenv.yaml +COPY openenv-polypharmacy/.env.example /app/.env.example +COPY openenv-polypharmacy/inference.py /app/inference.py + +COPY --from=frontend-builder /app/frontend/dist /app/frontend/dist + +RUN python3 /app/scripts/preprocess_data.py + +ENV PORT=7860 +ENV PYTHONPATH="/app/backend/src:${PYTHONPATH}" +ENV PYTHONUNBUFFERED=1 + +EXPOSE 7860 + +HEALTHCHECK --interval=30s --timeout=3s --start-period=15s --retries=3 \ + CMD curl -f http://localhost:7860/health || exit 1 + +CMD ["sh", "-c", "uvicorn backend.main:app --host 0.0.0.0 --port ${PORT:-7860}"] diff --git a/README.MD b/README.MD new file mode 100644 index 0000000000000000000000000000000000000000..dddbf4047eacd2e74adc50df3b8cf73f80f162f9 --- /dev/null +++ b/README.MD @@ -0,0 +1,245 @@ +# PolypharmacyEnv + +Monorepo for an OpenEnv-compatible medication safety environment with: + +- a FastAPI backend (`backend/`) +- a React frontend (`frontend/`) +- data assets (`data/`) +- utility scripts (`scripts/`) + +--- + +## Repository Structure + +```text +openenv-polypharmacy/ + backend/ + main.py # ASGI entrypoint (uvicorn target) + requirements.txt # Backend dependencies + Dockerfile # Backend container + src/polypharmacy_env/ # Python package source + api/ + app.py # FastAPI/OpenEnv app assembly + server.py # Compatibility import wrapper + routes/agent.py # /agent/suggest route + services/ + groq_agent.py # Groq-based action suggestion logic + env_core.py # OpenEnv environment core + models.py # Action/observation/state models + data_loader.py # CSV loading + ddi_simulator.py # DDI and Beers lookups + rewards.py # Reward shaping + graders.py # Task graders + tasks.py # Task/episode selection + tests/ # Backend tests + frontend/ + src/ # React UI code + package.json + Dockerfile # Frontend container + data/ + lookups/ # drug_metadata.csv, ddi_rules.csv, beers_criteria.csv + processed/ # patients_polypharmacy.csv + scripts/ + preprocess_data.py # Synthetic data generation + dev_backend.sh # Local backend run helper + dev_frontend.sh # Local frontend run helper + run_validation.sh # Tests + baseline validation + docker-compose.yml # Full stack orchestration + openenv.yaml # OpenEnv manifest + inference.py # Optional CLI inference baseline + .env.example # Environment template +``` + +--- + +## What It Does + +The environment simulates elderly polypharmacy review. Agent actions: + +- `query_ddi` +- `propose_intervention` +- `finish_review` + +Supported tasks: + +- `easy_screening` +- `budgeted_screening` +- `complex_tradeoff` + +--- + +## Prerequisites + +- Python 3.10+ +- Node.js 18+ (or 20+ recommended) +- npm +- Docker + Docker Compose (optional, for containerized run) + +--- + +## Environment Setup + +Create `.env`: + +```bash +cp .env.example .env +``` + +Set values: + +- `GROQ_API_KEY=...` (required) +- `GROQ_BASE_URL=https://api.groq.com/openai/v1` (recommended) +- `GROQ_MODEL_NAME=llama-3.3-70b-versatile` (recommended) + +--- + +## Local Run (Recommended During Development) + +### 1) Install dependencies + +Backend: + +```bash +pip install -r backend/requirements.txt +``` + +Frontend: + +```bash +cd frontend +npm install +cd .. +``` + +### 2) Generate/update synthetic data (if needed) + +```bash +python scripts/preprocess_data.py +``` + +### 3) Start services in two terminals + +Terminal A: + +```bash +./scripts/dev_backend.sh +``` + +Terminal B: + +```bash +./scripts/dev_frontend.sh +``` + +### 4) Open app + +- Frontend: [http://localhost:5173](http://localhost:5173) +- Backend health: [http://localhost:7860/health](http://localhost:7860/health) + +--- + +## Docker Run + +Run both services: + +```bash +docker compose up --build +``` + +Stop: + +```bash +docker compose down +``` + +Ports: + +- backend: `7860` +- frontend: `5173` + +--- + +## Hugging Face Spaces Deployment (Docker) + +This repo now includes a **root `Dockerfile`** that builds frontend + backend into one container, so Spaces can host both API and UI together. + +### 1) Create a new Space + +- Go to [Hugging Face Spaces](https://huggingface.co/new-space) +- Choose **Docker** SDK +- Create the Space + +### 2) Add Space secrets/variables + +In Space Settings -> Variables and Secrets: + +- Secret: `GROQ_API_KEY` +- Variable: `GROQ_BASE_URL=https://api.groq.com/openai/v1` +- Variable: `GROQ_MODEL_NAME=llama-3.3-70b-versatile` + +### 3) Push this repository to the Space + +Commit and push all files, including root `Dockerfile`. + +### 4) Verify after build + +- Space root URL loads the React UI +- `/health` returns healthy status +- OpenEnv endpoints are available (`/reset`, `/step`, `/state`, `/schema`) + +Notes: + +- Container reads `PORT` (defaults to `7860`) which is Space-friendly. +- Frontend static assets are served by FastAPI from `frontend/dist`. + +--- + +## API Endpoints + +OpenEnv/health: + +- `POST /reset` +- `POST /step` +- `GET /state` +- `GET /health` +- `GET /schema` +- `WS /ws` (stateful session) + +AI helper: + +- `POST /agent/suggest` + +--- + +## Testing + +Run backend tests: + +```bash +python -m pytest backend/src/polypharmacy_env/tests -v +``` + +Or run validation script: + +```bash +./scripts/run_validation.sh +``` + +--- + +## Notes + +- OpenEnv HTTP reset/step is stateless; multi-step episode continuity should use websocket (`/ws`). +- The frontend uses websocket for episode continuity and HTTP for AI suggestion. +- AI behavior includes rule-based guardrails to avoid repetitive low-value loops. + +--- + +## Troubleshooting + +- `ModuleNotFoundError: polypharmacy_env` + - Start backend using `./scripts/dev_backend.sh` from repo root. +- `/agent/suggest` fails + - Check `.env` keys and restart backend. +- UI state looks stale + - Hard refresh browser and click `Reset Episode`. diff --git a/openenv-polypharmacy/.dockerignore b/openenv-polypharmacy/.dockerignore new file mode 100644 index 0000000000000000000000000000000000000000..5007867e3a3b2c5514c4ff5bb18588b36951901f --- /dev/null +++ b/openenv-polypharmacy/.dockerignore @@ -0,0 +1,8 @@ +.git +.gitignore +**/__pycache__/ +**/.pytest_cache/ +**/.DS_Store +.env +frontend/node_modules +frontend/dist diff --git a/openenv-polypharmacy/.env.example b/openenv-polypharmacy/.env.example new file mode 100644 index 0000000000000000000000000000000000000000..1ef8a70cdf5d21640d8898e26a82e60734b583ff --- /dev/null +++ b/openenv-polypharmacy/.env.example @@ -0,0 +1,3 @@ +GROQ_API_KEY=your_groq_api_key_here +GROQ_BASE_URL=https://api.groq.com/openai/v1 +GROQ_MODEL_NAME=llama-3.3-70b-versatile diff --git a/openenv-polypharmacy/Dockerfile b/openenv-polypharmacy/Dockerfile index 8ebec352b765d69a459db95f91fd4a07427a979f..68b69d986a780501f6c9461410b2add26413473e 100644 --- a/openenv-polypharmacy/Dockerfile +++ b/openenv-polypharmacy/Dockerfile @@ -1,30 +1,39 @@ +FROM node:20-alpine AS frontend-builder +WORKDIR /app/frontend +COPY frontend/package*.json ./ +RUN npm ci +COPY frontend/ ./ +RUN npm run build + FROM python:3.11-slim -# System deps RUN apt-get update && \ apt-get install -y --no-install-recommends build-essential curl && \ rm -rf /var/lib/apt/lists/* WORKDIR /app -# Install Python deps first (layer caching) -COPY requirements.txt . -RUN pip install --no-cache-dir -r requirements.txt +COPY backend/requirements.txt /app/backend/requirements.txt +RUN pip install --no-cache-dir -r /app/backend/requirements.txt + +COPY backend /app/backend +COPY data /app/data +COPY scripts /app/scripts +COPY openenv.yaml /app/openenv.yaml +COPY .env.example /app/.env.example +COPY inference.py /app/inference.py -# Copy project -COPY . . +COPY --from=frontend-builder /app/frontend/dist /app/frontend/dist -# Generate data if not present -RUN python3 scripts/preprocess_data.py +RUN python3 /app/scripts/preprocess_data.py -# Environment ENV PORT=7860 -ENV PYTHONPATH="/app/src:${PYTHONPATH}" +ENV PYTHONPATH="/app/backend/src:${PYTHONPATH}" ENV PYTHONUNBUFFERED=1 EXPOSE 7860 -HEALTHCHECK --interval=30s --timeout=3s --start-period=10s --retries=3 \ +HEALTHCHECK --interval=30s --timeout=3s --start-period=15s --retries=3 \ CMD curl -f http://localhost:7860/health || exit 1 -CMD ["uvicorn", "polypharmacy_env.api.server:app", "--host", "0.0.0.0", "--port", "7860"] +CMD ["sh", "-c", "uvicorn backend.main:app --host 0.0.0.0 --port ${PORT:-7860}"] diff --git a/openenv-polypharmacy/PROMPT.md b/openenv-polypharmacy/PROMPT.md deleted file mode 100644 index d7d5481b1ba6a83c8590ebcec024b911f5800982..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/PROMPT.md +++ /dev/null @@ -1,571 +0,0 @@ -You are an expert Python backend, ML, and infrastructure engineer. -Your task is to implement a complete, production-ready OpenEnv environment called **PolypharmacyEnv** for training and evaluating agentic RL policies that act as an "elderly polypharmacy safety agent" (clinical pharmacist assistant). - -The deliverable MUST satisfy all of the following: -- Fully compliant with the OpenEnv spec (typed models, `step()` / `reset()` / `state()`, `openenv.yaml`, HTTP server, Dockerfile). -- Simulates a realistic healthcare workflow around elderly polypharmacy and dangerous drug combinations. -- Defines at least **3 tasks** (easy → medium → hard) with deterministic agent graders producing scores in (0.0, 1.0). -- Provides shaped rewards over the trajectory (not just sparse terminal rewards). -- Includes a baseline LLM-based inference script `inference.py` in the repo root, following the evaluation requirements: - - Uses the OpenAI Python client. - - Reads `OPENAI_API_KEY`, `API_BASE_URL`, `MODEL_NAME`, and `HF_TOKEN` from the environment. - - Emits structured stdout logs in the exact `[START]`, `[STEP]`, `[END]` format from the OpenEnv sample inference script. -- Is containerized and deployable as a **Hugging Face Space** tagged with `openenv` that responds to OpenEnv-style `reset` / `step` / `state` HTTP calls. - -Implement everything described below. - -================================================= -1. Repository and folder structure -================================================= - -Create a Python package repository with this structure (names are important unless clearly labeled as examples): - -- `openenv-polypharmacy/` - - `openenv.yaml` - - `README.md` - - `requirements.txt` - - `Dockerfile` - - `inference.py` # baseline LLM agent per spec - - `pyproject.toml` or `setup.cfg` (optional but recommended) - - `src/` - - `polypharmacy_env/` - - `__init__.py` - - `config.py` - - `models.py` # Action, Observation, State, helper models - - `env_core.py` # PolypharmacyEnv implementation - - `tasks.py` # task setup utilities - - `graders.py` # deterministic graders for each task - - `rewards.py` # reward shaping logic - - `data_loader.py` # load/preprocess patient and lookup data - - `ddi_simulator.py` # local DDI / guideline simulator - - `api/` - - `__init__.py` - - `schemas.py` # HTTP request/response schemas - - `server.py` # FastAPI app exposing OpenEnv endpoints - - `baselines/` - - `__init__.py` - - `heuristic_agent.py` # simple rule-based baseline agent - - `random_agent.py` # trivial random baseline (optional) - - `tests/` - - `__init__.py` - - `test_env_core.py` - - `test_api.py` - - `data/` - - `raw/` # placeholder for real/synthetic source data - - `processed/` - - `lookups/` - - `ddi_rules.csv` - - `beers_criteria.csv` - - `drug_metadata.csv` - - `scripts/` - - `preprocess_data.py` - - `run_validation.sh` # optional; runs OpenEnv validator, tests, etc. - -Use Python 3.10+ with full type hints, and keep the code black/isort-compatible. - -================================================= -2. Domain, data, and clinical abstraction -================================================= - -2.1. Core scenario - -Model an elderly patient (age ≥ 65) with: -- Demographics: age, sex. -- Comorbidities: e.g., hypertension, diabetes, heart failure, CKD, dementia. -- Basic labs: kidney function (eGFR category), liver function category. -- A current medication list (polypharmacy, e.g., 3–15 drugs depending on task). - -Each **episode** is one medication-review session where the agent: -- Observes patient info and current meds. -- Optionally **queries** a DDI/guideline tool for specific drug pairs. -- Proposes **interventions**: - - `stop`: discontinue a drug. - - `dose_reduce`: lower dose of a drug. - - `substitute`: swap to a safer alternative. - - `add_monitoring`: keep the drug but flag extra monitoring. -- Calls `finish_review` when it decides the regimen is acceptable or budgets are exhausted. - -No external PHI, EHRs, or online APIs: all data is **synthetic** or de-identified and local to the container (CSV files). - -2.2. Data files and CSV schemas - -Implement local CSVs under `data/lookups/`: - -**`drug_metadata.csv`** -- `drug_id` (string; unique key) -- `generic_name` (string) -- `atc_class` (string) -- `is_high_risk_elderly` (0/1) -- `default_dose_mg` (float) -- `min_dose_mg` (float) -- `max_dose_mg` (float) - -**`beers_criteria.csv`** -- `drug_id` (string) -- `criterion_type` (enum string: `avoid`, `caution`, `dose_adjust`, `avoid_in_condition`) -- `condition` (nullable string; e.g., `CKD`, `dementia`) -- `rationale` (brief text) - -**`ddi_rules.csv`** -- `drug_id_1` (string; normalized so `drug_id_1 < drug_id_2` lexicographically) -- `drug_id_2` (string) -- `severity` (enum string: `mild`, `moderate`, `severe`) -- `mechanism` (short text) -- `recommendation` (enum string: `avoid_combination`, `monitor_closely`, `dose_adjust`, `no_action`) -- `base_risk_score` (float in [0.0, 1.0]) - -Implement a synthetic patient-episode dataset under `data/processed/`: - -**`patients_polypharmacy.csv`** -- `episode_id` (string) -- `age` (int) -- `sex` (enum: `M`, `F`, `O`) -- `conditions` (semicolon-separated; e.g., `HTN;DM;CKD`) -- `eGFR_category` (enum: `normal`, `mild`, `moderate`, `severe`) -- `liver_function_category` (enum: `normal`, `impaired`) -- `medication_ids` (semicolon-separated list of `drug_id`) -- `baseline_risk_score` (float in [0.0, 1.0]) - -2.3. Preprocessing script - -In `scripts/preprocess_data.py`: -- If real data is not provided, procedurally generate synthetic but plausible data using: - - Random combinations of conditions and drugs constrained by simple rules (e.g., CKD + renally-cleared drugs). - - Controlled distribution of high-risk DDIs and Beers violations. -- Explicitly tag episodes as easy/medium/hard (e.g., via number of drugs, number/severity of DDIs, and number of Beers issues). -- Save `patients_polypharmacy.csv` ready for the environment to consume. - -================================================= -3. OpenEnv models and environment implementation -================================================= - -3.1. Models - -In `models.py`, define dataclasses or Pydantic models that extend the appropriate OpenEnv base types (`Action`, `Observation`, `State`) and are JSON-compatible. - -Auxiliary models: - -**`MedicationEntry`** -- `drug_id: str` -- `generic_name: str` -- `atc_class: str` -- `dose_mg: float` -- `frequency: str` # e.g., `qd`, `bid` -- `route: str` # e.g., `po` -- `is_high_risk_elderly: bool` -- `beers_flags: list[str]` # e.g., `["avoid", "dose_adjust_CKD"]` - -**`InteractionQueryRecord`** -- `drug_id_1: str` -- `drug_id_2: str` -- `severity: str | None` -- `recommendation: str | None` -- `risk_score: float | None` -- `step_index: int` - -**`InterventionRecord`** -- `target_drug_id: str` -- `action_type: Literal["stop", "dose_reduce", "substitute", "add_monitoring"]` -- `proposed_new_drug_id: str | None` -- `rationale: str` -- `step_index: int` - -Core wire models: - -**`PolypharmacyObservation`** (extends OpenEnv `Observation`) -- `episode_id: str` -- `task_id: Literal["easy_screening", "budgeted_screening", "complex_tradeoff"]` -- `age: int` -- `sex: str` -- `conditions: list[str]` -- `eGFR_category: str` -- `liver_function_category: str` -- `current_medications: list[MedicationEntry]` -- `interaction_queries: list[InteractionQueryRecord]` -- `interventions: list[InterventionRecord]` -- `step_index: int` -- `remaining_query_budget: int` -- `remaining_intervention_budget: int` -- `shaped_reward: float` # reward from last step -- `done: bool` - -**`PolypharmacyAction`** (extends OpenEnv `Action`) -- `action_type: Literal["query_ddi", "propose_intervention", "finish_review"]` -- `drug_id_1: str | None` # for DDI queries or some interventions -- `drug_id_2: str | None` # for DDI queries -- `target_drug_id: str | None` # for interventions -- `intervention_type: Literal["stop", "dose_reduce", "substitute", "add_monitoring", "none"] | None` -- `proposed_new_drug_id: str | None` -- `rationale: str | None` - -**`PolypharmacyState`** (extends OpenEnv `State`) -- `episode_id: str` -- `task_id: str` -- `step_count: int` -- `max_steps: int` -- `num_query_actions: int` -- `num_interventions: int` - -3.2. Environment core - -In `env_core.py`, implement `PolypharmacyEnv` extending the appropriate OpenEnv environment base class. It must implement: - -**`reset(task_id: str | None = None) -> PolypharmacyObservation`** -- If `task_id` is `None`, default to medium (`budgeted_screening`). -- Sample an episode from `patients_polypharmacy.csv` filtered by difficulty. -- Initialize: - - `episode_id` - - `step_count = 0` - - task-specific budgets (query, interventions, max_steps) - - baseline regime and risk - - empty `interaction_queries` and `interventions` -- Return the initial `PolypharmacyObservation` with: - - `step_index = 0` - - `shaped_reward = 0.0` - - `done = False` - -**`step(action: PolypharmacyAction) -> dict`** -- Validate the action; if invalid: - - Apply a negative reward. - - Do not modify regimen, but log error in `info`. -- If `action_type == "query_ddi"`: - - If query budget exhausted, apply penalty and do not query. - - Else: - - Use `ddi_simulator.lookup_ddi(drug_id_1, drug_id_2)` to get severity, recommendation, base_risk_score. - - Append an `InteractionQueryRecord`. - - Apply a small negative reward for query cost. -- If `action_type == "propose_intervention"`: - - If intervention budget exhausted, apply penalty and ignore change. - - Else: - - Update `current_medications` according to `intervention_type`: - - `stop`: remove medication. - - `dose_reduce`: adjust dose downward within [min_dose_mg, default_dose_mg]. - - `substitute`: replace with a safer alternative from same `atc_class`. - - `add_monitoring`: keep drug but tag in internal state. - - Append an `InterventionRecord`. - - Recompute current regimen risk using the risk model (see 3.3). - - Compute shaped reward = (previous_risk - new_risk) - small intervention cost. -- If `action_type == "finish_review"`: - - Mark `done = True`. - - Call the task’s grader to get episode-level score in [0.0, 1.0]. - - Add this as a terminal bonus to the current step reward. - -- In all cases: - - Increment `step_count`. - - Check `max_steps`; if exceeded, auto-terminate: - - `done = True` - - apply time-out penalty - - call grader with current trajectory for a final score if appropriate. - - Construct next `PolypharmacyObservation` with updated fields. - - Return a dict: - - `observation`: `PolypharmacyObservation` - - `reward`: float shaped reward for this step - - `done`: bool - - `info`: dict with fields like `current_risk`, `baseline_risk`, `grader_score_if_terminal`, and debug flags. - -**`state` property** -- Returns `PolypharmacyState` reflecting the current internal state. - -3.3. DDI simulator and risk model - -In `ddi_simulator.py`: -- Load `ddi_rules.csv` once via `data_loader`. -- Implement `lookup_ddi(drug_id_1, drug_id_2) -> tuple[severity, recommendation, base_risk_score]`: - - Normalize the pair ordering. - - Look up row; if missing, return: - - severity = `"none"` - - recommendation = `"no_action"` - - base_risk_score = 0.0 - -In `rewards.py` (or a dedicated module), implement: -- `compute_regimen_risk(current_drug_ids, patient_context, ddi_rules, beers_rules, drug_metadata) -> float` - - Aggregate contributions from: - - Beers violations (weighted by `criterion_type` and relevant conditions). - - DDI base risk scores for all present drug pairs. - - High-risk elderly drugs. - - Normalize and clip to [0.0, 1.0]. - -Use this function to compute: -- `baseline_risk` at episode start. -- Risk after each intervention step. - -Also implement: -- `compute_shaped_reward(previous_risk, new_risk, action, context, partial_metrics) -> float` - - Positive component: `previous_risk - new_risk`. - - Negative components: per-query cost, per-intervention cost, invalid-action penalty, time-out penalty. - -================================================= -4. Tasks and graders (3 difficulty levels) -================================================= - -Define three task IDs and semantics in `tasks.py` and `graders.py`: - -Task IDs: -- `easy_screening` -- `budgeted_screening` -- `complex_tradeoff` - -4.1. `easy_screening` (easy) - -- Small regimen: 3–5 drugs. -- Exactly one **severe** DDI pair and possibly one simple Beers violation. -- Budgets: - - query_budget ≈ 4 - - intervention_budget ≈ 2 - - max_steps ≈ 10 - -Grader: -- Input: full trajectory, baseline risk, final risk, list of interventions. -- Compute: - - `risk_reduction = max(0.0, baseline_risk - final_risk) / max(baseline_risk, ε)` (normalized). - - `targeted_intervention_flag = 1.0` if at least one intervention affects one of the drugs in the known severe DDI pair, else 0.0. -- Score: - - `score = 0.5 * risk_reduction + 0.5 * targeted_intervention_flag` - - Clip to [0.0, 1.0]. - -4.2. `budgeted_screening` (medium) - -- Medium regimen: 6–10 drugs. -- Multiple DDIs (mild/moderate/severe) and multiple Beers issues. -- Budgets: - - query_budget ≈ 8 - - intervention_budget ≈ 3 - - max_steps ≈ 20 - -Grader: -- Compute: - - `risk_reduction_score` as normalized risk drop. - - `intervention_precision_score` = fraction of interventions that actually reduce risk or fix guideline violations. - - `query_efficiency_score` = (number of severe/moderate DDIs discovered) / (number of queries used), normalized. -- Weighted score, for example: - - `score = 0.5 * risk_reduction_score + 0.3 * intervention_precision_score + 0.2 * query_efficiency_score` - - Clip to [0.0, 1.0]. - -4.3. `complex_tradeoff` (hard) - -- Larger regimen: 10–15 drugs. -- Some drugs are **clinically critical** (e.g., anticoagulants, insulin analogues) and encoded as such in `drug_metadata` or a small internal map. -- Episodes contain: - - multiple DDIs and Beers issues, including ones involving critical drugs. - - safer substitutes for some risky drugs. - -Budgets: -- query_budget ≈ 12 -- intervention_budget ≈ 5 -- max_steps ≈ 30 - -Grader adds a **regimen disruption penalty** component: -- Metrics: - - `risk_reduction_score` (as above). - - `critical_drug_penalty` = penalty if a critical drug is stopped without substitution to another suitable agent. - - `total_drug_changes` = number of drugs stopped or substituted. - - `regimen_disruption_penalty` derived from `total_drug_changes` and `critical_drug_penalty`. - -Example scoring: -- `base = risk_reduction_score` -- `penalty = α * regimen_disruption_penalty` -- `score = clamp(base - penalty, 0.0, 1.0)` - -4.4. Reward shaping - -In `rewards.py`, define a consistent shaping scheme: -- On each query: - - Small negative reward (e.g., −0.01) plus any small bonus if it discovers a severe DDI, if desired. -- On each intervention: - - Reward ≈ (previous_risk - new_risk) − small intervention cost. -- On invalid actions: - - Larger negative reward (e.g., −0.1) and no state change. -- On `finish_review`: - - Add the task-level `score` ∈ [0.0, 1.0] from the corresponding grader to that step’s shaped reward. - -Ensure the sum of step rewards per episode remains in a reasonable numeric range (e.g., roughly -5 to +5) while still allowing meaningful differentiation by graders. - -================================================= -5. HTTP API server and openenv.yaml -================================================= - -5.1. HTTP server (FastAPI) - -In `api/server.py`: -- Implement a FastAPI app that maintains a `PolypharmacyEnv` instance (or a multiplexing scheme if needed). -- Endpoints: - - `POST /reset`: - - Request body: may include `task_id` (string). - - Response: serialized `PolypharmacyObservation`. - - `POST /step`: - - Request body: serialized `PolypharmacyAction`. - - Response: dict with: - - `observation`: `PolypharmacyObservation` - - `reward`: float - - `done`: bool - - `info`: dict - - `GET /state`: - - Response: `PolypharmacyState`. - -Provide a module-level `app = FastAPI(...)` object for use with uvicorn and Hugging Face Spaces. Ensure the JSON schema is consistent with OpenEnv clients (simple, flat JSON for observation/action/state). - -5.2. `openenv.yaml` - -At repo root, define `openenv.yaml` consistent with the latest OpenEnv spec. At minimum, include: -- `name`: `polypharmacy_env` -- `version`: e.g., `0.1.0` -- `description`: human-readable description. -- `author`: your details. -- `tags`: e.g., `["healthcare", "polypharmacy", "openenv"]` -- `tasks`: - - One entry per task: - - `id`: `"easy_screening"` / `"budgeted_screening"` / `"complex_tradeoff"` - - `description`: one-line description - - `difficulty`: `"easy"`, `"medium"`, `"hard"` - -Ensure `openenv validate` (or equivalent validator) passes once implemented. - -================================================= -6. Baseline heuristic (non-LLM) agent -================================================= - -In `baselines/heuristic_agent.py`, implement a simple, deterministic baseline agent that: - -For each episode: -- Iterates through all unordered medication pairs within query budget: - - Calls `query_ddi` via the environment for each pair until the query budget is exhausted or all pairs are examined. - - Records severe and moderate interactions. -- After querying: - - For each severe DDI pair: - - Try `substitute` one of the drugs using `drug_metadata`: - - Prefer substitute within same `atc_class` that: - - is not marked high-risk elderly. - - does not participate in known severe DDIs with the rest of the regimen. - - If no substitute exists, propose `stop` for the higher-risk drug. - - Respect intervention budget limits. -- Finally, call `finish_review`. - -This baseline should be callable as a simple Python function that interacts with `PolypharmacyEnv` directly (without HTTP). - -================================================= -7. Baseline LLM inference script (inference.py) -================================================= - -At repo root, create `inference.py` that: - -7.1. Uses the OpenAI Python client - -- Import and configure the official OpenAI Python client. -- Read environment variables: - - `OPENAI_API_KEY` (required). - - `API_BASE_URL` (base URL for LLM; default to OpenAI standard if not set). - - `MODEL_NAME` (e.g., `gpt-4.1` or similar). - - `HF_TOKEN` (if needed for HF auth; do not hardcode). -- Read `POLYPHARMACY_ENV_URL` (or similar) for the environment’s HTTP base URL. - -7.2. Implements the required logging format - -- For each **run** across all tasks: - - Emit a `[START]` line with a JSON payload exactly matching the evaluation specification: - - Fields such as `run_id`, `task_id`, `model`, etc., in the same order and naming as the sample OpenEnv inference script. -- For each **step** in an episode: - - Emit a `[STEP]` line with JSON fields including: - - `run_id` - - `task_id` - - `episode_id` - - `step_index` - - `observation_summary` (brief, machine-readable summary) - - `action_payload` (the action sent to the env) - - `reward` - - `done` -- After finishing an episode for a task: - - Emit an `[END]` line summarizing: - - `run_id` - - `task_id` - - per-episode statistics (e.g., total reward, grader score from last step’s `info`). -- The stdout format MUST follow the sample exactly: - - Same tags: `[START]`, `[STEP]`, `[END]`. - - Same JSON field names and ordering as the provided reference. - - No extra prints except these structured logs (and necessary error messages to stderr). - -7.3. LLM agent loop - -- For each task (`easy_screening`, `budgeted_screening`, `complex_tradeoff`): - - Run a fixed small number of episodes (e.g., 5–10 per task) for baseline scoring. - - For each episode: - - Call `/reset` with the task id. - - At each step: - - Summarize the observation into a concise prompt for the LLM: - - Include age, sex, conditions, high-risk flags, budgets, and a compressed view of meds and previous actions. - - Ask the model to output a **strict JSON** representing `PolypharmacyAction` fields. - - Parse and validate the JSON; if invalid, fall back to a safe default (e.g., `finish_review` or a no-op) and penalize in evaluation. - - Send this action to `/step` and log `[STEP]`. - - End when `done=True` or max_steps is reached. -- At the end, print aggregate scores per task and overall. - -Make sure runtime < 20 minutes and that the script can run within 2 vCPUs and 8 GB RAM. - -================================================= -8. Dockerfile and Hugging Face Space -================================================= - -8.1. Dockerfile - -Create a `Dockerfile` that: -- Starts from a slim Python image (e.g., `python:3.11-slim`). -- Installs system dependencies as needed (e.g., `build-essential`, `curl`). -- Copies the project into the container. -- Installs Python dependencies from `requirements.txt`. -- Sets appropriate environment variables for the app (e.g., `PORT=7860`). -- Exposes port 7860. -- Uses a `CMD` or `ENTRYPOINT` that runs the FastAPI server, for example: - - `uvicorn polypharmacy_env.api.server:app --host 0.0.0.0 --port 7860` - -8.2. Hugging Face Space - -Ensure the repository is ready to be used as a Hugging Face Space: -- Space type: `docker`. -- Tag: `openenv`. -- On container start, the server must listen on the correct port and respond to: - - `POST /reset` - - `POST /step` - - `GET /state` -- The environment must start cleanly with `docker build` + `docker run` locally. - -================================================= -9. README and documentation -================================================= - -In `README.md`, include: - -- **Environment description & motivation**: - - What PolypharmacyEnv simulates. - - Why elderly polypharmacy safety matters. -- **Action and observation spaces**: - - Describe `PolypharmacyAction`, `PolypharmacyObservation`, and `PolypharmacyState` fields and semantics. -- **Task descriptions**: - - `easy_screening`, `budgeted_screening`, `complex_tradeoff`, their difficulty and goals. -- **Reward structure**: - - Summarize shaping and terminal rewards. -- **Setup & usage**: - - How to install dependencies. - - How to run the API server locally (uvicorn command). - - How to run the heuristic baseline. - - How to run `inference.py` with environment variables. -- **Baseline scores**: - - Document reproducible baseline scores for each task (heuristic agent, and LLM baseline if available). - -================================================= -10. Validation and quality gates -================================================= - -- Ensure: - - `openenv.yaml` and the HTTP server pass the OpenEnv validation script. - - `docker build` and `docker run` work without errors. - - `inference.py` completes under 20 minutes, within 2 vCPUs / 8 GB RAM. - - All graders: - - Are deterministic. - - Return scores strictly in [0.0, 1.0]. - - No grader returns a constant score irrespective of behavior. - -Aim for clean, well-structured, well-documented code with clear separation of concerns between: -- Data loading, -- Environment state & dynamics, -- Reward/grade logic, -- HTTP serving, -- Baseline agents and inference. \ No newline at end of file diff --git a/openenv-polypharmacy/README.md b/openenv-polypharmacy/README.md deleted file mode 100644 index 5707521073ad5ade9a331af60d2c4ad0695e1c94..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/README.md +++ /dev/null @@ -1,184 +0,0 @@ -# PolypharmacyEnv - -An [OpenEnv](https://github.com/meta-pytorch/OpenEnv)-compliant reinforcement-learning environment that simulates **elderly polypharmacy medication review**. An RL agent acts as a clinical pharmacist assistant, identifying dangerous drug-drug interactions (DDIs), Beers-criteria violations, and proposing safe interventions. - ---- - -## Motivation - -Polypharmacy (concurrent use of multiple medications) is extremely common in elderly patients (age >= 65) and carries significant risks: - -- **Drug-drug interactions** can cause adverse events, hospitalisation, and death. -- **Beers-criteria violations** flag medications that are inappropriate or require dose adjustments in older adults. -- Stopping critical medications (anticoagulants, insulin) without proper substitution can be equally dangerous. - -This environment lets RL and LLM-based agents learn to **balance risk reduction against regimen stability**. - ---- - -## Action Space - -Each step, the agent sends a `PolypharmacyAction` with one of three action types: - -| `action_type` | Required fields | Description | -|---|---|---| -| `query_ddi` | `drug_id_1`, `drug_id_2` | Query the DDI database for an interaction between two drugs | -| `propose_intervention` | `target_drug_id`, `intervention_type` | Propose changing a medication (`stop`, `dose_reduce`, `substitute`, `add_monitoring`) | -| `finish_review` | — | End the review and trigger final grading | - -Optional fields: `proposed_new_drug_id`, `rationale`. - -## Observation Space - -`PolypharmacyObservation` includes: - -- **Patient demographics**: `age`, `sex`, `conditions`, `eGFR_category`, `liver_function_category` -- **Medications**: list of `MedicationEntry` (drug_id, name, class, dose, high-risk flags, Beers flags) -- **History**: `interaction_queries` (past DDI query results), `interventions` (past actions) -- **Budgets**: `remaining_query_budget`, `remaining_intervention_budget` -- **Reward signals**: `shaped_reward`, `done` - -## State - -`PolypharmacyState`: `episode_id`, `task_id`, `step_count`, `max_steps`, `num_query_actions`, `num_interventions`. - ---- - -## Tasks - -| Task ID | Difficulty | Drugs | Query Budget | Intervention Budget | Max Steps | Description | -|---|---|---|---|---|---|---| -| `easy_screening` | Easy | 3-5 | 4 | 2 | 10 | One severe DDI, simple resolution | -| `budgeted_screening` | Medium | 6-10 | 8 | 3 | 20 | Multiple DDIs + Beers issues, limited budgets | -| `complex_tradeoff` | Hard | 10-15 | 12 | 5 | 30 | Critical drugs, trade-off between risk and regimen stability | - ---- - -## Reward Structure - -**Per-step shaped rewards:** - -| Event | Reward | -|---|---| -| DDI query | -0.01 (cost) + 0.03 bonus if severe DDI discovered | -| Successful intervention | +(previous_risk - new_risk) - 0.02 cost | -| Invalid action | -0.10 penalty | -| Timeout (max steps exceeded) | -0.20 penalty | -| `finish_review` | + grader score (0.0 to 1.0) | - -**Terminal grader scoring:** -- **Easy**: 50% risk reduction + 50% targeted intervention flag -- **Medium**: 50% risk reduction + 30% intervention precision + 20% query efficiency -- **Hard**: risk reduction - regimen disruption penalty - critical drug penalty - ---- - -## Setup & Usage - -### Install dependencies - -```bash -pip install -r requirements.txt -``` - -### Generate synthetic data - -```bash -python3 scripts/preprocess_data.py -``` - -### Run the API server locally - -```bash -PYTHONPATH=src uvicorn polypharmacy_env.api.server:app --host 0.0.0.0 --port 7860 -``` - -### Run the heuristic baseline - -```bash -PYTHONPATH=src python3 -m polypharmacy_env.baselines.heuristic_agent -``` - -### Run tests - -```bash -PYTHONPATH=src python3 -m pytest src/polypharmacy_env/tests/ -v -``` - -### Run `inference.py` (LLM baseline) - -```bash -# Start the server first, then in another terminal: -export OPENAI_API_KEY="sk-..." -export MODEL_NAME="gpt-4.1" -export POLYPHARMACY_ENV_URL="http://localhost:7860" -python3 inference.py -``` - -### Docker - -```bash -docker build -t polypharmacy-env . -docker run -p 7860:7860 polypharmacy-env -``` - ---- - -## Hugging Face Space - -This repo is ready for deployment as a HF Space: - -- **Space type**: `docker` -- **Tag**: `openenv` -- The container listens on port 7860 and exposes `/reset`, `/step`, `/state`, `/health`. - ---- - -## Baseline Scores - -### Heuristic Agent (deterministic, rule-based) - -| Task | Avg Score | Avg Reward | -|---|---|---| -| `easy_screening` | ~0.96 | ~1.30 | -| `budgeted_screening` | ~0.48 | ~0.45 | -| `complex_tradeoff` | ~0.24 | ~0.11 | - -*(Scores vary by seed; run `scripts/run_validation.sh` for exact numbers.)* - ---- - -## Project Structure - -``` -openenv-polypharmacy/ - openenv.yaml # OpenEnv manifest - Dockerfile # Container image - inference.py # LLM baseline script - requirements.txt - pyproject.toml - src/polypharmacy_env/ - config.py # Constants, task configs - models.py # Pydantic action/observation/state models - env_core.py # PolypharmacyEnv implementation - tasks.py # Task selection utilities - graders.py # Deterministic graders (3 difficulty levels) - rewards.py # Reward shaping logic - data_loader.py # CSV data loading - ddi_simulator.py # Drug interaction lookup engine - api/ - server.py # FastAPI HTTP server - schemas.py # Request/response schemas - baselines/ - heuristic_agent.py # Rule-based baseline - random_agent.py # Random baseline - tests/ - test_env_core.py - test_api.py - data/ - lookups/ # Drug metadata, DDI rules, Beers criteria CSVs - processed/ # Synthetic patient episodes - scripts/ - preprocess_data.py # Synthetic data generator - run_validation.sh # Run tests + baseline -``` diff --git a/openenv-polypharmacy/backend/Dockerfile b/openenv-polypharmacy/backend/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..0cba5065ef8349abee5686485d0ada06fe57ce05 --- /dev/null +++ b/openenv-polypharmacy/backend/Dockerfile @@ -0,0 +1,28 @@ +FROM python:3.11-slim + +RUN apt-get update && \ + apt-get install -y --no-install-recommends build-essential curl && \ + rm -rf /var/lib/apt/lists/* + +WORKDIR /app + +COPY backend/requirements.txt /app/backend/requirements.txt +RUN pip install --no-cache-dir -r /app/backend/requirements.txt + +COPY backend /app/backend +COPY data /app/data +COPY scripts /app/scripts +COPY .env.example /app/.env.example + +RUN python3 /app/scripts/preprocess_data.py + +ENV PORT=7860 +ENV PYTHONPATH="/app/backend/src:${PYTHONPATH}" +ENV PYTHONUNBUFFERED=1 + +EXPOSE 7860 + +HEALTHCHECK --interval=30s --timeout=3s --start-period=10s --retries=3 \ + CMD curl -f http://localhost:7860/health || exit 1 + +CMD ["uvicorn", "backend.main:app", "--host", "0.0.0.0", "--port", "7860"] diff --git a/openenv-polypharmacy/backend/__init__.py b/openenv-polypharmacy/backend/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..2f40af2be5beb19dd1c96a0a63b74124b144b304 --- /dev/null +++ b/openenv-polypharmacy/backend/__init__.py @@ -0,0 +1 @@ +"""Backend entrypoint package for monorepo structure.""" diff --git a/openenv-polypharmacy/backend/main.py b/openenv-polypharmacy/backend/main.py new file mode 100644 index 0000000000000000000000000000000000000000..d7058d14ed4d68e0e2612e4168c9ec6d3ee0828c --- /dev/null +++ b/openenv-polypharmacy/backend/main.py @@ -0,0 +1,15 @@ +"""ASGI entrypoint for backend service in monorepo layout.""" + +from __future__ import annotations + +import sys +from pathlib import Path + +BACKEND_DIR = Path(__file__).resolve().parent +SRC = BACKEND_DIR / "src" +if str(SRC) not in sys.path: + sys.path.insert(0, str(SRC)) + +from polypharmacy_env.api.app import app # noqa: E402 + +__all__ = ["app"] diff --git a/openenv-polypharmacy/src/polypharmacy_env.egg-info/requires.txt b/openenv-polypharmacy/backend/requirements.txt similarity index 72% rename from openenv-polypharmacy/src/polypharmacy_env.egg-info/requires.txt rename to openenv-polypharmacy/backend/requirements.txt index 21acf4c6feefb13b1c9bca99728a835b24b099a4..c975be48d5a69da77e34da8973f265732a115236 100644 --- a/openenv-polypharmacy/src/polypharmacy_env.egg-info/requires.txt +++ b/openenv-polypharmacy/backend/requirements.txt @@ -2,10 +2,8 @@ fastapi>=0.104.0 uvicorn>=0.24.0 pydantic>=2.0.0 requests>=2.31.0 +httpx>=0.25.0 +openenv-core>=0.2.0 openai>=1.0.0 - -[dev] +python-dotenv>=1.0.0 pytest>=7.0.0 -httpx>=0.25.0 -black -isort diff --git a/openenv-polypharmacy/src/polypharmacy_env/__init__.py b/openenv-polypharmacy/backend/src/polypharmacy_env/__init__.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/__init__.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/__init__.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/api/__init__.py b/openenv-polypharmacy/backend/src/polypharmacy_env/api/__init__.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/api/__init__.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/api/__init__.py diff --git a/openenv-polypharmacy/backend/src/polypharmacy_env/api/app.py b/openenv-polypharmacy/backend/src/polypharmacy_env/api/app.py new file mode 100644 index 0000000000000000000000000000000000000000..a4377baaca9f6c0d8191c1a2e89d1e9c70b48605 --- /dev/null +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/api/app.py @@ -0,0 +1,63 @@ +"""FastAPI app factory for PolypharmacyEnv.""" + +from __future__ import annotations + +from pathlib import Path + +from dotenv import load_dotenv +from fastapi import HTTPException +from fastapi.middleware.cors import CORSMiddleware +from fastapi.staticfiles import StaticFiles +from openenv.core.env_server.http_server import create_app +from starlette.responses import FileResponse + +from ..env_core import PolypharmacyEnv +from ..models import PolypharmacyAction, PolypharmacyObservation +from .routes.agent import router as agent_router + +load_dotenv() + + +class SPAStaticFiles(StaticFiles): + """Serve SPA index for unknown frontend routes.""" + + async def get_response(self, path: str, scope): + response = await super().get_response(path, scope) + if response.status_code != 404: + return response + index_path = Path(self.directory) / "index.html" + if index_path.exists(): + return FileResponse(index_path) + raise HTTPException(status_code=404, detail="Not Found") + + +def create_polypharmacy_app(): + app = create_app( + PolypharmacyEnv, + PolypharmacyAction, + PolypharmacyObservation, + env_name="polypharmacy_env", + ) + + app.add_middleware( + CORSMiddleware, + allow_origins=[ + "http://localhost:5173", + "http://127.0.0.1:5173", + ], + allow_credentials=True, + allow_methods=["*"], + allow_headers=["*"], + ) + app.include_router(agent_router) + + # In Docker Space deployment, serve built frontend from same container. + project_root = Path(__file__).resolve().parents[4] + frontend_dist = project_root / "frontend" / "dist" + if frontend_dist.exists(): + app.mount("/", SPAStaticFiles(directory=frontend_dist, html=True), name="frontend") + + return app + + +app = create_polypharmacy_app() diff --git a/openenv-polypharmacy/backend/src/polypharmacy_env/api/routes/__init__.py b/openenv-polypharmacy/backend/src/polypharmacy_env/api/routes/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..fb0a2f808230d18b89b49b68b2bce37b7c869206 --- /dev/null +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/api/routes/__init__.py @@ -0,0 +1 @@ +"""API route modules.""" diff --git a/openenv-polypharmacy/backend/src/polypharmacy_env/api/routes/agent.py b/openenv-polypharmacy/backend/src/polypharmacy_env/api/routes/agent.py new file mode 100644 index 0000000000000000000000000000000000000000..f74e627ff9f5fcea9954cc51f51991bdb6218fbf --- /dev/null +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/api/routes/agent.py @@ -0,0 +1,35 @@ +"""Agent suggestion API routes.""" + +from __future__ import annotations + +from fastapi import APIRouter, HTTPException +from pydantic import BaseModel, Field + +from ...models import PolypharmacyAction, PolypharmacyObservation +from ...services.groq_agent import suggest_action_from_observation + +router = APIRouter(prefix="/agent", tags=["agent"]) + + +class AgentSuggestRequest(BaseModel): + observation: PolypharmacyObservation + model_name: str | None = None + + +class AgentSuggestResponse(BaseModel): + action: PolypharmacyAction + source: str = Field(default="groq") + + +@router.post("/suggest", response_model=AgentSuggestResponse) +def suggest_agent_action(payload: AgentSuggestRequest) -> AgentSuggestResponse: + """Return a model-suggested action for the current observation.""" + try: + action = suggest_action_from_observation( + payload.observation, model_name=payload.model_name + ) + except ValueError as exc: + raise HTTPException(status_code=400, detail=str(exc)) from exc + except Exception as exc: + raise HTTPException(status_code=500, detail=f"Model call failed: {exc}") from exc + return AgentSuggestResponse(action=action) diff --git a/openenv-polypharmacy/backend/src/polypharmacy_env/api/server.py b/openenv-polypharmacy/backend/src/polypharmacy_env/api/server.py new file mode 100644 index 0000000000000000000000000000000000000000..63717ca71f81ef20f44c410d4dd7a59576942b2e --- /dev/null +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/api/server.py @@ -0,0 +1,6 @@ +"""Backward-compatible app import path. + +Use `polypharmacy_env.api.app:app` for the main app module. +""" + +from .app import app diff --git a/openenv-polypharmacy/src/polypharmacy_env/baselines/__init__.py b/openenv-polypharmacy/backend/src/polypharmacy_env/baselines/__init__.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/baselines/__init__.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/baselines/__init__.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/baselines/heuristic_agent.py b/openenv-polypharmacy/backend/src/polypharmacy_env/baselines/heuristic_agent.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/baselines/heuristic_agent.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/baselines/heuristic_agent.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/baselines/random_agent.py b/openenv-polypharmacy/backend/src/polypharmacy_env/baselines/random_agent.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/baselines/random_agent.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/baselines/random_agent.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/client.py b/openenv-polypharmacy/backend/src/polypharmacy_env/client.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/client.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/client.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/config.py b/openenv-polypharmacy/backend/src/polypharmacy_env/config.py similarity index 97% rename from openenv-polypharmacy/src/polypharmacy_env/config.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/config.py index bfe0d2a1878d584999ec8ae86d88362f0e221ff3..e71035ae3e075c08b7f0a9dbbef0857abb8be231 100644 --- a/openenv-polypharmacy/src/polypharmacy_env/config.py +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/config.py @@ -7,7 +7,7 @@ from pathlib import Path from typing import Dict # ── Paths ──────────────────────────────────────────────────────────────────── -PROJECT_ROOT = Path(__file__).resolve().parents[2] # openenv-polypharmacy/ +PROJECT_ROOT = Path(__file__).resolve().parents[3] # openenv-polypharmacy/ DATA_DIR = PROJECT_ROOT / "data" LOOKUPS_DIR = DATA_DIR / "lookups" PROCESSED_DIR = DATA_DIR / "processed" diff --git a/openenv-polypharmacy/src/polypharmacy_env/data_loader.py b/openenv-polypharmacy/backend/src/polypharmacy_env/data_loader.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/data_loader.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/data_loader.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/ddi_simulator.py b/openenv-polypharmacy/backend/src/polypharmacy_env/ddi_simulator.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/ddi_simulator.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/ddi_simulator.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/env_core.py b/openenv-polypharmacy/backend/src/polypharmacy_env/env_core.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/env_core.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/env_core.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/graders.py b/openenv-polypharmacy/backend/src/polypharmacy_env/graders.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/graders.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/graders.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/models.py b/openenv-polypharmacy/backend/src/polypharmacy_env/models.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/models.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/models.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/rewards.py b/openenv-polypharmacy/backend/src/polypharmacy_env/rewards.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/rewards.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/rewards.py diff --git a/openenv-polypharmacy/backend/src/polypharmacy_env/services/__init__.py b/openenv-polypharmacy/backend/src/polypharmacy_env/services/__init__.py new file mode 100644 index 0000000000000000000000000000000000000000..daa00ba9855c5ea54e0e4d3fe0a29407c421340a --- /dev/null +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/services/__init__.py @@ -0,0 +1 @@ +"""Service layer for external integrations.""" diff --git a/openenv-polypharmacy/backend/src/polypharmacy_env/services/groq_agent.py b/openenv-polypharmacy/backend/src/polypharmacy_env/services/groq_agent.py new file mode 100644 index 0000000000000000000000000000000000000000..9f15f22ff2ec9f4710949815b29f0431b2cac63b --- /dev/null +++ b/openenv-polypharmacy/backend/src/polypharmacy_env/services/groq_agent.py @@ -0,0 +1,246 @@ +"""Groq-powered action suggester for PolypharmacyEnv.""" + +from __future__ import annotations + +import json +import os +from typing import Any + +from openai import OpenAI + +from ..models import PolypharmacyAction, PolypharmacyObservation + +DEFAULT_MODEL = "llama-3.1-8b-instant" +FALLBACK_MODELS = [ + "llama-3.1-8b-instant", + "llama-3.3-70b-versatile", + "gemma2-9b-it", +] +CRITICAL_DRUG_IDS = {"DRUG_WARFARIN", "DRUG_INSULIN_GLARGINE", "DRUG_DIGOXIN"} + +SYSTEM_PROMPT = """You are a clinical medication safety assistant. +Return exactly one JSON object describing the next action. +Allowed output schema: +{ + "action_type": "query_ddi" | "propose_intervention" | "finish_review", + "drug_id_1": "optional", + "drug_id_2": "optional", + "target_drug_id": "optional", + "intervention_type": "stop|dose_reduce|substitute|add_monitoring|none", + "proposed_new_drug_id": "optional", + "rationale": "optional" +} +No markdown fences. No extra text. +Do NOT use finish_review early. First, gather evidence with query_ddi and/or +perform at least one meaningful intervention when needed. +""" + + +def _obs_to_prompt(obs: PolypharmacyObservation) -> str: + meds = ", ".join(m.drug_id for m in obs.current_medications) + conds = ", ".join(obs.conditions) + return ( + f"Task: {obs.task_id}\n" + f"Age: {obs.age}, sex: {obs.sex}\n" + f"Conditions: {conds}\n" + f"Medications: {meds}\n" + f"Query budget: {obs.remaining_query_budget}\n" + f"Intervention budget: {obs.remaining_intervention_budget}\n" + f"Step index: {obs.step_index}\n" + "Choose the single safest, most useful next action." + ) + + +def _parse_action(text: str) -> PolypharmacyAction: + raw = text.strip() + if raw.startswith("```"): + raw = raw.split("\n", 1)[-1] + if raw.endswith("```"): + raw = raw.rsplit("```", 1)[0] + raw = raw.strip() + payload: dict[str, Any] = json.loads(raw) + return PolypharmacyAction.model_validate(payload) + + +def _fallback_query_action(obs: PolypharmacyObservation) -> PolypharmacyAction: + meds = [m.drug_id for m in obs.current_medications] + if len(meds) >= 2 and obs.remaining_query_budget > 0: + return PolypharmacyAction( + action_type="query_ddi", + drug_id_1=meds[0], + drug_id_2=meds[1], + ) + return PolypharmacyAction(action_type="finish_review") + + +def _norm_pair(a: str, b: str) -> tuple[str, str]: + return (a, b) if a < b else (b, a) + + +def _pick_unseen_query_pair(obs: PolypharmacyObservation) -> tuple[str, str] | None: + meds = [m.drug_id for m in obs.current_medications] + if len(meds) < 2 or obs.remaining_query_budget <= 0: + return None + + seen = { + _norm_pair(q.drug_id_1, q.drug_id_2) + for q in obs.interaction_queries + } + # Prioritize pairs containing high-risk drugs. + high_risk = [m.drug_id for m in obs.current_medications if m.is_high_risk_elderly] + ordered = high_risk + [m for m in meds if m not in set(high_risk)] + + for i in range(len(ordered)): + for j in range(i + 1, len(ordered)): + p = _norm_pair(ordered[i], ordered[j]) + if p not in seen: + return p + return None + + +def _pick_intervention_target(obs: PolypharmacyObservation) -> str | None: + if obs.remaining_intervention_budget <= 0: + return None + med_set = {m.drug_id for m in obs.current_medications} + + # Use latest discovered severe/moderate query as intervention target. + for q in reversed(obs.interaction_queries): + if q.severity in ("severe", "moderate"): + m1 = next((m for m in obs.current_medications if m.drug_id == q.drug_id_1), None) + m2 = next((m for m in obs.current_medications if m.drug_id == q.drug_id_2), None) + candidates = [m for m in (m1, m2) if m is not None] + if not candidates: + continue + # Prefer non-critical risky drugs first. + candidates.sort( + key=lambda m: ( + m.drug_id in CRITICAL_DRUG_IDS, + 0 if any("avoid" in f for f in m.beers_flags) else 1, + 0 if m.is_high_risk_elderly else 1, + ) + ) + return candidates[0].drug_id + + # Fallback: if no severe/moderate discovered, still intervene on obviously + # risky medications (Beers/high-risk flags) when budgets permit. + risky = sorted( + obs.current_medications, + key=lambda m: ( + 0 if any("avoid" in f for f in m.beers_flags) else 1, + 0 if m.is_high_risk_elderly else 1, + 1 if m.drug_id in CRITICAL_DRUG_IDS else 0, + ), + ) + for med in risky: + if any("avoid" in f for f in med.beers_flags) or med.is_high_risk_elderly: + return med.drug_id + return None + + +def _rule_based_action(obs: PolypharmacyObservation) -> PolypharmacyAction | None: + # If we already discovered significant risk, intervene before more querying. + target = _pick_intervention_target(obs) + if target and ( + obs.step_index >= 1 + and ( + obs.remaining_query_budget <= 2 + or len(obs.interaction_queries) >= 4 + or any(q.severity in ("severe", "moderate") for q in obs.interaction_queries) + ) + ): + intervention = "stop" + rationale = "Remove likely contributor to discovered interaction risk" + if target in CRITICAL_DRUG_IDS: + # Avoid blunt stop for critical meds. + intervention = "dose_reduce" + rationale = "Critical medication: prefer dose reduction over abrupt stop" + return PolypharmacyAction( + action_type="propose_intervention", + target_drug_id=target, + intervention_type=intervention, + rationale=rationale, + ) + + pair = _pick_unseen_query_pair(obs) + if pair: + return PolypharmacyAction( + action_type="query_ddi", + drug_id_1=pair[0], + drug_id_2=pair[1], + ) + + if obs.remaining_intervention_budget > 0: + # Final fallback before finish: at least one safety action. + target = _pick_intervention_target(obs) + if target: + return PolypharmacyAction( + action_type="propose_intervention", + target_drug_id=target, + intervention_type="dose_reduce" + if target in CRITICAL_DRUG_IDS + else "stop", + rationale="Fallback intervention when query options are exhausted", + ) + + if obs.step_index >= 3: + return PolypharmacyAction(action_type="finish_review") + return None + + +def _postprocess_action( + obs: PolypharmacyObservation, action: PolypharmacyAction +) -> PolypharmacyAction: + # First apply deterministic guardrails to avoid repetitive loops. + ruled = _rule_based_action(obs) + if ruled is not None: + return ruled + + # Guardrail: prevent useless immediate finish actions. + if action.action_type == "finish_review": + if obs.step_index < 2 and obs.remaining_query_budget > 0: + return _fallback_query_action(obs) + if len(obs.interaction_queries) == 0 and obs.remaining_query_budget > 0: + return _fallback_query_action(obs) + return action + + +def suggest_action_from_observation( + observation: PolypharmacyObservation, + model_name: str | None = None, +) -> PolypharmacyAction: + """Use Groq chat completions to suggest a valid action.""" + api_key = os.getenv("GROQ_API_KEY", "").strip() + if not api_key: + raise ValueError("GROQ_API_KEY is missing. Add it to your .env file.") + + base_url = os.getenv("GROQ_BASE_URL", "https://api.groq.com/openai/v1").strip() + model = (model_name or os.getenv("GROQ_MODEL_NAME", DEFAULT_MODEL)).strip() + client = OpenAI(api_key=api_key, base_url=base_url) + + user_prompt = _obs_to_prompt(observation) + tried: list[tuple[str, str]] = [] + candidates: list[str] = [model] + [m for m in FALLBACK_MODELS if m != model] + + for candidate in candidates: + try: + resp = client.chat.completions.create( + model=candidate, + messages=[ + {"role": "system", "content": SYSTEM_PROMPT}, + {"role": "user", "content": user_prompt}, + ], + temperature=0.2, + max_tokens=220, + ) + generated = (resp.choices[0].message.content or "").strip() + parsed = _parse_action(generated) + return _postprocess_action(observation, parsed) + except Exception as exc: + tried.append((candidate, str(exc))) + + tried_txt = " | ".join(f"{m}: {err}" for m, err in tried) + raise ValueError( + "No Groq model worked. Try one of: " + "llama-3.3-70b-versatile, llama-3.1-8b-instant, gemma2-9b-it. " + f"Errors: {tried_txt}" + ) diff --git a/openenv-polypharmacy/src/polypharmacy_env/tasks.py b/openenv-polypharmacy/backend/src/polypharmacy_env/tasks.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/tasks.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/tasks.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/tests/__init__.py b/openenv-polypharmacy/backend/src/polypharmacy_env/tests/__init__.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/tests/__init__.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/tests/__init__.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/tests/test_api.py b/openenv-polypharmacy/backend/src/polypharmacy_env/tests/test_api.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/tests/test_api.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/tests/test_api.py diff --git a/openenv-polypharmacy/src/polypharmacy_env/tests/test_env_core.py b/openenv-polypharmacy/backend/src/polypharmacy_env/tests/test_env_core.py similarity index 100% rename from openenv-polypharmacy/src/polypharmacy_env/tests/test_env_core.py rename to openenv-polypharmacy/backend/src/polypharmacy_env/tests/test_env_core.py diff --git a/openenv-polypharmacy/data/processed/patients_polypharmacy.csv b/openenv-polypharmacy/data/processed/patients_polypharmacy.csv index d74ead76cefab3c65e7aa9975d6f148e982aa4fa..3dfd4b83053958e03a785dd8bd057c7c5879c74b 100644 --- a/openenv-polypharmacy/data/processed/patients_polypharmacy.csv +++ b/openenv-polypharmacy/data/processed/patients_polypharmacy.csv @@ -1,44 +1,44 @@ episode_id,age,sex,conditions,eGFR_category,liver_function_category,medication_ids,baseline_risk_score,difficulty -EP_0001,72,F,HTN,moderate,normal,DRUG_WARFARIN;DRUG_FUROSEMIDE;DRUG_LISINOPRIL;DRUG_AMLODIPINE;DRUG_NAPROXEN,0.264,easy +EP_0001,72,F,HTN,moderate,normal,DRUG_AMLODIPINE;DRUG_LISINOPRIL;DRUG_DIGOXIN;DRUG_FUROSEMIDE;DRUG_AMIODARONE,0.25,easy EP_0002,67,M,OA;COPD;neuropathy,normal,normal,DRUG_IBUPROFEN;DRUG_TRAMADOL;DRUG_AMITRIPTYLINE,0.2833,easy -EP_0003,73,F,HTN;HF,normal,normal,DRUG_IBUPROFEN;DRUG_WARFARIN;DRUG_FUROSEMIDE,0.2933,easy -EP_0004,74,M,CKD,mild,impaired,DRUG_TRAMADOL;DRUG_AMLODIPINE;DRUG_DIAZEPAM,0.3067,easy +EP_0003,73,F,HTN;HF,normal,normal,DRUG_FUROSEMIDE;DRUG_FLUOXETINE;DRUG_TRAMADOL,0.2733,easy +EP_0004,74,M,CKD,mild,impaired,DRUG_AMITRIPTYLINE;DRUG_AMLODIPINE;DRUG_TRAMADOL,0.2833,easy EP_0005,76,F,OA;neuropathy;CKD,mild,normal,DRUG_IBUPROFEN;DRUG_GABAPENTIN;DRUG_TRAMADOL;DRUG_NAPROXEN;DRUG_AMITRIPTYLINE,0.17,easy -EP_0006,74,M,HTN;OA,normal,impaired,DRUG_IBUPROFEN;DRUG_WARFARIN;DRUG_LISINOPRIL;DRUG_FUROSEMIDE;DRUG_NAPROXEN,0.44,easy -EP_0007,90,M,BPH;OA,moderate,normal,DRUG_DIGOXIN;DRUG_TAMSULOSIN;DRUG_GABAPENTIN;DRUG_NAPROXEN;DRUG_AMIODARONE,0.16,easy +EP_0006,74,M,HTN;OA,normal,impaired,DRUG_IBUPROFEN;DRUG_LISINOPRIL;DRUG_DIGOXIN;DRUG_FUROSEMIDE;DRUG_AMIODARONE,0.25,easy +EP_0007,90,M,BPH;OA,moderate,normal,DRUG_WARFARIN;DRUG_NAPROXEN;DRUG_TAMSULOSIN;DRUG_GABAPENTIN,0.225,easy EP_0008,77,F,CKD;OA;depression,mild,normal,DRUG_AMITRIPTYLINE;DRUG_IBUPROFEN;DRUG_SERTRALINE;DRUG_TRAMADOL;DRUG_FUROSEMIDE,0.17,easy -EP_0009,67,M,COPD;GERD;BPH,mild,normal,DRUG_TRAMADOL;DRUG_FLUOXETINE;DRUG_OMEPRAZOLE;DRUG_TAMSULOSIN,0.205,easy -EP_0010,75,M,dementia;HTN;depression,normal,impaired,DRUG_TRAMADOL;DRUG_DIAZEPAM;DRUG_SERTRALINE;DRUG_AMITRIPTYLINE,0.4425,easy -EP_0011,83,F,AF,moderate,normal,DRUG_TRAMADOL;DRUG_WARFARIN;DRUG_DIGOXIN;DRUG_ALPRAZOLAM,0.2275,easy -EP_0012,71,F,HTN;GERD;depression,normal,normal,DRUG_LISINOPRIL;DRUG_FLUOXETINE;DRUG_APIXABAN;DRUG_AMLODIPINE;DRUG_NAPROXEN,0.254,easy -EP_0013,70,F,HF;HTN;AF,mild,normal,DRUG_TRAMADOL;DRUG_FUROSEMIDE;DRUG_ALPRAZOLAM,0.3033,easy +EP_0009,67,M,COPD;GERD;BPH,mild,normal,DRUG_WARFARIN;DRUG_IBUPROFEN;DRUG_OMEPRAZOLE;DRUG_TAMSULOSIN,0.22,easy +EP_0010,75,M,dementia;HTN;depression,normal,impaired,DRUG_TRAMADOL;DRUG_SERTRALINE;DRUG_AMITRIPTYLINE,0.2833,easy +EP_0011,83,F,AF,moderate,normal,DRUG_ALPRAZOLAM;DRUG_WARFARIN;DRUG_DIGOXIN;DRUG_TRAMADOL,0.2275,easy +EP_0012,71,F,HTN;GERD;depression,normal,normal,DRUG_DIAZEPAM;DRUG_AMLODIPINE;DRUG_FLUOXETINE;DRUG_LISINOPRIL;DRUG_TRAMADOL,0.348,easy +EP_0013,70,F,HF;HTN;AF,mild,normal,DRUG_ALPRAZOLAM;DRUG_FUROSEMIDE;DRUG_TRAMADOL,0.3033,easy EP_0014,82,F,dementia,normal,normal,DRUG_DONEPEZIL;DRUG_NAPROXEN;DRUG_APIXABAN;DRUG_SPIRONOLACTONE;DRUG_FUROSEMIDE,0.17,easy EP_0015,84,F,dementia;neuropathy,normal,normal,DRUG_DONEPEZIL;DRUG_GABAPENTIN;DRUG_AMITRIPTYLINE;DRUG_CELECOXIB;DRUG_TRAMADOL,0.17,easy -EP_0016,83,M,HTN,normal,normal,DRUG_TRAMADOL;DRUG_METOPROLOL;DRUG_ALPRAZOLAM,0.3033,easy -EP_0017,83,F,CKD,severe,normal,DRUG_APIXABAN;DRUG_AMLODIPINE;DRUG_NAPROXEN,0.2833,easy -EP_0018,70,F,CKD;HF;HTN,mild,normal,DRUG_SPIRONOLACTONE;DRUG_ALPRAZOLAM;DRUG_TRAMADOL;DRUG_AMLODIPINE;DRUG_METOPROLOL,0.182,easy -EP_0019,84,M,DM;depression,normal,normal,DRUG_GLIPIZIDE;DRUG_FLUOXETINE;DRUG_TRAMADOL;DRUG_INSULIN_GLARGINE;DRUG_DIAZEPAM,0.448,easy -EP_0020,90,F,neuropathy;BPH;AF,normal,normal,DRUG_WARFARIN;DRUG_NAPROXEN;DRUG_TAMSULOSIN,0.3,easy -EP_0021,87,M,HTN;BPH;HF,normal,normal,DRUG_TRAMADOL;DRUG_AMITRIPTYLINE;DRUG_AMLODIPINE;DRUG_SPIRONOLACTONE,0.2125,easy -EP_0022,90,M,AF;GERD;DM,normal,impaired,DRUG_APIXABAN;DRUG_NAPROXEN;DRUG_METOPROLOL;DRUG_OMEPRAZOLE,0.2125,easy -EP_0023,90,F,HF,normal,normal,DRUG_APIXABAN;DRUG_NAPROXEN;DRUG_METOPROLOL,0.2833,easy +EP_0016,83,M,HTN,normal,normal,DRUG_ALPRAZOLAM;DRUG_METOPROLOL;DRUG_TRAMADOL,0.3033,easy +EP_0017,83,F,CKD,severe,normal,DRUG_DIAZEPAM;DRUG_AMLODIPINE;DRUG_TRAMADOL,0.3067,easy +EP_0018,70,F,CKD;HF;HTN,mild,normal,DRUG_SPIRONOLACTONE;DRUG_AMLODIPINE;DRUG_ALPRAZOLAM;DRUG_METOPROLOL;DRUG_TRAMADOL,0.182,easy +EP_0019,84,M,DM;depression,normal,normal,DRUG_INSULIN_GLARGINE;DRUG_FLUOXETINE;DRUG_AMITRIPTYLINE;DRUG_GLIPIZIDE;DRUG_TRAMADOL,0.434,easy +EP_0020,90,F,neuropathy;BPH;AF,normal,normal,DRUG_WARFARIN;DRUG_DIGOXIN;DRUG_AMIODARONE;DRUG_TAMSULOSIN,0.2,easy +EP_0021,87,M,HTN;BPH;HF,normal,normal,DRUG_SPIRONOLACTONE;DRUG_APIXABAN;DRUG_NAPROXEN;DRUG_AMLODIPINE,0.2125,easy +EP_0022,90,M,AF;GERD;DM,normal,impaired,DRUG_OMEPRAZOLE;DRUG_DIAZEPAM;DRUG_METOPROLOL;DRUG_TRAMADOL,0.23,easy +EP_0023,90,F,HF,normal,normal,DRUG_DIAZEPAM;DRUG_METOPROLOL;DRUG_TRAMADOL,0.3067,easy EP_0024,71,F,OA,mild,normal,DRUG_IBUPROFEN;DRUG_GABAPENTIN;DRUG_TRAMADOL;DRUG_NAPROXEN;DRUG_APIXABAN,0.17,easy -EP_0025,71,M,COPD;AF;neuropathy,mild,normal,DRUG_GABAPENTIN;DRUG_WARFARIN;DRUG_NAPROXEN,0.3,easy -EP_0026,88,M,GERD;dementia,severe,normal,DRUG_TRAMADOL;DRUG_AMITRIPTYLINE;DRUG_DONEPEZIL;DRUG_OMEPRAZOLE,0.2125,easy +EP_0025,71,M,COPD;AF;neuropathy,mild,normal,DRUG_WARFARIN;DRUG_DIGOXIN;DRUG_AMIODARONE;DRUG_GABAPENTIN,0.2,easy +EP_0026,88,M,GERD;dementia,severe,normal,DRUG_DONEPEZIL;DRUG_OMEPRAZOLE;DRUG_APIXABAN;DRUG_NAPROXEN,0.2125,easy EP_0027,76,M,AF,normal,normal,DRUG_DIGOXIN;DRUG_METOPROLOL;DRUG_WARFARIN;DRUG_APIXABAN;DRUG_NAPROXEN,0.43,easy EP_0028,73,F,CKD,moderate,normal,DRUG_AMLODIPINE;DRUG_FUROSEMIDE;DRUG_METFORMIN;DRUG_AMITRIPTYLINE;DRUG_TRAMADOL,0.17,easy -EP_0029,70,F,CKD;OA,mild,normal,DRUG_IBUPROFEN;DRUG_TRAMADOL;DRUG_GABAPENTIN;DRUG_AMLODIPINE;DRUG_DIAZEPAM,0.184,easy -EP_0030,87,F,dementia;HF;depression,normal,normal,DRUG_WARFARIN;DRUG_DONEPEZIL;DRUG_FLUOXETINE;DRUG_FUROSEMIDE;DRUG_NAPROXEN,0.27,easy -EP_0031,69,M,HF,severe,normal,DRUG_WARFARIN;DRUG_SPIRONOLACTONE;DRUG_LISINOPRIL;DRUG_FUROSEMIDE;DRUG_NAPROXEN,0.36,easy +EP_0029,70,F,CKD;OA,mild,normal,DRUG_IBUPROFEN;DRUG_AMLODIPINE;DRUG_AMITRIPTYLINE;DRUG_GABAPENTIN;DRUG_TRAMADOL,0.17,easy +EP_0030,87,F,dementia;HF;depression,normal,normal,DRUG_DIGOXIN;DRUG_FLUOXETINE;DRUG_DONEPEZIL;DRUG_FUROSEMIDE;DRUG_AMIODARONE,0.25,easy +EP_0031,69,M,HF,severe,normal,DRUG_SPIRONOLACTONE;DRUG_LISINOPRIL;DRUG_DIGOXIN;DRUG_FUROSEMIDE;DRUG_AMIODARONE,0.426,easy EP_0032,89,F,neuropathy,mild,normal,DRUG_AMITRIPTYLINE;DRUG_GABAPENTIN;DRUG_PREDNISONE;DRUG_TRAMADOL,0.2125,easy EP_0033,68,F,dementia,mild,impaired,DRUG_DONEPEZIL;DRUG_OMEPRAZOLE;DRUG_SPIRONOLACTONE;DRUG_TRAMADOL;DRUG_ALPRAZOLAM,0.182,easy -EP_0034,84,F,CKD;HF;HTN,moderate,normal,DRUG_HYDROCHLOROTHIAZIDE;DRUG_DIGOXIN;DRUG_AMIODARONE,0.2667,easy -EP_0035,74,M,HTN;DM,normal,impaired,DRUG_IBUPROFEN;DRUG_GLIPIZIDE;DRUG_WARFARIN;DRUG_HYDROCHLOROTHIAZIDE;DRUG_METOPROLOL,0.176,easy -EP_0036,80,F,DM;neuropathy;HTN,severe,normal,DRUG_WARFARIN;DRUG_AMLODIPINE;DRUG_AMITRIPTYLINE;DRUG_NAPROXEN,0.225,easy -EP_0037,78,M,HF,normal,normal,DRUG_TRAMADOL;DRUG_FUROSEMIDE;DRUG_DIAZEPAM;DRUG_LISINOPRIL,0.23,easy -EP_0038,89,F,HTN;AF,moderate,normal,DRUG_TRAMADOL;DRUG_FUROSEMIDE;DRUG_DIAZEPAM,0.3067,easy +EP_0034,84,F,CKD;HF;HTN,moderate,normal,DRUG_WARFARIN;DRUG_DIGOXIN;DRUG_NAPROXEN;DRUG_HYDROCHLOROTHIAZIDE,0.225,easy +EP_0035,74,M,HTN;DM,normal,impaired,DRUG_FLUOXETINE;DRUG_HYDROCHLOROTHIAZIDE;DRUG_GLIPIZIDE;DRUG_METOPROLOL;DRUG_TRAMADOL,0.164,easy +EP_0036,80,F,DM;neuropathy;HTN,severe,normal,DRUG_DIGOXIN;DRUG_AMLODIPINE;DRUG_AMIODARONE;DRUG_AMITRIPTYLINE,0.2,easy +EP_0037,78,M,HF,normal,normal,DRUG_LISINOPRIL;DRUG_AMITRIPTYLINE;DRUG_FUROSEMIDE;DRUG_TRAMADOL,0.2125,easy +EP_0038,89,F,HTN;AF,moderate,normal,DRUG_AMITRIPTYLINE;DRUG_FUROSEMIDE;DRUG_TRAMADOL,0.2833,easy EP_0039,78,F,OA;depression,moderate,normal,DRUG_GABAPENTIN;DRUG_FLUOXETINE;DRUG_TRAMADOL;DRUG_SERTRALINE,0.205,easy -EP_0040,72,F,neuropathy;COPD;BPH,normal,normal,DRUG_TRAMADOL;DRUG_ALPRAZOLAM;DRUG_AMITRIPTYLINE;DRUG_TAMSULOSIN,0.44,easy +EP_0040,72,F,neuropathy;COPD;BPH,normal,normal,DRUG_ALPRAZOLAM;DRUG_AMITRIPTYLINE;DRUG_TRAMADOL;DRUG_TAMSULOSIN,0.44,easy EP_0041,89,F,AF;BPH;DM;HF;HTN,mild,normal,DRUG_GLIPIZIDE;DRUG_DIGOXIN;DRUG_METOPROLOL;DRUG_WARFARIN;DRUG_METFORMIN;DRUG_AMLODIPINE;DRUG_INSULIN_GLARGINE;DRUG_HYDROCHLOROTHIAZIDE;DRUG_APIXABAN,0.1,medium EP_0042,66,F,HTN;AF;CKD,moderate,normal,DRUG_METOPROLOL;DRUG_AMLODIPINE;DRUG_LISINOPRIL;DRUG_DIGOXIN;DRUG_FUROSEMIDE;DRUG_WARFARIN;DRUG_APIXABAN;DRUG_HYDROCHLOROTHIAZIDE;DRUG_IBUPROFEN;DRUG_SERTRALINE,0.173,medium EP_0043,70,F,OA;HTN;dementia,moderate,normal,DRUG_TRAMADOL;DRUG_HYDROCHLOROTHIAZIDE;DRUG_GABAPENTIN;DRUG_IBUPROFEN;DRUG_DONEPEZIL;DRUG_FUROSEMIDE;DRUG_NAPROXEN;DRUG_LISINOPRIL;DRUG_METOPROLOL,0.0467,medium diff --git a/openenv-polypharmacy/docker-compose.yml b/openenv-polypharmacy/docker-compose.yml new file mode 100644 index 0000000000000000000000000000000000000000..2b2bde3a4b6870ab496787ea9e355ab209a085f9 --- /dev/null +++ b/openenv-polypharmacy/docker-compose.yml @@ -0,0 +1,35 @@ +version: "3.9" + +services: + backend: + build: + context: . + dockerfile: backend/Dockerfile + container_name: polypharmacy-backend + env_file: + - .env + ports: + - "7860:7860" + volumes: + - ./backend/src:/app/backend/src + - ./data:/app/data + - ./scripts:/app/scripts + - ./backend:/app/backend + healthcheck: + test: ["CMD", "curl", "-f", "http://localhost:7860/health"] + interval: 20s + timeout: 5s + retries: 5 + + frontend: + build: + context: . + dockerfile: frontend/Dockerfile + container_name: polypharmacy-frontend + depends_on: + - backend + ports: + - "5173:5173" + volumes: + - ./frontend:/app + - /app/node_modules diff --git a/openenv-polypharmacy/frontend/Dockerfile b/openenv-polypharmacy/frontend/Dockerfile new file mode 100644 index 0000000000000000000000000000000000000000..aa04742e98c70c50c11a21ee578eabd0f9269e15 --- /dev/null +++ b/openenv-polypharmacy/frontend/Dockerfile @@ -0,0 +1,12 @@ +FROM node:20-alpine + +WORKDIR /app + +COPY frontend/package*.json ./ +RUN npm ci + +COPY frontend/ ./ + +EXPOSE 5173 + +CMD ["npm", "run", "dev", "--", "--host", "0.0.0.0", "--port", "5173"] diff --git a/openenv-polypharmacy/frontend/index.html b/openenv-polypharmacy/frontend/index.html new file mode 100644 index 0000000000000000000000000000000000000000..a879a0927092473c247198a104ca9a5a4ab0dac9 --- /dev/null +++ b/openenv-polypharmacy/frontend/index.html @@ -0,0 +1,12 @@ + + + + + + Polypharmacy Control Center + + +
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"optional": true + }, + "less": { + "optional": true + }, + "lightningcss": { + "optional": true + }, + "sass": { + "optional": true + }, + "sass-embedded": { + "optional": true + }, + "stylus": { + "optional": true + }, + "sugarss": { + "optional": true + }, + "terser": { + "optional": true + } + } + }, + "node_modules/yallist": { + "version": "3.1.1", + "resolved": "https://registry.npmjs.org/yallist/-/yallist-3.1.1.tgz", + "integrity": "sha512-a4UGQaWPH59mOXUYnAG2ewncQS4i4F43Tv3JoAM+s2VDAmS9NsK8GpDMLrCHPksFT7h3K6TOoUNn2pb7RoXx4g==", + "dev": true, + "license": "ISC" + } + } +} diff --git a/openenv-polypharmacy/frontend/package.json b/openenv-polypharmacy/frontend/package.json new file mode 100644 index 0000000000000000000000000000000000000000..858ae22b50ac1a6732557b4815e882047b198712 --- /dev/null +++ b/openenv-polypharmacy/frontend/package.json @@ -0,0 +1,19 @@ +{ + "name": "polypharmacy-frontend", + "version": "0.1.0", + "private": true, + "type": "module", + "scripts": { + "dev": "vite", + "build": "vite build", + "preview": "vite preview --port 4173" + }, + "dependencies": { + "react": "^18.3.1", + "react-dom": "^18.3.1" + }, + "devDependencies": { + "@vitejs/plugin-react": "^4.3.1", + "vite": "^5.4.2" + } +} diff --git a/openenv-polypharmacy/frontend/src/App.jsx b/openenv-polypharmacy/frontend/src/App.jsx new file mode 100644 index 0000000000000000000000000000000000000000..60d1e4922436d0bde716bb9739cbf91ed0cb435a --- /dev/null +++ b/openenv-polypharmacy/frontend/src/App.jsx @@ -0,0 +1,387 @@ +import { useEffect, useMemo, useRef, useState } from "react"; + +function resolveApiBase() { + const explicitBase = import.meta.env.VITE_API_BASE; + if (explicitBase) return explicitBase.replace(/\/$/, ""); + + const host = window.location.hostname; + const isLocal = + host === "localhost" || host === "127.0.0.1" || host === "0.0.0.0"; + + // In local Vite dev, backend runs on :7860. In Spaces/prod, serve same-origin. + if (isLocal && window.location.port === "5173") { + return "http://localhost:7860"; + } + return window.location.origin.replace(/\/$/, ""); +} + +const API_BASE = resolveApiBase(); +const WS_URL = `${API_BASE.replace(/^http/, "ws")}/ws`; +const TASKS = ["easy_screening", "budgeted_screening", "complex_tradeoff"]; + +async function apiPost(path, body) { + const res = await fetch(`${API_BASE}${path}`, { + method: "POST", + headers: { "Content-Type": "application/json" }, + body: JSON.stringify(body), + }); + if (!res.ok) { + const msg = await res.text(); + throw new Error(msg || `HTTP ${res.status}`); + } + return res.json(); +} + +export default function App() { + const [taskId, setTaskId] = useState("budgeted_screening"); + const [obs, setObs] = useState(null); + const [log, setLog] = useState([]); + const [loading, setLoading] = useState(false); + const [action, setAction] = useState({ + action_type: "query_ddi", + drug_id_1: "", + drug_id_2: "", + target_drug_id: "", + intervention_type: "stop", + proposed_new_drug_id: "", + rationale: "", + }); + + const medIds = useMemo( + () => (obs?.current_medications || []).map((m) => m.drug_id), + [obs] + ); + const hasValidEpisode = Boolean(obs?.episode_id) && (obs?.current_medications?.length || 0) > 0; + const isDone = Boolean(obs?.done); + const finalScore = + typeof obs?.metadata?.grader_score === "number" ? obs.metadata.grader_score : null; + const noBudgetsLeft = + hasValidEpisode && + (obs?.remaining_query_budget ?? 0) <= 0 && + (obs?.remaining_intervention_budget ?? 0) <= 0; + const wsRef = useRef(null); + const pendingRef = useRef([]); + + const wsEnsure = async () => { + if (wsRef.current && wsRef.current.readyState === WebSocket.OPEN) return wsRef.current; + if (wsRef.current && wsRef.current.readyState === WebSocket.CONNECTING) { + await new Promise((r) => setTimeout(r, 80)); + return wsEnsure(); + } + + const ws = new WebSocket(WS_URL); + wsRef.current = ws; + + ws.onmessage = (evt) => { + try { + const msg = JSON.parse(evt.data); + const pending = pendingRef.current.shift(); + if (pending) pending.resolve(msg); + } catch (e) { + const pending = pendingRef.current.shift(); + if (pending) pending.reject(e); + } + }; + ws.onerror = (err) => { + const pending = pendingRef.current.shift(); + if (pending) pending.reject(err); + }; + ws.onclose = () => { + wsRef.current = null; + }; + + await new Promise((resolve, reject) => { + const t = setTimeout(() => reject(new Error("WebSocket connect timeout")), 2500); + ws.onopen = () => { + clearTimeout(t); + resolve(); + }; + }); + return ws; + }; + + const wsSend = async (type, data) => { + const ws = await wsEnsure(); + return await new Promise((resolve, reject) => { + pendingRef.current.push({ resolve, reject }); + ws.send(JSON.stringify({ type, data })); + }); + }; + + useEffect(() => { + return () => { + try { + wsRef.current?.close(); + } catch { + // ignore + } + }; + }, []); + + const appendLog = (text) => { + setLog((prev) => [`${new Date().toLocaleTimeString()} ${text}`, ...prev].slice(0, 20)); + }; + + const normalizeObsFromWs = (packetData) => { + const observation = packetData?.observation || {}; + const mergedMetadata = { + ...(observation?.metadata || {}), + ...(packetData?.info || {}), + }; + return { + ...observation, + done: Boolean(packetData?.done ?? observation?.done ?? false), + reward: packetData?.reward ?? observation?.reward ?? null, + metadata: mergedMetadata, + }; + }; + + const handleReset = async () => { + setLoading(true); + try { + const msg = await wsSend("reset", { task_id: taskId }); + const data = msg?.data || {}; + const normalized = normalizeObsFromWs(data); + setObs(normalized); + const ids = (normalized?.current_medications || []).map((m) => m.drug_id); + setAction((prev) => ({ + ...prev, + drug_id_1: ids[0] || "", + drug_id_2: ids[1] || "", + target_drug_id: ids[0] || "", + })); + appendLog(`Reset task=${taskId}`); + } catch (err) { + appendLog(`Reset failed: ${err.message}`); + } finally { + setLoading(false); + } + }; + + const buildActionPayload = () => { + if (noBudgetsLeft) { + return { action_type: "finish_review" }; + } + if (action.action_type === "query_ddi") { + return { + action_type: "query_ddi", + drug_id_1: action.drug_id_1, + drug_id_2: action.drug_id_2, + }; + } + if (action.action_type === "propose_intervention") { + return { + action_type: "propose_intervention", + target_drug_id: action.target_drug_id, + intervention_type: action.intervention_type, + proposed_new_drug_id: action.proposed_new_drug_id || undefined, + rationale: action.rationale || undefined, + }; + } + return { action_type: "finish_review" }; + }; + + const isActionValid = () => { + if (!hasValidEpisode) return false; + if (isDone) return false; + if (noBudgetsLeft) return true; + if (action.action_type === "query_ddi") { + return Boolean(action.drug_id_1 && action.drug_id_2); + } + if (action.action_type === "propose_intervention") { + return Boolean(action.target_drug_id && action.intervention_type); + } + return true; + }; + + const handleStep = async (overrideAction = null) => { + if (!hasValidEpisode) { + appendLog("Run Reset Episode before stepping."); + return; + } + setLoading(true); + try { + const payload = overrideAction || buildActionPayload(); + const msg = await wsSend("step", payload); + const data = msg?.data || {}; + const normalized = normalizeObsFromWs(data); + setObs(normalized); + appendLog(`Step: ${payload.action_type} -> reward=${data.reward ?? 0}`); + } catch (err) { + appendLog(`Step failed: ${err.message}`); + } finally { + setLoading(false); + } + }; + + const askAi = async () => { + if (!hasValidEpisode) { + appendLog("Run Reset Episode before asking AI."); + return; + } + setLoading(true); + try { + const data = await apiPost("/agent/suggest", { observation: obs }); + appendLog(`AI suggestion: ${data.action.action_type}`); + await handleStep(data.action); + } catch (err) { + appendLog(`AI suggestion failed: ${err.message}`); + } finally { + setLoading(false); + } + }; + + return ( +
+
+
+ +
+
+
+

Polypharmacy Control Center

+

Metaverse Clinical Ops Console

+
+
+ {hasValidEpisode ? "Session Live" : "Waiting for reset"} +
+
+ + + +
+
+ +
+
+

Episode

+ {hasValidEpisode ? ( +
+
Episode{obs.episode_id}
+
Task{obs.task_id}
+
Age / Sex{obs.age} / {obs.sex}
+
Step{obs.step_index}
+
Query budget{obs.remaining_query_budget}
+
Intervention budget{obs.remaining_intervention_budget}
+
+ ) : ( +

Start with Reset Episode. Until then, step actions are blocked.

+ )} + {noBudgetsLeft && ( +

Query and intervention budgets are exhausted. Finish review to get final score.

+ )} + {isDone && ( +

+ Episode complete + {finalScore !== null ? ` • final score: ${finalScore.toFixed(3)}` : ""}. + Click Reset Episode to start a new case. +

+ )} +
+ +
+

Action Console

+
+ + +
+ + {action.action_type === "query_ddi" && ( +
+ setAction((a) => ({ ...a, drug_id_1: e.target.value }))} + /> + setAction((a) => ({ ...a, drug_id_2: e.target.value }))} + /> +
+ )} + + {action.action_type === "propose_intervention" && ( +
+ + + + setAction((a) => ({ ...a, proposed_new_drug_id: e.target.value })) + } + /> + setAction((a) => ({ ...a, rationale: e.target.value }))} + /> +
+ )} + +
+ +
+

Current Medications

+
+ {(obs?.current_medications || []).map((m) => ( +
+ {m.drug_id} +

{m.generic_name}

+ {m.dose_mg} mg • {m.atc_class} +
+ ))} +
+
+ +
+

Event Log

+
+ {log.map((line, idx) => ( +
{line}
+ ))} +
+
+
+
+
+ ); +} diff --git a/openenv-polypharmacy/frontend/src/main.jsx b/openenv-polypharmacy/frontend/src/main.jsx new file mode 100644 index 0000000000000000000000000000000000000000..5733886c4cff3e43049f0daddcb06387ffd341d1 --- /dev/null +++ b/openenv-polypharmacy/frontend/src/main.jsx @@ -0,0 +1,10 @@ +import React from "react"; +import ReactDOM from "react-dom/client"; +import App from "./App"; +import "./styles.css"; + +ReactDOM.createRoot(document.getElementById("root")).render( + + + +); diff --git a/openenv-polypharmacy/frontend/src/styles.css b/openenv-polypharmacy/frontend/src/styles.css new file mode 100644 index 0000000000000000000000000000000000000000..e1534908aabae5c05be55664e7bec336d971909e --- /dev/null +++ b/openenv-polypharmacy/frontend/src/styles.css @@ -0,0 +1,383 @@ +:root { + --bg: #070814; + --bg-layer: #0a1026; + --panel: rgba(14, 22, 44, 0.72); + --panel-solid: rgba(20, 28, 52, 0.92); + --text: #e8f1ff; + --muted: #9ab2db; + --primary: #37d4ff; + --primary-2: #5a8dff; + --accent: #9d59ff; + --success: #6dfbcf; + --border: rgba(122, 162, 255, 0.28); + --line: rgba(109, 143, 225, 0.18); + --shadow: 0 16px 45px rgba(5, 8, 23, 0.6); + --shadow-strong: 0 14px 32px rgba(44, 105, 255, 0.4); +} + +* { + box-sizing: border-box; +} + +body { + margin: 0; + color: var(--text); + font-family: "Segoe UI", "SF Pro Text", "Helvetica Neue", sans-serif; + background: + radial-gradient(circle at 8% 12%, rgba(121, 87, 255, 0.22), transparent 38%), + radial-gradient(circle at 88% 20%, rgba(59, 204, 255, 0.26), transparent 34%), + radial-gradient(circle at 50% 100%, rgba(43, 128, 255, 0.26), transparent 40%), + linear-gradient(145deg, var(--bg) 0%, var(--bg-layer) 60%, #04060f 100%); + background-attachment: fixed; +} + +.shell { + min-height: 100vh; + position: relative; + overflow: hidden; + padding: 24px 16px 34px; +} + +.container { + width: min(1320px, 100%); + margin: 0 auto; + position: relative; + z-index: 2; +} + +.bg-orb { + position: absolute; + border-radius: 50%; + pointer-events: none; + opacity: 0.9; + filter: blur(18px); +} + +.orb-a { + width: min(46vw, 530px); + aspect-ratio: 1 / 1; + right: -9%; + top: -10%; + background: radial-gradient(circle, rgba(52, 203, 255, 0.35), rgba(52, 203, 255, 0.04) 70%); +} + +.orb-b { + width: min(40vw, 460px); + aspect-ratio: 1 / 1; + left: -9%; + bottom: -15%; + background: radial-gradient(circle, rgba(160, 102, 255, 0.3), rgba(160, 102, 255, 0.06) 72%); +} + +.glass { + background: + linear-gradient(180deg, rgba(255, 255, 255, 0.06), rgba(255, 255, 255, 0.01)), + var(--panel); + border: 1px solid var(--border); + box-shadow: var(--shadow); + backdrop-filter: blur(12px); +} + +.topbar { + border-radius: 24px; + padding: clamp(14px, 2vw, 20px); + display: grid; + gap: 12px 16px; + grid-template-columns: minmax(220px, 1.2fr) auto minmax(280px, 1fr); + align-items: center; +} + +.title-wrap h1 { + margin: 0; + font-size: clamp(1.15rem, 2.2vw, 1.95rem); + letter-spacing: 0.02em; + text-transform: uppercase; + text-shadow: 0 0 16px rgba(106, 192, 255, 0.3); +} + +.title-wrap p { + margin: 6px 0 0; + font-size: 0.84rem; + color: var(--muted); + letter-spacing: 0.03em; + text-transform: uppercase; +} + +.status-chip { + justify-self: center; + padding: 7px 14px; + border-radius: 999px; + font-size: 0.72rem; + font-weight: 700; + letter-spacing: 0.08em; + text-transform: uppercase; + border: 1px solid transparent; +} + +.status-chip.live { + color: #052c24; + background: linear-gradient(90deg, rgba(126, 255, 220, 0.9), rgba(84, 244, 196, 0.95)); + box-shadow: 0 0 14px rgba(96, 244, 198, 0.36); +} + +.status-chip.idle { + color: #d8e8ff; + border-color: rgba(117, 186, 255, 0.48); + background: rgba(60, 106, 198, 0.25); +} + +.actions { + display: flex; + justify-content: flex-end; + flex-wrap: wrap; + gap: 10px; +} + +button, +select, +input { + width: 100%; + min-height: 42px; + border-radius: 12px; + border: 1px solid var(--border); + font-size: 0.92rem; + padding: 10px 12px; + color: var(--text); + background: rgba(11, 19, 38, 0.84); +} + +select, +input { + transition: border-color 120ms ease, box-shadow 120ms ease; +} + +select:focus, +input:focus { + outline: none; + border-color: rgba(119, 200, 255, 0.88); + box-shadow: 0 0 0 2px rgba(95, 187, 255, 0.18); +} + +button { + cursor: pointer; + border: 0; + width: auto; + font-weight: 700; + letter-spacing: 0.02em; + background: linear-gradient(135deg, var(--primary), var(--primary-2) 55%, var(--accent)); + box-shadow: var(--shadow-strong); + transition: transform 140ms ease, filter 140ms ease, box-shadow 140ms ease; +} + +button:hover { + transform: translateY(-1px); + filter: brightness(1.04); + box-shadow: 0 18px 32px rgba(50, 141, 255, 0.48); +} + +button:active { + transform: translateY(0); +} + +button.secondary { + background: linear-gradient(135deg, rgba(95, 185, 255, 0.9), rgba(154, 102, 255, 0.86)); +} + +button:disabled { + opacity: 0.56; + cursor: not-allowed; + filter: grayscale(0.2); + box-shadow: none; + transform: none; +} + +.layout { + margin-top: 16px; + display: grid; + gap: 14px; + grid-template-columns: 1.12fr 0.88fr; + align-items: start; +} + +.panel { + border-radius: 20px; + padding: clamp(14px, 1.8vw, 20px); + position: relative; +} + +.panel::after { + content: ""; + position: absolute; + inset: 0; + border-radius: inherit; + border: 1px solid var(--line); + pointer-events: none; +} + +.panel-wide { + grid-column: 1 / -1; +} + +.panel h2 { + margin: 0 0 12px; + font-size: 1rem; + font-weight: 700; + letter-spacing: 0.05em; + text-transform: uppercase; +} + +.kpi-grid { + display: grid; + gap: 10px; + grid-template-columns: repeat(3, minmax(0, 1fr)); +} + +.kpi-grid div { + border-radius: 13px; + border: 1px solid var(--border); + background: var(--panel-solid); + padding: 11px 12px; +} + +.kpi-grid span { + display: block; + margin-bottom: 4px; + font-size: 0.72rem; + color: var(--muted); + text-transform: uppercase; + letter-spacing: 0.05em; +} + +.kpi-grid strong { + font-size: 1.06rem; + line-height: 1.2; +} + +.action-row, +.stack { + display: grid; + gap: 10px; + margin-bottom: 12px; +} + +.action-row label { + color: var(--muted); + font-size: 0.78rem; + letter-spacing: 0.05em; + text-transform: uppercase; +} + +.stack-two { + grid-template-columns: repeat(2, minmax(0, 1fr)); +} + +.med-grid { + display: grid; + grid-template-columns: repeat(3, minmax(0, 1fr)); + gap: 10px; + max-height: 430px; + overflow: auto; + padding-right: 4px; +} + +.med-card { + border-radius: 14px; + border: 1px solid var(--border); + background: var(--panel-solid); + padding: 11px 12px; + transition: transform 130ms ease, border-color 130ms ease; +} + +.med-card:hover { + transform: translateY(-1px); + border-color: rgba(109, 224, 255, 0.72); +} + +.med-card p { + margin: 6px 0 4px; + color: var(--muted); + text-transform: capitalize; +} + +.med-card small { + color: #c7d9ff; +} + +.logs { + max-height: 300px; + overflow: auto; + padding-right: 4px; + display: grid; + gap: 7px; + font-size: 0.84rem; + font-family: ui-monospace, SFMono-Regular, Menlo, Monaco, monospace; +} + +.logs div { + border-radius: 10px; + border: 1px solid var(--border); + background: rgba(10, 16, 31, 0.84); + padding: 8px 10px; + color: #dbebff; +} + +.muted { + margin: 0; + color: var(--muted); +} + +.budget-note { + margin-top: 10px; + border: 1px solid var(--border); + border-radius: 12px; + padding: 10px 12px; + background: rgba(13, 22, 42, 0.82); +} + +@media (max-width: 1180px) { + .layout { + grid-template-columns: 1fr; + } + + .topbar { + grid-template-columns: 1fr; + } + + .status-chip { + justify-self: start; + } + + .actions { + justify-content: flex-start; + } +} + +@media (max-width: 760px) { + .shell { + padding: 14px 10px 24px; + } + + .topbar, + .panel { + border-radius: 16px; + } + + .actions { + width: 100%; + } + + .actions button, + .actions select { + width: 100%; + } + + .kpi-grid, + .med-grid, + .stack-two { + grid-template-columns: 1fr; + } + + .logs { + max-height: 240px; + } +} diff --git a/openenv-polypharmacy/frontend/vite.config.js b/openenv-polypharmacy/frontend/vite.config.js new file mode 100644 index 0000000000000000000000000000000000000000..2a3f20a36de78020e9832ce22b3b8234ae1e5a13 --- /dev/null +++ b/openenv-polypharmacy/frontend/vite.config.js @@ -0,0 +1,10 @@ +import { defineConfig } from "vite"; +import react from "@vitejs/plugin-react"; + +export default defineConfig({ + plugins: [react()], + server: { + port: 5173, + host: "0.0.0.0", + }, +}); diff --git a/openenv-polypharmacy/inference.py b/openenv-polypharmacy/inference.py index 18406cd1aef5d8c9385df50057a357cd30bd04d7..a6809184af7dbc299ba4b8799eff00636647fb81 100644 --- a/openenv-polypharmacy/inference.py +++ b/openenv-polypharmacy/inference.py @@ -1,15 +1,14 @@ #!/usr/bin/env python3 """Baseline LLM inference script for the PolypharmacyEnv. -Uses the OpenAI Python client to drive an LLM agent through the +Uses Groq's OpenAI-compatible Chat Completions API to drive an LLM agent through the PolypharmacyEnv HTTP API. Emits structured stdout logs in the [START], [STEP], [END] format required by the OpenEnv evaluation spec. Environment variables: - OPENAI_API_KEY – required - API_BASE_URL – LLM endpoint (default: https://api.openai.com/v1) - MODEL_NAME – model to use (default: gpt-4.1) - HF_TOKEN – HuggingFace token (optional) + GROQ_API_KEY – required + GROQ_BASE_URL – optional (default: https://api.groq.com/openai/v1) + GROQ_MODEL_NAME – model to use (default: llama-3.1-8b-instant) POLYPHARMACY_ENV_URL – environment HTTP base URL (default: http://localhost:7860) """ @@ -18,7 +17,6 @@ from __future__ import annotations import json import os import sys -import time import uuid from typing import Any, Dict, List @@ -27,10 +25,9 @@ from openai import OpenAI # ── Configuration ──────────────────────────────────────────────────────────── -API_KEY = os.environ.get("OPENAI_API_KEY", "") -API_BASE = os.environ.get("API_BASE_URL", "https://api.openai.com/v1") -MODEL = os.environ.get("MODEL_NAME", "gpt-4.1") -HF_TOKEN = os.environ.get("HF_TOKEN", "") +MODEL = os.environ.get("GROQ_MODEL_NAME", "llama-3.1-8b-instant") +API_KEY = os.environ.get("GROQ_API_KEY", "") +API_BASE = os.environ.get("GROQ_BASE_URL", "https://api.groq.com/openai/v1") ENV_URL = os.environ.get("POLYPHARMACY_ENV_URL", "http://localhost:7860") TASKS = ["easy_screening", "budgeted_screening", "complex_tradeoff"] @@ -119,16 +116,16 @@ def _summarise_obs(obs: Dict[str, Any]) -> str: def _ask_llm(obs_summary: str) -> Dict[str, Any]: """Call the LLM and parse a PolypharmacyAction JSON.""" try: - resp = client.chat.completions.create( + chat_resp = client.chat.completions.create( model=MODEL, messages=[ {"role": "system", "content": SYSTEM_PROMPT}, {"role": "user", "content": obs_summary}, ], - temperature=0.2, max_tokens=256, + temperature=0.2, ) - text = resp.choices[0].message.content or "" + text = (chat_resp.choices[0].message.content or "").strip() # Strip markdown fences if present text = text.strip() if text.startswith("```"): @@ -146,7 +143,7 @@ def _ask_llm(obs_summary: str) -> Dict[str, Any]: def main() -> None: if not API_KEY: - _err("OPENAI_API_KEY is required") + _err("GROQ_API_KEY is required") sys.exit(1) run_id = str(uuid.uuid4())[:8] @@ -159,7 +156,6 @@ def main() -> None: "run_id": run_id, "task_id": task_id, "model": MODEL, - "api_base": API_BASE, "episodes": EPISODES_PER_TASK, }) diff --git a/openenv-polypharmacy/openenv.yaml b/openenv-polypharmacy/openenv.yaml index 6db62499e908e4244a846f216a136b50ea3476bc..695032aa05514c2e804d3199ef5a7ba417974f72 100644 --- a/openenv-polypharmacy/openenv.yaml +++ b/openenv-polypharmacy/openenv.yaml @@ -13,7 +13,7 @@ tags: - openenv type: space runtime: fastapi -app: polypharmacy_env.api.server:app +app: backend.main:app port: 7860 tasks: diff --git a/openenv-polypharmacy/pyproject.toml b/openenv-polypharmacy/pyproject.toml index 252e78b374d0f0bc25a9dac82a0c1d84e3b8dace..9bd219ea59455a8765851931c923b726ea32d1d9 100644 --- a/openenv-polypharmacy/pyproject.toml +++ b/openenv-polypharmacy/pyproject.toml @@ -13,6 +13,7 @@ dependencies = [ "pydantic>=2.0.0", "requests>=2.31.0", "openai>=1.0.0", + "python-dotenv>=1.0.0", "openenv-core>=0.2.0", ] @@ -25,11 +26,11 @@ dev = [ ] [tool.setuptools.packages.find] -where = ["src"] +where = ["backend/src"] [tool.pytest.ini_options] -testpaths = ["src/polypharmacy_env/tests"] -pythonpath = ["src"] +testpaths = ["backend/src/polypharmacy_env/tests"] +pythonpath = ["backend/src"] [tool.black] line-length = 99 diff --git a/openenv-polypharmacy/requirements.txt b/openenv-polypharmacy/requirements.txt index 8c3fddc07ec2557f30b561659bbead738a820776..82f21ff0993d8328c16385ebf07082f3318ecf27 100644 --- a/openenv-polypharmacy/requirements.txt +++ b/openenv-polypharmacy/requirements.txt @@ -1,8 +1 @@ -fastapi>=0.104.0 -uvicorn>=0.24.0 -pydantic>=2.0.0 -requests>=2.31.0 -openai>=1.0.0 -httpx>=0.25.0 -openenv-core>=0.2.0 -pytest>=7.0.0 +-r backend/requirements.txt diff --git a/openenv-polypharmacy/scripts/dev_backend.sh b/openenv-polypharmacy/scripts/dev_backend.sh new file mode 100755 index 0000000000000000000000000000000000000000..83c2586f4d2a8ded9eed3a1c9817ef7bcc710c30 --- /dev/null +++ b/openenv-polypharmacy/scripts/dev_backend.sh @@ -0,0 +1,4 @@ +#!/usr/bin/env bash +set -euo pipefail + +uvicorn backend.main:app --reload --host 0.0.0.0 --port 7860 diff --git a/openenv-polypharmacy/scripts/dev_frontend.sh b/openenv-polypharmacy/scripts/dev_frontend.sh new file mode 100755 index 0000000000000000000000000000000000000000..d840f21d1f981bb07e20b9b055641ee198888cc2 --- /dev/null +++ b/openenv-polypharmacy/scripts/dev_frontend.sh @@ -0,0 +1,5 @@ +#!/usr/bin/env bash +set -euo pipefail + +cd frontend +npm run dev diff --git a/openenv-polypharmacy/scripts/inference.py b/openenv-polypharmacy/scripts/inference.py deleted file mode 100644 index ca6610cb0e37b30aa55d173564b18de7da162f72..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/scripts/inference.py +++ /dev/null @@ -1,217 +0,0 @@ -#!/usr/bin/env python3 -"""LLM-based inference agent for PolypharmacyEnv. - -Connects to a running OpenEnv server via WebSocket (using PolypharmacyClient) -and runs an LLM agent that reviews a patient's medication regimen. - -Usage: - # Start server first: - # uvicorn polypharmacy_env.api.server:app --port 7860 - - # Then run inference: - python scripts/inference.py --task easy_screening --seed 42 - python scripts/inference.py --task budgeted_screening --model gpt-4o -""" - -from __future__ import annotations - -import argparse -import asyncio -import json -import os -import sys -from typing import Any, Dict, List - -# Add src to path -sys.path.insert(0, os.path.join(os.path.dirname(__file__), "..", "src")) - -from polypharmacy_env.client import PolypharmacyClient -from polypharmacy_env.models import PolypharmacyAction, PolypharmacyObservation - -try: - from openai import OpenAI -except ImportError: - OpenAI = None # type: ignore[assignment, misc] - - -def format_observation_for_llm(obs: PolypharmacyObservation) -> str: - """Convert an observation to a human-readable prompt for the LLM.""" - lines = [ - f"Patient: {obs.age}yo {obs.sex}", - f"Conditions: {', '.join(obs.conditions)}", - f"eGFR: {obs.eGFR_category}, Liver: {obs.liver_function_category}", - f"Step: {obs.step_index}", - f"Query budget remaining: {obs.remaining_query_budget}", - f"Intervention budget remaining: {obs.remaining_intervention_budget}", - "", - "Current Medications:", - ] - for med in obs.current_medications: - flags = f" [BEERS: {', '.join(med.beers_flags)}]" if med.beers_flags else "" - high_risk = " [HIGH RISK ELDERLY]" if med.is_high_risk_elderly else "" - lines.append( - f" - {med.drug_id} ({med.generic_name}) {med.atc_class} " - f"{med.dose_mg}mg{high_risk}{flags}" - ) - - if obs.interaction_queries: - lines.append("") - lines.append("DDI Queries So Far:") - for q in obs.interaction_queries: - lines.append( - f" - {q.drug_id_1} + {q.drug_id_2}: " - f"severity={q.severity}, rec={q.recommendation}" - ) - - if obs.interventions: - lines.append("") - lines.append("Interventions So Far:") - for iv in obs.interventions: - lines.append(f" - {iv.action_type} {iv.target_drug_id}: {iv.rationale}") - - return "\n".join(lines) - - -SYSTEM_PROMPT = """\ -You are a clinical pharmacist assistant reviewing an elderly patient's medication regimen. - -Your goal: identify dangerous drug-drug interactions and Beers Criteria violations, -then propose safe interventions (stop, dose_reduce, substitute, add_monitoring) to -reduce risk while preserving therapeutic coverage. - -Available actions (respond with JSON): -1. {"action_type": "query_ddi", "drug_id_1": "...", "drug_id_2": "..."} - - Check for a drug-drug interaction between two medications. -2. {"action_type": "propose_intervention", "target_drug_id": "...", \ -"intervention_type": "stop|dose_reduce|substitute|add_monitoring", "rationale": "..."} - - Propose a change to the regimen. -3. {"action_type": "finish_review"} - - End the review and submit your final regimen. - -Strategy tips: -- Query high-risk drug pairs first (especially those flagged as high-risk elderly or Beers). -- Prioritise resolving severe DDIs over moderate ones. -- Prefer substitution over stopping when possible. -- Always provide a clinical rationale for interventions. -- Finish the review when you've addressed all major issues or exhausted your budget. - -Respond with ONLY a valid JSON action object, no explanation outside the JSON.\ -""" - - -def parse_llm_action(text: str) -> PolypharmacyAction: - """Parse an LLM response into a PolypharmacyAction.""" - text = text.strip() - # Extract JSON from markdown code blocks if present - if "```" in text: - parts = text.split("```") - for part in parts: - part = part.strip() - if part.startswith("json"): - part = part[4:].strip() - if part.startswith("{"): - text = part - break - - data = json.loads(text) - return PolypharmacyAction(**data) - - -async def run_llm_episode( - base_url: str, - task_id: str, - seed: int, - model: str, - max_retries: int = 3, -) -> Dict[str, Any]: - """Run a single episode with LLM agent via WebSocket.""" - if OpenAI is None: - raise ImportError("openai package is required. Install with: pip install openai") - - llm = OpenAI() - total_reward = 0.0 - steps = 0 - messages: List[Dict[str, str]] = [{"role": "system", "content": SYSTEM_PROMPT}] - - async with PolypharmacyClient(base_url=base_url) as client: - result = await client.reset(task_id=task_id, seed=seed) - obs = result.observation - - while not result.done: - obs_text = format_observation_for_llm(obs) - messages.append({"role": "user", "content": obs_text}) - - # Call LLM - action = None - for attempt in range(max_retries): - try: - response = llm.chat.completions.create( - model=model, - messages=messages, - temperature=0.0, - max_tokens=256, - ) - llm_text = response.choices[0].message.content or "" - messages.append({"role": "assistant", "content": llm_text}) - action = parse_llm_action(llm_text) - break - except (json.JSONDecodeError, Exception) as e: - if attempt == max_retries - 1: - print(f" LLM parse failed after {max_retries} attempts: {e}") - action = PolypharmacyAction(action_type="finish_review") - else: - messages.append({ - "role": "user", - "content": f"Invalid JSON. Please respond with only a valid JSON action. Error: {e}", - }) - - assert action is not None - result = await client.step(action) - obs = result.observation - total_reward += result.reward or 0.0 - steps += 1 - - print( - f" step={steps} action={action.action_type} " - f"reward={result.reward:.4f} done={result.done}" - ) - - return { - "task_id": task_id, - "seed": seed, - "total_reward": total_reward, - "steps": steps, - } - - -async def amain(args: argparse.Namespace) -> None: - results = [] - for seed in range(args.seed, args.seed + args.episodes): - print(f"\n=== Episode: task={args.task} seed={seed} ===") - result = await run_llm_episode( - base_url=args.url, - task_id=args.task, - seed=seed, - model=args.model, - ) - results.append(result) - print(f" => reward={result['total_reward']:.4f} steps={result['steps']}") - - if results: - avg_reward = sum(r["total_reward"] for r in results) / len(results) - print(f"\nAverage reward over {len(results)} episodes: {avg_reward:.4f}") - - -def main() -> None: - parser = argparse.ArgumentParser(description="Run LLM agent on PolypharmacyEnv") - parser.add_argument("--url", default="ws://localhost:7860", help="Server URL") - parser.add_argument("--task", default="budgeted_screening", help="Task ID") - parser.add_argument("--seed", type=int, default=0, help="Starting seed") - parser.add_argument("--episodes", type=int, default=1, help="Number of episodes") - parser.add_argument("--model", default="gpt-4o", help="LLM model name") - args = parser.parse_args() - asyncio.run(amain(args)) - - -if __name__ == "__main__": - main() diff --git a/openenv-polypharmacy/scripts/run_validation.sh b/openenv-polypharmacy/scripts/run_validation.sh index 3e52345c08b0f5f0d8f9d9f9061bb3f1e648eea1..903c8176803d36fa91643db5aa55b521f7d725e5 100755 --- a/openenv-polypharmacy/scripts/run_validation.sh +++ b/openenv-polypharmacy/scripts/run_validation.sh @@ -5,11 +5,11 @@ set -euo pipefail cd "$(dirname "$0")/.." echo "=== Running unit tests ===" -PYTHONPATH=src python3 -m pytest src/polypharmacy_env/tests/ -v +PYTHONPATH=backend/src python3 -m pytest backend/src/polypharmacy_env/tests/ -v echo "" echo "=== Running heuristic baseline ===" -PYTHONPATH=src python3 -m polypharmacy_env.baselines.heuristic_agent +PYTHONPATH=backend/src python3 -m polypharmacy_env.baselines.heuristic_agent echo "" echo "=== Validation complete ===" diff --git a/openenv-polypharmacy/src/polypharmacy_env.egg-info/PKG-INFO b/openenv-polypharmacy/src/polypharmacy_env.egg-info/PKG-INFO deleted file mode 100644 index 05d83d9ac7e4cc3b71e1f66256af405eff75afe5..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/src/polypharmacy_env.egg-info/PKG-INFO +++ /dev/null @@ -1,15 +0,0 @@ -Metadata-Version: 2.4 -Name: polypharmacy-env -Version: 0.1.0 -Summary: OpenEnv environment for elderly polypharmacy medication-review safety -Requires-Python: >=3.10 -Requires-Dist: fastapi>=0.104.0 -Requires-Dist: uvicorn>=0.24.0 -Requires-Dist: pydantic>=2.0.0 -Requires-Dist: requests>=2.31.0 -Requires-Dist: openai>=1.0.0 -Provides-Extra: dev -Requires-Dist: pytest>=7.0.0; extra == "dev" -Requires-Dist: httpx>=0.25.0; extra == "dev" -Requires-Dist: black; extra == "dev" -Requires-Dist: isort; extra == "dev" diff --git a/openenv-polypharmacy/src/polypharmacy_env.egg-info/SOURCES.txt b/openenv-polypharmacy/src/polypharmacy_env.egg-info/SOURCES.txt deleted file mode 100644 index a2a2806957201f7f0f7b66e1d11408f3a340b983..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/src/polypharmacy_env.egg-info/SOURCES.txt +++ /dev/null @@ -1,25 +0,0 @@ -README.md -pyproject.toml -src/polypharmacy_env/__init__.py -src/polypharmacy_env/config.py -src/polypharmacy_env/data_loader.py -src/polypharmacy_env/ddi_simulator.py -src/polypharmacy_env/env_core.py -src/polypharmacy_env/graders.py -src/polypharmacy_env/models.py -src/polypharmacy_env/rewards.py -src/polypharmacy_env/tasks.py -src/polypharmacy_env.egg-info/PKG-INFO -src/polypharmacy_env.egg-info/SOURCES.txt -src/polypharmacy_env.egg-info/dependency_links.txt -src/polypharmacy_env.egg-info/requires.txt -src/polypharmacy_env.egg-info/top_level.txt -src/polypharmacy_env/api/__init__.py -src/polypharmacy_env/api/schemas.py -src/polypharmacy_env/api/server.py -src/polypharmacy_env/baselines/__init__.py -src/polypharmacy_env/baselines/heuristic_agent.py -src/polypharmacy_env/baselines/random_agent.py -src/polypharmacy_env/tests/__init__.py -src/polypharmacy_env/tests/test_api.py -src/polypharmacy_env/tests/test_env_core.py \ No newline at end of file diff --git a/openenv-polypharmacy/src/polypharmacy_env.egg-info/dependency_links.txt b/openenv-polypharmacy/src/polypharmacy_env.egg-info/dependency_links.txt deleted file mode 100644 index 8b137891791fe96927ad78e64b0aad7bded08bdc..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/src/polypharmacy_env.egg-info/dependency_links.txt +++ /dev/null @@ -1 +0,0 @@ - diff --git a/openenv-polypharmacy/src/polypharmacy_env.egg-info/top_level.txt b/openenv-polypharmacy/src/polypharmacy_env.egg-info/top_level.txt deleted file mode 100644 index 672034d5f27570102fa576097cec1a9c0cec5810..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/src/polypharmacy_env.egg-info/top_level.txt +++ /dev/null @@ -1 +0,0 @@ -polypharmacy_env diff --git a/openenv-polypharmacy/src/polypharmacy_env/api/schemas.py b/openenv-polypharmacy/src/polypharmacy_env/api/schemas.py deleted file mode 100644 index 1dc599143ee121be0892ec2b3e39c202ac17bc53..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/src/polypharmacy_env/api/schemas.py +++ /dev/null @@ -1,21 +0,0 @@ -"""HTTP request/response schemas. - -These are re-exported from openenv.core.env_server.types for convenience. -The OpenEnv create_app server uses these types natively. -""" - -from openenv.core.env_server.types import ( - HealthResponse, - ResetRequest, - ResetResponse, - StepRequest, - StepResponse, -) - -__all__ = [ - "ResetRequest", - "StepRequest", - "ResetResponse", - "StepResponse", - "HealthResponse", -] diff --git a/openenv-polypharmacy/src/polypharmacy_env/api/server.py b/openenv-polypharmacy/src/polypharmacy_env/api/server.py deleted file mode 100644 index e905fa539ffe5f30266312ad3f231d9b6c8e15d4..0000000000000000000000000000000000000000 --- a/openenv-polypharmacy/src/polypharmacy_env/api/server.py +++ /dev/null @@ -1,21 +0,0 @@ -"""FastAPI server exposing the PolypharmacyEnv via OpenEnv HTTP endpoints. - -Uses openenv.core.env_server.http_server.create_app to create a -standards-compliant OpenEnv server with WebSocket support. -""" - -from __future__ import annotations - -from openenv.core.env_server.http_server import create_app - -from ..env_core import PolypharmacyEnv -from ..models import PolypharmacyAction, PolypharmacyObservation - -# Create the OpenEnv-compliant app using the framework's create_app. -# Pass the class (factory) so the server can create per-session instances. -app = create_app( - PolypharmacyEnv, - PolypharmacyAction, - PolypharmacyObservation, - env_name="polypharmacy_env", -)