fsa

README.md

@@ -1,12 +1,13 @@
 ---
-title: Sw Test
-emoji: 🦀
-colorFrom: green
-colorTo: red
+title: Scienceworld Demo
+emoji: 🌍
+colorFrom: blue
+colorTo: blue
 sdk: streamlit
 sdk_version: 1.10.0
 app_file: app.py
 pinned: false
+license: mit
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

@@ -0,0 +1,52 @@
+import numpy as np
+import time
+import streamlit as st
+from scienceworld import ScienceWorldEnv
+
+st.title("ScienceWorld interactive demo")
+
+hash_env = lambda _: None
+
+import os
+stream = os.popen('java -version')
+output = stream.read()
+
+st.write('output')
+
+@st.cache(allow_output_mutation=True)
+def load_env():
+    simplification_str = 'easy'
+    task_idx = None
+
+    print('Loading envs')
+    step_limit = 100
+    env = ScienceWorldEnv("", None, step_limit, 0)
+
+    if task_idx is None:
+        task_idx = 13
+    if isinstance(task_idx, int):
+        task_names = env.getTaskNames()
+        task_name = task_names[task_idx]
+    else:
+        task_name = task_idx
+
+    # Just reset to variation 0, as another call (e.g. reset_with_variation...) will setup
+    # an appropriate variation (train/dev/test)
+    env.load(task_name, 0, simplification_str)
+    obs, info = env.resetWithVariation(0, simplification_str)
+
+    return env, obs, info
+
+
+class RandomAgent():
+
+    def act(self, info):
+        return np.random.choice(info['valid'])
+
+
+num_episodes = 10
+env, initial_obs, initial_info = load_env()
+act = st.text_input('action to perform')
+st.write(f'Action: {act}')
+obs, reward, done, info = env.step(act)
+st.write(f'Observation: {obs.strip()}')

packages.txt

@@ -0,0 +1,2 @@
+default-jre
+default-jdk

requirements.txt

@@ -0,0 +1,4 @@
+numpy
+py4j
+scienceworld
+