Update app.py

app.py

@@ -63,6 +63,18 @@ async def zero_shot_predict(text):
     response = await structured_llm.achat(messages)
     return response.raw.rating
 
+rng = np.random.Generator(np.random.PCG64(1234))
+def random_few_shot_examples_fn(**kwargs):
+    if n_samples:=kwargs.get('n_samples'):
+        random_examples = train.shuffle(generator=rng)[:n_samples]
+    else:
+        random_examples = train.shuffle(generator=rng)[:5]
+
+    result_strs = []
+    for text, rating in zip(random_examples['text'], random_examples['label']):
+        result_strs.append(f"Text: {text}\nRating: {rating}")
+    return "\n\n".join(result_strs)
+
 few_shot_prompt_tmpl_str = """\
 The review text is below.
 ---------------------
@@ -83,18 +95,6 @@ few_shot_prompt_tmpl = PromptTemplate(
     function_mappings={"random_few_shot_examples": random_few_shot_examples_fn},
 )
 
-rng = np.random.Generator(np.random.PCG64(1234))
-def random_few_shot_examples_fn(**kwargs):
-    if n_samples:=kwargs.get('n_samples'):
-        random_examples = train.shuffle(generator=rng)[:n_samples]
-    else:
-        random_examples = train.shuffle(generator=rng)[:5]
-
-    result_strs = []
-    for text, rating in zip(random_examples['text'], random_examples['label']):
-        result_strs.append(f"Text: {text}\nRating: {rating}")
-    return "\n\n".join(result_strs)
-
 async def random_few_shot_predict(text, n_examples=5):
     tasks = []
     for _ in range(3):