Api for writing task 2 v1.

testing.py

@@ -1,12 +1,37 @@
-import whisper
-import os
-from pydub import AudioSegment
+from functools import reduce
+from helper.token_counter import count_tokens
 
-model = whisper.load_model("base")
-file_path = "audio-samples/mynameisjeff.wav"
-audio_file = AudioSegment.from_file(file_path)
-if os.path.exists(file_path):
-    result = model.transcribe(file_path, fp16=False, language='English', verbose=True)
-    print(result["text"])
-else:
-    print("File not found:", file_path)
+# model = whisper.load_model("base")
+# file_path = "audio-samples/mynameisjeff.wav"
+# audio_file = AudioSegment.from_file(file_path)
+# if os.path.exists(file_path):
+#     result = model.transcribe(file_path, fp16=False, language='English', verbose=True)
+#     print(result["text"])
+# else:
+#     print("File not found:", file_path)
+
+messages = [
+    {
+        "role": "system",
+        "content": "You are a IELTS examiner.",
+    },
+    {
+        "role": "system",
+        "content": f"The question you have to grade is of type and is the following: ",
+    },
+    {
+        "role": "system",
+        "content": "Please provide a JSON object response with the overall grade and breakdown grades, "
+                   "formatted as follows: {'overall': 7.0, 'task_response': {'Task Achievement': 8.0, "
+                   "'Coherence and Cohesion': 6.5, 'Lexical Resource': 7.5, 'Grammatical Range and Accuracy': "
+                   "6.0}}",
+    },
+    {
+        "role": "user",
+        "content": f"Evaluate this answer according to ielts grading system:",
+    },
+]
+token_count = reduce(lambda count, item: count + count_tokens(item)['n_tokens'],
+                     map(lambda x: x["content"], filter(lambda x: "content" in x, messages)), 0)
+
+print(token_count)