use faster-whisper pipeline

trials/api.py

@@ -0,0 +1,56 @@
+import requests
+import spacy
+
+# This is the URL of text-generation-webui
+URL = "http://216.153.52.83:5000/api/v1/generate"
+
+headers = {
+    "Content-Type": "application/json"
+}
+
+
+def split_text_file(filename, token_count):
+    nlp = spacy.load('en_core_web_md')
+
+    with open(filename, 'r') as file:
+        text = file.read()
+
+    doc = nlp(text)
+    total_tokens = len(doc)
+
+    parts = []
+    start_index = 0
+
+    while start_index < total_tokens:
+        end_index = start_index + token_count
+        part_tokens = doc[start_index:end_index-5]
+        part = ' '.join(token.text for token in part_tokens)
+        parts.append(part)
+        start_index = end_index
+
+    return parts
+
+
+final_summary = ""
+parts = split_text_file("transcript.txt", 1600)
+previous_summary = ""
+
+for part in parts:
+    prompt = f"""
+              ### Human:
+             Given the following text, distill the most important information 
+             into a short summary:  {part}
+
+              ### Assistant:
+              """
+    data = {
+            "prompt": prompt
+    }
+    try:
+        response = requests.post(URL, headers=headers, json=data)
+        print(response.json())
+    except Exception as e:
+        print(str(e))
+
+with open("sum.txt", "w") as sum:
+    sum.write(" ".join(final_summary))