Upload 2 files

app.py

@@ -10,7 +10,7 @@ import whisper
 import ffmpeg
 import re
 import tempfile
-import openai
+from huggingface_hub import InferenceClient
 
 st.set_page_config(layout="wide", initial_sidebar_state="collapsed")
 
@@ -28,6 +28,15 @@ Transcript:
  {} \n\n Article:"""
 
 
+LLM = {
+    "llama3-8b": {'prompt': f"""<|begin_of_text|><|start_header_id|>user<|end_header_id|>
+
+{PROMPT}<|eot_id|><|start_header_id|>assistant<|end_header_id|>
+
+
+""", 'endpoint': "meta-llama/Meta-Llama-3-8B-Instruct"}
+}
+
 @st.cache_resource()
 def load_whisper(model):
     return whisper.load_model(model)
@@ -59,16 +68,11 @@ def convert_to_audio(video_filename):
 
 
 @st.cache_data
-def summarise(prompt, model="gpt-3.5-turbo"):
-    if openai.api_key is None:
-        return "No OpenAI API Key provided."
-    messages = [{"role": "user", "content": prompt}]
-    response = openai.ChatCompletion.create(
-        model=model,
-        messages=messages,
-        temperature=0,
-    )
-    return response.choices[0].message["content"]
+def summarise(prompt, llm):
+    model = InferenceClient(LLM[llm]["endpoint"])
+    user_message = LLM[llm]["prompt"].format(prompt)
+    return model.text_generation(user_message,  max_new_tokens=1024)
+    
 
 
 def delete_files(video_filename, audio_filename):
@@ -122,7 +126,7 @@ def main():
             - Fetch transcript from YouTube API (if available) by clicking the **Fetch Transcript** button.
             - Transcribe the video using the Whisper model by clicking the **Transcribe (Whisper)** button.
         - The transcript will be displayed in a text area below.
-        - If you have an OpenAI API Key, you will be able to generate a summary of the transcript by ChatGPT.
+        - A summary of the transcript will also be generated by the selected LLM.
         - The summary will be displayed in a text area below.
         - You can download the video, audio, transcript or summary by clicking the respective download buttons.
         """
@@ -131,9 +135,7 @@ def main():
     whisper_model = load_whisper("base")
 
     url = c2.text_input("Enter the video URL")
-    open_ai_key = c2.text_input("Enter your OpenAI API Key")
-    if open_ai_key != "":
-        openai.api_key = open_ai_key
+    llm = c2.selectbox("Select LLM", list(LLM.keys()), index=0)
     fetch_button = c2.button("Fetch")
     st.session_state.setdefault("load_state", False)
 
@@ -141,10 +143,10 @@ def main():
         st.session_state.load_state = True
 
         if url:
-            process_video(url, whisper_model)
+            process_video(url, whisper_model, llm)
 
 
-def process_video(url, whisper_model):
+def process_video(url, whisper_model, llm):
     yt = YouTube(url)
     video_id = yt.video_id
     try:
@@ -176,7 +178,7 @@ def process_video(url, whisper_model):
     col1, col2, col3, col4 = st.columns(4)
 
     if "youtube" in url or "youtu.be" in url:
-        process_youtube_video(video_id, col3, emp, text_filename)
+        process_youtube_video(video_id, col3, emp, text_filename, llm)
 
     process_whisper_transcript(whisper_model, audio_filename, col4, text_filename)
 
@@ -191,7 +193,7 @@ def process_video(url, whisper_model):
                 get_media_download_link("audio", audio_filename)
 
 
-def process_youtube_video(video_id, col, emp, text_filename):
+def process_youtube_video(video_id, col, emp, text_filename, llm):
     try:
         transcript_list = YouTubeTranscriptApi.list_transcripts(video_id)
         transcripts = [transcript for transcript in transcript_list]
@@ -221,7 +223,7 @@ def process_youtube_video(video_id, col, emp, text_filename):
                     st.download_button("Download Transcript", modified_text, text_filename)
                 with c2:
                     openai_summarization = summarise(
-                        PROMPT.format(modified_text)
+                        modified_text, llm
                     )
                     summarized_text = st.text_area(
                         "Summarized Transcript", openai_summarization, height=500

requirements.txt

@@ -5,5 +5,4 @@ pytube
 youtube-transcript-api
 openai-whisper
 moviepy
-transformers
-openai==0.28
+huggingface-hub