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https://github.com/Monadical-SAS/reflector.git
synced 2025-12-21 04:39:06 +00:00
organize imports
This commit is contained in:
34
server.py
34
server.py
@@ -1,25 +1,23 @@
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import asyncio
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import datetime
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import os
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import io
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import numpy as np
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import json
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import os
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import uuid
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import wave
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from concurrent.futures import ThreadPoolExecutor
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from faster_whisper import WhisperModel
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import aiohttp_cors
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import jax.numpy as jnp
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import requests
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from aiohttp import web
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from aiortc import MediaStreamTrack, RTCPeerConnection, RTCSessionDescription
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from aiortc.contrib.media import MediaRelay
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from av import AudioFifo
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from faster_whisper import WhisperModel
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from loguru import logger
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from whisper_jax import FlaxWhisperPipline
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from utils.run_utils import run_in_executor
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from sortedcontainers import SortedDict
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from utils.run_utils import run_in_executor
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pcs = set()
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relay = MediaRelay()
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data_channel = None
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@@ -45,7 +43,7 @@ blacklisted_messages = [" Thank you.", " See you next time!",
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def get_title_and_summary(llm_input_text, last_timestamp):
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print("Generating title and summary")
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("Generating title and summary")
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# output = llm.generate(prompt)
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# Use monadical-ml to fire this query to an LLM and get result
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@@ -69,13 +67,13 @@ def get_title_and_summary(llm_input_text, last_timestamp):
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"prompt": prompt
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}
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# To-do: Handle unexpected output formats from the model
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# TODO : Handle unexpected output formats from the model
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try:
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response = requests.post(LLM_URL, headers=headers, json=data)
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output = json.loads(response.json()["results"][0]["text"])
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output["description"] = output.pop("summary")
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output["transcript"] = llm_input_text
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output["timestamp"] =\
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output["timestamp"] = \
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str(datetime.timedelta(seconds=round(last_timestamp)))
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incremental_responses.append(output)
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result = {
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@@ -84,13 +82,13 @@ def get_title_and_summary(llm_input_text, last_timestamp):
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}
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except Exception as e:
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print("Exception" + str(e))
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logger.info("Exception" + str(e))
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result = None
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return result
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def channel_log(channel, t, message):
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print("channel(%s) %s %s" % (channel.label, t, message))
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logger.info("channel(%s) %s %s" % (channel.label, t, message))
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def channel_send(channel, message):
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@@ -120,17 +118,18 @@ def channel_send_transcript(channel):
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if len(sorted_transcripts) >= 3:
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del sorted_transcripts[least_time]
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except Exception as e:
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print("Exception", str(e))
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logger.info("Exception", str(e))
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pass
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def get_transcription(frames):
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print("Transcribing..")
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logger.info("Transcribing..")
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sorted_transcripts[frames[0].time] = None
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# TODO:
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# Passing IO objects instead of temporary files throws an error
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# Passing ndarrays (typecasted with float) does not give any
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# transcription. Refer issue
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# transcription. Refer issue,
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# https://github.com/guillaumekln/faster-whisper/issues/369
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audiofilename = "test" + str(datetime.datetime.now())
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wf = wave.open(audiofilename, "wb")
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@@ -170,7 +169,7 @@ def get_transcription(frames):
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transcription_text += result_text
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except Exception as e:
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print("Exception" + str(e))
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logger.info("Exception" + str(e))
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pass
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result = {
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@@ -195,7 +194,7 @@ def get_final_summary_response():
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"summary": final_summary
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}
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with open("meeting_titles_and_summaries.txt", "a") as f:
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with open("./artefacts/meeting_titles_and_summaries.txt", "a") as f:
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f.write(json.dumps(incremental_responses))
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return response
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@@ -275,7 +274,6 @@ async def offer(request):
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if isinstance(message, str) and message.startswith("ping"):
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channel_send(channel, "pong" + message[4:])
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@pc.on("connectionstatechange")
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async def on_connectionstatechange():
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log_info("Connection state is " + pc.connectionState)
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