Initiate "AvatarChatbot" (audio) example

[ctao456]

Description

Initiate AvatarChatbot (audio) example

Issues

RFC Link: https://github.com/opea-project/docs/blob/main/community/rfcs/24-08-02-OPEA-AIAvatarChatbot.md

Fixed commented issues in #523

Type of change

List the type of change like below. Please delete options that are not relevant.

• Bug fix (non-breaking change which fixes an issue)
• New feature (non-breaking change which adds new functionality)
• Breaking change (fix or feature that would break existing design and interface)
• Others (enhancement, documentation, validation, etc.)

Dependencies

PR for adding "animation" component: opea-project/GenAIComps#775

Tests

curl http://${host_ip}:3009/v1/avatarchatbot
-X POST
-d @sample_whoareyou.json
-H 'Content-Type: application/json'

If the megaservice is running properly, you should see the following output:

"/outputs/result.mp4"

[louie-tsai]

looks good. some minor feedbacks.

[ctao456]

There was an error with the latest "whisper-gaudi" docker image in GenAIComps that's causing the CI Docker container not starting properly:

$ docker run -p 7066:7066 --runtime=habana -e HABANA_VISIBLE_DEVICES=all -e OMPI_MCA_btl_vader_single_copy_mechanism=none --cap-add=sys_nice --ipc=host -e http_proxy=$http_proxy -e https_proxy=$https_proxy opea/whisper-gaudi:comp

[WARNING|utils.py:212] 2024-10-22 22:45:21,543 >> optimum-habana v1.14.0 has been validated for SynapseAI v1.18.0 but habana-frameworks v1.16.1.7 was found, this could lead to undefined behavior!
[WARNING|utils.py:225] 2024-10-22 22:45:22,337 >> optimum-habana v1.14.0 has been validated for SynapseAI v1.18.0 but the driver version is v1.16.2, this could lead to undefined behavior!
/home/user/.local/lib/python3.10/site-packages/transformers/deepspeed.py:24: FutureWarning: transformers.deepspeed module is deprecated and will be removed in a future version. Please import deepspeed modules directly from transformers.integrations
  warnings.warn(
============================= HABANA PT BRIDGE CONFIGURATION =========================== 
 PT_HPU_LAZY_MODE = 1
 PT_RECIPE_CACHE_PATH = 
 PT_CACHE_FOLDER_DELETE = 0
 PT_HPU_RECIPE_CACHE_CONFIG = 
 PT_HPU_MAX_COMPOUND_OP_SIZE = 9223372036854775807
 PT_HPU_LAZY_ACC_PAR_MODE = 1
 PT_HPU_ENABLE_REFINE_DYNAMIC_SHAPES = 0
---------------------------: System Configuration :---------------------------
Num CPU Cores : 152
CPU RAM       : 1056439240 KB
------------------------------------------------------------------------------
Downloading model: openai/whisper-small
[ASR] fetch warmup audio...
[ASR] warmup...
Traceback (most recent call last):
  File "/home/user/comps/asr/whisper/dependency/whisper_server.py", line 62, in <module>
    asr = WhisperModel(model_name_or_path=args.model_name_or_path, language=args.language, device=args.device)
  File "/home/user/comps/asr/whisper/dependency/whisper_model.py", line 36, in __init__
    self._warmup_whisper_hpu_graph("https://github.com/Spycsh/assets/raw/main/ljspeech_60s_audio.wav")
  File "/home/user/comps/asr/whisper/dependency/whisper_model.py", line 100, in _warmup_whisper_hpu_graph
    _ = self.model.generate(
  File "/home/user/.local/lib/python3.10/site-packages/transformers/models/whisper/generation_whisper.py", line 520, in generate
    timestamp_begin = self._set_return_timestamps(
  File "/home/user/.local/lib/python3.10/site-packages/transformers/models/whisper/generation_whisper.py", line 1188, in _set_return_timestamps
    raise ValueError(
ValueError: You have passed more than 3000 mel input features (> 30 seconds) which automatically enables long-form generation which requires the model to predict timestamp tokens. Please either pass `return_timestamps=True` or make sure to pass no more than 3000 mel input features.

The above issue is causing one check fail now for this PR. It was not related to changes from this PR.

[chensuyue]

Pending on issue opea-project/GenAIComps#817