mirror of
https://github.com/Monadical-SAS/reflector.git
synced 2025-12-20 20:29:06 +00:00
Merge pull request #85 from Monadical-SAS/feat-server-pipeline
Backend refactoring
This commit is contained in:
GitHub
16
.github/workflows/test_server.yml
vendored
16
.github/workflows/test_server.yml
vendored
@@ -39,7 +39,7 @@ jobs:
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cd server
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poetry run python -m pytest -v tests
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pep8:
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formatting:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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@@ -53,6 +53,20 @@ jobs:
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cd server
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black --check reflector tests
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linting:
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runs-on: ubuntu-latest
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steps:
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- uses: actions/checkout@v3
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- name: Set up Python 3.x
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uses: actions/setup-python@v4
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with:
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python-version: 3.11
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- name: Validate formatting
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run: |
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pip install ruff
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cd server
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ruff reflector tests
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docker:
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runs-on: ubuntu-latest
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steps:
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1
server/.gitignore
vendored
1
server/.gitignore
vendored
@@ -174,3 +174,4 @@ test_samples/
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.DS_Store
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.vscode/
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artefacts/
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audio_*.wav
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@@ -33,15 +33,28 @@ Then run the server:
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```
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# With a config.ini
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$ poetry run python -m reflector.server
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$ poetry run python -m reflector.app
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# Within a poetry env
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$ poetry shell
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$ LLM_URL=http://.../api/v1/generate python -m reflector.server
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$ LLM_URL=http://.../api/v1/generate python -m reflector.app
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```
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### Using local GPT4All
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- Start GPT4All with any model you want
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- Ensure the API server is activated in GPT4all
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- Run with: `LLM_BACKEND=openai LLM_URL=http://localhost:4891/v1/completions LLM_OPENAI_MODEL="GPT4All Falcon" python -m reflector.app`
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### Using local files
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```
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poetry run python -m reflector.tools.process path/to/audio.wav
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```
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# Old documentation
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This is the code base for the Reflector demo (formerly called agenda-talk-diff) for the leads : Troy Web Consulting
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285
server/poetry.lock
generated
285
server/poetry.lock
generated
@@ -677,27 +677,42 @@ pyyaml = ">=5.3,<7"
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[[package]]
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name = "dnspython"
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version = "2.4.0"
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version = "2.4.1"
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description = "DNS toolkit"
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optional = false
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python-versions = ">=3.8,<4.0"
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files = [
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{file = "dnspython-2.4.0-py3-none-any.whl", hash = "sha256:46b4052a55b56beea3a3bdd7b30295c292bd6827dd442348bc116f2d35b17f0a"},
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{file = "dnspython-2.4.0.tar.gz", hash = "sha256:758e691dbb454d5ccf4e1b154a19e52847f79e21a42fef17b969144af29a4e6c"},
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{file = "dnspython-2.4.1-py3-none-any.whl", hash = "sha256:5b7488477388b8c0b70a8ce93b227c5603bc7b77f1565afe8e729c36c51447d7"},
|
||||
{file = "dnspython-2.4.1.tar.gz", hash = "sha256:c33971c79af5be968bb897e95c2448e11a645ee84d93b265ce0b7aabe5dfdca8"},
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]
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[package.dependencies]
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httpcore = {version = ">=0.17.3", markers = "python_version >= \"3.8\""}
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sniffio = ">=1.1,<2.0"
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[package.extras]
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dnssec = ["cryptography (>=2.6,<42.0)"]
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doh = ["h2 (>=4.1.0)", "httpx (>=0.24.1)"]
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doh = ["h2 (>=4.1.0)", "httpcore (>=0.17.3)", "httpx (>=0.24.1)"]
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doq = ["aioquic (>=0.9.20)"]
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idna = ["idna (>=2.1,<4.0)"]
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trio = ["trio (>=0.14,<0.23)"]
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wmi = ["wmi (>=1.5.1,<2.0.0)"]
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[[package]]
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name = "fastapi"
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version = "0.100.1"
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description = "FastAPI framework, high performance, easy to learn, fast to code, ready for production"
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optional = false
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python-versions = ">=3.7"
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||||
files = [
|
||||
{file = "fastapi-0.100.1-py3-none-any.whl", hash = "sha256:ec6dd52bfc4eff3063cfcd0713b43c87640fefb2687bbbe3d8a08d94049cdf32"},
|
||||
{file = "fastapi-0.100.1.tar.gz", hash = "sha256:522700d7a469e4a973d92321ab93312448fbe20fca9c8da97effc7e7bc56df23"},
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||||
]
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||||
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[package.dependencies]
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pydantic = ">=1.7.4,<1.8 || >1.8,<1.8.1 || >1.8.1,<2.0.0 || >2.0.0,<2.0.1 || >2.0.1,<3.0.0"
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starlette = ">=0.27.0,<0.28.0"
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typing-extensions = ">=4.5.0"
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[package.extras]
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all = ["email-validator (>=2.0.0)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=2.11.2)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.5)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
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[[package]]
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name = "faster-whisper"
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version = "0.7.1"
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@@ -963,6 +978,53 @@ sniffio = "==1.*"
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http2 = ["h2 (>=3,<5)"]
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socks = ["socksio (==1.*)"]
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[[package]]
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name = "httptools"
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||||
version = "0.6.0"
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description = "A collection of framework independent HTTP protocol utils."
|
||||
optional = false
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||||
python-versions = ">=3.5.0"
|
||||
files = [
|
||||
{file = "httptools-0.6.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:818325afee467d483bfab1647a72054246d29f9053fd17cc4b86cda09cc60339"},
|
||||
{file = "httptools-0.6.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:72205730bf1be875003692ca54a4a7c35fac77b4746008966061d9d41a61b0f5"},
|
||||
{file = "httptools-0.6.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:33eb1d4e609c835966e969a31b1dedf5ba16b38cab356c2ce4f3e33ffa94cad3"},
|
||||
{file = "httptools-0.6.0-cp310-cp310-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:6bdc6675ec6cb79d27e0575750ac6e2b47032742e24eed011b8db73f2da9ed40"},
|
||||
{file = "httptools-0.6.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:463c3bc5ef64b9cf091be9ac0e0556199503f6e80456b790a917774a616aff6e"},
|
||||
{file = "httptools-0.6.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:82f228b88b0e8c6099a9c4757ce9fdbb8b45548074f8d0b1f0fc071e35655d1c"},
|
||||
{file = "httptools-0.6.0-cp310-cp310-win_amd64.whl", hash = "sha256:0781fedc610293a2716bc7fa142d4c85e6776bc59d617a807ff91246a95dea35"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:721e503245d591527cddd0f6fd771d156c509e831caa7a57929b55ac91ee2b51"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:274bf20eeb41b0956e34f6a81f84d26ed57c84dd9253f13dcb7174b27ccd8aaf"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:259920bbae18740a40236807915def554132ad70af5067e562f4660b62c59b90"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:03bfd2ae8a2d532952ac54445a2fb2504c804135ed28b53fefaf03d3a93eb1fd"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:f959e4770b3fc8ee4dbc3578fd910fab9003e093f20ac8c621452c4d62e517cb"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:6e22896b42b95b3237eccc42278cd72c0df6f23247d886b7ded3163452481e38"},
|
||||
{file = "httptools-0.6.0-cp311-cp311-win_amd64.whl", hash = "sha256:38f3cafedd6aa20ae05f81f2e616ea6f92116c8a0f8dcb79dc798df3356836e2"},
|
||||
{file = "httptools-0.6.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:47043a6e0ea753f006a9d0dd076a8f8c99bc0ecae86a0888448eb3076c43d717"},
|
||||
{file = "httptools-0.6.0-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:35a541579bed0270d1ac10245a3e71e5beeb1903b5fbbc8d8b4d4e728d48ff1d"},
|
||||
{file = "httptools-0.6.0-cp37-cp37m-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:65d802e7b2538a9756df5acc062300c160907b02e15ed15ba035b02bce43e89c"},
|
||||
{file = "httptools-0.6.0-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:26326e0a8fe56829f3af483200d914a7cd16d8d398d14e36888b56de30bec81a"},
|
||||
{file = "httptools-0.6.0-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:e41ccac9e77cd045f3e4ee0fc62cbf3d54d7d4b375431eb855561f26ee7a9ec4"},
|
||||
{file = "httptools-0.6.0-cp37-cp37m-win_amd64.whl", hash = "sha256:4e748fc0d5c4a629988ef50ac1aef99dfb5e8996583a73a717fc2cac4ab89932"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:cf8169e839a0d740f3d3c9c4fa630ac1a5aaf81641a34575ca6773ed7ce041a1"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:5dcc14c090ab57b35908d4a4585ec5c0715439df07be2913405991dbb37e049d"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0d0b0571806a5168013b8c3d180d9f9d6997365a4212cb18ea20df18b938aa0b"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0fb4a608c631f7dcbdf986f40af7a030521a10ba6bc3d36b28c1dc9e9035a3c0"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:93f89975465133619aea8b1952bc6fa0e6bad22a447c6d982fc338fbb4c89649"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:73e9d66a5a28b2d5d9fbd9e197a31edd02be310186db423b28e6052472dc8201"},
|
||||
{file = "httptools-0.6.0-cp38-cp38-win_amd64.whl", hash = "sha256:22c01fcd53648162730a71c42842f73b50f989daae36534c818b3f5050b54589"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:3f96d2a351b5625a9fd9133c95744e8ca06f7a4f8f0b8231e4bbaae2c485046a"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:72ec7c70bd9f95ef1083d14a755f321d181f046ca685b6358676737a5fecd26a"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b703d15dbe082cc23266bf5d9448e764c7cb3fcfe7cb358d79d3fd8248673ef9"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:82c723ed5982f8ead00f8e7605c53e55ffe47c47465d878305ebe0082b6a1755"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:b0a816bb425c116a160fbc6f34cece097fd22ece15059d68932af686520966bd"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:dea66d94e5a3f68c5e9d86e0894653b87d952e624845e0b0e3ad1c733c6cc75d"},
|
||||
{file = "httptools-0.6.0-cp39-cp39-win_amd64.whl", hash = "sha256:23b09537086a5a611fad5696fc8963d67c7e7f98cb329d38ee114d588b0b74cd"},
|
||||
{file = "httptools-0.6.0.tar.gz", hash = "sha256:9fc6e409ad38cbd68b177cd5158fc4042c796b82ca88d99ec78f07bed6c6b796"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
test = ["Cython (>=0.29.24,<0.30.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "httpx"
|
||||
version = "0.24.1"
|
||||
@@ -1282,13 +1344,13 @@ files = [
|
||||
|
||||
[[package]]
|
||||
name = "pathspec"
|
||||
version = "0.11.1"
|
||||
version = "0.11.2"
|
||||
description = "Utility library for gitignore style pattern matching of file paths."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "pathspec-0.11.1-py3-none-any.whl", hash = "sha256:d8af70af76652554bd134c22b3e8a1cc46ed7d91edcdd721ef1a0c51a84a5293"},
|
||||
{file = "pathspec-0.11.1.tar.gz", hash = "sha256:2798de800fa92780e33acca925945e9a19a133b715067cf165b8866c15a31687"},
|
||||
{file = "pathspec-0.11.2-py3-none-any.whl", hash = "sha256:1d6ed233af05e679efb96b1851550ea95bbb64b7c490b0f5aa52996c11e92a20"},
|
||||
{file = "pathspec-0.11.2.tar.gz", hash = "sha256:e0d8d0ac2f12da61956eb2306b69f9469b42f4deb0f3cb6ed47b9cce9996ced3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
@@ -1815,6 +1877,23 @@ docs = ["furo", "myst-parser", "prometheus-client", "sphinx", "sphinx-notfound-p
|
||||
tests = ["pytest", "pytest-asyncio"]
|
||||
typing = ["mypy (>=1.4)"]
|
||||
|
||||
[[package]]
|
||||
name = "starlette"
|
||||
version = "0.27.0"
|
||||
description = "The little ASGI library that shines."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "starlette-0.27.0-py3-none-any.whl", hash = "sha256:918416370e846586541235ccd38a474c08b80443ed31c578a418e2209b3eef91"},
|
||||
{file = "starlette-0.27.0.tar.gz", hash = "sha256:6a6b0d042acb8d469a01eba54e9cda6cbd24ac602c4cd016723117d6a7e73b75"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
anyio = ">=3.4.0,<5"
|
||||
|
||||
[package.extras]
|
||||
full = ["httpx (>=0.22.0)", "itsdangerous", "jinja2", "python-multipart", "pyyaml"]
|
||||
|
||||
[[package]]
|
||||
name = "structlog"
|
||||
version = "23.1.0"
|
||||
@@ -1962,6 +2041,188 @@ secure = ["certifi", "cryptography (>=1.9)", "idna (>=2.0.0)", "pyopenssl (>=17.
|
||||
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||
zstd = ["zstandard (>=0.18.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "uvicorn"
|
||||
version = "0.23.1"
|
||||
description = "The lightning-fast ASGI server."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "uvicorn-0.23.1-py3-none-any.whl", hash = "sha256:1d55d46b83ee4ce82b4e82f621f2050adb3eb7b5481c13f9af1744951cae2f1f"},
|
||||
{file = "uvicorn-0.23.1.tar.gz", hash = "sha256:da9b0c8443b2d7ee9db00a345f1eee6db7317432c9d4400f5049cc8d358383be"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
click = ">=7.0"
|
||||
colorama = {version = ">=0.4", optional = true, markers = "sys_platform == \"win32\" and extra == \"standard\""}
|
||||
h11 = ">=0.8"
|
||||
httptools = {version = ">=0.5.0", optional = true, markers = "extra == \"standard\""}
|
||||
python-dotenv = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
|
||||
pyyaml = {version = ">=5.1", optional = true, markers = "extra == \"standard\""}
|
||||
uvloop = {version = ">=0.14.0,<0.15.0 || >0.15.0,<0.15.1 || >0.15.1", optional = true, markers = "(sys_platform != \"win32\" and sys_platform != \"cygwin\") and platform_python_implementation != \"PyPy\" and extra == \"standard\""}
|
||||
watchfiles = {version = ">=0.13", optional = true, markers = "extra == \"standard\""}
|
||||
websockets = {version = ">=10.4", optional = true, markers = "extra == \"standard\""}
|
||||
|
||||
[package.extras]
|
||||
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{file = "websockets-11.0.3-cp37-cp37m-musllinux_1_1_aarch64.whl", hash = "sha256:6505c1b31274723ccaf5f515c1824a4ad2f0d191cec942666b3d0f3aa4cb4007"},
|
||||
{file = "websockets-11.0.3-cp37-cp37m-musllinux_1_1_i686.whl", hash = "sha256:f467ba0050b7de85016b43f5a22b46383ef004c4f672148a8abf32bc999a87f0"},
|
||||
{file = "websockets-11.0.3-cp37-cp37m-musllinux_1_1_x86_64.whl", hash = "sha256:9d9acd80072abcc98bd2c86c3c9cd4ac2347b5a5a0cae7ed5c0ee5675f86d9af"},
|
||||
{file = "websockets-11.0.3-cp37-cp37m-win32.whl", hash = "sha256:e590228200fcfc7e9109509e4d9125eace2042fd52b595dd22bbc34bb282307f"},
|
||||
{file = "websockets-11.0.3-cp37-cp37m-win_amd64.whl", hash = "sha256:b16fff62b45eccb9c7abb18e60e7e446998093cdcb50fed33134b9b6878836de"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:fb06eea71a00a7af0ae6aefbb932fb8a7df3cb390cc217d51a9ad7343de1b8d0"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:8a34e13a62a59c871064dfd8ffb150867e54291e46d4a7cf11d02c94a5275bae"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4841ed00f1026dfbced6fca7d963c4e7043aa832648671b5138008dc5a8f6d99"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:1a073fc9ab1c8aff37c99f11f1641e16da517770e31a37265d2755282a5d28aa"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:68b977f21ce443d6d378dbd5ca38621755f2063d6fdb3335bda981d552cfff86"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e1a99a7a71631f0efe727c10edfba09ea6bee4166a6f9c19aafb6c0b5917d09c"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-musllinux_1_1_aarch64.whl", hash = "sha256:bee9fcb41db2a23bed96c6b6ead6489702c12334ea20a297aa095ce6d31370d0"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-musllinux_1_1_i686.whl", hash = "sha256:4b253869ea05a5a073ebfdcb5cb3b0266a57c3764cf6fe114e4cd90f4bfa5f5e"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:1553cb82942b2a74dd9b15a018dce645d4e68674de2ca31ff13ebc2d9f283788"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-win32.whl", hash = "sha256:f61bdb1df43dc9c131791fbc2355535f9024b9a04398d3bd0684fc16ab07df74"},
|
||||
{file = "websockets-11.0.3-cp38-cp38-win_amd64.whl", hash = "sha256:03aae4edc0b1c68498f41a6772d80ac7c1e33c06c6ffa2ac1c27a07653e79d6f"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:777354ee16f02f643a4c7f2b3eff8027a33c9861edc691a2003531f5da4f6bc8"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:8c82f11964f010053e13daafdc7154ce7385ecc538989a354ccc7067fd7028fd"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:3580dd9c1ad0701169e4d6fc41e878ffe05e6bdcaf3c412f9d559389d0c9e016"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:6f1a3f10f836fab6ca6efa97bb952300b20ae56b409414ca85bff2ad241d2a61"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:df41b9bc27c2c25b486bae7cf42fccdc52ff181c8c387bfd026624a491c2671b"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:279e5de4671e79a9ac877427f4ac4ce93751b8823f276b681d04b2156713b9dd"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-musllinux_1_1_aarch64.whl", hash = "sha256:1fdf26fa8a6a592f8f9235285b8affa72748dc12e964a5518c6c5e8f916716f7"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:69269f3a0b472e91125b503d3c0b3566bda26da0a3261c49f0027eb6075086d1"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:97b52894d948d2f6ea480171a27122d77af14ced35f62e5c892ca2fae9344311"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-win32.whl", hash = "sha256:c7f3cb904cce8e1be667c7e6fef4516b98d1a6a0635a58a57528d577ac18a128"},
|
||||
{file = "websockets-11.0.3-cp39-cp39-win_amd64.whl", hash = "sha256:c792ea4eabc0159535608fc5658a74d1a81020eb35195dd63214dcf07556f67e"},
|
||||
{file = "websockets-11.0.3-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:f2e58f2c36cc52d41f2659e4c0cbf7353e28c8c9e63e30d8c6d3494dc9fdedcf"},
|
||||
{file = "websockets-11.0.3-pp37-pypy37_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:de36fe9c02995c7e6ae6efe2e205816f5f00c22fd1fbf343d4d18c3d5ceac2f5"},
|
||||
{file = "websockets-11.0.3-pp37-pypy37_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:0ac56b661e60edd453585f4bd68eb6a29ae25b5184fd5ba51e97652580458998"},
|
||||
{file = "websockets-11.0.3-pp37-pypy37_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e052b8467dd07d4943936009f46ae5ce7b908ddcac3fda581656b1b19c083d9b"},
|
||||
{file = "websockets-11.0.3-pp37-pypy37_pp73-win_amd64.whl", hash = "sha256:42cc5452a54a8e46a032521d7365da775823e21bfba2895fb7b77633cce031bb"},
|
||||
{file = "websockets-11.0.3-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:e6316827e3e79b7b8e7d8e3b08f4e331af91a48e794d5d8b099928b6f0b85f20"},
|
||||
{file = "websockets-11.0.3-pp38-pypy38_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:8531fdcad636d82c517b26a448dcfe62f720e1922b33c81ce695d0edb91eb931"},
|
||||
{file = "websockets-11.0.3-pp38-pypy38_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:c114e8da9b475739dde229fd3bc6b05a6537a88a578358bc8eb29b4030fac9c9"},
|
||||
{file = "websockets-11.0.3-pp38-pypy38_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e063b1865974611313a3849d43f2c3f5368093691349cf3c7c8f8f75ad7cb280"},
|
||||
{file = "websockets-11.0.3-pp38-pypy38_pp73-win_amd64.whl", hash = "sha256:92b2065d642bf8c0a82d59e59053dd2fdde64d4ed44efe4870fa816c1232647b"},
|
||||
{file = "websockets-11.0.3-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:0ee68fe502f9031f19d495dae2c268830df2760c0524cbac5d759921ba8c8e82"},
|
||||
{file = "websockets-11.0.3-pp39-pypy39_pp73-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:dcacf2c7a6c3a84e720d1bb2b543c675bf6c40e460300b628bab1b1efc7c034c"},
|
||||
{file = "websockets-11.0.3-pp39-pypy39_pp73-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b67c6f5e5a401fc56394f191f00f9b3811fe843ee93f4a70df3c389d1adf857d"},
|
||||
{file = "websockets-11.0.3-pp39-pypy39_pp73-manylinux_2_5_x86_64.manylinux1_x86_64.manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:1d5023a4b6a5b183dc838808087033ec5df77580485fc533e7dab2567851b0a4"},
|
||||
{file = "websockets-11.0.3-pp39-pypy39_pp73-win_amd64.whl", hash = "sha256:ed058398f55163a79bb9f06a90ef9ccc063b204bb346c4de78efc5d15abfe602"},
|
||||
{file = "websockets-11.0.3-py3-none-any.whl", hash = "sha256:6681ba9e7f8f3b19440921e99efbb40fc89f26cd71bf539e45d8c8a25c976dc6"},
|
||||
{file = "websockets-11.0.3.tar.gz", hash = "sha256:88fc51d9a26b10fc331be344f1781224a375b78488fc343620184e95a4b27016"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "win32-setctime"
|
||||
version = "1.1.0"
|
||||
@@ -2066,4 +2327,4 @@ multidict = ">=4.0"
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = "^3.11"
|
||||
content-hash = "d2b64390d1ea9038b6703b12060cdde1970b680a0ad891f24405323ff2ca0a60"
|
||||
content-hash = "d696a09d54edbfc0ab52bd4e7b1ba09f3930ac5d3156df511cc3094ddb7d6ac5"
|
||||
|
||||
@@ -18,6 +18,8 @@ sortedcontainers = "^2.4.0"
|
||||
loguru = "^0.7.0"
|
||||
pydantic-settings = "^2.0.2"
|
||||
structlog = "^23.1.0"
|
||||
uvicorn = {extras = ["standard"], version = "^0.23.1"}
|
||||
fastapi = "^0.100.1"
|
||||
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
||||
33
server/reflector/app.py
Normal file
33
server/reflector/app.py
Normal file
@@ -0,0 +1,33 @@
|
||||
from fastapi import FastAPI
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
from reflector.views.rtc_offer import router as rtc_offer_router
|
||||
from reflector.events import subscribers_startup, subscribers_shutdown
|
||||
from contextlib import asynccontextmanager
|
||||
|
||||
|
||||
# lifespan events
|
||||
@asynccontextmanager
|
||||
async def lifespan(app: FastAPI):
|
||||
for func in subscribers_startup:
|
||||
await func()
|
||||
yield
|
||||
for func in subscribers_shutdown:
|
||||
await func()
|
||||
|
||||
|
||||
# build app
|
||||
app = FastAPI(lifespan=lifespan)
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
allow_origins=["*"],
|
||||
allow_methods=["*"],
|
||||
allow_headers=["*"],
|
||||
)
|
||||
|
||||
# register views
|
||||
app.include_router(rtc_offer_router)
|
||||
|
||||
if __name__ == "__main__":
|
||||
import uvicorn
|
||||
|
||||
uvicorn.run("reflector.app:app", host="0.0.0.0", port=1250, reload=True)
|
||||
2
server/reflector/events.py
Normal file
2
server/reflector/events.py
Normal file
@@ -0,0 +1,2 @@
|
||||
subscribers_startup = []
|
||||
subscribers_shutdown = []
|
||||
3
server/reflector/llm/__init__.py
Normal file
3
server/reflector/llm/__init__.py
Normal file
@@ -0,0 +1,3 @@
|
||||
from .base import LLM # noqa: F401
|
||||
from . import llm_oobagooda # noqa: F401
|
||||
from . import llm_openai # noqa: F401
|
||||
67
server/reflector/llm/base.py
Normal file
67
server/reflector/llm/base.py
Normal file
@@ -0,0 +1,67 @@
|
||||
from reflector.logger import logger
|
||||
from reflector.settings import settings
|
||||
import asyncio
|
||||
import json
|
||||
import re
|
||||
|
||||
|
||||
class LLM:
|
||||
_registry = {}
|
||||
|
||||
@classmethod
|
||||
def register(cls, name, klass):
|
||||
cls._registry[name] = klass
|
||||
|
||||
@classmethod
|
||||
def instance(cls):
|
||||
"""
|
||||
Return an instance depending on the settings.
|
||||
Settings used:
|
||||
|
||||
- `LLM_BACKEND`: key of the backend, defaults to `oobagooda`
|
||||
- `LLM_URL`: url of the backend
|
||||
"""
|
||||
return cls._registry[settings.LLM_BACKEND]()
|
||||
|
||||
async def generate(
|
||||
self, prompt: str, retry_count: int = 5, retry_interval: int = 1, **kwargs
|
||||
) -> dict:
|
||||
while retry_count > 0:
|
||||
try:
|
||||
result = await self._generate(prompt=prompt, **kwargs)
|
||||
break
|
||||
except Exception:
|
||||
logger.exception("Failed to call llm")
|
||||
retry_count -= 1
|
||||
await asyncio.sleep(retry_interval)
|
||||
|
||||
if retry_count == 0:
|
||||
raise Exception("Failed to call llm after retrying")
|
||||
|
||||
if isinstance(result, str):
|
||||
result = self._parse_json(result)
|
||||
|
||||
return result
|
||||
|
||||
async def _generate(self, prompt: str, **kwargs) -> str:
|
||||
raise NotImplementedError
|
||||
|
||||
def _parse_json(self, result: str) -> dict:
|
||||
result = result.strip()
|
||||
# try detecting code block if exist
|
||||
# starts with ```json\n, ends with ```
|
||||
# or starts with ```\n, ends with ```
|
||||
# or starts with \n```javascript\n, ends with ```
|
||||
|
||||
regex = r"```(json|javascript|)?(.*)```"
|
||||
matches = re.findall(regex, result.strip(), re.MULTILINE | re.DOTALL)
|
||||
if matches:
|
||||
result = matches[0][1]
|
||||
|
||||
else:
|
||||
# maybe the prompt has been started with ```json
|
||||
# so if text ends with ```, just remove it and use it as json
|
||||
if result.endswith("```"):
|
||||
result = result[:-3]
|
||||
|
||||
return json.loads(result.strip())
|
||||
18
server/reflector/llm/llm_oobagooda.py
Normal file
18
server/reflector/llm/llm_oobagooda.py
Normal file
@@ -0,0 +1,18 @@
|
||||
from reflector.llm.base import LLM
|
||||
from reflector.settings import settings
|
||||
import httpx
|
||||
|
||||
|
||||
class OobagoodaLLM(LLM):
|
||||
async def _generate(self, prompt: str, **kwargs):
|
||||
async with httpx.AsyncClient() as client:
|
||||
response = await client.post(
|
||||
settings.LLM_URL,
|
||||
headers={"Content-Type": "application/json"},
|
||||
json={"prompt": prompt},
|
||||
)
|
||||
response.raise_for_status()
|
||||
return response.json()
|
||||
|
||||
|
||||
LLM.register("oobagooda", OobagoodaLLM)
|
||||
43
server/reflector/llm/llm_openai.py
Normal file
43
server/reflector/llm/llm_openai.py
Normal file
@@ -0,0 +1,43 @@
|
||||
from reflector.llm.base import LLM
|
||||
from reflector.logger import logger
|
||||
from reflector.settings import settings
|
||||
import httpx
|
||||
|
||||
|
||||
class OpenAILLM(LLM):
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self.openai_key = settings.LLM_OPENAI_KEY
|
||||
self.openai_url = settings.LLM_URL
|
||||
self.openai_model = settings.LLM_OPENAI_MODEL
|
||||
self.openai_temperature = settings.LLM_OPENAI_TEMPERATURE
|
||||
self.timeout = settings.LLM_TIMEOUT
|
||||
self.max_tokens = settings.LLM_MAX_TOKENS
|
||||
logger.info(f"LLM use openai backend at {self.openai_url}")
|
||||
|
||||
async def _generate(self, prompt: str, **kwargs) -> str:
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {self.openai_key}",
|
||||
}
|
||||
|
||||
logger.debug(f"LLM openai prompt: {prompt}")
|
||||
|
||||
async with httpx.AsyncClient(timeout=self.timeout) as client:
|
||||
response = await client.post(
|
||||
self.openai_url,
|
||||
headers=headers,
|
||||
json={
|
||||
"model": self.openai_model,
|
||||
"prompt": prompt,
|
||||
"max_tokens": self.max_tokens,
|
||||
"temperature": self.openai_temperature,
|
||||
},
|
||||
)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
logger.info(f"LLM openai result: {result}")
|
||||
return result["choices"][0]["text"]
|
||||
|
||||
|
||||
LLM.register("openai", OpenAILLM)
|
||||
9
server/reflector/processors/__init__.py
Normal file
9
server/reflector/processors/__init__.py
Normal file
@@ -0,0 +1,9 @@
|
||||
from .base import Processor, ThreadedProcessor, Pipeline # noqa: F401
|
||||
from .types import AudioFile, Transcript, Word, TitleSummary, FinalSummary # noqa: F401
|
||||
from .audio_chunker import AudioChunkerProcessor # noqa: F401
|
||||
from .audio_merge import AudioMergeProcessor # noqa: F401
|
||||
from .audio_transcript import AudioTranscriptProcessor # noqa: F401
|
||||
from .audio_transcript_auto import AudioTranscriptAutoProcessor # noqa: F401
|
||||
from .transcript_liner import TranscriptLinerProcessor # noqa: F401
|
||||
from .transcript_topic_detector import TranscriptTopicDetectorProcessor # noqa: F401
|
||||
from .transcript_final_summary import TranscriptFinalSummaryProcessor # noqa: F401
|
||||
27
server/reflector/processors/audio_chunker.py
Normal file
27
server/reflector/processors/audio_chunker.py
Normal file
@@ -0,0 +1,27 @@
|
||||
from reflector.processors.base import Processor
|
||||
import av
|
||||
|
||||
|
||||
class AudioChunkerProcessor(Processor):
|
||||
"""
|
||||
Assemble audio frames into chunks
|
||||
"""
|
||||
|
||||
INPUT_TYPE = av.AudioFrame
|
||||
OUTPUT_TYPE = list[av.AudioFrame]
|
||||
|
||||
def __init__(self, max_frames=256):
|
||||
super().__init__()
|
||||
self.frames: list[av.AudioFrame] = []
|
||||
self.max_frames = max_frames
|
||||
|
||||
async def _push(self, data: av.AudioFrame):
|
||||
self.frames.append(data)
|
||||
if len(self.frames) >= self.max_frames:
|
||||
await self.flush()
|
||||
|
||||
async def _flush(self):
|
||||
frames = self.frames[:]
|
||||
self.frames = []
|
||||
if frames:
|
||||
await self.emit(frames)
|
||||
47
server/reflector/processors/audio_merge.py
Normal file
47
server/reflector/processors/audio_merge.py
Normal file
@@ -0,0 +1,47 @@
|
||||
from reflector.processors.base import Processor
|
||||
from reflector.processors.types import AudioFile
|
||||
from pathlib import Path
|
||||
import wave
|
||||
import av
|
||||
|
||||
|
||||
class AudioMergeProcessor(Processor):
|
||||
"""
|
||||
Merge audio frame into a single file
|
||||
"""
|
||||
|
||||
INPUT_TYPE = list[av.AudioFrame]
|
||||
OUTPUT_TYPE = AudioFile
|
||||
|
||||
async def _push(self, data: list[av.AudioFrame]):
|
||||
if not data:
|
||||
return
|
||||
|
||||
# get audio information from first frame
|
||||
frame = data[0]
|
||||
channels = len(frame.layout.channels)
|
||||
sample_rate = frame.sample_rate
|
||||
sample_width = frame.format.bytes
|
||||
|
||||
# create audio file
|
||||
from time import monotonic_ns
|
||||
from uuid import uuid4
|
||||
|
||||
uu = uuid4().hex
|
||||
path = Path(f"audio_{monotonic_ns()}_{uu}.wav")
|
||||
with wave.open(path.as_posix(), "wb") as wf:
|
||||
wf.setnchannels(channels)
|
||||
wf.setsampwidth(sample_width)
|
||||
wf.setframerate(sample_rate)
|
||||
for frame in data:
|
||||
wf.writeframes(frame.to_ndarray().tobytes())
|
||||
|
||||
# emit audio file
|
||||
audiofile = AudioFile(
|
||||
path=path,
|
||||
sample_rate=sample_rate,
|
||||
channels=channels,
|
||||
sample_width=sample_width,
|
||||
timestamp=data[0].pts * data[0].time_base,
|
||||
)
|
||||
await self.emit(audiofile)
|
||||
22
server/reflector/processors/audio_transcript.py
Normal file
22
server/reflector/processors/audio_transcript.py
Normal file
@@ -0,0 +1,22 @@
|
||||
from reflector.processors.base import Processor
|
||||
from reflector.processors.types import AudioFile, Transcript
|
||||
|
||||
|
||||
class AudioTranscriptProcessor(Processor):
|
||||
"""
|
||||
Transcript audio file
|
||||
"""
|
||||
|
||||
INPUT_TYPE = AudioFile
|
||||
OUTPUT_TYPE = Transcript
|
||||
|
||||
async def _push(self, data: AudioFile):
|
||||
try:
|
||||
result = await self._transcript(data)
|
||||
if result:
|
||||
await self.emit(result)
|
||||
finally:
|
||||
data.release()
|
||||
|
||||
async def _transcript(self, data: AudioFile):
|
||||
raise NotImplementedError
|
||||
35
server/reflector/processors/audio_transcript_auto.py
Normal file
35
server/reflector/processors/audio_transcript_auto.py
Normal file
@@ -0,0 +1,35 @@
|
||||
from reflector.processors.base import Processor
|
||||
from reflector.processors.audio_transcript import AudioTranscriptProcessor
|
||||
from reflector.processors.audio_transcript_whisper import (
|
||||
AudioTranscriptWhisperProcessor,
|
||||
)
|
||||
from reflector.processors.types import AudioFile
|
||||
|
||||
|
||||
class AudioTranscriptAutoProcessor(AudioTranscriptProcessor):
|
||||
BACKENDS = {
|
||||
"whisper": AudioTranscriptWhisperProcessor,
|
||||
}
|
||||
BACKEND_DEFAULT = "whisper"
|
||||
|
||||
def __init__(self, backend=None, **kwargs):
|
||||
self.processor = self.BACKENDS[backend or self.BACKEND_DEFAULT]()
|
||||
super().__init__(**kwargs)
|
||||
|
||||
def connect(self, processor: Processor):
|
||||
self.processor.connect(processor)
|
||||
|
||||
def disconnect(self, processor: Processor):
|
||||
self.processor.disconnect(processor)
|
||||
|
||||
def on(self, callback):
|
||||
self.processor.on(callback)
|
||||
|
||||
def off(self, callback):
|
||||
self.processor.off(callback)
|
||||
|
||||
async def _push(self, data: AudioFile):
|
||||
return await self.processor._push(data)
|
||||
|
||||
async def _flush(self):
|
||||
return await self.processor._flush()
|
||||
42
server/reflector/processors/audio_transcript_whisper.py
Normal file
42
server/reflector/processors/audio_transcript_whisper.py
Normal file
@@ -0,0 +1,42 @@
|
||||
from reflector.processors.audio_transcript import AudioTranscriptProcessor
|
||||
from reflector.processors.types import AudioFile, Transcript, Word
|
||||
from faster_whisper import WhisperModel
|
||||
|
||||
|
||||
class AudioTranscriptWhisperProcessor(AudioTranscriptProcessor):
|
||||
def __init__(self):
|
||||
super().__init__()
|
||||
self.model = WhisperModel(
|
||||
"tiny", device="cpu", compute_type="float32", num_workers=12
|
||||
)
|
||||
|
||||
async def _transcript(self, data: AudioFile):
|
||||
segments, _ = self.model.transcribe(
|
||||
data.path.as_posix(),
|
||||
language="en",
|
||||
beam_size=5,
|
||||
# condition_on_previous_text=True,
|
||||
word_timestamps=True,
|
||||
vad_filter=True,
|
||||
vad_parameters={"min_silence_duration_ms": 500},
|
||||
)
|
||||
|
||||
if not segments:
|
||||
return
|
||||
|
||||
transcript = Transcript(words=[])
|
||||
segments = list(segments)
|
||||
ts = data.timestamp
|
||||
|
||||
for segment in segments:
|
||||
transcript.text += segment.text
|
||||
for word in segment.words:
|
||||
transcript.words.append(
|
||||
Word(
|
||||
text=word.word,
|
||||
start=round(ts + word.start, 3),
|
||||
end=round(ts + word.end, 3),
|
||||
)
|
||||
)
|
||||
|
||||
return transcript
|
||||
178
server/reflector/processors/base.py
Normal file
178
server/reflector/processors/base.py
Normal file
@@ -0,0 +1,178 @@
|
||||
from reflector.logger import logger
|
||||
from uuid import uuid4
|
||||
from concurrent.futures import ThreadPoolExecutor
|
||||
import asyncio
|
||||
|
||||
|
||||
class Processor:
|
||||
INPUT_TYPE: type = None
|
||||
OUTPUT_TYPE: type = None
|
||||
|
||||
def __init__(self, callback=None, custom_logger=None):
|
||||
self._processors = []
|
||||
self._callbacks = []
|
||||
if callback:
|
||||
self.on(callback)
|
||||
self.uid = uuid4().hex
|
||||
self.logger = (custom_logger or logger).bind(processor=self.__class__.__name__)
|
||||
|
||||
def set_pipeline(self, pipeline: "Pipeline"):
|
||||
self.logger = self.logger.bind(pipeline=pipeline.uid)
|
||||
|
||||
def connect(self, processor: "Processor"):
|
||||
"""
|
||||
Connect this processor output to another processor
|
||||
"""
|
||||
if processor.INPUT_TYPE != self.OUTPUT_TYPE:
|
||||
raise ValueError(
|
||||
f"Processor {processor} input type {processor.INPUT_TYPE} "
|
||||
f"does not match {self.OUTPUT_TYPE}"
|
||||
)
|
||||
self._processors.append(processor)
|
||||
|
||||
def disconnect(self, processor: "Processor"):
|
||||
"""
|
||||
Disconnect this processor data from another processor
|
||||
"""
|
||||
self._processors.remove(processor)
|
||||
|
||||
def on(self, callback):
|
||||
"""
|
||||
Register a callback to be called when data is emitted
|
||||
"""
|
||||
# ensure callback is asynchronous
|
||||
if not asyncio.iscoroutinefunction(callback):
|
||||
raise ValueError("Callback must be a coroutine function")
|
||||
self._callbacks.append(callback)
|
||||
|
||||
def off(self, callback):
|
||||
"""
|
||||
Unregister a callback to be called when data is emitted
|
||||
"""
|
||||
self._callbacks.remove(callback)
|
||||
|
||||
async def emit(self, data):
|
||||
for callback in self._callbacks:
|
||||
await callback(data)
|
||||
for processor in self._processors:
|
||||
await processor.push(data)
|
||||
|
||||
async def push(self, data):
|
||||
"""
|
||||
Push data to this processor. `data` must be of type `INPUT_TYPE`
|
||||
The function returns the output of type `OUTPUT_TYPE`
|
||||
"""
|
||||
# logger.debug(f"{self.__class__.__name__} push")
|
||||
try:
|
||||
return await self._push(data)
|
||||
except Exception:
|
||||
self.logger.exception("Error in push")
|
||||
|
||||
async def flush(self):
|
||||
"""
|
||||
Flush data to this processor
|
||||
"""
|
||||
# logger.debug(f"{self.__class__.__name__} flush")
|
||||
return await self._flush()
|
||||
|
||||
def describe(self, level=0):
|
||||
logger.info(" " * level + self.__class__.__name__)
|
||||
|
||||
async def _push(self, data):
|
||||
raise NotImplementedError
|
||||
|
||||
async def _flush(self):
|
||||
pass
|
||||
|
||||
@classmethod
|
||||
def as_threaded(cls, *args, **kwargs):
|
||||
"""
|
||||
Return a single threaded processor where output is guaranteed
|
||||
to be in order
|
||||
"""
|
||||
return ThreadedProcessor(cls(*args, **kwargs), max_workers=1)
|
||||
|
||||
|
||||
class ThreadedProcessor(Processor):
|
||||
"""
|
||||
A processor that runs in a separate thread
|
||||
"""
|
||||
|
||||
def __init__(self, processor: Processor, max_workers=1):
|
||||
super().__init__()
|
||||
# FIXME: This is a hack to make sure that the processor is single threaded
|
||||
# but if it is more than 1, then we need to make sure that the processor
|
||||
# is emiting data in order
|
||||
assert max_workers == 1
|
||||
self.processor = processor
|
||||
self.INPUT_TYPE = processor.INPUT_TYPE
|
||||
self.OUTPUT_TYPE = processor.OUTPUT_TYPE
|
||||
self.executor = ThreadPoolExecutor(max_workers=max_workers)
|
||||
self.queue = asyncio.Queue()
|
||||
self.task = asyncio.get_running_loop().create_task(self.loop())
|
||||
|
||||
async def loop(self):
|
||||
while True:
|
||||
data = await self.queue.get()
|
||||
try:
|
||||
if data is None:
|
||||
await self.processor.flush()
|
||||
break
|
||||
await self.processor.push(data)
|
||||
finally:
|
||||
self.queue.task_done()
|
||||
|
||||
async def _push(self, data):
|
||||
await self.queue.put(data)
|
||||
|
||||
async def _flush(self):
|
||||
await self.queue.put(None)
|
||||
await self.queue.join()
|
||||
|
||||
def connect(self, processor: Processor):
|
||||
self.processor.connect(processor)
|
||||
|
||||
def disconnect(self, processor: Processor):
|
||||
self.processor.disconnect(processor)
|
||||
|
||||
def on(self, callback):
|
||||
self.processor.on(callback)
|
||||
|
||||
def describe(self, level=0):
|
||||
super().describe(level)
|
||||
self.processor.describe(level + 1)
|
||||
|
||||
|
||||
class Pipeline(Processor):
|
||||
"""
|
||||
A pipeline of processors
|
||||
"""
|
||||
|
||||
INPUT_TYPE = None
|
||||
OUTPUT_TYPE = None
|
||||
|
||||
def __init__(self, *processors: Processor):
|
||||
super().__init__()
|
||||
self.processors = processors
|
||||
|
||||
for processor in processors:
|
||||
processor.set_pipeline(self)
|
||||
|
||||
for i in range(len(processors) - 1):
|
||||
processors[i].connect(processors[i + 1])
|
||||
|
||||
self.INPUT_TYPE = processors[0].INPUT_TYPE
|
||||
self.OUTPUT_TYPE = processors[-1].OUTPUT_TYPE
|
||||
|
||||
async def _push(self, data):
|
||||
await self.processors[0].push(data)
|
||||
|
||||
async def _flush(self):
|
||||
for processor in self.processors:
|
||||
await processor.flush()
|
||||
|
||||
def describe(self, level=0):
|
||||
logger.info(" " * level + "Pipeline:")
|
||||
for processor in self.processors:
|
||||
processor.describe(level + 1)
|
||||
logger.info("")
|
||||
30
server/reflector/processors/transcript_final_summary.py
Normal file
30
server/reflector/processors/transcript_final_summary.py
Normal file
@@ -0,0 +1,30 @@
|
||||
from reflector.processors.base import Processor
|
||||
from reflector.processors.types import TitleSummary, FinalSummary
|
||||
|
||||
|
||||
class TranscriptFinalSummaryProcessor(Processor):
|
||||
"""
|
||||
Assemble all summary into a line-based json
|
||||
"""
|
||||
|
||||
INPUT_TYPE = TitleSummary
|
||||
OUTPUT_TYPE = FinalSummary
|
||||
|
||||
def __init__(self, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self.chunks: list[TitleSummary] = []
|
||||
|
||||
async def _push(self, data: TitleSummary):
|
||||
self.chunks.append(data)
|
||||
|
||||
async def _flush(self):
|
||||
if not self.chunks:
|
||||
self.logger.warning("No summary to output")
|
||||
return
|
||||
|
||||
# FIXME improve final summary
|
||||
result = "\n".join([chunk.summary for chunk in self.chunks])
|
||||
last_chunk = self.chunks[-1]
|
||||
duration = last_chunk.timestamp + last_chunk.duration
|
||||
|
||||
await self.emit(FinalSummary(summary=result, duration=duration))
|
||||
47
server/reflector/processors/transcript_liner.py
Normal file
47
server/reflector/processors/transcript_liner.py
Normal file
@@ -0,0 +1,47 @@
|
||||
from reflector.processors.base import Processor
|
||||
from reflector.processors.types import Transcript
|
||||
|
||||
|
||||
class TranscriptLinerProcessor(Processor):
|
||||
"""
|
||||
Based on stream of transcript, assemble and remove duplicated words
|
||||
then cut per lines.
|
||||
"""
|
||||
|
||||
INPUT_TYPE = Transcript
|
||||
OUTPUT_TYPE = Transcript
|
||||
|
||||
def __init__(self, max_text=1000, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self.transcript = Transcript(words=[])
|
||||
self.max_text = max_text
|
||||
|
||||
async def _push(self, data: Transcript):
|
||||
# merge both transcript
|
||||
self.transcript.merge(data)
|
||||
|
||||
# check if a line is complete
|
||||
if "." not in self.transcript.text:
|
||||
# if the transcription text is still not too long, wait for more
|
||||
if len(self.transcript.text) < self.max_text:
|
||||
return
|
||||
|
||||
# cut to the next .
|
||||
partial = Transcript(words=[])
|
||||
for word in self.transcript.words[:]:
|
||||
partial.text += word.text
|
||||
partial.words.append(word)
|
||||
if "." not in word.text:
|
||||
continue
|
||||
|
||||
# emit line
|
||||
await self.emit(partial)
|
||||
|
||||
# create new transcript
|
||||
partial = Transcript(words=[])
|
||||
|
||||
self.transcript = partial
|
||||
|
||||
async def _flush(self):
|
||||
if self.transcript.words:
|
||||
await self.emit(self.transcript)
|
||||
55
server/reflector/processors/transcript_topic_detector.py
Normal file
55
server/reflector/processors/transcript_topic_detector.py
Normal file
@@ -0,0 +1,55 @@
|
||||
from reflector.processors.base import Processor
|
||||
from reflector.processors.types import Transcript, TitleSummary
|
||||
from reflector.llm import LLM
|
||||
|
||||
|
||||
class TranscriptTopicDetectorProcessor(Processor):
|
||||
"""
|
||||
Detect topic and summary from the transcript
|
||||
"""
|
||||
|
||||
INPUT_TYPE = Transcript
|
||||
OUTPUT_TYPE = TitleSummary
|
||||
|
||||
PROMPT = """
|
||||
### Human:
|
||||
Create a JSON object as response.The JSON object must have 2 fields:
|
||||
i) title and ii) summary.For the title field,generate a short title
|
||||
for the given text. For the summary field, summarize the given text
|
||||
in three sentences.
|
||||
|
||||
{input_text}
|
||||
|
||||
### Assistant:
|
||||
|
||||
"""
|
||||
|
||||
def __init__(self, min_transcript_length=100, **kwargs):
|
||||
super().__init__(**kwargs)
|
||||
self.transcript = None
|
||||
self.min_transcript_length = min_transcript_length
|
||||
self.llm = LLM.instance()
|
||||
|
||||
async def _push(self, data: Transcript):
|
||||
if self.transcript is None:
|
||||
self.transcript = data
|
||||
else:
|
||||
self.transcript.merge(data)
|
||||
if len(self.transcript.text) < self.min_transcript_length:
|
||||
return
|
||||
await self.flush()
|
||||
|
||||
async def _flush(self):
|
||||
if not self.transcript:
|
||||
return
|
||||
prompt = self.PROMPT.format(input_text=self.transcript.text)
|
||||
result = await self.llm.generate(prompt=prompt)
|
||||
summary = TitleSummary(
|
||||
title=result["title"],
|
||||
summary=result["summary"],
|
||||
timestamp=self.transcript.timestamp,
|
||||
duration=self.transcript.duration,
|
||||
transcript=self.transcript,
|
||||
)
|
||||
self.transcript = None
|
||||
await self.emit(summary)
|
||||
74
server/reflector/processors/types.py
Normal file
74
server/reflector/processors/types.py
Normal file
@@ -0,0 +1,74 @@
|
||||
from dataclasses import dataclass
|
||||
from pathlib import Path
|
||||
|
||||
|
||||
@dataclass
|
||||
class AudioFile:
|
||||
path: Path
|
||||
sample_rate: int
|
||||
channels: int
|
||||
sample_width: int
|
||||
timestamp: float = 0.0
|
||||
|
||||
def release(self):
|
||||
self.path.unlink()
|
||||
|
||||
|
||||
@dataclass
|
||||
class Word:
|
||||
text: str
|
||||
start: float
|
||||
end: float
|
||||
|
||||
|
||||
@dataclass
|
||||
class Transcript:
|
||||
text: str = ""
|
||||
words: list[Word] = None
|
||||
|
||||
@property
|
||||
def human_timestamp(self):
|
||||
minutes = int(self.timestamp / 60)
|
||||
seconds = int(self.timestamp % 60)
|
||||
milliseconds = int((self.timestamp % 1) * 1000)
|
||||
return f"{minutes:02d}:{seconds:02d}.{milliseconds:03d}"
|
||||
|
||||
@property
|
||||
def timestamp(self):
|
||||
if not self.words:
|
||||
raise ValueError("No words in transcript")
|
||||
return self.words[0].start
|
||||
|
||||
@property
|
||||
def duration(self):
|
||||
if not self.words:
|
||||
raise ValueError("No words in transcript")
|
||||
return self.words[-1].end - self.words[0].start
|
||||
|
||||
def merge(self, other: "Transcript"):
|
||||
if not self.words:
|
||||
self.words = other.words
|
||||
else:
|
||||
self.words.extend(other.words)
|
||||
self.text += other.text
|
||||
|
||||
def clone(self):
|
||||
words = [
|
||||
Word(text=word.text, start=word.start, end=word.end) for word in self.words
|
||||
]
|
||||
return Transcript(text=self.text, words=words)
|
||||
|
||||
|
||||
@dataclass
|
||||
class TitleSummary:
|
||||
title: str
|
||||
summary: str
|
||||
timestamp: float
|
||||
duration: float
|
||||
transcript: Transcript
|
||||
|
||||
|
||||
@dataclass
|
||||
class FinalSummary:
|
||||
summary: str
|
||||
duration: float
|
||||
@@ -31,6 +31,12 @@ class Settings(BaseSettings):
|
||||
LLM_URL: str | None = None
|
||||
LLM_HOST: str = "localhost"
|
||||
LLM_PORT: int = 7860
|
||||
LLM_OPENAI_KEY: str | None = None
|
||||
LLM_OPENAI_MODEL: str = "gpt-3.5-turbo"
|
||||
LLM_OPENAI_TEMPERATURE: float = 0.7
|
||||
LLM_TIMEOUT: int = 90
|
||||
LLM_MAX_TOKENS: int = 1024
|
||||
LLM_TEMPERATURE: float = 0.7
|
||||
|
||||
# Storage
|
||||
STORAGE_BACKEND: str = "aws"
|
||||
@@ -38,8 +44,5 @@ class Settings(BaseSettings):
|
||||
STORAGE_AWS_SECRET_KEY: str = ""
|
||||
STORAGE_AWS_BUCKET: str = ""
|
||||
|
||||
# OpenAI
|
||||
OPENAI_API_KEY: str = ""
|
||||
|
||||
|
||||
settings = Settings()
|
||||
|
||||
65
server/reflector/tools/process.py
Normal file
65
server/reflector/tools/process.py
Normal file
@@ -0,0 +1,65 @@
|
||||
import av
|
||||
from reflector.logger import logger
|
||||
from reflector.processors import (
|
||||
Pipeline,
|
||||
AudioChunkerProcessor,
|
||||
AudioMergeProcessor,
|
||||
AudioTranscriptAutoProcessor,
|
||||
TranscriptLinerProcessor,
|
||||
TranscriptTopicDetectorProcessor,
|
||||
TranscriptFinalSummaryProcessor,
|
||||
)
|
||||
import asyncio
|
||||
|
||||
|
||||
async def process_audio_file(filename, event_callback):
|
||||
async def on_transcript(data):
|
||||
await event_callback("transcript", data)
|
||||
|
||||
async def on_topic(data):
|
||||
await event_callback("topic", data)
|
||||
|
||||
async def on_summary(data):
|
||||
await event_callback("summary", data)
|
||||
|
||||
# transcription output
|
||||
pipeline = Pipeline(
|
||||
AudioChunkerProcessor(),
|
||||
AudioMergeProcessor(),
|
||||
AudioTranscriptAutoProcessor.as_threaded(),
|
||||
TranscriptLinerProcessor(callback=on_transcript),
|
||||
TranscriptTopicDetectorProcessor.as_threaded(callback=on_topic),
|
||||
TranscriptFinalSummaryProcessor.as_threaded(callback=on_summary),
|
||||
)
|
||||
pipeline.describe()
|
||||
|
||||
# start processing audio
|
||||
logger.info(f"Opening {filename}")
|
||||
container = av.open(filename)
|
||||
try:
|
||||
logger.info("Start pushing audio into the pipeline")
|
||||
for frame in container.decode(audio=0):
|
||||
await pipeline.push(frame)
|
||||
finally:
|
||||
logger.info("Flushing the pipeline")
|
||||
await pipeline.flush()
|
||||
|
||||
logger.info("All done !")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
import argparse
|
||||
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("source", help="Source file (mp3, wav, mp4...)")
|
||||
args = parser.parse_args()
|
||||
|
||||
async def event_callback(event, data):
|
||||
if event == "transcript":
|
||||
print(f"Transcript[{data.human_timestamp}]: {data.text}")
|
||||
elif event == "topic":
|
||||
print(f"Topic: {data}")
|
||||
elif event == "summary":
|
||||
print(f"Summary: {data}")
|
||||
|
||||
asyncio.run(process_audio_file(args.source, event_callback))
|
||||
159
server/reflector/views/rtc_offer.py
Normal file
159
server/reflector/views/rtc_offer.py
Normal file
@@ -0,0 +1,159 @@
|
||||
import asyncio
|
||||
from fastapi import Request, APIRouter
|
||||
from reflector.events import subscribers_shutdown
|
||||
from pydantic import BaseModel
|
||||
from reflector.models import TranscriptionContext
|
||||
from reflector.logger import logger
|
||||
from aiortc import RTCPeerConnection, RTCSessionDescription, MediaStreamTrack
|
||||
from json import loads, dumps
|
||||
import av
|
||||
from reflector.processors import (
|
||||
Pipeline,
|
||||
AudioChunkerProcessor,
|
||||
AudioMergeProcessor,
|
||||
AudioTranscriptAutoProcessor,
|
||||
TranscriptLinerProcessor,
|
||||
TranscriptTopicDetectorProcessor,
|
||||
TranscriptFinalSummaryProcessor,
|
||||
Transcript,
|
||||
TitleSummary,
|
||||
FinalSummary,
|
||||
)
|
||||
|
||||
sessions = []
|
||||
router = APIRouter()
|
||||
|
||||
|
||||
class AudioStreamTrack(MediaStreamTrack):
|
||||
"""
|
||||
An audio stream track.
|
||||
"""
|
||||
|
||||
kind = "audio"
|
||||
|
||||
def __init__(self, ctx: TranscriptionContext, track):
|
||||
super().__init__()
|
||||
self.ctx = ctx
|
||||
self.track = track
|
||||
|
||||
async def recv(self) -> av.audio.frame.AudioFrame:
|
||||
ctx = self.ctx
|
||||
frame = await self.track.recv()
|
||||
try:
|
||||
await ctx.pipeline.push(frame)
|
||||
except Exception as e:
|
||||
ctx.logger.error("Pipeline error", error=e)
|
||||
return frame
|
||||
|
||||
|
||||
class RtcOffer(BaseModel):
|
||||
sdp: str
|
||||
type: str
|
||||
|
||||
|
||||
@router.post("/offer")
|
||||
async def rtc_offer(params: RtcOffer, request: Request):
|
||||
# build an rtc session
|
||||
offer = RTCSessionDescription(sdp=params.sdp, type=params.type)
|
||||
|
||||
# client identification
|
||||
peername = request.client
|
||||
clientid = f"{peername[0]}:{peername[1]}"
|
||||
ctx = TranscriptionContext(logger=logger.bind(client=clientid))
|
||||
ctx.topics = []
|
||||
|
||||
# build pipeline callback
|
||||
async def on_transcript(transcript: Transcript):
|
||||
ctx.logger.info("Transcript", transcript=transcript)
|
||||
result = {
|
||||
"cmd": "SHOW_TRANSCRIPTION",
|
||||
"text": transcript.text,
|
||||
}
|
||||
ctx.data_channel.send(dumps(result))
|
||||
|
||||
async def on_topic(summary: TitleSummary):
|
||||
# FIXME: make it incremental with the frontend, not send everything
|
||||
ctx.logger.info("Summary", summary=summary)
|
||||
ctx.topics.append(
|
||||
{
|
||||
"title": summary.title,
|
||||
"timestamp": summary.timestamp,
|
||||
"transcript": summary.transcript.text,
|
||||
"desc": summary.summary,
|
||||
}
|
||||
)
|
||||
result = {"cmd": "UPDATE_TOPICS", "topics": ctx.topics}
|
||||
ctx.data_channel.send(dumps(result))
|
||||
|
||||
async def on_final_summary(summary: FinalSummary):
|
||||
ctx.logger.info("FinalSummary", final_summary=summary)
|
||||
result = {
|
||||
"cmd": "DISPLAY_FINAL_SUMMARY",
|
||||
"summary": summary.summary,
|
||||
"duration": summary.duration,
|
||||
}
|
||||
ctx.data_channel.send(dumps(result))
|
||||
|
||||
# create a context for the whole rtc transaction
|
||||
# add a customised logger to the context
|
||||
ctx.pipeline = Pipeline(
|
||||
AudioChunkerProcessor(),
|
||||
AudioMergeProcessor(),
|
||||
AudioTranscriptAutoProcessor.as_threaded(callback=on_transcript),
|
||||
TranscriptLinerProcessor(),
|
||||
TranscriptTopicDetectorProcessor.as_threaded(callback=on_topic),
|
||||
TranscriptFinalSummaryProcessor.as_threaded(callback=on_final_summary),
|
||||
)
|
||||
|
||||
# handle RTC peer connection
|
||||
pc = RTCPeerConnection()
|
||||
|
||||
async def flush_pipeline_and_quit():
|
||||
ctx.logger.info("Flushing pipeline")
|
||||
await ctx.pipeline.flush()
|
||||
ctx.logger.debug("Closing peer connection")
|
||||
await pc.close()
|
||||
|
||||
@pc.on("datachannel")
|
||||
def on_datachannel(channel):
|
||||
ctx.data_channel = channel
|
||||
ctx.logger = ctx.logger.bind(channel=channel.label)
|
||||
ctx.logger.info("Channel created by remote party")
|
||||
|
||||
@channel.on("message")
|
||||
def on_message(message: str):
|
||||
ctx.logger.info(f"Message: {message}")
|
||||
if loads(message)["cmd"] == "STOP":
|
||||
ctx.logger.debug("STOP command received")
|
||||
asyncio.get_event_loop().create_task(flush_pipeline_and_quit())
|
||||
|
||||
if isinstance(message, str) and message.startswith("ping"):
|
||||
channel.send("pong" + message[4:])
|
||||
|
||||
@pc.on("connectionstatechange")
|
||||
async def on_connectionstatechange():
|
||||
ctx.logger.info(f"Connection state: {pc.connectionState}")
|
||||
if pc.connectionState == "failed":
|
||||
await pc.close()
|
||||
|
||||
@pc.on("track")
|
||||
def on_track(track):
|
||||
ctx.logger.info(f"Track {track.kind} received")
|
||||
pc.addTrack(AudioStreamTrack(ctx, track))
|
||||
|
||||
await pc.setRemoteDescription(offer)
|
||||
|
||||
answer = await pc.createAnswer()
|
||||
await pc.setLocalDescription(answer)
|
||||
sessions.append(pc)
|
||||
|
||||
return RtcOffer(sdp=pc.localDescription.sdp, type=pc.localDescription.type)
|
||||
|
||||
|
||||
@subscribers_shutdown.append
|
||||
async def rtc_clean_sessions():
|
||||
logger.info("Closing all RTC sessions")
|
||||
for pc in sessions:
|
||||
logger.debug(f"Closing session {pc}")
|
||||
await pc.close()
|
||||
sessions.clear()
|
||||
44
server/tests/test_processors_pipeline.py
Normal file
44
server/tests/test_processors_pipeline.py
Normal file
@@ -0,0 +1,44 @@
|
||||
import pytest
|
||||
|
||||
|
||||
@pytest.mark.asyncio
|
||||
async def test_basic_process(event_loop):
|
||||
# goal is to start the server, and send rtc audio to it
|
||||
# validate the events received
|
||||
from reflector.tools.process import process_audio_file
|
||||
from reflector.settings import settings
|
||||
from reflector.llm.base import LLM
|
||||
from pathlib import Path
|
||||
|
||||
# use an LLM test backend
|
||||
settings.LLM_BACKEND = "test"
|
||||
|
||||
class LLMTest(LLM):
|
||||
async def _generate(self, prompt: str, **kwargs) -> str:
|
||||
return {
|
||||
"title": "TITLE",
|
||||
"summary": "SUMMARY",
|
||||
}
|
||||
|
||||
LLM.register("test", LLMTest)
|
||||
|
||||
# event callback
|
||||
marks = {
|
||||
"transcript": 0,
|
||||
"topic": 0,
|
||||
"summary": 0,
|
||||
}
|
||||
|
||||
async def event_callback(event, data):
|
||||
print(f"{event}: {data}")
|
||||
marks[event] += 1
|
||||
|
||||
# invoke the process and capture events
|
||||
path = Path(__file__).parent / "records" / "test_mathieu_hello.wav"
|
||||
await process_audio_file(path.as_posix(), event_callback)
|
||||
print(marks)
|
||||
|
||||
# validate the events
|
||||
assert marks["transcript"] == 5
|
||||
assert marks["topic"] == 2
|
||||
assert marks["summary"] == 1
|
||||
Reference in New Issue
Block a user