Salmanap/fix network agent demo (#153)

* staging my changes to re-based from main

* adding debug statements to rust

* merged with main

* ready to push network agent

* removed the incomplete sql example

---------

Co-authored-by: Salman Paracha <salmanparacha@MacBook-Pro-261.local>
This commit is contained in:
Salman Paracha 2024-10-08 22:19:20 -07:00 committed by GitHub
parent 6acfea7787
commit b63a01fe82
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41 changed files with 252 additions and 1987 deletions

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@ -35,11 +35,11 @@ def start_server():
print("Server is already running. Use 'model_server restart' to restart it.")
sys.exit(1)
print(f"Starting Archgw Model Server")
print(f"Starting Archgw Model Server - Loading some awesomeness, this may take a little time.)")
process = subprocess.Popen(
["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "51000"],
start_new_session=True,
stdout=subprocess.DEVNULL, # Suppress standard output. There is a logger that model_server prints to
stdout=subprocess.DEVNULL, # Suppress standard output. There is a logger that model_server prints to
stderr=subprocess.DEVNULL, # Suppress standard error. There is a logger that model_server prints to
)

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@ -7,6 +7,7 @@ from optimum.onnxruntime import ORTModelForFeatureExtraction, ORTModelForSequenc
def get_device():
if torch.cuda.is_available():
device = "cuda"
elif torch.backends.mps.is_available():
@ -14,10 +15,12 @@ def get_device():
else:
device = "cpu"
print(f"Devices Avialble: {device}")
return device
def load_transformers(model_name=os.getenv("MODELS", "katanemo/bge-large-en-v1.5-onnx")):
print("Loading Embedding Model")
transformers = {}
device = get_device()
transformers["tokenizer"] = AutoTokenizer.from_pretrained(model_name)
@ -33,6 +36,7 @@ def load_guard_model(
model_name,
hardware_config="cpu",
):
print("Loading Guard Model")
guard_model = {}
guard_model["tokenizer"] = AutoTokenizer.from_pretrained(
model_name, trust_remote_code=True
@ -58,9 +62,7 @@ def load_guard_model(
return guard_model
def load_zero_shot_models(
model_name=os.getenv("ZERO_SHOT_MODELS", "katanemo/deberta-base-nli-onnx")
):
def load_zero_shot_models(model_name=os.getenv("ZERO_SHOT_MODELS", "katanemo/deberta-base-nli-onnx")):
zero_shot_model = {}
device = get_device()
zero_shot_model["model"] = ORTModelForSequenceClassification.from_pretrained(
@ -79,6 +81,5 @@ def load_zero_shot_models(
return zero_shot_model
if __name__ == "__main__":
print(get_device())

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@ -26,6 +26,7 @@ guard_model_config = load_yaml_config("guard_model_config.yaml")
mode = os.getenv("MODE", "cloud")
logger.info(f"Serving model mode: {mode}")
print(f"Serving model mode: {mode}")
if mode not in ["cloud", "local-gpu", "local-cpu"]:
raise ValueError(f"Invalid mode: {mode}")
if mode == "local-cpu":