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import json
import sys
import time
from datetime import UTC, datetime
from http.server import BaseHTTPRequestHandler, ThreadingHTTPServer
from pathlib import Path
import sentencepiece as spm
import torch
sys.path.insert(0, str(Path(__file__).resolve().parents[1] / "src"))
from sovyn import SovynConfig, SovynForCausalLM
from sovyn.formatting import format_prompt
from chat import clean_answer, score_answer
def now_iso():
return datetime.now(UTC).isoformat(timespec="milliseconds").replace("+00:00", "Z")
class SovynRuntime:
def __init__(self, args):
self.model_name = args.model_name
self.max_new_tokens = args.max_new_tokens
self.temperature = args.temperature
self.top_k = args.top_k
self.best_of = args.best_of
self.checkpoint_path = Path(args.checkpoint)
device = args.device
if device == "cuda" and not torch.cuda.is_available():
device = "cpu"
self.device = device
self.tokenizer = spm.SentencePieceProcessor(model_file=args.tokenizer)
checkpoint = torch.load(self.checkpoint_path, map_location="cpu")
model_cfg = checkpoint["config"]["model"]
self.model = SovynForCausalLM(SovynConfig(**model_cfg))
self.model.load_state_dict(checkpoint["model"])
dtype = torch.bfloat16 if device == "cuda" else torch.float32
self.model.to(device=device, dtype=dtype)
self.model.eval()
self.eos_id = self.tokenizer.piece_to_id("<eos>")
self.stop_ids = [
self.tokenizer.piece_to_id(piece)
for piece in ["<system>", "<user>", "<state>", "<plan>", "<memory>", "<reflection>"]
if self.tokenizer.piece_to_id(piece) >= 0
]
self.suppress_ids = [
idx
for idx in [
self.tokenizer.piece_to_id("<pad>"),
self.tokenizer.piece_to_id("<unk>"),
self.tokenizer.piece_to_id("<bos>"),
]
if idx >= 0
]
@torch.no_grad()
def reply(self, user: str, system: str | None = None, options: dict | None = None) -> str:
options = options or {}
temperature = float(options.get("temperature", self.temperature))
top_k = int(options.get("top_k", self.top_k))
max_new_tokens = int(options.get("num_predict", self.max_new_tokens))
best_of = max(1, int(options.get("best_of", self.best_of)))
runs = best_of if temperature > 0 else 1
prompt = format_prompt(user, system=system)
ids = torch.tensor(
[self.tokenizer.encode(prompt, out_type=int)],
dtype=torch.long,
device=self.device,
)
candidates = []
for _ in range(runs):
out = self.model.generate(
ids,
max_new_tokens=max_new_tokens,
temperature=temperature,
top_k=top_k,
eos_id=self.eos_id,
stop_ids=self.stop_ids,
suppress_ids=self.suppress_ids,
)
answer = clean_answer(self.tokenizer.decode(out[0].tolist()))
candidates.append(answer)
return max(candidates, key=lambda answer: score_answer(user, answer))
def tags(self):
size = self.checkpoint_path.stat().st_size if self.checkpoint_path.exists() else 0
return {
"models": [
{
"name": self.model_name,
"model": self.model_name,
"modified_at": now_iso(),
"size": size,
"digest": "sovyn-local-pytorch",
"details": {
"parent_model": "",
"format": "pytorch",
"family": "sovyn",
"families": ["sovyn"],
"parameter_size": "300M",
"quantization_level": "BF16",
},
}
]
}
def json_bytes(payload: dict) -> bytes:
return json.dumps(payload, ensure_ascii=False).encode("utf-8")
def get_last_user_and_system(messages: list[dict]) -> tuple[str, str | None]:
system = None
user = ""
for message in messages:
role = message.get("role")
content = message.get("content", "")
if role == "system" and content:
system = content
elif role == "user" and content:
user = content
return user, system
def make_handler(runtime: SovynRuntime):
class Handler(BaseHTTPRequestHandler):
server_version = "SOVYN-Ollama-Bridge/0.1"
def log_message(self, fmt, *args):
sys.stdout.write("%s - %s\n" % (self.address_string(), fmt % args))
sys.stdout.flush()
def send_json(self, status: int, payload: dict):
body = json_bytes(payload)
self.send_response(status)
self.send_header("Content-Type", "application/json; charset=utf-8")
self.send_header("Content-Length", str(len(body)))
self.end_headers()
self.wfile.write(body)
def send_stream_json(self, payload: dict):
body = json_bytes(payload) + b"\n"
self.send_response(200)
self.send_header("Content-Type", "application/x-ndjson; charset=utf-8")
self.end_headers()
self.wfile.write(body)
def read_payload(self) -> dict:
length = int(self.headers.get("Content-Length", "0"))
if length <= 0:
return {}
raw = self.rfile.read(length).decode("utf-8")
return json.loads(raw) if raw else {}
def do_GET(self):
if self.path == "/" or self.path == "/api/version":
self.send_json(200, {"version": "sovyn-ollama-bridge-0.1"})
elif self.path == "/api/tags":
self.send_json(200, runtime.tags())
else:
self.send_json(404, {"error": f"unknown route: {self.path}"})
def do_POST(self):
started = time.perf_counter_ns()
try:
payload = self.read_payload()
if self.path == "/api/generate":
prompt = payload.get("prompt", "")
options = payload.get("options") or {}
answer = runtime.reply(prompt, options=options)
response = {
"model": runtime.model_name,
"created_at": now_iso(),
"response": answer,
"done": True,
"total_duration": time.perf_counter_ns() - started,
}
if payload.get("stream", True):
self.send_stream_json(response)
else:
self.send_json(200, response)
elif self.path == "/api/chat":
user, system = get_last_user_and_system(payload.get("messages", []))
options = payload.get("options") or {}
answer = runtime.reply(user, system=system, options=options)
response = {
"model": runtime.model_name,
"created_at": now_iso(),
"message": {"role": "assistant", "content": answer},
"done": True,
"total_duration": time.perf_counter_ns() - started,
}
if payload.get("stream", True):
self.send_stream_json(response)
else:
self.send_json(200, response)
elif self.path == "/api/show":
self.send_json(
200,
{
"modelfile": "FROM SOVYN PyTorch checkpoint via local bridge",
"parameters": "temperature 0.7\ntop_k 20",
"template": "{{ .Prompt }}",
"details": runtime.tags()["models"][0]["details"],
},
)
else:
self.send_json(404, {"error": f"unknown route: {self.path}"})
except Exception as exc:
self.send_json(500, {"error": str(exc)})
return Handler
def main():
parser = argparse.ArgumentParser()
parser.add_argument("--checkpoint", default="checkpoints/sovyn_300m_last.pt")
parser.add_argument("--tokenizer", default="tokenizer_300m/sovyn.model")
parser.add_argument("--model-name", default="sovyn:300m")
parser.add_argument("--host", default="127.0.0.1")
parser.add_argument("--port", type=int, default=11434)
parser.add_argument("--device", default="cuda")
parser.add_argument("--max-new-tokens", type=int, default=64)
parser.add_argument("--temperature", type=float, default=0.0)
parser.add_argument("--top-k", type=int, default=0)
parser.add_argument("--best-of", type=int, default=1)
args = parser.parse_args()
runtime = SovynRuntime(args)
server = ThreadingHTTPServer((args.host, args.port), make_handler(runtime))
print(f"SOVYN Ollama-compatible API listening on http://{args.host}:{args.port}")
print(f"model: {runtime.model_name}, device: {runtime.device}")
server.serve_forever()
if __name__ == "__main__":
main()
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