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File size: 2,796 Bytes
021e065 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 | from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from pydantic import BaseModel
import os
import sys
BASE_DIR = os.path.dirname(os.path.abspath(__file__))
sys.path.append(BASE_DIR)
from model import SentiCommunityEngine, SentiCommunityRLM
app = FastAPI(
title="SentiCommunity RLM API",
description="Service for SACCO dividend management, public finance explanation, and Swahili spend coaching.",
version="2.0.0"
)
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_methods=["*"],
allow_headers=["*"],
)
WEIGHTS_PATH = os.path.join(BASE_DIR, "weights", "community_model.pt")
engine = SentiCommunityEngine(WEIGHTS_PATH)
rlm_engine = SentiCommunityRLM()
class RequestBody(BaseModel):
text: str
tier: str = "A"
@app.get("/")
async def root():
return {"status": "active", "service": "senticommunity", "port": 9216}
@app.get("/health")
async def health():
rlm_health = await rlm_engine.engine.health_check()
return {
"status": "ok",
"rlm_health": rlm_health
}
@app.post("/api/v1/community/sacco")
async def predict_endpoint(body: RequestBody, deep: bool = False):
try:
if deep or body.tier in ("C", "D"):
return await rlm_engine.predict_deep(body.text, body.tier)
return engine.predict(body.text)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/v1/community/score")
async def score_endpoint(body: RequestBody, deep: bool = False):
try:
if deep or body.tier in ("C", "D"):
return await rlm_engine.predict_deep(body.text, body.tier)
return engine.predict(body.text)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.post("/api/v1/community/reason")
async def reason_endpoint(body: RequestBody):
try:
return await rlm_engine.predict_deep(body.text, body.tier)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
@app.on_event("shutdown")
async def shutdown_event():
from senti.core.engines.superpacks.rlm_engine import RLMEngine
await RLMEngine.shutdown()
@app.post("/api/v1/community/predict")
async def predict_endpoint_legacy_alias(body: RequestBody):
try:
# Try different possible engines
if 'engine' in globals():
return engine.predict(body.text)
elif 'rlm_engine' in globals():
return await rlm_engine.predict_deep(body.text, "A")
else:
return {"status": "ok", "service": "senticommunity"}
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
if __name__ == "__main__":
import uvicorn
uvicorn.run(app, host="0.0.0.0", port=9216)
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