added 2 funcs for predict

app/main.py

@@ -10,11 +10,14 @@
 from model import Model
 from predict import predict
 from config import CONFIG
+
+
 from schema import (
     InferenceResponse,
     InferenceInput,
     InferenceOutput,
     ErrorResponse,
+    ModelDayInput,
 )
 
 
@@ -55,41 +58,41 @@ async def lifespan(app: FastAPI):
 )
 
 
-@app.post(
-    "/api/v1/predict",
-    response_model=InferenceResponse,
-    responses={422: {"model": ErrorResponse}, 500: {"model": ErrorResponse}},
-)
-def do_predict(request: Request, body: InferenceInput):
-    """
-    Perform prediction on input data
-    """
+# @app.post(
+#     "/api/v1/predict_day",
+#     response_model=InferenceResponse,
+#     responses={422: {"model": ErrorResponse}, 500: {"model": ErrorResponse}},
+# )
+# def do_predict_day(request: Request, body: InferenceInput):
+#     """
+#     Perform prediction on input data
+#     """
 
-    logger.info("API predict called")
-    logger.info(f"input: {body}")
+#     logger.info("API predict called")
+#     logger.info(f"input: {body}")
 
-    # prepare input data
-    X = body
+#     # prepare input data
+#     X = body
 
-    # run model inference
-    y = predict(app.package, [X])
-    # generate prediction based on probablity
-    pred = ["setosa", "versicolor", "virginica"][y.index(max(y))]
+#     # run model inference
+#     y = predict(app.package, [X])
+#     # generate prediction based on probablity
+#     pred = ["setosa", "versicolor", "virginica"][y.index(max(y))]
 
-    # round probablities for json
-    y = list(map(lambda v: round(v, CONFIG["ROUND_DIGIT"]), y))
+#     # round probablities for json
+#     y = list(map(lambda v: round(v, CONFIG["ROUND_DIGIT"]), y))
 
-    # prepare json for returning
-    logger.info(f"results: {y}")
+#     # prepare json for returning
+#     logger.info(f"results: {y}")
 
-    return InferenceResponse(
-        data=InferenceOutput(
-            predicted_value=y[0],
-            predicted_confidence_interval_lower_bound=y[1],
-            predicted_confidence_interval_upper_bound=y[2],
-            text=pred,
-        )
-    )
+#     return InferenceResponse(
+#         data=InferenceOutput(
+#             predicted_value=y[0],
+#             predicted_confidence_interval_lower_bound=y[1],
+#             predicted_confidence_interval_upper_bound=y[2],
+#             text=pred,
+#         )
+#     )
 
 
 @app.get("/api/v1/about")
@@ -112,6 +115,52 @@ def bash(command):
 app.include_router(api_test, prefix="/api/v1", tags=["tests"])
 #############################################
 
+
+@app.post("/api/v1/predict_interval")
+def do_predict_interval():
+    """
+    TODO: Perform prediction on input data
+    """
+    from random import uniform
+
+    return {
+        "data": {
+            "dates": [
+                "2020-01-01",
+                "2020-01-02",
+                "2020-01-03",
+                "2020-01-04",
+                "2020-01-05",
+                "2020-01-06",
+            ],
+            "x": [1, 2, 3, 4, 5, 6],
+            "y_pred": [
+                1.8,
+                2.6,
+                uniform(1.3, 2.2),
+                uniform(2.2, 3.8),
+                uniform(3.3, 3.5),
+                uniform(1.0, 1.3),
+            ],
+            "y_true": [2, 3],
+        }
+    }
+
+
+@app.post(
+    "/api/v1/predict_day",
+    responses={422: {"model": ErrorResponse}, 500: {"model": ErrorResponse}},
+)
+def do_predict_day(data: ModelDayInput):
+    """
+    TODO: Perform prediction on input data
+    """
+    from random import uniform
+
+    logger.info("API predict called")
+    return {"data": uniform(1.0, 100.0)}
+
+
 if __name__ == "__main__":
     uvicorn.run(
         "main:app", host="0.0.0.0", port=8080, reload=True, log_config="log.ini"

app/schema.py

@@ -1,5 +1,5 @@
 from pydantic import BaseModel, Field
-from datetime import datetime
+from datetime import datetime, date
 
 
 class NewsData(BaseModel):
@@ -50,5 +50,49 @@ class InferenceResponse(BaseModel):
     data: InferenceOutput
 
 
+########
+########
+########
+################
+########
+########
+################
+########
+########
+################
+########
+########
+########
+
+
 class TestInput(BaseModel):
+    """Test schema"""
+
     date: str
+
+
+class ModelDayInput(BaseModel):
+    # Necessary
+    CAPITALIZATION: float
+    CLOSE: float
+    DIVISOR: float
+    HIGH: float
+    LOW: float
+    OPEN: float
+    TRADEDATE: date
+    finance: str
+    economic: str
+    politic: str
+
+    # Optional
+    NAME: str
+    SHORTNAME: str
+    SECID: str
+    BOARDID: str
+    DURATION: str
+    YIELD: str
+    DECIMALS: str
+    CURRENCYID: str
+    VOLUME: str
+    TRADINGSESSION: str
+    VALUE: str