values[0] = v;
  return TF_NewTensor(TF_DOUBLE, nullptr, 0, values, num_bytes,
                      &DoubleDeallocator, nullptr);
}

TF_Tensor* FloatTensor(float v) {
  const int num_bytes = sizeof(float);
  float* values = new float[1];
  values[0] = v;
  return TF_NewTensor(TF_FLOAT, nullptr, 0, values, num_bytes,
                      &FloatDeallocator, nullptr);
}

from fastapi import FastAPI

app = FastAPI()


@app.post("/index-weights/")
async def create_index_weights(weights: dict[int, float]):

    "aliases" : { },
    "mappings" : {
      "web_config" : {
        "properties" : {
          "available" : {
            "type" : "boolean"
          },
          "boost" : {
            "type" : "float"
          },
          "configParameter" : {
            "type" : "keyword"
          },
          "createdBy" : {
            "type" : "keyword"
          },
          "createdTime" : {

from fastapi import FastAPI

app = FastAPI()


@app.get("/keyword-weights/", response_model=dict[str, float])
async def read_keyword_weights():

    }
}
```

🔄, 🤸 👈 📄, ⏮️ **FastAPI** 👆 🤚:

* 👨‍🎨 🐕‍🦺 (🛠️, ♒️), 🐦 🏷
* 💽 🛠️
* 💽 🔬
* 🏧 🧾

## 🎁 🆎 & 🔬

↖️ ⚪️➡️ 😐 ⭐ 🆎 💖 `str`, `int`, `float`, ♒️. 👆 💪 ⚙️ 🌅 🏗 ⭐ 🆎 👈 😖 ⚪️➡️ `str`.

👀 🌐 🎛 👆 ✔️, 🛒 🩺 <a href="https://docs.pydantic.dev/latest/concepts/types/" class="external-link" target="_blank">Pydantic 😍 🆎</a>. 👆 🔜 👀 🖼 ⏭ 📃.

    }

    public void setBoost_Equal(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Equal(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {
        setBoost_Term(boost, opLambda);
    }

    public void setBoost_Term(Float boost) {
        setBoost_Term(boost, null);
    }

    public void setBoost_Term(Float boost, ConditionOptionCall<TermQueryBuilder> opLambda) {

      "depth": {
        "type": "integer"
      },
      "parentUrl": {
        "type": "keyword"
      },
      "method": {
        "type": "keyword"
      },
      "weight": {
        "type": "float"
      },
      "createTime": {
        "type": "long"
      },
      "lastModified": {
        "type": "long"
      },
      "sessionId": {
        "type": "keyword"
      },
      "url": {

{
  "fess_config.elevate_word" : {
    "aliases" : { },
    "mappings" : {
      "elevate_word" : {
        "properties" : {
          "boost" : {
            "type" : "float"
          },
          "createdBy" : {
            "type" : "keyword"
          },
          "createdTime" : {
            "type" : "long"
          },
          "permissions" : {
            "type" : "keyword"
          },
          "reading" : {

            docMap.put(fessConfig.getResponseFieldSitePath(), viewHelper.getSitePath(docMap));
        }

        if (!docMap.containsKey(Constants.SCORE)) {
            final float score = searchHit.getScore();
            if (Float.isFinite(score)) {
                docMap.put(Constants.SCORE, score);
            }
        }

        if (!docMap.containsKey(fessConfig.getIndexFieldId())) {

from fastapi import FastAPI
from pydantic import BaseModel

app = FastAPI()


class Item(BaseModel):
    name: str
    price: float


class ResponseMessage(BaseModel):
    message: str


@app.post("/items/", response_model=ResponseMessage)
async def create_item(item: Item):
    return {"message": "item received"}


@app.get("/items/", response_model=list[Item])
async def get_items():
    return [