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change port and update model #3

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2 changes: 1 addition & 1 deletion player-service-backend/player-service-model/Dockerfile
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Original file line number Diff line number Diff line change
Expand Up @@ -14,5 +14,5 @@ WORKDIR /usr/local/a4a_model
RUN poetry config virtualenvs.create false
RUN poetry install
WORKDIR /usr/local/a4a_model/a4a_model
EXPOSE 5000
EXPOSE 8657
ENTRYPOINT ["python", "server.py"]
35 changes: 21 additions & 14 deletions player-service-backend/player-service-model/README.md
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@@ -1,30 +1,37 @@
# Player Service Model

This is a thin model wrapper container based on `Player.csv` data.
This is a thin model wrapper container based on `Player.csv` data.

To build and run:
To build and run using docker:
```shell
docker build -t a4a_model .
docker run -d -p 5000:5000 a4a_model
docker run -d -p 8657:8657 a4a_model
```
OR, alternatively, using podman:
```shell
podman build -t a4a_model .
podman run --rm -p 8657:8657 -it localhost/a4a_model:latest
```


This will expose port 5000.
This will expose the model on port 8657.

To send an inference request to the AI model using a seed from the database:
To send an inference request to the AI model using player names:
```shell
$ curl -H "Content-type: application/json" -d '{"seed_id":"abbotji01","team_size":10}' http://127.0.0.1:5000/team/generate
{"seed_id":"abbotji01","team_size":10,"member_ids":["abbotji01","combspa01","maurero01","cummijo01","flemida01","macdobo01","eddych01","morriha02","mcgrifr01","blossgr01"]}
$ curl -H "Content-type: application/json" -d '{"seed_id":"abbotji01","team_size":10}' http://127.0.0.1:8657/team/generate
{"seed_id":"abbotji01","prediction_id":"38f5f02f-b1be-4282-8d0e-865b3995d50a","team_size":10,"member_ids":["abbotji01","combspa01","maurero01","cummijo01","flemida01","macdobo01","eddych01","morriha02","mcgrifr01","blossgr01"]}
```

To send an inference request to the AI model using a set of features:
To send an inference request to the AI model using features:
```shell
$ curl -H "Content-type: application/json" -d '{"features":{"birth_year":1970, "height":70, "weight":120, "bats":"R", "throws":"L"},"team_size":10}' http://127.0.0.1:5000/team/generate
To send an inference request to the AI model using a set of features:
```shell
$ curl -H "Content-type: application/json" -d '{"features":{"birth_year":1970, "height":70, "weight":120, "bats":"R", "throws":"L"},"team_size":10}' http://127.0.0.1:8657/team/generate
{"seed_id":null,"prediction_id":"ddedf511-2e68-4ab5-87c5-c77b8d15eb23","team_size":10,"member_ids":["roblevi01","deverra01","goharlu01","albieoz01","barrefr02","urenari01","uriasju01","verdual01","mejiafr01","sierrma01"]}
```
Note that the features are optional, and features that are not provided will be assumed to be the mean values in the training dataset. The unit of weight is pounds. The unit of height is inches. Batting and throwing may be right handed (`R`), left handed (`L`) or no preference (`N`).

To send feedback about the recommendations for a prior seed:
To send feedback about the recommendation of a prior seed:
```shell
$ curl -H "Content-type: application/json" -d '{"seed_id":"abbotji01","member_id":"maurero01","feedback":-1}' http://127.0.0.1:5000/team/feedback
{"seed_id":"abbotji01","member_id":"maurero01","accepted":true}
```
$ curl -H "Content-type: application/json" -d '{"seed_id":"abbotji01","member_id":"maurero01","feedback":-1,"prediction_id":"38f5f02f-b1be-4282-8d0e-865b3995d50a"}' http://127.0.0.1:8657/team/feedback
{"seed_id":"abbotji01","member_id":"maurero01","accepted":true,"prediction_id":"38f5f02f-b1be-4282-8d0e-865b3995d50a"}
```
2 changes: 1 addition & 1 deletion player-service-backend/player-service-model/a4a_model/features_db.csv
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@@ -1,4 +1,4 @@
playerId,birthYear,birthMonth,birthDay,birthCountry,birthState,birthCity,deathYear,deathMonth,deathDay,deathCountry,deathState,deathCity,nameFirst,nameLast,nameGiven,weight,height,bats,throws,debut,finalGame,retroID,bbrefID,birthFraction,birthZ,weightZ,heightZ,batsN,throwsN
playerID,birthYear,birthMonth,birthDay,birthCountry,birthState,birthCity,deathYear,deathMonth,deathDay,deathCountry,deathState,deathCity,nameFirst,nameLast,nameGiven,weight,height,bats,throws,debut,finalGame,retroID,bbrefID,birthFraction,birthZ,weightZ,heightZ,batsN,throwsN
aardsda01,1981.0,12.0,27.0,USA,CO,Denver,,,,,,,David,Aardsma,David Allan,215.0,75.0,R,R,2004-04-06,2015-08-23,aardd001,aardsda01,1.1765707013622462,1.1765707013622462,1.3135157142331944,1.0397594675507622,1.0,1.0
aaronha01,1934.0,2.0,5.0,USA,AL,Mobile,,,,,,,Hank,Aaron,Henry Louis,180.0,72.0,R,R,1954-04-13,1976-10-03,aaroh101,aaronha01,-0.004123827274949573,-0.004123827274949573,-0.3040341982765978,-0.11141752422902394,1.0,1.0
aaronto01,1939.0,8.0,5.0,USA,AL,Mobile,1984.0,8.0,16.0,USA,GA,Atlanta,Tommie,Aaron,Tommie Lee,190.0,75.0,R,R,1962-04-10,1971-09-26,aarot101,aaronto01,0.12958557370318188,0.12958557370318188,0.15812291958334285,1.0397594675507622,1.0,1.0
Expand Down
2 changes: 1 addition & 1 deletion player-service-backend/player-service-model/a4a_model/player.csv
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Original file line number Diff line number Diff line change
@@ -1,4 +1,4 @@
playerId,birthYear,birthMonth,birthDay,birthCountry,birthState,birthCity,deathYear,deathMonth,deathDay,deathCountry,deathState,deathCity,nameFirst,nameLast,nameGiven,weight,height,bats,throws,debut,finalGame,retroID,bbrefID
playerID,birthYear,birthMonth,birthDay,birthCountry,birthState,birthCity,deathYear,deathMonth,deathDay,deathCountry,deathState,deathCity,nameFirst,nameLast,nameGiven,weight,height,bats,throws,debut,finalGame,retroID,bbrefID
aardsda01,1981,12,27,USA,CO,Denver,,,,,,,David,Aardsma,David Allan,215,75,R,R,2004-04-06,2015-08-23,aardd001,aardsda01
aaronha01,1934,2,5,USA,AL,Mobile,,,,,,,Hank,Aaron,Henry Louis,180,72,R,R,1954-04-13,1976-10-03,aaroh101,aaronha01
aaronto01,1939,8,5,USA,AL,Mobile,1984,8,16,USA,GA,Atlanta,Tommie,Aaron,Tommie Lee,190,75,R,R,1962-04-10,1971-09-26,aarot101,aaronto01
Expand Down
17 changes: 11 additions & 6 deletions player-service-backend/player-service-model/a4a_model/server.py
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Expand Up @@ -13,7 +13,7 @@

nn_model = joblib.load("team_model.joblib")
player_db = pd.read_csv("features_db.csv")
all_players = set(player_db["playerId"])
all_players = set(player_db["playerID"])
features = ["birthZ", "heightZ", "weightZ", "batsN", "throwsN"]

@dataclasses.dataclass
Expand Down Expand Up @@ -64,6 +64,8 @@ class TeamFeedbackInput(BaseModel):
seed_id: str
member_id: str
feedback: Literal[-1, 1] # expect -1 or 1
prediction_id: str


class TeamFeedbackOutput(BaseModel):
seed_id: str
Expand All @@ -87,7 +89,7 @@ def generate_team(body: TeamGenerateInput) -> TeamGenerateOutput:
seed = body.seed_id
if body.seed_id:
try:
seed_features = player_db[player_db.playerId == seed][features]
seed_features = player_db[player_db.playerID == seed][features]
except:
raise TeamException(f"The seed {body.seed_id} has no associated player")
elif body.features:
Expand All @@ -106,7 +108,7 @@ def generate_team(body: TeamGenerateInput) -> TeamGenerateOutput:
# run exclusions
print(f"{seed=} {seed_features=} has {exclude_db.get(seed)=}")
member_ids = [m
for m in list(player_db.take(member_indices[0])["playerId"])
for m in list(player_db.take(member_indices[0])["playerID"])
if m not in exclude_db.get(seed, set())]
print(f"{member_ids=}")

Expand All @@ -123,6 +125,7 @@ def generate_team(body: TeamGenerateInput) -> TeamGenerateOutput:
def team_feedback(body: TeamFeedbackInput) -> TeamFeedbackOutput:
seed_id = body.seed_id
member_id = body.member_id
prediction_id = body.prediction_id
accepted = True
if seed_id not in all_players:
accepted = False
Expand All @@ -135,7 +138,8 @@ def team_feedback(body: TeamFeedbackInput) -> TeamFeedbackOutput:
return TeamFeedbackOutput(
seed_id=seed_id,
member_id=member_id,
accepted=accepted
accepted=accepted,
prediction_id=prediction_id or str(uuid.uuid4()),
)


Expand All @@ -154,7 +158,7 @@ class LLMFeedbackOutput(BaseModel):
user_prompt: str

@app.route('/llm/generate', methods=['POST'])
@validate
@validate()
def generate_description(body: LLMInput) -> LLMOutput:
data = request.json
# Implement logic to generate a description based on the provided data
Expand All @@ -163,6 +167,7 @@ def generate_description(body: LLMInput) -> LLMOutput:


@app.route('/llm/feedback', methods=['POST'])
@validate()
def description_feedback(body: LLMFeedbackInput) -> LLMFeedbackOutput:
data = request.json
# Implement logic to process feedback for a description
Expand All @@ -171,4 +176,4 @@ def description_feedback(body: LLMFeedbackInput) -> LLMFeedbackOutput:


if __name__ == '__main__':
app.run(host="0.0.0.0", debug=True)
app.run(host="0.0.0.0", port=8657, debug=True)
18 changes: 9 additions & 9 deletions player-service-backend/player-service-model/a4a_model/train.ipynb
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Expand Up @@ -41,7 +41,7 @@
{
"data": {
"text/plain": [
" playerId birthYear birthMonth birthDay birthCountry birthState \\\n",
" playerID birthYear birthMonth birthDay birthCountry birthState \\\n",
"0 aardsda01 1981.0 12.0 27.0 USA CO \n",
"1 aaronha01 1934.0 2.0 5.0 USA AL \n",
"2 aaronto01 1939.0 8.0 5.0 USA AL \n",
Expand Down Expand Up @@ -83,7 +83,7 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>playerId</th>\n",
" <th>playerID</th>\n",
" <th>birthYear</th>\n",
" <th>birthMonth</th>\n",
" <th>birthDay</th>\n",
Expand Down Expand Up @@ -759,7 +759,7 @@
"cell_type": "code",
"source": [
"def get_nearest_neighbors(id: str, n=25):\n",
" seed = df[df[\"playerId\"] == id][features]\n",
" seed = df[df[\"playerID\"] == id][features]\n",
" neighbor_indices = nn_model.kneighbors(seed, n, return_distance=False)\n",
" return df.take(neighbor_indices[0])[\"id\"]"
],
Expand All @@ -781,7 +781,7 @@
{
"data": {
"text/plain": [
" playerId birthYear birthMonth birthDay birthCountry birthState \\\n",
" playerID birthYear birthMonth birthDay birthCountry birthState \\\n",
"0 aardsda01 1981.0 12.0 27.0 USA CO \n",
"1 aaronha01 1934.0 2.0 5.0 USA AL \n",
"2 aaronto01 1939.0 8.0 5.0 USA AL \n",
Expand Down Expand Up @@ -830,7 +830,7 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>playerId</th>\n",
" <th>playerID</th>\n",
" <th>birthYear</th>\n",
" <th>birthMonth</th>\n",
" <th>birthDay</th>\n",
Expand Down Expand Up @@ -996,7 +996,7 @@
},
"cell_type": "code",
"source": [
"seed = df[df[\"playerId\"] == \"aaronha01\"][features]\n",
"seed = df[df[\"playerID\"] == \"aaronha01\"][features]\n",
"neighbor_indices = nn_model.kneighbors(seed, 25, return_distance=False)\n"
],
"id": "6d35d7781406b91f",
Expand All @@ -1017,7 +1017,7 @@
{
"data": {
"text/plain": [
" playerId birthYear birthMonth birthDay birthCountry birthState \\\n",
" playerID birthYear birthMonth birthDay birthCountry birthState \\\n",
"1 aaronha01 1934.0 2.0 5.0 USA AL \n",
"11649 mendomi01 1933.0 11.0 16.0 Cuba NaN \n",
"4059 davieje01 1933.0 2.0 10.0 USA MI \n",
Expand Down Expand Up @@ -1146,7 +1146,7 @@
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>playerId</th>\n",
" <th>playerID</th>\n",
" <th>birthYear</th>\n",
" <th>birthMonth</th>\n",
" <th>birthDay</th>\n",
Expand Down Expand Up @@ -1832,7 +1832,7 @@
}
},
"cell_type": "code",
"source": "\"aardsda01\" in list(df[\"playerId\"])",
"source": "\"aardsda01\" in list(df[\"playerID\"])",
"id": "db2f862e8f782268",
"outputs": [
{
Expand Down