Vector

Managed vector store (RAG): collections + upsert/query/delete, self-hosted on pgvector by default.

Overview

Base path: https://api.infrai.cc/v1/vector

Auth header: Authorization: Bearer $INFRAI_API_KEY

bash

# Call any /v1/vector capability over raw HTTP — no SDK to install.
# curl:
curl https://api.infrai.cc/v1/vector/... \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json"

Methods

vector.collection.create

POST /v1/vector/collection/create

Create a vector collection (namespace) for an embedding dimension and distance metric — the container for RAG vectors. Self-hosted on pgvector by default; free management.

Parameters

Name	Type	Required	Description
`collection`	`string`	Required	Collection (namespace) name.
`dimension`	`number`	Required	Embedding vector dimension (required on create; must match the embeddings you upsert).
`metric`	`"cosine" \| "euclidean" \| "dotproduct"`	Optional	Distance metric: cosine (default), euclidean, or dotproduct.
`idempotency_key`	`string`	Optional	Optional dedup key; identical retries return the same result.

Returns

Collection { collection, dimension, metric, vector_count, state }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X POST https://api.infrai.cc/v1/vector/collection/create \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"collection": "...", "dimension": 0}'

python

import os, requests

resp = requests.post(
    "https://api.infrai.cc/v1/vector/collection/create",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
    json={'collection': '...', 'dimension': 0},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/create",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "dimension": 0}),
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/create",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "dimension": 0}),
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

vector.upsert

POST /v1/vector/upsert

Insert or update vectors (id + embedding + metadata) into a collection. Pair ai.embed → vector.upsert for one-stop RAG ingestion. Billable work-action.

Parameters

Name	Type	Required	Description
`collection`	`string`	Required	Collection (namespace) name.
`vectors`	`Array<{ id, embedding: number[], metadata? }>`	Required	Vectors to write: each carries an id, an embedding (number[]) and optional metadata.
`idempotency_key`	`string`	Optional	Optional dedup key; identical retries return the same result.

Returns

UpsertResult { collection, upserted }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X POST https://api.infrai.cc/v1/vector/upsert \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"collection": "...", "vectors": []}'

python

import os, requests

resp = requests.post(
    "https://api.infrai.cc/v1/vector/upsert",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
    json={'collection': '...', 'vectors': []},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/upsert",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "vectors": []}),
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/upsert",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "vectors": []}),
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

vector.query

POST /v1/vector/query

Run an approximate nearest-neighbor (ANN) similarity search over a collection, returning the top-k closest vectors with scores and metadata. Billable work-action.

Parameters

Name	Type	Required	Description
`collection`	`string`	Required	Collection (namespace) name.
`embedding`	`number[]`	Required	Query embedding vector — the nearest neighbors of this point are returned.
`top_k`	`number`	Optional	Number of nearest matches to return (default 10).
`filter`	`Record<string, unknown>`	Optional	Optional metadata filter applied before the similarity search.

Returns

QueryResult { collection, matches: Array<{ id, score, metadata? }> }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X POST https://api.infrai.cc/v1/vector/query \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"collection": "...", "embedding": []}'

python

import os, requests

resp = requests.post(
    "https://api.infrai.cc/v1/vector/query",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
    json={'collection': '...', 'embedding': []},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/query",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "embedding": []}),
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/query",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "embedding": []}),
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

vector.collection.get

GET /v1/vector/collection/get

Fetch a vector collection's configuration (dimension, metric, vector count). Free management read.

Parameters

Name	Type	Required	Description
`collection`	`string`	Required	Collection (namespace) name.

Returns

Collection { collection, dimension, metric, vector_count, state }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X GET https://api.infrai.cc/v1/vector/collection/get \
  -H "Authorization: Bearer $INFRAI_API_KEY"

python

import os, requests

resp = requests.get(
    "https://api.infrai.cc/v1/vector/collection/get",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/get",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/get",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

vector.collection.list

GET /v1/vector/collection/list

List the account's vector collections. Free management read.

Returns

{ collections: Collection[] }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X GET https://api.infrai.cc/v1/vector/collection/list \
  -H "Authorization: Bearer $INFRAI_API_KEY"

python

import os, requests

resp = requests.get(
    "https://api.infrai.cc/v1/vector/collection/list",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/list",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/list",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

vector.collection.delete

DELETE /v1/vector/collection/delete

Delete a vector collection and all its vectors. Free management (idempotent).

Parameters

Name	Type	Required	Description
`collection`	`string`	Required	Collection (namespace) name.
`idempotency_key`	`string`	Optional	Optional dedup key; identical retries return the same result.

Returns

CollectionDeleteResult { collection, deleted }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X DELETE https://api.infrai.cc/v1/vector/collection/delete \
  -H "Authorization: Bearer $INFRAI_API_KEY"

python

import os, requests

resp = requests.delete(
    "https://api.infrai.cc/v1/vector/collection/delete",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

vector.delete

DELETE /v1/vector/delete

Delete specific vectors by id from a collection. Free management.

Parameters

Name	Type	Required	Description
`collection`	`string`	Required	Collection (namespace) name.
`ids`	`string[]`	Required	Vector ids to delete from the collection.
`idempotency_key`	`string`	Optional	Optional dedup key; identical retries return the same result.

Returns

DeleteResult { collection, deleted }

Example

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

curl -X DELETE https://api.infrai.cc/v1/vector/delete \
  -H "Authorization: Bearer $INFRAI_API_KEY"

python

import os, requests

resp = requests.delete(
    "https://api.infrai.cc/v1/vector/delete",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

javascript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

typescript

const resp = await fetch(
  "https://api.infrai.cc/v1/vector/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

All capabilities

Every routed capability in this module — the complete public REST contract. The methods above are the guided walkthrough; this index is the full reference.

Capability	Endpoint	Description
`vector.collection.create`	`POST /v1/vector/collection/create`	Create a vector collection (namespace) for an embedding dimension and distance metric — the container for RAG vectors. Self-hosted on pgvector by default; free management.
`vector.collection.delete`	`DELETE /v1/vector/collection/delete`	Delete a vector collection and all its vectors. Free management (idempotent).
`vector.collection.get`	`GET /v1/vector/collection/get`	Fetch a vector collection's configuration (dimension, metric, vector count). Free management read.
`vector.collection.list`	`GET /v1/vector/collection/list`	List the account's vector collections. Free management read.
`vector.delete`	`DELETE /v1/vector/delete`	Delete specific vectors by id from a collection. Free management.
`vector.query`	`POST /v1/vector/query`	Run an approximate nearest-neighbor (ANN) similarity search over a collection, returning the top-k closest vectors with scores and metadata. Billable work-action.
`vector.upsert`	`POST /v1/vector/upsert`	Insert or update vectors (id + embedding + metadata) into a collection. Pair ai.embed → vector.upsert for one-stop RAG ingestion. Billable work-action.

End-to-end example

A production-style walkthrough of this module: configure once, then run the flow. It exercises most of the module's APIs.

A copy-paste-runnable single-file Python program (stdlib only, no SDK): set your INFRAI_API_KEY, run it, and walk this module's core flow with REAL billed calls — later steps reuse real fields returned by earlier ones. The 12-line helper is the entire integration.

python

#!/usr/bin/env python3
"""Infrai · vector — runnable real-app example (single file, zero deps).

Copy this file, set your key, run it: every step is a REAL call to
api.infrai.cc, billed at the real (tiny) per-call price, printing the
live JSON response. Get a key at https://infrai.cc/login (Google/
GitHub sign-in grants $2 free credit); add funds at
https://infrai.cc/billing. No SDK — the 12-line helper below is the
entire integration."""
import json
import os
from urllib import error, request

KEY = os.environ.get("INFRAI_API_KEY") or "ifr_..."  # <- your key
BASE = "https://api.infrai.cc"


# Same raw HTTPS POST/GET as every per-method example on this page —
# wrapped once for reuse. There is nothing else to it: no SDK.
def infrai(method, path, body=None):
    req = request.Request(
        BASE + path, method=method,
        data=json.dumps(body).encode() if body is not None else None,
        headers={"Authorization": f"Bearer {KEY}",
                 "Content-Type": "application/json"})
    try:
        with request.urlopen(req, timeout=60) as r:
            return json.loads(r.read())
    except error.HTTPError as e:
        return json.loads(e.read())


def show(label, resp):
    print(f"\n== {label} ==")
    print(json.dumps(resp, indent=2, ensure_ascii=False))
    return resp


# 1) vector.collection.create — POST /v1/vector/collection/create · Create a vector collection (namespace) for an embedding dimension and distance metric — the container for RAG vectors. Self-hosted on pgvector by default; free management.
r1 = show("vector.collection.create", infrai("POST", "/v1/vector/collection/create", {"collection":"docs","dimension":3,"metric":"cosine"}))

# 2) vector.upsert — POST /v1/vector/upsert · Insert or update vectors (id + embedding + metadata) into a collection. Pair ai.embed → vector.upsert for one-stop RAG ingestion. Billable work-action.
r2 = show("vector.upsert", infrai("POST", "/v1/vector/upsert", {"collection":"docs","vectors":[{"id":"a","embedding":[0.1,0.2,0.3],"metadata":{"title":"intro"}}]}))

# 3) vector.query — POST /v1/vector/query · Run an approximate nearest-neighbor (ANN) similarity search over a collection, returning the top-k closest vectors with scores and metadata. Billable work-action.
r3 = show("vector.query", infrai("POST", "/v1/vector/query", {"collection":"docs","embedding":[0.1,0.2,0.3],"top_k":3}))

一次性前置(每个范例都假定已完成):

bash

# No SDK to install — every call is a plain HTTPS request.
# Get a project key by signing in at https://infrai.cc/login (Google/GitHub gives
# you $2 free credit; email sign-in starts at $0). On 402 INSUFFICIENT_CREDIT, add
# funds at https://infrai.cc/billing (or POST /v1/account/topup and open the
# returned checkout_url).
export INFRAI_API_KEY="ifr_..."

bash

# 1) Auth: every call is a raw HTTPS request to the Infrai gateway carrying
#    only your project key. No SDK, no install.
#    Get your key: sign in with Google/GitHub at https://infrai.cc/login for a
#    project key + $2 free credit (email sign-in starts at $0). On 402
#    INSUFFICIENT_CREDIT, add funds at https://infrai.cc/billing (or POST
#    /v1/account/topup and open the returned checkout_url).
export INFRAI_API_KEY="ifr_..."   # from https://infrai.cc/login


# 2) vector.collection.create
curl -X POST https://api.infrai.cc/v1/vector/collection/create \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"collection": "...", "dimension": 0}'

# 3) vector.upsert
curl -X POST https://api.infrai.cc/v1/vector/upsert \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"collection": "...", "vectors": []}'

# 4) vector.query
curl -X POST https://api.infrai.cc/v1/vector/query \
  -H "Authorization: Bearer $INFRAI_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"collection": "...", "embedding": []}'

# 5) vector.collection.get
curl -X GET https://api.infrai.cc/v1/vector/collection/get \
  -H "Authorization: Bearer $INFRAI_API_KEY"

# 6) vector.collection.list
curl -X GET https://api.infrai.cc/v1/vector/collection/list \
  -H "Authorization: Bearer $INFRAI_API_KEY"

# 7) vector.collection.delete
curl -X DELETE https://api.infrai.cc/v1/vector/collection/delete \
  -H "Authorization: Bearer $INFRAI_API_KEY"

# 8) vector.delete
curl -X DELETE https://api.infrai.cc/v1/vector/delete \
  -H "Authorization: Bearer $INFRAI_API_KEY"

python

# 1) Auth: every call is a raw HTTPS request carrying only your project key.
#    No SDK to install — just the `requests` library.
import os, requests

BASE = "https://api.infrai.cc"
HEADERS = {
    "Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}",
    "Content-Type": "application/json",
}


# 2) vector.collection.create
import os, requests

resp = requests.post(
    "https://api.infrai.cc/v1/vector/collection/create",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
    json={'collection': '...', 'dimension': 0},
)
resp.raise_for_status()
print(resp.json())

# 3) vector.upsert
import os, requests

resp = requests.post(
    "https://api.infrai.cc/v1/vector/upsert",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
    json={'collection': '...', 'vectors': []},
)
resp.raise_for_status()
print(resp.json())

# 4) vector.query
import os, requests

resp = requests.post(
    "https://api.infrai.cc/v1/vector/query",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
    json={'collection': '...', 'embedding': []},
)
resp.raise_for_status()
print(resp.json())

# 5) vector.collection.get
import os, requests

resp = requests.get(
    "https://api.infrai.cc/v1/vector/collection/get",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

# 6) vector.collection.list
import os, requests

resp = requests.get(
    "https://api.infrai.cc/v1/vector/collection/list",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

# 7) vector.collection.delete
import os, requests

resp = requests.delete(
    "https://api.infrai.cc/v1/vector/collection/delete",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

# 8) vector.delete
import os, requests

resp = requests.delete(
    "https://api.infrai.cc/v1/vector/delete",
    headers={"Authorization": f"Bearer {os.environ['INFRAI_API_KEY']}"},
)
resp.raise_for_status()
print(resp.json())

javascript

// 1) Auth: every call is a raw HTTPS request carrying only your project key.
//    No SDK to install — just the built-in fetch().
const BASE = "https://api.infrai.cc";
const HEADERS = {
  "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
  "Content-Type": "application/json",
};


// 2) vector.collection.create
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/create",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "dimension": 0}),
  },
);
console.log(await resp.json());

// 3) vector.upsert
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/upsert",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "vectors": []}),
  },
);
console.log(await resp.json());

// 4) vector.query
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/query",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "embedding": []}),
  },
);
console.log(await resp.json());

// 5) vector.collection.get
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/get",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

// 6) vector.collection.list
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/list",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

// 7) vector.collection.delete
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

// 8) vector.delete
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
console.log(await resp.json());

typescript

// 1) Auth: every call is a raw HTTPS request carrying only your project key.
//    No SDK to install — just the built-in fetch(), typed.
const BASE = "https://api.infrai.cc";
const HEADERS: Record<string, string> = {
  "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
  "Content-Type": "application/json",
};


// 2) vector.collection.create
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/create",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "dimension": 0}),
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

// 3) vector.upsert
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/upsert",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "vectors": []}),
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

// 4) vector.query
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/query",
  {
    method: "POST",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify({"collection": "...", "embedding": []}),
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

// 5) vector.collection.get
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/get",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

// 6) vector.collection.list
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/list",
  {
    method: "GET",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

// 7) vector.collection.delete
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/collection/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);

// 8) vector.delete
const resp = await fetch(
  "https://api.infrai.cc/v1/vector/delete",
  {
    method: "DELETE",
    headers: {
      "Authorization": `Bearer ${process.env.INFRAI_API_KEY}`,
    },
  },
);
if (!resp.ok) throw new Error(`infrai ${resp.status}`);
const data: unknown = await resp.json();
console.log(data);