OpenAI SDK¶

Simple code examples¶

The following examples show how to make requests to the OpenAI SDKs with Python, JavaScript/TypeScript, and curl.

Use the following code to help you get started with the Python SDK:

from openai import OpenAI

client = OpenAI(
api_key="<SNOWFLAKE_PAT>",
base_url="https://<account-identifier>.snowflakecomputing.com/api/v1/openai"
)

response = client.chat.completions.create(
model="<model_name>",
messages=[
      {"role": "system", "content": "You are a helpful assistant."},
      {
          "role": "user",
          "content": "How does a snowflake get its unique pattern?"
      }
  ]
)

print(response.choices[0].message)

In the preceding code, specify values for the following:

• base_url: Replace <account-identifier> with your Snowflake account identifier.

• api_key: Replace <SNOWFLAKE_PAT> with your Snowflake Programmatic Access Token (PAT).

• model: Replace <model_name> with the name of the model you want to use. For a list of supported models, see Snowflake Cortex AISQL (including LLM functions).

Use the following code to help you get started with the JavaScript/TypeScript SDK:

import OpenAI from "openai";

const openai = new OpenAI({
    apikey="SNOWFLAKE_PAT",
    baseURL: "https://<account-identifier>.snowflakecomputing.com/api/v1/openai"
});

const response = await openai.chat.completions.create({
    model: "claude-3-7-sonnet",
    messages: [
        { role: "system", content: "You are a helpful assistant." },
        {
            role: "user",
            content: "How does a snowflake get its unique pattern?",
        },
    ],
});

console.log(response.choices[0].message);

In the preceding code, specify values for the following:

• baseURL: Replace <account-identifier> with your Snowflake account identifier.

• apikey: Replace SNOWFLAKE_PAT with your Snowflake Personal Access Token (PAT).

• model: Replace <model_name> with the name of the model you want to use. For a list of supported models, see Snowflake Cortex AISQL (including LLM functions).

Use the following curl command to make a request to the Snowflake-hosted model:

curl "https://<account-identifier>.snowflakecomputing.com/api/v1/openai/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer <SNOWFLAKE_PAT>" \
-d '{
    "model": "<model_name>",
    "messages": [
        {"role": "user", "content": "How does a snowflake get its unique pattern?"}
    ]
    }'

In the preceding code, specify values for the following:

• <account-identifier>: Replace <account-identifier> with your Snowflake account identifier.

• <SNOWFLAKE_PAT>: Replace <SNOWFLAKE_PAT> with your Snowflake Personal Access Token (PAT).

• <model_name>: Replace <model_name> with the name of the model you want to use. For a list of supported models, see Snowflake Cortex AISQL (including LLM functions).

Stream responses¶

You can stream responses from the REST API by setting the stream parameter to True in the request.

The following Python code streams a response from the REST API:

from openai import OpenAI

client = OpenAI(
api_key="<SNOWFLAKE_PAT>",
base_url="https://<account-identifier>.snowflakecomputing.com/api/v1/openai"
)

response = client.chat.completions.create(
model="<model_name>",
messages=[
  {"role": "system", "content": "You are a helpful assistant."},
  {
      "role": "user",
      "content": "How does a snowflake get its unique pattern?"
  }
],
  stream=True
)

for event in stream:
print(event)
response = client.chat.completions.create(
model="<model_name>",
messages=[
      {"role": "system", "content": "You are a helpful assistant."},
      {
          "role": "user",
          "content": "How does a snowflake get its unique pattern?"
      }
  ],
  stream=True
)

for chunk in response:
    print(chunk.choices[0].delta.content, end="", flush=True)

The following JavaScript/TypeScript code streams a response from the REST API:

import OpenAI from "openai";

const openai = new OpenAI({
    apikey="SNOWFLAKE_PAT",
    baseURL: "https://<account-identifier>.snowflakecomputing.com/api/v1/openai"
});

const stream = await openai.chat.completions.create({
    model: "<model_name>",
    messages: [
        { role: "system", content: "You are a helpful assistant." },
        {
            role: "user",
            content: "How does a snowflake get its unique pattern?",
        },
    ],
    stream:true,
});


for await (const event of stream) {
console.log(event);
}

The following curl command streams a response from the Snowflake-hosted model:

curl "https://<account-identifier>.snowflakecomputing.com/api/v1/openai/chat/completions" \
-H "Content-Type: application/json" \
-H "Authorization: Bearer SNOWFLAKE_PAT" \
-d '{
    "model": "<model_name>",
    "messages": [
        {"role": "user", "content": "How does a snowflake get its unique pattern?"}
    ],
    "stream": true
    }'