OCI-OpenAI is a client library jointly maintained by the Oracle Cloud Infrastructure (OCI) Generative AI and OCI Data Science teams.
This package simplifies integration between OpenAI’s Python SDK and Oracle Cloud Infrastructure services — supporting both the OCI Generative AI Service and the OCI Data Science Model Deployment service. It provides robust authentication and authorization utilities that allow developers to securely connect to and invoke OCI-hosted large language models (LLMs) using standard OpenAI-compatible APIs.
By leveraging this library, you can:
- Seamlessly connect to OCI Generative AI endpoints.
- Interact with OCI Data Science Model Deployment LLM endpoints using the same OpenAI-style interface.
- Ensure compliance with OCI security and access control best practices.
pip install oci-openaifrom oci_openai import OciOpenAI, OciSessionAuth
client = OciOpenAI(
service_endpoint="https://inference.generativeai.us-chicago-1.oci.oraclecloud.com",
auth=OciSessionAuth(profile_name="<profile name>"),
compartment_id="<compartment ocid>",
)
completion = client.chat.completions.create(
model="<model name>",
messages=[
{
"role": "user",
"content": "How do I output all files in a directory using Python?",
},
],
)
print(completion.model_dump_json())from oci_openai import AsyncOciOpenAI, OciSessionAuth
client = AsyncOciOpenAI(
service_endpoint="https://inference.generativeai.us-chicago-1.oci.oraclecloud.com",
auth=OciSessionAuth(profile_name="<profile name>"),
compartment_id="<compartment ocid>",
)
completion = await client.chat.completions.create(
model="<model name>",
messages=[
{
"role": "user",
"content": "How do I output all files in a directory using Python?",
},
],
)
print(completion.model_dump_json())import httpx
from openai import OpenAI
from oci_openai import OciSessionAuth
# Example for OCI Data Science Model Deployment endpoint
client = OpenAI(
api_key="OCI",
base_url="https://inference.generativeai.us-chicago-1.oci.oraclecloud.com/20231130/actions/v1",
http_client=httpx.client(auth=OciSessionAuth()),
)
response = client.chat.completions.create(
model="<model-name>",
messages=[
{
"role": "user",
"content": "Explain how to list all files in a directory using Python.",
},
],
)
print(response.model_dump_json())from oci_openai import OciOpenAI, OciSessionAuth
client = OciOpenAI(
service_endpoint="https://modeldeployment.us-ashburn-1.oci.customer-oci.com/<OCID>/predict/v1",
auth=OciSessionAuth(profile_name="<profile name>")
)
response = client.chat.completions.create(
model="<model-name>",
messages=[
{
"role": "user",
"content": "Explain how to list all files in a directory using Python.",
},
],
)
print(response.model_dump_json())from oci_openai import AsyncOciOpenAI, OciSessionAuth
# Example for OCI Data Science Model Deployment endpoint
client = AsyncOciOpenAI(
service_endpoint="https://modeldeployment.us-ashburn-1.oci.customer-oci.com/<OCID>/predict/v1",
auth=OciSessionAuth(profile_name="<profile name>")
)
response = await client.chat.completions.create(
model="<model-name>",
messages=[
{
"role": "user",
"content": "Explain how to list all files in a directory using Python.",
},
],
)
print(response.model_dump_json())import httpx
from openai import OpenAI
from oci_openai import OciSessionAuth
# Example for OCI Data Science Model Deployment endpoint
client = OpenAI(
api_key="OCI",
base_url="https://modeldeployment.us-ashburn-1.oci.customer-oci.com/<OCID>/predict/v1",
http_client=httpx.client(auth=OciSessionAuth()),
)
response = client.chat.completions.create(
model="<model-name>",
messages=[
{
"role": "user",
"content": "Explain how to list all files in a directory using Python.",
},
],
)
print(response.model_dump_json())The library supports multiple OCI authentication methods (signers). Choose the one that matches your runtime environment and security posture.
Supported signers
OciSessionAuth— Uses an OCI session token from your local OCI CLI profile.OciResourcePrincipalAuth— Uses Resource Principal auth.OciInstancePrincipalAuth— Uses Instance Principal auth. Best for OCI Compute instances with dynamic group policies.OciUserPrincipalAuth— Uses an OCI user API key. Suitable for service accounts/automation where API keys are managed securely.
Minimal examples of constructing each auth type:
from oci_openai import (
OciOpenAI,
OciSessionAuth,
OciResourcePrincipleAuth,
OciInstancePrincipleAuth,
OciUserPrincipleAuth,
)
# 1) Session (local dev; uses ~/.oci/config + session token)
session_auth = OciSessionAuth(profile_name="DEFAULT")
# 2) Resource Principal (OCI services with RP)
rp_auth = OciResourcePrincipleAuth()
# 3) Instance Principal (OCI Compute)
ip_auth = OciInstancePrincipleAuth()
# 4) User Principal (API key in ~/.oci/config)
up_auth = OciUserPrincipleAuth(profile_name="DEFAULT")This project welcomes contributions from the community. Before submitting a pull request, please review our contribution guide.
Please consult the security guide for our responsible security vulnerability disclosure process.
Copyright (c) 2025 Oracle and/or its affiliates.
Released under the Universal Permissive License v1.0 as shown at https://oss.oracle.com/licenses/upl/
