Description

# Cohere Python SDK  [](https://pypi.org/project/cohere/)  [](https://github.com/fern-api/fern) The Cohere Python SDK allows access to Cohere models across many different platforms: the cohere platform, AWS (Bedrock, Sagemaker), Azure, GCP and Oracle OCI. For a full list of support and snippets, please take a look at the [SDK support docs page](https://docs.cohere.com/docs/cohere-works-everywhere). ## Documentation Cohere documentation and API reference is available [here](https://docs.cohere.com/). ## Installation ``` pip install cohere ``` ## Usage ```Python import cohere co = cohere.ClientV2() response = co.chat( model="command-r-plus-08-2024", messages=[{"role": "user", "content": "hello world!"}], ) print(response) ``` > [!TIP] > You can set a system environment variable `CO_API_KEY` to avoid writing your api key within your code, e.g. add `export CO_API_KEY=theapikeyforyouraccount` > in your ~/.zshrc or ~/.bashrc, open a new terminal, then code calling `cohere.Client()` will read this key. ## Streaming The SDK supports streaming endpoints. To take advantage of this feature for chat, use `chat_stream`. ```Python import cohere co = cohere.ClientV2() response = co.chat_stream( model="command-r-plus-08-2024", messages=[{"role": "user", "content": "hello world!"}], ) for event in response: if event.type == "content-delta": print(event.delta.message.content.text, end="") ``` ## Oracle Cloud Infrastructure (OCI) The SDK supports Oracle Cloud Infrastructure (OCI) Generative AI service. First, install the OCI SDK: ``` pip install 'cohere[oci]' ``` Then use the `OciClient` or `OciClientV2`: ```Python import cohere # Using OCI config file authentication (default: ~/.oci/config) co = cohere.OciClient( oci_region="us-chicago-1", oci_compartment_id="ocid1.compartment.oc1...", ) response = co.embed( model="embed-english-v3.0", texts=["Hello world"], input_type="search_document", ) print(response.embeddings) ``` ### OCI Authentication Methods **1. Config File (Default)** ```Python co = cohere.OciClient( oci_region="us-chicago-1", oci_compartment_id="ocid1.compartment.oc1...", # Uses ~/.oci/config with DEFAULT profile ) ``` **2. Custom Profile** ```Python co = cohere.OciClient( oci_profile="MY_PROFILE", oci_region="us-chicago-1", oci_compartment_id="ocid1.compartment.oc1...", ) ``` **3. Session-based Authentication (Security Token)** ```Python # Works with OCI CLI session tokens co = cohere.OciClient( oci_profile="MY_SESSION_PROFILE", # Profile with security_token_file oci_region="us-chicago-1", oci_compartment_id="ocid1.compartment.oc1...", ) ``` **4. Direct Credentials** ```Python co = cohere.OciClient( oci_user_id="ocid1.user.oc1...", oci_fingerprint="xx:xx:xx:...", oci_tenancy_id="ocid1.tenancy.oc1...", oci_private_key_path="~/.oci/key.pem", oci_region="us-chicago-1", oci_compartment_id="ocid1.compartment.oc1...", ) ``` **5. Instance Principal (for OCI Compute instances)** ```Python co = cohere.OciClient( auth_type="instance_principal", oci_region="us-chicago-1", oci_compartment_id="ocid1.compartment.oc1...", ) ``` ### Supported OCI APIs The OCI client supports the following Cohere APIs: - **Embed**: Full support for all embedding models - **Chat**: Full support with both V1 (`OciClient`) and V2 (`OciClientV2`) APIs - Streaming available via `chat_stream()` - Supports Command-R and Command-A model families ### OCI Model Availability and Limitations **Available on OCI On-Demand Inference:** - ✅ **Embed models**: available on OCI Generative AI - ✅ **Chat models**: available via `OciClient` (V1) and `OciClientV2` (V2) **Not Available on OCI On-Demand Inference:** - ❌ **Generate API**: OCI TEXT_GENERATION models are base models that require fine-tuning before deployment - ❌ **Rerank API**: OCI TEXT_RERANK models are base models that require fine-tuning before deployment - ❌ **Multiple Embedding Types**: OCI on-demand models only support single embedding type per request (cannot request both `float` and `int8` simultaneously) **Note**: To use Generate or Rerank models on OCI, you need to: 1. Fine-tune the base model using OCI's fine-tuning service 2. Deploy the fine-tuned model to a dedicated endpoint 3. Update your code to use the deployed model endpoint For the latest model availability, see the [OCI Generative AI documentation](https://docs.oracle.com/en-us/iaas/Content/generative-ai/home.htm). ## Contributing While we value open-source contributions to this SDK, the code is generated programmatically. Additions made directly would have to be moved over to our generation code, otherwise they would be overwritte