### CLI Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to list available language models using the CLI.

```bash
gdplabs models list
```

--------------------------------

### REST API Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to list available language models using the REST API.

```bash
curl https://api.gdplabs.com/v1/models \
  -H "Authorization: Bearer YOUR_API_KEY"
```

--------------------------------

### Instantiate a Model

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to instantiate a model with specific parameters.

```python
instruction="You are a helpful assistant.",
model=Model(
    id="deepinfra/Qwen/Qwen3-30B-A3B",
    credentials="your-deepinfra-api-key", # Override default credential lookup
    hyperparameters={
        "temperature": 0.7,
        "max_tokens": 4096,
    },
)
```

--------------------------------

### Agent Configuration Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to configure an agent with a specific model and name.

```json
124:["$","span","18",{"className":"highlight-line","aria-label":"$undefined","style":{"color":"light-dark(inherit, inherit)","--shiki-light":"inherit","--shiki-dark":"inherit","backgroundColor":"light-dark(inherit, inherit)","--shiki-light-bg":"inherit","--shiki-dark-bg":"inherit"},"children":[false,["$","span",null,{"className":"highlight-line-content","children":[[["$","span","0",{"style":{"color":"light-dark(inherit, inherit)","--shiki-light":"inherit","--shiki-dark":"inherit"},"children":["agent "]},"$","span","1",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-11)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-11))"},"children":["="]},"$","span","2",{"style":{"color":"light-dark(inherit, inherit)","--shiki-light":"inherit","--shiki-dark":"inherit"},"children":[" "]},"$","span","3",{"style":{"color":"light-dark(rgb(var(--primary-10)), rgb(var(--primary-11)))","--shiki-light":"rgb(var(--primary-10))","--shiki-dark":"rgb(var(--primary-11))"},"children":["Agent"]},"$","span","4",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":["("]},"\n"]}]}]}]]
125:["$","span","19",{"className":"highlight-line","aria-label":"$undefined","style":{"color":"light-dark(inherit, inherit)","--shiki-light":"inherit","--shiki-dark":"inherit","backgroundColor":"light-dark(inherit, inherit)","--shiki-light-bg":"inherit","--shiki-dark-bg":"inherit"},"children":[false,["$","span",null,{"className":"highlight-line-content","children":[[["$","span","0",{"style":{"color":"light-dark(rgb(var(--primary-10)), rgb(var(--primary-11)))","--shiki-light":"rgb(var(--primary-10))","--shiki-dark":"rgb(var(--primary-11))"},"children":[" "]},"$","span","1",{"style":{"color":"light-dark(rgb(var(--warning-10)), rgb(var(--warning-11)))","--shiki-light":"rgb(var(--warning-10))","--shiki-dark":"rgb(var(--warning-11))"},"children":["name"]},"$","span","2",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-11)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-11))"},"children":["="]},"$","span","3",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":["\""]},"$","span","4",{"style":{"color":"light-dark(rgb(var(--success-10)), rgb(var(--success-11)))","--shiki-light":"rgb(var(--success-10))","--shiki-dark":"rgb(var(--success-11))"},"children":["creative"]},"$","span","5",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":["\""]},"$","span","6",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":[","]},"\n"]}]}]}]]
126:["$","span","20",{"className":"highlight-line","aria-label":"$undefined","style":{"color":"light-dark(inherit, inherit)","--shiki-light":"inherit","--shiki-dark":"inherit","backgroundColor":"light-dark(inherit, inherit)","--shiki-light-bg":"inherit","--shiki-dark-bg":"inherit"},"children":[false,["$","span",null,{"className":"highlight-line-content","children":[[["$","span","0",{"style":{"color":"light-dark(rgb(var(--primary-10)), rgb(var(--primary-11)))","--shiki-light":"rgb(var(--primary-10))","--shiki-dark":"rgb(var(--primary-11))"},"children":[" "]},"$","span","1",{"style":{"color":"light-dark(rgb(var(--warning-10)), rgb(var(--warning-11)))","--shiki-light":"rgb(var(--warning-10))","--shiki-dark":"rgb(var(--warning-11))"},"children":["name"]},"$","span","2",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":["="]},"$","span","3",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":["\""]},"$","span","4",{"style":{"color":"light-dark(rgb(var(--success-10)), rgb(var(--success-11)))","--shiki-light":"rgb(var(--success-10))","--shiki-dark":"rgb(var(--success-11))"},"children":["creative"]},"$","span","5",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":["\""]},"$","span","6",{"style":{"color":"light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))","--shiki-light":"rgb(var(--tint-11))","--shiki-dark":"rgb(var(--tint-12))"},"children":[","]},"\n"]}]}]}]
```

--------------------------------

### Example CLI Command

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

This snippet shows an example of importing a language model using the CLI.

```bash
from glaip_sdk import import
```

--------------------------------

### OpenAI Agent Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to configure an agent for OpenAI models.

```python
agent = Agent(
    name="analysis",
    instruction="You are a precise analyst.",
    model="openai/gpt-5"
)
```

--------------------------------

### Python SDK Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to list available language models using the Python SDK.

```python
from gdplabs import Client

client = Client(api_key="YOUR_API_KEY")

models = client.models.list()

for model in models:
    print(f"- {model.id} ({model.provider})")
```

--------------------------------

### DeepInfra Agent Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to configure an agent for DeepInfra models.

```python
# DeepInfra: deepinfra/<org>/<model-name>
agent = Agent(
    name="research",
    instruction="You are a research assistant.",
    model="deepinfra/Qwen/Qwen3-30B-A3B"
)
```

--------------------------------

### Custom Model Configuration

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example demonstrating how to configure custom endpoints, credentials, and hyperparameters for models.

```javascript
self.__next_f.push([
  1,
  "}"
])
78:["$","p","VMX7w6rwxxc7",{"className":"has-[.button,input]:flex has-[.button,input]:flex-wrap has-[.button,input]:gap-2 has-[.button,input]:items-center decoration-primary/6 max-w-3xl w-full print:break-inside-avoid text-start self-start justify-start","children":[[ "$","$1","mIXkn6KvRGMv",{"children":[[ "$","$1","0",{"children": "For custom endpoints, credentials, and hyperparameters not covered by the standard format, use the "}],[ "$","$1","1",{"children":[[ "$","code","mark",{"className":"py-px px-1.5 min-w-6.5 justify-center items-center ring-1 ring-inset ring-tint bg-tint rounded-sm text-[.875em] leading-[calc(max(1.20em,1.25rem))] break-words hyphens-none","children": "Model"}]],[ "$","$1","2",{"children": " class:"}]]}]]}
7b:["$","h4","hFSsWjXVQR3T",{"id":"custom-deepinfra-model-with-credentials","className":"text-base @xs:text-lg @lg:text-xl font-semibold heading pdf-heading flex items-baseline scroll-mt-(--content-scroll-margin) text-start self-start justify-start relative group/hash decoration-primary/6 max-w-3xl w-full print:break-inside-avoid column-first-of-type:pt-0 pt-[0.5em]","data-pdf-heading":true,"children":[[ "$","div",null,{"className":"relative hash grid grid-area-1-1 h-[1em] border-0 opacity-0 site-background rounded group-hover/hash:opacity-[0] group-focus/hash:opacity-[0] md:group-hover/hash:opacity-[1] md:group-focus/hash:opacity-[1] -ml-6 pr-2 [.flip-heading-hash_&]:order-last [.flip-heading-hash_&]:ml-1 [.flip-heading-hash_&]:pl-2","children":[[ "$","$L4e",null,{"href":"#custom-deepinfra-model-with-credentials","aria-label":"Direct link to heading","className":"inline-flex h-full items-start leading-snug","children":[[ "$","$L5b",null,{"icon":"hashtag","className":"self-center transition-colors text-transparent group-hover/hash:text-tint-subtle contrast-more:group-hover/hash:text-tint-strong size-4"}]}]],[ "$","div",null,{"className":"flex-1 z-1 justify-self-start max-w-full break-words text-start self-start justify-start leading-snug","children":[[ "$","$1","dN5yVPYnO5Zd",{"children":[[ "$","$1","0",{"children": "Custom DeepInfra Model with Credentials"}]]}]}]],]}]}
```

--------------------------------

### OpenAI Model Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to specify an OpenAI model.

```python
# OpenAI: openai/<model-name>
agent = Agent(
```

--------------------------------

### Agent Initialization and Execution

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of initializing an Agent with specific parameters like name, instruction, and model, and then running a task.

```python
from glaip_sdk import Agent

# This works locally IF the model is available locally
# (API key and base_url resolved automatically for known providers)
agent = Agent(
    name="research",
    instruction="You are a research assistant.",
    model="deepinfra/Qwen/Qwen3-30B-A3B"
)

# Local execution - uses local credentials and base_url
result = agent.run("Research quantum computing")
```

--------------------------------

### Anthropic Agent Example

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of how to configure an agent for Anthropic models.

```python
# Anthropic: anthropic/<model-name>
agent = Agent(
    name="creative",
    instruction="You are a creative writer.",
    model="anthropic/claude-sonnet-4-0"
)
```

--------------------------------

### Agent Initialization and Local Execution

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Demonstrates how to initialize an Agent with specific parameters (name, instruction, model) and then run it for local execution using the OPENAI_API_KEY environment variable.

```python
from glaip_sdk import Agent

agent = Agent(
    name="my-agent",
    instruction="You are helpful.",
    model="openai/gpt-5"
)

# Local execution - uses local OPENAI_API_KEY
result = agent.run("Hello!")
```

--------------------------------

### Initialize Agent with Custom Model

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of initializing an Agent with a custom model configuration, including name, instruction, and model details.

```python
from glaip_sdk import Agent

agent = Agent(
    name="kimi-agent",
    instruction="You are helpful.",
    model="custom/kimi-k2.5", # Use provider/name format
)
```

--------------------------------

### Deploy and run Kimi agent on AIP server

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of initializing an Agent with a custom Kimi model and then deploying and running it on the AIP server.

```python
from glaip_sdk import Agent

agent = Agent(
    name="kimi-agent",
    instruction="You are helpful.",
    model="custom/kimi-k2.5",  # Use provider/name format
)

# Deploy and run on AIP server
agent.deploy()
result = agent.run("Hello!")
```

--------------------------------

### Agent Deployment and Execution

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example demonstrating how to deploy and run an agent using the GL-AIP SDK. The agent is configured with a specific model and instructions.

```python
from glaip_sdk import Agent
from glaip_sdk.models import Model

agent = Agent(
 name="kimi-agent",
 instruction="You are helpful.",
 model=Model(
 id="custom/kimi-k2.5",
 base_url="https://api.moonshot.ai/v1",
 credentials="sk-xxxx",
 hyperparameters={
 "temperature": 1.0,
 "max_tokens": 32768,
 }
 )
)

result = agent.run("Hello!") # Now runs on AIP server
```

--------------------------------

### Specifying GPT-4o Model

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of specifying the GPT-4o model.

```python
GPT_4O
```

--------------------------------

### Agent Configuration

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example configuration for an agent, specifying its name and role.

```json
{
  "name": "research",
  "instruction": "You are a research assistant."
}
```

--------------------------------

### Create Agent CLI Command

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Example of creating an agent using the CLI with specific instructions and model.

```bash
aip agents create \
 --name analysis \
 --instruction "You are a precise analyst." \
 --model openai/gpt-5
```

--------------------------------

### Example Usage

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

This snippet shows how to use a language model for analysis.

```javascript
self.__next_f.push([
1, "children\": \" \"}
], [
"$", "span", "1", {
"style": {
"color": "light-dark(rgb(var(--warning-10)), rgb(var(--warning-11)))",
"--shiki-light": "rgb(var(--warning-10))",
"--shiki-dark": "rgb(var(--warning-11))"
},
"children": "name"
}
], [
"$", "span", "2", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-11)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-11))"
},
"children": "="
}
], [
"$", "span", "3", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-12))"
},
"children": "\\\""
}
], [
"$", "span", "4", {
"style": {
"color": "light-dark(rgb(var(--success-10)), rgb(var(--success-11)))",
"--shiki-light": "rgb(var(--success-10))",
"--shiki-dark": "rgb(var(--success-11))"
},
"children": "analysis"
}
], [
"$", "span", "5", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-12))"
},
"children": "\\\""
}
], [
"$", "span", "6", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-12))"
},
"children": ","
}
]
], "\\n" 
]
}
]
]
}
]
]
118:[
"$", "span", "6", {
"className": "highlight-line",
"aria-label": "$undefined",
"style": {
"color": "light-dark(inherit, inherit)",
"--shiki-light": "inherit",
"--shiki-dark": "inherit",
"backgroundColor": "light-dark(inherit, inherit)",
"--shiki-light-bg": "inherit",
"--shiki-dark-bg": "inherit"
},
"children": [
false,
[
"$", "span", null,
{
"className": "highlight-line-content",
"children": [
[
[
"$", "span", "0", {
"style": {
"color": "light-dark(rgb(var(--primary-10)), rgb(var(--primary-11)))",
"--shiki-light": "rgb(var(--primary-10))",
"--shiki-dark": "rgb(var(--primary-11))"
},
"children": " "
}
],
[
"$", "span", "1", {
"style": {
"color": "light-dark(rgb(var(--warning-10)), rgb(var(--warning-11)))",
"--shiki-light": "rgb(var(--warning-10))",
"--shiki-dark": "rgb(var(--warning-11))"
},
"children": "instruction"
}
], [
"$", "span", "2", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-11)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-11))"
},
"children": "="
}
], [
"$", "span", "3", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-12))"
},
"children": "\\\""
}
], [
"$", "span", "4", {
"style": {
"color": "light-dark(rgb(var(--success-10)), rgb(var(--success-11)))",
"--shiki-light": "rgb(var(--success-10))",
"--shiki-dark": "rgb(var(--success-11))"
},
"children": "You are a precise analyst."
}
], [
"$", "span", "5", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-12))"
},
"children": "\\\""
}
], [
"$", "span", "6", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-12)))",
"--shiki-light": "rgb(var(--tint-11))",
"--shiki-dark": "rgb(var(--tint-12))"
},
"children": ","
}
]
], "\\n"
}
]
]
}
]
119:[
"$", "span", "7", {
"className": "highlight-line",
"aria-label": "$undefined",
"style": {
"color": "light-dark(inherit, inherit)",
"--shiki-light": "inherit",
"--shiki-dark": "inherit",
"backgroundColor": "light-dark(inherit, inherit)",
"--shiki-light-bg": "inherit",
"--shiki-dark-bg": "inherit"
},
"children": [
false,
[
"$", "span", null,
{
"className": "highlight-line-content",
"children": [
[
[
"$", "span", "0", {
"style": {
"color": "light-dark(rgb(var(--primary-10)), rgb(var(--primary-11)))",
"--shiki-light": "rgb(var(--primary-10))",
"--shiki-dark": "rgb(var(--primary-11))"
},
"children": " "
}
],
[
"$", "span", "1", {
"style": {
"color": "light-dark(rgb(var(--warning-10)), rgb(var(--warning-11)))",
"--shiki-light": "rgb(var(--warning-10))",
"--shiki-dark": "rgb(var(--warning-11))"
},
"children": "model"
}
], [
"$", "span", "2", {
"style": {
"color": "light-dark(rgb(var(--tint-11)), rgb(var(--tint-11)))",
"--shiki-light": "rgb(va
```

--------------------------------

### Creating Agents with Different Model Providers

Source: https://gdplabs.gitbook.io/gl-aip/how-to-guides/language-models-guide

Examples of creating agents using models from OpenAI, DeepInfra, and Anthropic, including the CLI command for agent creation.

```python
    # OpenAI: openai/<model-name>
    agent = Agent(
        name="analysis",
        instruction="You are a precise analyst.",
        model="openai/gpt-5",
    )
    
    # DeepInfra: deepinfra/<org>/<model-name>
    agent = Agent(
        name="research",
        instruction="You are a research assistant.",
        model="deepinfra/Qwen/Qwen3-30B-A3B",
    )
    
    # Anthropic: anthropic/<model-name>
    agent = Agent(
        name="creative",
        instruction="You are a creative writer.",
        model="anthropic/claude-sonnet-4-0",
    )
    
    # CLI also uses the string format
    aip agents create \
      --name analysis \
      --instruction "You are a precise analyst." \
      --model openai/gpt-5
```