> ## Documentation Index
> Fetch the complete documentation index at: https://www.adaline.ai/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# PromptSnapshot

# PromptSnapshot

The complete prompt configuration captured at deployment time. Contains model config, messages, tools, and variable definitions.

## Overview

`PromptSnapshot` is the prompt payload inside a [Deployment](/docs/reference/sdk/v2/python/types/deployment). When you call `get_deployment()` or `get_latest_deployment()`, the returned `Deployment.prompt` field is a `PromptSnapshot`.

```python theme={null}
from adaline_api.models.prompt_snapshot import PromptSnapshot
```

***

## Fields

<ParamField body="config" type="PromptSnapshotConfig" required>
  Model provider and settings. See [PromptSnapshotConfig](/docs/reference/sdk/v2/python/types/PromptSnapshotConfig).
</ParamField>

<ParamField body="messages" type="list[PromptMessage]" required>
  Array of prompt messages (role and content). See [PromptMessage](/docs/reference/sdk/v2/python/types/PromptMessage).
</ParamField>

<ParamField body="tools" type="list[ToolFunction]" required>
  Array of tool/function definitions available to the model. See [ToolFunction](/docs/reference/sdk/v2/python/types/ToolFunction).
</ParamField>

<ParamField body="variables" type="list[PromptVariable]" required>
  Array of variable definitions used in the prompt template. See [PromptVariable](/docs/reference/sdk/v2/python/types/PromptVariable).
</ParamField>

***

## Examples

### Accessing from a Deployment

```python theme={null}
from adaline.main import Adaline

adaline = Adaline()

deployment = await adaline.get_latest_deployment(
    prompt_id="prompt_abc123",
    deployment_environment_id="environment_abc123"
)

prompt: PromptSnapshot = deployment.prompt

print(f"Provider: {prompt.config.provider_name}")
print(f"Model: {prompt.config.model}")
print(f"Messages: {len(prompt.messages)}")
print(f"Tools: {len(prompt.tools)}")
print(f"Variables: {[v.name for v in prompt.variables]}")
```

### Inspecting Messages and Tools

```python theme={null}
from adaline_api.models.prompt_message import PromptMessage
from adaline_api.models.text_content import TextContent

prompt = deployment.prompt

for msg in prompt.messages:
    for c in msg.content:
        if isinstance(c.actual_instance, TextContent):
            print(f"[{msg.role}] {c.actual_instance.value}")

for tool in prompt.tools:
    fn = tool.definition.var_schema
    print(f"Tool: {fn.name} — {fn.description}")
```

### Using with a Provider SDK

```python theme={null}
import re
from adaline.main import Adaline
from openai import OpenAI

adaline = Adaline()
openai_client = OpenAI()

deployment = await adaline.get_latest_deployment(
    prompt_id="prompt_abc123",
    deployment_environment_id="environment_abc123",
)

# Replace {{variable_name}} placeholders with your runtime values.
# See PromptVariable for the full pattern (text + image + PDF).
variables = {"user_name": "Alice"}
pattern = re.compile(r"\{\{(\w+)\}\}")
for message in deployment.prompt.messages:
    for c in message.content:
        if c.modality == "text":
            c.value = pattern.sub(
                lambda m: str(variables.get(m.group(1), m.group(0))),
                c.value,
            )

config = deployment.prompt.config
response = openai_client.chat.completions.create(
    model=config.model,
    messages=[...],  # Build from deployment.prompt.messages
    temperature=config.settings.get("temperature"),
    max_tokens=config.settings.get("maxTokens"),
)
```

***

## Serialization

```python theme={null}
from adaline_api.models.prompt_snapshot import PromptSnapshot

prompt = deployment.prompt

d = prompt.to_dict()
j = prompt.to_json()

restored = PromptSnapshot.from_dict(d)
restored = PromptSnapshot.from_json(j)
```

***

## JSON Example

```json theme={null}
{
  "config": {
    "provider_name": "openai",
    "provider_id": "provider_abc123",
    "model": "gpt-4o",
    "settings": { "temperature": 0.7, "maxTokens": 1000 }
  },
  "messages": [
    {
      "role": "system",
      "content": [
        { "modality": "text", "value": "You are a helpful assistant." }
      ]
    }
  ],
  "tools": [],
  "variables": [
    { "name": "user_name", "modality": "text" }
  ]
}
```