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docs/template.md
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# Template
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Ollama provides a powerful templating engine backed by Go's built-in templating engine to construct prompts for your large language model. This feature is a valuable tool to get the most out of your models.
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## Basic Template Structure
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A basic Go template consists of three main parts:
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* **Layout**: The overall structure of the template.
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* **Variables**: Placeholders for dynamic data that will be replaced with actual values when the template is rendered.
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* **Functions**: Custom functions or logic that can be used to manipulate the template's content.
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Here's an example of a simple chat template:
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```gotmpl
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{{- range .Messages }}
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{{ .Role }}: {{ .Content }}
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{{- end }}
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```
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In this example, we have:
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* A basic messages structure (layout)
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* Three variables: `Messages`, `Role`, and `Content` (variables)
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* A custom function (action) that iterates over an array of items (`range .Messages`) and displays each item
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## Adding Templates to Your Model
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By default, models imported into Ollama have a default template of `{{ .Prompt }}`, i.e. user inputs are sent verbatim to the LLM. This is appropriate for text or code completion models but lacks essential markers for chat or instruction models.
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Omitting a template in these models puts the responsibility of correctly templating input onto the user. Adding a template allows users to easily get the best results from the model.
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To add templates in your model, you'll need to add a `TEMPLATE` command to the Modelfile. Here's an example using Meta's Llama 3.
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```dockerfile
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FROM llama3
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TEMPLATE """{{- if .System }}<|start_header_id|>system<|end_header_id|>
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{{ .System }}<|eot_id|>
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{{- end }}
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{{- range .Messages }}<|start_header_id|>{{ .Role }}<|end_header_id|>
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{{ .Content }}<|eot_id|>
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{{- end }}<|start_header_id|>assistant<|end_header_id|>
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"""
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```
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## Variables
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`System` (string): system prompt
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`Prompt` (string): user prompt
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`Response` (string): assistant response
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`Suffix` (string): text inserted after the assistant's response
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`Messages` (list): list of messages
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`Messages[].Role` (string): role which can be one of `system`, `user`, `assistant`, or `tool`
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`Messages[].Content` (string): message content
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`Messages[].ToolCalls` (list): list of tools the model wants to call
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`Messages[].ToolCalls[].Function` (object): function to call
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`Messages[].ToolCalls[].Function.Name` (string): function name
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`Messages[].ToolCalls[].Function.Arguments` (map): mapping of argument name to argument value
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`Tools` (list): list of tools the model can access
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`Tools[].Type` (string): schema type. `type` is always `function`
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`Tools[].Function` (object): function definition
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`Tools[].Function.Name` (string): function name
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`Tools[].Function.Description` (string): function description
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`Tools[].Function.Parameters` (object): function parameters
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`Tools[].Function.Parameters.Type` (string): schema type. `type` is always `object`
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`Tools[].Function.Parameters.Required` (list): list of required properties
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`Tools[].Function.Parameters.Properties` (map): mapping of property name to property definition
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`Tools[].Function.Parameters.Properties[].Type` (string): property type
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`Tools[].Function.Parameters.Properties[].Description` (string): property description
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`Tools[].Function.Parameters.Properties[].Enum` (list): list of valid values
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## Tips and Best Practices
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Keep the following tips and best practices in mind when working with Go templates:
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* **Be mindful of dot**: Control flow structures like `range` and `with` changes the value `.`
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* **Out-of-scope variables**: Use `$.` to reference variables not currently in scope, starting from the root
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* **Whitespace control**: Use `-` to trim leading (`{{-`) and trailing (`-}}`) whitespace
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## Examples
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### Example Messages
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#### ChatML
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ChatML is a popular template format. It can be used for models such as Databrick's DBRX, Intel's Neural Chat, and Microsoft's Orca 2.
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```gotmpl
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{{- if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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{{ end }}
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{{- range .Messages }}<|im_start|>{{ .Role }}
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{{ .Content }}<|im_end|>
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{{ end }}<|im_start|>assistant
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{{ else }}
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{{ if .System }}<|im_start|>system
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{{ .System }}<|im_end|>
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```
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### Example Tools
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Tools support can be added to a model by adding a `{{ .Tools }}` node to the template. This feature is useful for models trained to call external tools and can a powerful tool for retrieving real-time data or performing complex tasks.
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#### Mistral
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Mistral v0.3 and Mixtral 8x22B supports tool calling.
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```gotmpl
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{{- range $index, $_ := .Messages }}
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{{- if eq .Role "user" }}
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{{- if and (le (len (slice $.Messages $index)) 2) $.Tools }}[AVAILABLE_TOOLS] {{ json $.Tools }}[/AVAILABLE_TOOLS]
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{{- end }}[INST] {{ if and (eq (len (slice $.Messages $index)) 1) $.System }}{{ $.System }}
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{{ end }}{{ .Content }}[/INST]
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{{- else if eq .Role "assistant" }}
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{{- if .Content }} {{ .Content }}</s>
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{{- else if .ToolCalls }}[TOOL_CALLS] [
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{{- range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ json .Function.Arguments }}}
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{{- end }}]</s>
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{{- end }}
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{{- else if eq .Role "tool" }}[TOOL_RESULTS] {"content": {{ .Content }}}[/TOOL_RESULTS]
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{{- end }}
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{{- end }}
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```
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### Example Fill-in-Middle
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Fill-in-middle support can be added to a model by adding a `{{ .Suffix }}` node to the template. This feature is useful for models that are trained to generate text in the middle of user input, such as code completion models.
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#### CodeLlama
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CodeLlama [7B](https://ollama.com/library/codellama:7b-code) and [13B](https://ollama.com/library/codellama:13b-code) code completion models support fill-in-middle.
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```gotmpl
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<PRE> {{ .Prompt }} <SUF>{{ .Suffix }} <MID>
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```
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> [!NOTE]
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> CodeLlama 34B and 70B code completion and all instruct and Python fine-tuned models do not support fill-in-middle.
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#### Codestral
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Codestral [22B](https://ollama.com/library/codestral:22b) supports fill-in-middle.
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```gotmpl
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[SUFFIX]{{ .Suffix }}[PREFIX] {{ .Prompt }}
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```
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