@huggingface/ollama-utils/dist/browser/index.js

Various utilities for maintaining Ollama compatibility with models on Hugging Face hub

"use strict";Object.defineProperty(exports, "__esModule", {value: true});// src/chat-template.ts
var _jinja = require('@huggingface/jinja');

// src/chat-template-automap.ts
var OLLAMA_CHAT_TEMPLATE_MAPPING = [
  {
    model: "library/aya-expanse:8b",
    gguf: "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are Aya, a brilliant, sophisticated, multilingual AI-assistant trained to assist human users by providing thorough responses. You are able to interact and respond to questions in 23 languages and you are powered by a multilingual model built by Cohere For AI.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}",
    ollama: {
      template: '{{- if or .Tools .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>\n{{- if .Tools }}# Safety Preamble\nThe instructions in this section override those in the task description and style guide sections. Don\'t answer questions that are harmful or immoral.\n\n# System Preamble\n## Basic Rules\nYou are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user\'s requests, you cite your sources in your answers, according to those instructions.\n\n{{ if .System }}# User Preamble\n{{ .System }}\n{{- end }}\n\n## Available Tools\nHere is a list of tools that you have available to you:\n{{- range .Tools }}\n\n```python\ndef {{ .Function.Name }}(\n{{- range $name, $property := .Function.Parameters.Properties }}{{ $name }}: {{ $property.Type }}, {{ end }}) -> List[Dict]:\n    \'\'\'{{ .Function.Description }}\n\n{{- if .Function.Parameters.Properties }}\n\n    Args:\n{{- range $name, $property := .Function.Parameters.Properties }}\n        {{ $name }} ({{ $property.Type }}): {{ $property.Description }}\n{{- end }}\n{{- end }}\n    \'\'\'\n    pass\n```\n{{- end }}\n{{- else if .System }}{{ .System }}\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}\n{{- range .Messages }}\n{{- if eq .Role "system" }}\n{{- continue }}\n{{- end }}<|START_OF_TURN_TOKEN|>\n{{- if eq .Role "user" }}<|USER_TOKEN|>{{ .Content }}\n{{- if $.Tools }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write \'Action:\' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user\'s last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:\n```json\n[\n    {\n        "tool_name": title of the tool in the specification,\n        "parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters\n    }\n]```\n{{- end }}\n{{- else if eq .Role "assistant" }}<|CHATBOT_TOKEN|>\n{{- if .Content }}{{ .Content }}\n{{- else if .ToolCalls }}\nAction: ```json\n[\n{{- range .ToolCalls }}\n    {\n        "tool_name": "{{ .Function.Name }}",\n        "parameters": {{ .Function.Arguments }}\n    }\n{{- end }}\n]```\n{{- end }}\n{{- else if eq .Role "tool" }}<|SYSTEM_TOKEN|><results>\nconsole_output: {{ .Content }}\n</results>\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>',
      tokens: [
        "<|START_OF_TURN_TOKEN|>",
        "<|SYSTEM_TOKEN|>",
        "<|END_OF_TURN_TOKEN|>",
        "<|USER_TOKEN|>",
        "<|CHATBOT_TOKEN|>"
      ],
      params: {
        stop: ["<|START_OF_TURN_TOKEN|>", "<|END_OF_TURN_TOKEN|>"]
      }
    }
  },
  {
    model: "library/aya:35b",
    gguf: "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are Command-R, a brilliant, sophisticated, AI-assistant trained to assist human users by providing thorough responses. You are trained by Cohere.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}",
    ollama: {
      template: "{{ if .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{ .System }}<|END_OF_TURN_TOKEN|>{{ end }}{{ if .Prompt }}<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{ .Prompt }}<|END_OF_TURN_TOKEN|>{{ end }}<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>{{ .Response }}<|END_OF_TURN_TOKEN|>",
      tokens: [
        "<|START_OF_TURN_TOKEN|>",
        "<|SYSTEM_TOKEN|>",
        "<|END_OF_TURN_TOKEN|>",
        "<|USER_TOKEN|>",
        "<|CHATBOT_TOKEN|>"
      ],
      params: {
        stop: ["<|START_OF_TURN_TOKEN|>", "<|END_OF_TURN_TOKEN|>"]
      }
    }
  },
  {
    model: "library/cogito:14b",
    gguf: `{%- if not enable_thinking is defined %}
    {%- set enable_thinking = false %}
{%- endif %}
{%- if tools %}
    {{- "<|im_start|>system
" }}
    {%- if messages[0]['role'] == 'system' %}
        {%- if enable_thinking %}
            {{- "Enable deep thinking subroutine.

" + messages[0]['content'] + "

" }}
        {%- else %}
            {{- messages[0]['content'] + "

" }}
        {%- endif %}
    {%- elif enable_thinking %}
        {{- "Enable deep thinking subroutine.

" }}
    {%- endif %}
    {{- "# Tools

You may call one or more functions to assist with the user query.

You are provided with function signatures within <tools></tools> XML tags:
<tools>" }}
    {%- for tool in tools %}
        {{- "
" }}
        {{- tool | tojson }}
    {%- endfor %}
    {{- '
</tools>

For each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:
<tool_call>
{"name": <function-name>, "arguments": <args-json-object>}
</tool_call><|im_end|>
' }}
{%- else %}
    {%- if messages[0]['role'] == 'system' %}
        {%- if enable_thinking %}
            {{- "<|im_start|>system
" + "Enable deep thinking subroutine.

" + messages[0]['content'] + "<|im_end|>
" }}
        {%- else %}
            {{- "<|im_start|>system
" + messages[0]['content'] + "<|im_end|>
" }}
        {%- endif %}
    {%- elif enable_thinking %}
        {{- "<|im_start|>system
" + "Enable deep thinking subroutine." + "<|im_end|>
" }}
    {%- endif %}
{%- endif %}

{%- for message in messages %}
    {%- if (message.role == "user") or (message.role == "system" and not loop.first) or (message.role == "assistant" and not message.tool_calls) %}
        {{- '<|im_start|>' + message.role + '
' }}
        {%- if message.content is string %}
            {{- message.content }}
        {%- elif message.content is iterable and message.content is not string %}
            {%- for content_item in message.content %}
                {%- if content_item.type == 'text' %}
                    {{- content_item.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '<|im_end|>' + '
' }}
    {%- elif message.role == "assistant" %}
        {{- '<|im_start|>' + message.role }}
        {%- if message.content %}
            {{- '
' }}
            {%- if message.content is string %}
                {{- message.content }}
            {%- elif message.content is iterable and message.content is not string %}
                {%- for content_item in message.content %}
                    {%- if content_item.type == 'text' %}
                        {{- content_item.text }}
                    {%- endif %}
                {%- endfor %}
            {%- endif %}
        {%- endif %}
        {%- for tool_call in message.tool_calls %}
            {%- if tool_call.function is defined %}
                {%- set tool_call = tool_call.function %}
            {%- endif %}
            {{- '
<tool_call>
{"name": "' }}
            {{- tool_call.name }}
            {{- '", "arguments": ' }}
            {{- tool_call.arguments | tojson }}
            {{- '}
</tool_call>' }}
        {%- endfor %}
        {{- '<|im_end|>
' }}
    {%- elif message.role == "tool" %}
        {%- if (loop.index0 == 0) or (messages[loop.index0 - 1].role != "tool") %}
            {{- '<|im_start|>user' }}
        {%- endif %}
        {{- '
<tool_response>
' }}
        {%- if message.content is string %}
            {{- message.content }}
        {%- elif message.content is iterable and message.content is not string %}
            {%- for content_item in message.content %}
                {%- if content_item.type == 'text' %}
                    {{- content_item.text }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '
</tool_response>' }}
        {%- if loop.last or (messages[loop.index0 + 1].role != "tool") %}
            {{- '<|im_end|>
' }}
        {%- endif %}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
    {{- '<|im_start|>assistant
' }}
{%- endif %}`,
    ollama: {
      template: '{{- if .Messages }}\n{{- if or .System .Tools }}<|im_start|>system\n{{- if .System }}\n{{ .System }}\n{{- end }}\n{{- if .Tools }}\n\n# Tools\n\nYou may call one or more functions to assist with the user query.\n\nYou are provided with function signatures within <tools></tools> XML tags:\n<tools>\n{{- range .Tools }}\n{"type": "function", "function": {{ .Function }}}\n{{- end }}\n</tools>\n\nFor each function call, return a json object with function name and arguments within <tool_call></tool_call> XML tags:\n<tool_call>\n{"name": <function-name>, "arguments": <args-json-object>}\n</tool_call>\n{{- end }}<|im_end|>\n{{ end }}\n{{- range $i, $_ := .Messages }}\n{{- $last := eq (len (slice $.Messages $i)) 1 -}}\n{{- if eq .Role "user" }}<|im_start|>user\n{{ .Content }}<|im_end|>\n{{ else if eq .Role "assistant" }}<|im_start|>assistant\n{{ if .Content }}{{ .Content }}\n{{- else if .ToolCalls }}<tool_call>\n{{ range .ToolCalls }}{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}\n{{ end }}</tool_call>\n{{- end }}{{ if not $last }}<|im_end|>\n{{ end }}\n{{- else if eq .Role "tool" }}<|im_start|>user\n<tool_response>\n{{ .Content }}\n</tool_response><|im_end|>\n{{ end }}\n{{- if and (ne .Role "assistant") $last }}<|im_start|>assistant\n{{ end }}\n{{- end }}\n{{- else }}\n{{- if .System }}<|im_start|>system\n{{ .System }}<|im_end|>\n{{ end }}{{ if .Prompt }}<|im_start|>user\n{{ .Prompt }}<|im_end|>\n{{ end }}<|im_start|>assistant\n{{ end }}{{ .Response }}{{ if .Response }}<|im_end|>{{ end }}',
      tokens: ["<|im_start|>", "<tools>", "<tool_call>", "<|im_end|>", "<tool_response>"]
    }
  },
  {
    model: "library/cogito:3b",
    gguf: `{{- bos_token }}
{%- if not tools is defined %}
    {%- set tools = none %}
{%- endif %}
{%- if not enable_thinking is defined %}
    {%- set enable_thinking = false %}
{%- endif %}
{#- This block extracts the system message, so we can slot it into the right place. #}
{%- if messages[0]['role'] == 'system' %}
    {%- set system_message = messages[0]['content']|trim %}
    {%- set messages = messages[1:] %}
{%- else %}
    {%- set system_message = "" %}
{%- endif %}
{#- Set the system message. If enable_thinking is true, add the "Enable deep thinking subroutine." #}
{%- if enable_thinking %}
    {%- if system_message != "" %}
        {%- set system_message = "Enable deep thinking subroutine.

" ~ system_message %}
    {%- else %}
        {%- set system_message = "Enable deep thinking subroutine." %}
    {%- endif %}
{%- endif %}
{#- Set the system message. In case there are tools present, add them to the system message. #}
{%- if tools is not none or system_message != '' %}
    {{- "<|start_header_id|>system<|end_header_id|>

" }}
    {{- system_message }}
    {%- if tools is not none %}
        {%- if system_message != "" %}
            {{- "

" }}
        {%- endif %}
        {{- "Available Tools:
" }}
        {%- for t in tools %}
            {{- t | tojson(indent=4) }}
            {{- "

" }}
        {%- endfor %}
    {%- endif %}
    {{- "<|eot_id|>" }}
{%- endif %}

{#- Rest of the messages #}
{%- for message in messages %}
    {#- The special cases are when the message is from a tool (via role ipython/tool/tool_results) or when the message is from the assistant, but has "tool_calls". If not, we add the message directly as usual. #}
    {#- Case 1 - Usual, non tool related message. #}
    {%- if not (message.role == "ipython" or message.role == "tool" or message.role == "tool_results" or (message.tool_calls is defined and message.tool_calls is not none)) %}
        {{- '<|start_header_id|>' + message['role'] + '<|end_header_id|>

' }}
        {%- if message['content'] is string %}
            {{- message['content'] | trim }}
        {%- else %}
            {%- for item in message['content'] %}
                {%- if item.type == 'text' %}
                    {{- item.text | trim }}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- '<|eot_id|>' }}
    
    {#- Case 2 - the response is from the assistant, but has a tool call returned. The assistant may also have returned some content along with the tool call. #}
    {%- elif message.tool_calls is defined and message.tool_calls is not none %}
        {{- "<|start_header_id|>assistant<|end_header_id|>

" }}
        {%- if message['content'] is string %}
            {{- message['content'] | trim }}
        {%- else %}
            {%- for item in message['content'] %}
                {%- if item.type == 'text' %}
                    {{- item.text | trim }}
                    {%- if item.text | trim != "" %}
                        {{- "

" }}
                    {%- endif %}
                {%- endif %}
            {%- endfor %}
        {%- endif %}
        {{- "[" }}
        {%- for tool_call in message.tool_calls %}
            {%- set out = tool_call.function|tojson %}
            {%- if not tool_call.id is defined %}
                {{- out }}
            {%- else %}
                {{- out[:-1] }}
                {{- ', "id": "' + tool_call.id + '"}' }}
            {%- endif %}
            {%- if not loop.last %}
                {{- ", " }}
            {%- else %}
                {{- "]<|eot_id|>" }}
            {%- endif %}
        {%- endfor %}
    
    {#- Case 3 - the response is from a tool call. The tool call may have an id associated with it as well. If it does, we add it to the prompt. #}
    {%- elif message.role == "ipython" or message["role"] == "tool_results" or message["role"] == "tool" %}
        {{- "<|start_header_id|>ipython<|end_header_id|>

" }}
        {%- if message.tool_call_id is defined and message.tool_call_id != '' %}
            {{- '{"content": ' + (message.content | tojson) + ', "call_id": "' + message.tool_call_id + '"}' }}
        {%- else %}
            {{- '{"content": ' + (message.content | tojson) + '}' }}
        {%- endif %}
        {{- "<|eot_id|>" }}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt %}
    {{- '<|start_header_id|>assistant<|end_header_id|>

' }}
{%- endif %}`,
    ollama: {
      template: '{{- if or .System .Tools }}<|start_header_id|>system<|end_header_id|>\n{{- if .System }}\n\n{{ .System }}\n{{- end }}\n{{- if .Tools }}\n\nAvailable Tools:\n{{ range $.Tools }}{{- . }}\n{{ end }}\n{{ end }}<|eot_id|>\n{{- end }}\n{{- range $i, $_ := .Messages }}\n{{- $last := eq (len (slice $.Messages $i)) 1 }}\n{{- if eq .Role "user" }}<|start_header_id|>user<|end_header_id|>\n\n{{ .Content }}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ end }}\n{{- else if eq .Role "assistant" }}<|start_header_id|>assistant<|end_header_id|>\n{{- if .ToolCalls }}\n{{ range .ToolCalls }}\n<tool_call>\n{"name": "{{ .Function.Name }}", "arguments": {{ .Function.Arguments }}}\n</tool_call>{{ end }}\n{{- else }}\n\n{{ .Content }}\n{{- end }}{{ if not $last }}<|eot_id|>{{ end }}\n{{- else if eq .Role "tool" }}<|start_header_id|>ipython<|end_header_id|>\n\n{"content": "{{ .Content }}"}<|eot_id|>{{ if $last }}<|start_header_id|>assistant<|end_header_id|>\n\n{{ end }}\n{{- end }}\n{{- end }}',
      tokens: ["<|start_header_id|>", "<|end_header_id|>", "<|eot_id|>"],
      params: {
        repeat_penalty: 1.1
      }
    }
  },
  {
    model: "library/command-a:111b",
    gguf: `{% if documents %}
{% set tools = [] %}
{%- macro document_turn(documents) -%}
{# format documents into chat turn #}
<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_THINKING|>I will look through the document to address the users needs.<|END_THINKING|><|START_ACTION|>[
    {"tool_call_id": "0", "tool_name": "direct-injected-document", "parameters": {}}
]<|END_ACTION|><|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[
    {
        "tool_call_id": "0",
        "results": {
{% for doc in documents %}
            "{{ loop.index0 }}": {{doc|tojson}}{% if not loop.last %},
            {% endif %}
{% endfor %}

        },
        "is_error": null
    }
]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>{%- endmacro %}
{%- macro tool_call_id_to_int(messages, tool_call_id) %}
{%- set counter = namespace(value=0) %}
{%- set tool_call_id_seen = namespace(value=false) %}
{%- for msg in messages %}
    {%- if msg.tool_calls %}
        {%- for tool_call in msg.tool_calls %}
            {%- if tool_call.id == tool_call_id and not tool_call_id_seen.value -%}
                {{ counter.value }}
                {%- set tool_call_id_seen.value = true %}
            {%- endif %}
            {%- set counter.value = counter.value + 1 %}
        {%- endfor %}
    {%- endif %}
{%- endfor %}
{%- endmacro %}
{%- macro format_tool_message(messages, tool_msg) -%}
{# format tool message #}
    {
        "tool_call_id": "{{ tool_call_id_to_int(messages, tool_msg.tool_call_id) }}",
        "results": {
            "0": {"text": "{{ tool_msg.content }}"}
        },
        "is_error": null
    }
{%- endmacro -%}
{%- if messages and messages[0]['role']|lower == 'system' %}{%- set developer_preamble = messages[0]['content'] %}{% endif %}
{%- set tool_idx = namespace(value=0) %}
{%- set tool_ids_seen = namespace(value=[]) %}
{%- set sent_documents = namespace(value=false) %}
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|># System Preamble
You are in contextual safety mode. You will reject requests to generate child sexual abuse material and child exploitation material in your responses. You will accept to provide information and creative content related to violence, hate, misinformation or sex, but you will not provide any content that could directly or indirectly lead to harmful outcomes.

Your information cutoff date is June 2024.

You have been trained on data in English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Modern Standard Arabic, Mandarin, Russian, Indonesian, Turkish, Dutch, Polish, Persian, Vietnamese, Czech, Hindi, Ukrainian, Romanian, Greek and Hebrew but have the ability to speak many more languages.
{% if tools or documents %}

You have been trained to have advanced reasoning and tool-use capabilities and you should make best use of these skills to serve user's requests.

## Tool Use
Think about how you can make best use of the provided tools to help with the task and come up with a high level plan that you will execute first.

0. Start by writing <|START_THINKING|> followed by a detailed step by step plan of how you will solve the problem. For each step explain your thinking fully and give details of required tool calls (if needed). Unless specified otherwise, you write your plan in natural language. When you finish, close it out with <|END_THINKING|>.
    You can optionally choose to skip this step when the user request is so straightforward to address that only a trivial plan would be needed.
    NOTE: You MUST skip this step when you are directly responding to the user's request without using any tools.

Then carry out your plan by repeatedly executing the following steps.
1. Action: write <|START_ACTION|> followed by a list of JSON-formatted tool calls, with each one containing "tool_name" and "parameters" fields.
    When there are multiple tool calls which are completely independent of each other (i.e. they can be executed in parallel), you should list them out all together in one step. When you finish, close it out with <|END_ACTION|>.
2. Observation: you will then receive results of those tool calls in JSON format in the very next turn, wrapped around by <|START_TOOL_RESULT|> and <|END_TOOL_RESULT|>. Carefully observe those results and think about what to do next. Note that these results will be provided to you in a separate turn. NEVER hallucinate results.
    Every tool call produces a list of results (when a tool call produces no result or a single result, it'll still get wrapped inside a list). Each result is clearly linked to its originating tool call via its "tool_call_id".
3. Reflection: start the next turn by writing <|START_THINKING|> followed by what you've figured out so far, any changes you need to make to your plan, and what you will do next. When you finish, close it out with <|END_THINKING|>.
    You can optionally choose to skip this step when everything is going according to plan and no special pieces of information or reasoning chains need to be recorded.
    NOTE: You MUST skip this step when you are done with tool-use actions and are ready to respond to the user.

You can repeat the above 3 steps multiple times (could be 0 times too if no suitable tool calls are available or needed), until you decide it's time to finally respond to the user.

4. Response: then break out of the loop and write <|START_RESPONSE|> followed by a piece of text which serves as a response to the user's last request. Use all previous tool calls and results to help you when formulating your response. When you finish, close it out with <|END_RESPONSE|>.
{% if enable_citations %}

## Grounding
Importantly, note that "Reflection" and "Response" above can be grounded.
Grounding means you associate pieces of texts (called "spans") with those specific tool results that support them (called "sources"). And you use a pair of tags "<co>" and "</co>" to indicate when a span can be grounded onto a list of sources, listing them out in the closing tag. Sources from the same tool call are grouped together and listed as "{tool_call_id}:[{list of result indices}]", before they are joined together by ",". E.g., "<co>span</co: 0:[1,2],1:[0]>" means that "span" is supported by result 1 and 2 from "tool_call_id=0" as well as result 0 from "tool_call_id=1".
{% endif %}

## Available Tools
Here is the list of tools that you have available to you.
You can ONLY use the tools listed here. When a tool is not listed below, it is NOT available and you should NEVER attempt to use it.
Each tool is represented as a JSON object with fields like "name", "description", "parameters" (per JSON Schema), and optionally, "responses" (per JSON Schema).

\`\`\`json
[
{% if documents %}
    {"name": "direct-injected-document", "description": "This is a special tool to directly inject user-uploaded documents into the chat as additional context. DO NOT use this tool by yourself!", "parameters": {"type": "object", "properties": {}, "required": []}, "responses": {"200": {"description": "Successfully returned a list of chunked text snippets from the directly uploaded documents.", "content": {"application/json": {"schema": {"type": "array", "items": {"type": "object", "required": ["url", "snippet"], "properties": {"url": {"type": "string", "description": "The url of the uploaded document."}, "snippet": {"type": "string", "description": "The text snippet for the returned document chunk."}}}}}}}}}{%- if tools %},{% endif %}

{% endif %}
{% for tool in tools %}
    {"name": "{{ tool['function']['name'] }}", "description": "{{tool['function']['description']}}", "parameters": {{ tool['function']['parameters']['properties']|tojson }}, "responses": null}{%- if not loop.last %},{% endif %}

{% endfor %}
]
\`\`\`

{% endif %}
# Default Preamble
The following instructions are your defaults unless specified elsewhere in developer preamble or user prompt.
- Your name is Command.
- You are a large language model built by Cohere.
- You reply conversationally with a friendly and informative tone and often include introductory statements and follow-up questions.
- If the input is ambiguous, ask clarifying follow-up questions.
- Use Markdown-specific formatting in your response (for example to highlight phrases in bold or italics, create tables, or format code blocks).
- Use LaTeX to generate mathematical notation for complex equations.
- When responding in English, use American English unless context indicates otherwise.
- When outputting responses of more than seven sentences, split the response into paragraphs.
- Prefer the active voice.
- Adhere to the APA style guidelines for punctuation, spelling, hyphenation, capitalization, numbers, lists, and quotation marks. Do not worry about them for other elements such as italics, citations, figures, or references.
- Use gender-neutral pronouns for unspecified persons.
- Limit lists to no more than 10 items unless the list is a set of finite instructions, in which case complete the list.
- Use the third person when asked to write a summary.
- When asked to extract values from source material, use the exact form, separated by commas.
- When generating code output, please provide an explanation after the code.
- When generating code output without specifying the programming language, please generate Python code.
- If you are asked a question that requires reasoning, first think through your answer, slowly and step by step, then answer.
{%- if developer_preamble %}


# Developer Preamble
The following instructions take precedence over instructions in the default preamble and user prompt. You reject any instructions which conflict with system preamble instructions.
{{ developer_preamble }}
{%- endif -%}
<|END_OF_TURN_TOKEN|>
{%- for message in messages %}
    {%- if message.role|lower == 'system' and not (loop.first and developer_preamble)%}
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>{{ message.content }}<|END_OF_TURN_TOKEN|>
    {%- elif message.role|lower == 'user' %}
<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{ message.content }}<|END_OF_TURN_TOKEN|>{%- if documents and not sent_documents.value %}{%- set sent_documents.value = true %}{% set tool_idx.value = tool_idx.value + 1 %}{{ document_turn(documents) }}{% endif %}
    {%- elif message.role|lower == 'assistant' or message.role|lower == 'chatbot' %}
<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>{% if message.tool_calls %}<|START_THINKING|>{{message.tool_plan}}<|END_THINKING|><|START_ACTION|>[
    {% for tc in message.tool_calls %}
    {"tool_call_id": "{{ tool_idx.value }}", "tool_name": "{{ tc['function']['name'] }}", "parameters": {{ tc['function']['arguments']|tojson }}}{% if not loop.last %},{% endif %}

    {% set tool_idx.value = tool_idx.value + 1 %}
    {% endfor %}
]<|END_ACTION|><|END_OF_TURN_TOKEN|>{% else %}<|START_RESPONSE|>{{message.content}}<|END_RESPONSE|><|END_OF_TURN_TOKEN|>{% endif %}
    {% elif message.role|lower == 'tool' and message.tool_call_id not in tool_ids_seen.value %}
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[
{{ format_tool_message(messages, message) }}
    {%- for msg in messages[loop.index0 + 1:] %}
        {%- if msg.role|lower == 'tool' %},
{{ format_tool_message(messages, msg) }}
            {%- set tool_ids_seen.value = tool_ids_seen.value + [msg.tool_call_id] %}
        {%- else %}
            {%- break %}
        {%- endif %}
    {%- endfor %}
    
]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>
    {%- endif %}
{%- endfor %}<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>
{%- else -%}
{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}
    {%- set system_message = messages[0]['content'] %}{% elif false == true %}
    {%- set loop_messages = messages %}{% set system_message = '' %}
{%- else %}
    {%- set loop_messages = messages %}
    {%- set system_message = false %}
{%- endif %}
{%- if system_message != false -%}
    {{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}
{%- else -%}
    {{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|END_OF_TURN_TOKEN|>' }}
{%- endif %}
{%- for message in loop_messages %}
    {%- if (message['role'] == 'user') != (loop.index0 % 2 == 0) -%}
        {{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}
    {%- endif -%}
    {%- set content = message['content'] -%}
    {%- if message['role'] == 'user' -%}
        {{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}
    {%- elif message['role'] == 'assistant' -%}
        {{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>'  + content.strip() + '<|END_RESPONSE|><|END_OF_TURN_TOKEN|>' }}
    {%- endif %}
{%- endfor %}
{%- if add_generation_prompt -%}
    {{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>' }}
{%- endif %}
{% endif %}`,
    ollama: {
      template: '{{- if or .Tools .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>\n{{- if .Tools }}# System Preamble\nYou are in contextual safety mode. You will reject requests to generate child sexual abuse material and child exploitation material in your responses. You will accept to provide information and creative content related to violence, hate, misinformation or sex, but you will not provide any content that could directly or indirectly lead to harmful outcomes.\n\nYour information cutoff date is June 2024.\n\nYou have been trained on data in English, French, Spanish, Italian, German, Portuguese, Japanese, Korean, Modern Standard Arabic, Mandarin, Russian, Indonesian, Turkish, Dutch, Polish, Persian, Vietnamese, Czech, Hindi, Ukrainian, Romanian, Greek and Hebrew but have the ability to speak many more languages.\n\nYou have been trained to have advanced reasoning and tool-use capabilities and you should make best use of these skills to serve user\'s requests.\n\n## Tool Use\nThink about how you can make best use of the provided tools to help with the task and come up with a high level plan that you will execute first.\n\n0. Start by writing <|START_THINKING|> followed by a detailed step by step plan of how you will solve the problem. For each step explain your thinking fully and give details of required tool calls (if needed). Unless specified otherwise, you write your plan in natural language. When you finish, close it out with <|END_THINKING|>.\n    You can optionally choose to skip this step when the user request is so straightforward to address that only a trivial plan would be needed.\n    NOTE: You MUST skip this step when you are directly responding to the user\'s request without using any tools.\n\nThen carry out your plan by repeatedly executing the following steps.\n1. Action: write <|START_ACTION|> followed by a list of JSON-formatted tool calls, with each one containing "tool_name" and "parameters" fields.\n    When there are multiple tool calls which are completely independent of each other (i.e. they can be executed in parallel), you should list them out all together in one step. When you finish, close it out with <|END_ACTION|>.\n2. Observation: you will then receive results of those tool calls in JSON format in the very next turn, wrapped around by <|START_TOOL_RESULT|> and <|END_TOOL_RESULT|>. Carefully observe those results and think about what to do next. Note that these results will be provided to you in a separate turn. NEVER hallucinate results.\n    Every tool call produces a list of results (when a tool call produces no result or a single result, it\'ll still get wrapped inside a list). Each result is clearly linked to its originating tool call via its "tool_call_id".\n3. Reflection: start the next turn by writing <|START_THINKING|> followed by what you\'ve figured out so far, any changes you need to make to your plan, and what you will do next. When you finish, close it out with <|END_THINKING|>.\n    You can optionally choose to skip this step when everything is going according to plan and no special pieces of information or reasoning chains need to be recorded.\n    NOTE: You MUST skip this step when you are done with tool-use actions and are ready to respond to the user.\n\nYou can repeat the above 3 steps multiple times (could be 0 times too if no suitable tool calls are available or needed), until you decide it\'s time to finally respond to the user.\n\n4. Response: then break out of the loop and write <|START_RESPONSE|> followed by a piece of text which serves as a response to the user\'s last request. Use all previous tool calls and results to help you when formulating your response. When you finish, close it out with <|END_RESPONSE|>.\n\n## Available Tools\nHere is the list of tools that you have available to you.\nYou can ONLY use the tools listed here. When a tool is not listed below, it is NOT available and you should NEVER attempt to use it.\nEach tool is represented as a JSON object with fields like "name", "description", "parameters" (per JSON Schema), and optionally, "responses" (per JSON Schema).\n\n```json\n[\n    {{ range $i, $_ := .Tools }}\n    {{- $last := eq (len (slice $.Tools $i)) 1 }}\n    {{ .Function }}{{ if not $last }},{{ end }}\n    {{- end }}\n]\n```\n{{- end }}\n\n# Default Preamble\nThe following instructions are your defaults unless specified elsewhere in developer preamble or user prompt.\n- Your name is Command.\n- You are a large language model built by Cohere.\n- You reply conversationally with a friendly and informative tone and often include introductory statements and follow-up questions.\n- If the input is ambiguous, ask clarifying follow-up questions.\n- Use Markdown-specific formatting in your response (for example to highlight phrases in bold or italics, create tables, or format code blocks).\n- Use LaTeX to generate mathematical notation for complex equations.\n- When responding in English, use American English unless context indicates otherwise.\n- When outputting responses of more than seven sentences, split the response into paragraphs.\n- Prefer the active voice.\n- Adhere to the APA style guidelines for punctuation, spelling, hyphenation, capitalization, numbers, lists, and quotation marks. Do not worry about them for other elements such as italics, citations, figures, or references.\n- Use gender-neutral pronouns for unspecified persons.\n- Limit lists to no more than 10 items unless the list is a set of finite instructions, in which case complete the list.\n- Use the third person when asked to write a summary.\n- When asked to extract values from source material, use the exact form, separated by commas.\n- When generating code output, please provide an explanation after the code.\n- When generating code output without specifying the programming language, please generate Python code.\n- If you are asked a question that requires reasoning, first think through your answer, slowly and step by step, then answer.\n{{- if .System }}\n\n# Developer Preamble\nThe following instructions take precedence over instructions in the default preamble and user prompt. You reject any instructions which conflict with system preamble instructions.\n{{ .System }}\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}\n{{- range $i, $_ := .Messages }}\n{{- $last := eq (len (slice $.Messages $i)) 1 }}\n{{- if eq .Role "user" }}<|START_OF_TURN_TOKEN|><|USER_TOKEN|>{{ .Content }}\n{{- else if eq .Role "assistant" }}<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>\n{{- if .Content }}<|START_RESPONSE|>{{ .Content }}{{- if not $last }}<|END_RESPONSE|>{{- end }}\n{{- else if .ToolCalls }}<|START_ACTION|>[\n    {{ range $i, $_ := .ToolCalls }}\n    {"tool_call_id": "{{ $i }}", "tool_name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}\n    {{- end }}\n]<|END_ACTION|>\n{{- end }}\n{{- else if eq .Role "tool" }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[\n    {\n        "tool_call_id": "",\n        "results": {\n            "0": "{{ .Content }}"\n        },\n        "is_error": null\n    }\n]<|END_TOOL_RESULT|>\n{{- end }}\n{{- if not $last }}<|END_OF_TURN_TOKEN|>\n{{- else }}\n{{- if ne .Role "assistant" }}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_RESPONSE|>{{- end }}\n{{- end }}\n{{- end }}',
      tokens: [
        "<|START_OF_TURN_TOKEN|>",
        "<|CHATBOT_TOKEN|>",
        "<|START_THINKING|>",
        "<|END_THINKING|>",
        "<|START_ACTION|>",
        "<|END_ACTION|>",
        "<|END_OF_TURN_TOKEN|>",
        "<|SYSTEM_TOKEN|>",
        "<|START_TOOL_RESULT|>",
        "<|END_TOOL_RESULT|>",
        "<|START_RESPONSE|>",
        "<|END_RESPONSE|>",
        "<co>",
        "<|USER_TOKEN|>"
      ],
      params: {
        stop: ["<|START_OF_TURN_TOKEN|>", "<|END_OF_TURN_TOKEN|>", "<|END_RESPONSE|>"]
      }
    }
  },
  {
    model: "library/command-r-plus:104b",
    gguf: "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are a large language model called Command R+ built by the company Cohere. You act as a brilliant, sophisticated, AI-assistant chatbot trained to assist human users by providing thorough responses.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}",
    ollama: {
      template: '{{- if or .Tools .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>\n{{- if .Tools }}# Safety Preamble\nThe instructions in this section override those in the task description and style guide sections. Don\'t answer questions that are harmful or immoral.\n\n# System Preamble\n## Basic Rules\nYou are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user\'s requests, you cite your sources in your answers, according to those instructions.\n\n{{ if .System }}# User Preamble\n{{ .System }}\n{{- end }}\n\n## Available Tools\nHere is a list of tools that you have available to you:\n{{- range .Tools }}\n\n```python\ndef {{ .Function.Name }}(\n{{- range $name, $property := .Function.Parameters.Properties }}{{ $name }}: {{ $property.Type }}, {{ end }}) -> List[Dict]:\n    \'\'\'{{ .Function.Description }}\n\n{{- if .Function.Parameters.Properties }}\n\n    Args:\n{{- range $name, $property := .Function.Parameters.Properties }}\n        {{ $name }} ({{ $property.Type }}): {{ $property.Description }}\n{{- end }}\n{{- end }}\n    \'\'\'\n    pass\n```\n{{- end }}\n{{- else if .System }}{{ .System }}\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}\n{{- range .Messages }}\n{{- if eq .Role "system" }}\n{{- continue }}\n{{- end }}<|START_OF_TURN_TOKEN|>\n{{- if eq .Role "user" }}<|USER_TOKEN|>{{ .Content }}\n{{- if $.Tools }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write \'Action:\' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user\'s last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:\n```json\n[\n    {\n        "tool_name": title of the tool in the specification,\n        "parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters\n    }\n]```\n{{- end }}\n{{- else if eq .Role "assistant" }}<|CHATBOT_TOKEN|>\n{{- if .Content }}{{ .Content }}\n{{- else if .ToolCalls }}\nAction: ```json\n[\n{{- range .ToolCalls }}\n    {\n        "tool_name": "{{ .Function.Name }}",\n        "parameters": {{ .Function.Arguments }}\n    }\n{{- end }}\n]```\n{{- end }}\n{{- else if eq .Role "tool" }}<|SYSTEM_TOKEN|><results>\nconsole_output: {{ .Content }}\n</results>\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>',
      tokens: [
        "<|START_OF_TURN_TOKEN|>",
        "<|SYSTEM_TOKEN|>",
        "<|END_OF_TURN_TOKEN|>",
        "<|USER_TOKEN|>",
        "<|CHATBOT_TOKEN|>"
      ],
      params: {
        stop: ["<|START_OF_TURN_TOKEN|>", "<|END_OF_TURN_TOKEN|>"]
      }
    }
  },
  {
    model: "library/command-r:35b",
    gguf: "{{ bos_token }}{% if messages[0]['role'] == 'system' %}{% set loop_messages = messages[1:] %}{% set system_message = messages[0]['content'] %}{% elif false == true %}{% set loop_messages = messages %}{% set system_message = 'You are a large language model called Command R built by the company Cohere. You act as a brilliant, sophisticated, AI-assistant chatbot trained to assist human users by providing thorough responses.' %}{% else %}{% set loop_messages = messages %}{% set system_message = false %}{% endif %}{% if system_message != false %}{{ '<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>' + system_message + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% for message in loop_messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% set content = message['content'] %}{% if message['role'] == 'user' %}{{ '<|START_OF_TURN_TOKEN|><|USER_TOKEN|>' + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% elif message['role'] == 'assistant' %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>'  + content.strip() + '<|END_OF_TURN_TOKEN|>' }}{% endif %}{% endfor %}{% if add_generation_prompt %}{{ '<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>' }}{% endif %}",
    ollama: {
      template: '{{- if or .Tools .System }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>\n{{- if .Tools }}# Safety Preamble\nThe instructions in this section override those in the task description and style guide sections. Don\'t answer questions that are harmful or immoral.\n\n# System Preamble\n## Basic Rules\nYou are a powerful conversational AI trained by Cohere to help people. You are augmented by a number of tools, and your job is to use and consume the output of these tools to best help the user. You will see a conversation history between yourself and a user, ending with an utterance from the user. You will then see a specific instruction instructing you what kind of response to generate. When you answer the user\'s requests, you cite your sources in your answers, according to those instructions.\n\n{{ if .System }}# User Preamble\n{{ .System }}\n{{- end }}\n\n## Available Tools\nHere is a list of tools that you have available to you:\n{{- range .Tools }}\n\n```python\ndef {{ .Function.Name }}(\n{{- range $name, $property := .Function.Parameters.Properties }}{{ $name }}: {{ $property.Type }}, {{ end }}) -> List[Dict]:\n    \'\'\'{{ .Function.Description }}\n\n{{- if .Function.Parameters.Properties }}\n\n    Args:\n{{- range $name, $property := .Function.Parameters.Properties }}\n        {{ $name }} ({{ $property.Type }}): {{ $property.Description }}\n{{- end }}\n{{- end }}\n    \'\'\'\n    pass\n```\n{{- end }}\n{{- else if .System }}{{ .System }}\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}\n{{- range .Messages }}\n{{- if eq .Role "system" }}\n{{- continue }}\n{{- end }}<|START_OF_TURN_TOKEN|>\n{{- if eq .Role "user" }}<|USER_TOKEN|>{{ .Content }}\n{{- if $.Tools }}<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>Write \'Action:\' followed by a json-formatted list of actions that you want to perform in order to produce a good response to the user\'s last input. You can use any of the supplied tools any number of times, but you should aim to execute the minimum number of necessary actions for the input. You should use the `directly-answer` tool if calling the other tools is unnecessary. The list of actions you want to call should be formatted as a list of json objects, for example:\n```json\n[\n    {\n        "tool_name": title of the tool in the specification,\n        "parameters": a dict of parameters to input into the tool as they are defined in the specs, or {} if it takes no parameters\n    }\n]```\n{{- end }}\n{{- else if eq .Role "assistant" }}<|CHATBOT_TOKEN|>\n{{- if .Content }}{{ .Content }}\n{{- else if .ToolCalls }}\nAction: ```json\n[\n{{- range .ToolCalls }}\n    {\n        "tool_name": "{{ .Function.Name }}",\n        "parameters": {{ .Function.Arguments }}\n    }\n{{- end }}\n]```\n{{- end }}\n{{- else if eq .Role "tool" }}<|SYSTEM_TOKEN|><results>\nconsole_output: {{ .Content }}\n</results>\n{{- end }}<|END_OF_TURN_TOKEN|>\n{{- end }}<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>',
      tokens: [
        "<|START_OF_TURN_TOKEN|>",
        "<|SYSTEM_TOKEN|>",
        "<|END_OF_TURN_TOKEN|>",
        "<|USER_TOKEN|>",
        "<|CHATBOT_TOKEN|>"
      ],
      params: {
        stop: ["<|START_OF_TURN_TOKEN|>", "<|END_OF_TURN_TOKEN|>"]
      }
    }
  },
  {
    model: "library/command-r7b-arabic:7b",
    gguf: `{{ bos_token }}{% if documents %}
{% set tools = [] %}
{%- macro document_turn(documents) -%}
{# format documents into chat turn #}
<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|><|START_THINKING|>I will look through the document to address the users needs.<|END_THINKING|><|START_ACTION|>[
    {"tool_call_id": "0", "tool_name": "direct-injected-document", "parameters": {}}
]<|END_ACTION|><|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|><|START_TOOL_RESULT|>[
    {
        "tool_call_id": "0",
        "results": {
{% for doc in documents %}
            "{{ loop.index0 }}": {{doc|tojson}}{% if not loop.last %},
            {% endif %}
{% endfor %}

        },
        "is_error": null
    }
]<|END_TOOL_RESULT|><|END_OF_TURN_TOKEN|>{%- endmacro %}
{%- macro tool_call_id_to_int(messages, tool_call_id) %}
{%- set counter = namespace(value=0) %}
{%- set tool_call_id_seen = namespace(value=false) %}
{%- for msg in messages %}
    {%- if msg.tool_calls %}
        {%- for tool_call in msg.tool_calls %}
            {%- if tool_call.id == tool_call_id and not tool_call_id_seen.value -%}
                {{ counter.value }}
                {%- set tool_call_id_seen.value = true %}
            {%- endif %}
            {%- set counter.value = counter.value + 1 %}
        {%- endfor %}
    {%- endif %}
{%- endfor %}
{%- endmacro %}
{%- macro format_tool_message(messages, tool_msg) -%}
{# format tool message #}
    {
        "tool_call_id": "{{ tool_call_id_to_int(messages, tool_msg.tool_call_id) }}",
        "results": {
            "0": {"text": "{{ tool_msg.content }}"}
        },
        "is_error": null
    }
{%- endmacro -%}
{%- if messages and messages[0]['role']|lower == 'system' %}{%- set developer_preamble = messages[0]['content'] %}{% endif %}
{%- set tool_idx = namespace(value=0) %}
{%- set tool_ids_seen = namespace(value=[]) %}
{%- set sent_documents = namespace(value=false) %}
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|># System Preamble
You are in contextual