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Table of Contents

Supported templates
How to add a new template
Custom chat templates

The llama_chat_apply_template() was added in #5538, which allows developers to format the chat into text prompt. By default, this function takes the template stored inside model's metadata tokenizer.chat_template.

NOTE: We do not include a jinja parser in llama.cpp due to its complexity. Our implementation works by matching the supplied template with a list of pre-defined templates hard-coded inside the function.

This is the list of templates currently supported by llama_apply_chat_template. If you found another template on huggingface that's not yet supported by llama.cpp, please feel free to open an issue:

Supported templates

Usage: ./server -m ... --chat-template chatml
teknium/OpenHermes-2.5-Mistral-7B
<|im_start|>user
hello<|im_end|>
<|im_start|>assistant
response<|im_end|>
<|im_start|>user
again<|im_end|>
<|im_start|>assistant
response<|im_end|>

Usage: ./server -m ... --chat-template llama2
mistralai/Mistral-7B-Instruct-v0.2
<s>[INST] hello [/INST]response</s>[INST] again [/INST]response</s>

(Currently cannot select this template with --chat-template)
TheBloke/FusionNet_34Bx2_MoE-AWQ
[INST] <<SYS>>
test
<</SYS>>

hello [/INST] response </s><s>[INST] again [/INST] response </s>

(Currently cannot select this template with --chat-template)
bofenghuang/vigogne-2-70b-chat
<s>[INST] <<SYS>>
test
<</SYS>>

hello [/INST] response </s>[INST] again [/INST] response </s>

Usage: ./server -m ... --chat-template monarch
mlabonne/AlphaMonarch-7B
<s>system
test</s>
<s>user
hello</s>
<s>assistant
response</s>
<s>user
again</s>
<s>assistant
response</s>

Usage: ./server -m ... --chat-template gemma
google/gemma-7b-it
<start_of_turn>user
hello<end_of_turn>
<start_of_turn>model
response<end_of_turn>
<start_of_turn>user
again<end_of_turn>
<start_of_turn>model
response<end_of_turn>

Usage: ./server -m ... --chat-template orion
<s>Human: hello

Assistant: </s>response</s>Human: again

Assistant: </s>response</s>

Usage: ./server -m ... --chat-template openchat
openchat/openchat-3.5-0106
<s>GPT4 Correct System: You are a helpful assistant<|end_of_turn|>GPT4 Correct User: Hello<|end_of_turn|>GPT4 Correct Assistant: Hi there<|end_of_turn|>GPT4 Correct User: Who are you<|end_of_turn|>GPT4 Correct Assistant:    I am an assistant   <|end_of_turn|>GPT4 Correct User: Another question<|end_of_turn|>GPT4 Correct Assistant:

Usage: ./server -m ... --chat-template vicuna
NousResearch/Nous-Capybara-34B
You are a helpful assistant

USER: Hello
ASSISTANT: Hi there</s>
USER: Who are you
ASSISTANT:    I am an assistant   </s>
USER: Another question
ASSISTANT:

Usage: ./server -m ... --chat-template vicuna-orca
migtissera/Tess-2.0-Yi-34B-200K
SYSTEM: You are a helpful assistant
USER: Hello
ASSISTANT: Hi there</s>
USER: Who are you
ASSISTANT:    I am an assistant   </s>
USER: Another question
ASSISTANT:

Usage: ./server -m ... --chat-template deepseek
deepseek-ai/deepseek-coder-33b-instruct
You are a helpful assistant### Instruction:
Hello
### Response:
Hi there
<|EOT|>
### Instruction:
Who are you
### Response:
   I am an assistant   
<|EOT|>
### Instruction:
Another question
### Response:

Usage: ./server -m ... --chat-template command-r
CohereForAI/c4ai-command-r-plus
<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>You are a helpful assistant<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hello<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>Hi there<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Who are you<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>I am an assistant<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Another question<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>

Usage: ./server -m ... --chat-template llama3
meta-llama/Meta-Llama-3-8B-Instruct
<|start_header_id|>system<|end_header_id|>\n\nYou are a helpful assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nHello<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nHi there<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWho are you<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\nI am an assistant<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nAnother question<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n

Additionally, we also support zephyr template (I cannot find it on huggingface, but have seen in this list )

Usage: ./server -m ... --chat-template zephyr
<|system|>
test<|endoftext|>
<|user|>
hello<|endoftext|>
<|assistant|>
response<|endoftext|>
<|user|>
again<|endoftext|>
<|assistant|>
response<|endoftext|>

How to add a new template

Check the chat_template in the model's HuggingFace tokenizer_config.json (example).
- If there isn't one, open an issue first to discuss. Some older models actually predate chat templates and multi-turn responses and would be difficult to support.

Use the following python script to generate a test conversation.

Script

from transformers import AutoTokenizer

VARIANTS_TO_TEST = [
    'teknium/OpenHermes-2.5-Mistral-7B',
    'mistralai/Mistral-7B-Instruct-v0.2',
    'TheBloke/FusionNet_34Bx2_MoE-AWQ',
    'bofenghuang/vigogne-2-70b-chat',
    'mlabonne/AlphaMonarch-7B',
    'google/gemma-7b-it',
    'OrionStarAI/Orion-14B-Chat',
    'openbmb/MiniCPM-2B-dpo-fp32',
    'openchat/openchat-3.5-0106',
    'deepseek-ai/deepseek-coder-33b-instruct',
    # Replace with your model's HuggingFace name
]

HISTORY = [
    { 'role': 'system', 'content': 'You are a helpful assistant' },
    { 'role': 'user', 'content': 'Hello' },
    { 'role': 'assistant', 'content': 'Hi there' },
    { 'role': 'user', 'content': 'Who are you' },
    { 'role': 'assistant', 'content': '   I am an assistant   ' },
    { 'role': 'user', 'content': 'Another question' },
]

for variant in VARIANTS_TO_TEST:
    history = [m for m in HISTORY] # copy
    if 'Mistral' in variant or 'gemma' in variant:
        history.pop(0) # no system prompt for mistral and gemma
    if 'gemma' in variant:
        # GemmaTokenizer is quite buggy, let's hard code the template here
        GEMMA_TMLP = "{% if messages[0]['role'] == 'system' %}{{ raise_exception('System role not supported') }}{% endif %}{% for message in messages %}{% if (message['role'] == 'user') != (loop.index0 % 2 == 0) %}{{ raise_exception('Conversation roles must alternate user/assistant/user/assistant/...') }}{% endif %}{% if (message['role'] == 'assistant') %}{% set role = 'model' %}{% else %}{% set role = message['role'] %}{% endif %}{{ '<start_of_turn>' + role + '\n' + message['content'] | trim + '<end_of_turn>\n' }}{% endfor %}{% if add_generation_prompt %}{{'<start_of_turn>model\n'}}{% endif %}"
        print("\n----- Gemma -----")
        output = AutoTokenizer.from_pretrained(VARIANTS_TO_TEST[0]).apply_chat_template(history, tokenize=False, add_generation_prompt=True, chat_template=GEMMA_TMLP)
        print(output)
        print("\n[Test String]\n// google/gemma-7b-it")
        print(output.replace("\n", "\\n"))
        print('"' + output.replace("\n", "\\n") + '",')
    else:
        print("\n----- " + variant + " -----")
        tokenizer = AutoTokenizer.from_pretrained(variant)
        output = tokenizer.apply_chat_template(history, tokenize=False, add_generation_prompt=True)
        print(output)
        print("\n[Test String]\n// " + variant)
        print('"' + output.replace("\n", "\\n") + '",')

Copy both the chat_template from HuggingFace and the formatted text below [Test String] into tests/test-chat-template.cpp.
Run make tests/test-chat-template. You can now use this test to verify that your template implementation is identical to the original.
Implement your template in llama.cpp (search for llama_chat_apply_template_internal).
- This function attempts to detect the model's template when it's not specified. This uses the model's chat_template metadata, so pick a unique pattern.
make and run the test. Repeat until the output matches the original!

Custom chat templates

Currently, it's not possible to use your own chat template with llama.cpp server's /chat/completions

One of the possible solutions is use /completions endpoint instead, and write your own code (for example, using python) to apply a template before passing the final prompt to /completions

TODO: write demo python code

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