Templates supported by llama_chat_apply_template

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

1. 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.

2. 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") + '",')

3. Copy both the chat_template from HuggingFace and the formatted text below [Test String] into tests/test-chat-template.cpp.

4. Run make tests/test-chat-template. You can now use this test to verify that your template implementation is identical to the original.

5. 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.

6. 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