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server : add_special option for tokenize endpoint (#7059)
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@ -331,7 +331,7 @@ Notice that each `probs` is an array of length `n_probs`.
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`content`: Set the text to tokenize.
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Note that a special `BOS` token is never inserted.
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`add_special`: Boolean indicating if special tokens, i.e. `BOS`, should be inserted. Default: `false`
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- **POST** `/detokenize`: Convert tokens to text.
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@ -3647,7 +3647,8 @@ int main(int argc, char ** argv) {
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std::vector<llama_token> tokens;
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if (body.count("content") != 0) {
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tokens = ctx_server.tokenize(body["content"], false);
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const bool add_special = json_value(body, "add_special", false);
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tokens = ctx_server.tokenize(body["content"], add_special);
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}
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const json data = format_tokenizer_response(tokens);
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return res.set_content(data.dump(), "application/json; charset=utf-8");
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@ -7,6 +7,7 @@ Feature: llama.cpp server
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And a model file tinyllamas/stories260K.gguf from HF repo ggml-org/models
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And a model file test-model.gguf
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And a model alias tinyllama-2
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And BOS token is 1
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And 42 as server seed
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# KV Cache corresponds to the total amount of tokens
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# that can be stored across all independent sequences: #4130
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@ -91,7 +92,18 @@ Feature: llama.cpp server
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"""
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What is the capital of France ?
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"""
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Then tokens can be detokenize
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Then tokens can be detokenized
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And tokens do not begin with BOS
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Scenario: Tokenize w/ BOS
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Given adding special tokens
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When tokenizing:
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"""
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What is the capital of Germany?
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"""
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Then tokens begin with BOS
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Given first token is removed
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Then tokens can be detokenized
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Scenario: Models available
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Given available models
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@ -376,6 +376,11 @@ def step_seed(context, seed):
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context.seed.append(seed)
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@step('BOS token is {bos:d}')
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def step_bos_token(context, bos):
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context.bos = bos
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@step('a prefix prompt')
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def step_prompt_prefix(context):
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context.prompt_prefix = context_text(context)
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@ -656,21 +661,29 @@ async def all_embeddings_are_generated(context):
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assert_embeddings(context.tasks_result.pop().pop())
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@step('adding special tokens')
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def step_tokenize_set_add_special(context):
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context.tokenize_add_special = True
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@step('tokenizing')
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@async_run_until_complete
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async def step_tokenize(context):
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context.tokenized_text = context_text(context)
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async with aiohttp.ClientSession() as session:
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tokenize_args = {
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"content": context.tokenized_text,
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}
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if getattr(context, 'tokenize_add_special', None) is not None:
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tokenize_args['add_special'] = context.tokenize_add_special
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async with session.post(f'{context.base_url}/tokenize',
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json={
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"content": context.tokenized_text,
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}) as response:
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json=tokenize_args) as response:
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assert response.status == 200
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tokenize_json = await response.json()
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context.tokens = tokenize_json['tokens']
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@step('tokens can be detokenize')
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@step('tokens can be detokenized')
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@async_run_until_complete
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async def step_detokenize(context):
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assert len(context.tokens) > 0
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@ -685,6 +698,21 @@ async def step_detokenize(context):
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assert context.tokenized_text == detokenize_json['content'].strip()
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@step('tokens begin with BOS')
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def step_strings_for_tokenization(context):
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assert context.tokens[0] == context.bos
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@step('tokens do not begin with BOS')
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def step_strings_for_tokenization(context):
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assert context.tokens[0] != context.bos
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@step('first token is removed')
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def step_strings_for_tokenization(context):
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context.tokens = context.tokens[1:]
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@step('an OPTIONS request is sent from {origin}')
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@async_run_until_complete
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async def step_options_request(context, origin):
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