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server : add "/chat/completions" alias for "/v1/...` (#5722)
* Add "/chat/completions" as alias for "/v1/chat/completions" * merge to upstream master * minor : fix trailing whitespace --------- Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
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@ -3211,9 +3211,7 @@ int main(int argc, char **argv)
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res.set_content(models.dump(), "application/json; charset=utf-8");
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});
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// TODO: add mount point without "/v1" prefix -- how?
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svr.Post("/v1/chat/completions", [&llama, &validate_api_key, &sparams](const httplib::Request &req, httplib::Response &res)
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const auto chat_completions = [&llama, &validate_api_key, &sparams](const httplib::Request &req, httplib::Response &res)
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{
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res.set_header("Access-Control-Allow-Origin", req.get_header_value("Origin"));
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if (!validate_api_key(req, res)) {
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@ -3291,7 +3289,10 @@ int main(int argc, char **argv)
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res.set_chunked_content_provider("text/event-stream", chunked_content_provider, on_complete);
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}
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});
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};
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svr.Post("/chat/completions", chat_completions);
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svr.Post("/v1/chat/completions", chat_completions);
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svr.Post("/infill", [&llama, &validate_api_key](const httplib::Request &req, httplib::Response &res)
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{
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@ -54,6 +54,28 @@ Feature: Parallel
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| disabled | 128 |
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| enabled | 64 |
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Scenario Outline: Multi users OAI completions compatibility no v1
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Given a system prompt You are a writer.
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And a model tinyllama-2
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Given a prompt:
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"""
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Write a very long book.
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"""
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And a prompt:
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"""
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Write another a poem.
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"""
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And <n_predict> max tokens to predict
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And streaming is <streaming>
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Given concurrent OAI completions requests no v1
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Then the server is busy
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Then the server is idle
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Then all prompts are predicted with <n_predict> tokens
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Examples:
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| streaming | n_predict |
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| disabled | 128 |
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| enabled | 64 |
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Scenario: Multi users with total number of tokens to predict exceeds the KV Cache size #3969
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Given a prompt:
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"""
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@ -231,6 +231,7 @@ async def step_oai_chat_completions(context, api_error):
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completion = await oai_chat_completions(context.prompts.pop(),
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context.system_prompt,
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context.base_url,
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'/v1/chat',
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False,
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model=context.model if hasattr(context, 'model') else None,
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@ -288,6 +289,28 @@ async def step_oai_chat_completions(context):
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# user_prompt is inserted automatically
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context.system_prompt,
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context.base_url,
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'/v1/chat/completions',
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True, # async_client
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model=context.model
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if hasattr(context, 'model') else None,
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n_predict=context.n_predict
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if hasattr(context, 'n_predict') else None,
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enable_streaming=context.enable_streaming
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if hasattr(context, 'enable_streaming') else None,
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server_seed=context.server_seed
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if hasattr(context, 'server_seed') else None,
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user_api_key=context.user_api_key
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if hasattr(context, 'user_api_key') else None)
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@step(u'concurrent OAI completions requests no v1')
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@async_run_until_complete
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async def step_oai_chat_completions(context):
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await concurrent_requests(context, oai_chat_completions,
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# user_prompt is inserted automatically
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context.system_prompt,
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context.base_url,
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'/chat/completions',
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True, # async_client
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model=context.model
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if hasattr(context, 'model') else None,
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@ -497,6 +520,7 @@ async def request_completion(prompt,
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async def oai_chat_completions(user_prompt,
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system_prompt,
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base_url,
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base_path,
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async_client,
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debug=False,
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model=None,
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@ -537,7 +561,7 @@ async def oai_chat_completions(user_prompt,
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origin = 'llama.cpp'
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headers = {'Authorization': f'Bearer {user_api_key}', 'Origin': origin}
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async with aiohttp.ClientSession() as session:
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async with session.post(f'{base_url}/v1/chat/completions',
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async with session.post(f'{base_url}{base_path}',
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json=payload,
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headers=headers) as response:
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if enable_streaming:
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@ -579,7 +603,7 @@ async def oai_chat_completions(user_prompt,
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else:
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try:
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openai.api_key = user_api_key
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openai.api_base = f'{base_url}/v1/chat'
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openai.api_base = f'{base_url}{base_path}'
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chat_completion = openai.Completion.create(
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messages=payload['messages'],
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model=model,
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