feat: implement a templated endpoint for visibility into chat requests #2333
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Narsil
reviewed
Jul 31, 2024
router/src/server.rs
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201
| if response_format.is_some() && tools.is_some() { | ||
| return Err(( | ||
| StatusCode::UNPROCESSABLE_ENTITY, | ||
| Json(ErrorResponse { | ||
| error: "Grammar and tools are mutually exclusive".to_string(), | ||
| error_type: "validation".to_string(), | ||
| }), | ||
| )); | ||
| } | ||
|
|
||
| let tool_grammar = match ToolGrammar::apply(tools, tool_choice) { | ||
| Ok(grammar) => grammar, | ||
| Err(err) => { | ||
| metrics::counter!("tgi_request_failure", "err" => "validation").increment(1); | ||
| tracing::error!("{}", err); | ||
| return Err(( | ||
| StatusCode::UNPROCESSABLE_ENTITY, | ||
| Json(ErrorResponse { | ||
| error: err.to_string(), | ||
| error_type: err.error_type().to_string(), | ||
| }), | ||
| )); | ||
| } | ||
| }; | ||
|
|
||
| let tools_grammar_prompt = tool_grammar.as_ref().map(|t| { | ||
| ( | ||
| GrammarType::Json(serde_json::json!(t)), | ||
| tool_prompt.unwrap_or_default(), | ||
| ) | ||
| }); | ||
|
|
||
| let (tools_grammar_prompt, _grammar) = response_format | ||
| .map(|rf| (None, Some(rf))) | ||
| .unwrap_or_else(|| { | ||
| ( | ||
| tools_grammar_prompt.clone(), | ||
| tools_grammar_prompt.map(|(g, _)| g), | ||
| ) | ||
| }); | ||
|
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| let inputs = match infer.apply_chat_template(messages, tools_grammar_prompt) { | ||
| Ok(inputs) => inputs, | ||
| Err(err) => { | ||
| metrics::counter!("tgi_request_failure", "err" => "validation").increment(1); | ||
| tracing::error!("{}", err); | ||
| return Err(( | ||
| StatusCode::UNPROCESSABLE_ENTITY, | ||
| Json(ErrorResponse { | ||
| error: err.to_string(), | ||
| error_type: err.error_type().to_string(), | ||
| }), | ||
| )); | ||
| } | ||
| }; |
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This code is already used in some validation, we should probably extract it into a function (so this doesn't drift from the original implem later).
Also this code is very hard to read for me (lots of options everywhere). I'm sure we can simplify it a lot.
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totally agree! in the latest commit i've moved this code into a function called prepare_chat_input which is reusable and much easier to read.
router/src/server.rs
Outdated
| .zip(encoding.get_offsets()) | ||
| .map(|(&id, &(start, stop))| { | ||
| let text: String = | ||
| String::from_utf8_lossy(&input.as_bytes()[start..stop]).to_string(); |
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No, start and stop are defined in utf-8 char ranges.
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oh good catch, i've updated this code and the location it was copied from to operate on chars rather than bytes
drbh
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Narsil
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huggingface#2333) * feat: implement a templated endpoint for visibility into chat requests * feat: improve to tokenize too * fix: adjust return type * feat: simplify prepare_chat_input logic and adjust start stop chars
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This PR adds a new
/templatedPOST endpoint to allow users to send aChatRequestand return the templated request. This can help with prompt engineering and for debugging/transparency purposes.curl localhost:3000/chat_tokenize -s \ -H 'Content-Type: application/json' \ -X POST \ -d '{ "model": "meta-llama/Meta-Llama-3.1-405B-Instruct", "messages": [ { "role": "system", "content": "You are a helpful assistant." }, { "role": "user", "content": "What is deep learning?" } ], "stream": false, "max_tokens": 20, "seed": 42, "tools": null }' | jq{ "tokenize_response": [ { "id": 128000, "text": "", "start": 0, "stop": 0 }, { "id": 128000, "text": "<|begin_of_text|>", "start": 0, "stop": 17 }, { "id": 128006, "text": "<|start_header_id|>", "start": 17, "stop": 36 }, { "id": 9125, "text": "", "start": 36, "stop": 36 }, { "id": 128007, "text": "<|end_header_id|>", "start": 42, "stop": 59 }, { "id": 271, "text": "", "start": 59, "stop": 59 }, { "id": 38766, "text": "Cut", "start": 61, "stop": 64 }, { "id": 1303, "text": "ting", "start": 64, "stop": 68 }, { "id": 33025, "text": "", "start": 68, "stop": 68 }, { "id": 2696, "text": "", "start": 78, "stop": 78 }, { "id": 25, "text": "", "start": 83, "stop": 83 }, { "id": 6790, "text": "", "start": 84, "stop": 84 }, { "id": 220, "text": "", "start": 93, "stop": 93 }, { "id": 2366, "text": "", "start": 94, "stop": 94 }, { "id": 18, "text": "", "start": 97, "stop": 97 }, { "id": 198, "text": "", "start": 98, "stop": 98 }, { "id": 15724, "text": "", "start": 99, "stop": 99 }, { "id": 2696, "text": "", "start": 104, "stop": 104 }, { "id": 25, "text": "", "start": 109, "stop": 109 }, { "id": 220, "text": "", "start": 110, "stop": 110 }, { "id": 1627, "text": "", "start": 111, "stop": 111 }, { "id": 10263, "text": "", "start": 113, "stop": 113 }, { "id": 220, "text": "", "start": 117, "stop": 117 }, { "id": 2366, "text": "", "start": 118, "stop": 118 }, { "id": 19, "text": "", "start": 121, "stop": 121 }, { "id": 271, "text": "", "start": 122, "stop": 122 }, { "id": 2675, "text": "", "start": 124, "stop": 124 }, { "id": 527, "text": "", "start": 127, "stop": 127 }, { "id": 264, "text": "", "start": 131, "stop": 131 }, { "id": 11190, "text": "", "start": 133, "stop": 133 }, { "id": 18328, "text": "", "start": 141, "stop": 141 }, { "id": 13, "text": "", "start": 151, "stop": 151 }, { "id": 128009, "text": "<|eot_id|>", "start": 152, "stop": 162 }, { "id": 128006, "text": "<|start_header_id|>", "start": 162, "stop": 181 }, { "id": 882, "text": "", "start": 181, "stop": 181 }, { "id": 128007, "text": "<|end_header_id|>", "start": 185, "stop": 202 }, { "id": 271, "text": "", "start": 202, "stop": 202 }, { "id": 3923, "text": "", "start": 204, "stop": 204 }, { "id": 374, "text": "", "start": 208, "stop": 208 }, { "id": 5655, "text": "", "start": 211, "stop": 211 }, { "id": 6975, "text": "", "start": 216, "stop": 216 }, { "id": 30, "text": "", "start": 225, "stop": 225 }, { "id": 128009, "text": "<|eot_id|>", "start": 226, "stop": 236 }, { "id": 128006, "text": "<|start_header_id|>", "start": 236, "stop": 255 }, { "id": 78191, "text": "", "start": 255, "stop": 255 }, { "id": 128007, "text": "<|end_header_id|>", "start": 264, "stop": 281 }, { "id": 271, "text": "", "start": 281, "stop": 281 } ], "templated_text": "<|begin_of_text|><|start_header_id|>system<|end_header_id|>\n\nCutting Knowledge Date: December 2023\nToday Date: 26 Jul 2024\n\nYou are a helpful assistant.<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat is deep learning?<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n" }