`tokens`: Set the tokens to detokenize.
+### POST `/apply-template`: Apply chat template to a conversation
+
+Uses the server's prompt template formatting functionality to convert chat messages to a single string expected by a chat model as input, but does not perform inference. Instead, the prompt string is returned in the `prompt` field of the JSON response. The prompt can then be modified as desired (for example, to insert "Sure!" at the beginning of the model's response) before sending to `/completion` to generate the chat response.
+
+*Options:*
+
+`messages`: (Required) Chat turns in the same format as `/v1/chat/completions`.
+
### POST `/embedding`: Generate embedding of a given text
> [!IMPORTANT]
res_ok(res, root);
};
+ const auto handle_apply_template = [&ctx_server, ¶ms, &res_ok](const httplib::Request & req, httplib::Response & res) {
+ auto body = json::parse(req.body);
+ const auto & chat_template = body.contains("tools") && ctx_server.chat_templates.template_tool_use ? *ctx_server.chat_templates.template_tool_use : *ctx_server.chat_templates.template_default;
+ json data = oaicompat_completion_params_parse(body, chat_template, params.use_jinja);
+
+ res_ok(res, {{ "prompt", data.at("prompt") }});
+ };
+
const auto handle_embeddings = [&handle_embeddings_impl](const httplib::Request & req, httplib::Response & res) {
handle_embeddings_impl(req, res, OAICOMPAT_TYPE_NONE);
};
svr->Post("/v1/reranking", handle_rerank);
svr->Post("/tokenize", handle_tokenize);
svr->Post("/detokenize", handle_detokenize);
+ svr->Post("/apply-template", handle_apply_template);
// LoRA adapters hotswap
svr->Get ("/lora-adapters", handle_lora_adapters_list);
svr->Post("/lora-adapters", handle_lora_adapters_apply);
assert res.body["__verbose"]["prompt"] == "<s> <|start_header_id|>system<|end_header_id|>\n\nBook<|eot_id|><|start_header_id|>user<|end_header_id|>\n\nWhat is the best book<|eot_id|><|start_header_id|>assistant<|end_header_id|>\n\n"
+def test_apply_chat_template():
+ global server
+ server.chat_template = "command-r"
+ server.start()
+ res = server.make_request("POST", "/apply-template", data={
+ "messages": [
+ {"role": "system", "content": "You are a test."},
+ {"role": "user", "content":"Hi there"},
+ ]
+ })
+ assert res.status_code == 200
+ assert "prompt" in res.body
+ assert res.body["prompt"] == "<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>You are a test.<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|USER_TOKEN|>Hi there<|END_OF_TURN_TOKEN|><|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>"
+
+
@pytest.mark.parametrize("response_format,n_predicted,re_content", [
({"type": "json_object", "schema": {"const": "42"}}, 6, "\"42\""),
({"type": "json_object", "schema": {"items": [{"type": "integer"}]}}, 10, "[ -3000 ]"),