diff --git a/Makefile b/Makefile
index 66039d0fc..4b870bd47 100644
--- a/Makefile
+++ b/Makefile
@@ -4,7 +4,7 @@ BUILD_TARGETS = main quantize quantize-stats perplexity embedding vdot
 ifdef LLAMA_BUILD_SERVER
 	BUILD_TARGETS += server
 	LLAMA_SERVER_VERBOSE ?= 1
-server: CXXFLAGS += -DSERVER_VERBOSE=$(LLAMA_SERVER_VERBOSE)
+server: private CXXFLAGS += -DSERVER_VERBOSE=$(LLAMA_SERVER_VERBOSE)
 endif
 
 default: $(BUILD_TARGETS)
diff --git a/examples/server/CMakeLists.txt b/examples/server/CMakeLists.txt
index 1d992501b..07ba76ad3 100644
--- a/examples/server/CMakeLists.txt
+++ b/examples/server/CMakeLists.txt
@@ -3,13 +3,6 @@ option(LLAMA_SERVER_VERBOSE "Build verbose logging option for Server" ON)
 include_directories(${CMAKE_CURRENT_SOURCE_DIR})
 add_executable(${TARGET} server.cpp json.hpp httplib.h)
 target_compile_definitions(${TARGET} PRIVATE
-    # single thread
-    CPPHTTPLIB_THREAD_POOL_COUNT=1
-    # crash the server in debug mode, otherwise send an http 500 error
-    $<$<CONFIG:Debug>:
-        CPPHTTPLIB_NO_EXCEPTIONS=1
-    >
-
     SERVER_VERBOSE=$<BOOL:${LLAMA_SERVER_VERBOSE}>
 )
 target_link_libraries(${TARGET} PRIVATE common llama ${CMAKE_THREAD_LIBS_INIT})
diff --git a/examples/server/README.md b/examples/server/README.md
index 56399be29..824fd5194 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -167,8 +167,16 @@ node .
 ### Interactive mode
 
 Check the sample in [chat.mjs](chat.mjs).
-Run with node:
+Run with NodeJS version 16 or later:
 
 ```sh
 node chat.mjs
 ```
+
+Another sample in [chat.sh](chat.sh).
+Requires [bash](https://www.gnu.org/software/bash/), [curl](https://curl.se) and [jq](https://jqlang.github.io/jq/).
+Run with bash:
+
+```sh
+bash chat.sh
+```
diff --git a/examples/server/chat.mjs b/examples/server/chat.mjs
index 349937e94..8269e2592 100644
--- a/examples/server/chat.mjs
+++ b/examples/server/chat.mjs
@@ -1,61 +1,89 @@
-import * as readline from 'node:readline/promises';
-import { stdin as input, stdout as output } from 'node:process';
+import * as readline from 'node:readline'
+import { stdin, stdout } from 'node:process'
+
+const API_URL = 'http://127.0.0.1:8080'
 
 const chat = [
-  { human: "Hello, Assistant.",
-    assistant: "Hello. How may I help you today?" },
-  { human: "Please tell me the largest city in Europe.",
-    assistant: "Sure. The largest city in Europe is Moscow, the capital of Russia." },
+    {
+        human: "Hello, Assistant.",
+        assistant: "Hello. How may I help you today?"
+    },
+    {
+        human: "Please tell me the largest city in Europe.",
+        assistant: "Sure. The largest city in Europe is Moscow, the capital of Russia."
+    },
 ]
 
+const instruction = `A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions.`
+
 function format_prompt(question) {
-  return "A chat between a curious human and an artificial intelligence assistant. "
-    + "The assistant gives helpful, detailed, and polite answers to the human's questions.\n"
-    + chat.map(m => `### Human: ${m.human}\n### Assistant: ${m.assistant}`).join("\n")
-    + `\n### Human: ${question}\n### Assistant:`
+    return `${instruction}\n${
+        chat.map(m =>`### Human: ${m.human}\n### Assistant: ${m.assistant}`).join("\n")
+    }\n### Human: ${question}\n### Assistant:`
 }
 
-async function ChatCompletion(question) {
-  const result = await fetch("http://127.0.0.1:8080/completion", {
-    method: 'POST',
-    body: JSON.stringify({
-      prompt: format_prompt(question),
-      temperature: 0.2,
-      top_k: 40,
-      top_p: 0.9,
-      n_keep: 29,
-      n_predict: 256,
-      stop: ["\n### Human:"], // stop completion after generating this
-      stream: true,
+async function tokenize(content) {
+    const result = await fetch(`${API_URL}/tokenize`, {
+        method: 'POST',
+        body: JSON.stringify({ content })
     })
-  })
 
-  if (!result.ok) {
-    return;
-  }
-
-  let answer = ''
-
-  for await (var chunk of result.body) {
-    const t = Buffer.from(chunk).toString('utf8')
-    if (t.startsWith('data: ')) {
-      const message = JSON.parse(t.substring(6))
-      answer += message.content
-      process.stdout.write(message.content)
-      if (message.stop) break;
+    if (!result.ok) {
+        return []
     }
-  }
 
-  process.stdout.write('\n')
-  chat.push({ human: question, assistant: answer })
+    return await result.json().tokens
 }
 
-const rl = readline.createInterface({ input, output });
+const n_keep = await tokenize(instruction).length
+
+async function chat_completion(question) {
+    const result = await fetch(`${API_URL}/completion`, {
+        method: 'POST',
+        body: JSON.stringify({
+            prompt: format_prompt(question),
+            temperature: 0.2,
+            top_k: 40,
+            top_p: 0.9,
+            n_keep: n_keep,
+            n_predict: 256,
+            stop: ["\n### Human:"], // stop completion after generating this
+            stream: true,
+        })
+    })
+
+    if (!result.ok) {
+        return
+    }
+
+    let answer = ''
+
+    for await (var chunk of result.body) {
+        const t = Buffer.from(chunk).toString('utf8')
+        if (t.startsWith('data: ')) {
+            const message = JSON.parse(t.substring(6))
+            answer += message.content
+            process.stdout.write(message.content)
+            if (message.stop) {
+                if (message.truncated) {
+                    chat.shift()
+                }
+                break
+            }
+        }
+    }
+
+    process.stdout.write('\n')
+    chat.push({ human: question, assistant: answer.trimStart() })
+}
+
+const rl = readline.createInterface({ input: stdin, output: stdout });
+
+const readlineQuestion = (rl, query, options) => new Promise((resolve, reject) => {
+    rl.question(query, options, resolve)
+});
 
 while(true) {
-
-  const question = await rl.question('> ')
-  await ChatCompletion(question);
-
+    const question = await readlineQuestion(rl, '> ')
+    await chat_completion(question)
 }
-
diff --git a/examples/server/chat.sh b/examples/server/chat.sh
new file mode 100644
index 000000000..2429da665
--- /dev/null
+++ b/examples/server/chat.sh
@@ -0,0 +1,65 @@
+#!/bin/bash
+
+API_URL="http://127.0.0.1:8080"
+
+CHAT=(
+    "Hello, Assistant."
+    "Hello. How may I help you today?"
+    "Please tell me the largest city in Europe."
+    "Sure. The largest city in Europe is Moscow, the capital of Russia."
+)
+
+INSTRUCTION="A chat between a curious human and an artificial intelligence assistant. The assistant gives helpful, detailed, and polite answers to the human's questions."
+
+format_prompt() {
+    echo -n "${INSTRUCTION}"
+    printf "\n### Human: %s\n### Assistant: %s" "${CHAT[@]}" "$1"
+}
+
+tokenize() {
+    curl \
+        --silent \
+        --request POST \
+        --url "${API_URL}/tokenize" \
+        --data-raw "$(jq -ns --arg content "$1" '{content:$content}')" \
+    | jq '.tokens[]'
+}
+
+N_KEEP=$(tokenize "${INSTRUCTION}" | wc -l)
+
+chat_completion() {
+    DATA="$(format_prompt "$1" | jq -Rs --argjson n_keep $N_KEEP '{
+        prompt: .,
+        temperature: 0.2,
+        top_k: 40,
+        top_p: 0.9,
+        n_keep: $n_keep,
+        n_predict: 256,
+        stop: ["\n### Human:"],
+        stream: true
+    }')"
+
+    ANSWER=''
+
+    curl \
+        --silent \
+        --no-buffer \
+        --request POST \
+        --url "${API_URL}/completion" \
+        --data-raw "${DATA}" | while IFS= read -r LINE; do
+        if [[ $LINE = data:* ]]; then
+            CONTENT="$(echo "${LINE:5}" | jq -r '.content')"
+            printf "%s" "${CONTENT}"
+            ANSWER+="${CONTENT}"
+        fi
+    done
+
+    printf "\n"
+
+    CHAT+=("$1" "${ANSWER:1}")
+}
+
+while true; do
+    read -e -p "> " QUESTION
+    chat_completion "${QUESTION}"
+done
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index 908c648ea..2fd64d543 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -2,6 +2,13 @@
 #include "llama.h"
 #include "build-info.h"
 
+// single thread
+#define CPPHTTPLIB_THREAD_POOL_COUNT 1
+#ifndef NDEBUG
+// crash the server in debug mode, otherwise send an http 500 error
+#define CPPHTTPLIB_NO_EXCEPTIONS 1
+#endif
+
 #include "httplib.h"
 #include "json.hpp"
 
@@ -105,6 +112,10 @@ struct llama_server_context {
     llama_context * ctx = nullptr;
     gpt_params params;
 
+    bool truncated = false;
+    bool stopped_eos = false;
+    bool stopped_word = false;
+    bool stopped_limit = false;
     std::string stopping_word;
 
     int json_indent = -1;
@@ -122,6 +133,10 @@ struct llama_server_context {
         num_tokens_predicted = 0;
         generated_text = "";
         generated_text.reserve(params.n_ctx);
+        truncated = false;
+        stopped_eos = false;
+        stopped_word = false;
+        stopped_limit = false;
         stopping_word = "";
         multibyte_pending = 0;
 
@@ -166,6 +181,7 @@ struct llama_server_context {
                 { "new_tokens", tokens_to_str(ctx, new_tokens.cbegin(), new_tokens.cend()) },
             });
 
+            truncated = true;
             prompt_tokens = new_tokens;
         } else {
             const size_t ps = prompt_tokens.size();
@@ -207,14 +223,13 @@ struct llama_server_context {
             new_tokens.insert(new_tokens.end(), embd.end() - n_left, embd.end());
             embd = new_tokens;
             n_past = params.n_keep;
-            if (server_verbose) {
-                LOG_VERBOSE("input truncated", {
-                    { "n_ctx", params.n_ctx },
-                    { "n_keep", params.n_keep },
-                    { "n_left", n_left },
-                    { "new_tokens", tokens_to_str(ctx, new_tokens.cbegin(), new_tokens.cend()) },
-                });
-            }
+            truncated = true;
+            LOG_VERBOSE("input truncated", {
+                { "n_ctx", params.n_ctx },
+                { "n_keep", params.n_keep },
+                { "n_left", n_left },
+                { "new_tokens", tokens_to_str(ctx, new_tokens.cbegin(), new_tokens.cend()) },
+            });
         }
 
         while (n_past < embd.size()) {
@@ -314,8 +329,9 @@ struct llama_server_context {
         --n_remain;
 
         if (!embd.empty() && embd.back() == llama_token_eos()) {
-            stopping_word = llama_token_to_str(ctx, embd.back());
+            //stopping_word = llama_token_to_str(ctx, embd.back());
             has_next_token = false;
+            stopped_eos = true;
             LOG_VERBOSE("eos token found", {});
             return result;
         }
@@ -341,6 +357,7 @@ struct llama_server_context {
                 (stop_pos == std::string::npos || pos < stop_pos)) {
                 if (type == STOP_FULL) {
                     stopping_word = word;
+                    stopped_word = true;
                     has_next_token = false;
                 }
                 stop_pos = pos;
@@ -378,17 +395,22 @@ struct llama_server_context {
             n_remain++;
         }
 
-        if (server_verbose) {
-            LOG_VERBOSE("next token", {
-                { "token", token },
-                { "token_text", llama_token_to_str(ctx, token) },
-                { "has_next_token", has_next_token },
-                { "n_remain", n_remain },
-                { "num_tokens_predicted", num_tokens_predicted },
-                { "stopping_word", stopping_word },
-            });
+        if (!has_next_token && n_remain == 0) {
+            stopped_limit = true;
         }
 
+        LOG_VERBOSE("next token", {
+            { "token", token },
+            { "token_text", llama_token_to_str(ctx, token) },
+            { "has_next_token", has_next_token },
+            { "n_remain", n_remain },
+            { "num_tokens_predicted", num_tokens_predicted },
+            { "stopped_eos", stopped_eos },
+            { "stopped_word", stopped_word },
+            { "stopped_limit", stopped_limit },
+            { "stopping_word", stopping_word },
+        });
+
         return token_text;
     }
 };
@@ -578,7 +600,7 @@ void server_params_parse(int argc, char ** argv, server_params & sparams,
     }
 }
 
-json format_generation_settings(llama_server_context & llama) {
+static json format_generation_settings(llama_server_context & llama) {
     const auto eos_bias = llama.params.logit_bias.find(llama_token_eos());
     const bool ignore_eos = eos_bias != llama.params.logit_bias.end() &&
         eos_bias->second < 0.0f && std::isinf(eos_bias->second);
@@ -607,98 +629,62 @@ json format_generation_settings(llama_server_context & llama) {
     };
 }
 
-bool parse_options_completion(json body, llama_server_context & llama, Response & res) {
+static json format_final_response(llama_server_context & llama, const std::string & content) {
+    return json {
+        { "content", content },
+        { "stop", true },
+        { "model", llama.params.model_alias },
+        { "tokens_predicted", llama.num_tokens_predicted },
+        { "generation_settings", format_generation_settings(llama) },
+        { "prompt", llama.params.prompt },
+        { "truncated", llama.truncated },
+        { "stopped_eos", llama.stopped_eos },
+        { "stopped_word", llama.stopped_word },
+        { "stopped_limit", llama.stopped_limit },
+        { "stopping_word", llama.stopping_word },
+    };
+}
+
+static json format_partial_response(const std::string & content) {
+    return json {
+        { "content", content },
+        { "stop", false },
+    };
+}
+
+static json format_tokenizer_response(const std::vector<llama_token> & tokens) {
+    return json {
+        { "tokens", tokens }
+    };
+}
+
+bool parse_options_completion(json body, llama_server_context & llama) {
     gpt_params default_params;
-    if (!body["stream"].is_null()) {
-        llama.stream = body["stream"].get<bool>();
-    } else {
-        llama.stream = false;
-    }
-    if (!body["n_predict"].is_null()) {
-        llama.params.n_predict = body["n_predict"].get<int32_t>();
-    } else {
-        llama.params.n_predict = default_params.n_predict;
-    }
-    if (!body["top_k"].is_null()) {
-        llama.params.top_k = body["top_k"].get<int32_t>();
-    } else {
-        llama.params.top_k = default_params.top_k;
-    }
-    if (!body["top_p"].is_null()) {
-        llama.params.top_p = body["top_p"].get<float>();
-    } else {
-        llama.params.top_p = default_params.top_p;
-    }
-    if (!body["tfs_z"].is_null()) {
-        llama.params.tfs_z = body["tfs_z"].get<float>();
-    } else {
-        llama.params.tfs_z = default_params.tfs_z;
-    }
-    if (!body["typical_p"].is_null()) {
-        llama.params.typical_p = body["typical_p"].get<float>();
-    } else {
-        llama.params.typical_p = default_params.typical_p;
-    }
-    if (!body["repeat_last_n"].is_null()) {
-        llama.params.repeat_last_n = body["repeat_last_n"].get<int32_t>();
-    } else {
-        llama.params.repeat_last_n = default_params.repeat_last_n;
-    }
-    if (!body["temperature"].is_null()) {
-        llama.params.temp = body["temperature"].get<float>();
-    } else {
-        llama.params.temp = default_params.temp;
-    }
-    if (!body["repeat_penalty"].is_null()) {
-        llama.params.repeat_penalty = body["repeat_penalty"].get<float>();
-    } else {
-        llama.params.repeat_penalty = default_params.repeat_penalty;
-    }
-    if (!body["presence_penalty"].is_null()) {
-        llama.params.presence_penalty = body["presence_penalty"].get<float>();
-    } else {
-        llama.params.presence_penalty = default_params.presence_penalty;
-    }
-    if (!body["frequency_penalty"].is_null()) {
-        llama.params.frequency_penalty = body["frequency_penalty"].get<float>();
-    } else {
-        llama.params.frequency_penalty = default_params.frequency_penalty;
-    }
-    if (!body["mirostat"].is_null()) {
-        llama.params.mirostat = body["mirostat"].get<int>();
-    } else {
-        llama.params.mirostat = default_params.mirostat;
-    }
-    if (!body["mirostat_tau"].is_null()) {
-        llama.params.mirostat_tau = body["mirostat_tau"].get<float>();
-    } else {
-        llama.params.mirostat_tau = default_params.mirostat_tau;
-    }
-    if (!body["mirostat_eta"].is_null()) {
-        llama.params.mirostat_eta = body["mirostat_eta"].get<float>();
-    } else {
-        llama.params.mirostat_eta = default_params.mirostat_eta;
-    }
-    if (!body["penalize_nl"].is_null()) {
-        llama.params.penalize_nl = body["penalize_nl"].get<bool>();
-    } else {
-        llama.params.penalize_nl = default_params.penalize_nl;
-    }
-    if (!body["n_keep"].is_null()) {
-        llama.params.n_keep = body["n_keep"].get<int32_t>();
-    } else {
-        llama.params.n_keep = default_params.n_keep;
-    }
-    if (!body["seed"].is_null()) {
-        llama.params.seed = body["seed"].get<int32_t>();
-    } else {
-        llama.params.seed = time(NULL);
-    }
+
+    llama.stream = body.value("stream", false);
+    llama.params.n_predict = body.value("n_predict", default_params.n_predict);
+    llama.params.top_k = body.value("top_k", default_params.top_k);
+    llama.params.top_p = body.value("top_p", default_params.top_p);
+    llama.params.tfs_z = body.value("tfs_z", default_params.tfs_z);
+    llama.params.typical_p = body.value("typical_p", default_params.typical_p);
+    llama.params.repeat_last_n = body.value("repeat_last_n", default_params.repeat_last_n);
+    llama.params.temp = body.value("temperature", default_params.temp);
+    llama.params.repeat_penalty = body.value("repeat_penalty", default_params.repeat_penalty);
+    llama.params.presence_penalty = body.value("presence_penalty", default_params.presence_penalty);
+    llama.params.frequency_penalty = body.value("frequency_penalty", default_params.frequency_penalty);
+    llama.params.mirostat = body.value("mirostat", default_params.mirostat);
+    llama.params.mirostat_tau = body.value("mirostat_tau", default_params.mirostat_tau);
+    llama.params.mirostat_eta = body.value("mirostat_eta", default_params.mirostat_eta);
+    llama.params.penalize_nl = body.value("penalize_nl", default_params.penalize_nl);
+    llama.params.n_keep = body.value("n_keep", default_params.n_keep);
+    llama.params.seed = body.value("seed", default_params.seed);
+    llama.params.prompt = body.value("prompt", default_params.prompt);
 
     llama.params.logit_bias.clear();
-    if (!body["ignore_eos"].is_null() && body["ignore_eos"].get<bool>()) {
+    if (body.value("ignore_eos", false)) {
         llama.params.logit_bias[llama_token_eos()] = -INFINITY;
     }
+
     if (body["logit_bias"].is_array()) {
         int n_vocab = llama_n_vocab(llama.ctx);
         for (const auto & el : body["logit_bias"]) {
@@ -715,15 +701,6 @@ bool parse_options_completion(json body, llama_server_context & llama, Response
         }
     }
 
-    if (!body["prompt"].is_null()) {
-        llama.params.prompt = body["prompt"].get<std::string>();
-    } else {
-        json data = { {"status", "error"}, {"reason", "You need to provide a prompt"} };
-        res.set_content(data.dump(llama.json_indent), "application/json");
-        res.status = 400;
-        return false;
-    }
-
     llama.params.antiprompt.clear();
     if (!body["stop"].is_null()) {
         const auto stop = body["stop"].get<std::vector<std::string>>();
@@ -737,6 +714,17 @@ bool parse_options_completion(json body, llama_server_context & llama, Response
     return true;
 }
 
+static void log_server_request(const Request & req, const Response & res) {
+    LOG_INFO("request", {
+        { "remote_addr", req.remote_addr },
+        { "remote_port", req.remote_port },
+        { "status", res.status },
+        { "path", req.path },
+        { "request", req.body },
+        { "response", res.body },
+    });
+}
+
 int main(int argc, char ** argv) {
     // own arguments required by this example
     gpt_params params;
@@ -788,7 +776,7 @@ int main(int argc, char ** argv) {
         llama.rewind();
         llama_reset_timings(llama.ctx);
 
-        if (!parse_options_completion(json::parse(req.body), llama, res)) {
+        if (!parse_options_completion(json::parse(req.body), llama)) {
             return;
         }
 
@@ -813,15 +801,7 @@ int main(int argc, char ** argv) {
                     llama.generated_text.end());
             }
 
-            json data {
-                { "content", llama.generated_text },
-                { "stop", true },
-                { "model", llama.params.model_alias },
-                { "tokens_predicted", llama.num_tokens_predicted },
-                { "generation_settings", format_generation_settings(llama) },
-                { "prompt", llama.params.prompt },
-                { "stopping_word", llama.stopping_word },
-            };
+            json data = format_final_response(llama, llama.generated_text);
 
             llama_print_timings(llama.ctx);
 
@@ -859,22 +839,10 @@ int main(int argc, char ** argv) {
 
                     json data;
                     if (llama.has_next_token) {
-                        data = {
-                            { "content", to_send },
-                            { "stop", false },
-                        };
+                        data = format_partial_response(to_send);
                     } else {
                         // Generation is done, send extra information.
-                        data = {
-                            { "content", to_send },
-                            { "stop", true },
-                            { "model", llama.params.model_alias },
-                            { "tokens_predicted", llama.num_tokens_predicted },
-                            { "generation_settings", format_generation_settings(llama) },
-                            { "prompt", llama.params.prompt },
-                            { "stopping_word", llama.stopping_word },
-                            { "generated_text", llama.generated_text },
-                        };
+                        data = format_final_response(llama, to_send);
                     }
 
                     std::string str =
@@ -910,20 +878,11 @@ int main(int argc, char ** argv) {
         json body = json::parse(req.body);
         std::string content = body["content"].get<std::string>();
         std::vector<llama_token> tokens = ::llama_tokenize(llama.ctx, content, false);
-        json data {{ "tokens", tokens }};
+        json data = format_tokenizer_response(tokens);
         return res.set_content(data.dump(llama.json_indent), "application/json");
     });
 
-    svr.set_logger([](const Request & req, const Response & res) {
-        LOG_INFO("request", {
-            { "remote_addr", req.remote_addr },
-            { "remote_port", req.remote_port },
-            { "status", res.status },
-            { "path", req.path },
-            { "request", req.body },
-            { "response", res.body },
-        });
-    });
+    svr.set_logger(log_server_request);
 
     svr.set_exception_handler([](const Request &, Response & res, std::exception_ptr ep) {
         const auto * fmt = "500 Internal Server Error\n%s";