diff --git a/common/common.cpp b/common/common.cpp
index 2597ba06a..61e285c4b 100644
--- a/common/common.cpp
+++ b/common/common.cpp
@@ -356,6 +356,8 @@ bool gpt_params_parse(int argc, char ** argv, gpt_params & params) {
             params.interactive_first = true;
         } else if (arg == "-ins" || arg == "--instruct") {
             params.instruct = true;
+        } else if (arg == "--infill") {
+            params.infill = true;
         } else if (arg == "--multiline-input") {
             params.multiline_input = true;
         } else if (arg == "--simple-io") {
diff --git a/common/common.h b/common/common.h
index 18aea38ce..28a9ad359 100644
--- a/common/common.h
+++ b/common/common.h
@@ -118,6 +118,7 @@ struct gpt_params {
     bool numa              = false; // attempt optimizations that help on some NUMA systems
     bool export_cgraph     = false; // export the computation graph
     bool verbose_prompt    = false; // print prompt tokens before generation
+    bool infill            = false; // use infill mode
 };
 
 bool gpt_params_parse(int argc, char ** argv, gpt_params & params);
diff --git a/examples/main/main.cpp b/examples/main/main.cpp
index d78112260..365640ffb 100644
--- a/examples/main/main.cpp
+++ b/examples/main/main.cpp
@@ -239,8 +239,15 @@ int main(int argc, char ** argv) {
     LOG("add_bos: %d\n", add_bos);
 
     std::vector<llama_token> embd_inp;
-
-    if (params.interactive_first || params.instruct || !params.prompt.empty() || session_tokens.empty()) {
+    if(params.infill) {
+        std::vector<llama_token> inp_pfx = ::llama_tokenize(ctx, params.input_prefix, add_bos);
+        std::vector<llama_token> inp_sfx = ::llama_tokenize(ctx, params.input_suffix, add_bos);
+        inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(ctx));
+        inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(ctx));
+        embd_inp = inp_pfx;
+        embd_inp.insert(embd_inp.end(), inp_sfx.begin(), inp_sfx.end());
+        embd_inp.push_back(llama_token_middle(ctx));
+    } else if (params.interactive_first || params.instruct || !params.prompt.empty() || session_tokens.empty()) {
         LOG("tokenize the prompt\n");
         embd_inp = ::llama_tokenize(ctx, params.prompt, add_bos);
     } else {
@@ -709,9 +716,58 @@ int main(int argc, char ** argv) {
                     LOG("found antiprompt: %s\n", last_output.c_str());
                 }
             }
-
+            // deal with eot token in infill mode
+            if ((last_tokens.back() == llama_token_eot(ctx) || is_interacting) && params.infill && params.interactive){
+                if(is_interacting && !params.interactive_first) {
+                    // print an eot token
+                    printf("%s", llama_token_to_piece(ctx, llama_token_eot(ctx)).c_str());
+                }
+                fflush(stdout);
+                printf("\n");
+                console::set_display(console::user_input);
+                std::string buffer;
+                std::string line;
+                bool another_line=true;
+                // set a new prefix via stdin
+                do {
+                    another_line = console::readline(line, params.multiline_input);
+                    buffer += line;
+                } while (another_line);
+                // check if we got an empty line, if so we use the old input
+                if(!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
+                    params.input_prefix = buffer;
+                }
+                buffer.clear();
+                // set a new suffix via stdin
+                do {
+                    another_line = console::readline(line, params.multiline_input);
+                    buffer += line;
+                } while (another_line);
+                // check if we got an empty line
+                if(!buffer.empty() && !(buffer.length() == 1 && buffer[0] == '\n')) {
+                    params.input_suffix = buffer;
+                }
+                buffer.clear();
+                // done taking input, reset color
+                console::set_display(console::reset);
+                // tokenize new prefix and suffix
+                std::vector<llama_token> inp_pfx = ::llama_tokenize(ctx, params.input_prefix, add_bos);
+                std::vector<llama_token> inp_sfx = ::llama_tokenize(ctx, params.input_suffix, add_bos);
+                inp_pfx.insert(inp_pfx.begin(), llama_token_prefix(ctx));
+                inp_sfx.insert(inp_sfx.begin(), llama_token_suffix(ctx));
+                embd_inp = inp_pfx;
+                embd_inp.insert(embd_inp.end(), inp_sfx.begin(), inp_sfx.end());
+                embd_inp.push_back(llama_token_middle(ctx));
+                embd.clear();
+                embd_guidance.clear();
+                n_remain = params.n_predict;
+                n_past = 0;
+                n_consumed = 0;
+                // LOG_TEE("took new input\n");
+                is_interacting = false;
+            }
             // deal with end of text token in interactive mode
-            if (last_tokens.back() == llama_token_eos(ctx)) {
+            else if (last_tokens.back() == llama_token_eos(ctx)) {
                 LOG("found EOS token\n");
 
                 if (params.interactive) {
@@ -731,7 +787,7 @@ int main(int argc, char ** argv) {
                 }
             }
 
-            if (n_past > 0 && is_interacting) {
+            if (n_past > 0 && is_interacting && !(params.infill && params.interactive)) {
                 LOG("waiting for user input\n");
 
                 if (params.instruct) {
@@ -825,17 +881,23 @@ int main(int argc, char ** argv) {
 
         // end of text token
         if (!embd.empty() && embd.back() == llama_token_eos(ctx) && !(params.instruct || params.interactive)) {
-            LOG_TEE(" [end of text]\n");
+            if (!params.infill){
+                LOG_TEE(" [end of text]\n");
+            }
             break;
         }
 
         // In interactive mode, respect the maximum number of tokens and drop back to user input when reached.
         // We skip this logic when n_predict == -1 (infinite) or -2 (stop at context size).
-        if (params.interactive && n_remain <= 0 && params.n_predict >= 0) {
+        if (params.interactive && n_remain <= 0 && params.n_predict >= 0 ) {
             n_remain = params.n_predict;
             is_interacting = true;
         }
     }
+    if (params.infill && !params.interactive && n_remain <= 0) {
+        printf("%s", llama_token_to_piece(ctx, llama_token_eot(ctx)).c_str());
+        fflush(stdout);
+    }
 
     if (!path_session.empty() && params.prompt_cache_all && !params.prompt_cache_ro) {
         LOG_TEE("\n%s: saving final output to session file '%s'\n", __func__, path_session.c_str());
diff --git a/examples/server/README.md b/examples/server/README.md
index 517608046..d07f225e9 100644
--- a/examples/server/README.md
+++ b/examples/server/README.md
@@ -176,6 +176,16 @@ node index.js
 
     `content`: Set the text to process.
 
+    **POST** `/infill`: For code infilling. Takes a prefix and a suffix and returns the predicted completion as stream.
+
+    *Options:*
+
+    `input_prefix`: Set the prefix of the code to infill.
+
+    `input_suffix`: Set the suffix of the code to infill.
+
+    It also accepts all the options of `/completion` except `stream` and `prompt`.
+
 ## More examples
 
 ### Interactive mode
diff --git a/examples/server/server.cpp b/examples/server/server.cpp
index ebd7f2fc5..3b7c57a4f 100644
--- a/examples/server/server.cpp
+++ b/examples/server/server.cpp
@@ -341,6 +341,71 @@ struct llama_server_context
         return true;
     }
 
+    void loadInfill()
+    {
+        auto prefix_tokens = tokenize(params.input_prefix, true);  // always add BOS
+        auto suffix_tokens = tokenize(params.input_suffix, true);  // always add BOS
+        prefix_tokens.insert(prefix_tokens.begin(), llama_token_prefix(ctx));
+        prefix_tokens.insert(prefix_tokens.end(), llama_token_suffix(ctx));
+        prefix_tokens.insert(prefix_tokens.end(), suffix_tokens.begin(), suffix_tokens.end());
+        prefix_tokens.push_back(llama_token_middle(ctx));
+        auto prompt_tokens = prefix_tokens;
+
+        num_prompt_tokens = prompt_tokens.size();
+
+        if (params.n_keep < 0)
+        {
+            params.n_keep = (int)num_prompt_tokens;
+        }
+        params.n_keep = std::min(params.n_ctx - 4, params.n_keep);
+
+        // if input prompt is too big, truncate like normal
+        if (num_prompt_tokens >= (size_t)params.n_ctx)
+        {
+            printf("Input prompt is too big, truncating. Can only take %d tokens but got %zu\n", params.n_ctx, num_prompt_tokens);
+            // todo we probably want to cut from both sides
+            const int n_left = (params.n_ctx - params.n_keep) / 2;
+            std::vector<llama_token> new_tokens(prompt_tokens.begin(), prompt_tokens.begin() + params.n_keep);
+            const int erased_blocks = (num_prompt_tokens - params.n_keep - n_left - 1) / n_left;
+            new_tokens.insert(new_tokens.end(), prompt_tokens.begin() + params.n_keep + erased_blocks * n_left, prompt_tokens.end());
+            std::copy(prompt_tokens.end() - params.n_ctx, prompt_tokens.end(), last_n_tokens.begin());
+
+            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;
+            prompt_tokens = new_tokens;
+        }
+        else
+        {
+            const size_t ps = num_prompt_tokens;
+            std::fill(last_n_tokens.begin(), last_n_tokens.end() - ps, 0);
+            std::copy(prompt_tokens.begin(), prompt_tokens.end(), last_n_tokens.end() - ps);
+        }
+
+        // compare the evaluated prompt with the new prompt
+        n_past = common_part(embd, prompt_tokens);
+        printf("n_past: %d\n", n_past);
+        embd = prompt_tokens;
+        if (n_past == num_prompt_tokens)
+        {
+            // we have to evaluate at least 1 token to generate logits.
+            printf("we have to evaluate at least 1 token to generate logits\n");
+            n_past--;
+        }
+
+        LOG_VERBOSE("prompt ingested", {
+                                           {"n_past", n_past},
+                                           {"cached", tokens_to_str(ctx, embd.cbegin(), embd.cbegin() + n_past)},
+                                           {"to_eval", tokens_to_str(ctx, embd.cbegin() + n_past, embd.cend())},
+                                       });
+
+        has_next_token = true;
+    }
     void loadPrompt()
     {
         auto prompt_tokens = tokenize(prompt, true);  // always add BOS
@@ -1199,6 +1264,27 @@ static void parse_options_completion(const json &body, llama_server_context &lla
     LOG_VERBOSE("completion parameters parsed", format_generation_settings(llama));
 }
 
+static void parse_options_infill(const json &body, llama_server_context &llama)
+{
+    if (body.count("input_prefix") != 0)
+    {
+        llama.params.input_prefix = body["input_prefix"];
+    }
+    else
+    {
+        llama.params.input_prefix = "";
+    }
+    if (body.count("input_suffix") != 0)
+    {
+        llama.params.input_suffix = body["input_suffix"];
+    }
+    else
+    {
+        llama.params.input_suffix = "";
+    }
+    parse_options_completion(body, llama);
+}
+
 static void log_server_request(const Request &req, const Response &res)
 {
     LOG_INFO("request", {
@@ -1498,6 +1584,127 @@ int main(int argc, char **argv)
             res.set_chunked_content_provider("text/event-stream", chunked_content_provider, on_complete);
         } });
 
+    svr.Post("/infill", [&llama](const Request &req, Response &res)
+             {
+        auto lock = llama.lock();
+
+        llama.rewind();
+
+        llama_reset_timings(llama.ctx);
+
+        parse_options_infill(json::parse(req.body), llama);
+
+        if (!llama.loadGrammar())
+        {
+            res.status = 400;
+            return;
+        }
+        llama.loadInfill();
+        llama.beginCompletion();
+        const auto chunked_content_provider = [&](size_t, DataSink & sink) {
+            size_t sent_count = 0;
+            size_t sent_token_probs_index = 0;
+
+            while (llama.has_next_token) {
+                const completion_token_output token_with_probs = llama.doCompletion();
+                if (token_with_probs.tok == -1 || llama.multibyte_pending > 0) {
+                    continue;
+                }
+                const std::string token_text = llama_token_to_piece(llama.ctx, token_with_probs.tok);
+
+                size_t pos = std::min(sent_count, llama.generated_text.size());
+
+                const std::string str_test = llama.generated_text.substr(pos);
+                bool is_stop_full = false;
+                size_t stop_pos =
+                    llama.findStoppingStrings(str_test, token_text.size(), STOP_FULL);
+                if (stop_pos != std::string::npos) {
+                    is_stop_full = true;
+                    llama.generated_text.erase(
+                        llama.generated_text.begin() + pos + stop_pos,
+                        llama.generated_text.end());
+                    pos = std::min(sent_count, llama.generated_text.size());
+                } else {
+                    is_stop_full = false;
+                    stop_pos = llama.findStoppingStrings(str_test, token_text.size(),
+                        STOP_PARTIAL);
+                }
+
+                if (
+                    stop_pos == std::string::npos ||
+                    // Send rest of the text if we are at the end of the generation
+                    (!llama.has_next_token && !is_stop_full && stop_pos > 0)
+                ) {
+                    const std::string to_send = llama.generated_text.substr(pos, std::string::npos);
+
+                    sent_count += to_send.size();
+
+                    std::vector<completion_token_output> probs_output = {};
+
+                    if (llama.params.n_probs > 0) {
+                        const std::vector<llama_token> to_send_toks = llama_tokenize(llama.ctx, to_send, false);
+                        size_t probs_pos = std::min(sent_token_probs_index, llama.generated_token_probs.size());
+                        size_t probs_stop_pos = std::min(sent_token_probs_index + to_send_toks.size(), llama.generated_token_probs.size());
+                        if (probs_pos < probs_stop_pos) {
+                            probs_output = std::vector<completion_token_output>(llama.generated_token_probs.begin() + probs_pos, llama.generated_token_probs.begin() + probs_stop_pos);
+                        }
+                        sent_token_probs_index = probs_stop_pos;
+                    }
+
+                    const json data = format_partial_response(llama, to_send, probs_output);
+
+                    const std::string str =
+                        "data: " +
+                        data.dump(-1, ' ', false, json::error_handler_t::replace) +
+                        "\n\n";
+
+                    LOG_VERBOSE("data stream", {
+                        { "to_send", str }
+                    });
+
+                    if (!sink.write(str.data(), str.size())) {
+                        LOG_VERBOSE("stream closed", {});
+                        llama_print_timings(llama.ctx);
+                        return false;
+                    }
+                }
+
+                if (!llama.has_next_token) {
+                    // Generation is done, send extra information.
+                    const json data = format_final_response(
+                        llama,
+                        "",
+                        std::vector<completion_token_output>(llama.generated_token_probs.begin(), llama.generated_token_probs.begin() + sent_token_probs_index)
+                    );
+
+                    const std::string str =
+                        "data: " +
+                        data.dump(-1, ' ', false, json::error_handler_t::replace) +
+                        "\n\n";
+
+                    LOG_VERBOSE("data stream", {
+                        { "to_send", str }
+                    });
+
+                    if (!sink.write(str.data(), str.size())) {
+                        LOG_VERBOSE("stream closed", {});
+                        llama_print_timings(llama.ctx);
+                        return false;
+                    }
+                }
+            }
+
+            llama_print_timings(llama.ctx);
+            sink.done();
+            return true;
+        };
+        const auto on_complete = [&](bool) {
+            llama.mutex.unlock();
+        };
+        lock.release();
+        res.set_chunked_content_provider("text/event-stream", chunked_content_provider, on_complete);
+        });
+
     svr.Get("/model.json", [&llama](const Request &, Response &res)
             {
         const json data = format_generation_settings(llama);
diff --git a/llama.cpp b/llama.cpp
index 358bf5ec8..93afb3a57 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -1052,6 +1052,10 @@ struct llama_vocab {
     id special_pad_id = -1;
 
     id linefeed_id = 13;
+    id special_prefix_id = 32007;
+    id special_middle_id = 32009;
+    id special_suffix_id = 32008;
+    id special_eot_id = 32010;
 
     int find_bpe_rank(std::string token_left, std::string token_right) const {
         replace_all(token_left,  " ",  "\u0120");
@@ -7024,6 +7028,22 @@ llama_token llama_token_eos(const struct llama_context * ctx) {
 llama_token llama_token_nl(const struct llama_context * ctx) {
     return ctx->model.vocab.linefeed_id;
 }
+llama_token llama_token_prefix(const struct llama_context * ctx) {
+    return ctx->model.vocab.special_prefix_id;
+}
+
+llama_token llama_token_middle(const struct llama_context * ctx) {
+    return ctx->model.vocab.special_middle_id;
+}
+
+llama_token llama_token_suffix(const struct llama_context * ctx) {
+    return ctx->model.vocab.special_suffix_id;
+}
+
+llama_token llama_token_eot(const struct llama_context * ctx) {
+    return ctx->model.vocab.special_eot_id;
+}
+
 
 int llama_tokenize(
         struct llama_context * ctx,
diff --git a/llama.h b/llama.h
index 369be048c..d7aa9d5ef 100644
--- a/llama.h
+++ b/llama.h
@@ -362,6 +362,11 @@ extern "C" {
     LLAMA_API llama_token llama_token_bos(const struct llama_context * ctx);  // beginning-of-sentence
     LLAMA_API llama_token llama_token_eos(const struct llama_context * ctx);  // end-of-sentence
     LLAMA_API llama_token llama_token_nl (const struct llama_context * ctx);  // next-line
+    // codellama FIM tokens
+    LLAMA_API llama_token llama_token_prefix(const struct llama_context * ctx); // Beginning of FIM prefix
+    LLAMA_API llama_token llama_token_middle(const struct llama_context * ctx); // Beginning of FIM middle
+    LLAMA_API llama_token llama_token_suffix(const struct llama_context * ctx); // Beginning of FIM suffix
+    LLAMA_API llama_token llama_token_eot   (const struct llama_context * ctx); // End of FIM middle
 
     //
     // Tokenization