diff --git a/examples/server/server.cpp b/examples/server/server.cpp index b07477c1b..2530a326d 100644 --- a/examples/server/server.cpp +++ b/examples/server/server.cpp @@ -61,7 +61,7 @@ struct llama_server_context std::vector prompt_tokens = ::llama_tokenize(ctx, params.prompt, true); // compare the evaluated prompt with the new prompt int new_prompt_len = 0; - for (unsigned int i = 0;i < prompt_tokens.size(); i++) { + for (size_t i = 0; i < prompt_tokens.size(); i++) { if (i < processed_tokens.size() && processed_tokens[i] == prompt_tokens[i]) { @@ -71,7 +71,7 @@ struct llama_server_context { embd_inp.push_back(prompt_tokens[i]); if(new_prompt_len == 0) { - if(((int)i) - 1 < (int)n_past) { + if(((int32_t)i) - 1 < n_past) { processed_tokens.erase(processed_tokens.begin() + i, processed_tokens.end()); } // Evaluate the new fragment prompt from the last token processed. @@ -306,12 +306,12 @@ struct llama_server_context // Avoid add the no show words to the response for (std::vector word_tokens : no_show_words) { - unsigned int match_token = 1; + size_t match_token = 1; if (tokens_predicted.front() == word_tokens.front()) { bool execute_matching = true; if (tokens_predicted.size() > 1) { // if previus tokens had been tested - for (unsigned int i = 1; i < word_tokens.size(); i++) + for (size_t i = 1; i < word_tokens.size(); i++) { if (i >= tokens_predicted.size()) { match_token = i; @@ -649,7 +649,7 @@ int main(int argc, char **argv) {"tokens_predicted", llama.num_tokens_predicted}}; return res.set_content(data.dump(), "application/json"); } - catch (json::exception const &e) + catch (const json::exception &e) { // Some tokens have bad UTF-8 strings, the json parser is very sensitive json data = { @@ -701,7 +701,7 @@ int main(int argc, char **argv) {"content", result }, {"stop", !llama.has_next_token }}; return res.set_content(data.dump(), "application/json"); - } catch (json::exception const &e) { + } catch (const json::exception &e) { // Some tokens have bad UTF-8 strings, the json parser is very sensitive json data = { {"content", "" },