vbatts/llama.cpp
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Merge pull request #3 from WangHaoranRobin/robin_fork_master

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server: fix issue for multibyte character generation
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WangHaoranRobin 2023-06-22 21:36:50 -07:00 • committed by GitHub
commit bdb710efa2
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1 changed files with 73 additions and 62 deletions
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135
examples/server/server.cpp
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@ -26,17 +26,6 @@ struct server_params {
int32_t write_timeout = 600;
};
// completion string output with probabilities
struct completion_string_output {
struct token_prob {
std::string tok_str;
float prob;
};
std::vector<token_prob> probs;
std::string tok_str;
};
// completion token output with probabilities
struct completion_token_output {
struct token_prob {
@ -108,6 +97,36 @@ static void server_log(const char * level, const char * function, int line,
fflush(stdout);
}
// format incomplete utf-8 multibyte character for output
static std::string tokens_to_output_formatted_string(const llama_context * ctx, const llama_token token) {
const std::string out = token == -1 ? "" : llama_token_to_str(ctx, token);
if (out[0] > 127) {
out = "byte: \\x" + std::format("{:x}", out[0]);
}
return out;
}
// convert a vector of completion_token_output to json
static json probs_vector_to_json(const llama_context * ctx, const vector<completion_token_output> probs) {
json out = json::array();
for (const auto & prob : probs) {
json probs_for_token = json::array();
for (const auto & p : prob.probs) {
std::string tok_str = tokens_to_output_formatted_string(ctx, p.tok);
probs_for_token.push_back(json {
{ "tok_str", tok_str },
{ "prob", p.prob },
});
}
std::string tok_str = tokens_to_output_formatted_string(ctx, prob.tok);
out.push_back(json {
{"content", tok_str},
{"probs", probs_for_token},
});
}
return out;
}
static bool server_verbose = false;
#if SERVER_VERBOSE != 1
@ -129,7 +148,7 @@ struct llama_server_context {
bool stream = false;
bool has_next_token = false;
std::string generated_text;
std::vector<completion_string_output> generated_text_probs;
std::vector<completion_token_output> generated_token_probs;
size_t num_tokens_predicted = 0;
size_t n_past = 0;
@ -160,7 +179,7 @@ struct llama_server_context {
num_tokens_predicted = 0;
generated_text = "";
generated_text.reserve(params.n_ctx);
generated_text_probs.clear();
generated_token_probs.clear();
truncated = false;
stopped_eos = false;
stopped_word = false;
@ -406,22 +425,16 @@ struct llama_server_context {
return stop_pos;
}
completion_string_output doCompletion() {
completion_token_output doCompletion() {
const completion_token_output token_with_probs = nextToken();
completion_string_output result;
const std::string token_text = token_with_probs.tok == -1 ? "" : llama_token_to_str(ctx, token_with_probs.tok);
result.tok_str = token_text;
generated_text += token_text;
// iterate through token_with_probs.probs, if tok is valid, convert it to string and add to result.prob
for (const auto & prob : token_with_probs.probs) {
const std::string prob_text = prob.tok == -1 ? "" : llama_token_to_str(ctx, prob.tok);
result.probs.push_back({prob_text, prob.prob});
if (params.n_probs > 0) {
generated_token_probs.push_back(token_with_probs);
}
generated_text_probs.push_back(result);
if (multibyte_pending > 0) {
multibyte_pending -= token_text.size();
} else if (token_text.size() == 1) {
@ -451,7 +464,7 @@ struct llama_server_context {
LOG_VERBOSE("next token", {
{ "token", token_with_probs.tok },
{ "token_text", llama_token_to_str(ctx, token_with_probs.tok) },
{ "token_text", tokens_to_output_formatted_string(ctx, token_with_probs.tok) },
{ "has_next_token", has_next_token },
{ "n_remain", n_remain },
{ "num_tokens_predicted", num_tokens_predicted },
@ -461,7 +474,7 @@ struct llama_server_context {
{ "stopping_word", stopping_word },
});
return result;
return token_with_probs;
}
std::vector<float> getEmbedding() {
@ -713,26 +726,10 @@ static json format_embedding_response(llama_server_context & llama) {
};
}
static json format_final_response(llama_server_context & llama, const std::string & content, const std::vector<completion_string_output> & probs) {
static json format_final_response(llama_server_context & llama, const std::string & content, const std::vector<completion_token_output> & probs) {
json completion_probabilities_json = json::array();
for (const auto & prob : probs) {
json probs_for_token = json::array();
for (const auto & p : prob.probs) {
probs_for_token.push_back(json {
{ "tok_str", p.tok_str },
{ "prob", p.prob },
});
}
completion_probabilities_json.push_back(json {
{"content", prob.tok_str},
{"probs", probs_for_token},
});
}
return json {
json res = json {
{ "content", content },
{ "completion_probabilities", completion_probabilities_json},
{ "stop", true },
{ "model", llama.params.model_alias },
{ "tokens_predicted", llama.num_tokens_predicted },
@ -743,25 +740,25 @@ static json format_final_response(llama_server_context & llama, const std::strin
{ "stopped_word", llama.stopped_word },
{ "stopped_limit", llama.stopped_limit },
{ "stopping_word", llama.stopping_word },
};
}
if (llama.params.n_probs > 0) {
json completion_probabilities_json = probs_vector_to_json(llama.ctx, probs);
res["completion_probabilities"] = completion_probabilities_json;
}
return res;
}
static json format_partial_response(const std::string & content, const completion_string_output & probs) {
static json format_partial_response(llama_server_context & llama, const std::string & content, const std::vector<completion_token_output> & probs) {
json res = json {
{ "content", content },
{ "stop", false },
};
// iterate through probs.probs, and add to res
json probs_json = json::array();
for (const auto & prob : probs.probs) {
probs_json.push_back(json {
{ "tok_str", prob.tok_str },
{ "prob", prob.prob },
});
}
if (probs.probs.size() > 0) {
res["probs"] = probs_json;
if (llama.params.n_probs > 0) {
json completion_probabilities_json = probs_vector_to_json(llama.ctx, probs);
res["completion_probabilities"] = completion_probabilities_json;
}
return res;
@ -897,8 +894,8 @@ int main(int argc, char ** argv) {
size_t stop_pos = std::string::npos;
while (llama.has_next_token) {
const completion_string_output token_text_with_probs = llama.doCompletion();
const std::string token_text = token_text_with_probs.tok_str;
const completion_token_output token_with_probs = llama.doCompletion();
const std::string token_text = llama_token_to_str(llama.ctx, token_with_probs.tok);
stop_pos = llama.findStoppingStrings(llama.generated_text,
token_text.size(), STOP_FULL);
@ -912,7 +909,7 @@ int main(int argc, char ** argv) {
llama.generated_text.end());
}
const json data = format_final_response(llama, llama.generated_text, llama.generated_text_probs);
const json data = format_final_response(llama, llama.generated_text, llama.generated_token_probs);
llama_print_timings(llama.ctx);
@ -921,9 +918,11 @@ int main(int argc, char ** argv) {
} else {
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_string_output token_text_with_probs = llama.doCompletion();
const completion_token_output token_with_probs = llama.doCompletion();
const std::string token_text = llama_token_to_str(llama.ctx, token_with_probs.tok);
if (llama.multibyte_pending > 0) {
continue;
}
@ -932,24 +931,36 @@ int main(int argc, char ** argv) {
const std::string str_test = llama.generated_text.substr(pos);
size_t stop_pos =
llama.findStoppingStrings(str_test, token_text_with_probs.tok_str.size(), STOP_FULL);
llama.findStoppingStrings(str_test, token_text.size(), STOP_FULL);
if (stop_pos != std::string::npos) {
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 {
stop_pos = llama.findStoppingStrings(str_test, token_text_with_probs.tok_str.size(),
stop_pos = llama.findStoppingStrings(str_test, token_text.size(),
STOP_PARTIAL);
}
const std::string to_send = llama.generated_text.substr(pos, stop_pos);
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 = llama.has_next_token
? format_partial_response(to_send, token_text_with_probs)
? format_partial_response(llama, to_send, probs_output)
// Generation is done, send extra information.
: format_final_response(llama, to_send, {token_text_with_probs});
: format_final_response(llama, to_send, probs_output);
const std::string str =
"data: " +