From fd962a36e5201216932b3ca2b73c307c89f6d0e6 Mon Sep 17 00:00:00 2001 From: Jeffrey Morgan Date: Tue, 4 Jul 2023 00:47:00 -0400 Subject: [PATCH] client updates --- api/client.go | 63 +- cmd/cmd.go | 113 ++- go.mod | 2 +- go.sum | 1 - llama/binding/binding.cpp | 273 ++------ llama/binding/binding.h | 15 +- llama/llama.go | 126 +--- python/README.md | 39 -- python/ollama/__init__.py | 9 - python/ollama/__main__.py | 4 - python/ollama/cmd/__init__.py | 0 python/ollama/cmd/cli.py | 192 ------ python/ollama/cmd/server.py | 94 --- python/ollama/engine.py | 121 ---- python/ollama/model.py | 157 ----- python/ollama/prompt.py | 12 - python/poetry.lock | 1214 --------------------------------- python/pyproject.toml | 25 - python/requirements.txt | 779 --------------------- server/routes.go | 33 +- signature/signature.go | 63 -- 21 files changed, 198 insertions(+), 3137 deletions(-) delete mode 100644 python/README.md delete mode 100644 python/ollama/__init__.py delete mode 100644 python/ollama/__main__.py delete mode 100644 python/ollama/cmd/__init__.py delete mode 100644 python/ollama/cmd/cli.py delete mode 100644 python/ollama/cmd/server.py delete mode 100644 python/ollama/engine.py delete mode 100644 python/ollama/model.py delete mode 100644 python/ollama/prompt.py delete mode 100644 python/poetry.lock delete mode 100644 python/pyproject.toml delete mode 100644 python/requirements.txt delete mode 100644 signature/signature.go diff --git a/api/client.go b/api/client.go index e445e589..f2349df5 100644 --- a/api/client.go +++ b/api/client.go @@ -1,14 +1,13 @@ package api import ( + "bufio" "bytes" "context" "encoding/json" "fmt" "io" "net/http" - - "github.com/jmorganca/ollama/signature" ) type Client struct { @@ -36,7 +35,7 @@ func checkError(resp *http.Response, body []byte) error { return apiError } -func (c *Client) do(ctx context.Context, method string, path string, stream bool, reqData any, respData any) error { +func (c *Client) stream(ctx context.Context, method string, path string, reqData any, callback func (data []byte)) error { var reqBody io.Reader var data []byte var err error @@ -55,17 +54,50 @@ func (c *Client) do(ctx context.Context, method string, path string, stream bool return err } - if c.PrivateKey != nil { - s := signature.SignatureData{ - Method: method, - Path: url, - Data: data, + req.Header.Set("Content-Type", "application/json") + req.Header.Set("Accept", "application/json") + + for k, v := range c.Headers { + req.Header[k] = v + } + + res, err := c.HTTP.Do(req) + if err != nil { + return err + } + defer res.Body.Close() + + reader := bufio.NewReader(res.Body) + + for { + line, err := reader.ReadBytes('\n') + if err != nil { + break } - authHeader, err := signature.SignAuthData(s, c.PrivateKey) + + callback(bytes.TrimSuffix(line, []byte("\n"))) + } + + return nil +} + +func (c *Client) do(ctx context.Context, method string, path string, reqData any, respData any) error { + var reqBody io.Reader + var data []byte + var err error + if reqData != nil { + data, err = json.Marshal(reqData) if err != nil { return err } - req.Header.Set("Authorization", authHeader) + reqBody = bytes.NewReader(data) + } + + url := fmt.Sprintf("%s%s", c.URL, path) + + req, err := http.NewRequestWithContext(ctx, method, url, reqBody) + if err != nil { + return err } req.Header.Set("Content-Type", "application/json") @@ -97,3 +129,14 @@ func (c *Client) do(ctx context.Context, method string, path string, stream bool } return nil } + +func (c *Client) Generate(ctx context.Context, req *GenerateRequest, callback func(token string)) (*GenerateResponse, error) { + var res GenerateResponse + if err := c.stream(ctx, http.MethodPost, "/api/generate", req, func(token []byte) { + callback(string(token)) + }); err != nil { + return nil, err + } + + return &res, nil +} diff --git a/cmd/cmd.go b/cmd/cmd.go index c3c854fa..6933359d 100644 --- a/cmd/cmd.go +++ b/cmd/cmd.go @@ -2,7 +2,6 @@ package cmd import ( "context" - "fmt" "log" "net" "net/http" @@ -10,14 +9,59 @@ import ( "path" "time" - "github.com/spf13/cobra" - "github.com/jmorganca/ollama/api" "github.com/jmorganca/ollama/server" + "github.com/spf13/cobra" ) -func NewAPIClient(cmd *cobra.Command) (*api.Client, error) { - var rawKey []byte +func sockpath() string { + home, err := os.UserHomeDir() + if err != nil { + panic(err) + } + + return path.Join(home, ".ollama", "ollama.sock") +} + +func running() bool { + // Set a timeout duration + timeout := time.Second + // Dial the unix socket + conn, err := net.DialTimeout("unix", sockpath(), timeout) + if err != nil { + return false + } + + if conn != nil { + defer conn.Close() + } + return true +} + +func serve() error { + sp := sockpath() + + if err := os.MkdirAll(path.Dir(sp), 0o700); err != nil { + return err + } + + if err := os.RemoveAll(sp); err != nil { + return err + } + + ln, err := net.Listen("unix", sp) + if err != nil { + return err + } + + if err := os.Chmod(sp, 0o700); err != nil { + return err + } + + return server.Serve(ln) +} + +func NewAPIClient() (*api.Client, error) { var err error home, err := os.UserHomeDir() @@ -31,16 +75,6 @@ func NewAPIClient(cmd *cobra.Command) (*api.Client, error) { Timeout: 10 * time.Second, } - k, _ := cmd.Flags().GetString("key") - - if k != "" { - fn := path.Join(home, ".ollama/keys/", k) - rawKey, err = os.ReadFile(fn) - if err != nil { - return nil, err - } - } - return &api.Client{ URL: "http://localhost", HTTP: http.Client{ @@ -50,7 +84,6 @@ func NewAPIClient(cmd *cobra.Command) (*api.Client, error) { }, }, }, - PrivateKey: rawKey, }, nil } @@ -69,28 +102,12 @@ func NewCLI() *cobra.Command { }, } - rootCmd.PersistentFlags().StringP("key", "k", "", "Private key to use for authenticating") - cobra.EnableCommandSorting = false - modelsCmd := &cobra.Command{ - Use: "models", - Args: cobra.MaximumNArgs(1), - Short: "List models", - Long: "List the models", - RunE: func(cmd *cobra.Command, args []string) error { - client, err := NewAPIClient(cmd) - if err != nil { - return err - } - fmt.Printf("client = %q\n", client) - return nil - }, - } - runCmd := &cobra.Command{ - Use: "run", - Short: "Run a model and submit prompts.", + Use: "run MODEL", + Short: "Run a model", + Args: cobra.ExactArgs(1), RunE: func(cmd *cobra.Command,args []string) error { return nil }, @@ -101,35 +118,11 @@ func NewCLI() *cobra.Command { Aliases: []string{"start"}, Short: "Start ollama", RunE: func(cmd *cobra.Command, args []string) error { - home, err := os.UserHomeDir() - if err != nil { - return err - } - - socket := path.Join(home, ".ollama", "ollama.sock") - if err := os.MkdirAll(path.Dir(socket), 0o700); err != nil { - return err - } - - if err := os.RemoveAll(socket); err != nil { - return err - } - - ln, err := net.Listen("unix", socket) - if err != nil { - return err - } - - if err := os.Chmod(socket, 0o700); err != nil { - return err - } - - return server.Serve(ln) + return serve() }, } rootCmd.AddCommand( - modelsCmd, serveCmd, runCmd, ) diff --git a/go.mod b/go.mod index 219e14cf..335a60c2 100644 --- a/go.mod +++ b/go.mod @@ -5,7 +5,6 @@ go 1.20 require ( github.com/gin-gonic/gin v1.9.1 github.com/spf13/cobra v1.7.0 - golang.org/x/crypto v0.10.0 ) require ( @@ -30,6 +29,7 @@ require ( github.com/twitchyliquid64/golang-asm v0.15.1 // indirect github.com/ugorji/go/codec v1.2.11 // indirect golang.org/x/arch v0.3.0 // indirect + golang.org/x/crypto v0.10.0 // indirect golang.org/x/net v0.10.0 // indirect golang.org/x/sys v0.9.0 // indirect golang.org/x/text v0.10.0 // indirect diff --git a/go.sum b/go.sum index 7be172ba..155236b3 100644 --- a/go.sum +++ b/go.sum @@ -79,7 +79,6 @@ golang.org/x/sys v0.0.0-20220704084225-05e143d24a9e/go.mod h1:oPkhp1MJrh7nUepCBc golang.org/x/sys v0.6.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg= golang.org/x/sys v0.9.0 h1:KS/R3tvhPqvJvwcKfnBHJwwthS11LRhmM5D59eEXa0s= golang.org/x/sys v0.9.0/go.mod h1:oPkhp1MJrh7nUepCBck5+mAzfO9JrbApNNgaTdGDITg= -golang.org/x/term v0.9.0 h1:GRRCnKYhdQrD8kfRAdQ6Zcw1P0OcELxGLKJvtjVMZ28= golang.org/x/text v0.10.0 h1:UpjohKhiEgNc0CSauXmwYftY1+LlaC75SJwh0SgCX58= golang.org/x/text v0.10.0/go.mod h1:TvPlkZtksWOMsz7fbANvkp4WM8x/WCo/om8BMLbz+aE= golang.org/x/xerrors v0.0.0-20191204190536-9bdfabe68543/go.mod h1:I/5z698sn9Ka8TeJc9MKroUUfqBBauWjQqLJ2OPfmY0= diff --git a/llama/binding/binding.cpp b/llama/binding/binding.cpp index eff84d45..b41e27ac 100644 --- a/llama/binding/binding.cpp +++ b/llama/binding/binding.cpp @@ -55,78 +55,14 @@ void sigint_handler(int signo) { } #endif -int get_embeddings(void *params_ptr, void *state_pr, float *res_embeddings) { - gpt_params *params_p = (gpt_params *)params_ptr; - llama_context *ctx = (llama_context *)state_pr; - gpt_params params = *params_p; - - if (params.seed <= 0) { - params.seed = time(NULL); - } - - std::mt19937 rng(params.seed); - - llama_init_backend(params.numa); - - int n_past = 0; - - // Add a space in front of the first character to match OG llama tokenizer - // behavior - params.prompt.insert(0, 1, ' '); - - // tokenize the prompt - auto embd_inp = ::llama_tokenize(ctx, params.prompt, true); - - // determine newline token - auto llama_token_newline = ::llama_tokenize(ctx, "\n", false); - - if (embd_inp.size() > 0) { - if (llama_eval(ctx, embd_inp.data(), embd_inp.size(), n_past, - params.n_threads)) { - fprintf(stderr, "%s : failed to eval\n", __func__); - return 1; - } - } - - const int n_embd = llama_n_embd(ctx); - - const auto embeddings = llama_get_embeddings(ctx); - - for (int i = 0; i < n_embd; i++) { - res_embeddings[i] = embeddings[i]; - } - - return 0; -} - -int get_token_embeddings(void *params_ptr, void *state_pr, int *tokens, - int tokenSize, float *res_embeddings) { - gpt_params *params_p = (gpt_params *)params_ptr; - llama_context *ctx = (llama_context *)state_pr; - gpt_params params = *params_p; - - for (int i = 0; i < tokenSize; i++) { - auto token_str = llama_token_to_str(ctx, tokens[i]); - if (token_str == nullptr) { - continue; - } - std::vector my_vector; - std::string str_token(token_str); // create a new std::string from the char* - params_p->prompt += str_token; - } - - return get_embeddings(params_ptr, state_pr, res_embeddings); -} - -int eval(void *params_ptr, void *state_pr, char *text) { - gpt_params *params_p = (gpt_params *)params_ptr; - llama_context *ctx = (llama_context *)state_pr; +int eval(void *p, void *c, char *text) { + gpt_params *params = (gpt_params *)params; + llama_context *ctx = (llama_context *)ctx; auto n_past = 0; - auto last_n_tokens_data = - std::vector(params_p->repeat_last_n, 0); + auto last_n_tokens_data = std::vector(params->repeat_last_n, 0); - auto tokens = std::vector(params_p->n_ctx); + auto tokens = std::vector(params->n_ctx); auto n_prompt_tokens = llama_tokenize(ctx, text, tokens.data(), tokens.size(), true); @@ -135,26 +71,22 @@ int eval(void *params_ptr, void *state_pr, char *text) { return 1; } - // evaluate prompt return llama_eval(ctx, tokens.data(), n_prompt_tokens, n_past, - params_p->n_threads); + params->n_threads); } -int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { - gpt_params *params_p = (gpt_params *)params_ptr; - llama_context *ctx = (llama_context *)state_pr; - - gpt_params params = *params_p; +int llama_predict(void *p, void *c, char *result, bool debug) { + gpt_params *params = (gpt_params *)params; + llama_context *ctx = (llama_context *)ctx; const int n_ctx = llama_n_ctx(ctx); - if (params.seed <= 0) { - params.seed = time(NULL); + if (params->seed <= 0) { + params->seed = time(NULL); } - std::mt19937 rng(params.seed); - - std::string path_session = params.path_prompt_cache; + std::mt19937 rng(params->seed); + std::string path_session = params->path_prompt_cache; std::vector session_tokens; if (!path_session.empty()) { @@ -177,7 +109,7 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { return 1; } session_tokens.resize(n_token_count_out); - llama_set_rng_seed(ctx, params.seed); + llama_set_rng_seed(ctx, params->seed); if (debug) { fprintf(stderr, "%s: loaded a session with prompt size of %d tokens\n", __func__, (int)session_tokens.size()); @@ -191,12 +123,12 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { } std::vector embd_inp; - if (!params.prompt.empty() || session_tokens.empty()) { + if (!params->prompt.empty() || session_tokens.empty()) { // Add a space in front of the first character to match OG llama tokenizer // behavior - params.prompt.insert(0, 1, ' '); + params->prompt.insert(0, 1, ' '); - embd_inp = ::llama_tokenize(ctx, params.prompt, true); + embd_inp = ::llama_tokenize(ctx, params->prompt, true); } else { embd_inp = session_tokens; } @@ -212,7 +144,7 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { n_matching_session_tokens++; } if (debug) { - if (params.prompt.empty() && + if (params->prompt.empty() && n_matching_session_tokens == embd_inp.size()) { fprintf(stderr, "%s: using full prompt from session file\n", __func__); } else if (n_matching_session_tokens >= embd_inp.size()) { @@ -237,8 +169,8 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { session_tokens.resize(embd_inp.size() - 1); } // number of tokens to keep when resetting context - if (params.n_keep < 0 || params.n_keep > (int)embd_inp.size()) { - params.n_keep = (int)embd_inp.size(); + if (params->n_keep < 0 || params->n_keep > (int)embd_inp.size()) { + params->n_keep = (int)embd_inp.size(); } // determine newline token @@ -251,7 +183,7 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { bool need_to_save_session = !path_session.empty() && n_matching_session_tokens < embd_inp.size(); int n_past = 0; - int n_remain = params.n_predict; + int n_remain = params->n_predict; int n_consumed = 0; int n_session_consumed = 0; @@ -263,7 +195,7 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { const std::vector tmp = { llama_token_bos(), }; - llama_eval(ctx, tmp.data(), tmp.size(), 0, params.n_threads); + llama_eval(ctx, tmp.data(), tmp.size(), 0, params->n_threads); llama_reset_timings(ctx); } @@ -276,10 +208,10 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { // - take half of the last (n_ctx - n_keep) tokens and recompute the // logits in batches if (n_past + (int)embd.size() > n_ctx) { - const int n_left = n_past - params.n_keep; + const int n_left = n_past - params->n_keep; // always keep the first token - BOS - n_past = std::max(1, params.n_keep); + n_past = std::max(1, params->n_keep); // insert n_left/2 tokens at the start of embd from last_n_tokens embd.insert(embd.begin(), @@ -288,14 +220,6 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { // stop saving session if we run out of context path_session.clear(); - - // printf("\n---\n"); - // printf("resetting: '"); - // for (int i = 0; i < (int) embd.size(); i++) { - // printf("%s", llama_token_to_str(ctx, embd[i])); - // } - // printf("'\n"); - // printf("\n---\n"); } // try to reuse a matching prefix from the loaded session instead of @@ -324,15 +248,17 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { // evaluate tokens in batches // embd is typically prepared beforehand to fit within a batch, but not // always - for (int i = 0; i < (int)embd.size(); i += params.n_batch) { + for (int i = 0; i < (int)embd.size(); i += params->n_batch) { int n_eval = (int)embd.size() - i; - if (n_eval > params.n_batch) { - n_eval = params.n_batch; + if (n_eval > params->n_batch) { + n_eval = params->n_batch; } - if (llama_eval(ctx, &embd[i], n_eval, n_past, params.n_threads)) { + + if (llama_eval(ctx, &embd[i], n_eval, n_past, params->n_threads)) { fprintf(stderr, "%s : failed to eval\n", __func__); return 1; } + n_past += n_eval; } @@ -346,26 +272,26 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { if ((int)embd_inp.size() <= n_consumed) { // out of user input, sample next token - const float temp = params.temp; + const float temp = params->temp; const int32_t top_k = - params.top_k <= 0 ? llama_n_vocab(ctx) : params.top_k; - const float top_p = params.top_p; - const float tfs_z = params.tfs_z; - const float typical_p = params.typical_p; + params->top_k <= 0 ? llama_n_vocab(ctx) : params->top_k; + const float top_p = params->top_p; + const float tfs_z = params->tfs_z; + const float typical_p = params->typical_p; const int32_t repeat_last_n = - params.repeat_last_n < 0 ? n_ctx : params.repeat_last_n; - const float repeat_penalty = params.repeat_penalty; - const float alpha_presence = params.presence_penalty; - const float alpha_frequency = params.frequency_penalty; - const int mirostat = params.mirostat; - const float mirostat_tau = params.mirostat_tau; - const float mirostat_eta = params.mirostat_eta; - const bool penalize_nl = params.penalize_nl; + params->repeat_last_n < 0 ? n_ctx : params->repeat_last_n; + const float repeat_penalty = params->repeat_penalty; + const float alpha_presence = params->presence_penalty; + const float alpha_frequency = params->frequency_penalty; + const int mirostat = params->mirostat; + const float mirostat_tau = params->mirostat_tau; + const float mirostat_eta = params->mirostat_eta; + const bool penalize_nl = params->penalize_nl; // optionally save the session on first sample (for faster prompt loading // next time) if (!path_session.empty() && need_to_save_session && - !params.prompt_cache_ro) { + !params->prompt_cache_ro) { need_to_save_session = false; llama_save_session_file(ctx, path_session.c_str(), session_tokens.data(), session_tokens.size()); @@ -378,8 +304,8 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { auto n_vocab = llama_n_vocab(ctx); // Apply params.logit_bias map - for (auto it = params.logit_bias.begin(); it != params.logit_bias.end(); - it++) { + for (auto it = params->logit_bias.begin(); + it != params->logit_bias.end(); it++) { logits[it->first] += it->second; } @@ -435,7 +361,6 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { id = llama_sample_token(ctx, &candidates_p); } } - // printf("`%d`", candidates_p.size); last_n_tokens.erase(last_n_tokens.begin()); last_n_tokens.push_back(id); @@ -450,7 +375,7 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { // call the token callback, no need to check if one is actually // registered, that will be handled on the Go side. auto token_str = llama_token_to_str(ctx, id); - if (!tokenCallback(state_pr, (char *)token_str)) { + if (!tokenCallback(ctx, (char *)token_str)) { break; } } else { @@ -461,7 +386,7 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { last_n_tokens.erase(last_n_tokens.begin()); last_n_tokens.push_back(embd_inp[n_consumed]); ++n_consumed; - if ((int)embd.size() >= params.n_batch) { + if ((int)embd.size() >= params->n_batch) { break; } } @@ -472,13 +397,13 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { } // check for stop prompt - if (params.antiprompt.size()) { + if (params->antiprompt.size()) { std::string last_output; for (auto id : last_n_tokens) { last_output += llama_token_to_str(ctx, id); } // Check if each of the reverse prompts appears at the end of the output. - for (std::string &antiprompt : params.antiprompt) { + for (std::string &antiprompt : params->antiprompt) { // size_t extra_padding = params.interactive ? 0 : 2; size_t extra_padding = 2; size_t search_start_pos = @@ -501,8 +426,8 @@ int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug) { } } - if (!path_session.empty() && params.prompt_cache_all && - !params.prompt_cache_ro) { + if (!path_session.empty() && params->prompt_cache_all && + !params->prompt_cache_ro) { if (debug) { fprintf(stderr, "\n%s: saving final output to session file '%s'\n", __func__, path_session.c_str()); @@ -525,68 +450,8 @@ end: return 0; } -void llama_binding_free_model(void *state_ptr) { - llama_context *ctx = (llama_context *)state_ptr; - llama_free(ctx); -} - -void llama_free_params(void *params_ptr) { - gpt_params *params = (gpt_params *)params_ptr; - delete params; -} - -std::vector create_vector(const char **strings, int count) { - std::vector *vec = new std::vector; - for (int i = 0; i < count; i++) { - vec->push_back(std::string(strings[i])); - } - return *vec; -} - -void delete_vector(std::vector *vec) { delete vec; } - -int load_state(void *ctx, char *statefile, char *modes) { - llama_context *state = (llama_context *)ctx; - const llama_context *constState = static_cast(state); - const size_t state_size = llama_get_state_size(state); - uint8_t *state_mem = new uint8_t[state_size]; - - { - FILE *fp_read = fopen(statefile, modes); - if (state_size != llama_get_state_size(constState)) { - fprintf(stderr, "\n%s : failed to validate state size\n", __func__); - return 1; - } - - const size_t ret = fread(state_mem, 1, state_size, fp_read); - if (ret != state_size) { - fprintf(stderr, "\n%s : failed to read state\n", __func__); - return 1; - } - - llama_set_state_data( - state, state_mem); // could also read directly from memory mapped file - fclose(fp_read); - } - - return 0; -} - -void save_state(void *ctx, char *dst, char *modes) { - llama_context *state = (llama_context *)ctx; - - const size_t state_size = llama_get_state_size(state); - uint8_t *state_mem = new uint8_t[state_size]; - - // Save state (rng, logits, embedding and kv_cache) to file - { - FILE *fp_write = fopen(dst, modes); - llama_copy_state_data( - state, state_mem); // could also copy directly to memory mapped file - fwrite(state_mem, 1, state_size, fp_write); - fclose(fp_write); - } -} +void llama_binding_free_model(void *ctx) { llama_free((llama_context *)ctx); } +void llama_free_params(void *params) { delete (gpt_params *)params; } void *llama_allocate_params( const char *prompt, int seed, int threads, int tokens, int top_k, @@ -640,9 +505,13 @@ void *llama_allocate_params( if (ignore_eos) { params->logit_bias[llama_token_eos()] = -INFINITY; } + if (antiprompt_count > 0) { - params->antiprompt = create_vector(antiprompt, antiprompt_count); + for (int i = 0; i < antiprompt_count; i++) { + params->antiprompt.push_back(std::string(antiprompt[i])); + } } + params->tfs_z = tfs_z; params->typical_p = typical_p; params->presence_penalty = presence_penalty; @@ -650,6 +519,7 @@ void *llama_allocate_params( params->mirostat_eta = mirostat_eta; params->mirostat_tau = mirostat_tau; params->penalize_nl = penalize_nl; + std::stringstream ss(logit_bias); llama_token key; char sign; @@ -669,7 +539,6 @@ void *load_model(const char *fname, int n_ctx, int n_seed, bool memory_f16, bool mlock, bool embeddings, bool mmap, bool low_vram, bool vocab_only, int n_gpu_layers, int n_batch, const char *maingpu, const char *tensorsplit, bool numa) { - // load the model auto lparams = llama_context_default_params(); lparams.n_ctx = n_ctx; @@ -706,25 +575,11 @@ void *load_model(const char *fname, int n_ctx, int n_seed, bool memory_f16, lparams.n_batch = n_batch; llama_init_backend(numa); - void *res = nullptr; - try { - llama_model *model = llama_load_model_from_file(fname, lparams); - if (model == NULL) { - fprintf(stderr, "error: failed to load model \n"); - return res; - } - llama_context *lctx = llama_new_context_with_model(model, lparams); - if (lctx == NULL) { - fprintf(stderr, "error: failed to create context with model \n"); - llama_free_model(model); - return res; - } - - } catch (std::runtime_error &e) { - fprintf(stderr, "failed %s", e.what()); - return res; + struct llama_model *model = llama_load_model_from_file(fname, lparams); + if (!model) { + return nullptr; } - return res; + return llama_new_context_with_model(model, lparams); } diff --git a/llama/binding/binding.h b/llama/binding/binding.h index 56dd4d8e..0430de4c 100644 --- a/llama/binding/binding.h +++ b/llama/binding/binding.h @@ -30,22 +30,13 @@ extern "C" { extern unsigned char tokenCallback(void *, char *); -int load_state(void *ctx, char *statefile, char *modes); - -int eval(void *params_ptr, void *ctx, char *text); - -void save_state(void *ctx, char *dst, char *modes); +int eval(void *p, void *c, char *text); void *load_model(const char *fname, int n_ctx, int n_seed, bool memory_f16, bool mlock, bool embeddings, bool mmap, bool low_vram, bool vocab_only, int n_gpu, int n_batch, const char *maingpu, const char *tensorsplit, bool numa); -int get_embeddings(void *params_ptr, void *state_pr, float *res_embeddings); - -int get_token_embeddings(void *params_ptr, void *state_pr, int *tokens, - int tokenSize, float *res_embeddings); - void *llama_allocate_params( const char *prompt, int seed, int threads, int tokens, int top_k, float top_p, float temp, float repeat_penalty, int repeat_last_n, @@ -59,13 +50,11 @@ void *llama_allocate_params( void llama_free_params(void *params_ptr); -void llama_binding_free_model(void *state); +void llama_binding_free_model(void *ctx); int llama_predict(void *params_ptr, void *state_pr, char *result, bool debug); #ifdef __cplusplus } -std::vector create_vector(const char **strings, int count); -void delete_vector(std::vector *vec); #endif diff --git a/llama/llama.go b/llama/llama.go index 09243d6e..03da5410 100644 --- a/llama/llama.go +++ b/llama/llama.go @@ -31,135 +31,35 @@ package llama import "C" import ( "fmt" - "os" "strings" "sync" "unsafe" ) type LLama struct { - state unsafe.Pointer + ctx unsafe.Pointer embeddings bool contextSize int } func New(model string, opts ...ModelOption) (*LLama, error) { mo := NewModelOptions(opts...) + + // TODO: free this pointer modelPath := C.CString(model) - result := C.load_model(modelPath, C.int(mo.ContextSize), C.int(mo.Seed), C.bool(mo.F16Memory), C.bool(mo.MLock), C.bool(mo.Embeddings), C.bool(mo.MMap), C.bool(mo.LowVRAM), C.bool(mo.VocabOnly), C.int(mo.NGPULayers), C.int(mo.NBatch), C.CString(mo.MainGPU), C.CString(mo.TensorSplit), C.bool(mo.NUMA)) - if result == nil { + + ctx := C.load_model(modelPath, C.int(mo.ContextSize), C.int(mo.Seed), C.bool(mo.F16Memory), C.bool(mo.MLock), C.bool(mo.Embeddings), C.bool(mo.MMap), C.bool(mo.LowVRAM), C.bool(mo.VocabOnly), C.int(mo.NGPULayers), C.int(mo.NBatch), C.CString(mo.MainGPU), C.CString(mo.TensorSplit), C.bool(mo.NUMA)) + if ctx == nil { return nil, fmt.Errorf("failed loading model") } - ll := &LLama{state: result, contextSize: mo.ContextSize, embeddings: mo.Embeddings} + ll := &LLama{ctx: ctx, contextSize: mo.ContextSize, embeddings: mo.Embeddings} return ll, nil } func (l *LLama) Free() { - C.llama_binding_free_model(l.state) -} - -func (l *LLama) LoadState(state string) error { - d := C.CString(state) - w := C.CString("rb") - - result := C.load_state(l.state, d, w) - if result != 0 { - return fmt.Errorf("error while loading state") - } - - return nil -} - -func (l *LLama) SaveState(dst string) error { - d := C.CString(dst) - w := C.CString("wb") - - C.save_state(l.state, d, w) - - _, err := os.Stat(dst) - return err -} - -// Token Embeddings -func (l *LLama) TokenEmbeddings(tokens []int, opts ...PredictOption) ([]float32, error) { - if !l.embeddings { - return []float32{}, fmt.Errorf("model loaded without embeddings") - } - - po := NewPredictOptions(opts...) - - outSize := po.Tokens - if po.Tokens == 0 { - outSize = 9999999 - } - - floats := make([]float32, outSize) - - myArray := (*C.int)(C.malloc(C.size_t(len(tokens)) * C.sizeof_int)) - - // Copy the values from the Go slice to the C array - for i, v := range tokens { - (*[1<<31 - 1]int32)(unsafe.Pointer(myArray))[i] = int32(v) - } - - params := C.llama_allocate_params(C.CString(""), C.int(po.Seed), C.int(po.Threads), C.int(po.Tokens), C.int(po.TopK), - C.float(po.TopP), C.float(po.Temperature), C.float(po.Penalty), C.int(po.Repeat), - C.bool(po.IgnoreEOS), C.bool(po.F16KV), - C.int(po.Batch), C.int(po.NKeep), nil, C.int(0), - C.float(po.TailFreeSamplingZ), C.float(po.TypicalP), C.float(po.FrequencyPenalty), C.float(po.PresencePenalty), - C.int(po.Mirostat), C.float(po.MirostatETA), C.float(po.MirostatTAU), C.bool(po.PenalizeNL), C.CString(po.LogitBias), - C.CString(po.PathPromptCache), C.bool(po.PromptCacheAll), C.bool(po.MLock), C.bool(po.MMap), - C.CString(po.MainGPU), C.CString(po.TensorSplit), - C.bool(po.PromptCacheRO), - ) - ret := C.get_token_embeddings(params, l.state, myArray, C.int(len(tokens)), (*C.float)(&floats[0])) - if ret != 0 { - return floats, fmt.Errorf("embedding inference failed") - } - return floats, nil -} - -// Embeddings -func (l *LLama) Embeddings(text string, opts ...PredictOption) ([]float32, error) { - if !l.embeddings { - return []float32{}, fmt.Errorf("model loaded without embeddings") - } - - po := NewPredictOptions(opts...) - - input := C.CString(text) - if po.Tokens == 0 { - po.Tokens = 99999999 - } - floats := make([]float32, po.Tokens) - reverseCount := len(po.StopPrompts) - reversePrompt := make([]*C.char, reverseCount) - var pass **C.char - for i, s := range po.StopPrompts { - cs := C.CString(s) - reversePrompt[i] = cs - pass = &reversePrompt[0] - } - - params := C.llama_allocate_params(input, C.int(po.Seed), C.int(po.Threads), C.int(po.Tokens), C.int(po.TopK), - C.float(po.TopP), C.float(po.Temperature), C.float(po.Penalty), C.int(po.Repeat), - C.bool(po.IgnoreEOS), C.bool(po.F16KV), - C.int(po.Batch), C.int(po.NKeep), pass, C.int(reverseCount), - C.float(po.TailFreeSamplingZ), C.float(po.TypicalP), C.float(po.FrequencyPenalty), C.float(po.PresencePenalty), - C.int(po.Mirostat), C.float(po.MirostatETA), C.float(po.MirostatTAU), C.bool(po.PenalizeNL), C.CString(po.LogitBias), - C.CString(po.PathPromptCache), C.bool(po.PromptCacheAll), C.bool(po.MLock), C.bool(po.MMap), - C.CString(po.MainGPU), C.CString(po.TensorSplit), - C.bool(po.PromptCacheRO), - ) - - ret := C.get_embeddings(params, l.state, (*C.float)(&floats[0])) - if ret != 0 { - return floats, fmt.Errorf("embedding inference failed") - } - - return floats, nil + C.llama_binding_free_model(l.ctx) } func (l *LLama) Eval(text string, opts ...PredictOption) error { @@ -189,7 +89,7 @@ func (l *LLama) Eval(text string, opts ...PredictOption) error { C.CString(po.MainGPU), C.CString(po.TensorSplit), C.bool(po.PromptCacheRO), ) - ret := C.eval(params, l.state, input) + ret := C.eval(params, l.ctx, input) if ret != 0 { return fmt.Errorf("inference failed") } @@ -203,7 +103,7 @@ func (l *LLama) Predict(text string, opts ...PredictOption) (string, error) { po := NewPredictOptions(opts...) if po.TokenCallback != nil { - setCallback(l.state, po.TokenCallback) + setCallback(l.ctx, po.TokenCallback) } input := C.CString(text) @@ -231,7 +131,7 @@ func (l *LLama) Predict(text string, opts ...PredictOption) (string, error) { C.CString(po.MainGPU), C.CString(po.TensorSplit), C.bool(po.PromptCacheRO), ) - ret := C.llama_predict(params, l.state, (*C.char)(unsafe.Pointer(&out[0])), C.bool(po.DebugMode)) + ret := C.llama_predict(params, l.ctx, (*C.char)(unsafe.Pointer(&out[0])), C.bool(po.DebugMode)) if ret != 0 { return "", fmt.Errorf("inference failed") } @@ -248,7 +148,7 @@ func (l *LLama) Predict(text string, opts ...PredictOption) (string, error) { C.llama_free_params(params) if po.TokenCallback != nil { - setCallback(l.state, nil) + setCallback(l.ctx, nil) } return res, nil @@ -268,7 +168,7 @@ func (l *LLama) Predict(text string, opts ...PredictOption) (string, error) { // // It is save to call this method while a prediction is running. func (l *LLama) SetTokenCallback(callback func(token string) bool) { - setCallback(l.state, callback) + setCallback(l.ctx, callback) } var ( diff --git a/python/README.md b/python/README.md deleted file mode 100644 index b871efe7..00000000 --- a/python/README.md +++ /dev/null @@ -1,39 +0,0 @@ -# Ollama Python bindings - -``` -pip install ollama -``` - -## Developing - -Ollama is built using Python 3 and uses [Poetry](https://python-poetry.org/) to manage dependencies and build packages. - -``` -pip install poetry -``` - -Install ollama and its dependencies: - -``` -poetry install --extras server --with dev -``` - -Run ollama server: - -``` -poetry run ollama server -``` - -Update dependencies: - -``` -poetry update --extras server --with dev -poetry lock -poetry export >requirements.txt -``` - -Build binary package: - -``` -poetry build -``` diff --git a/python/ollama/__init__.py b/python/ollama/__init__.py deleted file mode 100644 index 384eea19..00000000 --- a/python/ollama/__init__.py +++ /dev/null @@ -1,9 +0,0 @@ -from ollama.model import models -from ollama.engine import generate, load, unload - -__all__ = [ - 'models', - 'generate', - 'load', - 'unload', -] diff --git a/python/ollama/__main__.py b/python/ollama/__main__.py deleted file mode 100644 index c422e75c..00000000 --- a/python/ollama/__main__.py +++ /dev/null @@ -1,4 +0,0 @@ -from ollama.cmd import cli - -if __name__ == '__main__': - cli.main() diff --git a/python/ollama/cmd/__init__.py b/python/ollama/cmd/__init__.py deleted file mode 100644 index e69de29b..00000000 diff --git a/python/ollama/cmd/cli.py b/python/ollama/cmd/cli.py deleted file mode 100644 index 26602fa3..00000000 --- a/python/ollama/cmd/cli.py +++ /dev/null @@ -1,192 +0,0 @@ -import os -import sys -from argparse import ArgumentParser, HelpFormatter, PARSER -from yaspin import yaspin - -from ollama import model, engine -from ollama.cmd import server - - -class CustomHelpFormatter(HelpFormatter): - """ - This class is used to customize the way the argparse help text is displayed. - We specifically override the _format_action method to exclude the line that - shows all the subparser command options in the help text. This line is typically - in the form "{serve,models,pull,run}". - """ - - def _format_action(self, action): - # get the original help text - parts = super()._format_action(action) - if action.nargs == PARSER: - # remove the unwanted first line - parts = "\n".join(parts.split("\n")[1:]) - return parts - - -def main(): - parser = ArgumentParser( - description='Ollama: Run any large language model on any machine.', - formatter_class=CustomHelpFormatter, - ) - - # create models home if it doesn't exist - os.makedirs(model.MODELS_CACHE_PATH, exist_ok=True) - - subparsers = parser.add_subparsers( - title='commands', - ) - - list_parser = subparsers.add_parser( - "models", - description="List all available models stored locally.", - help="List all available models stored locally.", - ) - list_parser.set_defaults(fn=list_models) - - search_parser = subparsers.add_parser( - "search", - description="Search for compatible models that Ollama can run.", - help="Search for compatible models that Ollama can run. Usage: search [model]", - ) - search_parser.add_argument( - "query", - nargs="?", - help="Optional name of the model to search for.", - ) - search_parser.set_defaults(fn=search) - - pull_parser = subparsers.add_parser( - "pull", - description="Download a specified model from a remote source.", - help="Download a specified model from a remote source. Usage: pull [model]", - ) - pull_parser.add_argument("model", help="Name of the model to download.") - pull_parser.set_defaults(fn=pull) - - run_parser = subparsers.add_parser( - "run", - description="Run a model and submit prompts.", - help="Run a model and submit prompts. Usage: run [model] [prompt]", - ) - run_parser.add_argument("model", help="Name of the model to run.") - run_parser.add_argument( - "prompt", - nargs="?", - help="Optional prompt for the model, interactive mode enabled when not specified.", - ) - run_parser.set_defaults(fn=run) - - server.set_parser( - subparsers.add_parser( - "serve", - description="Start a persistent server to interact with models via the API.", - help="Start a persistent server to interact with models via the API.", - ) - ) - - args = parser.parse_args() - args = vars(args) - - try: - fn = args.pop("fn") - fn(**args) - except KeyboardInterrupt: - pass - except KeyError: - parser.print_help() - except Exception as e: - print(e) - - -def list_models(*args, **kwargs): - for m in model.models(*args, **kwargs): - print(m) - - -def generate(*args, **kwargs): - if prompt := kwargs.get("prompt"): - print(">>>", prompt, flush=True) - generate_oneshot(*args, **kwargs) - return - - if sys.stdin.isatty(): - return generate_interactive(*args, **kwargs) - - return generate_batch(*args, **kwargs) - - -def generate_oneshot(*args, **kwargs): - print(flush=True) - - spinner = yaspin() - spinner.start() - spinner_running = True - try: - for output in engine.generate(model_name=kwargs.pop('model'), *args, **kwargs): - choices = output.get("choices", []) - if len(choices) > 0: - if spinner_running: - spinner.stop() - spinner_running = False - print("\r", end="") # move cursor back to beginning of line again - print(choices[0].get("text", ""), end="", flush=True) - except Exception: - spinner.stop() - raise - - # end with a new line - print(flush=True) - print(flush=True) - - -def generate_interactive(*args, **kwargs): - while True: - print(">>> ", end="", flush=True) - line = next(sys.stdin) - if not line: - return - - kwargs.update({"prompt": line}) - generate_oneshot(*args, **kwargs) - - -def generate_batch(*args, **kwargs): - for line in sys.stdin: - print(">>> ", line, end="", flush=True) - kwargs.update({"prompt": line}) - generate_oneshot(*args, **kwargs) - - -def search(*args, **kwargs): - try: - model_names = model.search_directory(*args, **kwargs) - if len(model_names) == 0: - print("No models found.") - return - elif len(model_names) == 1: - print(f"Found {len(model_names)} available model:") - else: - print(f"Found {len(model_names)} available models:") - for model_name in model_names: - print(model_name.lower()) - except Exception as e: - print("Failed to fetch available models, check your network connection") - - -def pull(*args, **kwargs): - try: - model.pull(model_name=kwargs.pop('model'), *args, **kwargs) - print("Up to date.") - except Exception as e: - print(f"An error occurred: {e}") - - -def run(*args, **kwargs): - try: - name = model.pull(model_name=kwargs.pop('model'), *args, **kwargs) - kwargs.update({"model": name}) - print(f"Running {name}...") - generate(*args, **kwargs) - except Exception as e: - print(f"An error occurred: {e}") diff --git a/python/ollama/cmd/server.py b/python/ollama/cmd/server.py deleted file mode 100644 index d634babe..00000000 --- a/python/ollama/cmd/server.py +++ /dev/null @@ -1,94 +0,0 @@ -import json -import aiohttp_cors -from aiohttp import web - -from ollama import engine - - -def set_parser(parser): - parser.add_argument("--host", default="127.0.0.1") - parser.add_argument("--port", default=7734) - parser.set_defaults(fn=serve) - - -def serve(*args, **kwargs): - app = web.Application() - - cors = aiohttp_cors.setup( - app, - defaults={ - "*": aiohttp_cors.ResourceOptions( - allow_credentials=True, - expose_headers="*", - allow_headers="*", - ) - }, - ) - - app.add_routes( - [ - web.post("/load", load), - web.post("/unload", unload), - web.post("/generate", generate), - ] - ) - - for route in app.router.routes(): - cors.add(route) - - app.update( - { - "models": {}, - } - ) - - web.run_app(app, **kwargs) - - -async def load(request): - body = await request.json() - name = body.get("model") - if not name: - raise web.HTTPBadRequest() - - kwargs = { - "models": request.app.get("models"), - } - - engine.load(name, **kwargs) - return web.Response() - - -async def unload(request): - body = await request.json() - name = body.get("model") - if not name: - raise web.HTTPBadRequest() - - engine.unload(name, models=request.app.get("models")) - return web.Response() - - -async def generate(request): - body = await request.json() - name = body.get("model") - if not name: - raise web.HTTPBadRequest() - - prompt = body.get("prompt") - if not prompt: - raise web.HTTPBadRequest() - - response = web.StreamResponse() - await response.prepare(request) - - kwargs = { - "models": request.app.get("models"), - } - - for output in engine.generate(name, prompt, **kwargs): - output = json.dumps(output).encode('utf-8') - await response.write(output) - await response.write(b"\n") - - return response diff --git a/python/ollama/engine.py b/python/ollama/engine.py deleted file mode 100644 index 63eeb769..00000000 --- a/python/ollama/engine.py +++ /dev/null @@ -1,121 +0,0 @@ -import os -import sys -from os import path -from contextlib import contextmanager -from thefuzz import process -from llama_cpp import Llama -from ctransformers import AutoModelForCausalLM - -import ollama.prompt -from ollama.model import MODELS_CACHE_PATH - - -@contextmanager -def suppress(file): - original = os.dup(file.fileno()) - with open(os.devnull, "w") as devnull: - os.dup2(devnull.fileno(), file.fileno()) - yield - - os.dup2(original, file.fileno()) - - -def generate(model_name, prompt, models={}, *args, **kwargs): - model = load(model_name, models=models) - inputs = ollama.prompt.template(model_name, prompt) - return model.generate(inputs, *args, **kwargs) - - -def load(model_name, models={}): - if not models.get(model_name, None): - model_path = path.expanduser(model_name) - if not path.exists(model_path): - model_path = str(MODELS_CACHE_PATH / (model_name + ".bin")) - - runners = { - model_type: cls - for cls in [LlamaCppRunner, CtransformerRunner] - for model_type in cls.model_types() - } - - for match, _ in process.extract(model_path, runners.keys(), limit=len(runners)): - try: - model = runners.get(match) - runner = model(model_path, match) - models.update({model_name: runner}) - return runner - except Exception: - pass - - raise Exception("failed to load model", model_path, model_name) - - -def unload(model_name, models={}): - if model_name in models: - models.pop(model_name) - - -class LlamaCppRunner: - def __init__(self, model_path, model_type): - try: - with suppress(sys.stderr), suppress(sys.stdout): - self.model = Llama(model_path, verbose=False, n_gpu_layers=1, seed=-1) - except Exception: - raise Exception("Failed to load model", model_path, model_type) - - @staticmethod - def model_types(): - return [ - 'llama', - 'orca', - 'vicuna', - 'ultralm', - ] - - def generate(self, prompt, *args, **kwargs): - if "max_tokens" not in kwargs: - kwargs.update({"max_tokens": 512}) - - if "stop" not in kwargs: - kwargs.update({"stop": ["Q:"]}) - - if "stream" not in kwargs: - kwargs.update({"stream": True}) - - with suppress(sys.stderr): - for output in self.model(prompt, *args, **kwargs): - yield output - - -class CtransformerRunner: - def __init__(self, model_path, model_type): - self.model = AutoModelForCausalLM.from_pretrained( - model_path, model_type=model_type, local_files_only=True - ) - - @staticmethod - def model_types(): - return [ - 'falcon', - 'mpt', - 'starcoder', - ] - - def generate(self, prompt, *args, **kwargs): - if "max_new_tokens" not in kwargs: - kwargs.update({"max_new_tokens": 512}) - - if "stop" not in kwargs: - kwargs.update({"stop": ["User"]}) - - if "stream" not in kwargs: - kwargs.update({"stream": True}) - - for output in self.model(prompt, *args, **kwargs): - yield { - 'choices': [ - { - 'text': output, - }, - ], - } diff --git a/python/ollama/model.py b/python/ollama/model.py deleted file mode 100644 index f3cefa79..00000000 --- a/python/ollama/model.py +++ /dev/null @@ -1,157 +0,0 @@ -import requests -import validators -from pathlib import Path -from os import path, walk -from urllib.parse import urlsplit, urlunsplit -from tqdm import tqdm - - -MODELS_MANIFEST = 'https://ollama.ai/api/models' -MODELS_CACHE_PATH = Path.home() / '.ollama' / 'models' - - -def models(*args, **kwargs): - for _, _, files in walk(MODELS_CACHE_PATH): - for file in files: - base, ext = path.splitext(file) - if ext == '.bin': - yield base - - -# search the directory and return all models which contain the search term as a substring, -# or all models if no search term is provided -def search_directory(query): - response = requests.get(MODELS_MANIFEST) - response.raise_for_status() - directory = response.json() - model_names = [] - for model_info in directory: - if not query or query.lower() in model_info.get('name', '').lower(): - model_names.append(model_info.get('name')) - return model_names - - -# get the url of the model from our curated directory -def get_url_from_directory(model): - response = requests.get(MODELS_MANIFEST) - response.raise_for_status() - directory = response.json() - for model_info in directory: - if model_info.get('name').lower() == model.lower(): - return model_info.get('url') - return model - - -def download_from_repo(url, file_name): - parts = urlsplit(url) - path_parts = parts.path.split('/tree/') - - if len(path_parts) == 1: - location = path_parts[0] - branch = 'main' - else: - location, branch = path_parts - - location = location.strip('/') - if file_name == '': - file_name = path.basename(location).lower() - download_url = urlunsplit( - ( - 'https', - parts.netloc, - f'/api/models/{location}/tree/{branch}', - parts.query, - parts.fragment, - ) - ) - response = requests.get(download_url) - response.raise_for_status() - json_response = response.json() - - download_url, file_size = find_bin_file(json_response, location, branch) - return download_file(download_url, file_name, file_size) - - -def find_bin_file(json_response, location, branch): - download_url = None - file_size = 0 - for file_info in json_response: - if file_info.get('type') == 'file' and file_info.get('path').endswith('.bin'): - f_path = file_info.get('path') - download_url = ( - f'https://huggingface.co/{location}/resolve/{branch}/{f_path}' - ) - file_size = file_info.get('size') - - if download_url is None: - raise Exception('No model found') - - return download_url, file_size - - -def download_file(download_url, file_name, file_size): - local_filename = MODELS_CACHE_PATH / str(file_name + '.bin') - - first_byte = path.getsize(local_filename) if path.exists(local_filename) else 0 - - if first_byte >= file_size: - return local_filename - - print(f'Pulling {file_name}...') - - header = {'Range': f'bytes={first_byte}-'} if first_byte != 0 else {} - - response = requests.get(download_url, headers=header, stream=True) - response.raise_for_status() - - total_size = int(response.headers.get('content-length', 0)) + first_byte - - with open(local_filename, 'ab' if first_byte else 'wb') as file, tqdm( - total=total_size, - unit='iB', - unit_scale=True, - unit_divisor=1024, - initial=first_byte, - ascii=' ==', - bar_format='Downloading [{bar}] {percentage:3.2f}% {rate_fmt}{postfix}', - ) as bar: - for data in response.iter_content(chunk_size=1024): - size = file.write(data) - bar.update(size) - - return local_filename - - -def pull(model_name, *args, **kwargs): - # check the remote model location and see if it needs to be downloaded - url = model_name - file_name = "" - if not validators.url(url) and not url.startswith('huggingface.co'): - try: - url = get_url_from_directory(model_name) - except Exception as e: - # may not have been able to check remote directory, return now - return model_name - if url is model_name: - # this is not a model from our directory, so can't check remote - maybe_existing_model_location = MODELS_CACHE_PATH / str(model_name + '.bin') - if path.exists(model_name) or path.exists(maybe_existing_model_location): - # a file on the filesystem is being specified - return model_name - raise Exception("unknown model") - else: - # this is a model from our directory, check remote - file_name = model_name - - if not (url.startswith('http://') or url.startswith('https://')): - url = f'https://{url}' - - if not validators.url(url): - if model_name in models(MODELS_CACHE_PATH): - # the model is already downloaded, and specified by name - return model_name - raise Exception(f'Unknown model {model_name}') - - local_filename = download_from_repo(url, file_name) - - return local_filename diff --git a/python/ollama/prompt.py b/python/ollama/prompt.py deleted file mode 100644 index 9759b249..00000000 --- a/python/ollama/prompt.py +++ /dev/null @@ -1,12 +0,0 @@ -from os import path -from difflib import get_close_matches -from jinja2 import Environment, PackageLoader - - -def template(name, prompt): - environment = Environment(loader=PackageLoader(__name__, 'templates')) - best_templates = get_close_matches( - path.basename(name), environment.list_templates(), n=1, cutoff=0 - ) - template = environment.get_template(best_templates.pop()) - return template.render(prompt=prompt) diff --git a/python/poetry.lock b/python/poetry.lock deleted file mode 100644 index fdd5a55d..00000000 --- a/python/poetry.lock +++ /dev/null @@ -1,1214 +0,0 @@ -# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. - 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--hash=sha256:d72916d27fb88741bfb576b0b0639354ca00f5e91046171c985262c68a86bbb5 \ - --hash=sha256:db5e71e5a810d2f1163c914e01b3ba241409a98286ac4850ff26076115ae401b \ - --hash=sha256:dc7f25e20781c8d42e813516ee4ff9043ecce4a8e25fc94ee6732a83d81c1c99 \ - --hash=sha256:de784bbe06d32e66617cd20766c37aae2438902d54b3fa608d2e0a929ca705f4 \ - --hash=sha256:e0755f5ac6c3d1dc2505eb2e6eaf5508ff17b42c084406714fbabf2d50d098b6 \ - --hash=sha256:e549da8d68ad4ee385c918ea8b9efeda875df9edf6c6b48df927bd061c00bfef \ - --hash=sha256:e6772eb7cc4429f1eae5a9b41e5b0b1af8f0d50727c6e338d9ad5bceee01da5a \ - --hash=sha256:ea3e46a534de97a6cad2018cb950492a0fcacad380e35440ce3c1c8fef96a261 \ - --hash=sha256:ec5523d5c08c639cd4e301d42f3ad7c6fb061a1f1cd6b5b627e59af345edfed7 \ - --hash=sha256:ef3ad80458e47723812976a2ea1282ff207ad20e6cb19da1917f76699bd5aaa5 \ - --hash=sha256:ef6c38040d868dcc0132fad377aafeb5b2da71354759e77f41ae599316df2dee \ - --hash=sha256:f1e23665be5918f979180130babedab9317fbb34cdae237c7defad7e86bc684e \ - --hash=sha256:f25d1975e846d07990cf946a5927a932aa7cccd308ae9979b03a58ff1cd80087 \ - --hash=sha256:f7acc5c9c7cf567372de5b6c817f93db508e7b9bd7f29bd6187df8d2cc60ced5 \ - --hash=sha256:fb7049dff52cded65184a3d2ff45cfd226bff7314f49a8f4b83f943eea9181a7 \ - --hash=sha256:fdd2ab5ab56fcaf839a9f58caa8756dbfeba0b3dc187850b763d0a1e6ee9c97a -requests==2.31.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f \ - --hash=sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1 -termcolor==2.3.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:3afb05607b89aed0ffe25202399ee0867ad4d3cb4180d98aaf8eefa6a5f7d475 \ - --hash=sha256:b5b08f68937f138fe92f6c089b99f1e2da0ae56c52b78bf7075fd95420fd9a5a -thefuzz[speedup]==0.19.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:4fcdde8e40f5ca5e8106bc7665181f9598a9c8b18b0a4d38c41a095ba6788972 \ - --hash=sha256:6f7126db2f2c8a54212b05e3a740e45f4291c497d75d20751728f635bb74aa3d -tqdm==4.65.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:1871fb68a86b8fb3b59ca4cdd3dcccbc7e6d613eeed31f4c332531977b89beb5 \ - --hash=sha256:c4f53a17fe37e132815abceec022631be8ffe1b9381c2e6e30aa70edc99e9671 -typing-extensions==4.7.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:5d8c9dac95c27d20df12fb1d97b9793ab8b2af8a3a525e68c80e21060c161771 \ - --hash=sha256:935ccf31549830cda708b42289d44b6f74084d616a00be651601a4f968e77c82 -urllib3==2.0.3 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:48e7fafa40319d358848e1bc6809b208340fafe2096f1725d05d67443d0483d1 \ - --hash=sha256:bee28b5e56addb8226c96f7f13ac28cb4c301dd5ea8a6ca179c0b9835e032825 -validators==0.20.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:24148ce4e64100a2d5e267233e23e7afeb55316b47d30faae7eb6e7292bc226a -yarl==1.9.2 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:04ab9d4b9f587c06d801c2abfe9317b77cdf996c65a90d5e84ecc45010823571 \ - --hash=sha256:066c163aec9d3d073dc9ffe5dd3ad05069bcb03fcaab8d221290ba99f9f69ee3 \ - 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--hash=sha256:b124e2a6d223b65ba8768d5706d103280914d61f5cae3afbc50fc3dfcc016623 \ - --hash=sha256:b25322201585c69abc7b0e89e72790469f7dad90d26754717f3310bfe30331c2 \ - --hash=sha256:b7232f8dfbd225d57340e441d8caf8652a6acd06b389ea2d3222b8bc89cbfca6 \ - --hash=sha256:b8cc1863402472f16c600e3e93d542b7e7542a540f95c30afd472e8e549fc3f7 \ - --hash=sha256:b9a4e67ad7b646cd6f0938c7ebfd60e481b7410f574c560e455e938d2da8e0f4 \ - --hash=sha256:be6b3fdec5c62f2a67cb3f8c6dbf56bbf3f61c0f046f84645cd1ca73532ea051 \ - --hash=sha256:bf74d08542c3a9ea97bb8f343d4fcbd4d8f91bba5ec9d5d7f792dbe727f88938 \ - --hash=sha256:c027a6e96ef77d401d8d5a5c8d6bc478e8042f1e448272e8d9752cb0aff8b5c8 \ - --hash=sha256:c0c77533b5ed4bcc38e943178ccae29b9bcf48ffd1063f5821192f23a1bd27b9 \ - --hash=sha256:c1012fa63eb6c032f3ce5d2171c267992ae0c00b9e164efe4d73db818465fac3 \ - --hash=sha256:c3a53ba34a636a256d767c086ceb111358876e1fb6b50dfc4d3f4951d40133d5 \ - --hash=sha256:d4e2c6d555e77b37288eaf45b8f60f0737c9efa3452c6c44626a5455aeb250b9 \ - --hash=sha256:de119f56f3c5f0e2fb4dee508531a32b069a5f2c6e827b272d1e0ff5ac040333 \ - --hash=sha256:e65610c5792870d45d7b68c677681376fcf9cc1c289f23e8e8b39c1485384185 \ - --hash=sha256:e9fdc7ac0d42bc3ea78818557fab03af6181e076a2944f43c38684b4b6bed8e3 \ - --hash=sha256:ee4afac41415d52d53a9833ebae7e32b344be72835bbb589018c9e938045a560 \ - --hash=sha256:f364d3480bffd3aa566e886587eaca7c8c04d74f6e8933f3f2c996b7f09bee1b \ - --hash=sha256:f3b078dbe227f79be488ffcfc7a9edb3409d018e0952cf13f15fd6512847f3f7 \ - --hash=sha256:f4e2d08f07a3d7d3e12549052eb5ad3eab1c349c53ac51c209a0e5991bbada78 \ - --hash=sha256:f7a3d8146575e08c29ed1cd287068e6d02f1c7bdff8970db96683b9591b86ee7 -yaspin==2.3.0 ; python_version >= "3.8" and python_version < "4.0" \ - --hash=sha256:17b5548479b3d5b30adec7a87ffcdcddb403d14a2bb86fbcee97f37951e13427 \ - --hash=sha256:547afd1a9700ac3a29a9f5591c70343bef186ed5dfb5e545a9bb0c77e561a1c9 diff --git a/server/routes.go b/server/routes.go index 4912d0c6..bd68ce04 100644 --- a/server/routes.go +++ b/server/routes.go @@ -17,26 +17,14 @@ import ( func Serve(ln net.Listener) error { r := gin.Default() - var l *llama.LLama - - gpulayers := 1 + // TODO: these should be request parameters + gpulayers := 0 tokens := 512 threads := runtime.NumCPU() - model := "/Users/pdevine/.cache/gpt4all/GPT4All-13B-snoozy.ggmlv3.q4_0.bin" - - r.POST("/api/load", func(c *gin.Context) { - var err error - l, err = llama.New(model, llama.EnableF16Memory, llama.SetContext(128), llama.EnableEmbeddings, llama.SetGPULayers(gpulayers)) - if err != nil { - fmt.Println("Loading the model failed:", err.Error()) - } - }) - - r.POST("/api/unload", func(c *gin.Context) { - }) r.POST("/api/generate", func(c *gin.Context) { // TODO: set prompt from template + fmt.Println("Generating text...") var req api.GenerateRequest if err := c.ShouldBindJSON(&req); err != nil { @@ -44,6 +32,14 @@ func Serve(ln net.Listener) error { return } + fmt.Println(req) + + l, err := llama.New(req.Model, llama.EnableF16Memory, llama.SetContext(128), llama.EnableEmbeddings, llama.SetGPULayers(gpulayers)) + if err != nil { + fmt.Println("Loading the model failed:", err.Error()) + return + } + ch := make(chan string) go func() { @@ -55,7 +51,7 @@ func Serve(ln net.Listener) error { if err != nil { panic(err) } - }() + }() c.Stream(func(w io.Writer) bool { tok, ok := <-ch @@ -65,11 +61,6 @@ func Serve(ln net.Listener) error { c.SSEvent("token", tok) return true }) - - // embeds, err := l.Embeddings(text) - // if err != nil { - // fmt.Printf("Embeddings: error %s \n", err.Error()) - // } }) log.Printf("Listening on %s", ln.Addr()) diff --git a/signature/signature.go b/signature/signature.go deleted file mode 100644 index 5f228144..00000000 --- a/signature/signature.go +++ /dev/null @@ -1,63 +0,0 @@ -package signature - -import ( - "bytes" - "crypto/sha256" - "encoding/base64" - "encoding/hex" - "fmt" - "strings" - - "golang.org/x/crypto/ssh" -) - -type SignatureData struct { - Method string - Path string - Data []byte -} - -func GetBytesToSign(s SignatureData) []byte { - // contentHash = base64(hex(sha256(s.Data))) - hash := sha256.Sum256(s.Data) - hashHex := make([]byte, hex.EncodedLen(len(hash))) - hex.Encode(hashHex, hash[:]) - contentHash := base64.StdEncoding.EncodeToString(hashHex) - - // bytesToSign e.g.: "GET,http://localhost,OTdkZjM1O... - bytesToSign := []byte(strings.Join([]string{s.Method, s.Path, contentHash}, ",")) - - return bytesToSign -} - -// SignData takes a SignatureData object and signs it with a raw private key -func SignAuthData(s SignatureData, rawKey []byte) (string, error) { - bytesToSign := GetBytesToSign(s) - - // TODO replace this w/ a non-SSH based private key - privateKey, err := ssh.ParseRawPrivateKey(rawKey) - if err != nil { - return "", err - } - - signer, err := ssh.NewSignerFromKey(privateKey) - if err != nil { - return "", err - } - - // get the pubkey, but remove the type - pubKey := ssh.MarshalAuthorizedKey(signer.PublicKey()) - parts := bytes.Split(pubKey, []byte(" ")) - if len(parts) < 2 { - return "", fmt.Errorf("malformed private key") - } - - signedData, err := signer.Sign(nil, bytesToSign) - if err != nil { - return "", err - } - - // signature is : - sig := fmt.Sprintf("%s:%s", bytes.TrimSpace(parts[1]), base64.StdEncoding.EncodeToString(signedData.Blob)) - return sig, nil -}