mirror of
https://github.com/nomic-ai/gpt4all
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104 lines
3.8 KiB
C++
104 lines
3.8 KiB
C++
#ifndef LLMODEL_H
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#define LLMODEL_H
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#include <string>
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#include <functional>
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#include <vector>
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#include <string_view>
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#include <fstream>
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#include <cstdint>
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#include <limits>
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#define LLMODEL_MAX_PROMPT_BATCH 128
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class Dlhandle;
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class LLModel {
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public:
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using Token = int32_t;
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class Implementation {
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public:
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Implementation(Dlhandle&&);
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Implementation(const Implementation&) = delete;
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Implementation(Implementation&&);
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~Implementation();
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std::string_view modelType() const { return m_modelType; }
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std::string_view buildVariant() const { return m_buildVariant; }
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static bool isImplementation(const Dlhandle&);
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static const std::vector<Implementation>& implementationList();
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static const Implementation *implementation(std::ifstream& f, const std::string& buildVariant);
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static LLModel *construct(const std::string &modelPath, std::string buildVariant = "auto");
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static void setImplementationsSearchPath(const std::string& path);
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static const std::string& implementationsSearchPath();
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private:
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bool (*m_magicMatch)(std::ifstream& f);
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LLModel *(*m_construct)();
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private:
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std::string_view m_modelType;
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std::string_view m_buildVariant;
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Dlhandle *m_dlhandle;
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};
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struct PromptContext {
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std::vector<float> logits; // logits of current context
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std::vector<int32_t> tokens; // current tokens in the context window
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int32_t n_past = 0; // number of tokens in past conversation
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int32_t n_ctx = 0; // number of tokens possible in context window
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int32_t n_predict = 200;
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int32_t top_k = 40;
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float top_p = 0.9f;
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float temp = 0.9f;
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int32_t n_batch = 9;
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float repeat_penalty = 1.10f;
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int32_t repeat_last_n = 64; // last n tokens to penalize
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float contextErase = 0.75f; // percent of context to erase if we exceed the context
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// window
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};
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explicit LLModel() {}
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virtual ~LLModel() {}
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virtual bool loadModel(const std::string &modelPath) = 0;
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virtual bool isModelLoaded() const = 0;
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virtual size_t requiredMem(const std::string &modelPath) = 0;
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virtual size_t stateSize() const { return 0; }
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virtual size_t saveState(uint8_t */*dest*/) const { return 0; }
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virtual size_t restoreState(const uint8_t */*src*/) { return 0; }
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virtual void prompt(const std::string &prompt,
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std::function<bool(int32_t)> promptCallback,
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std::function<bool(int32_t, const std::string&)> responseCallback,
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std::function<bool(bool)> recalculateCallback,
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PromptContext &ctx);
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virtual void setThreadCount(int32_t /*n_threads*/) {}
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virtual int32_t threadCount() const { return 1; }
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const Implementation& implementation() const {
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return *m_implementation;
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}
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protected:
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// These are pure virtual because subclasses need to implement as the default implementation of
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// 'prompt' above calls these functions
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virtual std::vector<Token> tokenize(PromptContext &, const std::string&) const = 0;
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virtual std::string tokenToString(Token) const = 0;
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virtual Token sampleToken(PromptContext &ctx) const = 0;
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virtual bool evalTokens(PromptContext &/*ctx*/, const std::vector<int32_t>& /*tokens*/) const = 0;
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virtual int32_t contextLength() const = 0;
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virtual const std::vector<Token>& endTokens() const = 0;
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// This is a helper function called from the default implementation of 'prompt' but it can be
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// shared by all base classes so it isn't virtual
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void recalculateContext(PromptContext &promptCtx, std::function<bool(bool)> recalculate);
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const Implementation *m_implementation = nullptr;
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private:
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friend class LLMImplementation;
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};
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#endif // LLMODEL_H
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