python: always check status code of HTTP responses (#1502)

* disable llama.cpp logging unless GPT4ALL_VERBOSE_LLAMACPP envvar is
  nonempty
* make verbose flag for retrieve_model default false (but also be
  overridable via gpt4all constructor)

should be able to run a basic test:

```python
import gpt4all
model = gpt4all.GPT4All('/Users/aaron/Downloads/rift-coder-v0-7b-q4_0.gguf')
print(model.generate('def fib(n):'))
```

and see no non-model output when successful

.codespellrc

@@ -1,3 +1,3 @@
 [codespell]
-ignore-words-list = blong, belong, afterall, som
+ignore-words-list = blong, belong, afterall, som, assistent
 skip = .git,*.pdf,*.svg,*.lock

gpt4all-backend/llama.cpp-mainline

@@ -1 +1 @@
-Subproject commit 7b8f00f5ccf4fc3cc67fe1ced792b3aec1ae6c1c
+Subproject commit 3742085b0429cbe0ede49bcb9f891e4a5e25a724

gpt4all-backend/llama.cpp.cmake

@@ -238,6 +238,10 @@ if (LLAMA_KOMPUTE)
           kompute/op_norm.comp
           kompute/op_rmsnorm.comp
           kompute/op_diagmask.comp
+          kompute/op_mul_mat_mat_f32.comp
+          kompute/op_mul_mat_mat_f16.comp
+          kompute/op_mul_mat_mat_q8_0.comp
+          kompute/op_mul_mat_mat_q4_0.comp
           kompute/op_mul_mat_f16.comp
           kompute/op_mul_mat_q8_0.comp
           kompute/op_mul_mat_q4_0.comp
@@ -268,6 +272,10 @@ if (LLAMA_KOMPUTE)
           shaderop_norm.h
           shaderop_rmsnorm.h
           shaderop_diagmask.h
+          shaderop_mul_mat_mat_f32.h
+          shaderop_mul_mat_mat_f16.h
+          shaderop_mul_mat_mat_q8_0.h
+          shaderop_mul_mat_mat_q4_0.h
           shaderop_mul_mat_f16.h
           shaderop_mul_mat_q8_0.h
           shaderop_mul_mat_q4_0.h

gpt4all-backend/llamamodel.cpp

@@ -36,6 +36,17 @@ namespace {
 const char *modelType_ = "LLaMA";
 }
 
+static void null_log_callback(enum ggml_log_level level, const char* text, void* userdata) {
+    (void)level;
+    (void)text;
+    (void)userdata;
+}
+
+static bool llama_verbose() {
+    const char* var = getenv("GPT4ALL_VERBOSE_LLAMACPP");
+    return var && *var;
+}
+
 struct gpt_params {
     int32_t seed          = -1;   // RNG seed
     int32_t n_keep        = 0;    // number of tokens to keep from initial prompt
@@ -144,7 +155,9 @@ bool LLamaModel::loadModel(const std::string &modelPath)
     d_ptr->params.use_mlock  = params.use_mlock;
 #endif
 #ifdef GGML_USE_METAL
+    if (llama_verbose()) {
         std::cerr << "llama.cpp: using Metal" << std::endl;
+    }
     // metal always runs the whole model if n_gpu_layers is not 0, at least
     // currently
     d_ptr->params.n_gpu_layers = 1;
@@ -390,6 +403,9 @@ DLL_EXPORT bool magic_match(const char * fname) {
 }
 
 DLL_EXPORT LLModel *construct() {
+    if (!llama_verbose()) {
+        llama_log_set(null_log_callback, nullptr);
+    }
     return new LLamaModel;
 }
 }

gpt4all-backend/llmodel.cpp

@@ -113,17 +113,18 @@ const std::vector<LLModel::Implementation> &LLModel::Implementation::implementat
 
 const LLModel::Implementation* LLModel::Implementation::implementation(const char *fname, const std::string& buildVariant) {
     for (const auto& i : implementationList()) {
-        if (!i.m_magicMatch(fname)) continue;
         if (buildVariant != i.m_buildVariant) continue;
+        if (!i.m_magicMatch(fname)) continue;
         return &i;
     }
     return nullptr;
 }
 
 LLModel *LLModel::Implementation::construct(const std::string &modelPath, std::string buildVariant) {
-
-    if (!has_at_least_minimal_hardware())
+    if (!has_at_least_minimal_hardware()) {
+        std::cerr << "LLModel ERROR: CPU does not support AVX\n";
         return nullptr;
+    }
 
     // Get correct implementation
     const Implementation* impl = nullptr;

gpt4all-bindings/python/gpt4all/gpt4all.py

@@ -1,6 +1,8 @@
 """
 Python only API for running all GPT4All models.
 """
+from __future__ import annotations
+
 import os
 import sys
 import time
@@ -60,11 +62,12 @@ class GPT4All:
     def __init__(
         self,
         model_name: str,
-        model_path: Optional[str] = None,
+        model_path: Optional[Union[str, os.PathLike[str]]] = None,
         model_type: Optional[str] = None,
         allow_download: bool = True,
         n_threads: Optional[int] = None,
         device: Optional[str] = "cpu",
+        verbose: bool = False,
     ):
         """
         Constructor
@@ -89,7 +92,7 @@ class GPT4All:
         self.model_type = model_type
         self.model = pyllmodel.LLModel()
         # Retrieve model and download if allowed
-        self.config: ConfigType = self.retrieve_model(model_name, model_path=model_path, allow_download=allow_download)
+        self.config: ConfigType = self.retrieve_model(model_name, model_path=model_path, allow_download=allow_download, verbose=verbose)
         if device is not None:
             if device != "cpu":
                 self.model.init_gpu(model_path=self.config["path"], device=device)
@@ -110,14 +113,17 @@ class GPT4All:
         Returns:
             Model list in JSON format.
         """
-        return requests.get("https://gpt4all.io/models/models2.json").json()
+        resp = requests.get("https://gpt4all.io/models/models2.json")
+        if resp.status_code != 200:
+            raise ValueError(f'Request failed: HTTP {resp.status_code} {resp.reason}')
+        return resp.json()
 
     @staticmethod
     def retrieve_model(
         model_name: str,
-        model_path: Optional[str] = None,
+        model_path: Optional[Union[str, os.PathLike[str]]] = None,
         allow_download: bool = True,
-        verbose: bool = True,
+        verbose: bool = False,
     ) -> ConfigType:
         """
         Find model file, and if it doesn't exist, download the model.
@@ -160,7 +166,7 @@ class GPT4All:
                 )
             model_path = DEFAULT_MODEL_DIRECTORY
         else:
-            model_path = model_path.replace("\\", "\\\\")
+            model_path = str(model_path).replace("\\", "\\\\")
 
         if not os.path.exists(model_path):
             raise ValueError(f"Invalid model directory: {model_path}")
@@ -185,7 +191,7 @@ class GPT4All:
     @staticmethod
     def download_model(
         model_filename: str,
-        model_path: str,
+        model_path: Union[str, os.PathLike[str]],
         verbose: bool = True,
         url: Optional[str] = None,
     ) -> str:
@@ -212,6 +218,9 @@ class GPT4All:
         download_url = get_download_url(model_filename)
 
         response = requests.get(download_url, stream=True)
+        if response.status_code != 200:
+            raise ValueError(f'Request failed: HTTP {response.status_code} {response.reason}')
+
         total_size_in_bytes = int(response.headers.get("content-length", 0))
         block_size = 2**20  # 1 MB
 

gpt4all-chat/chat.cpp

@@ -385,7 +385,7 @@ bool Chat::serialize(QDataStream &stream, int version) const
         stream << m_modelInfo.filename();
     if (version > 2)
         stream << m_collections;
-    if (!m_llmodel->serialize(stream, version))
+    if (!m_llmodel->serialize(stream, version, true /*serializeKV*/))
         return false;
     if (!m_chatModel->serialize(stream, version))
         return false;
@@ -404,29 +404,36 @@ bool Chat::deserialize(QDataStream &stream, int version)
     QString modelId;
     stream >> modelId;
     if (version > 4) {
-        if (!ModelList::globalInstance()->contains(modelId))
-            return false;
+        if (ModelList::globalInstance()->contains(modelId))
             m_modelInfo = ModelList::globalInstance()->modelInfo(modelId);
     } else {
-        if (!ModelList::globalInstance()->containsByFilename(modelId))
-            return false;
+        if (ModelList::globalInstance()->containsByFilename(modelId))
             m_modelInfo = ModelList::globalInstance()->modelInfoByFilename(modelId);
     }
+    if (!m_modelInfo.id().isEmpty())
         emit modelInfoChanged();
 
+    bool deserializeKV = true; // make this a setting
+    bool discardKV = m_modelInfo.id().isEmpty();
+
     // Prior to version 2 gptj models had a bug that fixed the kv_cache to F32 instead of F16 so
     // unfortunately, we cannot deserialize these
     if (version < 2 && m_modelInfo.filename().contains("gpt4all-j"))
-        return false;
+        discardKV = true;
+
     if (version > 2) {
         stream >> m_collections;
         emit collectionListChanged(m_collections);
     }
     m_llmodel->setModelInfo(m_modelInfo);
-    if (!m_llmodel->deserialize(stream, version))
+    if (!m_llmodel->deserialize(stream, version, deserializeKV, discardKV))
         return false;
     if (!m_chatModel->deserialize(stream, version))
         return false;
+
+    if (!deserializeKV || discardKV)
+        m_llmodel->setStateFromText(m_chatModel->text());
+
     emit chatModelChanged();
     return stream.status() == QDataStream::Ok;
 }

gpt4all-chat/chatlistmodel.cpp

@@ -84,13 +84,16 @@ void ChatSaver::saveChats(const QVector<Chat *> &chats)
     const QString savePath = MySettings::globalInstance()->modelPath();
     for (Chat *chat : chats) {
         QString fileName = "gpt4all-" + chat->id() + ".chat";
-        QFile file(savePath + "/" + fileName);
-        bool success = file.open(QIODevice::WriteOnly);
+        QString filePath = savePath + "/" + fileName;
+        QFile originalFile(filePath);
+        QFile tempFile(filePath + ".tmp"); // Temporary file
+
+        bool success = tempFile.open(QIODevice::WriteOnly);
         if (!success) {
-            qWarning() << "ERROR: Couldn't save chat to file:" << file.fileName();
+            qWarning() << "ERROR: Couldn't save chat to temporary file:" << tempFile.fileName();
             continue;
         }
-        QDataStream out(&file);
+        QDataStream out(&tempFile);
 
         out << (quint32)CHAT_FORMAT_MAGIC;
         out << (qint32)CHAT_FORMAT_VERSION;
@@ -98,11 +101,16 @@ void ChatSaver::saveChats(const QVector<Chat *> &chats)
 
         qDebug() << "serializing chat" << fileName;
         if (!chat->serialize(out, CHAT_FORMAT_VERSION)) {
-            qWarning() << "ERROR: Couldn't serialize chat to file:" << file.fileName();
-            file.remove();
+            qWarning() << "ERROR: Couldn't serialize chat to file:" << tempFile.fileName();
+            tempFile.remove();
+            continue;
         }
-        file.close();
+
+        if (originalFile.exists())
+            originalFile.remove();
+        tempFile.rename(filePath);
     }
+
     qint64 elapsedTime = timer.elapsed();
     qDebug() << "serializing chats took:" << elapsedTime << "ms";
     emit saveChatsFinished();
@@ -224,7 +232,6 @@ void ChatsRestoreThread::run()
             chat->moveToThread(qApp->thread());
             if (!chat->deserialize(in, version)) {
                 qWarning() << "ERROR: Couldn't deserialize chat from file:" << file.fileName();
-                file.remove();
             } else {
                 emit chatRestored(chat);
             }

gpt4all-chat/chatllm.cpp

@@ -69,6 +69,7 @@ ChatLLM::ChatLLM(Chat *parent, bool isServer)
     , m_forceMetal(MySettings::globalInstance()->forceMetal())
     , m_reloadingToChangeVariant(false)
     , m_processedSystemPrompt(false)
+    , m_restoreStateFromText(false)
 {
     moveToThread(&m_llmThread);
     connect(this, &ChatLLM::sendStartup, Network::globalInstance(), &Network::sendStartup);
@@ -726,7 +727,35 @@ bool ChatLLM::handleSystemRecalculate(bool isRecalc)
     return false;
 }
 
-bool ChatLLM::serialize(QDataStream &stream, int version)
+bool ChatLLM::handleRestoreStateFromTextPrompt(int32_t token)
+{
+#if defined(DEBUG)
+    qDebug() << "restore state from text prompt" << m_llmThread.objectName() << token << m_stopGenerating;
+#endif
+    Q_UNUSED(token);
+    return !m_stopGenerating;
+}
+
+bool ChatLLM::handleRestoreStateFromTextResponse(int32_t token, const std::string &response)
+{
+#if defined(DEBUG)
+    qDebug() << "restore state from text response" << m_llmThread.objectName() << token << response << m_stopGenerating;
+#endif
+    Q_UNUSED(token);
+    Q_UNUSED(response);
+    return false;
+}
+
+bool ChatLLM::handleRestoreStateFromTextRecalculate(bool isRecalc)
+{
+#if defined(DEBUG)
+    qDebug() << "restore state from text recalc" << m_llmThread.objectName() << isRecalc;
+#endif
+    Q_UNUSED(isRecalc);
+    return false;
+}
+
+bool ChatLLM::serialize(QDataStream &stream, int version, bool serializeKV)
 {
     if (version > 1) {
         stream << m_llModelType;
@@ -741,8 +770,16 @@ bool ChatLLM::serialize(QDataStream &stream, int version)
     stream << response();
     stream << generatedName();
     stream << m_promptResponseTokens;
+
+    if (!serializeKV) {
+#if defined(DEBUG)
+        qDebug() << "serialize" << m_llmThread.objectName() << m_state.size();
+#endif
+        return stream.status() == QDataStream::Ok;
+    }
+
     if (version <= 3) {
-        int responseLogits;
+        int responseLogits = 0;
         stream << responseLogits;
     }
     stream << m_ctx.n_past;
@@ -759,7 +796,7 @@ bool ChatLLM::serialize(QDataStream &stream, int version)
     return stream.status() == QDataStream::Ok;
 }
 
-bool ChatLLM::deserialize(QDataStream &stream, int version)
+bool ChatLLM::deserialize(QDataStream &stream, int version, bool deserializeKV, bool discardKV)
 {
     if (version > 1) {
         int internalStateVersion;
@@ -773,26 +810,60 @@ bool ChatLLM::deserialize(QDataStream &stream, int version)
     stream >> nameResponse;
     m_nameResponse = nameResponse.toStdString();
     stream >> m_promptResponseTokens;
+
+    // If we do not deserialize the KV or it is discarded, then we need to restore the state from the
+    // text only. This will be a costly operation, but the chat has to be restored from the text archive
+    // alone.
+    m_restoreStateFromText = !deserializeKV || discardKV;
+
+    if (!deserializeKV) {
+#if defined(DEBUG)
+        qDebug() << "deserialize" << m_llmThread.objectName();
+#endif
+        return stream.status() == QDataStream::Ok;
+    }
+
     if (version <= 3) {
         int responseLogits;
         stream >> responseLogits;
     }
-    stream >> m_ctx.n_past;
+
+    int32_t n_past;
+    stream >> n_past;
+    if (!discardKV) m_ctx.n_past = n_past;
+
     quint64 logitsSize;
     stream >> logitsSize;
+    if (!discardKV) {
         m_ctx.logits.resize(logitsSize);
         stream.readRawData(reinterpret_cast<char*>(m_ctx.logits.data()), logitsSize * sizeof(float));
+    } else {
+        stream.skipRawData(logitsSize * sizeof(float));
+    }
+
     quint64 tokensSize;
     stream >> tokensSize;
+    if (!discardKV) {
         m_ctx.tokens.resize(tokensSize);
         stream.readRawData(reinterpret_cast<char*>(m_ctx.tokens.data()), tokensSize * sizeof(int));
+    } else {
+        stream.skipRawData(tokensSize * sizeof(int));
+    }
+
     if (version > 0) {
         QByteArray compressed;
         stream >> compressed;
+        if (!discardKV)
             m_state = qUncompress(compressed);
     } else {
+        if (!discardKV)
+            stream >> m_state;
+        else {
+            QByteArray state;
             stream >> m_state;
         }
+    }
+
 #if defined(DEBUG)
     qDebug() << "deserialize" << m_llmThread.objectName();
 #endif
@@ -823,7 +894,7 @@ void ChatLLM::saveState()
 
 void ChatLLM::restoreState()
 {
-    if (!isModelLoaded() || m_state.isEmpty())
+    if (!isModelLoaded())
         return;
 
     if (m_llModelType == LLModelType::CHATGPT_) {
@@ -838,10 +909,19 @@ void ChatLLM::restoreState()
         return;
     }
 
+    if (m_restoreStateFromText) {
+        Q_ASSERT(m_state.isEmpty());
+        processRestoreStateFromText();
+    }
+
 #if defined(DEBUG)
     qDebug() << "restoreState" << m_llmThread.objectName() << "size:" << m_state.size();
 #endif
     m_processedSystemPrompt = true;
+
+    if (m_state.isEmpty())
+        return;
+
     m_llModelInfo.model->restoreState(static_cast<const uint8_t*>(reinterpret_cast<void*>(m_state.data())));
     m_state.clear();
     m_state.resize(0);
@@ -859,7 +939,10 @@ void ChatLLM::processSystemPrompt()
         return;
     }
 
+    // Start with a whole new context
     m_stopGenerating = false;
+    m_ctx = LLModel::PromptContext();
+
     auto promptFunc = std::bind(&ChatLLM::handleSystemPrompt, this, std::placeholders::_1);
     auto responseFunc = std::bind(&ChatLLM::handleSystemResponse, this, std::placeholders::_1,
         std::placeholders::_2);
@@ -890,5 +973,54 @@ void ChatLLM::processSystemPrompt()
     printf("\n");
     fflush(stdout);
 #endif
-    m_processedSystemPrompt = true;
+
+    m_processedSystemPrompt = !m_stopGenerating;
+}
+
+void ChatLLM::processRestoreStateFromText()
+{
+    Q_ASSERT(isModelLoaded());
+    if (!isModelLoaded() || !m_restoreStateFromText || m_isServer)
+        return;
+
+    m_isRecalc = true;
+    emit recalcChanged();
+
+    m_stopGenerating = false;
+    m_ctx = LLModel::PromptContext();
+
+    auto promptFunc = std::bind(&ChatLLM::handleRestoreStateFromTextPrompt, this, std::placeholders::_1);
+    auto responseFunc = std::bind(&ChatLLM::handleRestoreStateFromTextResponse, this, std::placeholders::_1,
+        std::placeholders::_2);
+    auto recalcFunc = std::bind(&ChatLLM::handleRestoreStateFromTextRecalculate, this, std::placeholders::_1);
+
+    const QString promptTemplate = MySettings::globalInstance()->modelPromptTemplate(m_modelInfo);
+    const int32_t n_predict = MySettings::globalInstance()->modelMaxLength(m_modelInfo);
+    const int32_t top_k = MySettings::globalInstance()->modelTopK(m_modelInfo);
+    const float top_p = MySettings::globalInstance()->modelTopP(m_modelInfo);
+    const float temp = MySettings::globalInstance()->modelTemperature(m_modelInfo);
+    const int32_t n_batch = MySettings::globalInstance()->modelPromptBatchSize(m_modelInfo);
+    const float repeat_penalty = MySettings::globalInstance()->modelRepeatPenalty(m_modelInfo);
+    const int32_t repeat_penalty_tokens = MySettings::globalInstance()->modelRepeatPenaltyTokens(m_modelInfo);
+    int n_threads = MySettings::globalInstance()->threadCount();
+    m_ctx.n_predict = n_predict;
+    m_ctx.top_k = top_k;
+    m_ctx.top_p = top_p;
+    m_ctx.temp = temp;
+    m_ctx.n_batch = n_batch;
+    m_ctx.repeat_penalty = repeat_penalty;
+    m_ctx.repeat_last_n = repeat_penalty_tokens;
+    m_llModelInfo.model->setThreadCount(n_threads);
+    for (auto pair : m_stateFromText) {
+        const QString str = pair.first == "Prompt: " ? promptTemplate.arg(pair.second) : pair.second;
+        m_llModelInfo.model->prompt(str.toStdString(), promptFunc, responseFunc, recalcFunc, m_ctx);
+    }
+
+    if (!m_stopGenerating) {
+        m_restoreStateFromText = false;
+        m_stateFromText.clear();
+    }
+
+    m_isRecalc = false;
+    emit recalcChanged();
 }

gpt4all-chat/chatllm.h

@@ -92,8 +92,9 @@ public:
 
     QString generatedName() const { return QString::fromStdString(m_nameResponse); }
 
-    bool serialize(QDataStream &stream, int version);
-    bool deserialize(QDataStream &stream, int version);
+    bool serialize(QDataStream &stream, int version, bool serializeKV);
+    bool deserialize(QDataStream &stream, int version, bool deserializeKV, bool discardKV);
+    void setStateFromText(const QVector<QPair<QString, QString>> &stateFromText) { m_stateFromText = stateFromText; }
 
 public Q_SLOTS:
     bool prompt(const QList<QString> &collectionList, const QString &prompt);
@@ -110,6 +111,7 @@ public Q_SLOTS:
     void handleForceMetalChanged(bool forceMetal);
     void handleDeviceChanged();
     void processSystemPrompt();
+    void processRestoreStateFromText();
 
 Q_SIGNALS:
     void recalcChanged();
@@ -144,6 +146,9 @@ protected:
     bool handleSystemPrompt(int32_t token);
     bool handleSystemResponse(int32_t token, const std::string &response);
     bool handleSystemRecalculate(bool isRecalc);
+    bool handleRestoreStateFromTextPrompt(int32_t token);
+    bool handleRestoreStateFromTextResponse(int32_t token, const std::string &response);
+    bool handleRestoreStateFromTextRecalculate(bool isRecalc);
     void saveState();
     void restoreState();
 
@@ -168,6 +173,8 @@ private:
     bool m_forceMetal;
     bool m_reloadingToChangeVariant;
     bool m_processedSystemPrompt;
+    bool m_restoreStateFromText;
+    QVector<QPair<QString, QString>> m_stateFromText;
 };
 
 #endif // CHATLLM_H

gpt4all-chat/chatmodel.h

@@ -285,6 +285,14 @@ public:
         return stream.status() == QDataStream::Ok;
     }
 
+    QVector<QPair<QString, QString>> text() const
+    {
+        QVector<QPair<QString, QString>> result;
+        for (const auto &c : m_chatItems)
+            result << qMakePair(c.name, c.value);
+        return result;
+    }
+
 Q_SIGNALS:
     void countChanged();