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jupyterlab · Nov 11, 2023 · 82f901f · 82f901f
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diff --git a/docs/source/users/index.md b/docs/source/users/index.md
@@ -120,6 +120,7 @@ Jupyter AI supports the following model providers:
 | Bedrock             | `bedrock`            | N/A                        | `boto3`                         |
 | Bedrock (chat)      | `bedrock-chat`       | N/A                        | `boto3`                         |
 | Cohere              | `cohere`             | `COHERE_API_KEY`           | `cohere`                        |
+| GPT4All             | `gpt4all`            | N/A                        | `gpt4all`                       |
 | Hugging Face Hub    | `huggingface_hub`    | `HUGGINGFACEHUB_API_TOKEN` | `huggingface_hub`, `ipywidgets`, `pillow` |
 | OpenAI              | `openai`             | `OPENAI_API_KEY`           | `openai`                        |
 | OpenAI (chat)       | `openai-chat`        | `OPENAI_API_KEY`           | `openai`                        |
@@ -352,19 +353,37 @@ response.  In this example, the endpoint returns an object with the schema
 ### GPT4All usage (early-stage)
 
 Currently, we offer experimental support for GPT4All. To get started, first
-decide which models you will use. We currently offer three models from GPT4All:
+decide which models you will use. We currently offer the following models from GPT4All:
 
 | Model name                   | Model size | Model bin URL                                              |
-|------------------------------|------------|------------------------------------------------------------|
-| `ggml-gpt4all-l13b-snoozy`   | 7.6 GB     | `http://gpt4all.io/models/ggml-gpt4all-l13b-snoozy.bin`    |
-| `ggml-gpt4all-j-v1.2-jazzy`  | 3.8 GB     | `https://gpt4all.io/models/ggml-gpt4all-j-v1.2-jazzy.bin`  |
-| `ggml-gpt4all-j-v1.3-groovy` | 3.8 GB     | `https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin` |
+|---------------------------------|------------|------------------------------------------------------------|
+| `ggml-gpt4all-l13b-snoozy`      | 7.6 GB     | `http://gpt4all.io/models/ggml-gpt4all-l13b-snoozy.bin`    |
+| `ggml-gpt4all-j-v1.2-jazzy`     | 3.8 GB     | `https://gpt4all.io/models/ggml-gpt4all-j-v1.2-jazzy.bin`  |
+| `ggml-gpt4all-j-v1.3-groovy`    | 3.8 GB     | `https://gpt4all.io/models/ggml-gpt4all-j-v1.3-groovy.bin` |
+| `mistral-7b-openorca.Q4_0`      | 3.8 GB     | `https://gpt4all.io/models/gguf/mistral-7b-openorca.Q4_0.gguf` |
+| `mistral-7b-instruct-v0.1.Q4_0` | 3.8 GB     | `https://gpt4all.io/models/gguf/mistral-7b-instruct-v0.1.Q4_0.gguf` |
+| `gpt4all-falcon-q4_0`           | 3.9 GB     | `https://gpt4all.io/models/gguf/gpt4all-falcon-q4_0.gguf` |
+| `wizardlm-13b-v1.2.Q4_0`        | 6.9 GB     | `https://gpt4all.io/models/gguf/wizardlm-13b-v1.2.Q4_0.gguf` |
+| `nous-hermes-llama2-13b.Q4_0`   | 6.9 GB     | `https://gpt4all.io/models/gguf/nous-hermes-llama2-13b.Q4_0.gguf` |
+| `gpt4all-13b-snoozy-q4_0`       | 6.9 GB     | `https://gpt4all.io/models/gguf/gpt4all-13b-snoozy-q4_0.gguf` |
+| `mpt-7b-chat-merges-q4_0`       | 3.5 GB     | `https://gpt4all.io/models/gguf/mpt-7b-chat-merges-q4_0.gguf` |
+| `orca-mini-3b-gguf2-q4_0`       | 1.8 GB     | `https://gpt4all.io/models/gguf/orca-mini-3b-gguf2-q4_0.gguf` |
+| `starcoder-q4_0`                | 8.4 GB     | `https://gpt4all.io/models/gguf/starcoder-q4_0.gguf` |
+| `rift-coder-v0-7b-q4_0`         | 3.6 GB     | `https://gpt4all.io/models/gguf/rift-coder-v0-7b-q4_0.gguf` |
+| `all-MiniLM-L6-v2-f16`          | 44 MB      | `https://gpt4all.io/models/gguf/all-MiniLM-L6-v2-f16.gguf` |
+| `em_german_mistral_v01.Q4_0`    | 3.8 GB     | `https://huggingface.co/TheBloke/em_german_mistral_v01-GGUF/resolve/main/em_german_mistral_v01.Q4_0.gguf` |
 
 
 Note that each model comes with its own license, and that users are themselves
 responsible for verifying that their usage complies with the license. You can
 find licensing details on the [GPT4All official site](https://gpt4all.io/index.html).
 
+First, create a folder to store the model files.
+
+```
+mkdir ~/.cache/gpt4all
+```
+
 For each model you use, you will have to run the command
 
 ```
@@ -949,9 +968,35 @@ following section.
 
 #### Configuring as a config file
 
-This configuration can also be specified in a config file in json format. The
-file should be named `jupyter_jupyter_ai_config.json` and saved in a path that
-JupyterLab can pick from. You can find this path by running `jupyter --paths`
+This configuration can also be specified in a config file in json format.
+
+Here is an example for configuring the `bedrock` provider for `ai21.j2-mid-v1`
+model.
+
+```json
+{
+    "AiExtension": {
+        "model_parameters": {
+            "bedrock:ai21.j2-mid-v1": {
+                "model_kwargs": {
+                    "maxTokens": 200
+                }
+            }
+        }
+    }
+}
+```
+
+There are several ways to specify JupyterLab to pick this config.
+
+The first option is to save this config in a file and specifying the filepath at startup using the `--config` or `-c` option.
+
+```bash
+jupyter lab --config <config-file-path>
+```
+
+The second option is to drop it in a location that JupyterLab scans for configuration files.
+The file should be named `jupyter_jupyter_ai_config.json` in this case. You can find these paths by running `jupyter --paths`
 command, and picking one of the paths from the `config` section.
 
 Here is an example of running the `jupyter --paths` command.
@@ -973,20 +1018,3 @@ data:
 runtime:
     /Users/3coins/Library/Jupyter/runtime
 ```
-
-Here is an example for configuring the `bedrock` provider for `ai21.j2-mid-v1`
-model.
-
-```json
-{
-    "AiExtension": {
-        "model_parameters": {
-            "bedrock:ai21.j2-mid-v1": {
-                "model_kwargs": {
-                    "maxTokens": 200
-                }
-            }
-        }
-    }
-}
-```
diff --git a/packages/jupyter-ai-magics/jupyter_ai_magics/__init__.py b/packages/jupyter-ai-magics/jupyter_ai_magics/__init__.py
@@ -4,6 +4,7 @@
 from .embedding_providers import (
     BedrockEmbeddingsProvider,
     CohereEmbeddingsProvider,
+    GPT4AllEmbeddingsProvider,
     HfHubEmbeddingsProvider,
     OpenAIEmbeddingsProvider,
 )

diff --git a/packages/jupyter-ai-magics/jupyter_ai_magics/embedding_providers.py b/packages/jupyter-ai-magics/jupyter_ai_magics/embedding_providers.py
@@ -1,3 +1,4 @@
+import os
 from typing import ClassVar, List
 
 from jupyter_ai_magics.providers import (
@@ -9,6 +10,7 @@
 from langchain.embeddings import (
     BedrockEmbeddings,
     CohereEmbeddings,
+    GPT4AllEmbeddings,
     HuggingFaceHubEmbeddings,
     OpenAIEmbeddings,
 )
@@ -103,3 +105,25 @@ class BedrockEmbeddingsProvider(BaseEmbeddingsProvider, BedrockEmbeddings):
     model_id_key = "model_id"
     pypi_package_deps = ["boto3"]
     auth_strategy = AwsAuthStrategy()
+
+
+class GPT4AllEmbeddingsProvider(BaseEmbeddingsProvider, GPT4AllEmbeddings):
+    def __init__(self, **kwargs):
+        from gpt4all import GPT4All
+
+        model_name = kwargs.get("model_id").split(":")[-1]
+
+        # GPT4AllEmbeddings doesn't allow any kwargs at the moment
+        # This will cause the class to start downloading the model
+        # if the model file is not present. Calling retrieve_model
+        # here will throw an exception if the file is not present.
+        GPT4All.retrieve_model(model_name=model_name, allow_download=False)
+
+        kwargs["allow_download"] = False
+        super().__init__(**kwargs)
+
+    id = "gpt4all"
+    name = "GPT4All Embeddings"
+    models = ["all-MiniLM-L6-v2-f16"]
+    model_id_key = "model_id"
+    pypi_package_deps = ["gpt4all"]
diff --git a/packages/jupyter-ai-magics/jupyter_ai_magics/providers.py b/packages/jupyter-ai-magics/jupyter_ai_magics/providers.py
@@ -342,6 +342,17 @@ def __init__(self, **kwargs):
         "ggml-gpt4all-j-v1.3-groovy",
         # this one needs llama backend and has licence restriction
         "ggml-gpt4all-l13b-snoozy",
+        "mistral-7b-openorca.Q4_0",
+        "mistral-7b-instruct-v0.1.Q4_0",
+        "gpt4all-falcon-q4_0",
+        "wizardlm-13b-v1.2.Q4_0",
+        "nous-hermes-llama2-13b.Q4_0",
+        "gpt4all-13b-snoozy-q4_0",
+        "mpt-7b-chat-merges-q4_0",
+        "orca-mini-3b-gguf2-q4_0",
+        "starcoder-q4_0",
+        "rift-coder-v0-7b-q4_0",
+        "em_german_mistral_v01.Q4_0",
     ]
     model_id_key = "model"
     pypi_package_deps = ["gpt4all"]

diff --git a/packages/jupyter-ai-magics/pyproject.toml b/packages/jupyter-ai-magics/pyproject.toml
@@ -72,6 +72,7 @@ amazon-bedrock-chat = "jupyter_ai_magics:BedrockChatProvider"
 [project.entry-points."jupyter_ai.embeddings_model_providers"]
 bedrock = "jupyter_ai_magics:BedrockEmbeddingsProvider"
 cohere = "jupyter_ai_magics:CohereEmbeddingsProvider"
+gpt4all = "jupyter_ai_magics:GPT4AllEmbeddingsProvider"
 huggingface_hub = "jupyter_ai_magics:HfHubEmbeddingsProvider"
 openai = "jupyter_ai_magics:OpenAIEmbeddingsProvider"
 

diff --git a/packages/jupyter-ai/jupyter_ai/chat_handlers/base.py b/packages/jupyter-ai/jupyter_ai/chat_handlers/base.py
@@ -68,7 +68,7 @@ async def handle_exc(self, e: Exception, message: HumanChatMessage):
         implementation is provided, however chat handlers (subclasses) should
         implement this method to provide a more helpful error response.
         """
-        self._default_handle_exc(e, message)
+        await self._default_handle_exc(e, message)
 
     async def _default_handle_exc(self, e: Exception, message: HumanChatMessage):
         """