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Add Ollama #646

Merged
merged 6 commits into from
Jul 10, 2024
Merged

Add Ollama #646

merged 6 commits into from
Jul 10, 2024

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jtpio
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@jtpio jtpio commented Feb 16, 2024

Fixes #482

Ollama seems to be getting popular for running models locally, and looks like it would be good to have in Jupyter AI by default.

  • Add OllamaProvider
  • Add OllamaEmbeddingsProvider
  • Expand the list of available models
  • Add documentation
  • Mark as experimental, like for GPT4All?

image

@jtpio jtpio added the enhancement New feature or request label Feb 16, 2024
@jtpio
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jtpio commented Feb 16, 2024

I guess it would also be fine to have it as a custom model provider in a separate package, if we don't want to maintain it here in this repo.

@dlqqq
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dlqqq commented Feb 17, 2024

Jeremy, thank you very much for working on this PR and for keeping up with the open source LLM ecosystem. I lack the time to engage there as much as I would like.

Let me know when this PR is ready, and I will approve & merge it once I run it locally. 👍

@lalanikarim
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Looking forward to this integration.
Is it feasible to have the list of supported models as configurable given that there are numerous finetunes out there that would be viable candidates with Ollama?

@jtpio
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jtpio commented Feb 20, 2024

Thanks @dlqqq and @lalanikarim!

Yeah I'll try to finish the PR soon. It was originally opened early to see if there was interest to have built-in support for Ollama in jupyter-ai.

Is it feasible to have the list of supported models as configurable given that there are numerous finetunes out there that would be viable candidates with Ollama?

Currently jupyter_ai seems to have support for allowing and blocking models:

allowed_models = List(
Unicode(),
default_value=None,
help="""
Language models to allow, as a list of global model IDs in the format
`<provider>:<local-model-id>`. If `None`, all are allowed. Defaults to
`None`.
Note: Currently, if `allowed_providers` is also set, then this field is
ignored. This is subject to change in a future non-major release. Using
both traits is considered to be undefined behavior at this time.
""",
allow_none=True,
config=True,
)

Although not sure if that would be enough to use models that have not been added to the list of models in jupyter_ai.

@startakovsky
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startakovsky commented Feb 24, 2024

🙇 @jtpio excited for this

@lalanikarim
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Since Ollama sports an OpenAI compatible Rest API, and jupyter-ai supports setting a base url to override the default OpenAI url, I created new local models based on models supported by Ollama and named them to match OpenAI models.

$ cat mistral-gpt-4.modelfile
FROM mistral

$ ollama create gpt-4 -f mistral-gpt-4.modelfile

This hack currently allows me to use Ollama with jupyter-ai.

Looking forward to integration to support local models hosted with Ollama.

Screenshot 2024-03-03 at 11 05 10 AM Screenshot 2024-03-03 at 11 08 55 AM

@triinity2221
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@lalanikarim - I am also replicating a similar setup. Just curious are you able to use the /learn, /generate commands in the chat

@lalanikarim
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@lalanikarim - I am also replicating a similar setup. Just curious are you able to use the /learn, /generate commands in the chat

I haven't had any luck with /generate. I run into pydantic errors.

pydantic.v1.error_wrappers.ValidationError: 1 validation error for Outline
sections
  field required (type=value_error.missing)

I haven't tried /learn yet.

@lalanikarim
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@jtpio I am wondering if it would make sense to provide model name in a free form text field for Ollama models and to require %%ai magic code to include model name for ollama models and limit models to a predefined list.

%%ai ollama:mistral

Thoughts?

@jtpio
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jtpio commented Mar 5, 2024

@jtpio I am wondering if it would make sense to provide model name in a free form text field for Ollama models and to require %%ai magic code to include model name for ollama models and limit models to a predefined list.

Yeah I guess given the number of available models it would be very difficult to pick just a few here in the jupyter-ai package. And that would also require updating Jupyter AI regularly, increasing maintenance load.

So yes having a way to let users configure the list of models sounds like a good idea.

@siliconberry
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Since Ollama sports an OpenAI compatible Rest API, and jupyter-ai supports setting a base url to override the default OpenAI url, I created new local models based on models supported by Ollama and named them to match OpenAI models.

$ cat mistral-gpt-4.modelfile
FROM mistral

$ ollama create gpt-4 -f mistral-gpt-4.modelfile

This hack currently allows me to use Ollama with jupyter-ai.

Looking forward to integration to support local models hosted with Ollama.

Screenshot 2024-03-03 at 11 05 10 AM Screenshot 2024-03-03 at 11 08 55 AM

Hi, Thanks for the hack. Its working. But curious.. how/what did you set the OPENAI API key ? Its working inside the chat box (Jupyternaut), but not inside the jupyter notebook. and its asking for OPEN_API_KEY. can u pl help ?

@Mrjaggu
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Mrjaggu commented Mar 13, 2024

Anything update on this pr for adding ollama to jupyter ai..

@jtpio
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jtpio commented Mar 13, 2024

I'll try to finish this PR soon, and provide a way to configure the list of models (+ docs).

@dannongruver
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@jtpio: Thank you for this ollama integration Jeremy! Also look forward to configurable models. Let me know where I can buy you a coffee.

@lalanikarim
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Hi, Thanks for the hack. Its working. But curious.. how/what did you set the OPENAI API key ? Its working inside the chat box (Jupyternaut), but not inside the jupyter notebook. and its asking for OPEN_API_KEY. can u pl help ?

@siliconberry You can put any value for OPANAI_API_KEY. It is needed for this hack to work but will be ignored by ollama.

@dannongruver
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@lalanikarim in answer to @siliconberry question, have you gotten both the chat/jupyternaut as well as notebook cell (ie magic %%ai) working with ollama?

I’m struggling now to get notebook working. When I set the OPENAI_API_KEY environment variable to a dummy key (sk-abcd1234), the notebook gives an error indicating that ChatGPT doesn’t accept the key. Jupyternaut chat works fine. It seems like either jupyter_ai’s notebook is not using the config.json like Jupyternaut or ollama does not support all ChatGPT api…? Idk, maybe I’m missing something

@dannongruver
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Nevermind @lalanikarim @siliconberry. The magic %%ai does work.

Note: The magic doesn’t use the config.json but uses environment vars for key and url.

@cboettig
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Just joining the chorus of folks who would be excited to see this, especially given the rate at which new open-weights models are regularly appearing for ollama (llama3, phi3, wizardlm2). ollama's use of local GPU seems a lot smoother too than gpt4all too.

@orkutmuratyilmaz
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I'm so excited for this! 😍😍😍

@pedrogutobjj
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any updates?

@srdas
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srdas commented Jul 2, 2024

@jtpio Please see also recent PR #868 in case this includes the remaining ideas you planned to implement?

@jtpio
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jtpio commented Jul 3, 2024

Thanks @srdas for the heads-up 👍

Looks like #868 lists more models, so we could continue with this PR instead of this one. But it would still be interesting for end users to have a way to configure the models, to avoid having to update Jupyter AI and make a new release each time there is a new model out there.

@srdas
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srdas commented Jul 3, 2024

Thanks @srdas for the heads-up 👍

Looks like #868 lists more models, so we could continue with this PR instead of this one. But it would still be interesting for end users to have a way to configure the models, to avoid having to update Jupyter AI and make a new release each time there is a new model out there.

Thanks @jtpio -- let me test the new PR locally and also summarize what remains from what you have proposed. The drop down list is becoming really long so keeping on adding new models at the pace they are being included in Ollama may not be ideal both from a maintenance point of view and from an interface one. It may be preferable to handle Ollama in the way HuggingFace models are treated in the drop-down listing, which may address your note above.

@dlqqq
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dlqqq commented Jul 8, 2024

@jtpio Thank you for checking in on this again! Since your PR does not duplicate the LangChain provider implementation and is older than #868, I think this PR (#646) should take precedence. Here are the next steps towards getting this merged:

Let me know if you need assistance!

@dlqqq
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dlqqq commented Jul 8, 2024

But it would still be interesting for end users to have a way to configure the models, to avoid having to update Jupyter AI and make a new release each time there is a new model out there.

@jtpio I agree! This should probably be done in a future PR however, as it is a broader change that is not strictly necessary for Ollama support in Jupyter AI.

@jtpio jtpio force-pushed the ollama branch 2 times, most recently from 697cf70 to bfb036a Compare July 10, 2024 08:42
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@srdas
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srdas commented Jul 10, 2024

@jtpio Awesome - the changes are working nicey. I tested it on the new embedding model list and it all seems to be working well.

### Ollama usage

To get started, follow the instructions on the [Ollama website](https://ollama.com/) to set up `ollama` and download the models locally. To select a model, enter the model name in the settings panel, for example `deepseek-coder-v2`.

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Use Ollama capitalized in line 362 in "... to set up ollama ... "

Suggest adding a few more notes to the docs as follows:

Once Ollama is installed, download the model using the following command in a terminal:

ollama pull <model_name>

For example: ollama pull llama3. Do this for both LLM models and embedding models, as many as needed.

Once the models are downloaded, start up the Ollama server:

ollama serve

The models will then be available in jupyter-ai.

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Good suggestion, but wouldn't block on this to merge. Also, this info can change based on ollama API, so we will be carrying instructions that are available in their docs and will have to update in case this changes.

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@3coins Agree. I tested it again and it's all working so merging is predicated.

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Thanks for adding the code to enable model choice.

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@jtpio
Looks great!

@3coins 3coins merged commit 9f70ea7 into jupyterlab:main Jul 10, 2024
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@jtpio jtpio deleted the ollama branch July 11, 2024 05:59
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jtpio commented Jul 11, 2024

Thanks all for the reviews and the merge!

@krassowski krassowski mentioned this pull request Jul 11, 2024
@pedrogutobjj
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image

I'm using the test version of 2.20, and I noticed that the line completion is not working, I tested it with the same model in VSCODE using the continue plugin and the code completion works, could it be a bug?

@srdas
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srdas commented Jul 12, 2024

@pedrogutobjj - it is working at my end. Did you enable Inline completion in settings?
image
Example:
image

@pedrogutobjj
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image

image

my configs @srdas

@pedrogutobjj
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@srdas
i need use -instruct for completion model? Or can I use the same one?

Another question, if I enable the "Whether to fetch completions History provider." It doesn't provide suggestions for models, it provides suggestions for what I've used on other notebooks in the past.

@srdas
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srdas commented Jul 12, 2024

You can use any model - I just used the instruct model as I could not find the version you are using on https://ollama.com/search. It shows this:
image
The run command gives a hint at what you need to name the model.
Also after you pull the Ollama model, you can run ollama list to see the exact name of the model.

I have to look into your second question some more.

@pedrogutobjj
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image

@srdas

@pedrogutobjj
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@srdas i need use -instruct for completion model? Or can I use the same one?

Another question, if I enable the "Whether to fetch completions History provider." It doesn't provide suggestions for models, it provides suggestions for what I've used on other notebooks in the past.

This happens when I activate the Whether to fetch completions History provider option, it brings codes that I have already used in the past, it has nothing to do with the model indications, as you mentioned in your post.

@srdas

image

@pedrogutobjj
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Another strange situation, even though there is no suggestion to complete the line, the gpu usage is at maximum, as if using a model, but nothing happens.

image

image

@kilmarnock
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kilmarnock commented Sep 28, 2024

for the records:

%%ai ollama:qwen2.5-coder:7b-instruct-q8_0 -m {"base_url":"http://192.168.x.y:11434"}
write some command in python

works.

Sort of
image

Marchlak pushed a commit to Marchlak/jupyter-ai that referenced this pull request Oct 28, 2024
* Add Ollama

* mistral:text for embeddings

* Add gemma

* Update the list of models

Co-authored-by: Bc <[email protected]>

* Mention Ollama in the docs

* Apply suggestions from code review

Co-authored-by: Piyush Jain <[email protected]>
Co-authored-by: david qiu <[email protected]>

---------

Co-authored-by: Bc <[email protected]>
Co-authored-by: Piyush Jain <[email protected]>
Co-authored-by: david qiu <[email protected]>
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