mirror of
https://github.com/explosion/spaCy.git
synced 2025-07-16 19:22:34 +03:00
Merge 91a8004f08 into fd48150d15
This commit is contained in:
Raphael Mitsch
GitHub
commit
795c24deeb
|
|
@ -21,8 +21,8 @@ through a generic `llm`
|
|||
[component factory](https://spacy.io/usage/processing-pipelines#custom-components-factories)
|
||||
as well as through task-specific component factories: `llm_ner`, `llm_spancat`,
|
||||
`llm_rel`, `llm_textcat`, `llm_sentiment`, `llm_summarization`,
|
||||
`llm_entity_linker`, `llm_raw` and `llm_translation`. For these factories, the
|
||||
GPT-3-5 model from OpenAI is used by default, but this can be customized.
|
||||
`llm_entity_linker`, `llm_raw` and `llm_translation`. For these factories,
|
||||
OpenAI's GPT-3.5 model is used by default, but this can be customized.
|
||||
|
||||
> #### Example
|
||||
>
|
||||
|
|
@ -31,7 +31,7 @@ GPT-3-5 model from OpenAI is used by default, but this can be customized.
|
|||
> config = {"task": {"@llm_tasks": "spacy.NER.v3", "labels": ["PERSON", "ORGANISATION", "LOCATION"]}}
|
||||
> llm = nlp.add_pipe("llm", config=config)
|
||||
>
|
||||
> # Construction via add_pipe with a task-specific factory and default GPT3.5 model
|
||||
> # Construction via add_pipe with a task-specific factory and default GPT-3.5 model
|
||||
> llm = nlp.add_pipe("llm_ner")
|
||||
>
|
||||
> # Construction via add_pipe with a task-specific factory and custom model
|
||||
|
|
@ -1382,7 +1382,7 @@ provider's API.
|
|||
|
||||
| Argument | Description |
|
||||
| ------------------ | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------ |
|
||||
| `name` | Model name, i. e. any supported variant for this particular model. Default depends on the specific model (cf. below) ~~str~~ |
|
||||
| `name` | Any supported model name for this particular model provider. ~~str~~ |
|
||||
| `config` | Further configuration passed on to the model. Default depends on the specific model (cf. below). ~~Dict[Any, Any]~~ |
|
||||
| `strict` | If `True`, raises an error if the LLM API returns a malformed response. Otherwise, return the error responses as is. Defaults to `True`. ~~bool~~ |
|
||||
| `max_tries` | Max. number of tries for API request. Defaults to `5`. ~~int~~ |
|
||||
|
|
@ -1394,50 +1394,21 @@ provider's API.
|
|||
>
|
||||
> ```ini
|
||||
> [components.llm.model]
|
||||
> @llm_models = "spacy.GPT-4.v1"
|
||||
> @llm_models = "spacy.OpenAI.v1"
|
||||
> name = "gpt-4"
|
||||
> config = {"temperature": 0.0}
|
||||
> ```
|
||||
|
||||
Currently, these models are provided as part of the core library:
|
||||
Currently, these model providers are supported as part of the core library (more
|
||||
can be used by leveraging the LangChain integration):
|
||||
|
||||
| Model | Provider | Supported names | Default name | Default config |
|
||||
| ----------------------------- | ----------------- | ------------------------------------------------------------------------------------------------------------------ | ---------------------- | ------------------------------------ |
|
||||
| `spacy.GPT-4.v1` | OpenAI | `["gpt-4", "gpt-4-0314", "gpt-4-32k", "gpt-4-32k-0314"]` | `"gpt-4"` | `{}` |
|
||||
| `spacy.GPT-4.v2` | OpenAI | `["gpt-4", "gpt-4-0314", "gpt-4-32k", "gpt-4-32k-0314"]` | `"gpt-4"` | `{temperature=0.0}` |
|
||||
| `spacy.GPT-4.v3` | OpenAI | All names of [GPT-4 models](https://platform.openai.com/docs/models/gpt-4-and-gpt-4-turbo) offered by OpenAI | `"gpt-4"` | `{temperature=0.0}` |
|
||||
| `spacy.GPT-3-5.v1` | OpenAI | `["gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-0613-16k", "gpt-3.5-turbo-instruct"]` | `"gpt-3.5-turbo"` | `{}` |
|
||||
| `spacy.GPT-3-5.v2` | OpenAI | `["gpt-3.5-turbo", "gpt-3.5-turbo-16k", "gpt-3.5-turbo-0613", "gpt-3.5-turbo-0613-16k", "gpt-3.5-turbo-instruct"]` | `"gpt-3.5-turbo"` | `{temperature=0.0}` |
|
||||
| `spacy.GPT-3-5.v3` | OpenAI | All names of [GPT-3.5 models](https://platform.openai.com/docs/models/gpt-3-5) offered by OpenAI | `"gpt-3.5-turbo"` | `{temperature=0.0}` |
|
||||
| `spacy.Davinci.v1` | OpenAI | `["davinci"]` | `"davinci"` | `{}` |
|
||||
| `spacy.Davinci.v2` | OpenAI | `["davinci"]` | `"davinci"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Text-Davinci.v1` | OpenAI | `["text-davinci-003", "text-davinci-002"]` | `"text-davinci-003"` | `{}` |
|
||||
| `spacy.Text-Davinci.v2` | OpenAI | `["text-davinci-003", "text-davinci-002"]` | `"text-davinci-003"` | `{temperature=0.0, max_tokens=1000}` |
|
||||
| `spacy.Code-Davinci.v1` | OpenAI | `["code-davinci-002"]` | `"code-davinci-002"` | `{}` |
|
||||
| `spacy.Code-Davinci.v2` | OpenAI | `["code-davinci-002"]` | `"code-davinci-002"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Curie.v1` | OpenAI | `["curie"]` | `"curie"` | `{}` |
|
||||
| `spacy.Curie.v2` | OpenAI | `["curie"]` | `"curie"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Text-Curie.v1` | OpenAI | `["text-curie-001"]` | `"text-curie-001"` | `{}` |
|
||||
| `spacy.Text-Curie.v2` | OpenAI | `["text-curie-001"]` | `"text-curie-001"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Babbage.v1` | OpenAI | `["babbage"]` | `"babbage"` | `{}` |
|
||||
| `spacy.Babbage.v2` | OpenAI | `["babbage"]` | `"babbage"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Text-Babbage.v1` | OpenAI | `["text-babbage-001"]` | `"text-babbage-001"` | `{}` |
|
||||
| `spacy.Text-Babbage.v2` | OpenAI | `["text-babbage-001"]` | `"text-babbage-001"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Ada.v1` | OpenAI | `["ada"]` | `"ada"` | `{}` |
|
||||
| `spacy.Ada.v2` | OpenAI | `["ada"]` | `"ada"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Text-Ada.v1` | OpenAI | `["text-ada-001"]` | `"text-ada-001"` | `{}` |
|
||||
| `spacy.Text-Ada.v2` | OpenAI | `["text-ada-001"]` | `"text-ada-001"` | `{temperature=0.0, max_tokens=500}` |
|
||||
| `spacy.Azure.v1` | Microsoft, OpenAI | Arbitrary values | No default | `{temperature=0.0}` |
|
||||
| `spacy.Command.v1` | Cohere | `["command", "command-light", "command-light-nightly", "command-nightly"]` | `"command"` | `{}` |
|
||||
| `spacy.Claude-2-1.v1` | Anthropic | `["claude-2-1"]` | `"claude-2-1"` | `{}` |
|
||||
| `spacy.Claude-2.v1` | Anthropic | `["claude-2", "claude-2-100k"]` | `"claude-2"` | `{}` |
|
||||
| `spacy.Claude-1.v1` | Anthropic | `["claude-1", "claude-1-100k"]` | `"claude-1"` | `{}` |
|
||||
| `spacy.Claude-1-0.v1` | Anthropic | `["claude-1.0"]` | `"claude-1.0"` | `{}` |
|
||||
| `spacy.Claude-1-2.v1` | Anthropic | `["claude-1.2"]` | `"claude-1.2"` | `{}` |
|
||||
| `spacy.Claude-1-3.v1` | Anthropic | `["claude-1.3", "claude-1.3-100k"]` | `"claude-1.3"` | `{}` |
|
||||
| `spacy.Claude-instant-1.v1` | Anthropic | `["claude-instant-1", "claude-instant-1-100k"]` | `"claude-instant-1"` | `{}` |
|
||||
| `spacy.Claude-instant-1-1.v1` | Anthropic | `["claude-instant-1.1", "claude-instant-1.1-100k"]` | `"claude-instant-1.1"` | `{}` |
|
||||
| `spacy.PaLM.v1` | Google | `["chat-bison-001", "text-bison-001"]` | `"text-bison-001"` | `{temperature=0.0}` |
|
||||
| Model | Provider | Information on available models | Default config |
|
||||
| -------------------- | ----------------- | -------------------------------------------------------------------------------------------------------------------------------- | ------------------- |
|
||||
| `spacy.OpenAI.v1` | OpenAI | All completion/chat models listed [here](https://platform.openai.com/docs/models) | `{}` |
|
||||
| `spacy.Azure.v1` | Microsoft, OpenAI | All completion/chat models listed [here](https://learn.microsoft.com/en-us/azure/ai-services/openai/concepts/models) | `{temperature=0.0}` |
|
||||
| `spacy.Cohere.v1` | Cohere | All models listed [here](https://docs.cohere.com/docs/models) | `{}` |
|
||||
| `spacy.Anthropic.v1` | Anthropic | All models listed [here](https://docs.anthropic.com/claude/reference/selecting-a-model) | `{}` |
|
||||
| `spacy.Google.v1` | Google | All completion/chat models listed [here](https://cloud.google.com/vertex-ai/docs/generative-ai/language-model-overview#palm-api) | `{temperature=0.0}` |
|
||||
|
||||
To use these models, make sure that you've [set the relevant API](#api-keys)
|
||||
keys as environment variables.
|
||||
|
|
@ -1506,20 +1477,21 @@ These models all take the same parameters:
|
|||
>
|
||||
> ```ini
|
||||
> [components.llm.model]
|
||||
> @llm_models = "spacy.Llama2.v1"
|
||||
> @llm_models = "spacy.HuggingFace.v1"
|
||||
> name = "Llama-2-7b-hf"
|
||||
> ```
|
||||
|
||||
Currently, these models are provided as part of the core library:
|
||||
Currently, these models are provided as part of the core library (more models
|
||||
can be accessed through the `langchain` integration):
|
||||
|
||||
| Model | Provider | Supported names | HF directory |
|
||||
| -------------------- | --------------- | ------------------------------------------------------------------------------------------------------------ | -------------------------------------- |
|
||||
| `spacy.Dolly.v1` | Databricks | `["dolly-v2-3b", "dolly-v2-7b", "dolly-v2-12b"]` | https://huggingface.co/databricks |
|
||||
| `spacy.Falcon.v1` | TII | `["falcon-rw-1b", "falcon-7b", "falcon-7b-instruct", "falcon-40b-instruct"]` | https://huggingface.co/tiiuae |
|
||||
| `spacy.Llama2.v1` | Meta AI | `["Llama-2-7b-hf", "Llama-2-13b-hf", "Llama-2-70b-hf"]` | https://huggingface.co/meta-llama |
|
||||
| `spacy.Mistral.v1` | Mistral AI | `["Mistral-7B-v0.1", "Mistral-7B-Instruct-v0.1"]` | https://huggingface.co/mistralai |
|
||||
| `spacy.StableLM.v1` | Stability AI | `["stablelm-base-alpha-3b", "stablelm-base-alpha-7b", "stablelm-tuned-alpha-3b", "stablelm-tuned-alpha-7b"]` | https://huggingface.co/stabilityai |
|
||||
| `spacy.OpenLLaMA.v1` | OpenLM Research | `["open_llama_3b", "open_llama_7b", "open_llama_7b_v2", "open_llama_13b"]` | https://huggingface.co/openlm-research |
|
||||
| Model family | Author | Names of available model | HF directory |
|
||||
| ------------ | --------------- | ------------------------------------------------------------------------------------------------------------ | -------------------------------------- |
|
||||
| Dolly | Databricks | `["dolly-v2-3b", "dolly-v2-7b", "dolly-v2-12b"]` | https://huggingface.co/databricks |
|
||||
| Falcon | TII | `["falcon-rw-1b", "falcon-7b", "falcon-7b-instruct", "falcon-40b-instruct"]` | https://huggingface.co/tiiuae |
|
||||
| Llama 2 | Meta AI | `["Llama-2-7b-hf", "Llama-2-13b-hf", "Llama-2-70b-hf"]` | https://huggingface.co/meta-llama |
|
||||
| Mistral | Mistral AI | `["Mistral-7B-v0.1", "Mistral-7B-Instruct-v0.1"]` | https://huggingface.co/mistralai |
|
||||
| Stable LM | Stability AI | `["stablelm-base-alpha-3b", "stablelm-base-alpha-7b", "stablelm-tuned-alpha-3b", "stablelm-tuned-alpha-7b"]` | https://huggingface.co/stabilityai |
|
||||
| OpenLLaMa | OpenLM Research | `["open_llama_3b", "open_llama_7b", "open_llama_7b_v2", "open_llama_13b"]` | https://huggingface.co/openlm-research |
|
||||
|
||||
<Infobox variant="warning" title="Gated models on Hugging Face" id="hf_licensing">
|
||||
|
||||
|
|
@ -1569,7 +1541,7 @@ To use [LangChain](https://github.com/hwchase17/langchain) for the API retrieval
|
|||
part, make sure you have installed it first:
|
||||
|
||||
```shell
|
||||
python -m pip install "langchain==0.0.191"
|
||||
python -m pip install "langchain>=0.1,<0.2"
|
||||
# Or install with spacy-llm directly
|
||||
python -m pip install "spacy-llm[extras]"
|
||||
```
|
||||
|
|
@ -1579,9 +1551,12 @@ Note that LangChain currently only supports Python 3.9 and beyond.
|
|||
LangChain models in `spacy-llm` work slightly differently. `langchain`'s models
|
||||
are parsed automatically, each LLM class in `langchain` has one entry in
|
||||
`spacy-llm`'s registry. As `langchain`'s design has one class per API and not
|
||||
per model, this results in registry entries like `langchain.OpenAI.v1` - i. e.
|
||||
there is one registry entry per API and not per model (family), as for the REST-
|
||||
and HuggingFace-based entries.
|
||||
per model, this results in registry entries like `langchain.OpenAIChat.v1` - i.
|
||||
e. there is one registry entry per API and not per model (family), as for the
|
||||
REST- and HuggingFace-based entries. LangChain provides access to many more
|
||||
model that `spacy-llm` does natively, so if your model or provider of choice
|
||||
isn't available directly, just leverage the `langchain` integration by
|
||||
specifying your model with `langchain.YourModel.v1`!
|
||||
|
||||
The name of the model to be used has to be passed in via the `name` attribute.
|
||||
|
||||
|
|
@ -1589,7 +1564,7 @@ The name of the model to be used has to be passed in via the `name` attribute.
|
|||
>
|
||||
> ```ini
|
||||
> [components.llm.model]
|
||||
> @llm_models = "langchain.OpenAI.v1"
|
||||
> @llm_models = "langchain.OpenAIChat.v1"
|
||||
> name = "gpt-3.5-turbo"
|
||||
> query = {"@llm_queries": "spacy.CallLangChain.v1"}
|
||||
> config = {"temperature": 0.0}
|
||||
|
|
|
|||
|
|
@ -107,7 +107,8 @@ factory = "llm"
|
|||
labels = ["COMPLIMENT", "INSULT"]
|
||||
|
||||
[components.llm.model]
|
||||
@llm_models = "spacy.GPT-3-5.v1"
|
||||
@llm_models = "spacy.OpenAI.v1"
|
||||
name = "gpt-3.5-turbo"
|
||||
config = {"temperature": 0.0}
|
||||
```
|
||||
|
||||
|
|
@ -146,7 +147,7 @@ factory = "llm"
|
|||
labels = ["PERSON", "ORGANISATION", "LOCATION"]
|
||||
|
||||
[components.llm.model]
|
||||
@llm_models = "spacy.Dolly.v1"
|
||||
@llm_models = "spacy.HuggingFace.v1"
|
||||
# For better performance, use dolly-v2-12b instead
|
||||
name = "dolly-v2-3b"
|
||||
```
|
||||
|
|
@ -457,12 +458,13 @@ models by specifying one of the models registered with the `langchain.` prefix.
|
|||
_Why LangChain if there are also are native REST and HuggingFace interfaces? When should I use what?_
|
||||
|
||||
Third-party libraries like `langchain` focus on prompt management, integration
|
||||
of many different LLM APIs, and other related features such as conversational
|
||||
memory or agents. `spacy-llm` on the other hand emphasizes features we consider
|
||||
useful in the context of NLP pipelines utilizing LLMs to process documents
|
||||
(mostly) independent from each other. It makes sense that the feature sets of
|
||||
such third-party libraries and `spacy-llm` aren't identical - and users might
|
||||
want to take advantage of features not available in `spacy-llm`.
|
||||
of many different LLM APIs and models, and other related features such as
|
||||
conversational memory or agents. `spacy-llm` on the other hand emphasizes
|
||||
features we consider useful in the context of NLP pipelines utilizing LLMs for
|
||||
(1) extractive NLP and (2) to process documents independent from each other. It
|
||||
makes sense that the feature sets of such third-party libraries and `spacy-llm`
|
||||
aren't identical - and users might want to take advantage of features not
|
||||
available in `spacy-llm`.
|
||||
|
||||
The advantage of implementing our own REST and HuggingFace integrations is that
|
||||
we can ensure a larger degree of stability and robustness, as we can guarantee
|
||||
|
|
@ -481,36 +483,15 @@ provider's documentation.
|
|||
|
||||
</Infobox>
|
||||
|
||||
| Model | Description |
|
||||
| ----------------------------------------------------------------------- | ---------------------------------------------- |
|
||||
| [`spacy.GPT-4.v2`](/api/large-language-models#models-rest) | OpenAI’s `gpt-4` model family. |
|
||||
| [`spacy.GPT-3-5.v2`](/api/large-language-models#models-rest) | OpenAI’s `gpt-3-5` model family. |
|
||||
| [`spacy.Text-Davinci.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-davinci` model family. |
|
||||
| [`spacy.Code-Davinci.v2`](/api/large-language-models#models-rest) | OpenAI’s `code-davinci` model family. |
|
||||
| [`spacy.Text-Curie.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-curie` model family. |
|
||||
| [`spacy.Text-Babbage.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-babbage` model family. |
|
||||
| [`spacy.Text-Ada.v2`](/api/large-language-models#models-rest) | OpenAI’s `text-ada` model family. |
|
||||
| [`spacy.Davinci.v2`](/api/large-language-models#models-rest) | OpenAI’s `davinci` model family. |
|
||||
| [`spacy.Curie.v2`](/api/large-language-models#models-rest) | OpenAI’s `curie` model family. |
|
||||
| [`spacy.Babbage.v2`](/api/large-language-models#models-rest) | OpenAI’s `babbage` model family. |
|
||||
| [`spacy.Ada.v2`](/api/large-language-models#models-rest) | OpenAI’s `ada` model family. |
|
||||
| [`spacy.Azure.v1`](/api/large-language-models#models-rest) | Azure's OpenAI models. |
|
||||
| [`spacy.Command.v1`](/api/large-language-models#models-rest) | Cohere’s `command` model family. |
|
||||
| [`spacy.Claude-2.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-2` model family. |
|
||||
| [`spacy.Claude-1.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1` model family. |
|
||||
| [`spacy.Claude-instant-1.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-instant-1` model family. |
|
||||
| [`spacy.Claude-instant-1-1.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-instant-1.1` model family. |
|
||||
| [`spacy.Claude-1-0.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.0` model family. |
|
||||
| [`spacy.Claude-1-2.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.2` model family. |
|
||||
| [`spacy.Claude-1-3.v1`](/api/large-language-models#models-rest) | Anthropic’s `claude-1.3` model family. |
|
||||
| [`spacy.PaLM.v1`](/api/large-language-models#models-rest) | Google’s `PaLM` model family. |
|
||||
| [`spacy.Dolly.v1`](/api/large-language-models#models-hf) | Dolly models through HuggingFace. |
|
||||
| [`spacy.Falcon.v1`](/api/large-language-models#models-hf) | Falcon models through HuggingFace. |
|
||||
| [`spacy.Mistral.v1`](/api/large-language-models#models-hf) | Mistral models through HuggingFace. |
|
||||
| [`spacy.Llama2.v1`](/api/large-language-models#models-hf) | Llama2 models through HuggingFace. |
|
||||
| [`spacy.StableLM.v1`](/api/large-language-models#models-hf) | StableLM models through HuggingFace. |
|
||||
| [`spacy.OpenLLaMA.v1`](/api/large-language-models#models-hf) | OpenLLaMA models through HuggingFace. |
|
||||
| [LangChain models](/api/large-language-models#langchain-models) | LangChain models for API retrieval. |
|
||||
| Model | Description |
|
||||
| --------------------------------------------------------------- | -------------------------------------------------- |
|
||||
| [`spacy.OpenAI.v1`](/api/large-language-models#models-rest) | OpenAI's chat and completion models. |
|
||||
| [`spacy.Azure.v1`](/api/large-language-models#models-rest) | Azure's OpenAI models. |
|
||||
| [`spacy.Cohere.v1`](/api/large-language-models#models-rest) | Cohere’s text models. |
|
||||
| [`spacy.Anthropic.v1`](/api/large-language-models#models-rest) | Anthropic’s text models. |
|
||||
| [`spacy.Google.v1`](/api/large-language-models#models-rest) | Google’s text models (e. g. PaLM). |
|
||||
| [`spacy.HuggingFace.v1`](/api/large-language-models#models-hf) | A selection of LLMs available through HuggingFace. |
|
||||
| [LangChain models](/api/large-language-models#langchain-models) | All models available through `langchain`. |
|
||||
|
||||
Note that the chat models variants of Llama 2 are currently not supported. This
|
||||
is because they need a particular prompting setup and don't add any discernible
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user