adding support for Hugging Face Inference Endpoints (#460)

* stream complete sketch

* correct structure but issues

* refactor: :art: clean up hf_inference_api.py

* fix: :bug: quick fix in hf_infrerence_api.py

* feat: :memo: update documentation code for hf_inference_api

* hf docs

* now working

---------

Co-authored-by: Nate Sesti <sestinj@gmail.com>

8 files changed, 212 insertions, 55 deletions

diff --git a/continuedev/poetry.lock b/continuedev/poetry.lock
index 6808a83e..23ff9094 100644
--- a/continuedev/poetry.lock
+++ b/continuedev/poetry.lock
@@ -635,6 +635,24 @@ doc = ["mdx-include (>=1.4.1,<2.0.0)", "mkdocs (>=1.1.2,<2.0.0)", "mkdocs-markdo
 test = ["anyio[trio] (>=3.2.1,<4.0.0)", "black (==23.1.0)", "coverage[toml] (>=6.5.0,<8.0)", "databases[sqlite] (>=0.3.2,<0.7.0)", "email-validator (>=1.1.1,<2.0.0)", "flask (>=1.1.2,<3.0.0)", "httpx (>=0.23.0,<0.24.0)", "isort (>=5.0.6,<6.0.0)", "mypy (==0.982)", "orjson (>=3.2.1,<4.0.0)", "passlib[bcrypt] (>=1.7.2,<2.0.0)", "peewee (>=3.13.3,<4.0.0)", "pytest (>=7.1.3,<8.0.0)", "python-jose[cryptography] (>=3.3.0,<4.0.0)", "python-multipart (>=0.0.5,<0.0.7)", "pyyaml (>=5.3.1,<7.0.0)", "ruff (==0.0.138)", "sqlalchemy (>=1.3.18,<1.4.43)", "types-orjson (==3.6.2)", "types-ujson (==5.7.0.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0,<6.0.0)"]
 
 [[package]]
+name = "filelock"
+version = "3.12.3"
+description = "A platform independent file lock."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "filelock-3.12.3-py3-none-any.whl", hash = "sha256:f067e40ccc40f2b48395a80fcbd4728262fab54e232e090a4063ab804179efeb"},
+    {file = "filelock-3.12.3.tar.gz", hash = "sha256:0ecc1dd2ec4672a10c8550a8182f1bd0c0a5088470ecd5a125e45f49472fac3d"},
+]
+
+[package.dependencies]
+typing-extensions = {version = ">=4.7.1", markers = "python_version < \"3.11\""}
+
+[package.extras]
+docs = ["furo (>=2023.7.26)", "sphinx (>=7.1.2)", "sphinx-autodoc-typehints (>=1.24)"]
+testing = ["covdefaults (>=2.3)", "coverage (>=7.3)", "diff-cover (>=7.7)", "pytest (>=7.4)", "pytest-cov (>=4.1)", "pytest-mock (>=3.11.1)", "pytest-timeout (>=2.1)"]
+
+[[package]]
 name = "frozenlist"
 version = "1.4.0"
 description = "A list-like structure which implements collections.abc.MutableSequence"
@@ -705,6 +723,41 @@ files = [
 ]
 
 [[package]]
+name = "fsspec"
+version = "2023.9.0"
+description = "File-system specification"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "fsspec-2023.9.0-py3-none-any.whl", hash = "sha256:d55b9ab2a4c1f2b759888ae9f93e40c2aa72c0808132e87e282b549f9e6c4254"},
+    {file = "fsspec-2023.9.0.tar.gz", hash = "sha256:4dbf0fefee035b7c6d3bbbe6bc99b2f201f40d4dca95b67c2b719be77bcd917f"},
+]
+
+[package.extras]
+abfs = ["adlfs"]
+adl = ["adlfs"]
+arrow = ["pyarrow (>=1)"]
+dask = ["dask", "distributed"]
+devel = ["pytest", "pytest-cov"]
+dropbox = ["dropbox", "dropboxdrivefs", "requests"]
+full = ["adlfs", "aiohttp (!=4.0.0a0,!=4.0.0a1)", "dask", "distributed", "dropbox", "dropboxdrivefs", "fusepy", "gcsfs", "libarchive-c", "ocifs", "panel", "paramiko", "pyarrow (>=1)", "pygit2", "requests", "s3fs", "smbprotocol", "tqdm"]
+fuse = ["fusepy"]
+gcs = ["gcsfs"]
+git = ["pygit2"]
+github = ["requests"]
+gs = ["gcsfs"]
+gui = ["panel"]
+hdfs = ["pyarrow (>=1)"]
+http = ["aiohttp (!=4.0.0a0,!=4.0.0a1)", "requests"]
+libarchive = ["libarchive-c"]
+oci = ["ocifs"]
+s3 = ["s3fs"]
+sftp = ["paramiko"]
+smb = ["smbprotocol"]
+ssh = ["paramiko"]
+tqdm = ["tqdm"]
+
+[[package]]
 name = "h11"
 version = "0.14.0"
 description = "A pure-Python, bring-your-own-I/O implementation of HTTP/1.1"
@@ -760,6 +813,38 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 
 [[package]]
+name = "huggingface-hub"
+version = "0.16.4"
+description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
+optional = false
+python-versions = ">=3.7.0"
+files = [
+    {file = "huggingface_hub-0.16.4-py3-none-any.whl", hash = "sha256:0d3df29932f334fead024afc7cb4cc5149d955238b8b5e42dcf9740d6995a349"},
+    {file = "huggingface_hub-0.16.4.tar.gz", hash = "sha256:608c7d4f3d368b326d1747f91523dbd1f692871e8e2e7a4750314a2dd8b63e14"},
+]
+
+[package.dependencies]
+filelock = "*"
+fsspec = "*"
+packaging = ">=20.9"
+pyyaml = ">=5.1"
+requests = "*"
+tqdm = ">=4.42.1"
+typing-extensions = ">=3.7.4.3"
+
+[package.extras]
+all = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (>=23.1,<24.0)", "gradio", "jedi", "mypy (==0.982)", "numpy", "pydantic", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)"]
+cli = ["InquirerPy (==0.3.4)"]
+dev = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "black (>=23.1,<24.0)", "gradio", "jedi", "mypy (==0.982)", "numpy", "pydantic", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "ruff (>=0.0.241)", "soundfile", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3", "urllib3 (<2.0)"]
+fastai = ["fastai (>=2.4)", "fastcore (>=1.3.27)", "toml"]
+inference = ["aiohttp", "pydantic"]
+quality = ["black (>=23.1,<24.0)", "mypy (==0.982)", "ruff (>=0.0.241)"]
+tensorflow = ["graphviz", "pydot", "tensorflow"]
+testing = ["InquirerPy (==0.3.4)", "Jinja2", "Pillow", "aiohttp", "gradio", "jedi", "numpy", "pydantic", "pytest", "pytest-asyncio", "pytest-cov", "pytest-env", "pytest-vcr", "pytest-xdist", "soundfile", "urllib3 (<2.0)"]
+torch = ["torch"]
+typing = ["pydantic", "types-PyYAML", "types-requests", "types-simplejson", "types-toml", "types-tqdm", "types-urllib3"]
+
+[[package]]
 name = "idna"
 version = "3.4"
 description = "Internationalized Domain Names in Applications (IDNA)"
@@ -1358,6 +1443,65 @@ websockets = ["websockets (>=10.3)"]
 yapf = ["whatthepatch (>=1.0.2,<2.0.0)", "yapf (>=0.33.0)"]
 
 [[package]]
+name = "pyyaml"
+version = "6.0.1"
+description = "YAML parser and emitter for Python"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "PyYAML-6.0.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:d858aa552c999bc8a8d57426ed01e40bef403cd8ccdd0fc5f6f04a00414cac2a"},
+    {file = "PyYAML-6.0.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:fd66fc5d0da6d9815ba2cebeb4205f95818ff4b79c3ebe268e75d961704af52f"},
+    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:69b023b2b4daa7548bcfbd4aa3da05b3a74b772db9e23b982788168117739938"},
+    {file = "PyYAML-6.0.1-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:81e0b275a9ecc9c0c0c07b4b90ba548307583c125f54d5b6946cfee6360c733d"},
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+    {file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
+    {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
+]
+
+[[package]]
 name = "redbaron"
 version = "0.9.2"
 description = "Abstraction on top of baron, a FST for python to make writing refactoring code a realistic task"
@@ -2267,4 +2411,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.8.1"
-content-hash = "d67290b217f5991c09c3073c8a97f8ffc5b51d69c7802db5f65462a029e5f99e"
+content-hash = "85e02897d3dd2c8b9bce7e15985eb7aecbd52c166478fceca445787fdde2d60b"
diff --git a/continuedev/pyproject.toml b/continuedev/pyproject.toml
index 134f9e16..d6cadfbc 100644
--- a/continuedev/pyproject.toml
+++ b/continuedev/pyproject.toml
@@ -33,6 +33,7 @@ bs4 = "^0.0.1"
 replicate = "^0.11.0"
 redbaron = "^0.9.2"
 python-lsp-server = "^1.7.4"
+huggingface-hub = "^0.16.4"
 
 [tool.poetry.scripts]
 typegen = "src.continuedev.models.generate_json_schema:main"
diff --git a/continuedev/requirements.txt b/continuedev/requirements.txt
index 91120c59..a689f085 100644
--- a/continuedev/requirements.txt
+++ b/continuedev/requirements.txt
@@ -23,4 +23,5 @@ ripgrepy==2.0.0
 replicate==0.11.0
 bs4==0.0.1
 redbaron==0.9.2
-python-lsp-server==1.2.0
\ No newline at end of file
+python-lsp-server==1.2.0
+huggingface-hub==0.16.4
\ No newline at end of file
diff --git a/continuedev/src/continuedev/core/models.py b/continuedev/src/continuedev/core/models.py
index 9816d5d9..f24c81ca 100644
--- a/continuedev/src/continuedev/core/models.py
+++ b/continuedev/src/continuedev/core/models.py
@@ -11,6 +11,7 @@ from ..libs.llm.ollama import Ollama
 from ..libs.llm.openai import OpenAI
 from ..libs.llm.replicate import ReplicateLLM
 from ..libs.llm.together import TogetherLLM
+from ..libs.llm.hf_inference_api import HuggingFaceInferenceAPI
 
 
 class ContinueSDK(BaseModel):
@@ -37,6 +38,7 @@ MODEL_CLASSES = {
         ReplicateLLM,
         Ollama,
         LlamaCpp,
+        HuggingFaceInferenceAPI,
     ]
 }
 
@@ -49,6 +51,7 @@ MODEL_MODULE_NAMES = {
     "ReplicateLLM": "replicate",
     "Ollama": "ollama",
     "LlamaCpp": "llamacpp",
+    "HuggingFaceInferenceAPI": "hf_inference_api",
 }
 
 
diff --git a/continuedev/src/continuedev/libs/llm/hf_inference_api.py b/continuedev/src/continuedev/libs/llm/hf_inference_api.py
index 43aac148..b8fc49a9 100644
--- a/continuedev/src/continuedev/libs/llm/hf_inference_api.py
+++ b/continuedev/src/continuedev/libs/llm/hf_inference_api.py
@@ -1,73 +1,53 @@
-from typing import List, Optional
+from typing import Callable, Dict, List
+from ..llm import LLM, CompletionOptions
 
-import aiohttp
-import requests
-
-from ...core.main import ChatMessage
-from ..llm import LLM
+from huggingface_hub import InferenceClient
+from .prompts.chat import llama2_template_messages
 from .prompts.edit import simplified_edit_prompt
 
-DEFAULT_MAX_TIME = 120.0
-
 
 class HuggingFaceInferenceAPI(LLM):
+    model: str = "Hugging Face Inference API"
     hf_token: str
-    self_hosted_url: str = None
-
-    verify_ssl: Optional[bool] = None
+    endpoint_url: str = None
 
-    _client_session: aiohttp.ClientSession = None
+    template_messages: Callable[[List[Dict[str, str]]], str] | None = llama2_template_messages
 
     prompt_templates = {
-        "edit": simplified_edit_prompt,
+       "edit": simplified_edit_prompt,
     }
 
     class Config:
         arbitrary_types_allowed = True
 
-    async def start(self, **kwargs):
-        await super().start(**kwargs)
-        self._client_session = aiohttp.ClientSession(
-            connector=aiohttp.TCPConnector(verify_ssl=self.verify_ssl),
-            timeout=aiohttp.ClientTimeout(total=self.timeout),
-        )
+    def collect_args(self, options: CompletionOptions):
+        options.stop = None
+        args = super().collect_args(options)
 
-    async def stop(self):
-        await self._client_session.close()
+        if "max_tokens" in args:
+            args["max_new_tokens"] = args["max_tokens"]
+            del args["max_tokens"]
+        if "stop" in args:
+            args["stop_sequences"] = args["stop"]
+            del args["stop"]
+        if "model" in args:
+            del args["model"]
+        return args
 
-    async def _complete(self, prompt: str, options):
-        """Return the completion of the text with the given temperature."""
-        API_URL = (
-            self.base_url or f"https://api-inference.huggingface.co/models/{self.model}"
-        )
-        headers = {"Authorization": f"Bearer {self.hf_token}"}
 
-        response = requests.post(
-            API_URL,
-            headers=headers,
-            json={
-                "inputs": prompt,
-                "parameters": {
-                    "max_new_tokens": min(
-                        250, self.max_context_length - self.count_tokens(prompt)
-                    ),
-                    "max_time": DEFAULT_MAX_TIME,
-                    "return_full_text": False,
-                },
-            },
-        )
-        data = response.json()
-
-        # Error if the response is not a list
-        if not isinstance(data, list):
-            raise Exception("Hugging Face returned an error response: \n\n", data)
+    async def _stream_complete(self, prompt, options):
+        args = self.collect_args(options)
 
-        return data[0]["generated_text"]
+        client = InferenceClient(self.endpoint_url, token=self.hf_token)
 
-    async def _stream_chat(self, messages: List[ChatMessage], options):
-        response = await self._complete(messages[-1].content, messages[:-1])
-        yield {"content": response, "role": "assistant"}
+        stream = client.text_generation(prompt, stream=True, details=True)
 
-    async def _stream_complete(self, prompt, options):
-        response = await self._complete(prompt, options)
-        yield response
+        for r in stream:
+            # skip special tokens
+            if r.token.special:
+                continue
+            # stop if we encounter a stop sequence
+            if options.stop is not None:
+                if r.token.text in options.stop:
+                    break
+            yield r.token.text
\ No newline at end of file
diff --git a/continuedev/src/continuedev/plugins/steps/setup_model.py b/continuedev/src/continuedev/plugins/steps/setup_model.py
index 3dae39c2..7fa34907 100644
--- a/continuedev/src/continuedev/plugins/steps/setup_model.py
+++ b/continuedev/src/continuedev/plugins/steps/setup_model.py
@@ -13,6 +13,7 @@ MODEL_CLASS_TO_MESSAGE = {
     "GGML": "GGML models can be run locally using the `llama-cpp-python` library. To learn how to set up a local llama-cpp-python server, read [here](https://github.com/continuedev/ggml-server-example). Once it is started on port 8000, you're all set!",
     "TogetherLLM": "To get started using models from Together, first obtain your Together API key from [here](https://together.ai). Paste it into the `api_key` field at config.models.default.api_key in `config.py`. Then, on their models page, press 'start' on the model of your choice and make sure the `model=` parameter in the config file for the `TogetherLLM` class reflects the name of this model. Finally, reload the VS Code window for changes to take effect.",
     "LlamaCpp": "To get started with this model, clone the [`llama.cpp` repo](https://github.com/ggerganov/llama.cpp) and follow the instructions to set up the server [here](https://github.com/ggerganov/llama.cpp/blob/master/examples/server/README.md#build). Any of the parameters described in the README can be passed to the `llama_cpp_args` field in the `LlamaCpp` class in `config.py`.",
+    "HuggingFaceInferenceAPI": "To get started with the HuggingFace Inference API, first deploy a model and obtain your API key from [here](https://huggingface.co/inference-api). Paste it into the `hf_token` field at config.models.default.hf_token in `config.py`. Finally, reload the VS Code window for changes to take effect."
 }
 
 
diff --git a/docs/docs/customization.md b/docs/docs/customization.md
index 5fc3eab5..fb7dc0c5 100644
--- a/docs/docs/customization.md
+++ b/docs/docs/customization.md
@@ -21,6 +21,7 @@ Open-Source Models (not local)
 
 - [TogetherLLM](#together) - Use any model from the [Together Models list](https://docs.together.ai/docs/models-inference) with your Together API key.
 - [ReplicateLLM](#replicate) - Use any open-source model from the [Replicate Streaming List](https://replicate.com/collections/streaming-language-models) with your Replicate API key.
+- [HuggingFaceInferenceAPI](#huggingface) - Use any open-source model from the [Hugging Face Inference API](https://huggingface.co/inference-api) with your Hugging Face token.
 
 ## Change the default LLM
 
@@ -206,6 +207,24 @@ config = ContinueConfig(
 
 If you don't specify the `model` parameter, it will default to `replicate/llama-2-70b-chat:58d078176e02c219e11eb4da5a02a7830a283b14cf8f94537af893ccff5ee781`.
 
+### Hugging Face
+
+Hugging Face Inference API is a great option for newly released language models. Sign up for an account and add billing [here](https://huggingface.co/settings/billing), access the Inference Endpoints [here](https://ui.endpoints.huggingface.co), click on “New endpoint”, and fill out the form (e.g. select a model like [WizardCoder-Python-34B-V1.0](https://huggingface.co/WizardLM/WizardCoder-Python-34B-V1.0)), and then deploy your model by clicking “Create Endpoint”. Change `~/.continue/config.py` to look like this:
+
+```python
+from continuedev.src.continuedev.core.models import Models
+from continuedev.src.continuedev.libs.llm.hf_inference_api import HuggingFaceInferenceAPI
+
+config = ContinueConfig(
+    ...
+    models=Models(
+        default=HuggingFaceInferenceAPI(
+            endpoint_url: "<INFERENCE_API_ENDPOINT_URL>", 
+            hf_token: "<HUGGING_FACE_TOKEN>",
+    )
+)
+```
+
 ### Self-hosting an open-source model
 
 If you want to self-host on Colab, RunPod, HuggingFace, Haven, or another hosting provider you will need to wire up a new LLM class. It only needs to implement 3 primary methods: `stream_complete`, `complete`, and `stream_chat`, and you can see examples in `continuedev/src/continuedev/libs/llm`.
diff --git a/extension/react-app/src/components/ModelSelect.tsx b/extension/react-app/src/components/ModelSelect.tsx
index e6c0e9c9..6a7692ff 100644
--- a/extension/react-app/src/components/ModelSelect.tsx
+++ b/extension/react-app/src/components/ModelSelect.tsx
@@ -60,6 +60,14 @@ const MODEL_INFO: { title: string; class: string; args: any }[] = [
     args: {},
   },
   {
+    title: "HuggingFace Inference API",
+    class: "HuggingFaceInferenceAPI",
+    args: {
+      endpoint_url: "<INFERENCE_API_ENDPOINT_URL>", 
+      hf_token: "<HUGGING_FACE_TOKEN>",
+    },
+  },
+  {
     title: "Other OpenAI-compatible API",
     class: "GGML",
     args: {