mirror of
https://github.com/hwchase17/langchain.git
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Added Hugging face inference api (#10280)
Embed documents without locally downloading the HF model --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
@@ -5,13 +5,23 @@
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"id": "ed47bb62",
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"metadata": {},
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"source": [
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"# Hugging Face Hub\n",
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"# Hugging Face\n",
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"Let's load the Hugging Face Embedding class."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": null,
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"id": "16b20335-da1d-46ba-aa23-fbf3e2c6fe60",
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"metadata": {},
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"outputs": [],
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"source": [
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"!pip install langchain sentence_transformers"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"id": "861521a9",
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"metadata": {},
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"outputs": [],
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@@ -21,7 +31,7 @@
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},
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"cell_type": "code",
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"execution_count": 16,
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"execution_count": 3,
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"id": "ff9be586",
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"metadata": {},
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"outputs": [],
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@@ -31,7 +41,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": 3,
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"id": "d0a98ae9",
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"metadata": {},
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"outputs": [],
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@@ -41,7 +51,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": 5,
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"id": "5d6c682b",
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"metadata": {},
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"outputs": [],
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@@ -51,7 +61,28 @@
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},
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{
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"cell_type": "code",
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"execution_count": 14,
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"execution_count": 6,
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"id": "b57b8ce9-ef7d-4e63-979e-aa8763d1f9a8",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[-0.04895168915390968, -0.03986193612217903, -0.021562768146395683]"
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]
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},
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"execution_count": 6,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"query_result[:3]"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"id": "bb5e74c0",
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"metadata": {},
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"outputs": [],
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@@ -60,19 +91,71 @@
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"id": "aaad49f8",
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"cell_type": "markdown",
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"id": "92019ef1-5d30-4985-b4e6-c0d98bdfe265",
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"metadata": {},
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"outputs": [],
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"source": []
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"source": [
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"## Hugging Face Inference API\n",
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"We can also access embedding models via the Hugging Face Inference API, which does not require us to install ``sentence_transformers`` and download models locally."
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]
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},
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{
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"cell_type": "code",
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"execution_count": 1,
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"id": "66f5c6ba-1446-43e1-b012-800d17cef300",
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"metadata": {},
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"outputs": [
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{
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"name": "stdin",
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"output_type": "stream",
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"text": [
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"Enter your HF Inference API Key:\n",
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"\n",
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" ········\n"
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]
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}
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],
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"source": [
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"import getpass\n",
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"\n",
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"inference_api_key = getpass.getpass(\"Enter your HF Inference API Key:\\n\\n\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": 4,
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"id": "d0623c1f-cd82-4862-9bce-3655cb9b66ac",
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"metadata": {},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"[-0.038338541984558105, 0.1234646737575531, -0.028642963618040085]"
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]
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},
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"execution_count": 4,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"from langchain.embeddings import HuggingFaceInferenceAPIEmbeddings\n",
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"\n",
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"embeddings = HuggingFaceInferenceAPIEmbeddings(\n",
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" api_key=inference_api_key,\n",
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" model_name=\"sentence-transformers/all-MiniLM-l6-v2\"\n",
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")\n",
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"\n",
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"query_result = embeddings.embed_query(text)\n",
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"query_result[:3]"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"display_name": "poetry-venv",
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"language": "python",
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"name": "python3"
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"name": "poetry-venv"
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},
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"language_info": {
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"codemirror_mode": {
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