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docs: moving FireworksEmbeddings documentation to docs folder (#19398)
**Description:** Moving FireworksEmbeddings documentation to the location docs/integration/text_embedding/ from langchain_fireworks/docs/ **Issue:** FireworksEmbeddings documentation was not in the correct location **Dependencies:** None --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"id": "b14a24db", | ||
"metadata": {}, | ||
"source": [ | ||
"# FireworksEmbeddings\n", | ||
"\n", | ||
"This notebook explains how to use Fireworks Embeddings, which is included in the langchain_fireworks package, to embed texts in langchain. We use the default nomic-ai v1.5 model in this example." | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"id": "0ab948fc", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"%pip install -qU langchain-fireworks" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "67c637ca", | ||
"metadata": {}, | ||
"source": [ | ||
"## Setup" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 1, | ||
"id": "5709b030", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"from langchain_fireworks import FireworksEmbeddings" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 2, | ||
"id": "3d81e58c", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"import getpass\n", | ||
"import os\n", | ||
"\n", | ||
"if \"FIREWORKS_API_KEY\" not in os.environ:\n", | ||
" os.environ[\"FIREWORKS_API_KEY\"] = getpass.getpass(\"Fireworks API Key:\")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"id": "4a2a098d", | ||
"metadata": {}, | ||
"source": [ | ||
"# Using the Embedding Model\n", | ||
"With `FireworksEmbeddings`, you can directly use the default model 'nomic-ai/nomic-embed-text-v1.5', or set a different one if available." | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 3, | ||
"id": "584b9af5", | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"embedding = FireworksEmbeddings(mode=\"nomic-ai/nomic-embed-text-v1.5\")" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": 4, | ||
"id": "be18b873", | ||
"metadata": {}, | ||
"outputs": [ | ||
{ | ||
"name": "stdout", | ||
"output_type": "stream", | ||
"text": [ | ||
"[0.01367950439453125, 0.0103607177734375, -0.157958984375, -0.003070831298828125, 0.05926513671875]\n", | ||
"[0.0369873046875, 0.00545501708984375, -0.179931640625, -0.018707275390625, 0.0552978515625]\n" | ||
] | ||
} | ||
], | ||
"source": [ | ||
"res_query = embedding.embed_query(\"The test information\")\n", | ||
"res_document = embedding.embed_documents([\"test1\", \"another test\"])\n", | ||
"print(res_query[:5])\n", | ||
"print(res_document[1][:5])" | ||
] | ||
} | ||
], | ||
"metadata": { | ||
"kernelspec": { | ||
"display_name": "poetry-venv-2", | ||
"language": "python", | ||
"name": "poetry-venv-2" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.9.1" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 5 | ||
} |
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