mirror of
https://github.com/hwchase17/langchain.git
synced 2025-09-06 13:33:37 +00:00
langchain[minor]: Adding infinity embedding integration. (#13928)
This adds integation to https://github.com/michaelfeil/infinity. Users requested it in https://github.com/michaelfeil/infinity/issues/36 @saatvikshah Follows my implementation of gradient.ai. Feedback 1: Well done - I love your CI / repo / poetry setup - I adapted a lot in https://github.com/michaelfeil/infinity. Feedback 2: Not so good: The openai integration contains to much reverse engineering - in general projects such as michaelfeil/infinity and huggingface/text-embeddings-inference are compatible to the `pip install openai` package. Reverse engineering like this one is really hindering the use for me:8e88ba16a8/libs/langchain/langchain/embeddings/openai.py (L347)8e88ba16a8/libs/langchain/langchain/embeddings/openai.py (L351)- it is about preventing 3rd party providers to use the same url + uses interfaces of openai, that are not publically documented.
This commit is contained in:
Michael Feil
GitHub
11
docs/docs/integrations/providers/infinity.mdx
Normal file
11
docs/docs/integrations/providers/infinity.mdx
Normal file
@@ -0,0 +1,11 @@
|
||||
# Infinity
|
||||
|
||||
>[Infinity](https://github.com/michaelfeil/infinity) allows the creation of text embeddings.
|
||||
|
||||
## Text Embedding Model
|
||||
|
||||
There exists an infinity Embedding model, which you can access with
|
||||
```python
|
||||
from langchain.embeddings import InfinityEmbeddings
|
||||
```
|
||||
For a more detailed walkthrough of this, see [this notebook](/docs/integrations/text_embedding/infinity)
|
||||
191
docs/docs/integrations/text_embedding/infinity.ipynb
Normal file
191
docs/docs/integrations/text_embedding/infinity.ipynb
Normal file
@@ -0,0 +1,191 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Infinity\n",
|
||||
"\n",
|
||||
"`Infinity` allows to create `Embeddings` using a MIT-licensed Embedding Server. \n",
|
||||
"\n",
|
||||
"This notebook goes over how to use Langchain with Embeddings with the [Infinity Github Project](https://github.com/michaelfeil/infinity).\n"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Imports"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 1,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain.embeddings import InfinityEmbeddings"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Optional: Make sure to start the Infinity instance\n",
|
||||
"\n",
|
||||
"To install infinity use the following command. For further details check out the [Docs on Github](https://github.com/michaelfeil/infinity).\n",
|
||||
"```bash\n",
|
||||
"pip install infinity_emb[all]\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 6,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"Requirement already satisfied: infinity_emb[cli] in /home/michi/langchain/.venv/lib/python3.10/site-packages (0.0.8)\n",
|
||||
"\u001b[33mWARNING: infinity-emb 0.0.8 does not provide the extra 'cli'\u001b[0m\u001b[33m\n",
|
||||
"\u001b[0mRequirement already satisfied: numpy>=1.20.0 in /home/michi/langchain/.venv/lib/python3.10/site-packages (from infinity_emb[cli]) (1.24.4)\n",
|
||||
"\u001b[33mWARNING: There was an error checking the latest version of pip.\u001b[0m\u001b[33m\n",
|
||||
"\u001b[0m"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# Install the infinity package\n",
|
||||
"!pip install infinity_emb[cli,torch]"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"Start up the server - best to be done from a separate terminal, not inside Jupyter Notebook\n",
|
||||
"\n",
|
||||
"```bash\n",
|
||||
"model=sentence-transformers/all-MiniLM-L6-v2\n",
|
||||
"port=7797\n",
|
||||
"infinity_emb --port $port --model-name-or-path $model\n",
|
||||
"```\n",
|
||||
"\n",
|
||||
"or alternativley just use docker:\n",
|
||||
"```bash\n",
|
||||
"model=sentence-transformers/all-MiniLM-L6-v2\n",
|
||||
"port=7797\n",
|
||||
"docker run -it --gpus all -p $port:$port michaelf34/infinity:latest --model-name-or-path $model --port $port\n",
|
||||
"```"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Embed your documents using your Infinity instance "
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"documents = [\n",
|
||||
" \"Baguette is a dish.\",\n",
|
||||
" \"Paris is the capital of France.\",\n",
|
||||
" \"numpy is a lib for linear algebra\",\n",
|
||||
" \"You escaped what I've escaped - You'd be in Paris getting fucked up too\",\n",
|
||||
"]\n",
|
||||
"query = \"Where is Paris?\""
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"name": "stdout",
|
||||
"output_type": "stream",
|
||||
"text": [
|
||||
"embeddings created successful\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"#\n",
|
||||
"infinity_api_url = \"http://localhost:7797/v1\"\n",
|
||||
"# model is currently not validated.\n",
|
||||
"embeddings = InfinityEmbeddings(\n",
|
||||
" model=\"sentence-transformers/all-MiniLM-L6-v2\", infinity_api_url=infinity_api_url\n",
|
||||
")\n",
|
||||
"try:\n",
|
||||
" documents_embedded = embeddings.embed_documents(documents)\n",
|
||||
" query_result = embeddings.embed_query(query)\n",
|
||||
" print(\"embeddings created successful\")\n",
|
||||
"except Exception as ex:\n",
|
||||
" print(\n",
|
||||
" \"Make sure the infinity instance is running. Verify by clicking on \"\n",
|
||||
" f\"{infinity_api_url.replace('v1','docs')} Exception: {ex}. \"\n",
|
||||
" )"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"outputs": [
|
||||
{
|
||||
"data": {
|
||||
"text/plain": [
|
||||
"{'Baguette is a dish.': 0.31344215908661155,\n",
|
||||
" 'Paris is the capital of France.': 0.8148670296896388,\n",
|
||||
" 'numpy is a lib for linear algebra': 0.004429399861302009,\n",
|
||||
" \"You escaped what I've escaped - You'd be in Paris getting fucked up too\": 0.5088476180154582}"
|
||||
]
|
||||
},
|
||||
"execution_count": 5,
|
||||
"metadata": {},
|
||||
"output_type": "execute_result"
|
||||
}
|
||||
],
|
||||
"source": [
|
||||
"# (demo) compute similarity\n",
|
||||
"import numpy as np\n",
|
||||
"\n",
|
||||
"scores = np.array(documents_embedded) @ np.array(query_result).T\n",
|
||||
"dict(zip(documents, scores))"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3 (ipykernel)",
|
||||
"language": "python",
|
||||
"name": "python3"
|
||||
},
|
||||
"language_info": {
|
||||
"codemirror_mode": {
|
||||
"name": "ipython",
|
||||
"version": 3
|
||||
},
|
||||
"file_extension": ".py",
|
||||
"mimetype": "text/x-python",
|
||||
"name": "python",
|
||||
"nbconvert_exporter": "python",
|
||||
"pygments_lexer": "ipython3",
|
||||
"version": "3.10.12"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "a0a0263b650d907a3bfe41c0f8d6a63a071b884df3cfdc1579f00cdc1aed6b03"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 4
|
||||
}
|
||||
Reference in New Issue
Block a user