langchain/docs/extras/modules/model_io/models/llms/integrations/octoai.ipynb
os1ma 2667ddc686
Fix make docs_build and related scripts (#7276)
**Description: a description of the change**

Fixed `make docs_build` and related scripts which caused errors. There
are several changes.

First, I made the build of the documentation and the API Reference into
two separate commands. This is because it takes less time to build. The
commands for documents are `make docs_build`, `make docs_clean`, and
`make docs_linkcheck`. The commands for API Reference are `make
api_docs_build`, `api_docs_clean`, and `api_docs_linkcheck`.

It looked like `docs/.local_build.sh` could be used to build the
documentation, so I used that. Since `.local_build.sh` was also building
API Rerefence internally, I removed that process. `.local_build.sh` also
added some Bash options to stop in error or so. Futher more added `cd
"${SCRIPT_DIR}"` at the beginning so that the script will work no matter
which directory it is executed in.

`docs/api_reference/api_reference.rst` is removed, because which is
generated by `docs/api_reference/create_api_rst.py`, and added it to
.gitignore.

Finally, the description of CONTRIBUTING.md was modified.

**Issue: the issue # it fixes (if applicable)**

https://github.com/hwchase17/langchain/issues/6413

**Dependencies: any dependencies required for this change**

`nbdoc` was missing in group docs so it was added. I installed it with
the `poetry add --group docs nbdoc` command. I am concerned if any
modifications are needed to poetry.lock. I would greatly appreciate it
if you could pay close attention to this file during the review.

**Tag maintainer**
- General / Misc / if you don't know who to tag: @baskaryan

If this PR needs any additional changes, I'll be happy to make them!

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-07-11 22:05:14 -04:00

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{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"## OctoAI Compute Service\n",
"This example goes over how to use LangChain to interact with `OctoAI` [LLM endpoints](https://octoai.cloud/templates)\n",
"## Environment setup\n",
"\n",
"To run our example app, there are four simple steps to take:\n",
"\n",
"1. Clone the MPT-7B demo template to your OctoAI account by visiting <https://octoai.cloud/templates/mpt-7b-demo> then clicking \"Clone Template.\" \n",
" 1. If you want to use a different LLM model, you can also containerize the model and make a custom OctoAI endpoint yourself, by following [Build a Container from Python](doc:create-custom-endpoints-from-python-code) and [Create a Custom Endpoint from a Container](doc:create-custom-endpoints-from-a-container)\n",
" \n",
"2. Paste your Endpoint URL in the code cell below\n",
"\n",
"3. Get an API Token from [your OctoAI account page](https://octoai.cloud/settings).\n",
" \n",
"4. Paste your API key in in the code cell below"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {},
"outputs": [],
"source": [
"import os\n",
"\n",
"os.environ[\"OCTOAI_API_TOKEN\"] = \"OCTOAI_API_TOKEN\"\n",
"os.environ[\"ENDPOINT_URL\"] = \"https://mpt-7b-demo-kk0powt97tmb.octoai.cloud/generate\""
]
},
{
"cell_type": "code",
"execution_count": 14,
"metadata": {},
"outputs": [],
"source": [
"from langchain.llms.octoai_endpoint import OctoAIEndpoint\n",
"from langchain import PromptTemplate, LLMChain"
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {},
"outputs": [],
"source": [
"template = \"\"\"Below is an instruction that describes a task. Write a response that appropriately completes the request.\\n Instruction:\\n{question}\\n Response: \"\"\"\n",
"prompt = PromptTemplate(template=template, input_variables=[\"question\"])"
]
},
{
"cell_type": "code",
"execution_count": 30,
"metadata": {},
"outputs": [],
"source": [
"llm = OctoAIEndpoint(\n",
" model_kwargs={\n",
" \"max_new_tokens\": 200,\n",
" \"temperature\": 0.75,\n",
" \"top_p\": 0.95,\n",
" \"repetition_penalty\": 1,\n",
" \"seed\": None,\n",
" \"stop\": [],\n",
" },\n",
")"
]
},
{
"cell_type": "code",
"execution_count": 31,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"'\\nLeonardo da Vinci was an Italian polymath and painter regarded by many as one of the greatest painters of all time. He is best known for his masterpieces including Mona Lisa, The Last Supper, and The Virgin of the Rocks. He was a draftsman, sculptor, architect, and one of the most important figures in the history of science. Da Vinci flew gliders, experimented with water turbines and windmills, and invented the catapult and a joystick-type human-powered aircraft control. He may have pioneered helicopters. As a scholar, he was interested in anatomy, geology, botany, engineering, mathematics, and astronomy.\\nOther painters and patrons claimed to be more talented, but Leonardo da Vinci was an incredibly productive artist, sculptor, engineer, anatomist, and scientist.'"
]
},
"execution_count": 31,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"question = \"Who was leonardo davinci?\"\n",
"\n",
"llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
"\n",
"llm_chain.run(question)"
]
}
],
"metadata": {
"kernelspec": {
"display_name": "langchain",
"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": "3.9.16"
},
"orig_nbformat": 4,
"vscode": {
"interpreter": {
"hash": "97697b63fdcee0a640856f91cb41326ad601964008c341809e43189d1cab1047"
}
}
},
"nbformat": 4,
"nbformat_minor": 2
}