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Fix ibm community (#12)
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Provide solutions for:

- LLMs
- embeddings
- tests

* Fix docs, dependencies and minor changes to code
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@FilipZmijewski
FilipZmijewski committed Oct 8, 2024
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362 changes: 362 additions & 0 deletions docs/core_docs/docs/integrations/llms/ibm.ipynb
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{
"cells": [
{
"cell_type": "raw",
"id": "67db2992",
"metadata": {
"vscode": {
"languageId": "raw"
}
},
"source": [
"---\n",
"sidebar_label: IBM watsonx.ai\n",
"---"
]
},
{
"cell_type": "markdown",
"id": "9597802c",
"metadata": {},
"source": [
"# IBM watsonx.ai\n",
"\n",
"\n",
"This will help you get started with IBM [text completion models (LLMs)](/docs/concepts#llms) using LangChain. For detailed documentation on `IBM watsonx.ai` features and configuration options, please refer to the [IBM watsonx.ai](https://api.js.langchain.com/classes/_langchain_community.llms_ibm.html).\n",
"\n",
"## Overview\n",
"### Integration details\n",
"\n",
"\n",
"| Class | Package | Local | Serializable | [PY support](https://python.langchain.com/docs/integrations/llms/ibm_watsonx/) | Package downloads | Package latest |\n",
"| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
"| [`IBM watsonx.ai`](https://api.js.langchain.com/modules/_langchain_community.llms_ibm.html) | [@langchain/community](https://api.js.langchain.com/modules/langchain_community_llms_ibm.html) | ❌ | ✅ | ✅ | ![NPM - Downloads](https://img.shields.io/npm/dm/@langchain/community?style=flat-square&label=%20&) | ![NPM - Version](https://img.shields.io/npm/v/@langchain/community?style=flat-square&label=%20&) |\n",
"\n",
"## Setup\n",
"\n",
"\n",
"To access IBM WatsonxAI models you'll need to create an IBM watsonx.ai account, get an API key or any other type of credentials, and install the `@langchain/community` integration package.\n",
"\n",
"### Credentials\n",
"\n",
"\n",
"Head to [IBM Cloud](https://cloud.ibm.com/login) to sign up to IBM watsonx.ai and generate an API key or provide any other authentication form as presented below.\n",
"\n",
"#### IAM authentication\n",
"\n",
"```bash\n",
"export WATSONX_AI_AUTH_TYPE=iam\n",
"export WATSONX_AI_APIKEY=<YOUR-APIKEY>\n",
"```\n",
"\n",
"#### Bearer token authentication\n",
"\n",
"```bash\n",
"export WATSONX_AI_AUTH_TYPE=bearertoken\n",
"export WATSONX_AI_BEARER_TOKEN=<YOUR-BEARER-TOKEN>\n",
"```\n",
"\n",
"#### CP4D authentication\n",
"\n",
"```bash\n",
"export WATSONX_AI_AUTH_TYPE=cp4d\n",
"export WATSONX_AI_USERNAME=<YOUR_USERNAME>\n",
"export WATSONX_AI_PASSWORD=<YOUR_PASSWORD>\n",
"export WATSONX_AI_URL=<URL>\n",
"```\n",
"\n",
"Once these are places in your enviromental variables and object is initialized authentication will proceed automatically.\n",
"\n",
"Authentication can also be accomplished by passing these values as parameters to a new instance.\n",
"\n",
"## IAM authentication\n",
"\n",
"```typescript\n",
"import { WatsonxLLM } from \"@langchain/community/llms/ibm\";\n",
"\n",
"const props = {\n",
" version: \"YYYY-MM-DD\",\n",
" serviceUrl: \"<SERVICE_URL>\",\n",
" projectId: \"<PROJECT_ID>\",\n",
" watsonxAIAuthType: \"iam\",\n",
" watsonxAIApikey: \"<YOUR-APIKEY>\",\n",
"};\n",
"const instance = new WatsonxLLM(props);\n",
"```\n",
"\n",
"## Bearer token authentication\n",
"\n",
"```typescript\n",
"import { WatsonxLLM } from \"@langchain/community/llms/ibm\";\n",
"\n",
"const props = {\n",
" version: \"YYYY-MM-DD\",\n",
" serviceUrl: \"<SERVICE_URL>\",\n",
" projectId: \"<PROJECT_ID>\",\n",
" watsonxAIAuthType: \"bearertoken\",\n",
" watsonxAIBearerToken: \"<YOUR-BEARERTOKEN>\",\n",
"};\n",
"const instance = new WatsonxLLM(props);\n",
"```\n",
"\n",
"### CP4D authentication\n",
"\n",
"```typescript\n",
"import { WatsonxLLM } from \"@langchain/community/llms/ibm\";\n",
"\n",
"const props = {\n",
" version: \"YYYY-MM-DD\",\n",
" serviceUrl: \"<SERVICE_URL>\",\n",
" projectId: \"<PROJECT_ID>\",\n",
" watsonxAIAuthType: \"cp4d\",\n",
" watsonxAIUsername: \"<YOUR-USERNAME>\",\n",
" watsonxAIPassword: \"<YOUR-PASSWORD>\",\n",
" watsonxAIUrl: \"<url>\",\n",
"};\n",
"const instance = new WatsonxLLM(props);\n",
"```\n",
"\n",
"If you want to get automated tracing of your model calls you can also set your [LangSmith](https://docs.smith.langchain.com/) API key by uncommenting below:\n",
"\n",
"```bash\n",
"# export LANGCHAIN_TRACING_V2=\"true\"\n",
"# export LANGCHAIN_API_KEY=\"your-api-key\"\n",
"```\n",
"\n",
"### Installation\n",
"\n",
"The LangChain IBM watsonx.ai integration lives in the `@langchain/community` package:\n",
"\n",
"```{=mdx}\n",
"import IntegrationInstallTooltip from \"@mdx_components/integration_install_tooltip.mdx\";\n",
"import Npm2Yarn from \"@theme/Npm2Yarn\";\n",
"\n",
"<IntegrationInstallTooltip></IntegrationInstallTooltip>\n",
"\n",
"<Npm2Yarn>\n",
" @langchain/community @langchain/core\n",
"</Npm2Yarn>\n",
"\n",
"```"
]
},
{
"cell_type": "markdown",
"id": "0a760037",
"metadata": {},
"source": [
"## Instantiation\n",
"\n",
"Now we can instantiate our model object and generate chat completions:\n"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "a0562a13",
"metadata": {},
"outputs": [],
"source": [
"import { WatsonxLLM } from \"@langchain/community/llms/ibm\";\n",
"\n",
"const props = {\n",
" decoding_method: \"sample\",\n",
" max_new_tokens: 100,\n",
" min_new_tokens: 1,\n",
" temperature: 0.5,\n",
" top_k: 50,\n",
" top_p: 1,\n",
"};\n",
"const instance = new WatsonxLLM({\n",
" version: \"YYYY-MM-DD\",\n",
" serviceUrl: process.env.API_URL,\n",
" projectId: \"<PROJECT_ID>\",\n",
" spaceId: \"<SPACE_ID>\",\n",
" idOrName: \"<DEPLOYMENT_ID>\",\n",
" modelId: \"<MODEL_ID>\",\n",
" ...props,\n",
"});"
]
},
{
"cell_type": "markdown",
"id": "f7498103",
"metadata": {},
"source": [
"Note:\n",
"\n",
"- You must provide spaceId, projectId or idOrName(deployment id) in order to proceed.\n",
"- Depending on the region of your provisioned service instance, use correct serviceUrl.\n",
"- You need to specify the model you want to use for inferencing through model_id."
]
},
{
"cell_type": "markdown",
"id": "0ee90032",
"metadata": {},
"source": [
"## Invocation and generation\n"
]
},
{
"cell_type": "code",
"execution_count": 4,
"id": "035dea0f",
"metadata": {
"tags": []
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"print('Hello world.')<|endoftext|>\n",
"{\n",
" generations: [ [ [Object] ], [ [Object] ] ],\n",
" llmOutput: { tokenUsage: { generated_token_count: 28, input_token_count: 10 } }\n",
"}\n"
]
}
],
"source": [
"const result = await instance.invoke(\"Print hello world.\");\n",
"console.log(result);\n",
"\n",
"const results = await instance.generate([\n",
" \"Print hello world.\",\n",
" \"Print bye, bye world!\",\n",
"]);\n",
"console.log(results);"
]
},
{
"cell_type": "markdown",
"id": "add38532",
"metadata": {},
"source": [
"## Chaining\n",
"\n",
"We can chain our completion model with a prompt template like so:"
]
},
{
"cell_type": "code",
"execution_count": 6,
"id": "078e9db2",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Ich liebe Programmieren.\n",
"\n",
"To express that you are passionate about programming in German,\n"
]
}
],
"source": [
"import { PromptTemplate } from \"@langchain/core/prompts\"\n",
"\n",
"const prompt = PromptTemplate.fromTemplate(\"How to say {input} in {output_language}:\\n\")\n",
"\n",
"const chain = prompt.pipe(instance);\n",
"await chain.invoke(\n",
" {\n",
" output_language: \"German\",\n",
" input: \"I love programming.\",\n",
" }\n",
")"
]
},
{
"cell_type": "markdown",
"id": "0c305670",
"metadata": {},
"source": [
"## Props overwrittion\n",
"\n",
"Passed props at initialization will last for the whole life cycle of the object, however you may overwrite them for a single method's call by passing second argument as below\n"
]
},
{
"cell_type": "code",
"execution_count": 9,
"id": "bb53235c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"print('Hello world.')<|endoftext|>\n"
]
}
],
"source": [
"const result = await instance.invoke(\"Print hello world.\", {\n",
" modelId: \"<NEW_MODEL_ID>\",\n",
" parameters: {\n",
" max_new_tokens: 20,\n",
" },\n",
" });\n",
" console.log(result);"
]
},
{
"cell_type": "markdown",
"id": "577a0583",
"metadata": {},
"source": [
"## Tokenization\n",
"This package has it's custom getNumTokens implementation which returns exact amount of tokens that would be used.\n"
]
},
{
"cell_type": "code",
"execution_count": 10,
"id": "339e237c",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"4\n"
]
}
],
"source": [
"const tokens = await instance.getNumTokens(\"Print hello world.\");\n",
"console.log(tokens);"
]
},
{
"cell_type": "markdown",
"id": "e9bdfcef",
"metadata": {},
"source": [
"## API reference\n",
"\n",
"For detailed documentation of all `IBM watsonx.ai` features and configurations head to the API reference: [API docs](https://api.js.langchain.com/modules/_langchain_community.embeddings_ibm.html)"
]
}
],
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