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https://github.com/hwchase17/langchain
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docs: standardize Together docs (#24617)
Part of #22296 --------- Co-authored-by: isaac hershenson <ihershenson@hmc.edu>
This commit is contained in:
Bagatur
GitHub
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{
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"cells": [
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{
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"cell_type": "markdown",
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"id": "2970dd75-8ebf-4b51-8282-9b454b8f356d",
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"cell_type": "raw",
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"id": "afaf8039",
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"metadata": {},
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"source": [
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"# Together AI\n",
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"\n",
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"[Together AI](https://www.together.ai/) offers an API to query [50+ leading open-source models](https://docs.together.ai/docs/inference-models) in a couple lines of code.\n",
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"\n",
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"This example goes over how to use LangChain to interact with Together AI models."
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"---\n",
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"sidebar_label: Together\n",
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"---"
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]
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},
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{
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"cell_type": "markdown",
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"id": "1c47fc36",
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"id": "e49f1e0d",
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"metadata": {},
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"source": [
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"## Installation"
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"# ChatTogether\n",
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"\n",
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"\n",
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"This page will help you get started with Together AI [chat models](../../concepts.mdx#chat-models). For detailed documentation of all ChatTogether features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/langchain_together.chat_models.ChatTogether.html).\n",
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"\n",
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"[Together AI](https://www.together.ai/) offers an API to query [50+ leading open-source models](https://docs.together.ai/docs/chat-models)\n",
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"\n",
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"## Overview\n",
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"### Integration details\n",
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"\n",
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"| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/v0.2/docs/integrations/chat/togetherai) | Package downloads | Package latest |\n",
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"| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
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"| [ChatTogether](https://api.python.langchain.com/en/latest/chat_models/langchain_together.chat_models.ChatTogether.html) | [langchain-together](https://api.python.langchain.com/en/latest/together_api_reference.html) | ❌ | beta | ✅ |  |  |\n",
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"\n",
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"### Model features\n",
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"| [Tool calling](../../how_to/tool_calling.ipynb) | [Structured output](../../how_to/structured_output.ipynb) | JSON mode | [Image input](../../how_to/multimodal_inputs.ipynb) | Audio input | Video input | [Token-level streaming](../../how_to/chat_streaming.ipynb) | Native async | [Token usage](../../how_to/chat_token_usage_tracking.ipynb) | [Logprobs](../../how_to/logprobs.ipynb) |\n",
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"| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n",
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"| ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ✅ | ❌ | ✅ | ✅ | \n",
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"\n",
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"## Setup\n",
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"\n",
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"To access Together models you'll need to create a/an Together account, get an API key, and install the `langchain-together` integration package.\n",
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"\n",
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"### Credentials\n",
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"\n",
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"Head to [this page](https://api.together.ai) to sign up to Together and generate an API key. Once you've done this set the TOGETHER_API_KEY environment variable:"
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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": "1ecdb29d",
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"execution_count": 1,
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"id": "433e8d2b-9519-4b49-b2c4-7ab65b046c94",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install --upgrade langchain-together"
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]
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},
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{
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"cell_type": "markdown",
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"id": "89883202",
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"metadata": {},
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"source": [
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"## Environment\n",
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"import getpass\n",
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"import os\n",
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"\n",
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"To use Together AI, you'll need an API key which you can find here:\n",
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"https://api.together.ai/settings/api-keys. This can be passed in as an init param\n",
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"``together_api_key`` or set as environment variable ``TOGETHER_API_KEY``.\n"
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"os.environ[\"TOGETHER_API_KEY\"] = getpass.getpass(\"Enter your Together API key: \")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "8304b4d9",
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"id": "72ee0c4b-9764-423a-9dbf-95129e185210",
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"metadata": {},
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"source": [
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"## Example"
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"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:"
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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": "637bb53f",
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"execution_count": 2,
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"id": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
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"metadata": {},
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"outputs": [],
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"source": [
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"# Querying chat models with Together AI\n",
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"# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith API key: \")\n",
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"# os.environ[\"LANGSMITH_TRACING\"] = \"true\""
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]
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},
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{
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"cell_type": "markdown",
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"id": "0730d6a1-c893-4840-9817-5e5251676d5d",
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"metadata": {},
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"source": [
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"### Installation\n",
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"\n",
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"The LangChain Together integration lives in the `langchain-together` package:"
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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": 3,
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"id": "652d6238-1f87-422a-b135-f5abbb8652fc",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"\n",
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"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m24.0\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m24.1.2\u001b[0m\n",
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"\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n",
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"Note: you may need to restart the kernel to use updated packages.\n"
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]
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}
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],
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"source": [
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"%pip install -qU langchain-together"
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]
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},
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{
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"cell_type": "markdown",
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"id": "a38cde65-254d-4219-a441-068766c0d4b5",
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"metadata": {},
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"source": [
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"## Instantiation\n",
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"\n",
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"Now we can instantiate our model object and generate chat completions:\n",
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"\n",
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"- TODO: Update model instantiation with relevant params."
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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": 5,
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"id": "cb09c344-1836-4e0c-acf8-11d13ac1dbae",
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_together import ChatTogether\n",
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"\n",
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"# choose from our 50+ models here: https://docs.together.ai/docs/inference-models\n",
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"chat = ChatTogether(\n",
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" # together_api_key=\"YOUR_API_KEY\",\n",
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"llm = ChatTogether(\n",
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" model=\"meta-llama/Llama-3-70b-chat-hf\",\n",
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")\n",
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"\n",
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"# stream the response back from the model\n",
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"for m in chat.stream(\"Tell me fun things to do in NYC\"):\n",
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" print(m.content, end=\"\", flush=True)\n",
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"\n",
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"# if you don't want to do streaming, you can use the invoke method\n",
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"# chat.invoke(\"Tell me fun things to do in NYC\")"
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" temperature=0,\n",
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" max_tokens=None,\n",
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" timeout=None,\n",
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" max_retries=2,\n",
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" # other params...\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "2b4f3e15",
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"metadata": {},
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"source": [
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"## Invocation"
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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": "e7b7170d-d7c5-4890-9714-a37238343805",
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"metadata": {},
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"outputs": [],
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"execution_count": 6,
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"id": "62e0dbc3",
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"metadata": {
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"tags": []
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},
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"outputs": [
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{
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"data": {
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"text/plain": [
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"AIMessage(content=\"J'adore la programmation.\", response_metadata={'token_usage': {'completion_tokens': 9, 'prompt_tokens': 35, 'total_tokens': 44}, 'model_name': 'meta-llama/Llama-3-70b-chat-hf', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-79efa49b-dbaf-4ef8-9dce-958533823ef6-0', usage_metadata={'input_tokens': 35, 'output_tokens': 9, 'total_tokens': 44})"
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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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"# Querying code and language models with Together AI\n",
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"messages = [\n",
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" (\n",
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" \"system\",\n",
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" \"You are a helpful assistant that translates English to French. Translate the user sentence.\",\n",
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" ),\n",
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" (\"human\", \"I love programming.\"),\n",
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"]\n",
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"ai_msg = llm.invoke(messages)\n",
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"ai_msg"
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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": "d86145b3-bfef-46e8-b227-4dda5c9c2705",
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"J'adore la programmation.\n"
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]
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}
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],
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"source": [
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"print(ai_msg.content)"
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]
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},
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{
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"cell_type": "markdown",
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"id": "18e2bfc0-7e78-4528-a73f-499ac150dca8",
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"metadata": {},
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"source": [
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"## Chaining\n",
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"\n",
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"from langchain_together import Together\n",
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"We can [chain](../../how_to/sequence.ipynb) our model with a prompt template like so:"
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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": 8,
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"id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
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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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"AIMessage(content='Ich liebe das Programmieren.', response_metadata={'token_usage': {'completion_tokens': 7, 'prompt_tokens': 30, 'total_tokens': 37}, 'model_name': 'meta-llama/Llama-3-70b-chat-hf', 'system_fingerprint': None, 'finish_reason': 'stop', 'logprobs': None}, id='run-80bba5fa-1723-4242-8d5a-c09b76b8350b-0', usage_metadata={'input_tokens': 30, 'output_tokens': 7, 'total_tokens': 37})"
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]
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},
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"execution_count": 8,
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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_core.prompts import ChatPromptTemplate\n",
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"\n",
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"llm = Together(\n",
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" model=\"codellama/CodeLlama-70b-Python-hf\",\n",
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" # together_api_key=\"...\"\n",
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"prompt = ChatPromptTemplate.from_messages(\n",
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" [\n",
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" (\n",
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" \"system\",\n",
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" \"You are a helpful assistant that translates {input_language} to {output_language}.\",\n",
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" ),\n",
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" (\"human\", \"{input}\"),\n",
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" ]\n",
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")\n",
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"\n",
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"print(llm.invoke(\"def bubble_sort(): \"))"
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"chain = prompt | llm\n",
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"chain.invoke(\n",
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" {\n",
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" \"input_language\": \"English\",\n",
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" \"output_language\": \"German\",\n",
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" \"input\": \"I love programming.\",\n",
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" }\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"id": "3a5bb5ca-c3ae-4a58-be67-2cd18574b9a3",
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"metadata": {},
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"source": [
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"## API reference\n",
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"\n",
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"For detailed documentation of all ChatTogether features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/langchain_together.chat_models.ChatTogether.html"
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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": ".venv",
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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@ -111,7 +271,7 @@
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.11.4"
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"version": "3.11.9"
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}
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},
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"nbformat": 4,
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