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Feature/chat deployment (#40)
* Rename auth method in docs * fix(core): Fix trim messages mutation bug (langchain-ai#7547) * release(core): 0.3.31 (langchain-ai#7548) * fix(community): Updated Embeddings URL (langchain-ai#7545) * fix(community): make sure guardrailConfig can be added even with anthropic models (langchain-ai#7542) * docs: Fix PGVectorStore import in install dependencies (TypeScript) example (langchain-ai#7533) * fix(community): Airtable url (langchain-ai#7532) * docs: Fix typo in OpenAIModerationChain example (langchain-ai#7528) * docs: Resolves langchain-ai#7483, resolves langchain-ai#7274 (langchain-ai#7505) Co-authored-by: jacoblee93 <[email protected]> * docs: Rename auth method in IBM docs (langchain-ai#7524) * docs: correct misspelling (langchain-ai#7522) Co-authored-by: jacoblee93 <[email protected]> * release(community): 0.3.25 (langchain-ai#7549) * feat(azure-cosmosdb): add session context for a user mongodb (langchain-ai#7436) Co-authored-by: jacoblee93 <[email protected]> * release(azure-cosmosdb): 0.2.7 (langchain-ai#7550) * fix(ci): Fix build (langchain-ai#7551) * feat(anthropic): Add Anthropic PDF support (document type) in invoke (langchain-ai#7496) Co-authored-by: jacoblee93 <[email protected]> * release(anthropic): 0.3.12 (langchain-ai#7552) * chore(core,langchain,community): Relax langsmith deps (langchain-ai#7556) * release(community): 0.3.26 (langchain-ai#7557) * release(core): 0.3.32 (langchain-ai#7558) * Release 0.3.12 (langchain-ai#7559) * fix(core): Prevent cache misses from triggering model start callback runs twice (langchain-ai#7565) * fix(core): Ensure that cached flag in run extras is only set for cache hits (langchain-ai#7566) * release(core): 0.3.33 (langchain-ai#7567) * feat(community): Adds graph_document to export list (langchain-ai#7555) Co-authored-by: quantropi-minh <[email protected]> Co-authored-by: jacoblee93 <[email protected]> * fix(langchain): Fix ZeroShotAgent createPrompt with correct formatted tool names (langchain-ai#7510) * docs: Add document for AzureCosmosDBMongoChatMessageHistory (langchain-ai#7519) Co-authored-by: root <root@CPC-yangq-FRSGK> * fix(langchain): Allow pulling hub prompts with associated models (langchain-ai#7569) * fix(community,aws): Update handleLLMNewToken to include chunk metadata (langchain-ai#7568) Co-authored-by: jacoblee93 <[email protected]> * feat(community): Provide fallback relationshipType in case it is not present in graph_transformer (langchain-ai#7521) Co-authored-by: quantropi-minh <[email protected]> Co-authored-by: jacoblee93 <[email protected]> * docs: Add redirect (langchain-ai#7570) * fix(langchain,core): Add shim for hub mustache templates with nested input variables (langchain-ai#7581) * fix(chat-models): honor disableStreaming even for `generateUncached` (langchain-ai#7575) * release(core): 0.3.34 (langchain-ai#7584) * feat(langchain): Add hub entrypoint with automatic dynamic entrypoint of models (langchain-ai#7583) * chore(ollama): Export `OllamaEmbeddingsParams` interface (langchain-ai#7574) * docs: Clarify tool creation process in structured outputs documentation (langchain-ai#7578) Co-authored-by: Sahar Shemesh <[email protected]> Co-authored-by: jacoblee93 <[email protected]> * fix(community): Set awaitHandlers to true in upstash ratelimit (langchain-ai#7571) Co-authored-by: Jacob Lee <[email protected]> * fix(core): Fix trim messages mutation (langchain-ai#7585) * feat(openai): Make only AzureOpenAI respect Azure env vars, remove class defaults, update withStructuredOutput defaults (langchain-ai#7535) * fix(community): Make postgresConnectionOptions optional in PostgresRecordManager (langchain-ai#7580) Co-authored-by: jacoblee93 <[email protected]> * release(community): 0.3.27 (langchain-ai#7586) * release(ollama): 0.1.5 (langchain-ai#7587) * Release 0.3.13 (langchain-ai#7588) * release(openai): 0.4.0 (langchain-ai#7589) * release(core): 0.3.35 (langchain-ai#7590) * fix(ci): Update lock (langchain-ai#7591) * feat(core): Allow passing returnDirect in tool wrapper params (langchain-ai#7594) * release(core): 0.3.36 (langchain-ai#7595) * fix(openai): Revert Azure default withStructuredOutput changes (langchain-ai#7596) * release(openai): 0.4.1 (langchain-ai#7597) * feat(openai): Refactor to allow easier subclassing (langchain-ai#7598) * release(openai): 0.4.2 (langchain-ai#7599) * feat(deepseek): Adds Deepseek integration (langchain-ai#7604) * release(deepseek): 0.0.1 (langchain-ai#7608) * feat: update Novita AI doc (langchain-ai#7602) * Add deployment chat to chat class * feat(langchain): Add DeepSeek to initChatModel (langchain-ai#7609) * Release 0.3.14 (langchain-ai#7611) * fix: Add test for pdf uploads anthropic (langchain-ai#7613) * feat: Update google genai to support file uploads (langchain-ai#7612) * chore(google-genai): Drop .only in test (langchain-ai#7614) * release(google-genai): 0.1.7 (langchain-ai#7615) * Upadate Watsonx sdk * fix(core): Fix stream events bug when errors are thrown too quickly during iteration (langchain-ai#7617) * release(core): 0.3.37 (langchain-ai#7619) * fix(langchain): Fix Groq import for hub (langchain-ai#7620) * docs: update README/intro * Release 0.3.15 * feat(community): improve support for Tavily search tool args (langchain-ai#7561) * feat(community): Add boolean metadata type support in Supabase structured query translator (langchain-ai#7601) * feat(google-genai): Add support for fileUri in media type in Google GenAI (langchain-ai#7621) Co-authored-by: Jacob Lee <[email protected]> * release(google-genai): 0.1.8 (langchain-ai#7628) * release(community): 0.3.28 (langchain-ai#7629) * Rework interfaces in llms as well * Bump watsonx-ai sdk version * Remove unused code * Add fake auth * Fix broken changes --------- Co-authored-by: Jacob Lee <[email protected]> Co-authored-by: Jacky Chen <[email protected]> Co-authored-by: Mohamed Belhadj <[email protected]> Co-authored-by: Brian Ploetz <[email protected]> Co-authored-by: Eduard-Constantin Ibinceanu <[email protected]> Co-authored-by: Jonathan V <[email protected]> Co-authored-by: ucev <[email protected]> Co-authored-by: crisjy <[email protected]> Co-authored-by: Adham Badr <[email protected]> Co-authored-by: Minh Ha <[email protected]> Co-authored-by: quantropi-minh <[email protected]> Co-authored-by: Chi Thu Le <[email protected]> Co-authored-by: fatmelon <[email protected]> Co-authored-by: root <root@CPC-yangq-FRSGK> Co-authored-by: Mohamad Mohebifar <[email protected]> Co-authored-by: David Duong <[email protected]> Co-authored-by: Brace Sproul <[email protected]> Co-authored-by: Matus Gura <[email protected]> Co-authored-by: Sahar Shemesh <[email protected]> Co-authored-by: Sahar Shemesh <[email protected]> Co-authored-by: Cahid Arda Öz <[email protected]> Co-authored-by: Jason <[email protected]> Co-authored-by: vbarda <[email protected]> Co-authored-by: Vadym Barda <[email protected]> Co-authored-by: Hugo Borsoni <[email protected]> Co-authored-by: Arman Ghazaryan <[email protected]> Co-authored-by: Andy <[email protected]>
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README.md

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@@ -43,7 +43,7 @@ The LangChain libraries themselves are made up of several different packages.
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- **[`@langchain/core`](https://github.com/langchain-ai/langchainjs/blob/main/langchain-core)**: Base abstractions and LangChain Expression Language.
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- **[`@langchain/community`](https://github.com/langchain-ai/langchainjs/blob/main/libs/langchain-community)**: Third party integrations.
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- **[`langchain`](https://github.com/langchain-ai/langchainjs/blob/main/langchain)**: Chains, agents, and retrieval strategies that make up an application's cognitive architecture.
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- **[LangGraph.js](https://langchain-ai.github.io/langgraphjs/)**: A library for building robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
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- **[LangGraph.js](https://langchain-ai.github.io/langgraphjs/)**: LangGraph powers production-grade agents, trusted by Linkedin, Uber, Klarna, GitLab, and many more. Build robust and stateful multi-actor applications with LLMs by modeling steps as edges and nodes in a graph. Integrates smoothly with LangChain, but can be used without it.
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Integrations may also be split into their own compatible packages.
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docs/core_docs/docs/concepts/structured_outputs.mdx

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Many [model providers support](/docs/integrations/chat/) tool calling, a concept discussed in more detail in our [tool calling guide](/docs/concepts/tool_calling/).
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In short, tool calling involves binding a tool to a model and, when appropriate, the model can _decide_ to call this tool and ensure its response conforms to the tool's schema.
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With this in mind, the central concept is straightforward: _simply bind our schema to a model as a tool!_
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With this in mind, the central concept is straightforward: _create a tool with our schema and bind it to the model!_
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Here is an example using the `ResponseFormatter` schema defined above:
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```typescript
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temperature: 0,
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});
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// Bind ResponseFormatter schema as a tool to the model
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const modelWithTools = model.bindTools([ResponseFormatter]);
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// Create a tool with ResponseFormatter as its schema.
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const responseFormatterTool = tool(async () => {}, {
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name: "responseFormatter",
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schema: ResponseFormatter,
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});
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// Bind the created tool to the model
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const modelWithTools = model.bindTools([responseFormatterTool]);
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// Invoke the model
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const aiMsg = await modelWithTools.invoke(

docs/core_docs/docs/how_to/graph_constructing.ipynb

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"\n",
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"const model = new ChatOpenAI({\n",
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" temperature: 0,\n",
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" model: \"gpt-4-turbo-preview\",\n",
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" model: \"gpt-4o-mini\",\n",
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"});\n",
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"\n",
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"const llmGraphTransformer = new LLMGraphTransformer({\n",

docs/core_docs/docs/how_to/query_high_cardinality.ipynb

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"metadata": {},
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"source": [
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"```{=mdx}\n",
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"<ChatModelTabs customVarName=\"llmLong\" openaiParams={`{ model: \"gpt-4-turbo-preview\" }`} />\n",
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"<ChatModelTabs customVarName=\"llmLong\" openaiParams={`{ model: \"gpt-4o-mini\" }`} />\n",
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"```"
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]
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},
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}
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}
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{
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"cells": [
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{
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"cell_type": "raw",
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"id": "afaf8039",
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"metadata": {
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"vscode": {
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"languageId": "raw"
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}
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},
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"source": [
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"---\n",
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"sidebar_label: DeepSeek\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": "e49f1e0d",
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"metadata": {},
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"source": [
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"# ChatDeepSeek\n",
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"\n",
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"This will help you getting started with DeepSeek [chat models](/docs/concepts/#chat-models). For detailed documentation of all `ChatDeepSeek` features and configurations head to the [API reference](https://api.js.langchain.com/classes/_langchain_deepseek.ChatDeepSeek.html).\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 | [PY support](https://python.langchain.com/docs/integrations/chat/deepseek) | Package downloads | Package latest |\n",
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"| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
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"| [`ChatDeepSeek`](https://api.js.langchain.com/classes/_langchain_deepseek.ChatDeepSeek.html) | [`@langchain/deepseek`](https://npmjs.com/@langchain/deepseek) | ❌ (see [Ollama](/docs/integrations/chat/ollama)) | beta | ✅ | ![NPM - Downloads](https://img.shields.io/npm/dm/@langchain/deepseek?style=flat-square&label=%20&) | ![NPM - Version](https://img.shields.io/npm/v/@langchain/deepseek?style=flat-square&label=%20&) |\n",
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"\n",
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"### Model features\n",
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"\n",
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"See the links in the table headers below for guides on how to use specific features.\n",
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"\n",
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"| [Tool calling](/docs/how_to/tool_calling) | [Structured output](/docs/how_to/structured_output/) | JSON mode | [Image input](/docs/how_to/multimodal_inputs/) | Audio input | Video input | [Token-level streaming](/docs/how_to/chat_streaming/) | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
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"| :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: | :---: |\n",
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"| ✅ | ✅ | ✅ | ❌ | ❌ | ❌ | ✅ | ✅ | ✅ | \n",
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"\n",
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"Note that as of 1/27/25, tool calling and structured output are not currently supported for `deepseek-reasoner`.\n",
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"\n",
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"## Setup\n",
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"\n",
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"To access DeepSeek models you'll need to create a DeepSeek account, get an API key, and install the `@langchain/deepseek` integration package.\n",
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"\n",
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"You can also access the DeepSeek API through providers like [Together AI](/docs/integrations/chat/togetherai) or [Ollama](/docs/integrations/chat/ollama).\n",
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"\n",
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"### Credentials\n",
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"\n",
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"Head to https://deepseek.com/ to sign up to DeepSeek and generate an API key. Once you've done this set the `DEEPSEEK_API_KEY` environment variable:\n",
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"\n",
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"```bash\n",
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"export DEEPSEEK_API_KEY=\"your-api-key\"\n",
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"```\n",
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"\n",
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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:\n",
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"\n",
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"```bash\n",
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"# export LANGSMITH_TRACING=\"true\"\n",
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"# export LANGSMITH_API_KEY=\"your-api-key\"\n",
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"```\n",
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"\n",
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"### Installation\n",
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"\n",
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"The LangChain ChatDeepSeek integration lives in the `@langchain/deepseek` package:\n",
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"\n",
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"```{=mdx}\n",
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"import IntegrationInstallTooltip from \"@mdx_components/integration_install_tooltip.mdx\";\n",
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"import Npm2Yarn from \"@theme/Npm2Yarn\";\n",
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"\n",
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"<IntegrationInstallTooltip></IntegrationInstallTooltip>\n",
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"\n",
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"<Npm2Yarn>\n",
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" @langchain/deepseek @langchain/core\n",
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"</Npm2Yarn>\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": "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:"
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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": 1,
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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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"import { ChatDeepSeek } from \"@langchain/deepseek\";\n",
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"\n",
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"const llm = new ChatDeepSeek({\n",
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" model: \"deepseek-reasoner\",\n",
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" temperature: 0,\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": 2,
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"AIMessage {\n",
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" \"id\": \"e2874482-68a7-4552-8154-b6a245bab429\",\n",
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" \"content\": \"J'adore la programmation.\",\n",
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" \"additional_kwargs\": {,\n",
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" \"reasoning_content\": \"...\",\n",
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" },\n",
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" \"response_metadata\": {\n",
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" \"tokenUsage\": {\n",
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" \"promptTokens\": 23,\n",
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" \"completionTokens\": 7,\n",
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" \"totalTokens\": 30\n",
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" },\n",
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" \"finish_reason\": \"stop\",\n",
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" \"model_name\": \"deepseek-reasoner\",\n",
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" \"usage\": {\n",
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" \"prompt_tokens\": 23,\n",
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" \"completion_tokens\": 7,\n",
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" \"total_tokens\": 30,\n",
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" \"prompt_tokens_details\": {\n",
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" \"cached_tokens\": 0\n",
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" },\n",
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" \"prompt_cache_hit_tokens\": 0,\n",
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" \"prompt_cache_miss_tokens\": 23\n",
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" },\n",
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" \"system_fingerprint\": \"fp_3a5770e1b4\"\n",
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" },\n",
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" \"tool_calls\": [],\n",
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" \"invalid_tool_calls\": [],\n",
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" \"usage_metadata\": {\n",
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" \"output_tokens\": 7,\n",
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" \"input_tokens\": 23,\n",
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" \"total_tokens\": 30,\n",
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" \"input_token_details\": {\n",
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" \"cache_read\": 0\n",
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" },\n",
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" \"output_token_details\": {}\n",
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" }\n",
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"}\n"
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]
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}
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],
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"source": [
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"const aiMsg = await llm.invoke([\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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"aiMsg"
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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": "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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"console.log(aiMsg.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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"We can [chain](/docs/how_to/sequence/) 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": 4,
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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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"name": "stdout",
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"output_type": "stream",
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"text": [
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"AIMessage {\n",
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" \"id\": \"6e7f6f8c-8d7a-4dad-be07-425384038fd4\",\n",
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" \"content\": \"Ich liebe es zu programmieren.\",\n",
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" \"additional_kwargs\": {,\n",
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" \"reasoning_content\": \"...\",\n",
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" },\n",
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" \"response_metadata\": {\n",
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" \"tokenUsage\": {\n",
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" \"promptTokens\": 18,\n",
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" \"completionTokens\": 9,\n",
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" \"totalTokens\": 27\n",
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" },\n",
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" \"finish_reason\": \"stop\",\n",
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" \"model_name\": \"deepseek-reasoner\",\n",
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" \"usage\": {\n",
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" \"prompt_tokens\": 18,\n",
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" \"completion_tokens\": 9,\n",
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" \"total_tokens\": 27,\n",
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" \"prompt_tokens_details\": {\n",
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" \"cached_tokens\": 0\n",
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" },\n",
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" \"prompt_cache_hit_tokens\": 0,\n",
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" \"prompt_cache_miss_tokens\": 18\n",
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" },\n",
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" \"system_fingerprint\": \"fp_3a5770e1b4\"\n",
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" },\n",
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" \"tool_calls\": [],\n",
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" \"invalid_tool_calls\": [],\n",
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" \"usage_metadata\": {\n",
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" \"output_tokens\": 9,\n",
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" \"input_tokens\": 18,\n",
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" \"total_tokens\": 27,\n",
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" \"input_token_details\": {\n",
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" \"cache_read\": 0\n",
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" },\n",
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" \"output_token_details\": {}\n",
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" }\n",
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"}\n"
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]
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}
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],
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"source": [
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"import { ChatPromptTemplate } from \"@langchain/core/prompts\"\n",
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"\n",
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"const prompt = ChatPromptTemplate.fromMessages(\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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"const chain = prompt.pipe(llm);\n",
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"await 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 ChatDeepSeek features and configurations head to the API reference: https://api.js.langchain.com/classes/_langchain_deepseek.ChatDeepSeek.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": "TypeScript",
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"language": "typescript",
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"name": "tslab"
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},
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"language_info": {
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"codemirror_mode": {
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"mode": "typescript",
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"name": "javascript",
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"typescript": true
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},
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"file_extension": ".ts",
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"mimetype": "text/typescript",
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"name": "typescript",
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"version": "3.7.2"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 5
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}

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