mirror of
https://github.com/hwchase17/langchain.git
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deepseek, docs: chatdeepseek integration added (#29445)
This commit is contained in:
Erick Friis
GitHub
parent
7cbf885c18
commit
dced0ed3fd
231
docs/docs/integrations/chat/deepseek.ipynb
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231
docs/docs/integrations/chat/deepseek.ipynb
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@ -0,0 +1,231 @@
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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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"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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"\n",
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"This will help you getting started with DeepSeek's hosted [chat models](/docs/concepts/chat_models). For detailed documentation of all ChatDeepSeek features and configurations head to the [API reference](https://python.langchain.com/api_reference/deepseek/chat_models/langchain_deepseek.chat_models.ChatDeepSeek.html).\n",
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"\n",
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":::tip\n",
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"\n",
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"DeepSeek's models are open source and can be run locally (e.g. in [Ollama](./ollama.ipynb)) or on other inference providers (e.g. [Fireworks](./fireworks.ipynb), [Together](./together.ipynb)) as well.\n",
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"\n",
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":::\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/docs/integrations/chat/deepseek) | Package downloads | Package latest |\n",
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"| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
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"| [ChatDeepSeek](https://python.langchain.com/api_reference/deepseek/chat_models/langchain_deepseek.chat_models.ChatDeepSeek.html) | [langchain-deepseek-official](https://python.langchain.com/api_reference/deepseek/) | ❌ | beta | ✅ |  |  |\n",
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"\n",
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"### Model features\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/) | Native async | [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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"## Setup\n",
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"\n",
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"To access DeepSeek models you'll need to create a/an DeepSeek account, get an API key, and install the `langchain-deepseek-official` 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 [DeepSeek's API Key page](https://platform.deepseek.com/api_keys) to sign up to DeepSeek and generate an API key. Once you've done this set the `DEEPSEEK_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": "433e8d2b-9519-4b49-b2c4-7ab65b046c94",
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"metadata": {},
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"outputs": [],
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"source": [
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"import getpass\n",
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"import os\n",
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"\n",
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"if not os.getenv(\"DEEPSEEK_API_KEY\"):\n",
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" os.environ[\"DEEPSEEK_API_KEY\"] = getpass.getpass(\"Enter your DeepSeek 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": "72ee0c4b-9764-423a-9dbf-95129e185210",
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"metadata": {},
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"source": [
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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": "a15d341e-3e26-4ca3-830b-5aab30ed66de",
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"metadata": {},
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"outputs": [],
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"source": [
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"# os.environ[\"LANGSMITH_TRACING\"] = \"true\"\n",
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"# os.environ[\"LANGSMITH_API_KEY\"] = getpass.getpass(\"Enter your LangSmith 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": "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 DeepSeek integration lives in the `langchain-deepseek-official` 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": null,
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"id": "652d6238-1f87-422a-b135-f5abbb8652fc",
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"metadata": {},
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"outputs": [],
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"source": [
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"%pip install -qU langchain-deepseek-official"
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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": null,
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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_deepseek import ChatDeepSeek\n",
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"\n",
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"llm = ChatDeepSeek(\n",
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" model=\"deepseek-chat\",\n",
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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": "62e0dbc3",
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"metadata": {
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"tags": []
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},
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"outputs": [],
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"source": [
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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.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": null,
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"id": "e197d1d7-a070-4c96-9f8a-a0e86d046e0b",
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"metadata": {},
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"outputs": [],
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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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"prompt = ChatPromptTemplate(\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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"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 ChatDeepSeek features and configurations head to the [API Reference](https://python.langchain.com/api_reference/deepseek/chat_models/langchain_deepseek.chat_models.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": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.11.9"
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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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48
docs/docs/integrations/providers/deepseek.ipynb
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48
docs/docs/integrations/providers/deepseek.ipynb
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@ -0,0 +1,48 @@
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
|
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"# DeepSeek\n",
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"\n",
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"[DeepSeek](https://www.deepseek.com/) is a Chinese artificial intelligence company that develops LLMs."
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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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"metadata": {
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"id": "y8ku6X96sebl"
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},
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"outputs": [],
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"source": [
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"from langchain_deepseek import ChatDeepSeek"
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]
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}
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],
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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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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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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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": "3.10.11"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 1
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}
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@ -19,7 +19,7 @@
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"\n",
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"- TODO: Make sure API reference link is correct.\n",
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"\n",
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"This will help you getting started with __ModuleName__ [chat models](/docs/concepts/chat_models). For detailed documentation of all Chat__ModuleName__ features and configurations head to the [API reference](https://api.python.langchain.com/en/latest/chat_models/__module_name__.chat_models.Chat__ModuleName__.html).\n",
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"This will help you getting started with __ModuleName__ [chat models](/docs/concepts/chat_models). For detailed documentation of all Chat__ModuleName__ features and configurations head to the [API reference](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html).\n",
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"\n",
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"- TODO: Add any other relevant links, like information about models, prices, context windows, etc. See https://python.langchain.com/docs/integrations/chat/openai/ for an example.\n",
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"\n",
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@ -32,7 +32,7 @@
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"\n",
|
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"| Class | Package | Local | Serializable | [JS support](https://js.langchain.com/docs/integrations/chat/__package_name_short_snake__) | Package downloads | Package latest |\n",
|
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"| :--- | :--- | :---: | :---: | :---: | :---: | :---: |\n",
|
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"| [Chat__ModuleName__](https://api.python.langchain.com/en/latest/chat_models/__module_name__.chat_models.Chat__ModuleName__.html) | [__package_name__](https://api.python.langchain.com/en/latest/__package_name_short_snake___api_reference.html) | ✅/❌ | beta/❌ | ✅/❌ |  |  |\n",
|
||||
"| [Chat__ModuleName__](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html) | [__package_name__](https://python.langchain.com/api_reference/__package_name_short_snake__/) | ✅/❌ | beta/❌ | ✅/❌ |  |  |\n",
|
||||
"\n",
|
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"### Model features\n",
|
||||
"| [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/) | Native async | [Token usage](/docs/how_to/chat_token_usage_tracking/) | [Logprobs](/docs/how_to/logprobs/) |\n",
|
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@ -234,7 +234,7 @@
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"source": [
|
||||
"## API reference\n",
|
||||
"\n",
|
||||
"For detailed documentation of all Chat__ModuleName__ features and configurations head to the API reference: https://api.python.langchain.com/en/latest/chat_models/__module_name__.chat_models.Chat__ModuleName__.html"
|
||||
"For detailed documentation of all Chat__ModuleName__ features and configurations head to the [API reference](https://python.langchain.com/api_reference/__package_name_short_snake__/chat_models/__module_name__.chat_models.Chat__ModuleName__.html)"
|
||||
]
|
||||
}
|
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],
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@ -365,3 +365,9 @@ packages:
|
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repo: sambanova/langchain-sambanova
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path: .
|
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downloads: 0
|
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- name: langchain-deepseek-official
|
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repo: langchain-ai/langchain
|
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path: libs/partners/deepseek
|
||||
downloads: 0
|
||||
js: '@langchain/deepseek'
|
||||
provider_page: deepseek
|
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|
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1
libs/partners/deepseek/.gitignore
vendored
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1
libs/partners/deepseek/.gitignore
vendored
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@ -0,0 +1 @@
|
||||
__pycache__
|
||||
21
libs/partners/deepseek/LICENSE
Normal file
21
libs/partners/deepseek/LICENSE
Normal file
@ -0,0 +1,21 @@
|
||||
MIT License
|
||||
|
||||
Copyright (c) 2024 LangChain, Inc.
|
||||
|
||||
Permission is hereby granted, free of charge, to any person obtaining a copy
|
||||
of this software and associated documentation files (the "Software"), to deal
|
||||
in the Software without restriction, including without limitation the rights
|
||||
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
|
||||
copies of the Software, and to permit persons to whom the Software is
|
||||
furnished to do so, subject to the following conditions:
|
||||
|
||||
The above copyright notice and this permission notice shall be included in all
|
||||
copies or substantial portions of the Software.
|
||||
|
||||
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
|
||||
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
|
||||
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
|
||||
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
|
||||
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
|
||||
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
|
||||
SOFTWARE.
|
||||
64
libs/partners/deepseek/Makefile
Normal file
64
libs/partners/deepseek/Makefile
Normal file
@ -0,0 +1,64 @@
|
||||
.PHONY: all format lint test tests integration_tests docker_tests help extended_tests
|
||||
|
||||
# Default target executed when no arguments are given to make.
|
||||
all: help
|
||||
|
||||
# Define a variable for the test file path.
|
||||
TEST_FILE ?= tests/unit_tests/
|
||||
integration_test integration_tests: TEST_FILE = tests/integration_tests/
|
||||
|
||||
|
||||
# unit tests are run with the --disable-socket flag to prevent network calls
|
||||
test tests:
|
||||
poetry run pytest --disable-socket --allow-unix-socket $(TEST_FILE)
|
||||
|
||||
test_watch:
|
||||
poetry run ptw --snapshot-update --now . -- -vv $(TEST_FILE)
|
||||
|
||||
# integration tests are run without the --disable-socket flag to allow network calls
|
||||
integration_test integration_tests:
|
||||
poetry run pytest --timeout=30 $(TEST_FILE)
|
||||
|
||||
######################
|
||||
# LINTING AND FORMATTING
|
||||
######################
|
||||
|
||||
# Define a variable for Python and notebook files.
|
||||
PYTHON_FILES=.
|
||||
MYPY_CACHE=.mypy_cache
|
||||
lint format: PYTHON_FILES=.
|
||||
lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/deepseek --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
|
||||
lint_package: PYTHON_FILES=langchain_deepseek
|
||||
lint_tests: PYTHON_FILES=tests
|
||||
lint_tests: MYPY_CACHE=.mypy_cache_test
|
||||
|
||||
lint lint_diff lint_package lint_tests:
|
||||
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check $(PYTHON_FILES)
|
||||
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
|
||||
[ "$(PYTHON_FILES)" = "" ] || mkdir -p $(MYPY_CACHE) && poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
|
||||
|
||||
format format_diff:
|
||||
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES)
|
||||
[ "$(PYTHON_FILES)" = "" ] || poetry run ruff check --select I --fix $(PYTHON_FILES)
|
||||
|
||||
spell_check:
|
||||
poetry run codespell --toml pyproject.toml
|
||||
|
||||
spell_fix:
|
||||
poetry run codespell --toml pyproject.toml -w
|
||||
|
||||
check_imports: $(shell find langchain_deepseek -name '*.py')
|
||||
poetry run python ./scripts/check_imports.py $^
|
||||
|
||||
######################
|
||||
# HELP
|
||||
######################
|
||||
|
||||
help:
|
||||
@echo '----'
|
||||
@echo 'check_imports - check imports'
|
||||
@echo 'format - run code formatters'
|
||||
@echo 'lint - run linters'
|
||||
@echo 'test - run unit tests'
|
||||
@echo 'tests - run unit tests'
|
||||
@echo 'test TEST_FILE=<test_file> - run all tests in file'
|
||||
24
libs/partners/deepseek/README.md
Normal file
24
libs/partners/deepseek/README.md
Normal file
@ -0,0 +1,24 @@
|
||||
# langchain-deepseek-official
|
||||
|
||||
This package contains the LangChain integration with the DeepSeek API
|
||||
|
||||
## Installation
|
||||
|
||||
```bash
|
||||
pip install -U langchain-deepseek-official
|
||||
```
|
||||
|
||||
And you should configure credentials by setting the following environment variables:
|
||||
|
||||
* `DEEPSEEK_API_KEY`
|
||||
|
||||
## Chat Models
|
||||
|
||||
`ChatDeepSeek` class exposes chat models from DeepSeek.
|
||||
|
||||
```python
|
||||
from langchain_deepseek import ChatDeepSeek
|
||||
|
||||
llm = ChatDeepSeek(model="deepseek-chat")
|
||||
llm.invoke("Sing a ballad of LangChain.")
|
||||
```
|
||||
15
libs/partners/deepseek/langchain_deepseek/__init__.py
Normal file
15
libs/partners/deepseek/langchain_deepseek/__init__.py
Normal file
@ -0,0 +1,15 @@
|
||||
from importlib import metadata
|
||||
|
||||
from langchain_deepseek.chat_models import ChatDeepSeek
|
||||
|
||||
try:
|
||||
__version__ = metadata.version(__package__)
|
||||
except metadata.PackageNotFoundError:
|
||||
# Case where package metadata is not available.
|
||||
__version__ = ""
|
||||
del metadata # optional, avoids polluting the results of dir(__package__)
|
||||
|
||||
__all__ = [
|
||||
"ChatDeepSeek",
|
||||
"__version__",
|
||||
]
|
||||
220
libs/partners/deepseek/langchain_deepseek/chat_models.py
Normal file
220
libs/partners/deepseek/langchain_deepseek/chat_models.py
Normal file
@ -0,0 +1,220 @@
|
||||
"""DeepSeek chat models."""
|
||||
|
||||
from typing import Dict, Optional, Union
|
||||
|
||||
import openai
|
||||
from langchain_core.outputs import ChatResult
|
||||
from langchain_core.utils import from_env, secret_from_env
|
||||
from langchain_openai.chat_models.base import BaseChatOpenAI
|
||||
from pydantic import ConfigDict, Field, SecretStr, model_validator
|
||||
from typing_extensions import Self
|
||||
|
||||
DEFAULT_API_BASE = "https://api.deepseek.com/v1"
|
||||
|
||||
|
||||
class ChatDeepSeek(BaseChatOpenAI):
|
||||
"""DeepSeek chat model integration to access models hosted in DeepSeek's API.
|
||||
|
||||
Setup:
|
||||
Install ``langchain-deepseek-official`` and set environment variable ``DEEPSEEK_API_KEY``.
|
||||
|
||||
.. code-block:: bash
|
||||
|
||||
pip install -U langchain-deepseek-official
|
||||
export DEEPSEEK_API_KEY="your-api-key"
|
||||
|
||||
Key init args — completion params:
|
||||
model: str
|
||||
Name of DeepSeek model to use, e.g. "deepseek-chat".
|
||||
temperature: float
|
||||
Sampling temperature.
|
||||
max_tokens: Optional[int]
|
||||
Max number of tokens to generate.
|
||||
|
||||
Key init args — client params:
|
||||
timeout: Optional[float]
|
||||
Timeout for requests.
|
||||
max_retries: int
|
||||
Max number of retries.
|
||||
api_key: Optional[str]
|
||||
DeepSeek API key. If not passed in will be read from env var DEEPSEEK_API_KEY.
|
||||
|
||||
See full list of supported init args and their descriptions in the params section.
|
||||
|
||||
Instantiate:
|
||||
.. code-block:: python
|
||||
|
||||
from langchain_deepseek import ChatDeepSeek
|
||||
|
||||
llm = ChatDeepSeek(
|
||||
model="...",
|
||||
temperature=0,
|
||||
max_tokens=None,
|
||||
timeout=None,
|
||||
max_retries=2,
|
||||
# api_key="...",
|
||||
# other params...
|
||||
)
|
||||
|
||||
Invoke:
|
||||
.. code-block:: python
|
||||
|
||||
messages = [
|
||||
("system", "You are a helpful translator. Translate the user sentence to French."),
|
||||
("human", "I love programming."),
|
||||
]
|
||||
llm.invoke(messages)
|
||||
|
||||
Stream:
|
||||
.. code-block:: python
|
||||
|
||||
for chunk in llm.stream(messages):
|
||||
print(chunk)
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
stream = llm.stream(messages)
|
||||
full = next(stream)
|
||||
for chunk in stream:
|
||||
full += chunk
|
||||
full
|
||||
|
||||
Async:
|
||||
.. code-block:: python
|
||||
|
||||
await llm.ainvoke(messages)
|
||||
|
||||
# stream:
|
||||
# async for chunk in (await llm.astream(messages))
|
||||
|
||||
# batch:
|
||||
# await llm.abatch([messages])
|
||||
|
||||
Tool calling:
|
||||
.. code-block:: python
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
class GetWeather(BaseModel):
|
||||
'''Get the current weather in a given location'''
|
||||
|
||||
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
|
||||
|
||||
class GetPopulation(BaseModel):
|
||||
'''Get the current population in a given location'''
|
||||
|
||||
location: str = Field(..., description="The city and state, e.g. San Francisco, CA")
|
||||
|
||||
llm_with_tools = llm.bind_tools([GetWeather, GetPopulation])
|
||||
ai_msg = llm_with_tools.invoke("Which city is hotter today and which is bigger: LA or NY?")
|
||||
ai_msg.tool_calls
|
||||
|
||||
See ``ChatDeepSeek.bind_tools()`` method for more.
|
||||
|
||||
Structured output:
|
||||
.. code-block:: python
|
||||
|
||||
from typing import Optional
|
||||
|
||||
from pydantic import BaseModel, Field
|
||||
|
||||
class Joke(BaseModel):
|
||||
'''Joke to tell user.'''
|
||||
|
||||
setup: str = Field(description="The setup of the joke")
|
||||
punchline: str = Field(description="The punchline to the joke")
|
||||
rating: Optional[int] = Field(description="How funny the joke is, from 1 to 10")
|
||||
|
||||
structured_llm = llm.with_structured_output(Joke)
|
||||
structured_llm.invoke("Tell me a joke about cats")
|
||||
|
||||
See ``ChatDeepSeek.with_structured_output()`` for more.
|
||||
|
||||
Token usage:
|
||||
.. code-block:: python
|
||||
|
||||
ai_msg = llm.invoke(messages)
|
||||
ai_msg.usage_metadata
|
||||
|
||||
.. code-block:: python
|
||||
|
||||
{'input_tokens': 28, 'output_tokens': 5, 'total_tokens': 33}
|
||||
|
||||
Response metadata
|
||||
.. code-block:: python
|
||||
|
||||
ai_msg = llm.invoke(messages)
|
||||
ai_msg.response_metadata
|
||||
|
||||
""" # noqa: E501
|
||||
|
||||
model_name: str = Field(alias="model")
|
||||
"""The name of the model"""
|
||||
api_key: Optional[SecretStr] = Field(
|
||||
default_factory=secret_from_env("DEEPSEEK_API_KEY", default=None)
|
||||
)
|
||||
"""DeepSeek API key"""
|
||||
api_base: str = Field(
|
||||
default_factory=from_env("DEEPSEEK_API_BASE", default=DEFAULT_API_BASE)
|
||||
)
|
||||
"""DeepSeek API base URL"""
|
||||
|
||||
model_config = ConfigDict(populate_by_name=True)
|
||||
|
||||
@property
|
||||
def _llm_type(self) -> str:
|
||||
"""Return type of chat model."""
|
||||
return "chat-deepseek"
|
||||
|
||||
@property
|
||||
def lc_secrets(self) -> Dict[str, str]:
|
||||
"""A map of constructor argument names to secret ids."""
|
||||
return {"api_key": "DEEPSEEK_API_KEY"}
|
||||
|
||||
@model_validator(mode="after")
|
||||
def validate_environment(self) -> Self:
|
||||
if self.api_base == DEFAULT_API_BASE and not (
|
||||
self.api_key and self.api_key.get_secret_value()
|
||||
):
|
||||
raise ValueError("If using default api base, DEEPSEEK_API_KEY must be set.")
|
||||
client_params: dict = {
|
||||
k: v
|
||||
for k, v in {
|
||||
"api_key": self.api_key.get_secret_value() if self.api_key else None,
|
||||
"base_url": self.api_base,
|
||||
"timeout": self.request_timeout,
|
||||
"max_retries": self.max_retries,
|
||||
"default_headers": self.default_headers,
|
||||
"default_query": self.default_query,
|
||||
}.items()
|
||||
if v is not None
|
||||
}
|
||||
|
||||
if not (self.client or None):
|
||||
sync_specific: dict = {"http_client": self.http_client}
|
||||
self.client = openai.OpenAI(
|
||||
**client_params, **sync_specific
|
||||
).chat.completions
|
||||
if not (self.async_client or None):
|
||||
async_specific: dict = {"http_client": self.http_async_client}
|
||||
self.async_client = openai.AsyncOpenAI(
|
||||
**client_params, **async_specific
|
||||
).chat.completions
|
||||
return self
|
||||
|
||||
def _create_chat_result(
|
||||
self,
|
||||
response: Union[dict, openai.BaseModel],
|
||||
generation_info: Optional[Dict] = None,
|
||||
) -> ChatResult:
|
||||
rtn = super()._create_chat_result(response, generation_info)
|
||||
|
||||
if not isinstance(response, openai.BaseModel):
|
||||
return rtn
|
||||
|
||||
if hasattr(response.choices[0].message, "reasoning_content"): # type: ignore
|
||||
rtn.generations[0].message.additional_kwargs["reasoning_content"] = (
|
||||
response.choices[0].message.reasoning_content # type: ignore
|
||||
)
|
||||
|
||||
return rtn
|
||||
0
libs/partners/deepseek/langchain_deepseek/py.typed
Normal file
0
libs/partners/deepseek/langchain_deepseek/py.typed
Normal file
1652
libs/partners/deepseek/poetry.lock
generated
Normal file
1652
libs/partners/deepseek/poetry.lock
generated
Normal file
File diff suppressed because it is too large
Load Diff
74
libs/partners/deepseek/pyproject.toml
Normal file
74
libs/partners/deepseek/pyproject.toml
Normal file
@ -0,0 +1,74 @@
|
||||
[build-system]
|
||||
requires = ["poetry-core>=1.0.0"]
|
||||
build-backend = "poetry.core.masonry.api"
|
||||
|
||||
[tool.poetry]
|
||||
name = "langchain-deepseek-official"
|
||||
packages = [{ include = "langchain_deepseek" }]
|
||||
version = "0.1.0"
|
||||
description = "An integration package connecting DeepSeek and LangChain"
|
||||
authors = []
|
||||
readme = "README.md"
|
||||
repository = "https://github.com/langchain-ai/langchain"
|
||||
license = "MIT"
|
||||
|
||||
[tool.mypy]
|
||||
disallow_untyped_defs = "True"
|
||||
|
||||
[tool.poetry.urls]
|
||||
"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/deepseek"
|
||||
"Release Notes" = "https://github.com/langchain-ai/langchain/releases?q=tag%3A%22deepseek%3D%3D0%22&expanded=true"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.9,<4.0"
|
||||
langchain-core = "^0.3.15"
|
||||
langchain-openai = "^0.3.2"
|
||||
|
||||
[tool.ruff.lint]
|
||||
select = ["E", "F", "I", "T201"]
|
||||
|
||||
[tool.coverage.run]
|
||||
omit = ["tests/*"]
|
||||
|
||||
[tool.pytest.ini_options]
|
||||
addopts = "--strict-markers --strict-config --durations=5"
|
||||
markers = [
|
||||
"compile: mark placeholder test used to compile integration tests without running them",
|
||||
]
|
||||
asyncio_mode = "auto"
|
||||
|
||||
[tool.poetry.group.test]
|
||||
optional = true
|
||||
|
||||
[tool.poetry.group.codespell]
|
||||
optional = true
|
||||
|
||||
[tool.poetry.group.test_integration]
|
||||
optional = true
|
||||
|
||||
[tool.poetry.group.lint]
|
||||
optional = true
|
||||
|
||||
[tool.poetry.group.dev]
|
||||
optional = true
|
||||
|
||||
[tool.poetry.group.dev.dependencies]
|
||||
|
||||
[tool.poetry.group.test.dependencies]
|
||||
pytest = "^7.4.3"
|
||||
pytest-asyncio = "^0.23.2"
|
||||
pytest-socket = "^0.7.0"
|
||||
pytest-watcher = "^0.3.4"
|
||||
langchain-tests = "^0.3.5"
|
||||
langchain-openai = { path = "../openai" }
|
||||
|
||||
[tool.poetry.group.codespell.dependencies]
|
||||
codespell = "^2.2.6"
|
||||
|
||||
[tool.poetry.group.test_integration.dependencies]
|
||||
|
||||
[tool.poetry.group.lint.dependencies]
|
||||
ruff = "^0.5"
|
||||
|
||||
[tool.poetry.group.typing.dependencies]
|
||||
mypy = "^1.10"
|
||||
17
libs/partners/deepseek/scripts/check_imports.py
Normal file
17
libs/partners/deepseek/scripts/check_imports.py
Normal file
@ -0,0 +1,17 @@
|
||||
import sys
|
||||
import traceback
|
||||
from importlib.machinery import SourceFileLoader
|
||||
|
||||
if __name__ == "__main__":
|
||||
files = sys.argv[1:]
|
||||
has_failure = False
|
||||
for file in files:
|
||||
try:
|
||||
SourceFileLoader("x", file).load_module()
|
||||
except Exception:
|
||||
has_failure = True
|
||||
print(file) # noqa: T201
|
||||
traceback.print_exc()
|
||||
print() # noqa: T201
|
||||
|
||||
sys.exit(1 if has_failure else 0)
|
||||
18
libs/partners/deepseek/scripts/lint_imports.sh
Executable file
18
libs/partners/deepseek/scripts/lint_imports.sh
Executable file
@ -0,0 +1,18 @@
|
||||
#!/bin/bash
|
||||
|
||||
set -eu
|
||||
|
||||
# Initialize a variable to keep track of errors
|
||||
errors=0
|
||||
|
||||
# make sure not importing from langchain, langchain_experimental, or langchain_community
|
||||
git --no-pager grep '^from langchain\.' . && errors=$((errors+1))
|
||||
git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
|
||||
git --no-pager grep '^from langchain_community\.' . && errors=$((errors+1))
|
||||
|
||||
# Decide on an exit status based on the errors
|
||||
if [ "$errors" -gt 0 ]; then
|
||||
exit 1
|
||||
else
|
||||
exit 0
|
||||
fi
|
||||
0
libs/partners/deepseek/tests/__init__.py
Normal file
0
libs/partners/deepseek/tests/__init__.py
Normal file
@ -0,0 +1,30 @@
|
||||
"""Test ChatDeepSeek chat model."""
|
||||
|
||||
from typing import Type
|
||||
|
||||
from langchain_tests.integration_tests import ChatModelIntegrationTests
|
||||
|
||||
from langchain_deepseek.chat_models import ChatDeepSeek
|
||||
|
||||
|
||||
class TestChatDeepSeek(ChatModelIntegrationTests):
|
||||
@property
|
||||
def chat_model_class(self) -> Type[ChatDeepSeek]:
|
||||
return ChatDeepSeek
|
||||
|
||||
@property
|
||||
def chat_model_params(self) -> dict:
|
||||
# These should be parameters used to initialize your integration for testing
|
||||
return {
|
||||
"model": "deepseek-chat",
|
||||
"temperature": 0,
|
||||
}
|
||||
|
||||
|
||||
def test_reasoning_content() -> None:
|
||||
"""Test reasoning content."""
|
||||
chat_model = ChatDeepSeek(model="deepseek-reasoner")
|
||||
response = chat_model.invoke("What is the square root of 256256?")
|
||||
assert response.content
|
||||
assert response.additional_kwargs["reasoning_content"]
|
||||
raise ValueError()
|
||||
@ -0,0 +1,7 @@
|
||||
import pytest
|
||||
|
||||
|
||||
@pytest.mark.compile
|
||||
def test_placeholder() -> None:
|
||||
"""Used for compiling integration tests without running any real tests."""
|
||||
pass
|
||||
0
libs/partners/deepseek/tests/unit_tests/__init__.py
Normal file
0
libs/partners/deepseek/tests/unit_tests/__init__.py
Normal file
37
libs/partners/deepseek/tests/unit_tests/test_chat_models.py
Normal file
37
libs/partners/deepseek/tests/unit_tests/test_chat_models.py
Normal file
@ -0,0 +1,37 @@
|
||||
"""Test chat model integration."""
|
||||
|
||||
from typing import Type
|
||||
|
||||
from langchain_tests.unit_tests import ChatModelUnitTests
|
||||
|
||||
from langchain_deepseek.chat_models import ChatDeepSeek
|
||||
|
||||
|
||||
class TestChatDeepSeekUnit(ChatModelUnitTests):
|
||||
@property
|
||||
def chat_model_class(self) -> Type[ChatDeepSeek]:
|
||||
return ChatDeepSeek
|
||||
|
||||
@property
|
||||
def init_from_env_params(self) -> tuple[dict, dict, dict]:
|
||||
return (
|
||||
{
|
||||
"DEEPSEEK_API_KEY": "api_key",
|
||||
"DEEPSEEK_API_BASE": "api_base",
|
||||
},
|
||||
{
|
||||
"model": "deepseek-chat",
|
||||
},
|
||||
{
|
||||
"api_key": "api_key",
|
||||
"api_base": "api_base",
|
||||
},
|
||||
)
|
||||
|
||||
@property
|
||||
def chat_model_params(self) -> dict:
|
||||
# These should be parameters used to initialize your integration for testing
|
||||
return {
|
||||
"model": "deepseek-chat",
|
||||
"api_key": "api_key",
|
||||
}
|
||||
Loading…
Reference in New Issue
Block a user