community[minor]: Added GigaChat Embeddings support + updated previou…

…s GigaChat integration (langchain-ai#19516) - **Description:** Added integration with [GigaChat](https://developers.sber.ru/portal/products/gigachat) embeddings. Also added support for extra fields in GigaChat LLM and fixed docs.
chrispy-snps · Mar 30, 2024 · 1cd039e · 1cd039e
1 parent 6f0dfd8
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Showing 9 changed files with 547 additions and 61 deletions.
diff --git a/docs/docs/integrations/chat/gigachat.ipynb b/docs/docs/integrations/chat/gigachat.ipynb
@@ -13,9 +13,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "pycharm": {
+     "is_executing": true
+    }
    },
    "outputs": [],
    "source": [
@@ -28,13 +31,14 @@
     "collapsed": false
    },
    "source": [
-    "To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/api/integration)\n",
+    "To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
+    "\n",
     "## Example"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
@@ -48,20 +52,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from langchain_community.chat_models import GigaChat\n",
     "\n",
-    "chat = GigaChat(verify_ssl_certs=False)"
+    "chat = GigaChat(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 8,
    "metadata": {
     "collapsed": false
    },
@@ -70,7 +74,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "What do you get when you cross a goat and a skunk? A smelly goat!\n"
+      "The capital of Russia is Moscow.\n"
      ]
     }
    ],
@@ -81,10 +85,10 @@
     "    SystemMessage(\n",
     "        content=\"You are a helpful AI that shares everything you know. Talk in English.\"\n",
     "    ),\n",
-    "    HumanMessage(content=\"Tell me a joke\"),\n",
+    "    HumanMessage(content=\"What is capital of Russia?\"),\n",
     "]\n",
     "\n",
-    "print(chat(messages).content)"
+    "print(chat.invoke(messages).content)"
    ]
   }
  ],

diff --git a/docs/docs/integrations/llms/gigachat.ipynb b/docs/docs/integrations/llms/gigachat.ipynb
@@ -15,7 +15,10 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
-    "collapsed": true
+    "collapsed": true,
+    "pycharm": {
+     "is_executing": true
+    }
    },
    "outputs": [],
    "source": [
@@ -28,13 +31,14 @@
     "collapsed": false
    },
    "source": [
-    "To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/api/integration)\n",
+    "To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
+    "\n",
     "## Example"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 2,
    "metadata": {
     "collapsed": false
    },
@@ -48,20 +52,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
     "from langchain_community.llms import GigaChat\n",
     "\n",
-    "llm = GigaChat(verify_ssl_certs=False)"
+    "llm = GigaChat(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 9,
    "metadata": {
     "collapsed": false
    },
@@ -84,8 +88,8 @@
     "\n",
     "llm_chain = LLMChain(prompt=prompt, llm=llm)\n",
     "\n",
-    "generated = llm_chain.run(country=\"Russia\")\n",
-    "print(generated)"
+    "generated = llm_chain.invoke(input={\"country\": \"Russia\"})\n",
+    "print(generated[\"text\"])"
    ]
   }
  ],

diff --git a/docs/docs/integrations/providers/salute_devices.mdx b/docs/docs/integrations/providers/salute_devices.mdx
@@ -26,4 +26,12 @@ See a [usage example](/docs/integrations/chat/gigachat).
 
 ```python
 from langchain_community.chat_models import GigaChat
+```
+
+## Embeddings
+
+See a [usage example](/docs/integrations/text_embedding/gigachat).
+
+```python
+from langchain_community.embeddings import GigaChatEmbeddings
 ```
diff --git a/docs/docs/integrations/text_embedding/gigachat.ipynb b/docs/docs/integrations/text_embedding/gigachat.ipynb
@@ -0,0 +1,116 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "source": [
+    "# GigaChat\n",
+    "This notebook shows how to use LangChain with [GigaChat embeddings](https://developers.sber.ru/portal/products/gigachat).\n",
+    "To use you need to install ```gigachat``` python package."
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "%pip install --upgrade --quiet  gigachat"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "markdown",
+   "source": [
+    "To get GigaChat credentials you need to [create account](https://developers.sber.ru/studio/login) and [get access to API](https://developers.sber.ru/docs/ru/gigachat/individuals-quickstart)\n",
+    "\n",
+    "## Example"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "from getpass import getpass\n",
+    "\n",
+    "os.environ[\"GIGACHAT_CREDENTIALS\"] = getpass()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "outputs": [],
+   "source": [
+    "from langchain_community.embeddings import GigaChatEmbeddings\n",
+    "\n",
+    "embeddings = GigaChatEmbeddings(verify_ssl_certs=False, scope=\"GIGACHAT_API_PERS\")"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "outputs": [],
+   "source": [
+    "query_result = embeddings.embed_query(\"The quick brown fox jumps over the lazy dog\")"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "outputs": [
+    {
+     "data": {
+      "text/plain": "[0.8398333191871643,\n -0.14180311560630798,\n -0.6161925792694092,\n -0.17103666067123413,\n 1.2884578704833984]"
+     },
+     "execution_count": 8,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "query_result[:5]"
+   ],
+   "metadata": {
+    "collapsed": false
+   }
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 2
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython2",
+   "version": "2.7.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}