Merge branch 'master' into eugene/extraction_use_Case

langchain-ai · Mar 5, 2024 · 94b46d5 · 94b46d5
2 parents a8ec227 + e1924b3
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diff --git a/.github/workflows/codespell.yml b/.github/workflows/codespell.yml
@@ -32,6 +32,6 @@ jobs:
       - name: Codespell
         uses: codespell-project/actions-codespell@v2
         with:
-          skip: guide_imports.json,*.ambr,./cookbook/data/imdb_top_1000.csv
+          skip: guide_imports.json,*.ambr,./cookbook/data/imdb_top_1000.csv,*.lock
           ignore_words_list: ${{ steps.extract_ignore_words.outputs.ignore_words_list }}
           exclude_file: libs/community/langchain_community/llms/yuan2.py
diff --git a/cookbook/RAPTOR.ipynb b/cookbook/RAPTOR.ipynb
diff --git a/cookbook/llm_checker.ipynb b/cookbook/llm_checker.ipynb
@@ -50,7 +50,7 @@
     "\n",
     "checker_chain = LLMCheckerChain.from_llm(llm, verbose=True)\n",
     "\n",
-    "checker_chain.run(text)"
+    "checker_chain.invoke(text)"
    ]
   },
   {

diff --git a/cookbook/llm_math.ipynb b/cookbook/llm_math.ipynb
@@ -51,7 +51,7 @@
     "llm = OpenAI(temperature=0)\n",
     "llm_math = LLMMathChain.from_llm(llm, verbose=True)\n",
     "\n",
-    "llm_math.run(\"What is 13 raised to the .3432 power?\")"
+    "llm_math.invoke(\"What is 13 raised to the .3432 power?\")"
    ]
   },
   {

diff --git a/docs/.yarnrc.yml b/docs/.yarnrc.yml
@@ -0,0 +1 @@
+nodeLinker: node-modules
diff --git a/docs/docs/get_started/introduction.mdx b/docs/docs/get_started/introduction.mdx
@@ -14,7 +14,16 @@ This framework consists of several parts.
 - **[LangServe](/docs/langserve)**: A library for deploying LangChain chains as a REST API.
 - **[LangSmith](/docs/langsmith)**: A developer platform that lets you debug, test, evaluate, and monitor chains built on any LLM framework and seamlessly integrates with LangChain.
 
-![Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers.](/svg/langchain_stack.svg "LangChain Framework Overview")
+import ThemedImage from '@theme/ThemedImage';
+
+<ThemedImage
+  alt="Diagram outlining the hierarchical organization of the LangChain framework, displaying the interconnected parts across multiple layers."
+  sources={{
+    light: '/svg/langchain_stack.svg',
+    dark: '/svg/langchain_stack_dark.svg',
+  }}
+  title="LangChain Framework Overview"
+/>
 
 Together, these products simplify the entire application lifecycle:
 - **Develop**: Write your applications in LangChain/LangChain.js. Hit the ground running using Templates for reference.

diff --git a/docs/docs/get_started/quickstart.mdx b/docs/docs/get_started/quickstart.mdx
@@ -134,7 +134,7 @@ We can then initialize the model:
 ```python
 from langchain_anthropic import ChatAnthropic
 
-llm = ChatAnthropic(model="claude-2.1", temperature=0.2, max_tokens=1024)
+llm = ChatAnthropic(model="claude-3-sonnet-20240229", temperature=0.2, max_tokens=1024)
 ```
 
 If you'd prefer not to set an environment variable you can pass the key in directly via the `anthropic_api_key` named parameter when initiating the Anthropic Chat Model class:

diff --git a/docs/docs/integrations/chat/anthropic.ipynb b/docs/docs/integrations/chat/anthropic.ipynb
diff --git a/docs/docs/integrations/chat/anthropic_functions.ipynb b/docs/docs/integrations/chat/anthropic_functions.ipynb
@@ -5,9 +5,13 @@
    "id": "5125a1e3",
    "metadata": {},
    "source": [
-    "# Anthropic Functions\n",
+    "# Anthropic Tools\n",
     "\n",
-    "This notebook shows how to use an experimental wrapper around Anthropic that gives it the same API as OpenAI Functions."
+    "This notebook shows how to use an experimental wrapper around Anthropic that gives it tool calling and structured output capabilities. It follows Anthropic's guide [here](https://docs.anthropic.com/claude/docs/functions-external-tools)\n",
+    "\n",
+    "The wrapper is available from the `langchain-anthropic` package, and it also requires the optional dependency `defusedxml` for parsing XML output from the llm.\n",
+    "\n",
+    "Note: this is a beta feature that will be replaced by Anthropic's formal implementation of tool calling, but it is useful for testing and experimentation in the meantime."
    ]
   },
   {
@@ -17,225 +21,82 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain_experimental.llms.anthropic_functions import AnthropicFunctions"
+    "%pip install -qU langchain-anthropic defusedxml\n",
+    "from langchain_anthropic.experimental import ChatAnthropicTools"
    ]
   },
   {
    "cell_type": "markdown",
    "id": "65499965",
    "metadata": {},
    "source": [
-    "## Initialize Model\n",
-    "\n",
-    "You can initialize this wrapper the same way you'd initialize ChatAnthropic"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "e1d535f6",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "model = AnthropicFunctions(model=\"claude-2\")"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "fcc9eaf4",
-   "metadata": {},
-   "source": [
-    "## Passing in functions\n",
+    "## Tool Binding\n",
     "\n",
-    "You can now pass in functions in a similar way"
+    "`ChatAnthropicTools` exposes a `bind_tools` method that allows you to pass in Pydantic models or BaseTools to the llm."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "0779c320",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "functions = [\n",
-    "    {\n",
-    "        \"name\": \"get_current_weather\",\n",
-    "        \"description\": \"Get the current weather in a given location\",\n",
-    "        \"parameters\": {\n",
-    "            \"type\": \"object\",\n",
-    "            \"properties\": {\n",
-    "                \"location\": {\n",
-    "                    \"type\": \"string\",\n",
-    "                    \"description\": \"The city and state, e.g. San Francisco, CA\",\n",
-    "                },\n",
-    "                \"unit\": {\"type\": \"string\", \"enum\": [\"celsius\", \"fahrenheit\"]},\n",
-    "            },\n",
-    "            \"required\": [\"location\"],\n",
-    "        },\n",
-    "    }\n",
-    "]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "ad75a933",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain_core.messages import HumanMessage"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "fc703085",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "response = model.invoke(\n",
-    "    [HumanMessage(content=\"whats the weater in boston?\")], functions=functions\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "04d7936a",
+   "id": "e1d535f6",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "AIMessage(content=' ', additional_kwargs={'function_call': {'name': 'get_current_weather', 'arguments': '{\"location\": \"Boston, MA\", \"unit\": \"fahrenheit\"}'}}, example=False)"
+       "AIMessage(content='', additional_kwargs={'tool_calls': [{'function': {'name': 'Person', 'arguments': '{\"name\": \"Erick\", \"age\": \"27\"}'}, 'type': 'function'}]})"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 3,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "response"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "0072fdba",
-   "metadata": {},
-   "source": [
-    "## Using for extraction\n",
+    "from langchain_core.pydantic_v1 import BaseModel\n",
     "\n",
-    "You can now use this for extraction."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "7af5c567",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain.chains import create_extraction_chain\n",
     "\n",
-    "schema = {\n",
-    "    \"properties\": {\n",
-    "        \"name\": {\"type\": \"string\"},\n",
-    "        \"height\": {\"type\": \"integer\"},\n",
-    "        \"hair_color\": {\"type\": \"string\"},\n",
-    "    },\n",
-    "    \"required\": [\"name\", \"height\"],\n",
-    "}\n",
-    "inp = \"\"\"\n",
-    "Alex is 5 feet tall. Claudia is 1 feet taller Alex and jumps higher than him. Claudia is a brunette and Alex is blonde.\n",
-    "        \"\"\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "bd01082a",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "chain = create_extraction_chain(schema, model)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "b5a23e9f",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "chain.invoke(inp)"
+    "class Person(BaseModel):\n",
+    "    name: str\n",
+    "    age: int\n",
+    "\n",
+    "\n",
+    "model = ChatAnthropicTools(model=\"claude-3-opus-20240229\").bind_tools(tools=[Person])\n",
+    "model.invoke(\"I am a 27 year old named Erick\")"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "90ec959e",
+   "id": "fcc9eaf4",
    "metadata": {},
    "source": [
-    "## Using for tagging\n",
+    "## Structured Output\n",
     "\n",
-    "You can now use this for tagging"
+    "`ChatAnthropicTools` also implements the [`with_structured_output` spec](/docs/guides/structured_output) for extracting values. Note: this may not be as stable as with models that explicitly offer tool calling."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
-   "id": "03c1eb0d",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from langchain.chains import create_tagging_chain"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 12,
-   "id": "581c0ece",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "schema = {\n",
-    "    \"properties\": {\n",
-    "        \"sentiment\": {\"type\": \"string\"},\n",
-    "        \"aggressiveness\": {\"type\": \"integer\"},\n",
-    "        \"language\": {\"type\": \"string\"},\n",
-    "    }\n",
-    "}"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 14,
-   "id": "d9a8570e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "chain = create_tagging_chain(schema, model)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 15,
-   "id": "cf37d679",
+   "execution_count": 4,
+   "id": "0779c320",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'sentiment': 'positive', 'aggressiveness': '0', 'language': 'english'}"
+       "Person(name='Erick', age=27)"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "chain.invoke(\"this is really cool\")"
+    "chain = ChatAnthropicTools(model=\"claude-3-opus-20240229\").with_structured_output(\n",
+    "    Person\n",
+    ")\n",
+    "chain.invoke(\"I am a 27 year old named Erick\")"
    ]
   }
  ],
@@ -255,7 +116,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.0"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,

diff --git a/docs/docs/integrations/document_loaders/telegram.ipynb b/docs/docs/integrations/document_loaders/telegram.ipynb
@@ -80,7 +80,7 @@
     "    chat_entity=\"<CHAT_URL>\",  # recommended to use Entity here\n",
     "    api_hash=\"<API HASH >\",\n",
     "    api_id=\"<API_ID>\",\n",
-    "    user_name=\"\",  # needed only for caching the session.\n",
+    "    username=\"\",  # needed only for caching the session.\n",
     ")"
    ]
   },

diff --git a/docs/docs/integrations/llms/anthropic.ipynb b/docs/docs/integrations/llms/anthropic.ipynb
@@ -19,6 +19,8 @@
     "\n",
     "This example goes over how to use LangChain to interact with `Anthropic` models.\n",
     "\n",
+    "NOTE: AnthropicLLM only supports legacy Claude 2 models. To use the newest Claude 3 models, please use [`ChatAnthropic`](/docs/integrations/chat/anthropic) instead.\n",
+    "\n",
     "## Installation"
    ]
   },

diff --git a/docs/docs/integrations/memory/mongodb_chat_message_history.ipynb b/docs/docs/integrations/memory/mongodb_chat_message_history.ipynb
@@ -21,10 +21,10 @@
    "source": [
     "## Setup\n",
     "\n",
-    "The integration lives in the `langchain-community` package, so we need to install that. We also need to install the `pymongo` package.\n",
+    "The integration lives in the `langchain-mongodb` package, so we need to install that.\n",
     "\n",
     "```bash\n",
-    "pip install -U --quiet langchain-community pymongo\n",
+    "pip install -U --quiet langchain-mongodb\n",
     "```"
    ]
   },
@@ -80,7 +80,7 @@
    },
    "outputs": [],
    "source": [
-    "from langchain_community.chat_message_histories import MongoDBChatMessageHistory\n",
+    "from langchain_mongodb.chat_message_histories import MongoDBChatMessageHistory\n",
     "\n",
     "chat_message_history = MongoDBChatMessageHistory(\n",
     "    session_id=\"test_session\",\n",

diff --git a/docs/docs/integrations/platforms/anthropic.mdx b/docs/docs/integrations/platforms/anthropic.mdx
@@ -26,7 +26,7 @@ You can import this wrapper with the following code:
 
 ```
 from langchain_anthropic import ChatAnthropic
-model = ChatAnthropic(model='claude-2.1')
+model = ChatAnthropic(model='claude-3-opus-20240229')
 ```
 
 Read more in the [ChatAnthropic documentation](/docs/integrations/chat/anthropic).

diff --git a/docs/docs/integrations/platforms/index.mdx b/docs/docs/integrations/platforms/index.mdx
@@ -16,6 +16,7 @@ These providers have standalone `langchain-{provider}` packages for improved ver
 - [Astra DB](/docs/integrations/providers/astradb)
 - [Exa Search](/docs/integrations/providers/exa_search)
 - [Google](/docs/integrations/platforms/google)
+- [Groq](/docs/integrations/providers/groq)
 - [IBM](/docs/integrations/providers/ibm)
 - [MistralAI](/docs/integrations/providers/mistralai)
 - [Nomic](/docs/integrations/providers/nomic)