various templates improvements (#12500)

templates/extraction-anthropic-functions/LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2023 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.

templates/extraction-anthropic-functions/README.md

@@ -0,0 +1,14 @@
+# Extraction with Anthropic Function Calling
+
+This template enables [Anthropic function calling](https://python.langchain.com/docs/integrations/chat/extraction_anthropic_functions).
+This is a wrapper around Anthropic's API that uses prompting and output parsing to replicate the OpenAI functions experience.
+
+Specify the information you want to extract in `chain.py`
+
+By default, it will extract the title and author of papers.
+
+##  LLM
+
+This template will use `Claude2` by default. 
+
+Be sure that `ANTHROPIC_API_KEY` is set in your enviorment.

templates/extraction-anthropic-functions/extraction_anthropic_functions.ipynb

@@ -0,0 +1,83 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4ae4b789",
+   "metadata": {},
+   "source": [
+    "## Document Loading\n",
+    "\n",
+    "Load a blog post on agents."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5d6bd62e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.document_loaders import WebBaseLoader\n",
+    "loader = WebBaseLoader(\"https://lilianweng.github.io/posts/2023-06-23-agent/\")\n",
+    "text = loader.load()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "8e21575d",
+   "metadata": {},
+   "source": [
+    "## Run Template\n",
+    "\n",
+    "As shown in the README, add template and start server:\n",
+    "```\n",
+    "langchain serve add extraction-anthropic-functions\n",
+    "langchain start\n",
+    "```\n",
+    "\n",
+    "We can now look at the endpoints:\n",
+    "\n",
+    "http://127.0.0.1:8000/docs#\n",
+    "\n",
+    "And specifically at our loaded template:\n",
+    "\n",
+    "http://127.0.0.1:8000/docs#/default/invoke_extraction-anthropic-functions_invoke_post\n",
+    " \n",
+    "We can also use remote runnable to call it:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "92edba86",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langserve.client import RemoteRunnable\n",
+    "anthropic_function_model = RemoteRunnable('http://localhost:8000/extraction-anthropic-functions')\n",
+    "anthropic_function_model.invoke(text[0].page_content[0:1500])"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "langserve",
+   "language": "python",
+   "name": "langserve"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

templates/extraction-anthropic-functions/extraction_anthropic_functions/__init__.py

@@ -0,0 +1,3 @@
+from extraction_anthropic_functions.chain import chain
+
+__all__ = ["chain"]

templates/extraction-anthropic-functions/extraction_anthropic_functions/chain.py

@@ -0,0 +1,38 @@
+from typing import List, Optional
+
+from langchain.output_parsers.openai_functions import JsonKeyOutputFunctionsParser
+from langchain.prompts import ChatPromptTemplate
+from langchain.pydantic_v1 import BaseModel
+from langchain.utils.openai_functions import convert_pydantic_to_openai_function
+from langchain_experimental.llms.anthropic_functions import AnthropicFunctions
+
+template = """A article will be passed to you. Extract from it all papers that are mentioned by this article. 
+
+Do not extract the name of the article itself. If no papers are mentioned that's fine - you don't need to extract any! Just return an empty list.
+
+Do not make up or guess ANY extra information. Only extract what exactly is in the text."""  # noqa: E501
+
+prompt = ChatPromptTemplate.from_messages([("system", template), ("human", "{input}")])
+
+
+# Function output schema
+class Paper(BaseModel):
+    """Information about papers mentioned."""
+
+    title: str
+    author: Optional[str]
+
+
+class Info(BaseModel):
+    """Information to extract"""
+
+    papers: List[Paper]
+
+
+# Function definition
+model = AnthropicFunctions()
+function = [convert_pydantic_to_openai_function(Info)]
+
+chain = prompt | model.bind(
+    functions=function, function_call={"name": "Info"}
+) | JsonKeyOutputFunctionsParser(key_name="papers")

templates/extraction-anthropic-functions/pyproject.toml

@@ -0,0 +1,21 @@
+[tool.poetry]
+name = "extraction-anthropic-functions"
+version = "0.1.0"
+description = ""
+authors = ["Lance Martin <lance@langchain.dev>"]
+readme = "README.md"
+
+[tool.poetry.dependencies]
+python = ">=3.8.1,<4.0"
+langchain = ">=0.0.322"
+anthropic = ">=0.5.0"
+langchainhub = ">=0.1.13"
+langchain-experimental = "^0.0.36"
+
+[tool.langserve]
+export_module = "extraction_anthropic_functions"
+export_attr = "chain"
+
+[build-system]
+requires = ["poetry-core"]
+build-backend = "poetry.core.masonry.api"