embeddings) result = vectorstore.as_retriever().get_relevant_documents("用户注册资格") print(result...
LangChain 是基于提示词工程(Prompt Engineering),提供一个桥接大型语言模型(LLMs)以及实际应用App的胶水层框架。 LangChain中的模块,每个模块如何使用? 前提:运行一下代码,需要OPENAI_API_KEY(OpenAI申请的key),同时统一引入这些库: # 导入LLM包装器 from langchain import OpenAI, ConversationChain from langchain....
As an open source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infra, or better documentation. For detailed information on how to contribute, seehere. ...
Let's take an example of a simple app that usesOPENAI_API_KEYstored as secrets. This app directory contains the following files: .├── main.py # The app ├── jcloud.yml # JCloud deployment config file ├── README.md # This README file ├── requirements.txt # The requirements...
LLMs in LangChain refer to pure text completion models. The APIs they wrap take a string prompt as input and output a string completion. OpenAI’s GPT-3 is implemented as an LLM. (LangChain中的LLMs指的是纯文本补全模型。它们包装的API将字符串提示作为输入并输出字符串完成。OpenAI 的 GPT-3...
部署:使用LangServe将任何链变成API。 jupyter 具体来说,该框架由以下开源库组成: langchain-core:基础抽象和LangChain表达式语言。 langchain-community:第三方集成。 合作伙伴包(例如langchain-openai,,langchain-anthropic等):一些集成已被进一步拆分为自己的轻量级包,仅依赖于langchain-core. ...
在本文范例,我们使用LangChain4J的高阶API来创建一个简单的Agent,用户通过Agent与ERNIE-Bot交互,并通过ERNIE-Bot的Function calling功能来调用工具(以下称为Tool,即外部API),模拟一个非常简单的本地商店发现与下单场景。范例的目的除了学习LangChain4J的Agent与Tool之基本开发外,还包括部分的协议追踪分析。我们使用Kotlin...
import streamlit as st import openai import qanda from vector_search import * from utils import * from io import StringIO # take openai api key in api_key = st.sidebar.text_input("Enter your OpenAI API key:", type='password')
Suppose that we want to try another prompt variation for our app. Adding a new prompt requires adding an alternative in the chain configuration and a new variation to the feature flag that references that alternative.As an example of an alternative prompt, we consider prompt that replies as an...
\n\nUse a json blob to specify a tool by providing an action key (tool name) and an action_input key (tool input).\n\nValid "action" values: "Final Answer" or Search movies, Calculator\n\nProvide only ONE action per $JSON_BLOB, as shown:\n\n```\n{\n "action":...