id stringlengths 14 16 | text stringlengths 29 2.73k | source stringlengths 49 117 |
|---|---|---|
a14e5c2ac01f-4 | chain({"input_documents": docs, "question": query}, return_only_outputs=True)
{'intermediate_steps': ["\nStasera vorrei onorare qualcuno che ha dedicato la sua vita a servire questo paese: il giustizia Stephen Breyer - un veterano dell'esercito, uno studioso costituzionale e un giustizia in uscita della Corte Suprema d... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-5 | chain({"input_documents": docs, "question": query}, return_only_outputs=True)
{'output_text': '\n\nThe president said that he wanted to honor Justice Breyer for his dedication to serving the country, his legacy of excellence, and his commitment to advancing liberty and justice, as well as for his support of the Equalit... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-6 | '\n\nThe president said that he wanted to honor Justice Breyer for his dedication to serving the country, his legacy of excellence, and his commitment to advancing liberty and justice, as well as for his support of the Equality Act and his commitment to protecting the rights of LGBTQ+ Americans. He also praised Justice... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-7 | )
initial_qa_template = (
"Context information is below. \n"
"---------------------\n"
"{context_str}"
"\n---------------------\n"
"Given the context information and not prior knowledge, "
"answer the question: {question}\nYour answer should be in Italian.\n"
)
initial_qa_prompt = PromptTemplate... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-8 | "\nIl presidente ha detto che Justice Breyer ha dedicato la sua vita al servizio di questo paese, ha reso omaggio al suo servizio e ha sostenuto la nomina di una top litigatrice in pratica privata, un ex difensore pubblico federale e una famiglia di insegnanti e agenti di polizia delle scuole pubbliche. Ha anche sottol... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-9 | 'output_text': "\n\nIl presidente ha detto che Justice Breyer ha dedicato la sua vita al servizio di questo paese, ha reso omaggio al suo servizio e ha sostenuto la nomina di una top litigatrice in pratica privata, un ex difensore pubblico federale e una famiglia di insegnanti e agenti di polizia delle scuole pubbliche... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-10 | {'answer': ' This document does not answer the question', 'score': '0'},
{'answer': ' This document does not answer the question', 'score': '0'},
{'answer': ' This document does not answer the question', 'score': '0'}]
Custom Prompts
You can also use your own prompts with this chain. In this example, we will respond ... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
a14e5c2ac01f-11 | 'score': '100'},
{'answer': ' Il presidente non ha detto nulla sulla Giustizia Breyer.',
'score': '100'},
{'answer': ' Non so.', 'score': '0'},
{'answer': ' Non so.', 'score': '0'}],
'output_text': ' Il presidente ha detto che Justice Breyer ha dedicato la sua vita a servire questo paese.'}
previous
Question ... | https://python.langchain.com/en/latest/modules/chains/index_examples/question_answering.html |
911a949ecdf1-0 | .ipynb
.pdf
Hypothetical Document Embeddings
Contents
Multiple generations
Using our own prompts
Using HyDE
Hypothetical Document Embeddings#
This notebook goes over how to use Hypothetical Document Embeddings (HyDE), as described in this paper.
At a high level, HyDE is an embedding technique that takes queries, gene... | https://python.langchain.com/en/latest/modules/chains/index_examples/hyde.html |
911a949ecdf1-1 | result = embeddings.embed_query("Where is the Taj Mahal?")
Using our own prompts#
Besides using preconfigured prompts, we can also easily construct our own prompts and use those in the LLMChain that is generating the documents. This can be useful if we know the domain our queries will be in, as we can condition the pro... | https://python.langchain.com/en/latest/modules/chains/index_examples/hyde.html |
911a949ecdf1-2 | Using DuckDB in-memory for database. Data will be transient.
print(docs[0].page_content)
In state after state, new laws have been passed, not only to suppress the vote, but to subvert entire elections.
We cannot let this happen.
Tonight. I call on the Senate to: Pass the Freedom to Vote Act. Pass the John Lewis Votin... | https://python.langchain.com/en/latest/modules/chains/index_examples/hyde.html |
66d32eaceaaf-0 | .ipynb
.pdf
Summarization
Contents
Prepare Data
Quickstart
The stuff Chain
The map_reduce Chain
The refine Chain
Summarization#
This notebook walks through how to use LangChain for summarization over a list of documents. It covers three different chain types: stuff, map_reduce, and refine. For a more in depth explana... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-1 | chain.run(docs)
' In response to Russian aggression in Ukraine, the United States and its allies are taking action to hold Putin accountable, including economic sanctions, asset seizures, and military assistance. The US is also providing economic and humanitarian aid to Ukraine, and has passed the American Rescue Plan ... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-2 | chain.run(docs)
"\n\nIn questa serata, il Presidente degli Stati Uniti ha annunciato una serie di misure per affrontare la crisi in Ucraina, causata dall'aggressione di Putin. Ha anche annunciato l'invio di aiuti economici, militari e umanitari all'Ucraina. Ha anche annunciato che gli Stati Uniti e i loro alleati stann... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-3 | chain = load_summarize_chain(OpenAI(temperature=0), chain_type="map_reduce", return_intermediate_steps=True)
chain({"input_documents": docs}, return_only_outputs=True)
{'map_steps': [" In response to Russia's aggression in Ukraine, the United States has united with other freedom-loving nations to impose economic sancti... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-4 | prompt_template = """Write a concise summary of the following:
{text}
CONCISE SUMMARY IN ITALIAN:"""
PROMPT = PromptTemplate(template=prompt_template, input_variables=["text"])
chain = load_summarize_chain(OpenAI(temperature=0), chain_type="map_reduce", return_intermediate_steps=True, map_prompt=PROMPT, combine_prompt=... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-5 | "\n\nStiamo unendo le nostre forze con quelle dei nostri alleati europei per sequestrare yacht, appartamenti di lusso e jet privati di Putin. Abbiamo chiuso lo spazio aereo americano ai voli russi e stiamo fornendo più di un miliardo di dollari in assistenza all'Ucraina. Abbiamo anche mobilitato le nostre forze terrest... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-6 | "\n\nIl Presidente Biden ha lottato per passare l'American Rescue Plan per aiutare le persone che soffrivano a causa della pandemia. Il piano ha fornito sollievo economico immediato a milioni di americani, ha aiutato a mettere cibo sulla loro tavola, a mantenere un tetto sopra le loro teste e a ridurre il costo dell'as... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-7 | The refine Chain#
This sections shows results of using the refine Chain to do summarization.
chain = load_summarize_chain(llm, chain_type="refine")
chain.run(docs)
"\n\nIn response to Russia's aggression in Ukraine, the United States has united with other freedom-loving nations to impose economic sanctions and hold Put... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-8 | chain({"input_documents": docs}, return_only_outputs=True)
{'refine_steps': [" In response to Russia's aggression in Ukraine, the United States has united with other freedom-loving nations to impose economic sanctions and hold Putin accountable. The U.S. Department of Justice is also assembling a task force to go after... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-9 | "\n\nIn response to Russia's aggression in Ukraine, the United States has united with other freedom-loving nations to impose economic sanctions and hold Putin accountable. The U.S. Department of Justice is also assembling a task force to go after the crimes of Russian oligarchs and seize their ill-gotten gains. We are ... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-10 | 'output_text': "\n\nIn response to Russia's aggression in Ukraine, the United States has united with other freedom-loving nations to impose economic sanctions and hold Putin accountable. The U.S. Department of Justice is also assembling a task force to go after the crimes of Russian oligarchs and seize their ill-gotten... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-11 | "------------\n"
"{text}\n"
"------------\n"
"Given the new context, refine the original summary in Italian"
"If the context isn't useful, return the original summary."
)
refine_prompt = PromptTemplate(
input_variables=["existing_answer", "text"],
template=refine_template,
)
chain = load_summari... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-12 | "\n\nQuesta sera, ci incontriamo come democratici, repubblicani e indipendenti, ma soprattutto come americani. La Russia di Putin ha cercato di scuotere le fondamenta del mondo libero, ma ha sottovalutato la forza della gente ucraina. Insieme ai nostri alleati, stiamo imponendo sanzioni economiche, tagliando l'accesso ... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-13 | "\n\nQuesta sera, ci incontriamo come democratici, repubblicani e indipendenti, ma soprattutto come americani. La Russia di Putin ha cercato di scuotere le fondamenta del mondo libero, ma ha sottovalutato la forza della gente ucraina. Insieme ai nostri alleati, stiamo imponendo sanzioni economiche, tagliando l'accesso ... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
66d32eaceaaf-14 | 'output_text': "\n\nQuesta sera, ci incontriamo come democratici, repubblicani e indipendenti, ma soprattutto come americani. La Russia di Putin ha cercato di scuotere le fondamenta del mondo libero, ma ha sottovalutato la forza della gente ucraina. Insieme ai nostri alleati, stiamo imponendo sanzioni economiche, tagli... | https://python.langchain.com/en/latest/modules/chains/index_examples/summarize.html |
331e33b7a7ed-0 | .ipynb
.pdf
Retrieval Question/Answering
Contents
Chain Type
Custom Prompts
Return Source Documents
Retrieval Question/Answering#
This example showcases question answering over an index.
from langchain.embeddings.openai import OpenAIEmbeddings
from langchain.vectorstores import Chroma
from langchain.text_splitter imp... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
331e33b7a7ed-1 | There are two ways to load different chain types. First, you can specify the chain type argument in the from_chain_type method. This allows you to pass in the name of the chain type you want to use. For example, in the below we change the chain type to map_reduce.
qa = RetrievalQA.from_chain_type(llm=OpenAI(), chain_ty... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
331e33b7a7ed-2 | query = "What did the president say about Ketanji Brown Jackson"
qa.run(query)
" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, and from a family of public school educators and police officers. He also s... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
331e33b7a7ed-3 | Return Source Documents#
Additionally, we can return the source documents used to answer the question by specifying an optional parameter when constructing the chain.
qa = RetrievalQA.from_chain_type(llm=OpenAI(), chain_type="stuff", retriever=docsearch.as_retriever(), return_source_documents=True)
query = "What did th... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
331e33b7a7ed-4 | Document(page_content='A former top litigator in private practice. A former federal public defender. And from a family of public school educators and police officers. A consensus builder. Since she’s been nominated, she’s received a broad range of support—from the Fraternal Order of Police to former judges appointed by... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
331e33b7a7ed-5 | Document(page_content='And for our LGBTQ+ Americans, let’s finally get the bipartisan Equality Act to my desk. The onslaught of state laws targeting transgender Americans and their families is wrong. \n\nAs I said last year, especially to our younger transgender Americans, I will always have your back as your President... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
331e33b7a7ed-6 | Document(page_content='Tonight, I’m announcing a crackdown on these companies overcharging American businesses and consumers. \n\nAnd as Wall Street firms take over more nursing homes, quality in those homes has gone down and costs have gone up. \n\nThat ends on my watch. \n\nMedicare is going to set higher standards ... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_qa.html |
f755c0d9a7a6-0 | .ipynb
.pdf
Vector DB Text Generation
Contents
Prepare Data
Set Up Vector DB
Set Up LLM Chain with Custom Prompt
Generate Text
Vector DB Text Generation#
This notebook walks through how to use LangChain for text generation over a vector index. This is useful if we want to generate text that is able to draw from a lar... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-1 | relative_path = markdown_file.relative_to(repo_path)
github_url = f"https://github.com/{repo_owner}/{repo_name}/blob/{git_sha}/{relative_path}"
yield Document(page_content=f.read(), metadata={"source": github_url})
sources = get_github_docs("yirenlu92", "deno-manual-forked")
source_chunk... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-2 | chain = LLMChain(llm=llm, prompt=PROMPT)
Generate Text#
Finally, we write a function to apply our inputs to the chain. The function takes an input parameter topic. We find the documents in the vector index that correspond to that topic, and use them as additional context in our simple LLM chain.
def generate_blog_post(... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-3 | [{'text': '\n\nEnvironment variables are a great way to store and access sensitive information in your Deno applications. Deno offers built-in support for environment variables with `Deno.env`, and you can also use a `.env` file to store and access environment variables.\n\nUsing `Deno.env` is simple. It has getter and... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-4 | into the code. This makes it easier to change settings without having to modify the code.\n\nIn Deno, environment variables can be set in a few different ways. The most common way is to use the `VAR=value` syntax. This will set the environment variable `VAR` to the value `value`. This can be used to set any number of e... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-5 | to hard-code it into their applications. In Deno, you can access environment variables using the `Deno.env.get()` function.\n\nFor example, if you wanted to access the `HOME` environment variable, you could do so like this:\n\n```js\n// env.js\nDeno.env.get("HOME");\n```\n\nWhen running this code, you\'ll need to grant... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-6 | variables are an important part of any programming language, and Deno is no exception. Deno is a secure JavaScript and TypeScript runtime built on the V8 JavaScript engine, and it recently added support for environment variables. This feature was added in Deno version 1.6.0, and it is now available for use in Deno appl... | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-7 | example, if you wanted to set the `FOO` environment variable to `bar`, you would use the following code:\n\n```'}] | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
f755c0d9a7a6-8 | previous
Retrieval Question Answering with Sources
next
API Chains
Contents
Prepare Data
Set Up Vector DB
Set Up LLM Chain with Custom Prompt
Generate Text
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/modules/chains/index_examples/vector_db_text_generation.html |
979c6b5378ad-0 | .ipynb
.pdf
FLARE
Contents
Imports
Retriever
FLARE Chain
FLARE#
This notebook is an implementation of Forward-Looking Active REtrieval augmented generation (FLARE).
Please see the original repo here.
The basic idea is:
Start answering a question
If you start generating tokens the model is uncertain about, look up rel... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-1 | min_prob: Any tokens generated with probability below this will be considered uncertain
Imports#
import os
os.environ["SERPER_API_KEY"] = ""
import re
import numpy as np
from langchain.schema import BaseRetriever
from langchain.utilities import GoogleSerperAPIWrapper
from langchain.embeddings import OpenAIEmbeddings
fr... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-2 | >>> RESPONSE:
> Entering new QuestionGeneratorChain chain...
Prompt after formatting:
Given a user input and an existing partial response as context, ask a question to which the answer is the given term/entity/phrase:
>>> USER INPUT: explain in great detail the difference between the langchain framework and baby agi
>... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-3 | Baby AGI, on the other hand, is an artificial general intelligence (AGI) platform. It uses a combination of deep learning and reinforcement learning to create an AI system that can learn and adapt to new tasks. Baby AGI is designed to be a general-purpose AI system that can be used for a variety of applications, includ... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-4 | >>> USER INPUT: explain in great detail the difference between the langchain framework and baby agi
>>> EXISTING PARTIAL RESPONSE:
The Langchain Framework is a decentralized platform for natural language processing (NLP) applications. It uses a blockchain-based distributed ledger to store and process data, allowing f... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-5 | Baby AGI, on the other hand, is an artificial general intelligence (AGI) platform. It uses a combination of deep learning and reinforcement learning to create an AI system that can learn and adapt to new tasks. Baby AGI is designed to be a general-purpose AI system that can be used for a variety of applications, includ... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-6 | >>> USER INPUT: explain in great detail the difference between the langchain framework and baby agi
>>> EXISTING PARTIAL RESPONSE:
The Langchain Framework is a decentralized platform for natural language processing (NLP) applications. It uses a blockchain-based distributed ledger to store and process data, allowing f... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-7 | Baby AGI, on the other hand, is an artificial general intelligence (AGI) platform. It uses a combination of deep learning and reinforcement learning to create an AI system that can learn and adapt to new tasks. Baby AGI is designed to be a general-purpose AI system that can be used for a variety of applications, includ... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-8 | >>> CONTEXT: LangChain: Software. LangChain is a software development framework designed to simplify the creation of applications using large language models. LangChain Initial release date: October 2022. LangChain Programming languages: Python and JavaScript. LangChain Developer(s): Harrison Chase. LangChain License: ... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-9 | LangChain is a framework for including AI from large language models inside data pipelines and applications. This tutorial provides an overview of what you ... Missing: secure | Must include:secure. Blockchain is the best way to secure the data of the shared community. Utilizing the capabilities of the blockchain nobod... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-10 | LangChain is a framework for including AI from large language models inside data pipelines and applications. This tutorial provides an overview of what you ... LangChain is an intuitive framework created to assist in developing applications driven by a language model, such as OpenAI or Hugging Face. This documentation ... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-11 | Blockchain is one type of a distributed ledger. Distributed ledgers use independent computers (referred to as nodes) to record, share and ... Missing: Langchain | Must include:Langchain. Blockchain is used in distributed storage software where huge data is broken down into chunks. This is available in encrypted data ac... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-12 | LangChain is an intuitive framework created to assist in developing applications driven by a language model, such as OpenAI or Hugging Face. Missing: decentralized | Must include:decentralized. LangChain, created by Harrison Chase, is a Python library that provides out-of-the-box support to build NLP applications using... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-13 | LangChain is a powerful tool that can be used to work with Large Language ... If an API key has been provided, create an OpenAI language model instance At its core, LangChain is a framework built around LLMs. We can use it for chatbots, Generative Question-Answering (GQA), summarization, and much more. A tutorial of th... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-14 | At its core, LangChain is a framework built around LLMs. We can use it for chatbots, Generative Question-Answering (GQA), summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.
>>> USER INPUT: explain in great detail... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-15 | llm = OpenAI()
llm(query)
'\n\nThe Langchain framework and Baby AGI are both artificial intelligence (AI) frameworks that are used to create intelligent agents. The Langchain framework is a supervised learning system that is based on the concept of “language chains”. It uses a set of rules to map natural language input... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-16 | >>> USER INPUT: how are the origin stories of langchain and bitcoin similar or different?
>>> EXISTING PARTIAL RESPONSE:
Langchain and Bitcoin have very different origin stories. Bitcoin was created by the mysterious Satoshi Nakamoto in 2008 as a decentralized digital currency. Langchain, on the other hand, was creat... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-17 | FINISHED
The question to which the answer is the term/entity/phrase " developers as a platform for creating and managing decentralized language learning applications." is:
> Finished chain.
Generated Questions: ['How would you describe the origin stories of Langchain and Bitcoin in terms of their similarities or differ... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-18 | >>> CONTEXT: Bitcoin and Ethereum have many similarities but different long-term visions and limitations. Ethereum changed from proof of work to proof of ... Bitcoin will be around for many years and examining its white paper origins is a great exercise in understanding why. Satoshi Nakamoto's blueprint describes ... B... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
979c6b5378ad-19 | At its core, LangChain is a framework built around LLMs. We can use it for chatbots, Generative Question-Answering (GQA), summarization, and much more. The core idea of the library is that we can “chain” together different components to create more advanced use cases around LLMs.
>>> USER INPUT: how are the origin stor... | https://python.langchain.com/en/latest/modules/chains/examples/flare.html |
2b235c39e35e-0 | .ipynb
.pdf
OpenAPI Chain
Contents
Load the spec
Select the Operation
Construct the chain
Return raw response
Example POST message
OpenAPI Chain#
This notebook shows an example of using an OpenAPI chain to call an endpoint in natural language, and get back a response in natural language.
from langchain.tools import O... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-1 | llm,
requests=Requests(),
verbose=True,
return_intermediate_steps=True # Return request and response text
)
output = chain("whats the most expensive shirt?")
> Entering new OpenAPIEndpointChain chain...
> Entering new APIRequesterChain chain...
Prompt after formatting:
You are a helpful AI Assistant. Plea... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-2 | ARGS: ```json
{valid json conforming to API_SCHEMA}
```
Example
-----
ARGS: ```json
{"foo": "bar", "baz": {"qux": "quux"}}
```
The block must be no more than 1 line long, and all arguments must be valid JSON. All string arguments must be wrapped in double quotes.
You MUST strictly comply to the types indicated by the p... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-3 | You attempted to call an API, which resulted in:
API_RESPONSE: {"products":[{"name":"Burberry Check Poplin Shirt","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201810981/Clothing/Burberry-Check-Poplin-Shirt/?utm_source=openai&ref-site=openai_plugin","price":"$360.00","attributes":["Material:Cotton","Target Grou... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-4 | 'response_text': '{"products":[{"name":"Burberry Check Poplin Shirt","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201810981/Clothing/Burberry-Check-Poplin-Shirt/?utm_source=openai&ref-site=openai_plugin","price":"$360.00","attributes":["Material:Cotton","Target Group:Man","Color:Gray,Blue,Beige","Properties:Po... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-5 | q: string,
/* number of products returned */
size?: number,
/* (Optional) Minimum price in local currency for the product searched for. Either explicitly stated by the user or implicitly inferred from a combination of the user's request and the kind of product searched for. */
min_price?: number,
/* (Optional) Maxi... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-6 | {"products":[{"name":"Burberry Check Poplin Shirt","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201810981/Clothing/Burberry-Check-Poplin-Shirt/?utm_source=openai&ref-site=openai_plugin","price":"$360.00","attributes":["Material:Cotton","Target Group:Man","Color:Gray,Blue,Beige","Properties:Pockets","Pattern:Ch... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-7 | Somerton Check Shirt - Camel","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201112728/Clothing/Burberry-Somerton-Check-Shirt-Camel/?utm_source=openai&ref-site=openai_plugin","price":"$450.00","attributes":["Material:Elastane/Lycra/Spandex,Cotton","Target Group:Man","Color:Beige"]},{"name":"Magellan Outdoors Lag... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-8 | > Finished chain.
output
{'instructions': 'whats the most expensive shirt?', | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-9 | 'output': '{"products":[{"name":"Burberry Check Poplin Shirt","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201810981/Clothing/Burberry-Check-Poplin-Shirt/?utm_source=openai&ref-site=openai_plugin","price":"$360.00","attributes":["Material:Cotton","Target Group:Man","Color:Gray,Blue,Beige","Properties:Pockets",... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-10 | Somerton Check Shirt - Camel","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201112728/Clothing/Burberry-Somerton-Check-Shirt-Camel/?utm_source=openai&ref-site=openai_plugin","price":"$450.00","attributes":["Material:Elastane/Lycra/Spandex,Cotton","Target Group:Man","Color:Beige"]},{"name":"Magellan Outdoors Lag... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-11 | 'intermediate_steps': {'request_args': '{"q": "shirt", "max_price": null}', | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-12 | 'response_text': '{"products":[{"name":"Burberry Check Poplin Shirt","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201810981/Clothing/Burberry-Check-Poplin-Shirt/?utm_source=openai&ref-site=openai_plugin","price":"$360.00","attributes":["Material:Cotton","Target Group:Man","Color:Gray,Blue,Beige","Properties:Po... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-13 | Somerton Check Shirt - Camel","url":"https://www.klarna.com/us/shopping/pl/cl10001/3201112728/Clothing/Burberry-Somerton-Check-Shirt-Camel/?utm_source=openai&ref-site=openai_plugin","price":"$450.00","attributes":["Material:Elastane/Lycra/Spandex,Cotton","Target Group:Man","Color:Beige"]},{"name":"Magellan Outdoors Lag... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-14 | Example POST message#
For this demo, we will interact with the speak API.
spec = OpenAPISpec.from_url("https://api.speak.com/openapi.yaml")
Attempting to load an OpenAPI 3.0.1 spec. This may result in degraded performance. Convert your OpenAPI spec to 3.1.* spec for better support.
Attempting to load an OpenAPI 3.0.1 ... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-15 | learning_language?: string,
/* The user's native language. Infer this value from the language the user asked their question in. Always use the full name of the language (e.g. Spanish, French). */
native_language?: string,
/* A description of any additional context in the user's question that could affect the explanat... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-16 | {"explanation":"<what-to-say language=\"Hindi\" context=\"None\">\nऔर चाय लाओ। (Aur chai lao.) \n</what-to-say>\n\n<alternatives context=\"None\">\n1. \"चाय थोड़ी ज्यादा मिल सकती है?\" *(Chai thodi zyada mil sakti hai? - Polite, asking if more tea is available)*\n2. \"मुझे महसूस हो रहा है कि मुझे कुछ अन्य प्रकार की चाय... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-17 | tone, asking for an extra serving of milk or tea powder)*\n</alternatives>\n\n<usage-notes>\nIn India and Indian culture, serving guests with food and beverages holds great importance in hospitality. You will find people always offering drinks like water or tea to their guests as soon as they arrive at their house or o... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-18 | an issue or leave feedback](https://speak.com/chatgpt?rid=d4mcapbkopo164pqpbk321oc})*","extra_response_instructions":"Use all information in the API response and fully render all Markdown.\nAlways end your response with a link to report an issue or leave feedback on the plugin."} | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-19 | > Entering new APIResponderChain chain...
Prompt after formatting:
You are a helpful AI assistant trained to answer user queries from API responses.
You attempted to call an API, which resulted in: | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-20 | API_RESPONSE: {"explanation":"<what-to-say language=\"Hindi\" context=\"None\">\nऔर चाय लाओ। (Aur chai lao.) \n</what-to-say>\n\n<alternatives context=\"None\">\n1. \"चाय थोड़ी ज्यादा मिल सकती है?\" *(Chai thodi zyada mil sakti hai? - Polite, asking if more tea is available)*\n2. \"मुझे महसूस हो रहा है कि मुझे कुछ अन्य... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-21 | tone, asking for an extra serving of milk or tea powder)*\n</alternatives>\n\n<usage-notes>\nIn India and Indian culture, serving guests with food and beverages holds great importance in hospitality. You will find people always offering drinks like water or tea to their guests as soon as they arrive at their house or o... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-22 | an issue or leave feedback](https://speak.com/chatgpt?rid=d4mcapbkopo164pqpbk321oc})*","extra_response_instructions":"Use all information in the API response and fully render all Markdown.\nAlways end your response with a link to report an issue or leave feedback on the plugin."} | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-23 | USER_COMMENT: "How would ask for more tea in Delhi?"
If the API_RESPONSE can answer the USER_COMMENT respond with the following markdown json block:
Response: ```json
{"response": "Concise response to USER_COMMENT based on API_RESPONSE."}
```
Otherwise respond with the following markdown json block:
Response Error: ```... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-24 | '{"explanation":"<what-to-say language=\\"Hindi\\" context=\\"None\\">\\nऔर चाय लाओ। (Aur chai lao.) \\n</what-to-say>\\n\\n<alternatives context=\\"None\\">\\n1. \\"चाय थोड़ी ज्यादा मिल सकती है?\\" *(Chai thodi zyada mil sakti hai? - Polite, asking if more tea is available)*\\n2. \\"मुझे महसूस हो रहा है कि मुझे कुछ अन... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-25 | - Very informal/casual tone, asking for an extra serving of milk or tea powder)*\\n</alternatives>\\n\\n<usage-notes>\\nIn India and Indian culture, serving guests with food and beverages holds great importance in hospitality. You will find people always offering drinks like water or tea to their guests as soon as they... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-26 | add a little extra in the quantity of tea as well.)\\n</example-convo>\\n\\n*[Report an issue or leave feedback](https://speak.com/chatgpt?rid=d4mcapbkopo164pqpbk321oc})*","extra_response_instructions":"Use all information in the API response and fully render all Markdown.\\nAlways end your response with a link to repo... | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
2b235c39e35e-27 | previous
Router Chains: Selecting from multiple prompts with MultiRetrievalQAChain
next
PAL
Contents
Load the spec
Select the Operation
Construct the chain
Return raw response
Example POST message
By Harrison Chase
© Copyright 2023, Harrison Chase.
Last updated on May 29, 2023. | https://python.langchain.com/en/latest/modules/chains/examples/openapi.html |
3b8febabf493-0 | .ipynb
.pdf
LLMRequestsChain
LLMRequestsChain#
Using the request library to get HTML results from a URL and then an LLM to parse results
from langchain.llms import OpenAI
from langchain.chains import LLMRequestsChain, LLMChain
from langchain.prompts import PromptTemplate
template = """Between >>> and <<< are the raw se... | https://python.langchain.com/en/latest/modules/chains/examples/llm_requests.html |
5dc7e847d77d-0 | .ipynb
.pdf
LLM Math
LLM Math#
This notebook showcases using LLMs and Python REPLs to do complex word math problems.
from langchain import OpenAI, LLMMathChain
llm = OpenAI(temperature=0)
llm_math = LLMMathChain.from_llm(llm, verbose=True)
llm_math.run("What is 13 raised to the .3432 power?")
> Entering new LLMMathChai... | https://python.langchain.com/en/latest/modules/chains/examples/llm_math.html |
6ade9830a1f8-0 | .ipynb
.pdf
Router Chains: Selecting from multiple prompts with MultiRetrievalQAChain
Router Chains: Selecting from multiple prompts with MultiRetrievalQAChain#
This notebook demonstrates how to use the RouterChain paradigm to create a chain that dynamically selects which Retrieval system to use. Specifically we show h... | https://python.langchain.com/en/latest/modules/chains/examples/multi_retrieval_qa_router.html |
6ade9830a1f8-1 | "retriever": sou_retriever
},
{
"name": "pg essay",
"description": "Good for answer quesitons about Paul Graham's essay on his career",
"retriever": pg_retriever
},
{
"name": "personal",
"description": "Good for answering questions about me",
"retrieve... | https://python.langchain.com/en/latest/modules/chains/examples/multi_retrieval_qa_router.html |
6ade9830a1f8-2 | > Finished chain.
Your background is Peruvian.
print(chain.run("What year was the Internet created in?"))
> Entering new MultiRetrievalQAChain chain...
None: {'query': 'What year was the Internet created in?'}
> Finished chain.
The Internet was created in 1969 through a project called ARPANET, which was funded by the ... | https://python.langchain.com/en/latest/modules/chains/examples/multi_retrieval_qa_router.html |
36c66e32a99c-0 | .ipynb
.pdf
SQL Chain example
Contents
Use Query Checker
Customize Prompt
Return Intermediate Steps
Choosing how to limit the number of rows returned
Adding example rows from each table
Custom Table Info
SQLDatabaseSequentialChain
Using Local Language Models
SQL Chain example#
This example demonstrates the use of the... | https://python.langchain.com/en/latest/modules/chains/examples/sqlite.html |
36c66e32a99c-1 | db_chain.run("How many employees are there?")
> Entering new SQLDatabaseChain chain...
How many employees are there?
SQLQuery:
/workspace/langchain/langchain/sql_database.py:191: SAWarning: Dialect sqlite+pysqlite does *not* support Decimal objects natively, and SQLAlchemy must convert from floating point - rounding er... | https://python.langchain.com/en/latest/modules/chains/examples/sqlite.html |
36c66e32a99c-2 | Use the following format:
Question: "Question here"
SQLQuery: "SQL Query to run"
SQLResult: "Result of the SQLQuery"
Answer: "Final answer here"
Only use the following tables:
{table_info}
If someone asks for the table foobar, they really mean the employee table.
Question: {input}"""
PROMPT = PromptTemplate(
input_... | https://python.langchain.com/en/latest/modules/chains/examples/sqlite.html |
36c66e32a99c-3 | Answer:There are 8 employees in the foobar table.
> Finished chain.
[{'input': 'How many employees are there in the foobar table?\nSQLQuery:SELECT COUNT(*) FROM Employee;\nSQLResult: [(8,)]\nAnswer:',
'top_k': '5',
'dialect': 'sqlite', | https://python.langchain.com/en/latest/modules/chains/examples/sqlite.html |
36c66e32a99c-4 | 'table_info': '\nCREATE TABLE "Artist" (\n\t"ArtistId" INTEGER NOT NULL, \n\t"Name" NVARCHAR(120), \n\tPRIMARY KEY ("ArtistId")\n)\n\n/*\n3 rows from Artist table:\nArtistId\tName\n1\tAC/DC\n2\tAccept\n3\tAerosmith\n*/\n\n\nCREATE TABLE "Employee" (\n\t"EmployeeId" INTEGER NOT NULL, \n\t"LastName" NVARCHAR(20) NOT NULL... | https://python.langchain.com/en/latest/modules/chains/examples/sqlite.html |
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