Commit Graph

7 Commits

Author SHA1 Message Date
Wenbin Fang
a7e09d46c5
Add podcast api tool to use NLP to search all podcasts or episodes. (#1833)
Use the following code to test:

```python
import os
from langchain.llms import OpenAI
from langchain.chains.api import podcast_docs
from langchain.chains import APIChain

# Get api key here: https://openai.com/pricing
os.environ["OPENAI_API_KEY"] = "sk-xxxxx"

# Get api key here: https://www.listennotes.com/api/pricing/
listen_api_key = 'xxx'

llm = OpenAI(temperature=0)
headers = {"X-ListenAPI-Key": listen_api_key}
chain = APIChain.from_llm_and_api_docs(llm, podcast_docs.PODCAST_DOCS, headers=headers, verbose=True)
chain.run("Search for 'silicon valley bank' podcast episodes, audio length is more than 30 minutes, return only 1 results")
```

Known issues: the api response data might be too big, and we'll get such
error:
`openai.error.InvalidRequestError: This model's maximum context length
is 4097 tokens, however you requested 6733 tokens (6477 in your prompt;
256 for the completion). Please reduce your prompt; or completion
length.`
2023-03-20 22:04:17 -07:00
Zach Schillaci
624c72c266
Add wikipedia tool doc (#1579) 2023-03-10 07:07:27 -08:00
3ecdea8be4
SearxNG meta search api helper (#854)
This is a work in progress PR to track my progres.

## TODO:

- [x]  Get results using the specifed searx host
- [x]  Prioritize returning an  `answer`  or results otherwise
    - [ ] expose the field `infobox` when available
    - [ ] expose `score` of result to help agent's decision
- [ ] expose the `suggestions` field to agents so they could try new
queries if no results are found with the orignial query ?

- [ ] Dynamic tool description for agents ?
- Searx offers many engines and a search syntax that agents can take
advantage of. It would be nice to generate a dynamic Tool description so
that it can be used many times as a tool but for different purposes.

- [x]  Limit number of results
- [ ]   Implement paging
- [x]  Miror the usage of the Google Search tool
- [x] easy selection of search engines
- [x]  Documentation
    - [ ] update HowTo guide notebook on Search Tools
- [ ] Handle async 
- [ ]  Tests

###  Add examples / documentation on possible uses with
 - [ ]  getting factual answers with `!wiki` option and `infoboxes`
 - [ ]  getting `suggestions`
 - [ ]  getting `corrections`

---------

Co-authored-by: blob42 <spike@w530>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
2023-02-15 23:03:57 -08:00
rogerserper
e46cd3b7db
Google Search API integration with serper.dev (wrapper, tests, docs, … (#909)
Adds Google Search integration with [Serper](https://serper.dev) a
low-cost alternative to SerpAPI (10x cheaper + generous free tier).
Includes documentation, tests and examples. Hopefully I am not missing
anything.

Developers can sign up for a free account at
[serper.dev](https://serper.dev) and obtain an api key.

## Usage

```python
from langchain.utilities import GoogleSerperAPIWrapper
from langchain.llms.openai import OpenAI
from langchain.agents import initialize_agent, Tool

import os
os.environ["SERPER_API_KEY"] = ""
os.environ['OPENAI_API_KEY'] = ""

llm = OpenAI(temperature=0)
search = GoogleSerperAPIWrapper()
tools = [
    Tool(
        name="Intermediate Answer",
        func=search.run
    )
]

self_ask_with_search = initialize_agent(tools, llm, agent="self-ask-with-search", verbose=True)
self_ask_with_search.run("What is the hometown of the reigning men's U.S. Open champion?")
```

### Output
```
Entering new AgentExecutor chain...
 Yes.
Follow up: Who is the reigning men's U.S. Open champion?
Intermediate answer: Current champions Carlos Alcaraz, 2022 men's singles champion.
Follow up: Where is Carlos Alcaraz from?
Intermediate answer: El Palmar, Spain
So the final answer is: El Palmar, Spain

> Finished chain.

'El Palmar, Spain'
```
2023-02-15 22:47:17 -08:00
Harrison Chase
3d41af0aba
Harrison/load tools kwargs (#681)
Co-authored-by: Bruno Bornsztein <bruno.bornsztein@gmail.com>
2023-01-21 16:03:02 -08:00
Harrison Chase
ffc7e04d44
Harrison/wolfram alpha (#579)
Co-authored-by: Nicolas <nicolascamara29@gmail.com>
2023-01-11 05:52:19 -08:00
Harrison Chase
985496f4be
Docs refactor (#480)
Big docs refactor! Motivation is to make it easier for people to find
resources they are looking for. To accomplish this, there are now three
main sections:

- Getting Started: steps for getting started, walking through most core
functionality
- Modules: these are different modules of functionality that langchain
provides. Each part here has a "getting started", "how to", "key
concepts" and "reference" section (except in a few select cases where it
didnt easily fit).
- Use Cases: this is to separate use cases (like summarization, question
answering, evaluation, etc) from the modules, and provide a different
entry point to the code base.

There is also a full reference section, as well as extra resources
(glossary, gallery, etc)

Co-authored-by: Shreya Rajpal <ShreyaR@users.noreply.github.com>
2023-01-02 08:24:09 -08:00