mirror of https://github.com/hwchase17/langchain
extraction docs (#1898)
parent
15b5a08f4b
commit
1f93c5cf69
@ -0,0 +1,20 @@
|
||||
# Extraction
|
||||
|
||||
Most APIs and databases still deal with structured information.
|
||||
Therefore, in order to better work with those, it can be useful to extract structured information from text.
|
||||
Examples of this include:
|
||||
|
||||
- Extracting a structured row to insert into a database from a sentence
|
||||
- Extracting multiple rows to insert into a database from a long document
|
||||
- Extracting the correct API parameters from a user query
|
||||
|
||||
This work is extremely related to [output parsing](../modules/prompts/examples/output_parsers.ipynb).
|
||||
Output parsers are responsible for instructing the LLM to respond in a specific format.
|
||||
In this case, the output parsers specify the format of the data you would like to extract from the document.
|
||||
Then, in addition to the output format instructions, the prompt should also contain the data you would like to extract information from.
|
||||
|
||||
While normal output parsers are good enough for basic structuring of response data,
|
||||
when doing extraction you often want to extract more complicated or nested structures.
|
||||
For a deep dive on extraction, we recommend checking out [`kor`](https://eyurtsev.github.io/kor/),
|
||||
a library that uses the existing LangChain chain and OutputParser abstractions
|
||||
but deep dives on allowing extraction of more complicated schemas.
|
Loading…
Reference in New Issue