github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-06-23 07:09:31 +00:00
Code Issues Packages Projects Releases Wiki Activity

docs: Update structured_outputs.mdx (#27613)

Browse Source 
`strightforward` => `straightforward`
`adavanced` => `advanced`
`There a few challenges` => `There are a few challenges`

Documentation Correction:

*
[`docs/docs/concepts/structured_output.mdx`]:
Corrected several typos in the sentence directing users to the API
reference.
This commit is contained in:
Adarsh Sahu 2024-10-24 20:43:28 +05:30 committed by GitHub
parent da6b526770
commit 2d58a8a08d
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
1 changed files with 4 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
docs/docs/concepts/structured_outputs.mdx
View File

@ -66,7 +66,7 @@ Several more powerful methods that utilizes native features in the model provide
Many [model providers support](/docs/integrations/chat/) tool calling, a concept discussed in more detail in our [tool calling guide](/docs/concepts/tool_calling/). Many [model providers support](/docs/integrations/chat/) tool calling, a concept discussed in more detail in our [tool calling guide](/docs/concepts/tool_calling/).
In short, tool calling involves binding a tool to a model and, when appropriate, the model can *decide* to call this tool and ensure its response conforms to the tool's schema. In short, tool calling involves binding a tool to a model and, when appropriate, the model can *decide* to call this tool and ensure its response conforms to the tool's schema.
With this in mind, the central concept is strightforward: *simply bind our schema to a model as a tool!* With this in mind, the central concept is straightforward: *simply bind our schema to a model as a tool!*
Here is an example using the `ResponseFormatter` schema defined above: Here is an example using the `ResponseFormatter` schema defined above:
```python ```python
@ -106,7 +106,7 @@ ai_msg.content
``` ```
One important point to flag: the model *still* returns a string, which needs to be parsed into a JSON object. One important point to flag: the model *still* returns a string, which needs to be parsed into a JSON object.
This can, of course, simply use the `json` library or a JSON output parser if you need more adavanced functionality. This can, of course, simply use the `json` library or a JSON output parser if you need more advanced functionality.
See this [how-to guide on the JSON output parser](/docs/how_to/output_parser_json) for more details. See this [how-to guide on the JSON output parser](/docs/how_to/output_parser_json) for more details.
```python ```python
@ -117,7 +117,7 @@ json_object = json.loads(ai_msg.content)
## Structured output method ## Structured output method
There a few challenges when producing structured output with the above methods: There are a few challenges when producing structured output with the above methods:
(1) If using tool calling, tool call arguments needs to be parsed from a dictionary back to the original schema. (1) If using tool calling, tool call arguments needs to be parsed from a dictionary back to the original schema.