Description: I was following the docs and got an error about missing
tiktoken dependency. Adding it to the comment where the langchain and
docarray libs are.
Many jupyter notebooks didn't pass linting. List of these files are
presented in the [tool.ruff.lint.per-file-ignores] section of the
pyproject.toml . Addressed these bugs:
- fixed bugs; added missed imports; updated pyproject.toml
Only the `document_loaders/tensorflow_datasets.ipyn`,
`cookbook/gymnasium_agent_simulation.ipynb` are not completely fixed.
I'm not sure about imports.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
### Description
Fixed 3 doc issues:
1. `ConfigurableField ` needs to be imported in
`docs/docs/expression_language/how_to/configure.ipynb`
2. use `error` instead of `RateLimitError()` in
`docs/docs/expression_language/how_to/fallbacks.ipynb`
3. I think it might be better to output the fixed json data(when I
looked at this example, I didn't understand its purpose at first, but
then I suddenly realized):
<img width="1219" alt="Screenshot 2023-12-05 at 10 34 13 PM"
src="https://github.com/langchain-ai/langchain/assets/10000925/7623ba13-7b56-4964-8c98-b7430fabc6de">
Switches to a more maintained solution for building ipynb -> md files
(`quarto`)
Also bumps us down to python3.8 because it's significantly faster in the
vercel build step. Uses default openssl version instead of upgrading as
well.
### Description
The `RateLimitError` initialization method has changed after openai v1,
and the usage of `patch` needs to be changed.
### Twitter handle
[lin_bob57617](https://twitter.com/lin_bob57617)
- **Description:** Change instances of RunnableMap to RunnableParallel,
as that should be the one used going forward. This makes it consistent
across the codebase.
### Description:
Doc addition for LCEL introduction. Adds a more basic starter guide for
using LCEL.
---------
Co-authored-by: Alex Kira <akira@Alexs-MBP.local.tld>
Co-authored-by: Bagatur <baskaryan@gmail.com>
grammar correction
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Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
### Description:
Hey 👋🏽 this is a small docs example fix. Hoping it helps future developers who are working with Langchain.
### Problem:
Take a look at the original example code. You were not able to get the `dialogue_turn[0]` while it was a tuple.
Original code:
```python
def _format_chat_history(chat_history: List[Tuple]) -> str:
buffer = ""
for dialogue_turn in chat_history:
human = "Human: " + dialogue_turn[0]
ai = "Assistant: " + dialogue_turn[1]
buffer += "\n" + "\n".join([human, ai])
return buffer
```
In the original code you were getting this error:
```bash
human = "Human: " + dialogue_turn[0].content
~~~~~~~~~~~~~^^^
TypeError: 'HumanMessage' object is not subscriptable
```
### Solution:
The fix is to just for loop over the chat history and look to see if its a human or ai message and add it to the buffer.
The new ruff version fixed the blocking bugs, and I was able to fairly
easily us to a passing state: ruff fixed some issues on its own, I fixed
a handful by hand, and I added a list of narrowly-targeted exclusions
for files that are currently failing ruff rules that we probably should
look into eventually.
I went pretty lenient on the docs / cookbooks rules, allowing dead code
and such things. Perhaps in the future we may want to tighten the rules
further, but this is already a good set of checks that found real issues
and will prevent them going forward.
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