- it's only node ids that are limited
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I can't seem to reproduce, but i got this:
```
SystemError: AST constructor recursion depth mismatch (before=102, after=37)
```
And the operation isn't critical for the actual forward pass so seems
preferable to expand our caught exceptions
Causes an issue for this code
```python
from langchain.chat_models.openai import ChatOpenAI
from langchain.output_parsers.openai_tools import JsonOutputToolsParser
from langchain.schema import SystemMessage
prompt = SystemMessage(content="You are a nice assistant.") + "{question}"
llm = ChatOpenAI(
model_kwargs={
"tools": [
{
"type": "function",
"function": {
"name": "web_search",
"description": "Searches the web for the answer to the question.",
"parameters": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "The question to search for.",
},
},
},
},
}
],
},
streaming=True,
)
parser = JsonOutputToolsParser(first_tool_only=True)
llm_chain = prompt | llm | parser | (lambda x: x)
for chunk in llm_chain.stream({"question": "tell me more about turtles"}):
print(chunk)
# message = llm_chain.invoke({"question": "tell me more about turtles"})
# print(message)
```
Instead by definition, we'll assume that RunnableLambdas consume the
entire stream and that if the stream isn't addable then it's the last
message of the stream that's in the usable format.
---
If users want to use addable dicts, they can wrap the dict in an
AddableDict class.
---
Likely, need to follow up with the same change for other places in the
code that do the upgrade
- would happen when user's code tries to access attritbute that doesnt
exist, we prefer to let this crash in the user's code, rather than here
- also catch more cases where a runnable is invoked/streamed inside a
lambda. before we weren't seeing these as deps
- Add conditional: bool property to json representation of the graphs
- Add option to generate mermaid graph stripped of styles (useful as a
text representation of graph)
…s arg too
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Description: For simplicity, migrate the logic of excluding intermediate
nodes in the .get_graph() of langgraph package
(https://github.com/langchain-ai/langgraph/pull/310) at graph creation
time instead of graph rendering time.
Note: #20381 needs to be approved first
---------
Co-authored-by: Angel Igareta <angel.igareta@klarna.com>
Co-authored-by: Nuno Campos <nuno@langchain.dev>
Co-authored-by: Nuno Campos <nuno@boringbits.io>
Description of features on mermaid graph renderer:
- Fixing CDN to use official Mermaid JS CDN:
https://www.jsdelivr.com/package/npm/mermaid?tab=files
- Add device_scale_factor to allow increasing quality of resulting PNG.
Description: This update refines the documentation for
`RunnablePassthrough` by removing an unnecessary import and correcting a
minor syntactical error in the example provided. This change enhances
the clarity and correctness of the documentation, ensuring that users
have a more accurate guide to follow.
Issue: N/A
Dependencies: None
This PR focuses solely on documentation improvements, specifically
targeting the `RunnablePassthrough` class within the `langchain_core`
module. By clarifying the example provided in the docstring, users are
offered a more straightforward and error-free guide to utilizing the
`RunnablePassthrough` class effectively.
As this is a documentation update, it does not include changes that
require new integrations, tests, or modifications to dependencies. It
adheres to the guidelines of minimal package interference and backward
compatibility, ensuring that the overall integrity and functionality of
the LangChain package remain unaffected.
Thank you for considering this documentation refinement for inclusion in
the LangChain project.
- **Description:** Improvement for #19599: fixing missing return of
graph.draw_mermaid_png and improve it to make the saving of the rendered
image optional
Co-authored-by: Angel Igareta <angel.igareta@klarna.com>
- This ensures ids are stable across streamed chunks
- Multiple messages in batch call get separate ids
- Also fix ids being dropped when combining message chunks
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- **Description:** Add functionality to generate Mermaid syntax and
render flowcharts from graph data. This includes support for custom node
colors and edge curve styles, as well as the ability to export the
generated graphs to PNG images using either the Mermaid.INK API or
Pyppeteer for local rendering.
- **Dependencies:** Optional dependencies are `pyppeteer` if rendering
wants to be done using Pypeteer and Javascript code.
---------
Co-authored-by: Angel Igareta <angel.igareta@klarna.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
**Description:** Update to the docstring for class RunnableSerializable,
method configurable_fields
**Issue:** [Add in code documentation to core Runnable methods
#18804](https://github.com/langchain-ai/langchain/issues/18804)
**Dependencies:** None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
**Description:** Update to the docstring for class RunnableSerializable,
method configurable_alternatives
**Issue:** [Add in code documentation to core Runnable methods
#18804](https://github.com/langchain-ai/langchain/issues/18804)
**Dependencies:** None
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
Added example to the docstring of the "bind" method of Runnable. This
makes it easier to understand the purpose of the method when reviewing
in code editors. E.g. VS Code below.
<img width="833" alt="Screenshot 2024-03-27 at 16 24 18"
src="https://github.com/langchain-ai/langchain/assets/45722942/ad022d4e-7bc0-4f4b-aa7a-838f1816cc52">
---------
Co-authored-by: Chester Curme <chester.curme@gmail.com>
The root run id (~trace id's) is useful for assigning feedback, but the
current recommended approach is to use callbacks to retrieve it, which
has some drawbacks:
1. Doesn't work for streaming until after the first event
2. Doesn't let you call other endpoints with the same trace ID in
parallel (since you have to wait until the call is completed/started to
use
This PR lets you provide = "run_id" in the runnable config.
Couple considerations:
1. For batch calls, we split the trace up into separate trees (to permit
better rendering). We keep the provided run ID for the first one and
generate a unique one for other elements of the batch.
2. For nested calls, the provided ID is ONLY used on the top root/trace.
### Example Usage
```
chain.invoke("foo", {"run_id": uuid.uuid4()})
```
- Description: [a description of the change] Add in code documentation
to core Runnable with_fallbacks method (docs only)
- Issue: the issue #18804
@eyurtsev PTAL
**PR message**: ***Delete this entire checklist*** and replace with
- **Description:** [a description of the change](docs: Add in code
documentation to core Runnable assign method)
- **Issue:** the issue #18804
- **Description:** When calling the `_stream_log_implementation` from
the `astream_log` method in the `Runnable` class, it is not handing over
the `kwargs` argument. Therefore, even if i want to customize APIHandler
and implement additional features with additional arguments, it is not
possible. Conversely, the `astream_events` method normally handing over
the `kwargs` argument.
- **Issue:** https://github.com/langchain-ai/langchain/issues/19054
- **Dependencies:**
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mention, we'll gladly shout you out!
Co-authored-by: hyungwookyang <hyungwookyang@worksmobile.com>
This PR adds `batch as completed` method to the standard Runnable
interface. It takes in a list of inputs and yields the corresponding
outputs as the inputs are completed.
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h/t @hinthornw
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This PR updates RunnableWithMessageHistory to use add_messages which
will save on round-trips for any chat
history abstractions that implement the optimization. If the
optimization isn't
implemented, add_messages automatically invokes add_message serially.
