Hi! My name is Alex, I'm an SDK engineer from
[Comet](https://www.comet.com/site/)
This PR updates the `CometTracer` class.
Fixed an issue when `CometTracer` failed while logging the data to Comet
because this data is not JSON-encodable.
The problem was in some of the `Run` attributes that could contain
non-default types inside, now these attributes are taken not from the
run instance, but from the `run.dict()` return value.
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
- **Description:** In January, Laiyer.ai became part of ProtectAI, which
means the model became owned by ProtectAI. In addition to that,
yesterday, we released a new version of the model addressing issues the
Langchain's community and others mentioned to us about false-positives.
The new model has a better accuracy compared to the previous version,
and we thought the Langchain community would benefit from using the
[latest version of the
model](https://huggingface.co/protectai/deberta-v3-base-prompt-injection-v2).
- **Issue:** N/A
- **Dependencies:** N/A
- **Twitter handle:** @alex_yaremchuk
This PR moves the implementations for chat history to core. So it's
easier to determine which dependencies need to be broken / add
deprecation warnings
Fixed an error in the sample code to ensure that the code can run
directly.
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
langchain_community.document_loaders depricated
new langchain_google_community
Thank you for contributing to LangChain!
- [ ] **PR title**: "package: description"
- Where "package" is whichever of langchain, community, core,
experimental, etc. is being modified. Use "docs: ..." for purely docs
changes, "templates: ..." for template changes, "infra: ..." for CI
changes.
- Example: "community: add foobar LLM"
- [ ] **PR message**: ***Delete this entire checklist*** and replace
with
- **Description:** a description of the change
- **Issue:** the issue # it fixes, if applicable
- **Dependencies:** any dependencies required for this change
- **Twitter handle:** if your PR gets announced, and you'd like a
mention, we'll gladly shout you out!
- [ ] **Add tests and docs**: If you're adding a new integration, please
include
1. a test for the integration, preferably unit tests that do not rely on
network access,
2. an example notebook showing its use. It lives in
`docs/docs/integrations` directory.
- [ ] **Lint and test**: Run `make format`, `make lint` and `make test`
from the root of the package(s) you've modified. See contribution
guidelines for more: https://python.langchain.com/docs/contributing/
Additional guidelines:
- Make sure optional dependencies are imported within a function.
- Please do not add dependencies to pyproject.toml files (even optional
ones) unless they are required for unit tests.
- Most PRs should not touch more than one package.
- Changes should be backwards compatible.
- If you are adding something to community, do not re-import it in
langchain.
If no one reviews your PR within a few days, please @-mention one of
baskaryan, efriis, eyurtsev, hwchase17.
docs: Fix link for `partition_pdf` in Semi_Structured_RAG.ipynb cookbook
- **Description:** Fix incorrect link to unstructured-io `partition_pdf`
section
Vector indexes in ClickHouse are experimental at the moment and can
sometimes break/change behaviour. So this PR makes it possible to say
that you don't want to specify an index type.
Any queries against the embedding column will be brute force/linear
scan, but that gives reasonable performance for small-medium dataset
sizes.
---------
Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Thank you for contributing to LangChain!
- [ ] **PR title**: "docs: added a description of differences
langchain_google_genai vs langchain_google_vertexai"
- [ ]
- **Description:** added a description of differences
langchain_google_genai vs langchain_google_vertexai
**Description:** implemented GraphStore class for Apache Age graph db
**Dependencies:** depends on psycopg2
Unit and integration tests included. Formatting and linting have been
run.
---------
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
