Commit Graph

532 Commits

Author SHA1 Message Date
Bagatur
093ae04d58
core[patch]: Pin pydantic in py3.12.4 (#23130) 2024-06-18 12:00:02 -07:00
Bagatur
d96f67b06f
standard-tests[patch]: Update chat model standard tests (#22378)
- Refactor standard test classes to make them easier to configure
- Update openai to support stop_sequences init param
- Update groq to support stop_sequences init param
- Update fireworks to support max_retries init param
- Update ChatModel.bind_tools to type tool_choice
- Update groq to handle tool_choice="any". **this may be controversial**

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-06-17 13:37:41 -07:00
ccurme
722c8f50ea
openai[patch]: add stream_usage parameter (#22854)
Here we add `stream_usage` to ChatOpenAI as:

1. a boolean attribute
2. a kwarg to _stream and _astream.

Question: should the `stream_usage` attribute be `bool`, or `bool |
None`?

Currently I've kept it `bool` and defaulted to False. It was implemented
on
[ChatAnthropic](e832bbb486/libs/partners/anthropic/langchain_anthropic/chat_models.py (L535))
as a bool. However, to maintain support for users who access the
behavior via OpenAI's `stream_options` param, this ends up being
possible:
```python
llm = ChatOpenAI(model_kwargs={"stream_options": {"include_usage": True}})
assert not llm.stream_usage
```
(and this model will stream token usage).

Some options for this:
- it's ok
- make the `stream_usage` attribute bool or None
- make an \_\_init\_\_ for ChatOpenAI, set a `._stream_usage` attribute
and read `.stream_usage` from a property

Open to other ideas as well.
2024-06-17 13:35:18 -04:00
Hakan Özdemir
c437b1aab7
[Partner]: Add metadata to stream response (#22716)
Adds `response_metadata` to stream responses from OpenAI. This is
returned with `invoke` normally, but wasn't implemented for `stream`.

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-06-17 09:46:50 -04:00
Jacob Lee
181a61982f
anthropic[minor]: Adds streaming tool call support for Anthropic (#22687)
Preserves string content chunks for non tool call requests for
convenience.

One thing - Anthropic events look like this:

```
RawContentBlockStartEvent(content_block=TextBlock(text='', type='text'), index=0, type='content_block_start')
RawContentBlockDeltaEvent(delta=TextDelta(text='<thinking>\nThe', type='text_delta'), index=0, type='content_block_delta')
RawContentBlockDeltaEvent(delta=TextDelta(text=' provide', type='text_delta'), index=0, type='content_block_delta')
...
RawContentBlockStartEvent(content_block=ToolUseBlock(id='toolu_01GJ6x2ddcMG3psDNNe4eDqb', input={}, name='get_weather', type='tool_use'), index=1, type='content_block_start')
RawContentBlockDeltaEvent(delta=InputJsonDelta(partial_json='', type='input_json_delta'), index=1, type='content_block_delta')
```

Note that `delta` has a `type` field. With this implementation, I'm
dropping it because `merge_list` behavior will concatenate strings.

We currently have `index` as a special field when merging lists, would
it be worth adding `type` too?

If so, what do we set as a context block chunk? `text` vs.
`text_delta`/`tool_use` vs `input_json_delta`?

CC @ccurme @efriis @baskaryan
2024-06-14 09:14:43 -07:00
ccurme
f40b2c6f9d
fireworks[patch]: add usage_metadata to (a)invoke and (a)stream (#22906) 2024-06-14 12:07:19 -04:00
ccurme
73c76b9628
anthropic[patch]: always add tool_result type to ToolMessage content (#22721)
Anthropic tool results can contain image data, which are typically
represented with content blocks having `"type": "image"`. Currently,
these content blocks are passed as-is as human/user messages to
Anthropic, which raises BadRequestError as it expects a tool_result
block to follow a tool_use.

Here we update ChatAnthropic to nest the content blocks inside a
tool_result content block.

Example:
```python
import base64

import httpx
from langchain_anthropic import ChatAnthropic
from langchain_core.messages import AIMessage, HumanMessage, ToolMessage
from langchain_core.pydantic_v1 import BaseModel, Field


# Fetch image
image_url = "https://upload.wikimedia.org/wikipedia/commons/thumb/d/dd/Gfp-wisconsin-madison-the-nature-boardwalk.jpg/2560px-Gfp-wisconsin-madison-the-nature-boardwalk.jpg"
image_data = base64.b64encode(httpx.get(image_url).content).decode("utf-8")


class FetchImage(BaseModel):
    should_fetch: bool = Field(..., description="Whether an image is requested.")


llm = ChatAnthropic(model="claude-3-sonnet-20240229").bind_tools([FetchImage])

messages = [
    HumanMessage(content="Could you summon a beautiful image please?"),
    AIMessage(
        content=[
            {
                "type": "tool_use",
                "id": "toolu_01Rn6Qvj5m7955x9m9Pfxbcx",
                "name": "FetchImage",
                "input": {"should_fetch": True},
            },
        ],
        tool_calls=[
            {
                "name": "FetchImage",
                "args": {"should_fetch": True},
                "id": "toolu_01Rn6Qvj5m7955x9m9Pfxbcx",
            },
        ],
    ),
    ToolMessage(
        name="FetchImage",
        content=[
            {
                "type": "image",
                "source": {
                    "type": "base64",
                    "media_type": "image/jpeg",
                    "data": image_data,
                },
            },
        ],
        tool_call_id="toolu_01Rn6Qvj5m7955x9m9Pfxbcx",
    ),
]

llm.invoke(messages)
```

Trace:
https://smith.langchain.com/public/d27e4fc1-a96d-41e1-9f52-54f5004122db/r
2024-06-13 20:14:23 -07:00
Lucas Tucker
7114aed78f
docs: Standardize ChatGroq (#22751)
Updated ChatGroq doc string as per issue
https://github.com/langchain-ai/langchain/issues/22296:"langchain_groq:
updated docstring for ChatGroq in langchain_groq to match that of the
description (in the appendix) provided in issue
https://github.com/langchain-ai/langchain/issues/22296. "

Issue: This PR is in response to issue
https://github.com/langchain-ai/langchain/issues/22296, and more
specifically the ChatGroq model. In particular, this PR updates the
docstring for langchain/libs/partners/groq/langchain_groq/chat_model.py
by adding the following sections: Instantiate, Invoke, Stream, Async,
Tool calling, Structured Output, and Response metadata. I used the
template from the Anthropic implementation and referenced the Appendix
of the original issue post. I also noted that: `usage_metadata `returns
none for all ChatGroq models I tested; there is no mention of image
input in the ChatGroq documentation; unlike that of ChatHuggingFace,
`.stream(messages)` for ChatGroq returned blocks of output.

---------

Co-authored-by: lucast2021 <lucast2021@headroyce.org>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-06-14 03:08:36 +00:00
Anush
e002c855bd
qdrant[patch]: Use collection_exists API instead of exceptions (#22764)
## Description

Currently, the Qdrant integration relies on exceptions raised by
[`get_collection`
](https://qdrant.tech/documentation/concepts/collections/#collection-info)
to check if a collection exists.

Using
[`collection_exists`](https://qdrant.tech/documentation/concepts/collections/#check-collection-existence)
is recommended to avoid missing any unhandled exceptions. This PR
addresses this.

## Testing
All integration and unit tests pass. No user-facing changes.
2024-06-13 20:01:32 -07:00
ccurme
42257b120f
partners: fix numpy dep (#22858)
Following https://github.com/langchain-ai/langchain/pull/22813, which
added python 3.12 to CI, here we update numpy accordingly in partner
packages.
2024-06-13 14:46:42 -04:00
ccurme
b626c3ca23
groq[patch]: add usage_metadata to (a)invoke and (a)stream (#22834) 2024-06-13 10:26:27 -04:00
ccurme
936aedd10c
mistral[patch]: add usage_metadata to (a)invoke and (a)stream (#22781) 2024-06-11 15:34:50 -04:00
Lucas Tucker
cb79e80b0b
docs: standardize ChatHuggingFace (#22693)
**Updated ChatHuggingFace doc string as per issue #22296**:
"langchain_huggingface: updated docstring for ChatHuggingFace in
langchain_huggingface to match that of the description (in the appendix)
provided in issue #22296. "

**Issue:** This PR is in response to issue #22296, and more specifically
ChatHuggingFace model. In particular, this PR updates the docstring for
langchain/libs/partners/hugging_face/langchain_huggingface/chat_models/huggingface.py
by adding the following sections: Instantiate, Invoke, Stream, Async,
Tool calling, and Response metadata. I used the template from the
Anthropic implementation and referenced the Appendix of the original
issue post. I also noted that: langchain_community hugging face llms do
not work with langchain_huggingface's ChatHuggingFace model (at least
for me); the .stream(messages) functionality of ChatHuggingFace only
returned a block of response.

---------

Co-authored-by: lucast2021 <lucast2021@headroyce.org>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-06-10 20:54:36 +00:00
ccurme
f9fdca6cc2
openai: add parallel_tool_calls to api ref (#22746)
![Screenshot 2024-06-10 at 1 41 24
PM](https://github.com/langchain-ai/langchain/assets/26529506/2626bf9c-41c6-4431-b2e1-f59de1e4e468)
2024-06-10 17:44:43 +00:00
Nithish Raghunandanan
f2f0e0e13d
couchbase: Add the initial version of Couchbase partner package (#22087)
Co-authored-by: Nithish Raghunandanan <nithishr@users.noreply.github.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-06-07 14:04:08 -07:00
ccurme
f32d57f6f0
anthropic: refactor streaming to use events api; add streaming usage metadata (#22628)
- Refactor streaming to use raw events;
- Add `stream_usage` class attribute and kwarg to stream methods that,
if True, will include separate chunks in the stream containing usage
metadata.

There are two ways to implement streaming with anthropic's python sdk.
They have slight differences in how they surface usage metadata.
1. [Use helper
functions](https://github.com/anthropics/anthropic-sdk-python?tab=readme-ov-file#streaming-helpers).
This is what we are doing now.
```python
count = 1
with client.messages.stream(**params) as stream:
    for text in stream.text_stream:
        snapshot = stream.current_message_snapshot
        print(f"{count}: {snapshot.usage} -- {text}")
        count = count + 1

final_snapshot = stream.get_final_message()
print(f"{count}: {final_snapshot.usage}")
```
```
1: Usage(input_tokens=8, output_tokens=1) -- Hello
2: Usage(input_tokens=8, output_tokens=1) -- !
3: Usage(input_tokens=8, output_tokens=1) --  How
4: Usage(input_tokens=8, output_tokens=1) --  can
5: Usage(input_tokens=8, output_tokens=1) --  I
6: Usage(input_tokens=8, output_tokens=1) --  assist
7: Usage(input_tokens=8, output_tokens=1) --  you
8: Usage(input_tokens=8, output_tokens=1) --  today
9: Usage(input_tokens=8, output_tokens=1) -- ?
10: Usage(input_tokens=8, output_tokens=12)
```
To do this correctly, we need to emit a new chunk at the end of the
stream containing the usage metadata.

2. [Handle raw
events](https://github.com/anthropics/anthropic-sdk-python?tab=readme-ov-file#streaming-responses)
```python
stream = client.messages.create(**params, stream=True)
count = 1
for event in stream:
    print(f"{count}: {event}")
    count = count + 1
```
```
1: RawMessageStartEvent(message=Message(id='msg_01Vdyov2kADZTXqSKkfNJXcS', content=[], model='claude-3-haiku-20240307', role='assistant', stop_reason=None, stop_sequence=None, type='message', usage=Usage(input_tokens=8, output_tokens=1)), type='message_start')
2: RawContentBlockStartEvent(content_block=TextBlock(text='', type='text'), index=0, type='content_block_start')
3: RawContentBlockDeltaEvent(delta=TextDelta(text='Hello', type='text_delta'), index=0, type='content_block_delta')
4: RawContentBlockDeltaEvent(delta=TextDelta(text='!', type='text_delta'), index=0, type='content_block_delta')
5: RawContentBlockDeltaEvent(delta=TextDelta(text=' How', type='text_delta'), index=0, type='content_block_delta')
6: RawContentBlockDeltaEvent(delta=TextDelta(text=' can', type='text_delta'), index=0, type='content_block_delta')
7: RawContentBlockDeltaEvent(delta=TextDelta(text=' I', type='text_delta'), index=0, type='content_block_delta')
8: RawContentBlockDeltaEvent(delta=TextDelta(text=' assist', type='text_delta'), index=0, type='content_block_delta')
9: RawContentBlockDeltaEvent(delta=TextDelta(text=' you', type='text_delta'), index=0, type='content_block_delta')
10: RawContentBlockDeltaEvent(delta=TextDelta(text=' today', type='text_delta'), index=0, type='content_block_delta')
11: RawContentBlockDeltaEvent(delta=TextDelta(text='?', type='text_delta'), index=0, type='content_block_delta')
12: RawContentBlockStopEvent(index=0, type='content_block_stop')
13: RawMessageDeltaEvent(delta=Delta(stop_reason='end_turn', stop_sequence=None), type='message_delta', usage=MessageDeltaUsage(output_tokens=12))
14: RawMessageStopEvent(type='message_stop')
```

Here we implement the second option, in part because it should make
things easier when implementing streaming tool calls in the near future.

This would add two new chunks to the stream-- one at the beginning and
one at the end-- with blank content and containing usage metadata. We
add kwargs to the stream methods and a class attribute allowing for this
behavior to be toggled. I enabled it by default. If we merge this we can
add the same kwargs / attribute to OpenAI.

Usage:
```python
from langchain_anthropic import ChatAnthropic

model = ChatAnthropic(
    model="claude-3-haiku-20240307",
    temperature=0
)

full = None
for chunk in model.stream("hi"):
    full = chunk if full is None else full + chunk
    print(chunk)

print(f"\nFull: {full}")
```
```
content='' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 8, 'output_tokens': 0, 'total_tokens': 8}
content='Hello' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content='!' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content=' How' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content=' can' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content=' I' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content=' assist' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content=' you' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content=' today' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content='?' id='run-8a20843f-25c7-4025-ad72-9add395899e3'
content='' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 0, 'output_tokens': 12, 'total_tokens': 12}

Full: content='Hello! How can I assist you today?' id='run-8a20843f-25c7-4025-ad72-9add395899e3' usage_metadata={'input_tokens': 8, 'output_tokens': 12, 'total_tokens': 20}
```
2024-06-07 13:21:46 +00:00
seyf97
2904c50cd5
openai[patch]: correct grammar in exception message in embeddings/base.py (#22629)
Correct the grammar error for missing transformers package ValueError
2024-06-06 18:55:04 +00:00
Anush
80560419b0
qdrant[patch]: Make path optional in from_existing_collection() (#21875)
## Description

The `path` param is used to specify the local persistence directory,
which isn't required if using Qdrant server.

This is a breaking but necessary change.
2024-06-06 10:37:08 -07:00
ccurme
b57aa89f34
multiple: implement ls_params (#22621)
implement ls_params for ai21, fireworks, groq.
2024-06-06 16:51:37 +00:00
ccurme
c1ef731503
anthropic: update attribute name and alias (#22625)
update name to `stop_sequences` and alias to `stop` (instead of the
other way around), since `stop_sequences` is the name used by anthropic.
2024-06-06 12:29:10 -04:00
ccurme
3999761201
multiple: add stop attribute (#22573) 2024-06-06 12:11:52 -04:00
ccurme
e08879147b
Revert "anthropic: stream token usage" (#22624)
Reverts langchain-ai/langchain#20180
2024-06-06 12:05:08 -04:00
Bagatur
0d495f3f63
anthropic: stream token usage (#20180)
open to other ideas
<img width="1181" alt="Screenshot 2024-04-08 at 5 34 08 PM"
src="https://github.com/langchain-ai/langchain/assets/22008038/03eb11c4-5eb5-43e3-9109-a13f76098fa4">

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-06-06 11:51:34 -04:00
Satyam Kumar
17b486a37b
openai, azure: update model_name in ChatResult to use name from API response (#22569)
The response.get("model", self.model_name) checks if the model key
exists in the response dictionary. If it does, it uses that value;
otherwise, it uses self.model_name.

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, ccurme, vbarda, hwchase17.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-06-06 11:00:09 -04:00
ccurme
1925bde32e
together: bump langchain-core (#22616)
langchain-together depends on langchain-openai ^0.1.8
langchain-openai 0.1.8 has langchain-core >= 0.2.2

Here we bump langchain-core to 0.2.2, just to pass minimum dependency
version tests.
2024-06-06 14:09:40 +00:00
ccurme
35f4aa927b
together[patch]: Release 0.1.3 (#22615) 2024-06-06 13:58:35 +00:00
Ethan Yang
29064848f9
[Community]add option to delete the prompt from HF output (#22225)
This will help to solve pattern mismatching issue when parsing the
output in Agent.

https://github.com/langchain-ai/langchain/issues/21912
2024-06-05 18:38:54 -04:00
Bagatur
b2daba37c7
nomic[patch]: Release 0.1.2 (#22561) 2024-06-05 17:06:58 +00:00
Zach Nussbaum
14f3014cce
embeddings: nomic embed vision (#22482)
Thank you for contributing to LangChain!

**Description:** Adds Langchain support for Nomic Embed Vision
**Twitter handle:** nomic_ai,zach_nussbaum


- [x] **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, ccurme, vbarda, hwchase17.

---------

Co-authored-by: Lance Martin <122662504+rlancemartin@users.noreply.github.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2024-06-05 09:47:17 -07:00
Erick Friis
4050d6ea2b
huggingface: remove text-generation dep (#22543) 2024-06-05 12:13:40 +00:00
Erick Friis
a6fc74f379
ai21: fix core version (#22544) 2024-06-05 08:09:19 -04:00
Asaf Joseph Gardin
75cba742e5
ai21: fix ai21 unittests (#22526)
Co-authored-by: Asaf Gardin <asafg@ai21.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
2024-06-05 08:00:42 -04:00
Bagatur
cb183a9bf1
docs: update anthropic chat model (#22483)
Related to #22296

And update anthropic to accept base_url
2024-06-04 12:42:06 -07:00
Erick Friis
d700ce8545
robocorp: typo (#22509) 2024-06-04 15:33:38 -04:00
Erick Friis
39fd44579a
robocorp: release 0.0.9.post1 (#22507) 2024-06-04 15:32:30 -04:00
Erick Friis
339e3b7f55
ai21: release 0.1.6 (#22508) 2024-06-04 15:31:23 -04:00
ccurme
3c53cea760
together, upstage: bump minimum langchain-openai version (#22505) 2024-06-04 15:20:41 -04:00
Bagatur
efcb04f84b
mongodb[patch]: Release 0.1.6 (#22501) 2024-06-04 12:01:37 -07:00
Bagatur
222b1ba112
groq[patch]: Release 0.1.5 (#22500) 2024-06-04 12:01:17 -07:00
Bagatur
f021be510e
milvus[patch]: Release 0.1.1 (#22499) 2024-06-04 12:00:53 -07:00
Bagatur
64d68c17cd
upstage[patch]: Release 0.1.6 (#22498) 2024-06-04 11:58:44 -07:00
Bagatur
8e86080def
mistralai[patch]: Release 0.1.8 (#22494) 2024-06-04 11:33:06 -07:00
Bagatur
e850de2422
huggingface[patch]: release 0.0.2 (#22493) 2024-06-04 11:32:36 -07:00
Joydeep Banik Roy
3796672c67
community, milvus, pinecone, qdrant, mongo: Broadcast operation failure while using simsimd beyond v3.7.7 (#22271)
- [ ] **Packages affected**: 
  - community: fix `cosine_similarity` to support simsimd beyond 3.7.7
- partners/milvus: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/mongodb: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/pinecone: fix `cosine_similarity` to support simsimd beyond
3.7.7
- partners/qdrant: fix `cosine_similarity` to support simsimd beyond
3.7.7


- [ ] **Broadcast operation failure while using simsimd beyond v3.7.7**:
- **Description:** I was using simsimd 4.3.1 and the unsupported operand
type issue popped up. When I checked out the repo and ran the tests,
they failed as well (have attached a screenshot for that). Looks like it
is a variant of https://github.com/langchain-ai/langchain/issues/18022 .
Prior to 3.7.7, simd.cdist returned an ndarray but now it returns
simsimd.DistancesTensor which is ineligible for a broadcast operation
with numpy. With this change, it also remove the need to explicitly cast
`Z` to numpy array
    - **Issue:** #19905
    - **Dependencies:** No
    - **Twitter handle:** https://x.com/GetzJoydeep

<img width="1622" alt="Screenshot 2024-05-29 at 2 50 00 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/fb27b383-a9ae-4a6f-b355-6d503b72db56">

- [ ] **Considerations**: 
1. I started with community but since similar changes were there in
Milvus, MongoDB, Pinecone, and QDrant so I modified their files as well.
If touching multiple packages in one PR is not the norm, then I can
remove them from this PR and raise separate ones
2. I have run and verified that the tests work. Since, only MongoDB had
tests, I ran theirs and verified it works as well. Screenshots attached
:
<img width="1573" alt="Screenshot 2024-05-29 at 2 52 13 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/ce87d1ea-19b6-4900-9384-61fbc1a30de9">
<img width="1614" alt="Screenshot 2024-05-29 at 3 33 51 PM"
src="https://github.com/langchain-ai/langchain/assets/31132555/6ce1d679-db4c-4291-8453-01028ab2dca5">
  

I have added a test for simsimd. I feel it may not go well with the
CI/CD setup as installing simsimd is not a dependency requirement. I
have just imported simsimd to ensure simsimd cosine similarity is
invoked. However, its not a good approach. Suggestions are welcome and I
can make the required changes on the PR. Please provide guidance on the
same as I am new to the community.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-06-04 17:36:31 +00:00
Michal Gregor
98b2e7b195
huggingface[patch]: Support for HuggingFacePipeline in ChatHuggingFace. (#22194)
- **Description:** Added support for using HuggingFacePipeline in
ChatHuggingFace (previously it was only usable with API endpoints,
probably by oversight).
- **Issue:** #19997 
- **Dependencies:** none
- **Twitter handle:** none

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>
2024-06-04 00:47:35 +00:00
Miroslav
cbd5720011
huggingface[patch]: Skip Login to HuggingFaceHub when token is not set (#22365) 2024-06-03 15:20:32 -07:00
Bagatur
678a19a5f7
infra: bump anthropic mypy 1 (#22373) 2024-06-03 08:21:55 -07:00
Bagatur
a8098f5ddb
anthropic[patch]: Release 0.1.15, fix sdk tools break (#22369) 2024-05-31 12:10:22 -07:00
Erick Friis
6ffa0acf32
ai21: fix text-splitters version (#22366) 2024-05-31 11:41:05 -04:00
ccurme
f34337447f
openai: update ChatOpenAI api ref (#22324)
Update to reflect that token usage is no longer default in streaming
mode.

Add detail for streaming context under Token Usage section.
2024-05-30 12:31:28 -04:00