Commit Graph

84 Commits (9ac302cb97cbf9392ab8c37309873b069e277176)

Author SHA1 Message Date
Bagatur 93d0ad97fe
anthropic[patch]: test image input (#23155) 3 months ago
Leonid Ganeline 3dfd055411
anthropic: docstrings (#23145)
Added missed docstrings. Format docstrings to the consistent format
(used in the API Reference)
3 months ago
Bagatur 90559fde70
openai[patch], standard-tests[patch]: don't pass in falsey stop vals (#23153)
adds an image input test to standard-tests as well
3 months ago
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>
3 months ago
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
3 months ago
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
3 months ago
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}
```
3 months ago
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.
3 months ago
ccurme 3999761201
multiple: add `stop` attribute (#22573) 3 months ago
ccurme e08879147b
Revert "anthropic: stream token usage" (#22624)
Reverts langchain-ai/langchain#20180
3 months ago
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>
3 months ago
Bagatur cb183a9bf1
docs: update anthropic chat model (#22483)
Related to #22296

And update anthropic to accept base_url
4 months ago
Bagatur 678a19a5f7
infra: bump anthropic mypy 1 (#22373) 4 months ago
Bagatur a8098f5ddb
anthropic[patch]: Release 0.1.15, fix sdk tools break (#22369) 4 months ago
Erick Friis 42ffcb2ff1
anthropic: release 0.1.14rc2, test release note gen (#22147) 4 months ago
Bagatur baa3c975cb
anthropic[patch]: allow tool call mutation (#22130)
If tool_use blocks and tool_calls with overlapping IDs are present,
prefer the values of the tool_calls. Allows for mutating AIMessages just
via tool_calls.
4 months ago
Eugene Yurtsev 2d693c484e
docs: fix some spelling mistakes caught by newest version of code spell (#22090)
Going to merge this even though it doesn't pass all tests, and open a
separate PR for the remaining spelling mistakes.
4 months ago
ccurme 152c8cac33
anthropic, openai: cut pre-releases (#22083) 4 months ago
ccurme fbfed65fb1
core, partners: add token usage attribute to AIMessage (#21944)
```python
class UsageMetadata(TypedDict):
    """Usage metadata for a message, such as token counts.

    Attributes:
        input_tokens: (int) count of input (or prompt) tokens
        output_tokens: (int) count of output (or completion) tokens
        total_tokens: (int) total token count
    """

    input_tokens: int
    output_tokens: int
    total_tokens: int
```
```python
class AIMessage(BaseMessage):
    ...
    usage_metadata: Optional[UsageMetadata] = None
    """If provided, token usage information associated with the message."""
    ...
```
4 months ago
Bagatur 50186da0a1
infra: rm unused # noqa violations (#22049)
Updating #21137
4 months ago
ccurme 4be5537837
Revert "anthropic: set default model" (#21987)
Reverts langchain-ai/langchain#21986
4 months ago
ccurme 35439cf3bd
anthropic: set default model (#21986)
Various docs reference `ChatAnthropic()`, but this currently raises
ValidationError.
4 months ago
ccurme 4470d3b4a0
partners: bump core in packages implementing ls_params (#21868)
These packages all import `LangSmithParams` which was released in
langchain-core==0.2.0.

N.B. we will need to release `openai` and then bump `langchain-openai`
in `together` and `upstage`.
4 months ago
ccurme 181dfef118
core, standard tests, partner packages: add test for model params (#21677)
1. Adds `.get_ls_params` to BaseChatModel which returns
```python
class LangSmithParams(TypedDict, total=False):
    ls_provider: str
    ls_model_name: str
    ls_model_type: Literal["chat"]
    ls_temperature: Optional[float]
    ls_max_tokens: Optional[int]
    ls_stop: Optional[List[str]]
```
by default it will only return
```python
{ls_model_type="chat", ls_stop=stop}
```

2. Add these params to inheritable metadata in
`CallbackManager.configure`

3. Implement `.get_ls_params` and populate all params for Anthropic +
all subclasses of BaseChatOpenAI

Sample trace:
https://smith.langchain.com/public/d2962673-4c83-47c7-b51e-61d07aaffb1b/r

**OpenAI**:
<img width="984" alt="Screenshot 2024-05-17 at 10 03 35 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/2ef41f74-a9df-4e0e-905d-da74fa82a910">

**Anthropic**:
<img width="978" alt="Screenshot 2024-05-17 at 10 06 07 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/39701c9f-7da5-4f1a-ab14-84e9169d63e7">

**Mistral** (and all others for which params are not yet populated):
<img width="977" alt="Screenshot 2024-05-17 at 10 08 43 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/37d7d894-fec2-4300-986f-49a5f0191b03">
4 months ago
Bagatur 6416d16d39
anthropic[patch]: Release 0.1.13, tool_choice support (#21773) 4 months ago
Erick Friis aca98fd150
multiple: releases with relaxed core dep (#21724) 4 months ago
Erick Friis c77d2f2b06
multiple: core 0.2 nonbreaking dep, check_diff community->langchain dep (#21646)
0.2 is not a breaking release for core (but it is for langchain and
community)

To keep the core+langchain+community packages in sync at 0.2, we will
relax deps throughout the ecosystem to tolerate `langchain-core` 0.2
4 months ago
aditya thomas b868c78a12
partners[anthropic]: update unit test for key passed in from the environment (#21290)
**Description:** Update unit test for ChatAnthropic
**Issue:** Test for key passed in from the environment should not have
the key initialized in the constructor
**Dependencies:** None
5 months ago
ccurme 6da3d92b42
(all): update removal in deprecation warnings from 0.2 to 0.3 (#21265)
We are pushing out the removal of these to 0.3.

`find . -type f -name "*.py" -exec sed -i ''
's/removal="0\.2/removal="0.3/g' {} +`
5 months ago
aditya thomas 8b59bddc03
anthropic[patch]: add tests for secret_str for api key (#20986)
**Description:** Add tests to check API keys are masked
**Issue:** Resolves
https://github.com/langchain-ai/langchain/issues/12165 for Anthropic
models
**Dependencies:** None
5 months ago
ccurme 481d3855dc
patch: remove usage of llm, chat model __call__ (#20788)
- `llm(prompt)` -> `llm.invoke(prompt)`
- `llm(prompt=prompt` -> `llm.invoke(prompt)` (same with `messages=`)
- `llm(prompt, callbacks=callbacks)` -> `llm.invoke(prompt,
config={"callbacks": callbacks})`
- `llm(prompt, **kwargs)` -> `llm.invoke(prompt, **kwargs)`
5 months ago
Erick Friis 8c95ac3145
docs, multiple: de-beta with_structured_output (#20850) 5 months ago
Bagatur 54e9271504
anthropic[patch]: fix msg mutation (#20572) 5 months ago
Bagatur 984e7e36c2
anthropic[patch]: Release 0.1.10 (#20568) 5 months ago
Eugene Yurtsev 7a7851aa06
anthropic[patch]: Handle empty text block (#20566)
Handle empty text block
5 months ago
Erick Friis e7fe5f7d3f
anthropic[patch]: serialization in partner package (#18828) 5 months ago
Bagatur f74d5d642e
anthropic[patch]: bump to core 0.1.43 (#20537) 5 months ago
Bagatur 96d8769eae
anthropic[patch]: release 0.1.9, use tool calls if content is empty (#20535) 5 months ago
Fayfox 9fd36efdb5
anthropic[patch]: env ANTHROPIC_API_URL not work (#20507)
enviroment variable ANTHROPIC_API_URL will not work if anthropic_api_url
has default value

---------

Co-authored-by: Eugene Yurtsev <eugene@langchain.dev>
5 months ago
Bagatur f7667c614b
docs: update tool use case (#20404) 5 months ago
Erick Friis e6806a08d4
multiple: standard chat model tests (#20359) 5 months ago
Bagatur 799714c629
release anthropic, fireworks, openai, groq, mistral (#20333) 5 months ago
Erick Friis 9eb6f538f0
infra, multiple: rc release versions (#20252) 5 months ago
Bagatur e4046939d0
anthropic[patch]: Pre-release 0.1.8-rc.1 (#20250) 5 months ago
Bagatur 9514bc4d67
core[minor], ...: add tool calls message (#18947)
core[minor], langchain[patch], openai[minor], anthropic[minor], fireworks[minor], groq[minor], mistralai[minor]

```python
class ToolCall(TypedDict):
    name: str
    args: Dict[str, Any]
    id: Optional[str]

class InvalidToolCall(TypedDict):
    name: Optional[str]
    args: Optional[str]
    id: Optional[str]
    error: Optional[str]

class ToolCallChunk(TypedDict):
    name: Optional[str]
    args: Optional[str]
    id: Optional[str]
    index: Optional[int]


class AIMessage(BaseMessage):
    ...
    tool_calls: List[ToolCall] = []
    invalid_tool_calls: List[InvalidToolCall] = []
    ...


class AIMessageChunk(AIMessage, BaseMessageChunk):
    ...
    tool_call_chunks: Optional[List[ToolCallChunk]] = None
    ...
```
Important considerations:
- Parsing logic occurs within different providers;
- ~Changing output type is a breaking change for anyone doing explicit
type checking;~
- ~Langsmith rendering will need to be updated:
https://github.com/langchain-ai/langchainplus/pull/3561~
- ~Langserve will need to be updated~
- Adding chunks:
- ~AIMessage + ToolCallsMessage = ToolCallsMessage if either has
non-null .tool_calls.~
- Tool call chunks are appended, merging when having equal values of
`index`.
  - additional_kwargs accumulate the normal way.
- During streaming:
- ~Messages can change types (e.g., from AIMessageChunk to
AIToolCallsMessageChunk)~
- Output parsers parse additional_kwargs (during .invoke they read off
tool calls).

Packages outside of `partners/`:
- https://github.com/langchain-ai/langchain-cohere/pull/7
- https://github.com/langchain-ai/langchain-google/pull/123/files

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
5 months ago
Bagatur 4b84c9b28c
anthropic[patch]: Release 0.1.7 (#20240) 5 months ago
kaijietti a812839f0c
community: add request_timeout and max_retries to ChatAnthropic (#19402)
This PR make `request_timeout` and `max_retries` configurable for
ChatAnthropic.

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Erick Friis <erick@langchain.dev>
5 months ago
Bagatur a27d88f12a
anthropic[patch]: standardize init args (#20161)
Related to #20085
5 months ago
Maxime Perrin 5ac0d1f67b
partners[anthropic]: fix anthropic chat model message type lookup keys (#19034)
- **Description:** Fixing message formatting issue in ChatAnthropic
model by adding dictionary keys for `AIMessageChunk `and
`HumanMessageChunk`
  - **Issue:** #19025 
  - **Twitter handle:** @maximeperrin_

Co-authored-by: Maxime Perrin <mperrin@doing.fr>
Co-authored-by: Erick Friis <erick@langchain.dev>
6 months ago
Bagatur 46f580d42d
docs: anthropic tool docstring (#20091) 6 months ago