lock

Co-authored-by: Lance Martin <lance@langchain.dev>

cookbook/code-analysis-deeplake.ipynb

@@ -648,7 +648,7 @@
     {
      "data": {
       "text/plain": [
-       "OpenAIEmbeddings(client=<class 'openai.api_resources.embedding.Embedding'>, model='text-embedding-ada-002', deployment='text-embedding-ada-002', openai_api_version='', openai_api_base='', openai_api_type='', openai_proxy='', embedding_ctx_length=8191, openai_api_key='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', openai_organization='', allowed_special=set(), disallowed_special='all', chunk_size=1000, max_retries=6, request_timeout=None, headers=None, tiktoken_model_name=None, show_progress_bar=False, model_kwargs={})"
+       "OpenAIEmbeddings(client=<class 'openai.api_resources.embedding.Embedding'>, model='text-embedding-ada-002', deployment='text-embedding-ada-002', openai_api_version='', openai_api_base='', openai_api_type='', openai_proxy='', embedding_ctx_length=8191, openai_api_key='', openai_organization='', allowed_special=set(), disallowed_special='all', chunk_size=1000, max_retries=6, request_timeout=None, headers=None, tiktoken_model_name=None, show_progress_bar=False, model_kwargs={})"
       ]
      },
      "execution_count": 13,

cookbook/docugami_xml_kg_rag.ipynb

@@ -52,6 +52,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "c6fb4903-f845-4907-ae14-df305891b0ff",
    "metadata": {},
    "source": [
     "## Data Loading\n",
@@ -76,17 +77,18 @@
   {
    "cell_type": "code",
    "execution_count": 45,
+   "id": "fc0767d4-9155-4591-855c-ef2e14e0e10f",
    "metadata": {},
    "outputs": [],
    "source": [
     "import os\n",
+    "import tempfile\n",
     "from pathlib import Path\n",
     "from pprint import pprint\n",
-    "import requests\n",
-    "import tempfile\n",
     "from time import sleep\n",
     "from typing import Dict, List\n",
     "\n",
+    "import requests\n",
     "from docugami import Docugami\n",
     "from docugami.types import Document as DocugamiDocument\n",
     "\n",
@@ -166,6 +168,7 @@
   {
    "cell_type": "code",
    "execution_count": 46,
+   "id": "ce0b2b21-7623-46e7-ae2c-3a9f67e8b9b9",
    "metadata": {},
    "outputs": [
     {
@@ -207,6 +210,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "01f035e5-c3f8-4d23-9d1b-8d2babdea8e9",
    "metadata": {},
    "source": [
     "If you are on the free Docugami tier, your files should be done in ~15 minutes or less depending on the number of pages uploaded and available resources (please contact Docugami for paid plans for faster processing). You can re-run the code above without reprocessing your files to continue waiting if your notebook is not continuously running (it does not re-upload)."
@@ -225,6 +229,7 @@
   {
    "cell_type": "code",
    "execution_count": 47,
+   "id": "05fcdd57-090f-44bf-a1fb-2c3609c80e34",
    "metadata": {},
    "outputs": [
     {
@@ -268,6 +273,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "bfc1f2c9-e6d4-4d98-a799-6bc30bc61661",
    "metadata": {},
    "source": [
     "The file processed by Docugami in the example above was [this one](https://data.ntsb.gov/carol-repgen/api/Aviation/ReportMain/GenerateNewestReport/192541/pdf) from the NTSB and you can look at the PDF side by side to compare the XML chunks above. \n",
@@ -278,6 +284,7 @@
   {
    "cell_type": "code",
    "execution_count": 48,
+   "id": "8a4b49e0-de78-4790-a930-ad7cf324697a",
    "metadata": {},
    "outputs": [
     {
@@ -326,6 +333,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "1cfc06bc-67d2-46dd-b04d-95efa3619d0a",
    "metadata": {},
    "source": [
     "## Docugami XML Deep Dive: Jane Doe NDA Example\n",
@@ -336,6 +344,7 @@
   {
    "cell_type": "code",
    "execution_count": 109,
+   "id": "7b697d30-1e94-47f0-87e8-f81d4b180da2",
    "metadata": {},
    "outputs": [
     {
@@ -361,6 +370,7 @@
   {
    "cell_type": "code",
    "execution_count": 98,
+   "id": "14714576-6e1d-499b-bcc8-39140bb2fd78",
    "metadata": {},
    "outputs": [
     {
@@ -415,6 +425,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "dc09ba64-4973-4471-9501-54294c1143fc",
    "metadata": {},
    "source": [
     "The Docugami XML contains extremely detailed semantics and visual bounding boxes for all elements. The `dgml-utils` library parses text and non-text elements into formats appropriate to pass into LLMs (chunked text with XML semantic labels)"
@@ -423,6 +434,7 @@
   {
    "cell_type": "code",
    "execution_count": 100,
+   "id": "2b4ece00-2e43-4254-adc9-66dbb79139a6",
    "metadata": {},
    "outputs": [
     {
@@ -460,6 +472,7 @@
   {
    "cell_type": "code",
    "execution_count": 101,
+   "id": "08350119-aa22-4ec1-8f65-b1316a0d4123",
    "metadata": {},
    "outputs": [
     {
@@ -476,6 +489,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "dca87b46-c0c2-4973-94ec-689c18075653",
    "metadata": {},
    "source": [
     "The XML markup contains structural as well as semantic tags, which provide additional semantics to the LLM for improved retrieval and generation.\n",
@@ -486,6 +500,7 @@
   {
    "cell_type": "code",
    "execution_count": 112,
+   "id": "bcac8294-c54a-4b6e-af9d-3911a69620b2",
    "metadata": {},
    "outputs": [
     {
@@ -539,8 +554,8 @@
     "from langchain.chat_models import ChatOpenAI\n",
     "from langchain.prompts import (\n",
     "    ChatPromptTemplate,\n",
-    "    SystemMessagePromptTemplate,\n",
     "    HumanMessagePromptTemplate,\n",
+    "    SystemMessagePromptTemplate,\n",
     ")\n",
     "from langchain.schema.output_parser import StrOutputParser"
    ]
@@ -610,11 +625,12 @@
    "outputs": [],
    "source": [
     "import uuid\n",
-    "from langchain.vectorstores.chroma import Chroma\n",
-    "from langchain.storage import InMemoryStore\n",
-    "from langchain.schema.document import Document\n",
+    "\n",
     "from langchain.embeddings import OpenAIEmbeddings\n",
     "from langchain.retrievers.multi_vector import MultiVectorRetriever\n",
+    "from langchain.schema.document import Document\n",
+    "from langchain.storage import InMemoryStore\n",
+    "from langchain.vectorstores.chroma import Chroma\n",
     "\n",
     "\n",
     "def build_retriever(text_elements, tables, table_summaries):\n",
@@ -710,6 +726,7 @@
   {
    "cell_type": "code",
    "execution_count": 120,
+   "id": "636e992f-823b-496b-a082-8b4fcd479de5",
    "metadata": {},
    "outputs": [
     {
@@ -743,6 +760,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "86cad5db-81fe-4ae6-a20e-550b85fcbe96",
    "metadata": {},
    "source": [
     "# RAG on Llama2 paper\n",
@@ -753,6 +771,7 @@
   {
    "cell_type": "code",
    "execution_count": 121,
+   "id": "0e4a2f43-dd48-4ae3-8e27-7e87d169965f",
    "metadata": {},
    "outputs": [
     {
@@ -777,6 +796,7 @@
   {
    "cell_type": "code",
    "execution_count": 124,
+   "id": "56b78fb3-603d-4343-ae72-be54a3c5dd72",
    "metadata": {},
    "outputs": [
     {
@@ -801,6 +821,7 @@
   {
    "cell_type": "code",
    "execution_count": 125,
+   "id": "d3cc5ba9-8553-4eda-a5d1-b799751186af",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -812,6 +833,7 @@
   {
    "cell_type": "code",
    "execution_count": 126,
+   "id": "d7c73faf-74cb-400d-8059-b69e2493de38",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -823,6 +845,7 @@
   {
    "cell_type": "code",
    "execution_count": 127,
+   "id": "4c553722-be42-42ce-83b8-76a17f323f1c",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -832,6 +855,7 @@
   {
    "cell_type": "code",
    "execution_count": 128,
+   "id": "65dce40b-f1c3-494a-949e-69a9c9544ddb",
    "metadata": {},
    "outputs": [
     {
@@ -851,6 +875,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "59877edf-9a02-45db-95cb-b7f4234abfa3",
    "metadata": {},
    "source": [
     "We can check the [trace](https://smith.langchain.com/public/5de100c3-bb40-4234-bf02-64bc708686a1/r) to see what chunks were retrieved.\n",
@@ -939,6 +964,7 @@
   },
   {
    "cell_type": "markdown",
+   "id": "0879349e-7298-4f2c-b246-f1142e97a8e5",
    "metadata": {},
    "source": []
   }

cookbook/llm_bash.ipynb

@@ -69,8 +69,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "from langchain.chains.llm_bash.prompt import BashOutputParser\n",
     "from langchain.prompts.prompt import PromptTemplate\n",
+    "from langchain_experimental.llm_bash.prompt import BashOutputParser\n",
     "\n",
     "_PROMPT_TEMPLATE = \"\"\"If someone asks you to perform a task, your job is to come up with a series of bash commands that will perform the task. There is no need to put \"#!/bin/bash\" in your answer. Make sure to reason step by step, using this format:\n",
     "Question: \"copy the files in the directory named 'target' into a new directory at the same level as target called 'myNewDirectory'\"\n",

libs/core/Makefile

@@ -26,6 +26,8 @@ lint format: PYTHON_FILES=.
 lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/experimental --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
 
 lint lint_diff:
+	./scripts/check_pydantic.sh .
+	./scripts/check_imports.sh
 	poetry run ruff .
 	[ "$(PYTHON_FILES)" = "" ] || poetry run ruff format $(PYTHON_FILES) --diff
 	[ "$(PYTHON_FILES)" = "" ] || poetry run mypy $(PYTHON_FILES)

libs/core/langchain_core/callbacks/base.py

@@ -1,15 +1,16 @@
 """Base callback handler that can be used to handle callbacks in langchain."""
 from __future__ import annotations
 
-from typing import Any, Dict, List, Optional, Sequence, TypeVar, Union
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, TypeVar, Union
 from uuid import UUID
 
 from tenacity import RetryCallState
 
-from langchain_core.agents import AgentAction, AgentFinish
-from langchain_core.documents import Document
-from langchain_core.messages import BaseMessage
-from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult
+if TYPE_CHECKING:
+    from langchain_core.agents import AgentAction, AgentFinish
+    from langchain_core.documents import Document
+    from langchain_core.messages import BaseMessage
+    from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult
 
 
 class RetrieverManagerMixin:

libs/core/langchain_core/callbacks/manager.py

@@ -7,6 +7,7 @@ import uuid
 from concurrent.futures import ThreadPoolExecutor
 from contextlib import asynccontextmanager, contextmanager
 from typing import (
+    TYPE_CHECKING,
     Any,
     AsyncGenerator,
     Coroutine,
@@ -25,7 +26,6 @@ from uuid import UUID
 from langsmith.run_helpers import get_run_tree_context
 from tenacity import RetryCallState
 
-from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.callbacks.base import (
     BaseCallbackHandler,
     BaseCallbackManager,
@@ -37,11 +37,14 @@ from langchain_core.callbacks.base import (
     ToolManagerMixin,
 )
 from langchain_core.callbacks.stdout import StdOutCallbackHandler
-from langchain_core.documents import Document
 from langchain_core.messages import BaseMessage, get_buffer_string
-from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult
 from langchain_core.utils.env import env_var_is_set
 
+if TYPE_CHECKING:
+    from langchain_core.agents import AgentAction, AgentFinish
+    from langchain_core.documents import Document
+    from langchain_core.outputs import ChatGenerationChunk, GenerationChunk, LLMResult
+
 logger = logging.getLogger(__name__)
 
 

libs/core/langchain_core/callbacks/stdout.py

@@ -1,11 +1,15 @@
 """Callback Handler that prints to std out."""
-from typing import Any, Dict, List, Optional
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Any, Dict, List, Optional
 
-from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.callbacks.base import BaseCallbackHandler
-from langchain_core.outputs import LLMResult
 from langchain_core.utils import print_text
 
+if TYPE_CHECKING:
+    from langchain_core.agents import AgentAction, AgentFinish
+    from langchain_core.outputs import LLMResult
+
 
 class StdOutCallbackHandler(BaseCallbackHandler):
     """Callback Handler that prints to std out."""

libs/core/langchain_core/callbacks/streaming_stdout.py

@@ -1,11 +1,15 @@
 """Callback Handler streams to stdout on new llm token."""
-import sys
-from typing import Any, Dict, List
+from __future__ import annotations
+
+import sys
+from typing import TYPE_CHECKING, Any, Dict, List
 
-from langchain_core.agents import AgentAction, AgentFinish
 from langchain_core.callbacks.base import BaseCallbackHandler
-from langchain_core.messages import BaseMessage
-from langchain_core.outputs import LLMResult
+
+if TYPE_CHECKING:
+    from langchain_core.agents import AgentAction, AgentFinish
+    from langchain_core.messages import BaseMessage
+    from langchain_core.outputs import LLMResult
 
 
 class StreamingStdOutCallbackHandler(BaseCallbackHandler):

libs/core/langchain_core/document_transformers.py

@@ -3,9 +3,10 @@ from __future__ import annotations
 import asyncio
 from abc import ABC, abstractmethod
 from functools import partial
-from typing import Any, Sequence
+from typing import TYPE_CHECKING, Any, Sequence
 
-from langchain_core.documents import Document
+if TYPE_CHECKING:
+    from langchain_core.documents import Document
 
 
 class BaseDocumentTransformer(ABC):

libs/core/langchain_core/example_selectors/semantic_similarity.py

@@ -1,13 +1,15 @@
 """Example selector that selects examples based on SemanticSimilarity."""
 from __future__ import annotations
 
-from typing import Any, Dict, List, Optional, Type
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Type
 
-from langchain_core.embeddings import Embeddings
 from langchain_core.example_selectors.base import BaseExampleSelector
 from langchain_core.pydantic_v1 import BaseModel, Extra
 from langchain_core.vectorstores import VectorStore
 
+if TYPE_CHECKING:
+    from langchain_core.embeddings import Embeddings
+
 
 def sorted_values(values: Dict[str, str]) -> List[Any]:
     """Return a list of values in dict sorted by key."""

libs/core/langchain_core/language_models/base.py

@@ -16,13 +16,13 @@ from typing import (
 from typing_extensions import TypeAlias
 
 from langchain_core.messages import AnyMessage, BaseMessage, get_buffer_string
-from langchain_core.outputs import LLMResult
 from langchain_core.prompt_values import PromptValue
 from langchain_core.runnables import RunnableSerializable
 from langchain_core.utils import get_pydantic_field_names
 
 if TYPE_CHECKING:
     from langchain_core.callbacks import Callbacks
+    from langchain_core.outputs import LLMResult
 
 
 @lru_cache(maxsize=None)  # Cache the tokenizer

libs/core/langchain_core/language_models/chat_models.py

@@ -1,9 +1,12 @@
+from __future__ import annotations
+
 import asyncio
 import inspect
 import warnings
 from abc import ABC, abstractmethod
 from functools import partial
 from typing import (
+    TYPE_CHECKING,
     Any,
     AsyncIterator,
     Dict,
@@ -41,7 +44,9 @@ from langchain_core.outputs import (
 )
 from langchain_core.prompt_values import ChatPromptValue, PromptValue, StringPromptValue
 from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.runnables import RunnableConfig
+
+if TYPE_CHECKING:
+    from langchain_core.runnables import RunnableConfig
 
 
 def _get_verbosity() -> bool:

libs/core/langchain_core/language_models/llms.py

@@ -37,10 +37,10 @@ from tenacity import (
     wait_exponential,
 )
 
-from langchain_core.callbacks.base import BaseCallbackManager
-from langchain_core.callbacks.manager import (
+from langchain_core.callbacks import (
     AsyncCallbackManager,
     AsyncCallbackManagerForLLMRun,
+    BaseCallbackManager,
     CallbackManager,
     CallbackManagerForLLMRun,
     Callbacks,

libs/core/langchain_core/messages/__init__.py

@@ -54,6 +54,8 @@ def get_buffer_string(
             role = "System"
         elif isinstance(m, FunctionMessage):
             role = "Function"
+        elif isinstance(m, ToolMessage):
+            role = "Tool"
         elif isinstance(m, ChatMessage):
             role = m.role
         else:

libs/core/langchain_core/output_parsers/base.py

@@ -4,6 +4,7 @@ import asyncio
 import functools
 from abc import ABC, abstractmethod
 from typing import (
+    TYPE_CHECKING,
     Any,
     Dict,
     Generic,
@@ -18,9 +19,11 @@ from typing_extensions import get_args
 
 from langchain_core.messages import AnyMessage, BaseMessage
 from langchain_core.outputs import ChatGeneration, Generation
-from langchain_core.prompt_values import PromptValue
 from langchain_core.runnables import RunnableConfig, RunnableSerializable
 
+if TYPE_CHECKING:
+    from langchain_core.prompt_values import PromptValue
+
 T = TypeVar("T")
 
 

libs/core/langchain_core/output_parsers/transform.py

@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 from typing import (
+    TYPE_CHECKING,
     Any,
     AsyncIterator,
     Iterator,
@@ -16,7 +17,9 @@ from langchain_core.outputs import (
     Generation,
     GenerationChunk,
 )
-from langchain_core.runnables import RunnableConfig
+
+if TYPE_CHECKING:
+    from langchain_core.runnables import RunnableConfig
 
 
 class BaseTransformOutputParser(BaseOutputParser[T]):

libs/core/langchain_core/prompts/__init__.py

@@ -41,7 +41,7 @@ from langchain_core.prompts.few_shot import (
 from langchain_core.prompts.few_shot_with_templates import FewShotPromptWithTemplates
 from langchain_core.prompts.loading import load_prompt
 from langchain_core.prompts.pipeline import PipelinePromptTemplate
-from langchain_core.prompts.prompt import Prompt, PromptTemplate
+from langchain_core.prompts.prompt import PromptTemplate
 from langchain_core.prompts.string import (
     StringPromptTemplate,
     check_valid_template,
@@ -62,7 +62,6 @@ __all__ = [
     "HumanMessagePromptTemplate",
     "MessagesPlaceholder",
     "PipelinePromptTemplate",
-    "Prompt",
     "PromptTemplate",
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",

libs/core/langchain_core/prompts/base.py

@@ -3,16 +3,32 @@ from __future__ import annotations
 import json
 from abc import ABC, abstractmethod
 from pathlib import Path
-from typing import Any, Callable, Dict, List, Mapping, Optional, Type, Union
+from typing import (
+    TYPE_CHECKING,
+    Any,
+    Callable,
+    Dict,
+    List,
+    Mapping,
+    Optional,
+    Type,
+    Union,
+)
 
 import yaml
 
-from langchain_core.documents import Document
 from langchain_core.output_parsers.base import BaseOutputParser
-from langchain_core.prompt_values import PromptValue
+from langchain_core.prompt_values import (
+    ChatPromptValueConcrete,
+    PromptValue,
+    StringPromptValue,
+)
 from langchain_core.pydantic_v1 import BaseModel, Field, create_model, root_validator
 from langchain_core.runnables import RunnableConfig, RunnableSerializable
 
+if TYPE_CHECKING:
+    from langchain_core.documents import Document
+
 
 class BasePromptTemplate(RunnableSerializable[Dict, PromptValue], ABC):
     """Base class for all prompt templates, returning a prompt."""
@@ -40,11 +56,6 @@ class BasePromptTemplate(RunnableSerializable[Dict, PromptValue], ABC):
 
     @property
     def OutputType(self) -> Any:
-        from langchain_core.prompt_values import (
-            ChatPromptValueConcrete,
-            StringPromptValue,
-        )
-
         return Union[StringPromptValue, ChatPromptValueConcrete]
 
     def get_input_schema(

libs/core/langchain_core/prompts/chat.py

@@ -8,6 +8,7 @@ from typing import (
     Callable,
     Dict,
     List,
+    Optional,
     Sequence,
     Set,
     Tuple,
@@ -136,6 +137,7 @@ class BaseStringMessagePromptTemplate(BaseMessagePromptTemplate, ABC):
         cls: Type[MessagePromptTemplateT],
         template: str,
         template_format: str = "f-string",
+        partial_variables: Optional[Dict[str, Any]] = None,
         **kwargs: Any,
     ) -> MessagePromptTemplateT:
         """Create a class from a string template.
@@ -143,12 +145,21 @@ class BaseStringMessagePromptTemplate(BaseMessagePromptTemplate, ABC):
         Args:
             template: a template.
             template_format: format of the template.
+            partial_variables: A dictionary of variables that can be used to partially
+                               fill in the template. For example, if the template is
+                              `"{variable1} {variable2}"`, and `partial_variables` is
+                              `{"variable1": "foo"}`, then the final prompt will be
+                              `"foo {variable2}"`.
             **kwargs: keyword arguments to pass to the constructor.
 
         Returns:
             A new instance of this class.
         """
-        prompt = PromptTemplate.from_template(template, template_format=template_format)
+        prompt = PromptTemplate.from_template(
+            template,
+            template_format=template_format,
+            partial_variables=partial_variables,
+        )
         return cls(prompt=prompt, **kwargs)
 
     @classmethod

libs/core/langchain_core/prompts/prompt.py

@@ -244,7 +244,3 @@ class PromptTemplate(StringPromptTemplate):
             partial_variables=_partial_variables,
             **kwargs,
         )
-
-
-# For backwards compatibility.
-Prompt = PromptTemplate

libs/core/langchain_core/runnables/base.py

@@ -31,17 +31,6 @@ from typing import (
 
 from typing_extensions import Literal, get_args
 
-if TYPE_CHECKING:
-    from langchain_core.callbacks.manager import (
-        AsyncCallbackManagerForChainRun,
-        CallbackManagerForChainRun,
-    )
-    from langchain_core.runnables.fallbacks import (
-        RunnableWithFallbacks as RunnableWithFallbacksT,
-    )
-    from langchain_core.tracers.log_stream import RunLog, RunLogPatch
-    from langchain_core.tracers.root_listeners import Listener
-
 from langchain_core.load.dump import dumpd
 from langchain_core.load.serializable import Serializable
 from langchain_core.pydantic_v1 import BaseModel, Field, create_model
@@ -75,6 +64,18 @@ from langchain_core.runnables.utils import (
 from langchain_core.utils.aiter import atee, py_anext
 from langchain_core.utils.iter import safetee
 
+if TYPE_CHECKING:
+    from langchain_core.callbacks.manager import (
+        AsyncCallbackManagerForChainRun,
+        CallbackManagerForChainRun,
+    )
+    from langchain_core.runnables.fallbacks import (
+        RunnableWithFallbacks as RunnableWithFallbacksT,
+    )
+    from langchain_core.tracers.log_stream import RunLog, RunLogPatch
+    from langchain_core.tracers.root_listeners import Listener
+
+
 Other = TypeVar("Other")
 
 

libs/core/langchain_core/tools.py

@@ -9,10 +9,10 @@ from functools import partial
 from inspect import signature
 from typing import Any, Awaitable, Callable, Dict, List, Optional, Tuple, Type, Union
 
-from langchain_core.callbacks.base import BaseCallbackManager
-from langchain_core.callbacks.manager import (
+from langchain_core.callbacks import (
     AsyncCallbackManager,
     AsyncCallbackManagerForToolRun,
+    BaseCallbackManager,
     CallbackManager,
     CallbackManagerForToolRun,
     Callbacks,

libs/core/langchain_core/tracers/base.py

@@ -4,13 +4,12 @@ from __future__ import annotations
 import logging
 from abc import ABC, abstractmethod
 from datetime import datetime
-from typing import Any, Dict, List, Optional, Sequence, Union, cast
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, Union, cast
 from uuid import UUID
 
 from tenacity import RetryCallState
 
 from langchain_core.callbacks.base import BaseCallbackHandler
-from langchain_core.documents import Document
 from langchain_core.exceptions import TracerException
 from langchain_core.load import dumpd
 from langchain_core.outputs import (
@@ -21,6 +20,9 @@ from langchain_core.outputs import (
 )
 from langchain_core.tracers.schemas import Run
 
+if TYPE_CHECKING:
+    from langchain_core.documents import Document
+
 logger = logging.getLogger(__name__)
 
 

libs/core/langchain_core/tracers/evaluation.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 import logging
 import threading
 import weakref
-from concurrent.futures import Future, ThreadPoolExecutor, wait
+from concurrent.futures import Future, ThreadPoolExecutor, as_completed, wait
 from typing import Any, Dict, List, Optional, Sequence, Tuple, Union, cast
 from uuid import UUID
 
@@ -22,12 +22,33 @@ logger = logging.getLogger(__name__)
 _TRACERS: weakref.WeakSet[EvaluatorCallbackHandler] = weakref.WeakSet()
 
 
-def wait_for_all_evaluators() -> None:
-    """Wait for all tracers to finish."""
+def wait_for_all_evaluators(verbose: bool = True) -> None:
+    """Wait for all tracers to finish using concurrent futures."""
     global _TRACERS
-    for tracer in list(_TRACERS):
-        if tracer is not None:
-            tracer.wait_for_futures()
+    tracers = list(_TRACERS)
+    futures = []
+
+    with ThreadPoolExecutor() as executor:
+        for tracer in tracers:
+            if tracer is not None:
+                # Submit each wait_for_futures call to the executor
+                futures.append(executor.submit(tracer.wait_for_futures))
+
+        if verbose:
+            try:
+                from tqdm.auto import tqdm  # noqa: F401
+
+                # Iterate over futures as they complete
+                for future in tqdm(
+                    as_completed(futures),
+                    total=len(futures),
+                    desc="Waiting for evaluators to finish",
+                ):
+                    future.result()  # You can handle results or exceptions here
+            except ImportError:
+                # If tqdm is not installed, just wait without progress bar
+                for future in as_completed(futures):
+                    future.result()
 
 
 class EvaluatorCallbackHandler(BaseTracer):

libs/core/langchain_core/tracers/langchain.py

@@ -5,7 +5,7 @@ import logging
 import weakref
 from concurrent.futures import Future, ThreadPoolExecutor, wait
 from datetime import datetime
-from typing import Any, Callable, Dict, List, Optional, Union
+from typing import TYPE_CHECKING, Any, Callable, Dict, List, Optional, Union
 from uuid import UUID
 
 from langsmith import Client
@@ -19,10 +19,12 @@ from tenacity import (
 
 from langchain_core.env import get_runtime_environment
 from langchain_core.load import dumpd
-from langchain_core.messages import BaseMessage
 from langchain_core.tracers.base import BaseTracer
 from langchain_core.tracers.schemas import Run
 
+if TYPE_CHECKING:
+    from langchain_core.messages import BaseMessage
+
 logger = logging.getLogger(__name__)
 _LOGGED = set()
 _TRACERS: weakref.WeakSet[LangChainTracer] = weakref.WeakSet()

libs/core/langchain_core/vectorstores.py

@@ -21,7 +21,6 @@ from typing import (
     TypeVar,
 )
 
-from langchain_core.documents import Document
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.retrievers import BaseRetriever
@@ -31,6 +30,7 @@ if TYPE_CHECKING:
         AsyncCallbackManagerForRetrieverRun,
         CallbackManagerForRetrieverRun,
     )
+    from langchain_core.documents import Document
 
 logger = logging.getLogger(__name__)
 

libs/core/poetry.lock

@@ -793,7 +793,6 @@ optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
     {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
-    {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
 ]
 
 [[package]]
@@ -2524,6 +2523,17 @@ files = [
 [package.dependencies]
 urllib3 = ">=2"
 
+[[package]]
+name = "types-tqdm"
+version = "4.66.0.4"
+description = "Typing stubs for tqdm"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "types-tqdm-4.66.0.4.tar.gz", hash = "sha256:a2f0ebd4cfd48f4914395819a176d7947387e1b98f9228fca38f8cac1b59891c"},
+    {file = "types_tqdm-4.66.0.4-py3-none-any.whl", hash = "sha256:8eda4c5123dd66985a4cb44268705cfa18beb32d66772271ae185e92b8b10c40"},
+]
+
 [[package]]
 name = "typing-extensions"
 version = "4.8.0"
@@ -2686,4 +2696,4 @@ testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "p
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "b08d47f726dd194af0f801d300402b174c8db96a4184cc1136cb8e5a0e287190"
+content-hash = "6c0cc519dbf48494aa7f95416fa777406ae0a3c0b68d1056b38fd2e1446ea718"

libs/core/pyproject.toml

@@ -22,6 +22,7 @@ ruff = "^0.1.5"
 mypy = "^0.991"
 types-pyyaml = "^6.0.12.2"
 types-requests = "^2.28.11.5"
+types-tqdm = "^4.66.0.4"
 
 [tool.poetry.group.dev.dependencies]
 jupyter = "^1.0.0"

libs/core/scripts/check_imports.sh

@@ -0,0 +1,17 @@
+#!/bin/bash
+
+set -eu
+
+# Initialize a variable to keep track of errors
+errors=0
+
+# make sure not importing from langchain or langchain_experimental
+git --no-pager grep '^from langchain\.' . && errors=$((errors+1))
+git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
+
+# Decide on an exit status based on the errors
+if [ "$errors" -gt 0 ]; then
+    exit 1
+else
+    exit 0
+fi

libs/core/scripts/check_pydantic.sh

@@ -0,0 +1,27 @@
+#!/bin/bash
+#
+# This script searches for lines starting with "import pydantic" or "from pydantic"
+# in tracked files within a Git repository.
+#
+# Usage: ./scripts/check_pydantic.sh /path/to/repository
+
+# Check if a path argument is provided
+if [ $# -ne 1 ]; then
+  echo "Usage: $0 /path/to/repository"
+  exit 1
+fi
+
+repository_path="$1"
+
+# Search for lines matching the pattern within the specified repository
+result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic')
+
+# Check if any matching lines were found
+if [ -n "$result" ]; then
+  echo "ERROR: The following lines need to be updated:"
+  echo "$result"
+  echo "Please replace the code with an import from langchain_core.pydantic_v1."
+  echo "For example, replace 'from pydantic import BaseModel'"
+  echo "with 'from langchain_core.pydantic_v1 import BaseModel'"
+  exit 1
+fi

libs/core/tests/unit_tests/language_models/llms/test_base.py

@@ -0,0 +1,19 @@
+from tests.unit_tests.fake.llm import FakeListLLM
+
+
+def test_batch() -> None:
+    llm = FakeListLLM(responses=["foo"] * 3)
+    output = llm.batch(["foo", "bar", "foo"])
+    assert output == ["foo"] * 3
+
+    output = llm.batch(["foo", "bar", "foo"], config={"max_concurrency": 2})
+    assert output == ["foo"] * 3
+
+
+async def test_abatch() -> None:
+    llm = FakeListLLM(responses=["foo"] * 3)
+    output = await llm.abatch(["foo", "bar", "foo"])
+    assert output == ["foo"] * 3
+
+    output = await llm.abatch(["foo", "bar", "foo"], config={"max_concurrency": 2})
+    assert output == ["foo"] * 3

libs/core/tests/unit_tests/prompts/test_imports.py

@@ -13,7 +13,6 @@ EXPECTED_ALL = [
     "HumanMessagePromptTemplate",
     "MessagesPlaceholder",
     "PipelinePromptTemplate",
-    "Prompt",
     "PromptTemplate",
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",

libs/core/tests/unit_tests/test_messages.py

@@ -1,10 +1,21 @@
+import unittest
+
 import pytest
 
 from langchain_core.messages import (
+    AIMessage,
     AIMessageChunk,
+    ChatMessage,
     ChatMessageChunk,
+    FunctionMessage,
     FunctionMessageChunk,
+    HumanMessage,
     HumanMessageChunk,
+    SystemMessage,
+    ToolMessage,
+    get_buffer_string,
+    messages_from_dict,
+    messages_to_dict,
 )
 
 
@@ -100,3 +111,76 @@ def test_ani_message_chunks() -> None:
         AIMessageChunk(example=True, content="I am") + AIMessageChunk(
             example=False, content=" indeed."
         )
+
+
+class TestGetBufferString(unittest.TestCase):
+    def setUp(self) -> None:
+        self.human_msg = HumanMessage(content="human")
+        self.ai_msg = AIMessage(content="ai")
+        self.sys_msg = SystemMessage(content="system")
+        self.func_msg = FunctionMessage(name="func", content="function")
+        self.tool_msg = ToolMessage(tool_call_id="tool_id", content="tool")
+        self.chat_msg = ChatMessage(role="Chat", content="chat")
+
+    def test_empty_input(self) -> None:
+        self.assertEqual(get_buffer_string([]), "")
+
+    def test_valid_single_message(self) -> None:
+        expected_output = f"Human: {self.human_msg.content}"
+        self.assertEqual(
+            get_buffer_string([self.human_msg]),
+            expected_output,
+        )
+
+    def test_custom_human_prefix(self) -> None:
+        prefix = "H"
+        expected_output = f"{prefix}: {self.human_msg.content}"
+        self.assertEqual(
+            get_buffer_string([self.human_msg], human_prefix="H"),
+            expected_output,
+        )
+
+    def test_custom_ai_prefix(self) -> None:
+        prefix = "A"
+        expected_output = f"{prefix}: {self.ai_msg.content}"
+        self.assertEqual(
+            get_buffer_string([self.ai_msg], ai_prefix="A"),
+            expected_output,
+        )
+
+    def test_multiple_msg(self) -> None:
+        msgs = [
+            self.human_msg,
+            self.ai_msg,
+            self.sys_msg,
+            self.func_msg,
+            self.tool_msg,
+            self.chat_msg,
+        ]
+        expected_output = "\n".join(
+            [
+                "Human: human",
+                "AI: ai",
+                "System: system",
+                "Function: function",
+                "Tool: tool",
+                "Chat: chat",
+            ]
+        )
+        self.assertEqual(
+            get_buffer_string(msgs),
+            expected_output,
+        )
+
+
+def test_multiple_msg() -> None:
+    human_msg = HumanMessage(content="human", additional_kwargs={"key": "value"})
+    ai_msg = AIMessage(content="ai")
+    sys_msg = SystemMessage(content="sys")
+
+    msgs = [
+        human_msg,
+        ai_msg,
+        sys_msg,
+    ]
+    assert messages_from_dict(messages_to_dict(msgs)) == msgs

libs/langchain/langchain/chat_models/base.py

@@ -3,6 +3,7 @@ from langchain_core.language_models.chat_models import (
     SimpleChatModel,
     _agenerate_from_stream,
     _generate_from_stream,
+    _get_verbosity,
 )
 
 __all__ = [
@@ -10,4 +11,5 @@ __all__ = [
     "SimpleChatModel",
     "_generate_from_stream",
     "_agenerate_from_stream",
+    "_get_verbosity",
 ]

libs/langchain/langchain/chat_models/bedrock.py

@@ -28,7 +28,7 @@ class ChatPromptAdapter:
     ) -> str:
         if provider == "anthropic":
             prompt = convert_messages_to_prompt_anthropic(messages=messages)
-        if provider == "meta":
+        elif provider == "meta":
             prompt = convert_messages_to_prompt_llama(messages=messages)
         else:
             raise NotImplementedError(

libs/langchain/langchain/embeddings/voyageai.py

@@ -115,10 +115,16 @@ class VoyageEmbeddings(BaseModel, Embeddings):
         return params
 
     def _get_embeddings(
-        self, texts: List[str], batch_size: int, input_type: Optional[str] = None
+        self,
+        texts: List[str],
+        batch_size: Optional[int] = None,
+        input_type: Optional[str] = None,
     ) -> List[List[float]]:
         embeddings: List[List[float]] = []
 
+        if batch_size is None:
+            batch_size = self.batch_size
+
         if self.show_progress_bar:
             try:
                 from tqdm.auto import tqdm
@@ -168,9 +174,24 @@ class VoyageEmbeddings(BaseModel, Embeddings):
         Args:
             text: The text to embed.
 
+        Returns:
+            Embedding for the text.
+        """
+        return self._get_embeddings([text], input_type="query")[0]
+
+    def embed_general_texts(
+        self, texts: List[str], *, input_type: Optional[str] = None
+    ) -> List[List[float]]:
+        """Call out to Voyage Embedding endpoint for embedding general text.
+
+        Args:
+            texts: The list of texts to embed.
+            input_type: Type of the input text. Default to None, meaning the type is
+                unspecified. Other options: query, document.
+
         Returns:
             Embedding for the text.
         """
         return self._get_embeddings(
-            [text], batch_size=self.batch_size, input_type="query"
-        )[0]
+            texts, batch_size=self.batch_size, input_type=input_type
+        )

libs/langchain/langchain/llms/base.py

@@ -1,6 +1,9 @@
+# Backwards compatibility.
+from langchain_core.language_models import BaseLanguageModel
 from langchain_core.language_models.llms import (
     LLM,
     BaseLLM,
+    _get_verbosity,
     create_base_retry_decorator,
     get_prompts,
     update_cache,
@@ -10,6 +13,8 @@ __all__ = [
     "create_base_retry_decorator",
     "get_prompts",
     "update_cache",
+    "BaseLanguageModel",
+    "_get_verbosity",
     "BaseLLM",
     "LLM",
 ]

libs/langchain/langchain/prompts/__init__.py

@@ -44,7 +44,6 @@ from langchain_core.prompts import (
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
     PipelinePromptTemplate,
-    Prompt,
     PromptTemplate,
     StringPromptTemplate,
     SystemMessagePromptTemplate,
@@ -52,6 +51,7 @@ from langchain_core.prompts import (
 )
 
 from langchain.prompts.example_selector import NGramOverlapExampleSelector
+from langchain.prompts.prompt import Prompt
 
 __all__ = [
     "AIMessagePromptTemplate",
@@ -67,11 +67,11 @@ __all__ = [
     "MessagesPlaceholder",
     "NGramOverlapExampleSelector",
     "PipelinePromptTemplate",
-    "Prompt",
     "PromptTemplate",
     "SemanticSimilarityExampleSelector",
     "StringPromptTemplate",
     "SystemMessagePromptTemplate",
     "load_prompt",
     "FewShotChatMessagePromptTemplate",
+    "Prompt",
 ]

libs/langchain/langchain/prompts/base.py

@@ -1,3 +1,4 @@
+from langchain_core.prompt_values import StringPromptValue
 from langchain_core.prompts import (
     BasePromptTemplate,
     StringPromptTemplate,
@@ -6,6 +7,7 @@ from langchain_core.prompts import (
     jinja2_formatter,
     validate_jinja2,
 )
+from langchain_core.prompts.string import _get_jinja2_variables_from_template
 
 __all__ = [
     "jinja2_formatter",
@@ -14,4 +16,6 @@ __all__ = [
     "get_template_variables",
     "StringPromptTemplate",
     "BasePromptTemplate",
+    "StringPromptValue",
+    "_get_jinja2_variables_from_template",
 ]

libs/langchain/langchain/prompts/chat.py

@@ -1,3 +1,4 @@
+from langchain_core.prompt_values import ChatPromptValue, ChatPromptValueConcrete
 from langchain_core.prompts.chat import (
     AIMessagePromptTemplate,
     BaseChatPromptTemplate,
@@ -8,6 +9,8 @@ from langchain_core.prompts.chat import (
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
     SystemMessagePromptTemplate,
+    _convert_to_message,
+    _create_template_from_message_type,
 )
 
 __all__ = [
@@ -20,4 +23,8 @@ __all__ = [
     "SystemMessagePromptTemplate",
     "BaseChatPromptTemplate",
     "ChatPromptTemplate",
+    "ChatPromptValue",
+    "ChatPromptValueConcrete",
+    "_convert_to_message",
+    "_create_template_from_message_type",
 ]

libs/langchain/langchain/prompts/few_shot.py

@@ -1,6 +1,11 @@
 from langchain_core.prompts.few_shot import (
     FewShotChatMessagePromptTemplate,
     FewShotPromptTemplate,
+    _FewShotPromptTemplateMixin,
 )
 
-__all__ = ["FewShotPromptTemplate", "FewShotChatMessagePromptTemplate"]
+__all__ = [
+    "FewShotPromptTemplate",
+    "FewShotChatMessagePromptTemplate",
+    "_FewShotPromptTemplateMixin",
+]

libs/langchain/langchain/prompts/loading.py

@@ -1,4 +1,23 @@
-from langchain_core.prompts.loading import load_prompt, load_prompt_from_config
+from langchain_core.prompts.loading import (
+    _load_examples,
+    _load_few_shot_prompt,
+    _load_output_parser,
+    _load_prompt,
+    _load_prompt_from_file,
+    _load_template,
+    load_prompt,
+    load_prompt_from_config,
+)
 from langchain_core.utils.loading import try_load_from_hub
 
-__all__ = ["load_prompt_from_config", "load_prompt", "try_load_from_hub"]
+__all__ = [
+    "load_prompt_from_config",
+    "load_prompt",
+    "try_load_from_hub",
+    "_load_examples",
+    "_load_few_shot_prompt",
+    "_load_output_parser",
+    "_load_prompt",
+    "_load_prompt_from_file",
+    "_load_template",
+]

libs/langchain/langchain/prompts/pipeline.py

@@ -1,3 +1,3 @@
-from langchain_core.prompts.pipeline import PipelinePromptTemplate
+from langchain_core.prompts.pipeline import PipelinePromptTemplate, _get_inputs
 
-__all__ = ["PipelinePromptTemplate"]
+__all__ = ["PipelinePromptTemplate", "_get_inputs"]

libs/langchain/langchain/prompts/prompt.py

@@ -1,3 +1,6 @@
 from langchain_core.prompts.prompt import PromptTemplate
 
-__all__ = ["PromptTemplate"]
+# For backwards compatibility.
+Prompt = PromptTemplate
+
+__all__ = ["PromptTemplate", "Prompt"]

libs/langchain/langchain/smith/evaluation/runner_utils.py

@@ -996,7 +996,7 @@ def _collect_test_results(
     configs: List[RunnableConfig],
     project_name: str,
 ) -> TestResult:
-    wait_for_all_evaluators()
+    wait_for_all_evaluators(verbose=True)
     all_eval_results = {}
     all_execution_time = {}
     for c in configs:

libs/langchain/langchain/tools/base.py

@@ -4,6 +4,9 @@ from langchain_core.tools import (
     StructuredTool,
     Tool,
     ToolException,
+    _create_subset_model,
+    _get_filtered_args,
+    _SchemaConfig,
     create_schema_from_function,
     tool,
 )
@@ -16,4 +19,7 @@ __all__ = [
     "Tool",
     "StructuredTool",
     "tool",
+    "_SchemaConfig",
+    "_create_subset_model",
+    "_get_filtered_args",
 ]

libs/langchain/langchain/vectorstores/redis/base.py

@@ -1381,7 +1381,7 @@ def _prepare_metadata(metadata: Dict[str, Any]) -> Dict[str, Any]:
 
     clean_meta: Dict[str, Union[str, float, int]] = {}
     for key, value in metadata.items():
-        if not value:
+        if value is None:
             clean_meta[key] = ""
             continue
 

libs/langchain/poetry.lock

@@ -3778,7 +3778,6 @@ optional = false
 python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*"
 files = [
     {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"},
-    {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"},
 ]
 
 [[package]]
@@ -4603,16 +4602,6 @@ files = [
     {file = "MarkupSafe-2.1.3-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5bbe06f8eeafd38e5d0a4894ffec89378b6c6a625ff57e3028921f8ff59318ac"},
     {file = "MarkupSafe-2.1.3-cp311-cp311-win32.whl", hash = "sha256:dd15ff04ffd7e05ffcb7fe79f1b98041b8ea30ae9234aed2a9168b5797c3effb"},
     {file = "MarkupSafe-2.1.3-cp311-cp311-win_amd64.whl", hash = "sha256:134da1eca9ec0ae528110ccc9e48041e0828d79f24121a1a146161103c76e686"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_universal2.whl", hash = "sha256:f698de3fd0c4e6972b92290a45bd9b1536bffe8c6759c62471efaa8acb4c37bc"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-macosx_10_9_x86_64.whl", hash = "sha256:aa57bd9cf8ae831a362185ee444e15a93ecb2e344c8e52e4d721ea3ab6ef1823"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ffcc3f7c66b5f5b7931a5aa68fc9cecc51e685ef90282f4a82f0f5e9b704ad11"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:47d4f1c5f80fc62fdd7777d0d40a2e9dda0a05883ab11374334f6c4de38adffd"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:1f67c7038d560d92149c060157d623c542173016c4babc0c1913cca0564b9939"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:9aad3c1755095ce347e26488214ef77e0485a3c34a50c5a5e2471dff60b9dd9c"},
-    {file = "MarkupSafe-2.1.3-cp312-cp312-musllinux_1_1_i686.whl", hash = "sha256:14ff806850827afd6b07a5f32bd917fb7f45b046ba40c57abdb636674a8b559c"},
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@@ -7749,7 +7725,6 @@ files = [
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-    {file = "PyYAML-6.0.1-cp38-cp38-musllinux_1_1_x86_64.whl", hash = "sha256:49a183be227561de579b4a36efbb21b3eab9651dd81b1858589f796549873dd6"},
     {file = "PyYAML-6.0.1-cp38-cp38-win32.whl", hash = "sha256:184c5108a2aca3c5b3d3bf9395d50893a7ab82a38004c8f61c258d4428e80206"},
     {file = "PyYAML-6.0.1-cp38-cp38-win_amd64.whl", hash = "sha256:1e2722cc9fbb45d9b87631ac70924c11d3a401b2d7f410cc0e3bbf249f2dca62"},
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@@ -7757,7 +7732,6 @@ files = [
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-    {file = "PyYAML-6.0.1-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:04ac92ad1925b2cff1db0cfebffb6ffc43457495c9b3c39d3fcae417d7125dc5"},
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     {file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
@@ -10214,6 +10188,17 @@ files = [
     {file = "types_toml-0.10.8.7-py3-none-any.whl", hash = "sha256:61951da6ad410794c97bec035d59376ce1cbf4453dc9b6f90477e81e4442d631"},
 ]
 
+[[package]]
+name = "types-tqdm"
+version = "4.66.0.4"
+description = "Typing stubs for tqdm"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "types-tqdm-4.66.0.4.tar.gz", hash = "sha256:a2f0ebd4cfd48f4914395819a176d7947387e1b98f9228fca38f8cac1b59891c"},
+    {file = "types_tqdm-4.66.0.4-py3-none-any.whl", hash = "sha256:8eda4c5123dd66985a4cb44268705cfa18beb32d66772271ae185e92b8b10c40"},
+]
+
 [[package]]
 name = "types-urllib3"
 version = "1.26.25.14"
@@ -11085,4 +11070,4 @@ text-helpers = ["chardet"]
 [metadata]
 lock-version = "2.0"
 python-versions = ">=3.8.1,<4.0"
-content-hash = "54acd6074885fa2e4069cdba7dfe5b497ca4820b506983a5792fb1e78b53f4a3"
+content-hash = "84ead96758fe7104796f18249521e2ff0a3408f916bd15f7df493c027a28da0c"

libs/langchain/pyproject.toml

@@ -201,6 +201,7 @@ types-toml = "^0.10.8.1"
 types-redis = "^4.3.21.6"
 types-pytz = "^2023.3.0.0"
 types-chardet = "^5.0.4.6"
+types-tqdm = "^4.66.0.4"
 mypy-protobuf = "^3.0.0"
 
 [tool.poetry.group.typing.dependencies]

libs/langchain/scripts/check_imports.sh

@@ -24,6 +24,9 @@ git grep '^from langchain\.' langchain/embeddings | grep -vE 'from langchain.(py
 git grep '^from langchain\.' langchain/docstore | grep -vE 'from langchain.(pydantic_v1|utils|schema|docstore)' && errors=$((errors+1))
 git grep '^from langchain\.' langchain/vectorstores | grep -vE 'from langchain.(pydantic_v1|utils|schema|load|callbacks|env|_api|storage|llms|docstore|vectorstores|utilities)' && errors=$((errors+1))
 
+# make sure not importing from langchain_experimental
+git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
+
 # Decide on an exit status based on the errors
 if [ "$errors" -gt 0 ]; then
     exit 1

libs/langchain/tests/unit_tests/chat_models/test_base.py

@@ -0,0 +1,13 @@
+from langchain.chat_models.base import __all__
+
+EXPECTED_ALL = [
+    "BaseChatModel",
+    "SimpleChatModel",
+    "_agenerate_from_stream",
+    "_generate_from_stream",
+    "_get_verbosity",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/chat_models/test_bedrock.py

@@ -1,8 +1,10 @@
 """Test Anthropic Chat API wrapper."""
 from typing import List
+from unittest.mock import MagicMock
 
 import pytest
 
+from langchain.chat_models import BedrockChat
 from langchain.chat_models.meta import convert_messages_to_prompt_llama
 from langchain.schema import AIMessage, BaseMessage, HumanMessage, SystemMessage
 
@@ -28,3 +30,19 @@ from langchain.schema import AIMessage, BaseMessage, HumanMessage, SystemMessage
 def test_formatting(messages: List[BaseMessage], expected: str) -> None:
     result = convert_messages_to_prompt_llama(messages)
     assert result == expected
+
+
+def test_anthropic_bedrock() -> None:
+    client = MagicMock()
+    respbody = MagicMock(
+        read=MagicMock(
+            return_value=MagicMock(
+                decode=MagicMock(return_value=b'{"completion":"Hi back"}')
+            )
+        )
+    )
+    client.invoke_model.return_value = {"body": respbody}
+    model = BedrockChat(model_id="anthropic.claude-v2", client=client)
+
+    # should not throw an error
+    model.invoke("hello there")

libs/langchain/tests/unit_tests/llms/test_base.py

@@ -10,8 +10,23 @@ from langchain_core.outputs import Generation, LLMResult
 
 from langchain.cache import InMemoryCache, SQLAlchemyCache
 from langchain.globals import get_llm_cache, set_llm_cache
+from langchain.llms.base import __all__
 from tests.unit_tests.llms.fake_llm import FakeLLM
 
+EXPECTED_ALL = [
+    "BaseLLM",
+    "LLM",
+    "_get_verbosity",
+    "create_base_retry_decorator",
+    "get_prompts",
+    "update_cache",
+    "BaseLanguageModel",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)
+
 
 def test_caching() -> None:
     """Test caching behavior."""
@@ -74,21 +89,3 @@ def test_custom_caching() -> None:
         llm_output=None,
     )
     assert output == expected_output
-
-
-def test_batch() -> None:
-    llm = FakeLLM()
-    output = llm.batch(["foo", "bar", "foo"])
-    assert output == ["foo"] * 3
-
-    output = llm.batch(["foo", "bar", "foo"], config={"max_concurrency": 2})
-    assert output == ["foo"] * 3
-
-
-async def test_abatch() -> None:
-    llm = FakeLLM()
-    output = await llm.abatch(["foo", "bar", "foo"])
-    assert output == ["foo"] * 3
-
-    output = await llm.abatch(["foo", "bar", "foo"], config={"max_concurrency": 2})
-    assert output == ["foo"] * 3

libs/langchain/tests/unit_tests/prompts/__init__.py

@@ -0,0 +1 @@
+"""Test prompt functionality."""

libs/langchain/tests/unit_tests/prompts/test_base.py

@@ -0,0 +1,16 @@
+from langchain.prompts.base import __all__
+
+EXPECTED_ALL = [
+    "BasePromptTemplate",
+    "StringPromptTemplate",
+    "StringPromptValue",
+    "_get_jinja2_variables_from_template",
+    "check_valid_template",
+    "get_template_variables",
+    "jinja2_formatter",
+    "validate_jinja2",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_chat.py

@@ -0,0 +1,21 @@
+from langchain.prompts.chat import __all__
+
+EXPECTED_ALL = [
+    "AIMessagePromptTemplate",
+    "BaseChatPromptTemplate",
+    "BaseMessagePromptTemplate",
+    "BaseStringMessagePromptTemplate",
+    "ChatMessagePromptTemplate",
+    "ChatPromptTemplate",
+    "ChatPromptValue",
+    "ChatPromptValueConcrete",
+    "HumanMessagePromptTemplate",
+    "MessagesPlaceholder",
+    "SystemMessagePromptTemplate",
+    "_convert_to_message",
+    "_create_template_from_message_type",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_few_shot.py

@@ -0,0 +1,11 @@
+from langchain.prompts.few_shot import __all__
+
+EXPECTED_ALL = [
+    "FewShotChatMessagePromptTemplate",
+    "FewShotPromptTemplate",
+    "_FewShotPromptTemplateMixin",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_few_shot_with_templates.py

@@ -0,0 +1,7 @@
+from langchain.prompts.few_shot_with_templates import __all__
+
+EXPECTED_ALL = ["FewShotPromptWithTemplates"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_imports.py

@@ -0,0 +1,28 @@
+from langchain.prompts import __all__
+
+EXPECTED_ALL = [
+    "AIMessagePromptTemplate",
+    "BaseChatPromptTemplate",
+    "BasePromptTemplate",
+    "ChatMessagePromptTemplate",
+    "ChatPromptTemplate",
+    "FewShotPromptTemplate",
+    "FewShotPromptWithTemplates",
+    "HumanMessagePromptTemplate",
+    "LengthBasedExampleSelector",
+    "MaxMarginalRelevanceExampleSelector",
+    "MessagesPlaceholder",
+    "NGramOverlapExampleSelector",
+    "PipelinePromptTemplate",
+    "Prompt",
+    "PromptTemplate",
+    "SemanticSimilarityExampleSelector",
+    "StringPromptTemplate",
+    "SystemMessagePromptTemplate",
+    "load_prompt",
+    "FewShotChatMessagePromptTemplate",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_loading.py

@@ -0,0 +1,17 @@
+from langchain.prompts.loading import __all__
+
+EXPECTED_ALL = [
+    "_load_examples",
+    "_load_few_shot_prompt",
+    "_load_output_parser",
+    "_load_prompt",
+    "_load_prompt_from_file",
+    "_load_template",
+    "load_prompt",
+    "load_prompt_from_config",
+    "try_load_from_hub",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_pipeline.py

@@ -0,0 +1,7 @@
+from langchain.prompts.pipeline import __all__
+
+EXPECTED_ALL = ["PipelinePromptTemplate", "_get_inputs"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/prompts/test_prompt.py

@@ -0,0 +1,7 @@
+from langchain.prompts.prompt import __all__
+
+EXPECTED_ALL = ["Prompt", "PromptTemplate"]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

libs/langchain/tests/unit_tests/test_schema.py

@@ -1,5 +1,4 @@
 """Test formatting functionality."""
-import unittest
 from typing import Union
 
 import pytest
@@ -16,75 +15,12 @@ from langchain_core.messages import (
     HumanMessageChunk,
     SystemMessage,
     SystemMessageChunk,
-    get_buffer_string,
-    messages_from_dict,
-    messages_to_dict,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, Generation
 from langchain_core.prompt_values import ChatPromptValueConcrete, StringPromptValue
 from langchain_core.pydantic_v1 import BaseModel, ValidationError
 
 
-class TestGetBufferString(unittest.TestCase):
-    def setUp(self) -> None:
-        self.human_msg = HumanMessage(content="human")
-        self.ai_msg = AIMessage(content="ai")
-        self.sys_msg = SystemMessage(content="sys")
-
-    def test_empty_input(self) -> None:
-        self.assertEqual(get_buffer_string([]), "")
-
-    def test_valid_single_message(self) -> None:
-        expected_output = f"Human: {self.human_msg.content}"
-        self.assertEqual(
-            get_buffer_string([self.human_msg]),
-            expected_output,
-        )
-
-    def test_custom_human_prefix(self) -> None:
-        prefix = "H"
-        expected_output = f"{prefix}: {self.human_msg.content}"
-        self.assertEqual(
-            get_buffer_string([self.human_msg], human_prefix="H"),
-            expected_output,
-        )
-
-    def test_custom_ai_prefix(self) -> None:
-        prefix = "A"
-        expected_output = f"{prefix}: {self.ai_msg.content}"
-        self.assertEqual(
-            get_buffer_string([self.ai_msg], ai_prefix="A"),
-            expected_output,
-        )
-
-    def test_multiple_msg(self) -> None:
-        msgs = [self.human_msg, self.ai_msg, self.sys_msg]
-        expected_output = "\n".join(
-            [
-                f"Human: {self.human_msg.content}",
-                f"AI: {self.ai_msg.content}",
-                f"System: {self.sys_msg.content}",
-            ]
-        )
-        self.assertEqual(
-            get_buffer_string(msgs),
-            expected_output,
-        )
-
-
-def test_multiple_msg() -> None:
-    human_msg = HumanMessage(content="human", additional_kwargs={"key": "value"})
-    ai_msg = AIMessage(content="ai")
-    sys_msg = SystemMessage(content="sys")
-
-    msgs = [
-        human_msg,
-        ai_msg,
-        sys_msg,
-    ]
-    assert messages_from_dict(messages_to_dict(msgs)) == msgs
-
-
 def test_serialization_of_wellknown_objects() -> None:
     """Test that pydantic is able to serialize and deserialize well known objects."""
 

libs/langchain/tests/unit_tests/tools/test_base.py

@@ -0,0 +1,18 @@
+from langchain.tools.base import __all__
+
+EXPECTED_ALL = [
+    "BaseTool",
+    "SchemaAnnotationError",
+    "StructuredTool",
+    "Tool",
+    "ToolException",
+    "_SchemaConfig",
+    "_create_subset_model",
+    "_get_filtered_args",
+    "create_schema_from_function",
+    "tool",
+]
+
+
+def test_all_imports() -> None:
+    assert set(__all__) == set(EXPECTED_ALL)

templates/anthropic-iterative-search/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "anthropic-iterative-search"
 version = "0.0.1"
-description = ""
+description = "A virtual research assistant with the ability to search Wikipedia and answer questions"
 authors = []
 readme = "README.md"
 
@@ -18,6 +18,12 @@ langchain-cli = {extras = ["serve"], version = "^0.0.13"}
 export_module = "anthropic_iterative_search"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "research"
+author = "LangChain"
+integrations = ["Anthropic", "Wikipedia"]
+tags = ["research", "agents"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/basic-critique-revise/README.md

@@ -1,10 +1,10 @@
 # basic-critique-revise
 
-TODO: What does this package do
+Iteratively generate schema candidates and revise them based on errors.
 
 ## Environment Setup
 
-TODO: What environment variables need to be set (if any)
+This template uses OpenAI function calling, so you will need to set the `OPENAI_API_KEY` environment variable in order to use this template.
 
 ## Usage
 

templates/basic-critique-revise/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "basic_critique_revise"
 version = "0.0.1"
-description = ""
+description = "Iteratively generate schema candidates and revise based on errors"
 authors = []
 readme = "README.md"
 
@@ -19,6 +19,12 @@ sse-starlette = "^1.6.5"
 export_module = "basic_critique_revise"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "research"
+author = "LangChain"
+integrations = ["OpenAI", "Function Calling", "Pydantic"]
+tags = ["research", "function-calling"]
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

templates/cassandra-entomology-rag/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "cassandra-entomology-rag"
 version = "0.0.1"
-description = ""
+description = "RAG using Apache Cassandra® or Astra DB"
 authors = [
     "Stefano Lottini <stefano.lottini@datastax.com>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "cassandra_entomology_rag"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "DataStax"
+integrations = ["OpenAI", "Cassandra"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/cassandra-synonym-caching/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "cassandra-synonym-caching"
 version = "0.0.1"
-description = ""
+description = "LLM caching backed by Apache Cassandra® or Astra DB"
 authors = [
     "Stefano Lottini <stefano.lottini@datastax.com>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "cassandra_synonym_caching"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "DataStax"
+integrations = ["OpenAI", "Cassandra"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/chain-of-note-wiki/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "chain-of-note-wiki"
 version = "0.0.1"
-description = ""
+description = "Implementation of Chain of Note prompting for Wikipedia."
 authors = []
 readme = "README.md"
 
@@ -21,6 +21,12 @@ sse-starlette = "^1.6.5"
 export_module = "chain_of_note_wiki"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["Anthropic", "Wikipedia", "LangChain Hub"]
+tags = ["paper", "prompt-hub"]
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

templates/chat-bot-feedback/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "chat-bot-feedback"
 version = "0.0.1"
-description = ""
+description = "Evaluate your chatbot without human feedback"
 authors = []
 readme = "README.md"
 
@@ -21,6 +21,12 @@ sse-starlette = "^1.6.5"
 export_module = "chat_bot_feedback.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "evaluation"
+author = "LangChain"
+integrations = ["OpenAI", "LangSmith"]
+tags = ["langsmith"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/csv-agent/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "csv-agent"
 version = "0.0.1"
-description = ""
+description = "Analyze csv data with Pandas and OpenAI"
 authors = []
 readme = "README.md"
 
@@ -24,6 +24,12 @@ langchain-cli = ">=0.0.15"
 export_module = "csv_agent"
 export_attr = "agent_executor"
 
+[tool.templates-hub]
+use-case = "question-answering"
+author = "LangChain"
+integrations = ["OpenAI", "Pandas"]
+tags = ["data", "agents"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/elastic-query-generator/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "elastic-query-generator"
 version = "0.0.1"
-description = ""
+description = "Interact with Elasticsearch analytics databases using natural language"
 authors = []
 readme = "README.md"
 
@@ -18,6 +18,12 @@ langchain-cli = ">=0.0.15"
 export_module = "elastic_query_generator"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "query"
+author = "LangChain"
+integrations = ["Elasticsearch", "OpenAI"]
+tags = ["query-generation"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/extraction-anthropic-functions/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "extraction-anthropic-functions"
 version = "0.1.0"
-description = ""
+description = "Use Anthropic function calling for tasks like extraction or tagging"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "extraction_anthropic_functions"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "extraction"
+author = "LangChain"
+integrations = ["Anthropic", "Function Calling"]
+tags = ["function-calling", "tagging", "extraction"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/extraction-openai-functions/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "extraction-openai-functions"
 version = "0.1.0"
-description = ""
+description = "Use OpenAI function calling for tasks like extraction or tagging"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -19,6 +19,12 @@ langchain-cli = ">=0.0.15"
 export_module = "extraction_openai_functions"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "extraction"
+author = "LangChain"
+integrations = ["OpenAI", "Function Calling"]
+tags = ["function-calling", "tagging", "extraction"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/guardrails-output-parser/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "guardrails-output-parser"
 version = "0.0.1"
-description = ""
+description = "Use guardrails-ai to validate LLM output"
 authors = []
 readme = "README.md"
 
@@ -21,6 +21,12 @@ sse-starlette = "^1.6.5"
 export_module = "guardrails_output_parser.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "validation"
+author = "LangChain"
+integrations = ["Guardrails", "OpenAI"]
+tags = ["moderation"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/hybrid-search-weaviate/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "hybrid-search-weaviate"
 version = "0.1.0"
-description = ""
+description = "Improve accuracy and relevance with Weaviate hybrid search"
 authors = ["Erika Cardenas <erika@weaviate.io>"]
 readme = "README.md"
 
@@ -24,6 +24,12 @@ version = "^1.0.0"
 export_module = "hybrid_search_weaviate"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "search"
+author = "Weaviate"
+integrations = ["Weaviate", "OpenAI"]
+tags = ["hybrid-search", "vectordb"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/hyde/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "hyde"
 version = "0.0.1"
-description = ""
+description = "Retrieval with Hypothetical Document Embeddings (HyDE)"
 authors = []
 readme = "README.md"
 
@@ -22,6 +22,12 @@ sse-starlette = "^1.6.5"
 export_module = "hyde.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["OpenAI", "ChromaDB"]
+tags = ["paper"]
+
 [tool.poe.tasks.start]
 cmd = "uvicorn langchain_cli.dev_scripts:create_demo_server --reload --port $port --host $host"
 args = [

templates/llama2-functions/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "llama2-functions"
 version = "0.1.0"
-description = ""
+description = "Extraction with a JSON-output LLaMA2 model"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -19,6 +19,12 @@ langchain-cli = ">=0.0.15"
 export_module = "llama2_functions"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "extraction"
+author = "LangChain"
+integrations = ["Llama.cpp", "Replicate"]
+tags = ["local-llm", "function-calling"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/mongo-parent-document-retrieval/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "mongo-parent-document-retrieval"
 version = "0.0.1"
-description = ""
+description = "RAG using MongoDB and OpenAI"
 authors = []
 readme = "README.md"
 
@@ -22,6 +22,12 @@ sse-starlette = "^1.6.5"
 export_module = "mongo_parent_document_retrieval"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["MongoDB", "OpenAI"]
+tags = ["vectordb"]
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

templates/neo4j-advanced-rag/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-advanced-rag"
 version = "0.1.0"
-description = ""
+description = "Balance precise embeddings and context retention with advanced strategies"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -18,6 +18,12 @@ neo4j = "^5.14.0"
 export_module = "neo4j_advanced_rag"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["vectordb", "parent", "summarization"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/neo4j-cypher-ft/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-cypher-ft"
 version = "0.1.0"
-description = ""
+description = "Interact with a Neo4j graph database using natural language"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -20,6 +20,12 @@ langchain-cli = ">=0.0.15"
 export_module = "neo4j_cypher_ft"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "query"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["search", "graph-database", "query"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/neo4j-cypher-memory/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-cypher-memory"
 version = "0.1.0"
-description = ""
+description = "Conversational interface for a Neo4j graph database"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -20,6 +20,12 @@ langchain-cli = ">=0.0.15"
 export_module = "neo4j_cypher_memory"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "query"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["conversation", "graph-database"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/neo4j-cypher/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-cypher"
 version = "0.1.0"
-description = ""
+description = "Natural language interface for a Neo4j graph database"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -20,6 +20,12 @@ langchain-cli = ">=0.0.15"
 export_module = "neo4j_cypher"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "query"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["search", "graph-database"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/neo4j-generation/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-generation"
 version = "0.0.1"
-description = ""
+description = "Knowledge graph extraction with Neo4j AuraDB"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -20,6 +20,12 @@ langchain-cli = ">=0.0.15"
 export_module = "neo4j_generation.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "extraction"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["graph-database", "search"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/neo4j-parent/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-parent"
 version = "0.1.0"
-description = ""
+description = "Balance precise embeddings and context retention with Neo4j hybrid search"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "neo4j_parent"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["hybrid-search", "graph-database"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/neo4j-vector-memory/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "neo4j-vector-memory"
 version = "0.1.0"
-description = ""
+description = "Store conversational flows in a Neo4j graph database"
 authors = [
     "Tomaz Bratanic <tomaz.bratanic@neo4j.com>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "neo4j_vector_memory"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "Neo4j"
+integrations = ["Neo4j", "OpenAI"]
+tags = ["graph-database", "conversation"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/openai-functions-agent/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "openai-functions-agent"
 version = "0.1.0"
-description = ""
+description = "Agent using OpenAI function calling to execute functions, including search"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -20,6 +20,12 @@ langchain-cli = ">=0.0.15"
 export_module = "openai_functions_agent"
 export_attr = "agent_executor"
 
+[tool.templates-hub]
+use-case = "research"
+author = "LangChain"
+integrations = ["OpenAI", "Tavily"]
+tags = ["search", "agents", "function-calling"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/openai-functions-tool-retrieval-agent/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "openai-functions-tool-retrieval-agent"
 version = "0.0.1"
-description = ""
+description = "Use large numbers of tools with tool retrieval strategies"
 authors = []
 readme = "README.md"
 
@@ -21,6 +21,12 @@ sse-starlette = "^1.6.5"
 export_module = "openai_functions_tool_retrieval_agent"
 export_attr = "agent_executor"
 
+[tool.templates-hub]
+use-case = "agents"
+author = "LangChain"
+integrations = ["OpenAI", "FAISS"]
+tags = ["agents", "function-calling"]
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

templates/pii-protected-chatbot/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "pii_protected_chatbot"
 version = "0.0.1"
-description = ""
+description = "Flag PII before passing it to the LLM"
 authors = []
 readme = "README.md"
 
@@ -20,6 +20,12 @@ sse-starlette = "^1.6.5"
 export_module = "pii_protected_chatbot.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "chatbot"
+author = "LangChain"
+integrations = ["OpenAI", "Microsoft Presidio"]
+tags = ["data", "redaction"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/pirate-speak-configurable/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "pirate-speak-configurable"
 version = "0.0.1"
-description = ""
+description = "Use Configurable Alternatives to allow clients to choose their Runnables"
 authors = []
 readme = "README.md"
 
@@ -21,6 +21,12 @@ sse-starlette = "^1.6.5"
 export_module = "pirate_speak_configurable"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "chatbot"
+author = "LangChain"
+integrations = ["Cohere", "Anthropic", "OpenAI"]
+tags = ["configurable"]
+
 [build-system]
 requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

templates/pirate-speak/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "pirate-speak"
 version = "0.0.1"
-description = ""
+description = "Get started with a simple template that speaks like a pirate"
 authors = []
 readme = "README.md"
 
@@ -19,6 +19,12 @@ sse-starlette = "^1.6.5"
 export_module = "pirate_speak.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "chatbot"
+author = "LangChain"
+integrations = ["OpenAI"]
+tags = ["getting-started"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/plate-chain/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "plate-chain"
 version = "0.0.1"
-description = ""
+description = "Parse data from laboratory plates into standardized formats"
 authors = []
 readme = "README.md"
 
@@ -20,6 +20,12 @@ sse-starlette = "^1.6.5"
 export_module = "plate_chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "extraction"
+author = "Sphinx Bio"
+integrations = ["OpenAI"]
+tags = ["bio", "data"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/rag-astradb/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "astradb_entomology_rag"
 version = "0.0.1"
-description = ""
+description = "RAG using AstraDB"
 authors = [
     "Stefano Lottini <stefano.lottini@datastax.com>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "astradb_entomology_rag"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "Datastax"
+integrations = ["AstraDB"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/rag-aws-bedrock/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "rag-aws-bedrock"
 version = "0.1.0"
-description = ""
+description = "RAG using AWS Bedrock"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -22,6 +22,12 @@ langchain-cli = ">=0.0.15"
 export_module = "rag_aws_bedrock"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["OpenAI", "FAISS"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/rag-aws-kendra/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "rag-aws-kendra"
 version = "0.0.1"
-description = ""
+description = "RAG using AWS-Kendra and anthropic"
 authors = []
 readme = "README.md"
 
@@ -21,6 +21,12 @@ sse-starlette = "^1.6.5"
 export_module = "rag_aws_kendra.chain"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["AWS"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/rag-chroma-private/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "rag-chroma-private"
 version = "0.1.0"
-description = ""
+description = "Private RAG using local LLM, embeddings, vectorstore"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -22,6 +22,12 @@ langchain-cli = ">=0.0.15"
 export_module = "rag_chroma_private"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["OpenAI", "Chroma", "Gpt4all", "Ollama"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/rag-chroma/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "rag-chroma"
 version = "0.1.0"
-description = ""
+description = "RAG using Chroma"
 authors = [
     "Erick Friis <erick@langchain.dev>",
 ]
@@ -21,6 +21,12 @@ langchain-cli = ">=0.0.15"
 export_module = "rag_chroma"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "LangChain"
+integrations = ["OpenAI", "Chroma"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",

templates/rag-codellama-fireworks/pyproject.toml

@@ -1,7 +1,7 @@
 [tool.poetry]
 name = "rag-codellama-fireworks"
 version = "0.1.0"
-description = ""
+description = "RAG using OSS LLMs via Fireworks"
 authors = [
     "Lance Martin <lance@langchain.dev>",
 ]
@@ -22,6 +22,12 @@ langchain-cli = ">=0.0.15"
 export_module = "rag_codellama_fireworks"
 export_attr = "chain"
 
+[tool.templates-hub]
+use-case = "rag"
+author = "Elastic"
+integrations = ["OpenAI", "Fireworks"]
+tags = ["vectordbs"]
+
 [build-system]
 requires = [
     "poetry-core",