PR Merging Master with CogniSwitch Chains

.github/CONTRIBUTING.md

@@ -70,17 +70,18 @@ Install Poetry: **[documentation on how to install it](https://python-poetry.org
 ❗Note: If you use `Conda` or `Pyenv` as your environment/package manager, after installing Poetry,
 tell Poetry to use the virtualenv python environment (`poetry config virtualenvs.prefer-active-python true`)
 
-### Core vs. Experimental
+### Different packages
 
-This repository contains three separate projects:
-- `langchain`: core langchain code, abstractions, and use cases.
-- `langchain_core`: contain interfaces for key abstractions as well as logic for combining them in chains (LCEL).
-- `langchain_experimental`: see the [Experimental README](https://github.com/langchain-ai/langchain/tree/master/libs/experimental/README.md) for more information.
+This repository contains multiple packages:
+- `langchain-core`: Base interfaces for key abstractions as well as logic for combining them in chains (LangChain Expression Language).
+- `langchain-community`: Third-party integrations of various components.
+- `langchain`: Chains, agents, and retrieval logic that makes up the cognitive architecture of your applications.
+- `langchain-experimental`: Components and chains that are experimental, either in the sense that the techniques are novel and still being tested, or they require giving the LLM more access than would be possible in most production systems.
 
 Each of these has its own development environment. Docs are run from the top-level makefile, but development
 is split across separate test & release flows.
 
-For this quickstart, start with langchain core:
+For this quickstart, start with langchain:
 
 ```bash
 cd libs/langchain
@@ -330,15 +331,50 @@ what you wanted by clicking the `View deployment` or `Visit Preview` buttons on
 This will take you to a preview of the documentation changes.
 This preview is created by [Vercel](https://vercel.com/docs/getting-started-with-vercel).
 
-## 🏭 Release Process
+## 📕 Releases & Versioning
 
 As of now, LangChain has an ad hoc release process: releases are cut with high frequency by
-a developer and published to [PyPI](https://pypi.org/project/langchain/).
+a maintainer and published to [PyPI](https://pypi.org/). 
+The different packages are versioned slightly differently.
 
-LangChain follows the [semver](https://semver.org/) versioning standard. However, as pre-1.0 software,
-even patch releases may contain [non-backwards-compatible changes](https://semver.org/#spec-item-4).
+### `langchain-core`
 
-### 🌟 Recognition
+`langchain-core` is currently on version `0.1.x`. 
+
+As `langchain-core` contains the base abstractions and runtime for the whole LangChain ecosystem, we will communicate any breaking changes with advance notice and version bumps. The exception for this is anything in `langchain_core.beta`. The reason for `langchain_core.beta` is that given the rate of change of the field, being able to move quickly is still a priority, and this module is our attempt to do so.
+
+Minor version increases will occur for:
+
+- Breaking changes for any public interfaces NOT in `langchain_core.beta`
+
+Patch version increases will occur for:
+
+- Bug fixes
+- New features
+- Any changes to private interfaces
+- Any changes to `langchain_core.beta`
+
+### `langchain`
+
+`langchain` is currently on version `0.0.x`
+
+All changes will be accompanied by a patch version increase. Any changes to public interfaces are nearly always done in a backwards compatible way and will be communicated ahead of time when they are not backwards compatible.
+
+We are targeting January 2024 for a release of `langchain` v0.1, at which point `langchain` will adopt the same versioning policy as `langchain-core`.
+
+### `langchain-community`
+
+`langchain-community` is currently on version `0.0.x`
+
+All changes will be accompanied by a patch version increase.
+
+### `langchain-experimental`
+
+`langchain-experimental` is currently on version `0.0.x`
+
+All changes will be accompanied by a patch version increase.
+
+## 🌟 Recognition
 
 If your contribution has made its way into a release, we will want to give you credit on Twitter (only if you want though)!
 If you have a Twitter account you would like us to mention, please let us know in the PR or through another means.

.github/scripts/check_diff.py

@@ -5,6 +5,7 @@
     "libs/core",
     "libs/langchain",
     "libs/experimental",
+    "libs/community",
 }
 
 if __name__ == "__main__":

.github/workflows/_all_ci.yml

@@ -18,6 +18,7 @@ on:
         - libs/langchain
         - libs/core
         - libs/experimental
+        - libs/community
 
 
 # If another push to the same PR or branch happens while this workflow is still running,

.github/workflows/_lint.yml

@@ -85,7 +85,8 @@ jobs:
         with:
           path: |
             ${{ env.WORKDIR }}/.mypy_cache
-          key: mypy-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', env.WORKDIR)) }}
+          key: mypy-lint-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', env.WORKDIR)) }}
+
 
       - name: Analysing the code with our lint
         working-directory: ${{ inputs.working-directory }}
@@ -105,13 +106,13 @@ jobs:
         run: |
           poetry install --with test
 
-      - name: Get .mypy_cache to speed up mypy
+      - name: Get .mypy_cache_test to speed up mypy
         uses: actions/cache@v3
         env:
           SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2"
         with:
           path: |
-            ${{ env.WORKDIR }}/.mypy_cache
+            ${{ env.WORKDIR }}/.mypy_cache_test
           key: mypy-test-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', env.WORKDIR)) }}
 
       - name: Analysing the code with our lint

.github/workflows/_release.yml

@@ -7,6 +7,17 @@ on:
         required: true
         type: string
         description: "From which folder this pipeline executes"
+  workflow_dispatch:
+    inputs:
+      working-directory:
+        required: true
+        type: choice
+        default: 'libs/langchain'
+        options:
+          - libs/langchain
+          - libs/core
+          - libs/experimental
+          - libs/community
 
 env:
   PYTHON_VERSION: "3.10"

.github/workflows/langchain_openai_release.yml

@@ -0,0 +1,13 @@
+---
+name: libs/core Release
+
+on:
+  workflow_dispatch:  # Allows to trigger the workflow manually in GitHub UI
+
+jobs:
+  release:
+    uses:
+      ./.github/workflows/_release.yml
+    with:
+      working-directory: libs/core
+    secrets: inherit

.scripts/community_split/libs/community/langchain_community/__init__.py

@@ -0,0 +1,9 @@
+"""Main entrypoint into package."""
+from importlib import metadata
+
+try:
+    __version__ = metadata.version(__package__)
+except metadata.PackageNotFoundError:
+    # Case where package metadata is not available.
+    __version__ = ""
+del metadata  # optional, avoids polluting the results of dir(__package__)

.scripts/community_split/libs/community/langchain_community/agent_toolkits/__init__.py

@@ -0,0 +1,79 @@
+"""Agent toolkits contain integrations with various resources and services.
+
+LangChain has a large ecosystem of integrations with various external resources
+like local and remote file systems, APIs and databases.
+
+These integrations allow developers to create versatile applications that combine the
+power of LLMs with the ability to access, interact with and manipulate external
+resources.
+
+When developing an application, developers should inspect the capabilities and
+permissions of the tools that underlie the given agent toolkit, and determine
+whether permissions of the given toolkit are appropriate for the application.
+
+See [Security](https://python.langchain.com/docs/security) for more information.
+"""
+from langchain_community.agent_toolkits.ainetwork.toolkit import AINetworkToolkit
+from langchain_community.agent_toolkits.amadeus.toolkit import AmadeusToolkit
+from langchain_community.agent_toolkits.azure_cognitive_services import (
+    AzureCognitiveServicesToolkit,
+)
+from langchain_community.agent_toolkits.conversational_retrieval.openai_functions import (  # noqa: E501
+    create_conversational_retrieval_agent,
+)
+from langchain_community.agent_toolkits.file_management.toolkit import (
+    FileManagementToolkit,
+)
+from langchain_community.agent_toolkits.gmail.toolkit import GmailToolkit
+from langchain_community.agent_toolkits.jira.toolkit import JiraToolkit
+from langchain_community.agent_toolkits.json.base import create_json_agent
+from langchain_community.agent_toolkits.json.toolkit import JsonToolkit
+from langchain_community.agent_toolkits.multion.toolkit import MultionToolkit
+from langchain_community.agent_toolkits.nasa.toolkit import NasaToolkit
+from langchain_community.agent_toolkits.nla.toolkit import NLAToolkit
+from langchain_community.agent_toolkits.office365.toolkit import O365Toolkit
+from langchain_community.agent_toolkits.openapi.base import create_openapi_agent
+from langchain_community.agent_toolkits.openapi.toolkit import OpenAPIToolkit
+from langchain_community.agent_toolkits.playwright.toolkit import (
+    PlayWrightBrowserToolkit,
+)
+from langchain_community.agent_toolkits.powerbi.base import create_pbi_agent
+from langchain_community.agent_toolkits.powerbi.chat_base import create_pbi_chat_agent
+from langchain_community.agent_toolkits.powerbi.toolkit import PowerBIToolkit
+from langchain_community.agent_toolkits.slack.toolkit import SlackToolkit
+from langchain_community.agent_toolkits.spark_sql.base import create_spark_sql_agent
+from langchain_community.agent_toolkits.spark_sql.toolkit import SparkSQLToolkit
+from langchain_community.agent_toolkits.sql.base import create_sql_agent
+from langchain_community.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
+from langchain_community.agent_toolkits.steam.toolkit import SteamToolkit
+from langchain_community.agent_toolkits.zapier.toolkit import ZapierToolkit
+
+
+__all__ = [
+    "AINetworkToolkit",
+    "AmadeusToolkit",
+    "AzureCognitiveServicesToolkit",
+    "FileManagementToolkit",
+    "GmailToolkit",
+    "JiraToolkit",
+    "JsonToolkit",
+    "MultionToolkit",
+    "NasaToolkit",
+    "NLAToolkit",
+    "O365Toolkit",
+    "OpenAPIToolkit",
+    "PlayWrightBrowserToolkit",
+    "PowerBIToolkit",
+    "SlackToolkit",
+    "SteamToolkit",
+    "SQLDatabaseToolkit",
+    "SparkSQLToolkit",
+    "ZapierToolkit",
+    "create_json_agent",
+    "create_openapi_agent",
+    "create_pbi_agent",
+    "create_pbi_chat_agent",
+    "create_spark_sql_agent",
+    "create_sql_agent",
+    "create_conversational_retrieval_agent",
+]

.scripts/community_split/libs/community/langchain_community/agent_toolkits/json/base.py

@@ -0,0 +1,53 @@
+"""Json agent."""
+from __future__ import annotations
+from typing import Any, Dict, List, Optional, TYPE_CHECKING
+
+from langchain_core.callbacks import BaseCallbackManager
+from langchain_core.language_models import BaseLanguageModel
+
+from langchain_community.agent_toolkits.json.prompt import JSON_PREFIX, JSON_SUFFIX
+from langchain_community.agent_toolkits.json.toolkit import JsonToolkit
+
+if TYPE_CHECKING:
+    from langchain.agents.agent import AgentExecutor
+
+
+def create_json_agent(
+    llm: BaseLanguageModel,
+    toolkit: JsonToolkit,
+    callback_manager: Optional[BaseCallbackManager] = None,
+    prefix: str = JSON_PREFIX,
+    suffix: str = JSON_SUFFIX,
+    format_instructions: Optional[str] = None,
+    input_variables: Optional[List[str]] = None,
+    verbose: bool = False,
+    agent_executor_kwargs: Optional[Dict[str, Any]] = None,
+    **kwargs: Any,
+) -> AgentExecutor:
+    """Construct a json agent from an LLM and tools."""
+    from langchain.agents.agent import AgentExecutor
+    from langchain.agents.mrkl.base import ZeroShotAgent
+    from langchain.chains.llm import LLMChain
+    tools = toolkit.get_tools()
+    prompt_params = {"format_instructions": format_instructions} if format_instructions is not None else {}
+    prompt = ZeroShotAgent.create_prompt(
+        tools,
+        prefix=prefix,
+        suffix=suffix,
+        input_variables=input_variables,
+        **prompt_params,
+    )
+    llm_chain = LLMChain(
+        llm=llm,
+        prompt=prompt,
+        callback_manager=callback_manager,
+    )
+    tool_names = [tool.name for tool in tools]
+    agent = ZeroShotAgent(llm_chain=llm_chain, allowed_tools=tool_names, **kwargs)
+    return AgentExecutor.from_agent_and_tools(
+        agent=agent,
+        tools=tools,
+        callback_manager=callback_manager,
+        verbose=verbose,
+        **(agent_executor_kwargs or {}),
+    )

.scripts/community_split/libs/community/langchain_community/agent_toolkits/nla/tool.py

@@ -0,0 +1,57 @@
+"""Tool for interacting with a single API with natural language definition."""
+
+from __future__ import annotations
+from typing import Any, Optional, TYPE_CHECKING
+
+from langchain_core.language_models import BaseLanguageModel
+from langchain_core.tools import Tool
+
+from langchain_community.tools.openapi.utils.api_models import APIOperation
+from langchain_community.tools.openapi.utils.openapi_utils import OpenAPISpec
+from langchain_community.utilities.requests import Requests
+
+if TYPE_CHECKING:
+    from langchain.chains.api.openapi.chain import OpenAPIEndpointChain
+
+
+class NLATool(Tool):
+    """Natural Language API Tool."""
+
+    @classmethod
+    def from_open_api_endpoint_chain(
+        cls, chain: OpenAPIEndpointChain, api_title: str
+    ) -> "NLATool":
+        """Convert an endpoint chain to an API endpoint tool."""
+        expanded_name = (
+            f'{api_title.replace(" ", "_")}.{chain.api_operation.operation_id}'
+        )
+        description = (
+            f"I'm an AI from {api_title}. Instruct what you want,"
+            " and I'll assist via an API with description:"
+            f" {chain.api_operation.description}"
+        )
+        return cls(name=expanded_name, func=chain.run, description=description)
+
+    @classmethod
+    def from_llm_and_method(
+        cls,
+        llm: BaseLanguageModel,
+        path: str,
+        method: str,
+        spec: OpenAPISpec,
+        requests: Optional[Requests] = None,
+        verbose: bool = False,
+        return_intermediate_steps: bool = False,
+        **kwargs: Any,
+    ) -> "NLATool":
+        """Instantiate the tool from the specified path and method."""
+        api_operation = APIOperation.from_openapi_spec(spec, path, method)
+        chain = OpenAPIEndpointChain.from_api_operation(
+            api_operation,
+            llm,
+            requests=requests,
+            verbose=verbose,
+            return_intermediate_steps=return_intermediate_steps,
+            **kwargs,
+        )
+        return cls.from_open_api_endpoint_chain(chain, spec.info.title)