Harrison/official pre release (#8106)

libs/experimental/langchain/__init__.py

@@ -1,19 +0,0 @@
-from langchain.experimental.autonomous_agents.autogpt.agent import AutoGPT
-from langchain.experimental.autonomous_agents.baby_agi.baby_agi import BabyAGI
-from langchain.experimental.generative_agents.generative_agent import GenerativeAgent
-from langchain.experimental.generative_agents.memory import GenerativeAgentMemory
-from langchain.experimental.plan_and_execute import (
-    PlanAndExecute,
-    load_agent_executor,
-    load_chat_planner,
-)
-
-__all__ = [
-    "BabyAGI",
-    "AutoGPT",
-    "GenerativeAgent",
-    "GenerativeAgentMemory",
-    "PlanAndExecute",
-    "load_agent_executor",
-    "load_chat_planner",
-]

libs/experimental/langchain/experimental/autonomous_agents/__init__.py

@@ -1,4 +0,0 @@
-from langchain.experimental.autonomous_agents.autogpt.agent import AutoGPT
-from langchain.experimental.autonomous_agents.baby_agi.baby_agi import BabyAGI
-
-__all__ = ["BabyAGI", "AutoGPT"]

libs/experimental/langchain/experimental/llms/__init__.py

@@ -1,6 +0,0 @@
-"""Experimental LLM wrappers."""
-
-from langchain.experimental.llms.jsonformer_decoder import JsonFormer
-from langchain.experimental.llms.rellm_decoder import RELLM
-
-__all__ = ["RELLM", "JsonFormer"]

libs/experimental/langchain/experimental/plan_and_execute/__init__.py

@@ -1,9 +0,0 @@
-from langchain.experimental.plan_and_execute.agent_executor import PlanAndExecute
-from langchain.experimental.plan_and_execute.executors.agent_executor import (
-    load_agent_executor,
-)
-from langchain.experimental.plan_and_execute.planners.chat_planner import (
-    load_chat_planner,
-)
-
-__all__ = ["PlanAndExecute", "load_agent_executor", "load_chat_planner"]

libs/experimental/langchain/experimental/prompts/__init__.py

@@ -1,3 +0,0 @@
-from langchain.experimental.prompts.load import load_prompt
-
-__all__ = ["load_prompt"]

libs/experimental/langchain_experimental/__init__.py

@@ -0,0 +1,19 @@
+from langchain_experimental.autonomous_agents.autogpt.agent import AutoGPT
+from langchain_experimental.autonomous_agents.baby_agi.baby_agi import BabyAGI
+from langchain_experimental.generative_agents.generative_agent import GenerativeAgent
+from langchain_experimental.generative_agents.memory import GenerativeAgentMemory
+from langchain_experimental.plan_and_execute import (
+    PlanAndExecute,
+    load_agent_executor,
+    load_chat_planner,
+)
+
+__all__ = [
+    "BabyAGI",
+    "AutoGPT",
+    "GenerativeAgent",
+    "GenerativeAgentMemory",
+    "PlanAndExecute",
+    "load_agent_executor",
+    "load_chat_planner",
+]

libs/experimental/langchain_experimental/autonomous_agents/__init__.py

@@ -0,0 +1,4 @@
+from langchain_experimental.autonomous_agents.autogpt.agent import AutoGPT
+from langchain_experimental.autonomous_agents.baby_agi.baby_agi import BabyAGI
+
+__all__ = ["BabyAGI", "AutoGPT"]

libs/experimental/langchain_experimental/autonomous_agents/autogpt/agent.py

@@ -2,18 +2,8 @@ from __future__ import annotations
 
 from typing import List, Optional
 
-from pydantic import ValidationError
-
 from langchain.chains.llm import LLMChain
 from langchain.chat_models.base import BaseChatModel
-from langchain.experimental.autonomous_agents.autogpt.output_parser import (
-    AutoGPTOutputParser,
-    BaseAutoGPTOutputParser,
-)
-from langchain.experimental.autonomous_agents.autogpt.prompt import AutoGPTPrompt
-from langchain.experimental.autonomous_agents.autogpt.prompt_generator import (
-    FINISH_NAME,
-)
 from langchain.memory import ChatMessageHistory
 from langchain.schema import (
     BaseChatMessageHistory,
@@ -23,6 +13,16 @@ from langchain.schema.messages import AIMessage, HumanMessage, SystemMessage
 from langchain.tools.base import BaseTool
 from langchain.tools.human.tool import HumanInputRun
 from langchain.vectorstores.base import VectorStoreRetriever
+from pydantic import ValidationError
+
+from langchain_experimental.autonomous_agents.autogpt.output_parser import (
+    AutoGPTOutputParser,
+    BaseAutoGPTOutputParser,
+)
+from langchain_experimental.autonomous_agents.autogpt.prompt import AutoGPTPrompt
+from langchain_experimental.autonomous_agents.autogpt.prompt_generator import (
+    FINISH_NAME,
+)
 
 
 class AutoGPT:

libs/experimental/langchain_experimental/autonomous_agents/autogpt/memory.py

@@ -1,9 +1,8 @@
 from typing import Any, Dict, List
 
-from pydantic import Field
-
 from langchain.memory.chat_memory import BaseChatMemory, get_prompt_input_key
 from langchain.vectorstores.base import VectorStoreRetriever
+from pydantic import Field
 
 
 class AutoGPTMemory(BaseChatMemory):

libs/experimental/langchain_experimental/autonomous_agents/autogpt/prompt.py

@@ -1,15 +1,15 @@
 import time
 from typing import Any, Callable, List
 
-from pydantic import BaseModel
-
-from langchain.experimental.autonomous_agents.autogpt.prompt_generator import get_prompt
 from langchain.prompts.chat import (
     BaseChatPromptTemplate,
 )
 from langchain.schema.messages import BaseMessage, HumanMessage, SystemMessage
 from langchain.tools.base import BaseTool
 from langchain.vectorstores.base import VectorStoreRetriever
+from pydantic import BaseModel
+
+from langchain_experimental.autonomous_agents.autogpt.prompt_generator import get_prompt
 
 
 class AutoGPTPrompt(BaseChatPromptTemplate, BaseModel):

libs/experimental/langchain_experimental/autonomous_agents/baby_agi/__init__.py

@@ -1,11 +1,11 @@
-from langchain.experimental.autonomous_agents.baby_agi.baby_agi import BabyAGI
-from langchain.experimental.autonomous_agents.baby_agi.task_creation import (
+from langchain_experimental.autonomous_agents.baby_agi.baby_agi import BabyAGI
+from langchain_experimental.autonomous_agents.baby_agi.task_creation import (
     TaskCreationChain,
 )
-from langchain.experimental.autonomous_agents.baby_agi.task_execution import (
+from langchain_experimental.autonomous_agents.baby_agi.task_execution import (
     TaskExecutionChain,
 )
-from langchain.experimental.autonomous_agents.baby_agi.task_prioritization import (
+from langchain_experimental.autonomous_agents.baby_agi.task_prioritization import (
     TaskPrioritizationChain,
 )
 

libs/experimental/langchain_experimental/autonomous_agents/baby_agi/baby_agi.py

@@ -2,21 +2,21 @@
 from collections import deque
 from typing import Any, Dict, List, Optional
 
-from pydantic import BaseModel, Field
-
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
-from langchain.experimental.autonomous_agents.baby_agi.task_creation import (
-    TaskCreationChain,
-)
-from langchain.experimental.autonomous_agents.baby_agi.task_execution import (
-    TaskExecutionChain,
-)
-from langchain.experimental.autonomous_agents.baby_agi.task_prioritization import (
-    TaskPrioritizationChain,
-)
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.vectorstores.base import VectorStore
+from pydantic import BaseModel, Field
+
+from langchain_experimental.autonomous_agents.baby_agi.task_creation import (
+    TaskCreationChain,
+)
+from langchain_experimental.autonomous_agents.baby_agi.task_execution import (
+    TaskExecutionChain,
+)
+from langchain_experimental.autonomous_agents.baby_agi.task_prioritization import (
+    TaskPrioritizationChain,
+)
 
 
 class BabyAGI(Chain, BaseModel):

libs/experimental/langchain_experimental/cpal/base.py

@@ -7,33 +7,33 @@ import json
 from typing import Any, ClassVar, Dict, List, Optional, Type
 
 import pydantic
-
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
-from langchain.experimental.cpal.constants import Constant
-from langchain.experimental.cpal.models import (
+from langchain.output_parsers import PydanticOutputParser
+from langchain.prompts.prompt import PromptTemplate
+
+from langchain_experimental.cpal.constants import Constant
+from langchain_experimental.cpal.models import (
     CausalModel,
     InterventionModel,
     NarrativeModel,
     QueryModel,
     StoryModel,
 )
-from langchain.experimental.cpal.templates.univariate.causal import (
+from langchain_experimental.cpal.templates.univariate.causal import (
     template as causal_template,
 )
-from langchain.experimental.cpal.templates.univariate.intervention import (
+from langchain_experimental.cpal.templates.univariate.intervention import (
     template as intervention_template,
 )
-from langchain.experimental.cpal.templates.univariate.narrative import (
+from langchain_experimental.cpal.templates.univariate.narrative import (
     template as narrative_template,
 )
-from langchain.experimental.cpal.templates.univariate.query import (
+from langchain_experimental.cpal.templates.univariate.query import (
     template as query_template,
 )
-from langchain.output_parsers import PydanticOutputParser
-from langchain.prompts.prompt import PromptTemplate
 
 
 class _BaseStoryElementChain(Chain):

libs/experimental/langchain_experimental/cpal/models.py

@@ -5,10 +5,10 @@ from typing import Any, Optional, Union
 
 import duckdb
 import pandas as pd
+from langchain.graphs.networkx_graph import NetworkxEntityGraph
 from pydantic import BaseModel, Field, PrivateAttr, root_validator, validator
 
-from langchain.experimental.cpal.constants import Constant
-from langchain.graphs.networkx_graph import NetworkxEntityGraph
+from langchain_experimental.cpal.constants import Constant
 
 
 class NarrativeModel(BaseModel):

libs/experimental/langchain_experimental/generative_agents/__init__.py

@@ -1,5 +1,5 @@
 """Generative Agents primitives."""
-from langchain.experimental.generative_agents.generative_agent import GenerativeAgent
-from langchain.experimental.generative_agents.memory import GenerativeAgentMemory
+from langchain_experimental.generative_agents.generative_agent import GenerativeAgent
+from langchain_experimental.generative_agents.memory import GenerativeAgentMemory
 
 __all__ = ["GenerativeAgent", "GenerativeAgentMemory"]

libs/experimental/langchain_experimental/generative_agents/generative_agent.py

@@ -2,12 +2,12 @@ import re
 from datetime import datetime
 from typing import Any, Dict, List, Optional, Tuple
 
-from pydantic import BaseModel, Field
-
 from langchain.chains import LLMChain
-from langchain.experimental.generative_agents.memory import GenerativeAgentMemory
 from langchain.prompts import PromptTemplate
 from langchain.schema.language_model import BaseLanguageModel
+from pydantic import BaseModel, Field
+
+from langchain_experimental.generative_agents.memory import GenerativeAgentMemory
 
 
 class GenerativeAgent(BaseModel):

libs/experimental/langchain_experimental/llms/__init__.py

@@ -0,0 +1,6 @@
+"""Experimental LLM wrappers."""
+
+from langchain_experimental.llms.jsonformer_decoder import JsonFormer
+from langchain_experimental.llms.rellm_decoder import RELLM
+
+__all__ = ["RELLM", "JsonFormer"]

libs/experimental/langchain_experimental/llms/jsonformer_decoder.py

@@ -4,10 +4,9 @@ from __future__ import annotations
 import json
 from typing import TYPE_CHECKING, Any, List, Optional, cast
 
-from pydantic import Field, root_validator
-
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
+from pydantic import Field, root_validator
 
 if TYPE_CHECKING:
     import jsonformer

libs/experimental/langchain_experimental/llms/rellm_decoder.py

@@ -3,11 +3,10 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, Any, List, Optional, cast
 
-from pydantic import Field, root_validator
-
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
 from langchain.llms.utils import enforce_stop_tokens
+from pydantic import Field, root_validator
 
 if TYPE_CHECKING:
     import rellm

libs/experimental/langchain_experimental/pal_chain/__init__.py

@@ -5,6 +5,6 @@ As in https://arxiv.org/pdf/2211.10435.pdf.
 This is vulnerable to arbitrary code execution:
 https://github.com/hwchase17/langchain/issues/5872
 """
-from langchain.experimental.pal_chain.base import PALChain
+from langchain_experimental.pal_chain.base import PALChain
 
 __all__ = ["PALChain"]

libs/experimental/langchain_experimental/pal_chain/base.py

@@ -11,16 +11,16 @@ import ast
 import warnings
 from typing import Any, Dict, List, Optional
 
-from pydantic import Extra, Field, root_validator
-
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
-from langchain.chains.pal.colored_object_prompt import COLORED_OBJECT_PROMPT
-from langchain.chains.pal.math_prompt import MATH_PROMPT
 from langchain.schema import BasePromptTemplate
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.utilities import PythonREPL
+from pydantic import Extra, Field, root_validator
+
+from langchain_experimental.pal_chain.colored_object_prompt import COLORED_OBJECT_PROMPT
+from langchain_experimental.pal_chain.math_prompt import MATH_PROMPT
 
 COMMAND_EXECUTION_FUNCTIONS = ["system", "exec", "execfile", "eval"]
 

libs/experimental/langchain_experimental/plan_and_execute/__init__.py

@@ -0,0 +1,9 @@
+from langchain_experimental.plan_and_execute.agent_executor import PlanAndExecute
+from langchain_experimental.plan_and_execute.executors.agent_executor import (
+    load_agent_executor,
+)
+from langchain_experimental.plan_and_execute.planners.chat_planner import (
+    load_chat_planner,
+)
+
+__all__ = ["PlanAndExecute", "load_agent_executor", "load_chat_planner"]

libs/experimental/langchain_experimental/plan_and_execute/agent_executor.py

@@ -1,12 +1,12 @@
 from typing import Any, Dict, List, Optional
 
-from pydantic import Field
-
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
-from langchain.experimental.plan_and_execute.executors.base import BaseExecutor
-from langchain.experimental.plan_and_execute.planners.base import BasePlanner
-from langchain.experimental.plan_and_execute.schema import (
+from pydantic import Field
+
+from langchain_experimental.plan_and_execute.executors.base import BaseExecutor
+from langchain_experimental.plan_and_execute.planners.base import BasePlanner
+from langchain_experimental.plan_and_execute.schema import (
     BaseStepContainer,
     ListStepContainer,
 )

libs/experimental/langchain_experimental/plan_and_execute/executors/agent_executor.py

@@ -2,10 +2,11 @@ from typing import List
 
 from langchain.agents.agent import AgentExecutor
 from langchain.agents.structured_chat.base import StructuredChatAgent
-from langchain.experimental.plan_and_execute.executors.base import ChainExecutor
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools import BaseTool
 
+from langchain_experimental.plan_and_execute.executors.base import ChainExecutor
+
 HUMAN_MESSAGE_TEMPLATE = """Previous steps: {previous_steps}
 
 Current objective: {current_step}

libs/experimental/langchain_experimental/plan_and_execute/executors/base.py

@@ -1,11 +1,11 @@
 from abc import abstractmethod
 from typing import Any
 
-from pydantic import BaseModel
-
 from langchain.callbacks.manager import Callbacks
 from langchain.chains.base import Chain
-from langchain.experimental.plan_and_execute.schema import StepResponse
+from pydantic import BaseModel
+
+from langchain_experimental.plan_and_execute.schema import StepResponse
 
 
 class BaseExecutor(BaseModel):

libs/experimental/langchain_experimental/plan_and_execute/planners/base.py

@@ -1,11 +1,11 @@
 from abc import abstractmethod
 from typing import Any, List, Optional
 
-from pydantic import BaseModel
-
 from langchain.callbacks.manager import Callbacks
 from langchain.chains.llm import LLMChain
-from langchain.experimental.plan_and_execute.schema import Plan, PlanOutputParser
+from pydantic import BaseModel
+
+from langchain_experimental.plan_and_execute.schema import Plan, PlanOutputParser
 
 
 class BasePlanner(BaseModel):

libs/experimental/langchain_experimental/plan_and_execute/planners/chat_planner.py

@@ -1,15 +1,16 @@
 import re
 
 from langchain.chains import LLMChain
-from langchain.experimental.plan_and_execute.planners.base import LLMPlanner
-from langchain.experimental.plan_and_execute.schema import (
+from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
+from langchain.schema.language_model import BaseLanguageModel
+from langchain.schema.messages import SystemMessage
+
+from langchain_experimental.plan_and_execute.planners.base import LLMPlanner
+from langchain_experimental.plan_and_execute.schema import (
     Plan,
     PlanOutputParser,
     Step,
 )
-from langchain.prompts import ChatPromptTemplate, HumanMessagePromptTemplate
-from langchain.schema.language_model import BaseLanguageModel
-from langchain.schema.messages import SystemMessage
 
 SYSTEM_PROMPT = (
     "Let's first understand the problem and devise a plan to solve the problem."

libs/experimental/langchain_experimental/plan_and_execute/schema.py

@@ -1,9 +1,8 @@
 from abc import abstractmethod
 from typing import List, Tuple
 
-from pydantic import BaseModel, Field
-
 from langchain.schema import BaseOutputParser
+from pydantic import BaseModel, Field
 
 
 class Step(BaseModel):

libs/experimental/langchain_experimental/prompts/__init__.py

@@ -0,0 +1,3 @@
+from langchain_experimental.prompts.load import load_prompt
+
+__all__ = ["load_prompt"]

libs/experimental/langchain_experimental/prompts/load.py

@@ -5,7 +5,6 @@ from pathlib import Path
 from typing import Union
 
 import yaml
-
 from langchain.prompts.loading import load_prompt_from_config, try_load_from_hub
 from langchain.schema.prompts import BasePromptTemplate
 

libs/experimental/langchain_experimental/sql/__init__.py

@@ -1,4 +1,4 @@
 """Chain for interacting with SQL Database."""
-from langchain.experimental.sql.base import SQLDatabaseChain
+from langchain_experimental.sql.base import SQLDatabaseChain
 
 __all__ = ["SQLDatabaseChain"]

libs/experimental/langchain_experimental/sql/base.py

@@ -4,17 +4,17 @@ from __future__ import annotations
 import warnings
 from typing import Any, Dict, List, Optional
 
-from pydantic import Extra, Field, root_validator
-
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
-from langchain.chains.sql_database.prompt import DECIDER_PROMPT, PROMPT, SQL_PROMPTS
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.sql_database.prompt import QUERY_CHECKER
 from langchain.utilities.sql_database import SQLDatabase
+from pydantic import Extra, Field, root_validator
+
+from langchain_experimental.sql.prompt import DECIDER_PROMPT, PROMPT, SQL_PROMPTS
 
 INTERMEDIATE_STEPS_KEY = "intermediate_steps"
 
@@ -25,7 +25,7 @@ class SQLDatabaseChain(Chain):
     Example:
         .. code-block:: python
 
-            from langchain.experimental.sql import SQLDatabaseChain
+            from langchain_experimental.sql import SQLDatabaseChain
             from langchain import OpenAI, SQLDatabase
             db = SQLDatabase(...)
             db_chain = SQLDatabaseChain.from_llm(OpenAI(), db)

libs/experimental/pyproject.toml

@@ -1,14 +1,11 @@
 [tool.poetry]
 name = "langchain-experimental"
-version = "0.0.1rc0"
+version = "0.0.1rc4"
 description = "Building applications with LLMs through composability"
 authors = []
 license = "MIT"
 readme = "README.md"
 repository = "https://www.github.com/hwchase17/langchain"
-packages = [
-    {include = "langchain"}
-]
 
 
 [tool.poetry.dependencies]