move base prompt to schema (#6995)

Co-authored-by: Dev 2049 <dev.dev2049@gmail.com>
Co-authored-by: Bagatur <baskaryan@gmail.com>

langchain/__init__.py

@@ -38,11 +38,11 @@ from langchain.llms import (
 )
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
 from langchain.prompts import (
-    BasePromptTemplate,
     FewShotPromptTemplate,
     Prompt,
     PromptTemplate,
 )
+from langchain.schema.prompt_template import BasePromptTemplate
 from langchain.sql_database import SQLDatabase
 from langchain.utilities.arxiv import ArxivAPIWrapper
 from langchain.utilities.google_search import GoogleSearchAPIWrapper

langchain/agents/agent.py

@@ -26,13 +26,13 @@ from langchain.callbacks.manager import (
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.input import get_color_mapping
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.few_shot import FewShotPromptTemplate
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import (
     AgentAction,
     AgentFinish,
     BaseOutputParser,
+    BasePromptTemplate,
     OutputParserException,
 )
 from langchain.schema.messages import BaseMessage

langchain/agents/agent_toolkits/openapi/planner.py

@@ -34,8 +34,8 @@ from langchain.chains.llm import LLMChain
 from langchain.llms.openai import OpenAI
 from langchain.memory import ReadOnlySharedMemory
 from langchain.prompts import PromptTemplate
-from langchain.prompts.base import BasePromptTemplate
 from langchain.requests import RequestsWrapper
+from langchain.schema import BasePromptTemplate
 from langchain.tools.base import BaseTool
 from langchain.tools.requests.tool import BaseRequestsTool
 

langchain/agents/agent_toolkits/pandas/base.py

@@ -19,7 +19,7 @@ from langchain.agents.types import AgentType
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.schema.messages import SystemMessage
 from langchain.tools.python.tool import PythonAstREPLTool
 

langchain/agents/chat/base.py

@@ -14,13 +14,12 @@ from langchain.agents.utils import validate_tools_single_input
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
-from langchain.schema import AgentAction
+from langchain.schema import AgentAction, BasePromptTemplate
 from langchain.tools.base import BaseTool
 
 

langchain/agents/conversational_chat/base.py

@@ -16,17 +16,13 @@ from langchain.agents.utils import validate_tools_single_input
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains import LLMChain
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
     SystemMessagePromptTemplate,
 )
-from langchain.schema import (
-    AgentAction,
-    BaseOutputParser,
-)
+from langchain.schema import AgentAction, BaseOutputParser, BasePromptTemplate
 from langchain.schema.messages import AIMessage, BaseMessage, HumanMessage
 from langchain.tools.base import BaseTool
 

langchain/agents/openai_functions_agent/base.py

@@ -11,7 +11,6 @@ from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.callbacks.manager import Callbacks
 from langchain.chat_models.openai import ChatOpenAI
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.chat import (
     BaseMessagePromptTemplate,
     ChatPromptTemplate,
@@ -21,6 +20,7 @@ from langchain.prompts.chat import (
 from langchain.schema import (
     AgentAction,
     AgentFinish,
+    BasePromptTemplate,
     OutputParserException,
 )
 from langchain.schema.messages import (

langchain/agents/openai_functions_multi_agent/base.py

@@ -11,7 +11,6 @@ from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.callbacks.manager import Callbacks
 from langchain.chat_models.openai import ChatOpenAI
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.chat import (
     BaseMessagePromptTemplate,
     ChatPromptTemplate,
@@ -21,6 +20,7 @@ from langchain.prompts.chat import (
 from langchain.schema import (
     AgentAction,
     AgentFinish,
+    BasePromptTemplate,
     OutputParserException,
 )
 from langchain.schema.messages import (

langchain/agents/react/base.py

@@ -13,7 +13,7 @@ from langchain.agents.utils import validate_tools_single_input
 from langchain.base_language import BaseLanguageModel
 from langchain.docstore.base import Docstore
 from langchain.docstore.document import Document
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.tools.base import BaseTool
 
 

langchain/agents/self_ask_with_search/base.py

@@ -10,7 +10,7 @@ from langchain.agents.self_ask_with_search.prompt import PROMPT
 from langchain.agents.tools import Tool
 from langchain.agents.utils import validate_tools_single_input
 from langchain.base_language import BaseLanguageModel
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.tools.base import BaseTool
 from langchain.utilities.google_serper import GoogleSerperAPIWrapper
 from langchain.utilities.serpapi import SerpAPIWrapper

langchain/agents/structured_chat/base.py

@@ -11,13 +11,12 @@ from langchain.agents.structured_chat.prompt import FORMAT_INSTRUCTIONS, PREFIX,
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.base import BaseCallbackManager
 from langchain.chains.llm import LLMChain
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
-from langchain.schema import AgentAction
+from langchain.schema import AgentAction, BasePromptTemplate
 from langchain.tools import BaseTool
 
 HUMAN_MESSAGE_TEMPLATE = "{input}\n\n{agent_scratchpad}"

langchain/callbacks/tracers/evaluation.py

@@ -1,5 +1,4 @@
 """A tracer that runs evaluators over completed runs."""
-import logging
 from concurrent.futures import Future, ThreadPoolExecutor, wait
 from typing import Any, Optional, Sequence, Set, Union
 from uuid import UUID
@@ -9,8 +8,6 @@ from langchainplus_sdk import LangChainPlusClient, RunEvaluator
 from langchain.callbacks.tracers.base import BaseTracer
 from langchain.callbacks.tracers.schemas import Run
 
-logger = logging.getLogger(__name__)
-
 
 class EvaluatorCallbackHandler(BaseTracer):
     """A tracer that runs a run evaluator whenever a run is persisted.
@@ -50,7 +47,7 @@ class EvaluatorCallbackHandler(BaseTracer):
         max_workers: Optional[int] = None,
         client: Optional[LangChainPlusClient] = None,
         example_id: Optional[Union[UUID, str]] = None,
-        **kwargs: Any,
+        **kwargs: Any
     ) -> None:
         super().__init__(**kwargs)
         self.example_id = (
@@ -63,17 +60,6 @@ class EvaluatorCallbackHandler(BaseTracer):
         )
         self.futures: Set[Future] = set()
 
-    def _evaluate_run(self, run: Run, evaluator: RunEvaluator) -> None:
-        try:
-            self.client.evaluate_run(run, evaluator)
-        except Exception as e:
-            logger.error(
-                f"Error evaluating run {run.id} with "
-                f"{evaluator.__class__.__name__}: {e}",
-                exc_info=True,
-            )
-            raise e
-
     def _persist_run(self, run: Run) -> None:
         """Run the evaluator on the run.
 
@@ -86,7 +72,9 @@ class EvaluatorCallbackHandler(BaseTracer):
         run_ = run.copy()
         run_.reference_example_id = self.example_id
         for evaluator in self.evaluators:
-            self.futures.add(self.executor.submit(self._evaluate_run, run_, evaluator))
+            self.futures.add(
+                self.executor.submit(self.client.evaluate_run, run_, evaluator)
+            )
 
     def wait_for_futures(self) -> None:
         """Wait for all futures to complete."""

langchain/chains/api/base.py

@@ -13,8 +13,8 @@ from langchain.callbacks.manager import (
 from langchain.chains.api.prompt import API_RESPONSE_PROMPT, API_URL_PROMPT
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
-from langchain.prompts import BasePromptTemplate
 from langchain.requests import TextRequestsWrapper
+from langchain.schema import BasePromptTemplate
 
 
 class APIChain(Chain):

langchain/chains/combine_documents/base.py

@@ -11,7 +11,7 @@ from langchain.callbacks.manager import (
 )
 from langchain.chains.base import Chain
 from langchain.docstore.document import Document
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.text_splitter import RecursiveCharacterTextSplitter, TextSplitter
 
 

langchain/chains/combine_documents/refine.py

@@ -13,8 +13,8 @@ from langchain.chains.combine_documents.base import (
 )
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.prompt import PromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 def _get_default_document_prompt() -> PromptTemplate:

langchain/chains/combine_documents/stuff.py

@@ -11,8 +11,8 @@ from langchain.chains.combine_documents.base import (
 )
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.prompt import PromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 def _get_default_document_prompt() -> PromptTemplate:

langchain/chains/constitutional_ai/base.py

@@ -8,7 +8,7 @@ from langchain.chains.constitutional_ai.models import ConstitutionalPrinciple
 from langchain.chains.constitutional_ai.principles import PRINCIPLES
 from langchain.chains.constitutional_ai.prompts import CRITIQUE_PROMPT, REVISION_PROMPT
 from langchain.chains.llm import LLMChain
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class ConstitutionalChain(Chain):

langchain/chains/conversation/base.py

@@ -6,8 +6,7 @@ from pydantic import Extra, Field, root_validator
 from langchain.chains.conversation.prompt import PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.memory.buffer import ConversationBufferMemory
-from langchain.prompts.base import BasePromptTemplate
-from langchain.schema import BaseMemory
+from langchain.schema import BaseMemory, BasePromptTemplate
 
 
 class ConversationChain(LLMChain):

langchain/chains/conversational_retrieval/base.py

@@ -21,8 +21,7 @@ from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.conversational_retrieval.prompts import CONDENSE_QUESTION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.chains.question_answering import load_qa_chain
-from langchain.prompts.base import BasePromptTemplate
-from langchain.schema import BaseRetriever, Document
+from langchain.schema import BasePromptTemplate, BaseRetriever, Document
 from langchain.schema.messages import BaseMessage
 from langchain.vectorstores.base import VectorStore
 

langchain/chains/flare/base.py

@@ -19,8 +19,7 @@ from langchain.chains.flare.prompts import (
 )
 from langchain.chains.llm import LLMChain
 from langchain.llms import OpenAI
-from langchain.prompts import BasePromptTemplate
-from langchain.schema import BaseRetriever, Generation
+from langchain.schema import BasePromptTemplate, BaseRetriever, Generation
 
 
 class _ResponseChain(LLMChain):

langchain/chains/graph_qa/base.py

@@ -11,7 +11,7 @@ from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import ENTITY_EXTRACTION_PROMPT, PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.networkx_graph import NetworkxEntityGraph, get_entities
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class GraphQAChain(Chain):

langchain/chains/graph_qa/cypher.py

@@ -12,7 +12,7 @@ from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import CYPHER_GENERATION_PROMPT, CYPHER_QA_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.neo4j_graph import Neo4jGraph
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 INTERMEDIATE_STEPS_KEY = "intermediate_steps"
 

langchain/chains/graph_qa/kuzu.py

@@ -11,7 +11,7 @@ from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import CYPHER_QA_PROMPT, KUZU_GENERATION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.kuzu_graph import KuzuGraph
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class KuzuQAChain(Chain):

langchain/chains/graph_qa/nebulagraph.py

@@ -11,7 +11,7 @@ from langchain.chains.base import Chain
 from langchain.chains.graph_qa.prompts import CYPHER_QA_PROMPT, NGQL_GENERATION_PROMPT
 from langchain.chains.llm import LLMChain
 from langchain.graphs.nebula_graph import NebulaGraph
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class NebulaGraphQAChain(Chain):

langchain/chains/llm.py

@@ -17,10 +17,10 @@ from langchain.callbacks.manager import (
 from langchain.chains.base import Chain
 from langchain.input import get_colored_text
 from langchain.load.dump import dumpd
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import (
     BaseLLMOutputParser,
+    BasePromptTemplate,
     LLMResult,
     NoOpOutputParser,
     PromptValue,

langchain/chains/llm_bash/base.py

@@ -12,8 +12,7 @@ from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_bash.prompt import PROMPT
-from langchain.prompts.base import BasePromptTemplate
-from langchain.schema import OutputParserException
+from langchain.schema import BasePromptTemplate, OutputParserException
 from langchain.utilities.bash import BashProcess
 
 logger = logging.getLogger(__name__)

langchain/chains/llm_math/base.py

@@ -17,7 +17,7 @@ from langchain.callbacks.manager import (
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.llm_math.prompt import PROMPT
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class LLMMathChain(Chain):

langchain/chains/mapreduce.py

@@ -17,7 +17,7 @@ from langchain.chains.combine_documents.map_reduce import MapReduceDocumentsChai
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.text_splitter import TextSplitter
 
 

langchain/chains/openai_functions/openapi.py

@@ -7,7 +7,7 @@ import requests
 from openapi_schema_pydantic import Parameter
 from requests import Response
 
-from langchain import BasePromptTemplate, LLMChain
+from langchain import LLMChain
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
@@ -16,6 +16,7 @@ from langchain.chat_models import ChatOpenAI
 from langchain.input import get_colored_text
 from langchain.output_parsers.openai_functions import JsonOutputFunctionsParser
 from langchain.prompts import ChatPromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.tools import APIOperation
 from langchain.utilities.openapi import OpenAPISpec
 

langchain/chains/pal/base.py

@@ -15,7 +15,7 @@ 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.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.utilities import PythonREPL
 
 

langchain/chains/prompt_selector.py

@@ -6,7 +6,7 @@ from pydantic import BaseModel, Field
 from langchain.base_language import BaseLanguageModel
 from langchain.chat_models.base import BaseChatModel
 from langchain.llms.base import BaseLLM
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class BasePromptSelector(BaseModel, ABC):

langchain/chains/qa_generation/base.py

@@ -10,7 +10,7 @@ from langchain.callbacks.manager import CallbackManagerForChainRun
 from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain.chains.qa_generation.prompt import PROMPT_SELECTOR
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.text_splitter import RecursiveCharacterTextSplitter, TextSplitter
 
 

langchain/chains/qa_with_sources/base.py

@@ -26,7 +26,7 @@ from langchain.chains.qa_with_sources.map_reduce_prompt import (
     QUESTION_PROMPT,
 )
 from langchain.docstore.document import Document
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class BaseQAWithSourcesChain(Chain, ABC):

langchain/chains/qa_with_sources/loading.py

@@ -18,7 +18,7 @@ from langchain.chains.qa_with_sources import (
 from langchain.chains.question_answering.map_rerank_prompt import (
     PROMPT as MAP_RERANK_PROMPT,
 )
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema.prompt_template import BasePromptTemplate
 
 
 class LoadingCallable(Protocol):

langchain/chains/query_constructor/base.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 import json
 from typing import Any, Callable, List, Optional, Sequence
 
-from langchain import BasePromptTemplate, FewShotPromptTemplate, LLMChain
+from langchain import FewShotPromptTemplate, LLMChain
 from langchain.base_language import BaseLanguageModel
 from langchain.chains.query_constructor.ir import (
     Comparator,
@@ -23,7 +23,7 @@ from langchain.chains.query_constructor.prompt import (
 )
 from langchain.chains.query_constructor.schema import AttributeInfo
 from langchain.output_parsers.json import parse_and_check_json_markdown
-from langchain.schema import BaseOutputParser, OutputParserException
+from langchain.schema import BaseOutputParser, BasePromptTemplate, OutputParserException
 
 
 class StructuredQueryOutputParser(BaseOutputParser[StructuredQuery]):

langchain/chains/question_answering/__init__.py

@@ -18,7 +18,7 @@ from langchain.chains.question_answering import (
 from langchain.chains.question_answering.map_rerank_prompt import (
     PROMPT as MAP_RERANK_PROMPT,
 )
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema.prompt_template import BasePromptTemplate
 
 
 class LoadingCallable(Protocol):

langchain/chains/router/llm_router.py

@@ -13,8 +13,7 @@ from langchain.callbacks.manager import (
 from langchain.chains import LLMChain
 from langchain.chains.router.base import RouterChain
 from langchain.output_parsers.json import parse_and_check_json_markdown
-from langchain.prompts import BasePromptTemplate
-from langchain.schema import BaseOutputParser, OutputParserException
+from langchain.schema import BaseOutputParser, BasePromptTemplate, OutputParserException
 
 
 class LLMRouterChain(RouterChain):

langchain/chains/sql_database/base.py

@@ -11,8 +11,8 @@ 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.base import BasePromptTemplate
 from langchain.prompts.prompt import PromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.sql_database import SQLDatabase
 from langchain.tools.sql_database.prompt import QUERY_CHECKER
 

langchain/chains/summarize/__init__.py

@@ -8,7 +8,7 @@ from langchain.chains.combine_documents.refine import RefineDocumentsChain
 from langchain.chains.combine_documents.stuff import StuffDocumentsChain
 from langchain.chains.llm import LLMChain
 from langchain.chains.summarize import map_reduce_prompt, refine_prompts, stuff_prompt
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 
 
 class LoadingCallable(Protocol):

langchain/evaluation/criteria/eval_chain.py

@@ -8,8 +8,7 @@ from langchain.base_language import BaseLanguageModel
 from langchain.chains.constitutional_ai.models import ConstitutionalPrinciple
 from langchain.chains.llm import LLMChain
 from langchain.evaluation.criteria.prompt import PROMPT, PROMPT_WITH_REFERENCES
-from langchain.prompts.base import BasePromptTemplate
-from langchain.schema import BaseOutputParser
+from langchain.schema import BaseOutputParser, BasePromptTemplate
 
 _SUPPORTED_CRITERIA = {
     "conciseness": "Is the submission concise and to the point?",

langchain/evaluation/qa/eval_chain.py

@@ -19,20 +19,14 @@ def _parse_string_eval_output(text: str) -> dict:
     Returns:
         Any: The parsed output.
     """
-    splits = text.strip().rsplit("\n", maxsplit=1)
-    if len(splits) == 1:
-        verdict = splits[0]
-        reasoning = None
-    else:
-        reasoning, verdict = splits
-        reasoning = reasoning.strip()
+    reasoning, verdict = text.strip().rsplit("\n", maxsplit=1)
     score = (
         1
         if verdict.upper() == "CORRECT"
         else (0 if verdict.upper() == "INCORRECT" else None)
     )
     return {
-        "reasoning": reasoning,
+        "reasoning": reasoning.strip(),
         "value": verdict,
         "score": score,
     }

langchain/evaluation/run_evaluators/implementations.py

@@ -23,9 +23,8 @@ from langchain.evaluation.run_evaluators.base import (
     RunEvaluatorInputMapper,
     RunEvaluatorOutputParser,
 )
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.prompt import PromptTemplate
-from langchain.schema import OutputParserException
+from langchain.schema import BasePromptTemplate, OutputParserException
 from langchain.tools.base import BaseTool
 
 _QA_PROMPTS = {

langchain/memory/entity.py

@@ -13,7 +13,7 @@ from langchain.memory.prompt import (
     ENTITY_SUMMARIZATION_PROMPT,
 )
 from langchain.memory.utils import get_prompt_input_key
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.schema.messages import BaseMessage, get_buffer_string
 
 logger = logging.getLogger(__name__)

langchain/memory/kg.py

@@ -12,7 +12,7 @@ from langchain.memory.prompt import (
     KNOWLEDGE_TRIPLE_EXTRACTION_PROMPT,
 )
 from langchain.memory.utils import get_prompt_input_key
-from langchain.prompts.base import BasePromptTemplate
+from langchain.schema import BasePromptTemplate
 from langchain.schema.messages import BaseMessage, SystemMessage, get_buffer_string
 
 

langchain/memory/summary.py

@@ -8,9 +8,9 @@ from langchain.base_language import BaseLanguageModel
 from langchain.chains.llm import LLMChain
 from langchain.memory.chat_memory import BaseChatMemory
 from langchain.memory.prompt import SUMMARY_PROMPT
-from langchain.prompts.base import BasePromptTemplate
 from langchain.schema import (
     BaseChatMessageHistory,
+    BasePromptTemplate,
 )
 from langchain.schema.messages import BaseMessage, SystemMessage, get_buffer_string
 

langchain/output_parsers/fix.py

@@ -5,8 +5,7 @@ from typing import TypeVar
 from langchain.base_language import BaseLanguageModel
 from langchain.chains.llm import LLMChain
 from langchain.output_parsers.prompts import NAIVE_FIX_PROMPT
-from langchain.prompts.base import BasePromptTemplate
-from langchain.schema import BaseOutputParser, OutputParserException
+from langchain.schema import BaseOutputParser, BasePromptTemplate, OutputParserException
 
 T = TypeVar("T")
 

langchain/output_parsers/retry.py

@@ -4,10 +4,10 @@ from typing import TypeVar
 
 from langchain.base_language import BaseLanguageModel
 from langchain.chains.llm import LLMChain
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import (
     BaseOutputParser,
+    BasePromptTemplate,
     OutputParserException,
     PromptValue,
 )

langchain/prompts/__init__.py

@@ -1,5 +1,5 @@
 """Prompt template classes."""
-from langchain.prompts.base import BasePromptTemplate, StringPromptTemplate
+from langchain.prompts.base import StringPromptTemplate
 from langchain.prompts.chat import (
     AIMessagePromptTemplate,
     BaseChatPromptTemplate,
@@ -20,6 +20,7 @@ from langchain.prompts.few_shot_with_templates import FewShotPromptWithTemplates
 from langchain.prompts.loading import load_prompt
 from langchain.prompts.pipeline import PipelinePromptTemplate
 from langchain.prompts.prompt import Prompt, PromptTemplate
+from langchain.schema.prompt_template import BasePromptTemplate
 
 __all__ = [
     "AIMessagePromptTemplate",

langchain/prompts/base.py

@@ -1,18 +1,13 @@
 """BasePrompt schema definition."""
 from __future__ import annotations
 
-import json
-from abc import ABC, abstractmethod
-from pathlib import Path
-from typing import Any, Callable, Dict, List, Mapping, Optional, Set, Union
-
-import yaml
-from pydantic import Field, root_validator
+from abc import ABC
+from typing import Any, Callable, Dict, List, Set
 
 from langchain.formatting import formatter
-from langchain.load.serializable import Serializable
-from langchain.schema import BaseOutputParser, PromptValue
+from langchain.schema import BasePromptTemplate
 from langchain.schema.messages import BaseMessage, HumanMessage
+from langchain.schema.prompt import PromptValue
 
 
 def jinja2_formatter(template: str, **kwargs: Any) -> str:
@@ -110,133 +105,6 @@ class StringPromptValue(PromptValue):
         return [HumanMessage(content=self.text)]
 
 
-class BasePromptTemplate(Serializable, ABC):
-    """Base class for all prompt templates, returning a prompt."""
-
-    input_variables: List[str]
-    """A list of the names of the variables the prompt template expects."""
-    output_parser: Optional[BaseOutputParser] = None
-    """How to parse the output of calling an LLM on this formatted prompt."""
-    partial_variables: Mapping[str, Union[str, Callable[[], str]]] = Field(
-        default_factory=dict
-    )
-
-    @property
-    def lc_serializable(self) -> bool:
-        return True
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
-
-    @abstractmethod
-    def format_prompt(self, **kwargs: Any) -> PromptValue:
-        """Create Chat Messages."""
-
-    @root_validator()
-    def validate_variable_names(cls, values: Dict) -> Dict:
-        """Validate variable names do not include restricted names."""
-        if "stop" in values["input_variables"]:
-            raise ValueError(
-                "Cannot have an input variable named 'stop', as it is used internally,"
-                " please rename."
-            )
-        if "stop" in values["partial_variables"]:
-            raise ValueError(
-                "Cannot have an partial variable named 'stop', as it is used "
-                "internally, please rename."
-            )
-
-        overall = set(values["input_variables"]).intersection(
-            values["partial_variables"]
-        )
-        if overall:
-            raise ValueError(
-                f"Found overlapping input and partial variables: {overall}"
-            )
-        return values
-
-    def partial(self, **kwargs: Union[str, Callable[[], str]]) -> BasePromptTemplate:
-        """Return a partial of the prompt template."""
-        prompt_dict = self.__dict__.copy()
-        prompt_dict["input_variables"] = list(
-            set(self.input_variables).difference(kwargs)
-        )
-        prompt_dict["partial_variables"] = {**self.partial_variables, **kwargs}
-        return type(self)(**prompt_dict)
-
-    def _merge_partial_and_user_variables(self, **kwargs: Any) -> Dict[str, Any]:
-        # Get partial params:
-        partial_kwargs = {
-            k: v if isinstance(v, str) else v()
-            for k, v in self.partial_variables.items()
-        }
-        return {**partial_kwargs, **kwargs}
-
-    @abstractmethod
-    def format(self, **kwargs: Any) -> str:
-        """Format the prompt with the inputs.
-
-        Args:
-            kwargs: Any arguments to be passed to the prompt template.
-
-        Returns:
-            A formatted string.
-
-        Example:
-
-        .. code-block:: python
-
-            prompt.format(variable1="foo")
-        """
-
-    @property
-    def _prompt_type(self) -> str:
-        """Return the prompt type key."""
-        raise NotImplementedError
-
-    def dict(self, **kwargs: Any) -> Dict:
-        """Return dictionary representation of prompt."""
-        prompt_dict = super().dict(**kwargs)
-        prompt_dict["_type"] = self._prompt_type
-        return prompt_dict
-
-    def save(self, file_path: Union[Path, str]) -> None:
-        """Save the prompt.
-
-        Args:
-            file_path: Path to directory to save prompt to.
-
-        Example:
-        .. code-block:: python
-
-            prompt.save(file_path="path/prompt.yaml")
-        """
-        if self.partial_variables:
-            raise ValueError("Cannot save prompt with partial variables.")
-        # Convert file to Path object.
-        if isinstance(file_path, str):
-            save_path = Path(file_path)
-        else:
-            save_path = file_path
-
-        directory_path = save_path.parent
-        directory_path.mkdir(parents=True, exist_ok=True)
-
-        # Fetch dictionary to save
-        prompt_dict = self.dict()
-
-        if save_path.suffix == ".json":
-            with open(file_path, "w") as f:
-                json.dump(prompt_dict, f, indent=4)
-        elif save_path.suffix == ".yaml":
-            with open(file_path, "w") as f:
-                yaml.dump(prompt_dict, f, default_flow_style=False)
-        else:
-            raise ValueError(f"{save_path} must be json or yaml")
-
-
 class StringPromptTemplate(BasePromptTemplate, ABC):
     """String prompt should expose the format method, returning a prompt."""
 

langchain/prompts/chat.py

@@ -8,9 +8,10 @@ from typing import Any, Callable, List, Sequence, Tuple, Type, TypeVar, Union
 from pydantic import Field, root_validator
 
 from langchain.load.serializable import Serializable
-from langchain.prompts.base import BasePromptTemplate, StringPromptTemplate
+from langchain.prompts.base import StringPromptTemplate
 from langchain.prompts.prompt import PromptTemplate
 from langchain.schema import (
+    BasePromptTemplate,
     PromptValue,
 )
 from langchain.schema.messages import (

langchain/prompts/loading.py

@@ -8,10 +8,9 @@ from typing import Union
 import yaml
 
 from langchain.output_parsers.regex import RegexParser
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.few_shot import FewShotPromptTemplate
 from langchain.prompts.prompt import PromptTemplate
-from langchain.schema import BaseLLMOutputParser, NoOpOutputParser
+from langchain.schema import BaseLLMOutputParser, BasePromptTemplate, NoOpOutputParser
 from langchain.utilities.loading import try_load_from_hub
 
 URL_BASE = "https://raw.githubusercontent.com/hwchase17/langchain-hub/master/prompts/"

langchain/prompts/pipeline.py

@@ -2,9 +2,8 @@ from typing import Any, Dict, List, Tuple
 
 from pydantic import root_validator
 
-from langchain.prompts.base import BasePromptTemplate
 from langchain.prompts.chat import BaseChatPromptTemplate
-from langchain.schema import PromptValue
+from langchain.schema import BasePromptTemplate, PromptValue
 
 
 def _get_inputs(inputs: dict, input_variables: List[str]) -> dict:

langchain/retrievers/document_compressors/chain_filter.py

@@ -1,7 +1,7 @@
 """Filter that uses an LLM to drop documents that aren't relevant to the query."""
 from typing import Any, Callable, Dict, Optional, Sequence
 
-from langchain import BasePromptTemplate, LLMChain, PromptTemplate
+from langchain import LLMChain, PromptTemplate
 from langchain.base_language import BaseLanguageModel
 from langchain.callbacks.manager import Callbacks
 from langchain.output_parsers.boolean import BooleanOutputParser
@@ -9,7 +9,7 @@ from langchain.retrievers.document_compressors.base import BaseDocumentCompresso
 from langchain.retrievers.document_compressors.chain_filter_prompt import (
     prompt_template,
 )
-from langchain.schema import Document
+from langchain.schema import BasePromptTemplate, Document
 
 
 def _get_default_chain_prompt() -> PromptTemplate:

langchain/schema/__init__.py

@@ -28,6 +28,7 @@ from langchain.schema.output_parser import (
     OutputParserException,
 )
 from langchain.schema.prompt import PromptValue
+from langchain.schema.prompt_template import BasePromptTemplate
 from langchain.schema.retriever import BaseRetriever
 
 RUN_KEY = "__run"
@@ -64,4 +65,5 @@ __all__ = [
     "NoOpOutputParser",
     "BaseOutputParser",
     "BaseLLMOutputParser",
+    "BasePromptTemplate",
 ]

langchain/schema/prompt_template.py

@@ -0,0 +1,139 @@
+from __future__ import annotations
+
+import json
+from abc import ABC, abstractmethod
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Mapping, Optional, Union
+
+import yaml
+from pydantic import Field, root_validator
+
+from langchain.load.serializable import Serializable
+from langchain.schema import BaseOutputParser, PromptValue
+
+
+class BasePromptTemplate(Serializable, ABC):
+    """Base class for all prompt templates, returning a prompt."""
+
+    input_variables: List[str]
+    """A list of the names of the variables the prompt template expects."""
+    output_parser: Optional[BaseOutputParser] = None
+    """How to parse the output of calling an LLM on this formatted prompt."""
+    partial_variables: Mapping[str, Union[str, Callable[[], str]]] = Field(
+        default_factory=dict
+    )
+
+    @property
+    def lc_serializable(self) -> bool:
+        return True
+
+    class Config:
+        """Configuration for this pydantic object."""
+
+        arbitrary_types_allowed = True
+
+    @abstractmethod
+    def format_prompt(self, **kwargs: Any) -> PromptValue:
+        """Create Chat Messages."""
+
+    @root_validator()
+    def validate_variable_names(cls, values: Dict) -> Dict:
+        """Validate variable names do not include restricted names."""
+        if "stop" in values["input_variables"]:
+            raise ValueError(
+                "Cannot have an input variable named 'stop', as it is used internally,"
+                " please rename."
+            )
+        if "stop" in values["partial_variables"]:
+            raise ValueError(
+                "Cannot have an partial variable named 'stop', as it is used "
+                "internally, please rename."
+            )
+
+        overall = set(values["input_variables"]).intersection(
+            values["partial_variables"]
+        )
+        if overall:
+            raise ValueError(
+                f"Found overlapping input and partial variables: {overall}"
+            )
+        return values
+
+    def partial(self, **kwargs: Union[str, Callable[[], str]]) -> BasePromptTemplate:
+        """Return a partial of the prompt template."""
+        prompt_dict = self.__dict__.copy()
+        prompt_dict["input_variables"] = list(
+            set(self.input_variables).difference(kwargs)
+        )
+        prompt_dict["partial_variables"] = {**self.partial_variables, **kwargs}
+        return type(self)(**prompt_dict)
+
+    def _merge_partial_and_user_variables(self, **kwargs: Any) -> Dict[str, Any]:
+        # Get partial params:
+        partial_kwargs = {
+            k: v if isinstance(v, str) else v()
+            for k, v in self.partial_variables.items()
+        }
+        return {**partial_kwargs, **kwargs}
+
+    @abstractmethod
+    def format(self, **kwargs: Any) -> str:
+        """Format the prompt with the inputs.
+
+        Args:
+            kwargs: Any arguments to be passed to the prompt template.
+
+        Returns:
+            A formatted string.
+
+        Example:
+
+        .. code-block:: python
+
+            prompt.format(variable1="foo")
+        """
+
+    @property
+    def _prompt_type(self) -> str:
+        """Return the prompt type key."""
+        raise NotImplementedError
+
+    def dict(self, **kwargs: Any) -> Dict:
+        """Return dictionary representation of prompt."""
+        prompt_dict = super().dict(**kwargs)
+        prompt_dict["_type"] = self._prompt_type
+        return prompt_dict
+
+    def save(self, file_path: Union[Path, str]) -> None:
+        """Save the prompt.
+
+        Args:
+            file_path: Path to directory to save prompt to.
+
+        Example:
+        .. code-block:: python
+
+            prompt.save(file_path="path/prompt.yaml")
+        """
+        if self.partial_variables:
+            raise ValueError("Cannot save prompt with partial variables.")
+        # Convert file to Path object.
+        if isinstance(file_path, str):
+            save_path = Path(file_path)
+        else:
+            save_path = file_path
+
+        directory_path = save_path.parent
+        directory_path.mkdir(parents=True, exist_ok=True)
+
+        # Fetch dictionary to save
+        prompt_dict = self.dict()
+
+        if save_path.suffix == ".json":
+            with open(file_path, "w") as f:
+                json.dump(prompt_dict, f, indent=4)
+        elif save_path.suffix == ".yaml":
+            with open(file_path, "w") as f:
+                yaml.dump(prompt_dict, f, default_flow_style=False)
+        else:
+            raise ValueError(f"{save_path} must be json or yaml")