move prompts to core

langchain/agents/agent.py

@@ -17,7 +17,7 @@ from langchain.agents.tools import InvalidTool
 from langchain.chains.llm import LLMChain
 from langchain.input import get_color_mapping
 from langchain.prompts.few_shot import FewShotPromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import (
     AgentAction,
     AgentFinish,

langchain/agents/agent_toolkits/openapi/planner_prompt.py

@@ -1,6 +1,6 @@
 # flake8: noqa
 
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 API_PLANNER_PROMPT = """You are a planner that plans a sequence of API calls to assist with user queries against an API.

langchain/agents/agent_toolkits/powerbi/toolkit.py

@@ -7,7 +7,7 @@ from langchain.agents.agent_toolkits.base import BaseToolkit
 from langchain.chains.llm import LLMChain
 from langchain.chat_models.base import BaseChatModel
 from langchain.prompts import PromptTemplate
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,

langchain/agents/agent_toolkits/sql/base.py

@@ -13,7 +13,7 @@ from langchain.agents.mrkl.base import ZeroShotAgent
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
 from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
 from langchain.chains.llm import LLMChain
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,

langchain/agents/chat/base.py

@@ -12,7 +12,7 @@ from langchain.agents.chat.prompt import (
 )
 from langchain.agents.utils import validate_tools_single_input
 from langchain.chains.llm import LLMChain
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,

langchain/agents/conversational_chat/base.py

@@ -14,7 +14,7 @@ from langchain.agents.conversational_chat.prompt import (
 )
 from langchain.agents.utils import validate_tools_single_input
 from langchain.chains import LLMChain
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     MessagesPlaceholder,

langchain/agents/openai_functions_agent/base.py

@@ -8,7 +8,7 @@ from pydantic import root_validator
 
 from langchain.agents import BaseSingleActionAgent
 from langchain.chat_models.openai import ChatOpenAI
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     BaseMessagePromptTemplate,
     ChatPromptTemplate,
     HumanMessagePromptTemplate,

langchain/agents/openai_functions_multi_agent/base.py

@@ -8,7 +8,7 @@ from pydantic import root_validator
 
 from langchain.agents import BaseMultiActionAgent
 from langchain.chat_models.openai import ChatOpenAI
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     BaseMessagePromptTemplate,
     ChatPromptTemplate,
     HumanMessagePromptTemplate,

langchain/agents/react/textworld_prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLES = [
     """Setup: You are now playing a fast paced round of TextWorld! Here is your task for

langchain/agents/react/wiki_prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLES = [
     """Question: What is the elevation range for the area that the eastern sector of the Colorado orogeny extends into?

langchain/agents/schema.py

@@ -1,6 +1,6 @@
 from typing import Any, Dict, List, Tuple
 
-from langchain.prompts.chat import ChatPromptTemplate
+from langchain.core.prompts.chat import ChatPromptTemplate
 from langchain.schema import AgentAction
 
 

langchain/agents/self_ask_with_search/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _DEFAULT_TEMPLATE = """Question: Who lived longer, Muhammad Ali or Alan Turing?
 Are follow up questions needed here: Yes.

langchain/agents/structured_chat/base.py

@@ -9,7 +9,7 @@ from langchain.agents.structured_chat.output_parser import (
 )
 from langchain.agents.structured_chat.prompt import FORMAT_INSTRUCTIONS, PREFIX, SUFFIX
 from langchain.chains.llm import LLMChain
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,

langchain/chains/api/openapi/requests_chain.py

@@ -6,7 +6,7 @@ from typing import Any
 
 from langchain.chains.api.openapi.prompts import REQUEST_TEMPLATE
 from langchain.chains.llm import LLMChain
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser
 from langchain.schema.language_model import BaseLanguageModel
 

langchain/chains/api/openapi/response_chain.py

@@ -6,7 +6,7 @@ from typing import Any
 
 from langchain.chains.api.openapi.prompts import RESPONSE_TEMPLATE
 from langchain.chains.llm import LLMChain
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser
 from langchain.schema.language_model import BaseLanguageModel
 

langchain/chains/api/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 API_URL_PROMPT_TEMPLATE = """You are given the below API Documentation:
 {api_docs}

langchain/chains/chat_vector_db/prompts.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.
 

langchain/chains/combine_documents/refine.py

@@ -11,7 +11,7 @@ from langchain.chains.combine_documents.base import (
 )
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate, format_document
 from langchain.schema.callbacks.manager import Callbacks
 

langchain/chains/combine_documents/stuff.py

@@ -9,7 +9,7 @@ from langchain.chains.combine_documents.base import (
 )
 from langchain.chains.llm import LLMChain
 from langchain.docstore.document import Document
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate, format_document
 from langchain.schema.callbacks.manager import Callbacks
 

langchain/chains/constitutional_ai/prompts.py

@@ -1,8 +1,7 @@
 # flake8: noqa
-from copy import deepcopy
 
 from langchain.prompts.few_shot import FewShotPromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 critique_example = PromptTemplate(
     template="""Human: {input_prompt}

langchain/chains/conversation/prompt.py

@@ -6,7 +6,7 @@ from langchain.memory.prompt import (
     KNOWLEDGE_TRIPLE_EXTRACTION_PROMPT,
     SUMMARY_PROMPT,
 )
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 DEFAULT_TEMPLATE = """The following is a friendly conversation between a human and an AI. The AI is talkative and provides lots of specific details from its context. If the AI does not know the answer to a question, it truthfully says it does not know.
 

langchain/chains/conversational_retrieval/prompts.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _template = """Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question, in its original language.
 

langchain/chains/graph_qa/prompts.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _DEFAULT_ENTITY_EXTRACTION_TEMPLATE = """Extract all entities from the following text. As a guideline, a proper noun is generally capitalized. You should definitely extract all names and places.
 

langchain/chains/graph_qa/sparql.py

@@ -15,7 +15,7 @@ from langchain.chains.graph_qa.prompts import (
 )
 from langchain.chains.llm import LLMChain
 from langchain.graphs.rdf_graph import RdfGraph
-from langchain.prompts.base import BasePromptTemplate
+from langchain.core.prompts.base import BasePromptTemplate
 from langchain.schema.callbacks.manager import CallbackManagerForChainRun
 from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel

langchain/chains/hyde/prompts.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 web_search_template = """Please write a passage to answer the question 
 Question: {QUESTION}

langchain/chains/llm.py

@@ -8,7 +8,7 @@ from pydantic import Extra, Field
 
 from langchain.input import get_colored_text
 from langchain.load.dump import dumpd
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import (
     BaseLLMOutputParser,
     BasePromptTemplate,

langchain/chains/llm_bash/prompt.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 import re
 from typing import List
 
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser, OutputParserException
 
 _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:

langchain/chains/llm_checker/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _CREATE_DRAFT_ANSWER_TEMPLATE = """{question}\n\n"""
 CREATE_DRAFT_ANSWER_PROMPT = PromptTemplate(

langchain/chains/llm_math/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _PROMPT_TEMPLATE = """Translate a math problem into a expression that can be executed using Python's numexpr library. Use the output of running this code to answer the question.
 

langchain/chains/llm_summarization_checker/base.py

@@ -10,7 +10,7 @@ from pydantic import Extra, root_validator
 
 from langchain.chains.llm import LLMChain
 from langchain.chains.sequential import SequentialChain
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema.callbacks.manager import CallbackManagerForChainRun
 from langchain.schema.chain import Chain
 from langchain.schema.language_model import BaseLanguageModel

langchain/chains/natbot/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _PROMPT_TEMPLATE = """
 You are an agents controlling a browser. You are given:

langchain/chains/openai_functions/citation_fuzzy_match.py

@@ -7,7 +7,7 @@ from langchain.chains.openai_functions.utils import get_llm_kwargs
 from langchain.output_parsers.openai_functions import (
     PydanticOutputFunctionsParser,
 )
-from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
+from langchain.core.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import HumanMessage, SystemMessage
 

langchain/chains/openai_functions/qa_with_structure.py

@@ -9,7 +9,7 @@ from langchain.output_parsers.openai_functions import (
     PydanticOutputFunctionsParser,
 )
 from langchain.prompts import PromptTemplate
-from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
+from langchain.core.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
 from langchain.schema import BaseLLMOutputParser
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.schema.messages import HumanMessage, SystemMessage

langchain/chains/pal/colored_object_prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 template = (
     """

langchain/chains/pal/math_prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 template = (
     '''

langchain/chains/qa_generation/prompt.py

@@ -1,11 +1,11 @@
 # flake8: noqa
 from langchain.chains.prompt_selector import ConditionalPromptSelector, is_chat_model
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 templ1 = """You are a smart assistant designed to help high school teachers come up with reading comprehension questions.
 Given a piece of text, you must come up with a question and answer pair that can be used to test a student's reading comprehension abilities.

langchain/chains/question_answering/map_reduce_prompt.py

@@ -1,11 +1,11 @@
 # flake8: noqa
 from langchain.chains.prompt_selector import ConditionalPromptSelector, is_chat_model
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 question_prompt_template = """Use the following portion of a long document to see if any of the text is relevant to answer the question. 
 Return any relevant text verbatim.

langchain/chains/question_answering/refine_prompts.py

@@ -1,12 +1,12 @@
 # flake8: noqa
 from langchain.chains.prompt_selector import ConditionalPromptSelector, is_chat_model
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     AIMessagePromptTemplate,
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 DEFAULT_REFINE_PROMPT_TMPL = (
     "The original question is as follows: {question}\n"

langchain/chains/question_answering/stuff_prompt.py

@@ -1,7 +1,7 @@
 # flake8: noqa
 from langchain.chains.prompt_selector import ConditionalPromptSelector, is_chat_model
 from langchain.prompts import PromptTemplate
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,

langchain/chains/sql_database/base.py

@@ -8,7 +8,7 @@ from pydantic import Extra, Field, root_validator
 
 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.core.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate
 from langchain.schema.callbacks.manager import CallbackManagerForChainRun
 from langchain.schema.chain import Chain

langchain/chains/sql_database/prompt.py

@@ -1,6 +1,6 @@
 # flake8: noqa
 from langchain.output_parsers.list import CommaSeparatedListOutputParser
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 PROMPT_SUFFIX = """Only use the following tables:

langchain/core/formatting.py

@@ -0,0 +1,38 @@
+"""Utilities for formatting strings."""
+from string import Formatter
+from typing import Any, List, Mapping, Sequence, Union
+
+
+class StrictFormatter(Formatter):
+    """A subclass of formatter that checks for extra keys."""
+
+    def check_unused_args(
+        self,
+        used_args: Sequence[Union[int, str]],
+        args: Sequence,
+        kwargs: Mapping[str, Any],
+    ) -> None:
+        """Check to see if extra parameters are passed."""
+        extra = set(kwargs).difference(used_args)
+        if extra:
+            raise KeyError(extra)
+
+    def vformat(
+        self, format_string: str, args: Sequence, kwargs: Mapping[str, Any]
+    ) -> str:
+        """Check that no arguments are provided."""
+        if len(args) > 0:
+            raise ValueError(
+                "No arguments should be provided, "
+                "everything should be passed as keyword arguments."
+            )
+        return super().vformat(format_string, args, kwargs)
+
+    def validate_input_variables(
+        self, format_string: str, input_variables: List[str]
+    ) -> None:
+        dummy_inputs = {input_variable: "foo" for input_variable in input_variables}
+        super().format(format_string, **dummy_inputs)
+
+
+formatter = StrictFormatter()

langchain/core/input.py

@@ -0,0 +1,42 @@
+"""Handle chained inputs."""
+from typing import Dict, List, Optional, TextIO
+
+_TEXT_COLOR_MAPPING = {
+    "blue": "36;1",
+    "yellow": "33;1",
+    "pink": "38;5;200",
+    "green": "32;1",
+    "red": "31;1",
+}
+
+
+def get_color_mapping(
+    items: List[str], excluded_colors: Optional[List] = None
+) -> Dict[str, str]:
+    """Get mapping for items to a support color."""
+    colors = list(_TEXT_COLOR_MAPPING.keys())
+    if excluded_colors is not None:
+        colors = [c for c in colors if c not in excluded_colors]
+    color_mapping = {item: colors[i % len(colors)] for i, item in enumerate(items)}
+    return color_mapping
+
+
+def get_colored_text(text: str, color: str) -> str:
+    """Get colored text."""
+    color_str = _TEXT_COLOR_MAPPING[color]
+    return f"\u001b[{color_str}m\033[1;3m{text}\u001b[0m"
+
+
+def get_bolded_text(text: str) -> str:
+    """Get bolded text."""
+    return f"\033[1m{text}\033[0m"
+
+
+def print_text(
+    text: str, color: Optional[str] = None, end: str = "", file: Optional[TextIO] = None
+) -> None:
+    """Print text with highlighting and no end characters."""
+    text_to_print = get_colored_text(text, color) if color else text
+    print(text_to_print, end=end, file=file)
+    if file:
+        file.flush()  # ensure all printed content are written to file

langchain/core/prompts/base.py

@@ -5,7 +5,7 @@ import warnings
 from abc import ABC
 from typing import Any, Callable, Dict, List, Set
 
-from langchain.formatting import formatter
+from langchain.core.formatting import formatter
 from langchain.schema import BasePromptTemplate
 from langchain.schema.messages import BaseMessage, HumanMessage
 from langchain.schema.prompt import PromptValue

langchain/core/prompts/chat.py

@@ -8,8 +8,8 @@ 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 StringPromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.base import StringPromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import (
     BasePromptTemplate,
     PromptValue,

langchain/core/prompts/prompt.py

@@ -7,7 +7,7 @@ from typing import Any, Dict, List, Union
 
 from pydantic import root_validator
 
-from langchain.prompts.base import (
+from langchain.core.prompts.base import (
     DEFAULT_FORMATTER_MAPPING,
     StringPromptTemplate,
     _get_jinja2_variables_from_template,

langchain/evaluation/agents/trajectory_eval_prompt.py

@@ -2,7 +2,7 @@
 # flake8: noqa
 from langchain.schema.messages import HumanMessage, AIMessage, SystemMessage
 
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     ChatPromptTemplate,
     HumanMessagePromptTemplate,
 )

langchain/evaluation/comparison/eval_chain.py

@@ -8,7 +8,7 @@ from pydantic import Extra, Field
 from langchain.chains.llm import LLMChain
 from langchain.evaluation.comparison.prompt import PROMPT, PROMPT_WITH_REFERENCE
 from langchain.evaluation.schema import LLMEvalChain, PairwiseStringEvaluator
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser
 from langchain.schema.callbacks.manager import Callbacks
 from langchain.schema.language_model import BaseLanguageModel

langchain/evaluation/run_evaluators/implementations.py

@@ -21,7 +21,7 @@ from langchain.evaluation.run_evaluators.base import (
     RunEvaluatorInputMapper,
     RunEvaluatorOutputParser,
 )
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BasePromptTemplate
 from langchain.schema.language_model import BaseLanguageModel
 from langchain.tools.base import BaseTool

langchain/example_generator.py

@@ -3,7 +3,7 @@ from typing import List
 
 from langchain.chains.llm import LLMChain
 from langchain.prompts.few_shot import FewShotPromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema.language_model import BaseLanguageModel
 
 TEST_GEN_TEMPLATE_SUFFIX = "Add another example."

langchain/experimental/autonomous_agents/autogpt/prompt.py

@@ -4,7 +4,7 @@ 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 (
+from langchain.core.prompts.chat import (
     BaseChatPromptTemplate,
 )
 from langchain.schema.messages import BaseMessage, HumanMessage, SystemMessage

langchain/formatting.py

@@ -1,38 +1 @@
-"""Utilities for formatting strings."""
-from string import Formatter
-from typing import Any, List, Mapping, Sequence, Union
 
-
-class StrictFormatter(Formatter):
-    """A subclass of formatter that checks for extra keys."""
-
-    def check_unused_args(
-        self,
-        used_args: Sequence[Union[int, str]],
-        args: Sequence,
-        kwargs: Mapping[str, Any],
-    ) -> None:
-        """Check to see if extra parameters are passed."""
-        extra = set(kwargs).difference(used_args)
-        if extra:
-            raise KeyError(extra)
-
-    def vformat(
-        self, format_string: str, args: Sequence, kwargs: Mapping[str, Any]
-    ) -> str:
-        """Check that no arguments are provided."""
-        if len(args) > 0:
-            raise ValueError(
-                "No arguments should be provided, "
-                "everything should be passed as keyword arguments."
-            )
-        return super().vformat(format_string, args, kwargs)
-
-    def validate_input_variables(
-        self, format_string: str, input_variables: List[str]
-    ) -> None:
-        dummy_inputs = {input_variable: "foo" for input_variable in input_variables}
-        super().format(format_string, **dummy_inputs)
-
-
-formatter = StrictFormatter()

langchain/indexes/prompts/entity_extraction.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _DEFAULT_ENTITY_EXTRACTION_TEMPLATE = """You are an AI assistant reading the transcript of a conversation between an AI and a human. Extract all of the proper nouns from the last line of conversation. As a guideline, a proper noun is generally capitalized. You should definitely extract all names and places.
 

langchain/indexes/prompts/entity_summarization.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _DEFAULT_ENTITY_SUMMARIZATION_TEMPLATE = """You are an AI assistant helping a human keep track of facts about relevant people, places, and concepts in their life. Update the summary of the provided entity in the "Entity" section based on the last line of your conversation with the human. If you are writing the summary for the first time, return a single sentence.
 The update should only include facts that are relayed in the last line of conversation about the provided entity, and should only contain facts about the provided entity.

langchain/indexes/prompts/knowledge_triplet_extraction.py

@@ -1,7 +1,7 @@
 # flake8: noqa
 
 from langchain.graphs.networkx_graph import KG_TRIPLE_DELIMITER
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _DEFAULT_KNOWLEDGE_TRIPLE_EXTRACTION_TEMPLATE = (
     "You are a networked intelligence helping a human track knowledge triples"

langchain/input.py

@@ -1,42 +1,9 @@
-"""Handle chained inputs."""
-from typing import Dict, List, Optional, TextIO
+"""Purely for backwards compatibility."""
+from langchain.core.input import get_colored_text, get_bolded_text, get_color_mapping, print_text
 
-_TEXT_COLOR_MAPPING = {
-    "blue": "36;1",
-    "yellow": "33;1",
-    "pink": "38;5;200",
-    "green": "32;1",
-    "red": "31;1",
-}
-
-
-def get_color_mapping(
-    items: List[str], excluded_colors: Optional[List] = None
-) -> Dict[str, str]:
-    """Get mapping for items to a support color."""
-    colors = list(_TEXT_COLOR_MAPPING.keys())
-    if excluded_colors is not None:
-        colors = [c for c in colors if c not in excluded_colors]
-    color_mapping = {item: colors[i % len(colors)] for i, item in enumerate(items)}
-    return color_mapping
-
-
-def get_colored_text(text: str, color: str) -> str:
-    """Get colored text."""
-    color_str = _TEXT_COLOR_MAPPING[color]
-    return f"\u001b[{color_str}m\033[1;3m{text}\u001b[0m"
-
-
-def get_bolded_text(text: str) -> str:
-    """Get bolded text."""
-    return f"\033[1m{text}\033[0m"
-
-
-def print_text(
-    text: str, color: Optional[str] = None, end: str = "", file: Optional[TextIO] = None
-) -> None:
-    """Print text with highlighting and no end characters."""
-    text_to_print = get_colored_text(text, color) if color else text
-    print(text_to_print, end=end, file=file)
-    if file:
-        file.flush()  # ensure all printed content are written to file
+__all__ = [
+    "get_bolded_text",
+    "get_color_mapping",
+    "get_colored_text",
+    "print_text"
+]

langchain/memory/prompt.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 _DEFAULT_ENTITY_MEMORY_CONVERSATION_TEMPLATE = """You are an assistant to a human, powered by a large language model trained by OpenAI.
 

langchain/model_laboratory.py

@@ -6,7 +6,7 @@ from typing import List, Optional, Sequence
 from langchain.chains.llm import LLMChain
 from langchain.input import get_color_mapping, print_text
 from langchain.llms.base import BaseLLM
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema.chain import Chain
 
 

langchain/output_parsers/prompts.py

@@ -1,5 +1,5 @@
 # flake8: noqa
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 NAIVE_FIX = """Instructions:
 --------------

langchain/output_parsers/retry.py

@@ -3,7 +3,7 @@ from __future__ import annotations
 from typing import TypeVar
 
 from langchain.chains.llm import LLMChain
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import (
     BaseOutputParser,
     BasePromptTemplate,

langchain/prompts/__init__.py

@@ -1,6 +1,6 @@
 """Prompt template classes."""
-from langchain.prompts.base import StringPromptTemplate
-from langchain.prompts.chat import (
+from langchain.core.prompts.base import StringPromptTemplate
+from langchain.core.prompts.chat import (
     AIMessagePromptTemplate,
     BaseChatPromptTemplate,
     ChatMessagePromptTemplate,
@@ -19,7 +19,7 @@ from langchain.prompts.few_shot import FewShotPromptTemplate
 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.core.prompts.prompt import Prompt, PromptTemplate
 from langchain.schema.prompt_template import BasePromptTemplate
 
 __all__ = [

langchain/prompts/example_selector/length_based.py

@@ -5,7 +5,7 @@ from typing import Callable, Dict, List
 from pydantic import BaseModel, validator
 
 from langchain.prompts.example_selector.base import BaseExampleSelector
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 def _get_length_based(text: str) -> int:

langchain/prompts/example_selector/ngram_overlap.py

@@ -9,7 +9,7 @@ import numpy as np
 from pydantic import BaseModel, root_validator
 
 from langchain.prompts.example_selector.base import BaseExampleSelector
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 def ngram_overlap_score(source: List[str], example: List[str]) -> float:

langchain/prompts/few_shot.py

@@ -3,13 +3,13 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.prompts.base import (
+from langchain.core.prompts.base import (
     DEFAULT_FORMATTER_MAPPING,
     StringPromptTemplate,
     check_valid_template,
 )
 from langchain.prompts.example_selector.base import BaseExampleSelector
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 class FewShotPromptTemplate(StringPromptTemplate):

langchain/prompts/few_shot_with_templates.py

@@ -3,9 +3,9 @@ from typing import Any, Dict, List, Optional
 
 from pydantic import Extra, root_validator
 
-from langchain.prompts.base import DEFAULT_FORMATTER_MAPPING, StringPromptTemplate
+from langchain.core.prompts.base import DEFAULT_FORMATTER_MAPPING, StringPromptTemplate
 from langchain.prompts.example_selector.base import BaseExampleSelector
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 class FewShotPromptWithTemplates(StringPromptTemplate):

langchain/prompts/loading.py

@@ -9,7 +9,7 @@ import yaml
 
 from langchain.output_parsers.regex import RegexParser
 from langchain.prompts.few_shot import FewShotPromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseLLMOutputParser, BasePromptTemplate, NoOpOutputParser
 from langchain.utilities.loading import try_load_from_hub
 

langchain/prompts/pipeline.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Tuple
 
 from pydantic import root_validator
 
-from langchain.prompts.chat import BaseChatPromptTemplate
+from langchain.core.prompts.chat import BaseChatPromptTemplate
 from langchain.schema import BasePromptTemplate, PromptValue
 
 

langchain/retrievers/multi_query.py

@@ -6,7 +6,7 @@ from pydantic import BaseModel, Field
 from langchain.chains.llm import LLMChain
 from langchain.llms.base import BaseLLM
 from langchain.output_parsers.pydantic import PydanticOutputParser
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseRetriever, Document
 from langchain.schema.callbacks.manager import (
     AsyncCallbackManagerForRetrieverRun,

tests/integration_tests/prompts/test_ngram_overlap_example_selector.py

@@ -6,7 +6,7 @@ from langchain.prompts.example_selector.ngram_overlap import (
     NGramOverlapExampleSelector,
     ngram_overlap_score,
 )
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLES = [
     {"input": "See Spot run.", "output": "foo1"},

tests/unit_tests/agents/test_react.py

@@ -7,7 +7,7 @@ from langchain.agents.tools import Tool
 from langchain.docstore.base import Docstore
 from langchain.docstore.document import Document
 from langchain.llms.fake import FakeListLLM
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import AgentAction
 
 _PAGE_CONTENT = """This is a page about LangChain.

tests/unit_tests/chains/test_conversation.py

@@ -5,7 +5,7 @@ from langchain.chains.conversation.base import ConversationChain
 from langchain.memory.buffer import ConversationBufferMemory
 from langchain.memory.buffer_window import ConversationBufferWindowMemory
 from langchain.memory.summary import ConversationSummaryMemory
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseMemory
 from tests.unit_tests.llms.fake_llm import FakeLLM
 

tests/unit_tests/chains/test_llm.py

@@ -7,7 +7,7 @@ import pytest
 
 from langchain.chains.llm import LLMChain
 from langchain.chains.loading import load_chain
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 from langchain.schema import BaseOutputParser
 from tests.unit_tests.llms.fake_llm import FakeLLM
 

tests/unit_tests/load/test_dump.py

@@ -10,8 +10,8 @@ from langchain.chat_models.openai import ChatOpenAI
 from langchain.llms.openai import OpenAI
 from langchain.load.dump import dumps
 from langchain.load.serializable import Serializable
-from langchain.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.chat import ChatPromptTemplate, HumanMessagePromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 class Person(Serializable):

tests/unit_tests/load/test_load.py

@@ -6,7 +6,7 @@ from langchain.chains.llm import LLMChain
 from langchain.llms.openai import OpenAI
 from langchain.load.dump import dumps
 from langchain.load.load import loads
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 class NotSerializable:

tests/unit_tests/prompts/test_chat.py

@@ -4,7 +4,7 @@ from typing import List
 import pytest
 
 from langchain.prompts import PromptTemplate
-from langchain.prompts.chat import (
+from langchain.core.prompts.chat import (
     AIMessagePromptTemplate,
     BaseMessagePromptTemplate,
     ChatMessagePromptTemplate,

tests/unit_tests/prompts/test_few_shot.py

@@ -4,7 +4,7 @@ from typing import Dict, List, Tuple
 import pytest
 
 from langchain.prompts.few_shot import FewShotPromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLE_PROMPT = PromptTemplate(
     input_variables=["question", "answer"], template="{question}: {answer}"

tests/unit_tests/prompts/test_few_shot_with_templates.py

@@ -1,7 +1,7 @@
 """Test few shot prompt template."""
 
 from langchain.prompts.few_shot_with_templates import FewShotPromptWithTemplates
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLE_PROMPT = PromptTemplate(
     input_variables=["question", "answer"], template="{question}: {answer}"

tests/unit_tests/prompts/test_length_based_example_selector.py

@@ -2,7 +2,7 @@
 import pytest
 
 from langchain.prompts.example_selector.length_based import LengthBasedExampleSelector
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLES = [
     {"question": "Question: who are you?\nAnswer: foo"},

tests/unit_tests/prompts/test_loading.py

@@ -7,7 +7,7 @@ from typing import Iterator
 from langchain.output_parsers import RegexParser
 from langchain.prompts.few_shot import FewShotPromptTemplate
 from langchain.prompts.loading import load_prompt
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 EXAMPLE_DIR = Path("tests/unit_tests/examples").absolute()
 

tests/unit_tests/prompts/test_pipeline_prompt.py

@@ -1,6 +1,6 @@
-from langchain.prompts.chat import ChatPromptTemplate, MessagesPlaceholder
+from langchain.core.prompts.chat import ChatPromptTemplate, MessagesPlaceholder
 from langchain.prompts.pipeline import PipelinePromptTemplate
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 def test_get_input_variables() -> None:

tests/unit_tests/prompts/test_prompt.py

@@ -1,7 +1,7 @@
 """Test functionality related to prompts."""
 import pytest
 
-from langchain.prompts.prompt import PromptTemplate
+from langchain.core.prompts.prompt import PromptTemplate
 
 
 def test_prompt_valid() -> None: