Tru Chain

Langchain instrumentation and monitoring.

TruChain

Bases: App

Instantiates the Langchain Wrapper.

Usage:

Langchain Code: Langchain Quickstart

 # Code snippet taken from langchain 0.0.281 (API subject to change with new versions)
from langchain.chains import LLMChain
from langchain.llms import OpenAI
from langchain.prompts.chat import ChatPromptTemplate
from langchain.prompts.chat import HumanMessagePromptTemplate
from langchain.prompts.chat import PromptTemplate

full_prompt = HumanMessagePromptTemplate(
    prompt=PromptTemplate(
        template=
        "Provide a helpful response with relevant background information for the following: {prompt}",
        input_variables=["prompt"],
    )
)

chat_prompt_template = ChatPromptTemplate.from_messages([full_prompt])

llm = OpenAI(temperature=0.9, max_tokens=128)

chain = LLMChain(llm=llm, prompt=chat_prompt_template, verbose=True)

Trulens Eval Code:

from trulens_eval import TruChain
# f_lang_match, f_qa_relevance, f_qs_relevance are feedback functions
tru_recorder = TruChain(
    chain,
    app_id='Chain1_ChatApplication',
    feedbacks=[f_lang_match, f_qa_relevance, f_qs_relevance])
)
with tru_recorder as recording:
    chain(""What is langchain?")

tru_record = recording.records[0]

# To add record metadata 
with tru_recorder as recording:
    recording.record_metadata="this is metadata for all records in this context that follow this line"
    chain("What is langchain?")
    recording.record_metadata="this is different metadata for all records in this context that follow this line"
    chain("Where do I download langchain?")

See Feedback Functions for instantiating feedback functions.

Parameters:

Name	Type	Description	Default
app	Chain	A langchain application.	required

Source code in trulens_eval/trulens_eval/tru_chain.py

class TruChain(App):
    """Instantiates the Langchain Wrapper.

        **Usage:**

        Langchain Code: [Langchain Quickstart](https://python.langchain.com/docs/get_started/quickstart)
        ```
         # Code snippet taken from langchain 0.0.281 (API subject to change with new versions)
        from langchain.chains import LLMChain
        from langchain.llms import OpenAI
        from langchain.prompts.chat import ChatPromptTemplate
        from langchain.prompts.chat import HumanMessagePromptTemplate
        from langchain.prompts.chat import PromptTemplate

        full_prompt = HumanMessagePromptTemplate(
            prompt=PromptTemplate(
                template=
                "Provide a helpful response with relevant background information for the following: {prompt}",
                input_variables=["prompt"],
            )
        )

        chat_prompt_template = ChatPromptTemplate.from_messages([full_prompt])

        llm = OpenAI(temperature=0.9, max_tokens=128)

        chain = LLMChain(llm=llm, prompt=chat_prompt_template, verbose=True)

        ```

        Trulens Eval Code:
        ```

        from trulens_eval import TruChain
        # f_lang_match, f_qa_relevance, f_qs_relevance are feedback functions
        tru_recorder = TruChain(
            chain,
            app_id='Chain1_ChatApplication',
            feedbacks=[f_lang_match, f_qa_relevance, f_qs_relevance])
        )
        with tru_recorder as recording:
            chain(""What is langchain?")

        tru_record = recording.records[0]

        # To add record metadata 
        with tru_recorder as recording:
            recording.record_metadata="this is metadata for all records in this context that follow this line"
            chain("What is langchain?")
            recording.record_metadata="this is different metadata for all records in this context that follow this line"
            chain("Where do I download langchain?")
        ```
        See [Feedback Functions](https://www.trulens.org/trulens_eval/api/feedback/) for instantiating feedback functions.

        Args:
            app (Chain): A langchain application.
    """

    app: Chain

    # TODO: what if _acall is being used instead?
    root_callable: ClassVar[FunctionOrMethod] = Field(
        default_factory=lambda: FunctionOrMethod.of_callable(TruChain._call),
        const=True
    )

    # Normally pydantic does not like positional args but chain here is
    # important enough to make an exception.
    def __init__(self, app: Chain, **kwargs):
        """
        Wrap a langchain chain for monitoring.

        Arguments:
        - app: Chain -- the chain to wrap.
        - More args in App
        - More args in AppDefinition
        - More args in WithClassInfo
        """

        super().update_forward_refs()

        # TruChain specific:
        kwargs['app'] = app
        kwargs['root_class'] = Class.of_object(app)
        kwargs['instrument'] = LangChainInstrument(app=self)

        super().__init__(**kwargs)

        self.post_init()

    # TODEP
    # Chain requirement
    @property
    def _chain_type(self):
        return "TruChain"

    # TODEP
    # Chain requirement
    @property
    def input_keys(self) -> List[str]:
        return self.app.input_keys

    # TODEP
    # Chain requirement
    @property
    def output_keys(self) -> List[str]:
        return self.app.output_keys

    def main_input(
        self, func: Callable, sig: Signature, bindings: BoundArguments
    ) -> str:
        """
        Determine the main input string for the given function `func` with
        signature `sig` if it is to be called with the given bindings
        `bindings`.
        """

        if 'inputs' in bindings.arguments:
            # langchain specific:
            ins = self.app.prep_inputs(bindings.arguments['inputs'])

            if len(self.app.input_keys) == 0:
                logger.warning(
                    "langchain app has no inputs. `main_input` will be `None`."
                )
                return None

            return ins[self.app.input_keys[0]]

        return App.main_input(self, func, sig, bindings)

    def main_output(
        self, func: Callable, sig: Signature, bindings: BoundArguments, ret: Any
    ) -> str:
        """
        Determine the main out string for the given function `func` with
        signature `sig` after it is called with the given `bindings` and has
        returned `ret`.
        """

        if isinstance(ret, Dict):
            # langchain specific:
            if self.app.output_keys[0] in ret:
                return ret[self.app.output_keys[0]]

        return App.main_output(self, func, sig, bindings, ret)

    def main_call(self, human: str):
        # If available, a single text to a single text invocation of this app.

        out_key = self.app.output_keys[0]

        return self.app(human)[out_key]

    async def main_acall(self, human: str):
        # If available, a single text to a single text invocation of this app.

        out_key = self.app.output_keys[0]

        return await self._acall(human)[out_key]

    def __getattr__(self, __name: str) -> Any:
        # A message for cases where a user calls something that the wrapped
        # chain has but we do not wrap yet.

        if safe_hasattr(self.app, __name):
            return RuntimeError(
                f"TruChain has no attribute {__name} but the wrapped app ({type(self.app)}) does. ",
                f"If you are calling a {type(self.app)} method, retrieve it from that app instead of from `TruChain`. "
                f"TruChain presently only wraps Chain.__call__, Chain._call, and Chain._acall ."
            )
        else:
            raise RuntimeError(f"TruChain has no attribute named {__name}.")

    # NOTE: Input signature compatible with langchain.chains.base.Chain.acall
    # TODEP
    async def acall_with_record(self, *args, **kwargs) -> Tuple[Any, Record]:
        """
        Run the chain acall method and also return a record metadata object.
        """

        self._with_dep_message(method="acall", is_async=True, with_record=True)

        return await self.awith_record(self.app.acall, *args, **kwargs)

    # NOTE: Input signature compatible with langchain.chains.base.Chain.__call__
    # TODEP
    def call_with_record(self, *args, **kwargs) -> Tuple[Any, Record]:
        """
        Run the chain call method and also return a record metadata object.
        """

        self._with_dep_message(
            method="__call__", is_async=False, with_record=True
        )

        return self.with_record(self.app.__call__, *args, **kwargs)

    # TODEP
    # Mimics Chain
    def __call__(self, *args, **kwargs) -> Dict[str, Any]:
        """
        Wrapped call to self.app._call with instrumentation. If you need to
        get the record, use `call_with_record` instead. 
        """

        self._with_dep_message(
            method="__call__", is_async=False, with_record=False
        )

        return self.with_(self.app, *args, **kwargs)

    # TODEP
    # Chain requirement
    def _call(self, *args, **kwargs) -> Any:

        self._with_dep_message(
            method="_call", is_async=False, with_record=False
        )

        ret, _ = self.with_(self.app._call, *args, **kwargs)

        return ret

    # TODEP
    # Optional Chain requirement
    async def _acall(self, *args, **kwargs) -> Any:

        self._with_dep_message(
            method="_acall", is_async=True, with_record=False
        )

        ret, _ = await self.awith_(self.app.acall, *args, **kwargs)

        return ret

__call__(*args, **kwargs)

Wrapped call to self.app._call with instrumentation. If you need to get the record, use call_with_record instead.

Source code in trulens_eval/trulens_eval/tru_chain.py

def __call__(self, *args, **kwargs) -> Dict[str, Any]:
    """
    Wrapped call to self.app._call with instrumentation. If you need to
    get the record, use `call_with_record` instead. 
    """

    self._with_dep_message(
        method="__call__", is_async=False, with_record=False
    )

    return self.with_(self.app, *args, **kwargs)

__init__(app, **kwargs)

Wrap a langchain chain for monitoring.

• app: Chain -- the chain to wrap.
• More args in App
• More args in AppDefinition
• More args in WithClassInfo

Source code in trulens_eval/trulens_eval/tru_chain.py

def __init__(self, app: Chain, **kwargs):
    """
    Wrap a langchain chain for monitoring.

    Arguments:
    - app: Chain -- the chain to wrap.
    - More args in App
    - More args in AppDefinition
    - More args in WithClassInfo
    """

    super().update_forward_refs()

    # TruChain specific:
    kwargs['app'] = app
    kwargs['root_class'] = Class.of_object(app)
    kwargs['instrument'] = LangChainInstrument(app=self)

    super().__init__(**kwargs)

    self.post_init()

acall_with_record(*args, **kwargs) async

Run the chain acall method and also return a record metadata object.

Source code in trulens_eval/trulens_eval/tru_chain.py

async def acall_with_record(self, *args, **kwargs) -> Tuple[Any, Record]:
    """
    Run the chain acall method and also return a record metadata object.
    """

    self._with_dep_message(method="acall", is_async=True, with_record=True)

    return await self.awith_record(self.app.acall, *args, **kwargs)

call_with_record(*args, **kwargs)

Run the chain call method and also return a record metadata object.

Source code in trulens_eval/trulens_eval/tru_chain.py

def call_with_record(self, *args, **kwargs) -> Tuple[Any, Record]:
    """
    Run the chain call method and also return a record metadata object.
    """

    self._with_dep_message(
        method="__call__", is_async=False, with_record=True
    )

    return self.with_record(self.app.__call__, *args, **kwargs)

main_input(func, sig, bindings)

Determine the main input string for the given function func with signature sig if it is to be called with the given bindings bindings.

Source code in trulens_eval/trulens_eval/tru_chain.py

def main_input(
    self, func: Callable, sig: Signature, bindings: BoundArguments
) -> str:
    """
    Determine the main input string for the given function `func` with
    signature `sig` if it is to be called with the given bindings
    `bindings`.
    """

    if 'inputs' in bindings.arguments:
        # langchain specific:
        ins = self.app.prep_inputs(bindings.arguments['inputs'])

        if len(self.app.input_keys) == 0:
            logger.warning(
                "langchain app has no inputs. `main_input` will be `None`."
            )
            return None

        return ins[self.app.input_keys[0]]

    return App.main_input(self, func, sig, bindings)

main_output(func, sig, bindings, ret)

Determine the main out string for the given function func with signature sig after it is called with the given bindings and has returned ret.

Source code in trulens_eval/trulens_eval/tru_chain.py

def main_output(
    self, func: Callable, sig: Signature, bindings: BoundArguments, ret: Any
) -> str:
    """
    Determine the main out string for the given function `func` with
    signature `sig` after it is called with the given `bindings` and has
    returned `ret`.
    """

    if isinstance(ret, Dict):
        # langchain specific:
        if self.app.output_keys[0] in ret:
            return ret[self.app.output_keys[0]]

    return App.main_output(self, func, sig, bindings, ret)