Harrison/get rid of prints (#490)

deprecate all prints in favor of callback_manager.on_text (open to
better naming)
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Harrison Chase 2022-12-30 13:55:30 -05:00 committed by GitHub
parent b902bddb8a
commit 175a248506
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11 changed files with 35 additions and 34 deletions

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@ -218,7 +218,7 @@ class AgentExecutor(Chain, BaseModel):
# If the tool chosen is the finishing tool, then we end and return.
if isinstance(output, AgentFinish):
if self.verbose:
self.callback_manager.on_agent_end(output.log, color="green")
self.callback_manager.on_text(output.log, color="green")
final_output = output.return_values
if self.return_intermediate_steps:
final_output["intermediate_steps"] = intermediate_steps

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@ -55,7 +55,7 @@ class BaseCallbackHandler(ABC):
"""Run when tool errors."""
@abstractmethod
def on_agent_end(self, log: str, **kwargs: Any) -> None:
def on_text(self, text: str, **kwargs: Any) -> None:
"""Run when agent ends."""
@ -132,10 +132,10 @@ class CallbackManager(BaseCallbackManager):
for handler in self.handlers:
handler.on_tool_error(error)
def on_agent_end(self, log: str, **kwargs: Any) -> None:
def on_text(self, text: str, **kwargs: Any) -> None:
"""Run when agent ends."""
for handler in self.handlers:
handler.on_agent_end(log, **kwargs)
handler.on_text(text, **kwargs)
def add_handler(self, handler: BaseCallbackHandler) -> None:
"""Add a handler to the callback manager."""

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@ -88,10 +88,10 @@ class SharedCallbackManager(Singleton, BaseCallbackManager):
with self._lock:
self._callback_manager.on_tool_error(error)
def on_agent_end(self, log: str, **kwargs: Any) -> None:
def on_text(self, text: str, **kwargs: Any) -> None:
"""Run when agent ends."""
with self._lock:
self._callback_manager.on_agent_end(log, **kwargs)
self._callback_manager.on_text(text, **kwargs)
def add_handler(self, callback: BaseCallbackHandler) -> None:
"""Add a callback to the callback manager."""

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@ -67,8 +67,12 @@ class StdOutCallbackHandler(BaseCallbackHandler):
"""Do nothing."""
pass
def on_agent_end(
self, log: str, color: Optional[str] = None, **kwargs: Any
def on_text(
self,
text: str,
color: Optional[str] = None,
end: str = "",
**kwargs: Optional[str],
) -> None:
"""Run when agent ends."""
print_text(log, color=color)
print_text(text, color=color, end=end)

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@ -8,7 +8,6 @@ from pydantic import BaseModel, root_validator
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.input import print_text
from langchain.llms.base import BaseLLM
from langchain.requests import RequestsWrapper
@ -67,10 +66,10 @@ class APIChain(Chain, BaseModel):
question=question, api_docs=self.api_docs
)
if self.verbose:
print_text(api_url, color="green", end="\n")
self.callback_manager.on_text(api_url, color="green", end="\n")
api_response = self.requests_wrapper.run(api_url)
if self.verbose:
print_text(api_response, color="yellow", end="\n")
self.callback_manager.on_text(api_response, color="yellow", end="\n")
answer = self.api_answer_chain.predict(
question=question,
api_docs=self.api_docs,

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@ -6,7 +6,6 @@ from pydantic import BaseModel, Extra
from langchain.chains.base import Chain
from langchain.chains.llm import LLMChain
from langchain.chains.llm_bash.prompt import PROMPT
from langchain.input import print_text
from langchain.llms.base import BaseLLM
from langchain.utilities.bash import BashProcess
@ -52,11 +51,11 @@ class LLMBashChain(Chain, BaseModel):
llm_executor = LLMChain(prompt=PROMPT, llm=self.llm)
bash_executor = BashProcess()
if self.verbose:
print_text(inputs[self.input_key])
self.callback_manager.on_text(inputs[self.input_key])
t = llm_executor.predict(question=inputs[self.input_key])
if self.verbose:
print_text(t, color="green")
self.callback_manager.on_text(t, color="green")
t = t.strip()
if t.startswith("```bash"):
@ -69,8 +68,8 @@ class LLMBashChain(Chain, BaseModel):
output = bash_executor.run(command_list)
if self.verbose:
print_text("\nAnswer: ")
print_text(output, color="yellow")
self.callback_manager.on_text("\nAnswer: ")
self.callback_manager.on_text(output, color="yellow")
else:
raise ValueError(f"unknown format from LLM: {t}")

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@ -6,7 +6,6 @@ from pydantic import BaseModel, Extra
from langchain.chains.base import Chain
from langchain.chains.llm import LLMChain
from langchain.chains.llm_math.prompt import PROMPT
from langchain.input import print_text
from langchain.llms.base import BaseLLM
from langchain.python import PythonREPL
@ -52,17 +51,17 @@ class LLMMathChain(Chain, BaseModel):
llm_executor = LLMChain(prompt=PROMPT, llm=self.llm)
python_executor = PythonREPL()
if self.verbose:
print_text(inputs[self.input_key])
self.callback_manager.on_text(inputs[self.input_key])
t = llm_executor.predict(question=inputs[self.input_key], stop=["```output"])
if self.verbose:
print_text(t, color="green")
self.callback_manager.on_text(t, color="green")
t = t.strip()
if t.startswith("```python"):
code = t[9:-4]
output = python_executor.run(code)
if self.verbose:
print_text("\nAnswer: ")
print_text(output, color="yellow")
self.callback_manager.on_text("\nAnswer: ")
self.callback_manager.on_text(output, color="yellow")
answer = "Answer: " + output
elif t.startswith("Answer:"):
answer = t

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@ -12,7 +12,6 @@ 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.input import print_text
from langchain.llms.base import BaseLLM
from langchain.prompts.base import BasePromptTemplate
from langchain.python import PythonREPL
@ -53,7 +52,7 @@ class PALChain(Chain, BaseModel):
llm_chain = LLMChain(llm=self.llm, prompt=self.prompt)
code = llm_chain.predict(stop=[self.stop], **inputs)
if self.verbose:
print_text(code, color="green", end="\n")
self.callback_manager.on_text(code, color="green", end="\n")
repl = PythonREPL()
res = repl.run(code + f"\n{self.get_answer_expr}")
return {self.output_key: res.strip()}

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@ -5,7 +5,7 @@ from typing import Dict, List
from pydantic import BaseModel, Extra, root_validator
from langchain.chains.base import Chain
from langchain.input import get_color_mapping, print_text
from langchain.input import get_color_mapping
class SequentialChain(Chain, BaseModel):
@ -133,5 +133,7 @@ class SimpleSequentialChain(Chain, BaseModel):
if self.strip_outputs:
_input = _input.strip()
if self.verbose:
print_text(_input, color=color_mapping[str(i)], end="\n")
self.callback_manager.on_text(
_input, color=color_mapping[str(i)], end="\n"
)
return {self.output_key: _input}

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@ -6,7 +6,6 @@ from pydantic import BaseModel, Extra
from langchain.chains.base import Chain
from langchain.chains.llm import LLMChain
from langchain.chains.sql_database.prompt import PROMPT
from langchain.input import print_text
from langchain.llms.base import BaseLLM
from langchain.sql_database import SQLDatabase
@ -55,7 +54,7 @@ class SQLDatabaseChain(Chain, BaseModel):
llm_chain = LLMChain(llm=self.llm, prompt=PROMPT)
input_text = f"{inputs[self.input_key]} \nSQLQuery:"
if self.verbose:
print_text(input_text)
self.callback_manager.on_text(input_text)
llm_inputs = {
"input": input_text,
"dialect": self.database.dialect,
@ -64,15 +63,15 @@ class SQLDatabaseChain(Chain, BaseModel):
}
sql_cmd = llm_chain.predict(**llm_inputs)
if self.verbose:
print_text(sql_cmd, color="green")
self.callback_manager.on_text(sql_cmd, color="green")
result = self.database.run(sql_cmd)
if self.verbose:
print_text("\nSQLResult: ")
print_text(result, color="yellow")
print_text("\nAnswer:")
self.callback_manager.on_text("\nSQLResult: ")
self.callback_manager.on_text(result, color="yellow")
self.callback_manager.on_text("\nAnswer:")
input_text += f"{sql_cmd}\nSQLResult: {result}\nAnswer:"
llm_inputs["input"] = input_text
final_result = llm_chain.predict(**llm_inputs)
if self.verbose:
print_text(final_result, color="green")
self.callback_manager.on_text(final_result, color="green")
return {self.output_key: final_result}

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@ -59,6 +59,6 @@ class FakeCallbackHandler(BaseCallbackHandler):
"""Run when tool errors."""
self.errors += 1
def on_agent_end(self, log: str, **kwargs: Any) -> None:
def on_text(self, text: str, **kwargs: Any) -> None:
"""Run when agent is ending."""
self.ends += 1