github/langchain
1
0
Fork 0
mirror of https://github.com/hwchase17/langchain.git synced 2025-08-11 05:45:01 +00:00
Code Issues Packages Projects Releases Wiki Activity

stop using chained input except in agent (#249)

Browse Source
This commit is contained in:
Harrison Chase 2022-12-03 14:15:56 -08:00 committed by GitHub
parent b5d8434a50
commit 9481a23314
No known key found for this signature in database
GPG Key ID: 4AEE18F83AFDEB23
3 changed files with 26 additions and 19 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

15
langchain/chains/llm_math/base.py
View File

@ -7,7 +7,7 @@ from langchain.chains.base import Chain
from langchain.chains.llm import LLMChain
from langchain.chains.llm_math.prompt import PROMPT
from langchain.chains.python import PythonChain
from langchain.input import ChainedInput
from langchain.input import print_text
from langchain.llms.base import LLM
@ -51,15 +51,18 @@ class LLMMathChain(Chain, BaseModel):
def _call(self, inputs: Dict[str, str]) -> Dict[str, str]:
llm_executor = LLMChain(prompt=PROMPT, llm=self.llm)
python_executor = PythonChain()
chained_input = ChainedInput(inputs[self.input_key], verbose=self.verbose)
t = llm_executor.predict(question=chained_input.input, stop=["```output"])
chained_input.add(t, color="green")
if self.verbose:
print_text(inputs[self.input_key])
t = llm_executor.predict(question=inputs[self.input_key], stop=["```output"])
if self.verbose:
print_text(t, color="green")
t = t.strip()
if t.startswith("```python"):
code = t[9:-4]
output = python_executor.run(code)
chained_input.add("\nAnswer: ")
chained_input.add(output, color="yellow")
if self.verbose:
print_text("\nAnswer: ")
print_text(output, color="yellow")
answer = "Answer: " + output
elif t.startswith("Answer:"):
answer = t

26
langchain/chains/sql_database/base.py
View File

@ -6,7 +6,7 @@ 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 ChainedInput
from langchain.input import print_text
from langchain.llms.base import LLM
from langchain.sql_database import SQLDatabase
@ -53,22 +53,26 @@ class SQLDatabaseChain(Chain, BaseModel):
def _call(self, inputs: Dict[str, str]) -> Dict[str, str]:
llm_chain = LLMChain(llm=self.llm, prompt=PROMPT)
chained_input = ChainedInput(
f"{inputs[self.input_key]} \nSQLQuery:", verbose=self.verbose
)
input_text = f"{inputs[self.input_key]} \nSQLQuery:"
if self.verbose:
print_text(input_text)
llm_inputs = {
"input": chained_input.input,
"input": input_text,
"dialect": self.database.dialect,
"table_info": self.database.table_info,
"stop": ["\nSQLResult:"],
}
sql_cmd = llm_chain.predict(**llm_inputs)
chained_input.add(sql_cmd, color="green")
if self.verbose:
print_text(sql_cmd, color="green")
result = self.database.run(sql_cmd)
chained_input.add("\nSQLResult: ")
chained_input.add(result, color="yellow")
chained_input.add("\nAnswer:")
llm_inputs["input"] = chained_input.input
if self.verbose:
print_text("\nSQLResult: ")
print_text(result, color="yellow")
print_text("\nAnswer:")
input_text += f"{sql_cmd}\nSQLResult: {result}\nAnswer:"
llm_inputs["input"] = input_text
final_result = llm_chain.predict(**llm_inputs)
chained_input.add(final_result, color="green")
if self.verbose:
print_text(final_result, color="green")
return {self.output_key: final_result}

4
langchain/input.py
View File

@ -36,13 +36,13 @@ class ChainedInput:
"""Initialize with verbose flag and initial text."""
self._verbose = verbose
if self._verbose:
print_text(text, None)
print_text(text, color=None)
self._input = text
def add(self, text: str, color: Optional[str] = None) -> None:
"""Add text to input, print if in verbose mode."""
if self._verbose:
print_text(text, color)
print_text(text, color=color)
self._input += text
@property