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Fixed translate script part

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This commit is contained in:
Vasilije 2023-08-24 10:39:12 +02:00
parent 697c49a670
commit 2f85f6baff
1 changed files with 12 additions and 5 deletions
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17
level_2/level_2_pdf_vectorstore__dlt_contracts.py
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@ -655,7 +655,7 @@ class EpisodicBuffer:
#we just filter the data here
prompt_filter = ChatPromptTemplate.from_template(
"Filter and remove uneccessary information that is not relevant in the user query {query}")
"Filter and remove uneccessary information that is not relevant in the user query, keep it as original as possbile: {query}")
chain_filter = prompt_filter | self.llm
output = await chain_filter.ainvoke({"query": user_input})
@ -699,6 +699,7 @@ class EpisodicBuffer:
task_order: str = Field(..., description="The order at which the task needs to be performed")
task_name: str = Field(None, description="The task that needs to be performed")
operation: str = Field(None, description="The operation to be performed")
original_query: str = Field(None, description="Original user query provided")
class TaskList(BaseModel):
"""Schema for the record containing a list of tasks."""
@ -777,15 +778,15 @@ class EpisodicBuffer:
description="observation we want to translate"
)
@tool("translate_to_en", args_schema=TranslateText, return_direct=True)
def translate_to_en(observation, args_schema=TranslateText):
@tool("translate_to_de", args_schema=TranslateText, return_direct=True)
def translate_to_de(observation, args_schema=TranslateText):
"""Translate to English"""
out = GoogleTranslator(source='auto', target='en').translate(text=observation)
out = GoogleTranslator(source='auto', target='de').translate(text=observation)
return out
agent = initialize_agent(
llm=self.llm,
tools=[translate_to_en, convert_to_structured],
tools=[translate_to_de, convert_to_structured],
agent=AgentType.OPENAI_FUNCTIONS,
verbose=True,
@ -797,6 +798,10 @@ class EpisodicBuffer:
result_tasks.append(output)
print("HERE IS THE RESULT TASKS", str(result_tasks))
await self.encoding(str(result_tasks), self.namespace, params=params)
@ -827,6 +832,8 @@ class EpisodicBuffer:
_input = prompt.format_prompt(query=user_input, steps=str(tasks_list), buffer=buffer_result)
print("a few things to do like load episodic memory in a structured format")
return "a few things to do like load episodic memory in a structured format"
# output = self.llm(_input.to_string())