|
1 | | -import logging |
2 | 1 | import asyncio |
3 | | - |
4 | | -from dialog.llm.abstract_llm import AbstractLLM |
5 | | -from dialog.learn.idf import categorize_conversation_history |
6 | | -from dialog.llm.memory import generate_memory_instance |
7 | | -from dialog.llm.embeddings import get_most_relevant_contents_from_message |
| 2 | +import logging |
8 | 3 |
|
9 | 4 | from langchain.chains.llm import LLMChain |
10 | | -from langchain.memory.chat_memory import BaseChatMemory |
11 | | - |
12 | 5 | from langchain.chat_models import ChatOpenAI |
13 | 6 | from langchain.memory import ConversationBufferWindowMemory |
| 7 | +from langchain.memory.chat_memory import BaseChatMemory |
14 | 8 | from langchain.prompts import (ChatPromptTemplate, HumanMessagePromptTemplate, |
15 | 9 | MessagesPlaceholder, |
16 | 10 | SystemMessagePromptTemplate) |
17 | 11 |
|
18 | | -from dialog.settings import OPENAI_API_KEY |
| 12 | +from dialog.learn.idf import categorize_conversation_history |
| 13 | +from dialog.llm.abstract_llm import AbstractLLM |
| 14 | +from dialog.llm.embeddings import get_most_relevant_contents_from_message |
| 15 | +from dialog.llm.memory import generate_memory_instance |
| 16 | +from dialog.settings import OPENAI_API_KEY, VERBOSE_LLM |
19 | 17 |
|
20 | 18 |
|
21 | 19 | class DialogLLM(AbstractLLM): |
@@ -57,7 +55,8 @@ def generate_prompt(self, input): |
57 | 55 |
|
58 | 56 | question_text = self.config.get("prompt").get("question_signalizer") |
59 | 57 | prompt_templating.append(HumanMessagePromptTemplate.from_template(f"{question_text}" + ":\n{user_message}")) |
60 | | - |
| 58 | + if VERBOSE_LLM: |
| 59 | + logging.info(f"Verbose LLM prompt: {prompt_templating}") |
61 | 60 | self.prompt = ChatPromptTemplate(messages=prompt_templating) |
62 | 61 |
|
63 | 62 | @property |
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