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from langchain.callbacks.base import BaseCallbackHandler | |
class StreamHandler(BaseCallbackHandler): | |
def __init__(self, container, initial_text: str = ""): | |
self.container = container | |
self.text = initial_text | |
self.run_id_ignore_token = None | |
def on_llm_start(self, serialized: dict, prompts: list, **kwargs): | |
# Workaround to prevent showing the rephrased question as output | |
if prompts[0].startswith("Human"): | |
self.run_id_ignore_token = kwargs.get("run_id") | |
def on_llm_new_token(self, token: str, **kwargs) -> None: | |
if self.run_id_ignore_token == kwargs.get("run_id", False): | |
return | |
self.text += token | |
self.container.markdown(self.text) | |
class PrintRetrievalHandler(BaseCallbackHandler): | |
def __init__(self, container): | |
self.status = container.status("**Thinking...**") | |
self.container = container | |
def on_retriever_start(self, serialized: dict, query: str, **kwargs): | |
self.status.write(f"**Checking document for query:** `{query}`. Please wait...") | |
def on_retriever_end(self, documents, **kwargs): | |
self.container.empty() | |