Merge pull request 'Change RetGenLangGraph to use streaming instead of invoking on the LLM' (#17) from reg_gen_stream into main

Reviewed-on: AI_team/generic-RAG-demo#17
This commit is contained in:
rubenl 2025-04-09 11:21:13 +02:00
commit 6ad6ac4a34
2 changed files with 27 additions and 26 deletions

View File

@ -98,9 +98,8 @@ async def process_response(message):
chainlit_response = cl.Message(content="")
response = graph.invoke(message.content, config=config)
await chainlit_response.stream_token(f"{response}\n")
async for response in graph.stream(message.content, config=config):
await chainlit_response.stream_token(response)
pdf_sources = graph.get_last_pdf_sources()
if len(pdf_sources) > 0:

View File

@ -1,9 +1,12 @@
import logging
from pathlib import Path
from typing import Any, Union
from typing import Any, AsyncGenerator
from langchain import hub
from langchain_chroma import Chroma
from langchain_core.documents import Document
from langchain_core.embeddings import Embeddings
from langchain_core.language_models.chat_models import BaseChatModel
from langgraph.checkpoint.memory import MemorySaver
from langgraph.graph import END, START, StateGraph
from typing_extensions import List, TypedDict
@ -19,7 +22,7 @@ class State(TypedDict):
class RetGenLangGraph:
def __init__(self, vector_store, chat_model, embedding_model):
def __init__(self, vector_store: Chroma, chat_model: BaseChatModel, embedding_model: Embeddings):
self.vector_store = vector_store
self.chat_model = chat_model
self.embedding_model = embedding_model
@ -32,21 +35,21 @@ class RetGenLangGraph:
graph_builder.add_edge("_generate", END)
self.graph = graph_builder.compile(memory)
self.last_invoke = None
self.last_retrieved_docs = []
def invoke(self, message: str, config: dict) -> Union[dict[str, Any], Any]:
self.last_invoke = self.graph.invoke({"question": message}, config=config)
return self.last_invoke["answer"]
async def stream(self, message: str, config: dict) -> AsyncGenerator[Any, Any]:
async for response, _ in self.graph.astream({"question": message}, stream_mode="messages", config=config):
yield response.content
def _retrieve(self, state: State) -> dict:
retrieved_docs = self.vector_store.similarity_search(state["question"])
return {"context": retrieved_docs}
self.last_retrieved_docs = self.vector_store.similarity_search(state["question"])
return {"context": self.last_retrieved_docs}
def _generate(self, state: State) -> dict:
async def _generate(self, state: State) -> AsyncGenerator[Any, Any]:
docs_content = "\n\n".join(doc.page_content for doc in state["context"])
messages = self.prompt.invoke({"question": state["question"], "context": docs_content})
response = self.chat_model.invoke(messages)
return {"answer": response.content}
messages = await self.prompt.ainvoke({"question": state["question"], "context": docs_content})
async for response in self.chat_model.astream(messages):
yield {"answer": response.content}
def get_last_pdf_sources(self) -> dict[str, list[int]]:
"""
@ -54,30 +57,30 @@ class RetGenLangGraph:
"""
pdf_sources = {}
if self.last_invoke is None:
if not self.last_retrieved_docs:
return pdf_sources
for context in self.last_invoke["context"]:
for doc in self.last_retrieved_docs:
try:
Path(context.metadata["source"]).suffix == ".pdf"
Path(doc.metadata["source"]).suffix == ".pdf"
except KeyError:
continue
else:
source = context.metadata["source"]
source = doc.metadata["source"]
if source not in pdf_sources:
pdf_sources[source] = set()
# The page numbers are in the `page_numer` and `page` fields.
try:
page_number = context.metadata["page_number"]
page_number = doc.metadata["page_number"]
except KeyError:
pass
else:
pdf_sources[source].add(page_number)
try:
page_number = context.metadata["page"]
page_number = doc.metadata["page"]
except KeyError:
pass
else:
@ -94,15 +97,14 @@ class RetGenLangGraph:
"""
web_sources = set()
if self.last_invoke is None:
if not self.last_retrieved_docs:
return web_sources
for context in self.last_invoke["context"]:
for doc in self.last_retrieved_docs:
try:
context.metadata["filetype"] == "web"
if doc.metadata["filetype"] == "web":
web_sources.add(doc.metadata["source"])
except KeyError:
continue
else:
web_sources.add(context.metadata["source"])
return web_sources