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feat:document summary

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aries_ckt
2023-10-31 15:09:11 +08:00
parent 16dd8e3ef5
commit 523838fb79
1 changed files with 17 additions and 8 deletions
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25
pilot/server/knowledge/service.py
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@@ -429,14 +429,15 @@ class KnowledgeService:
from llama_index import PromptHelper
from llama_index.prompts.default_prompt_selectors import DEFAULT_TREE_SUMMARIZE_PROMPT_SEL
texts = [doc.page_content for doc in chunk_docs]
prompt_helper = PromptHelper()
prompt_helper = PromptHelper(context_window=5000)
texts = prompt_helper.repack(prompt=DEFAULT_TREE_SUMMARIZE_PROMPT_SEL, text_chunks=texts)
logger.info(
f"async_document_summary, doc:{doc.doc_name}, chunk_size:{len(texts)}, begin generate summary"
)
summary = self._llm_extract_summary(texts[0])
# summaries = self._mapreduce_extract_summary(texts)
outputs, summary = self._refine_extract_summary(texts[1:], summary)
logger.info(
f"async_document_summary, doc:{doc.doc_name}, chunk_size:{len(chunk_docs)}, begin embedding to graph store"
)
doc.summary = summary
return knowledge_document_dao.update_knowledge_document(doc)
@@ -525,14 +526,18 @@ class KnowledgeService:
ChatScene.ExtractSummary.value(), **{"chat_param": chat_param}
)
)
logger.info(
f"initialize summary is :{summary}"
)
return summary
def _refine_extract_summary(self, docs, summary: str):
def _refine_extract_summary(self, docs, summary: str, max_iteration:int = 5):
"""Extract refine summary by llm"""
from pilot.scene.base import ChatScene
from pilot.common.chat_util import llm_chat_response_nostream
import uuid
outputs = []
for doc in docs:
max_iteration = max_iteration if len(docs) > max_iteration else len(docs)
for doc in docs[0:max_iteration]:
chat_param = {
"chat_session_id": uuid.uuid1(),
"current_user_input": doc,
@@ -547,6 +552,9 @@ class KnowledgeService:
)
)
outputs.append(summary)
logger.info(
f"iterator is {len(outputs)} current summary is :{summary}"
)
return outputs, summary
def _mapreduce_extract_summary(self, docs):
@@ -567,7 +575,8 @@ class KnowledgeService:
ChatScene.ExtractSummary.value(), **{"chat_param": chat_param}
))
from pilot.common.chat_util import run_async_tasks
summaries = run_async_tasks(tasks)
summary_iters = run_async_tasks(tasks)
summary = self._llm_extract_summary(" ".join(summary_iters))
# from pilot.utils import utils
# loop = utils.get_or_create_event_loop()
# summary = loop.run_until_complete(
@@ -576,6 +585,6 @@ class KnowledgeService:
# )
# )
# outputs.append(summary)
return summaries
return summary