AI/ragflow
1
0
Fork 0
mirror of https://git.mirrors.martin98.com/https://github.com/infiniflow/ragflow.git synced 2025-08-15 00:45:57 +08:00
Code Issues Packages Projects Releases Wiki Activity

Fix FlagRerank max_length issue. (#5366)

Browse Source 
### What problem does this PR solve?

#5352

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
This commit is contained in:
Kevin Hu 2025-02-26 11:01:13 +08:00 committed by GitHub
parent 11e6d84d46
commit 4e2afcd3b8
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
2 changed files with 4 additions and 4 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

2
api/db/services/dialog_service.py
View File

@ -859,7 +859,7 @@ Output:
def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LLMBundle, def reasoning(chunk_info: dict, question: str, chat_mdl: LLMBundle, embd_mdl: LLMBundle,
tenant_ids: list[str], kb_ids: list[str], prompt_config, MAX_SEARCH_LIMIT: int = 3, tenant_ids: list[str], kb_ids: list[str], prompt_config, MAX_SEARCH_LIMIT: int = 6,
top_n: int = 5, similarity_threshold: float = 0.4, vector_similarity_weight: float = 0.3): top_n: int = 5, similarity_threshold: float = 0.4, vector_similarity_weight: float = 0.3):
BEGIN_SEARCH_QUERY = "<|begin_search_query|>" BEGIN_SEARCH_QUERY = "<|begin_search_query|>"
END_SEARCH_QUERY = "<|end_search_query|>" END_SEARCH_QUERY = "<|end_search_query|>"

4
rag/llm/rerank_model.py
View File

@ -131,10 +131,10 @@ class DefaultRerank(Base):
self._dynamic_batch_size = old_dynamic_batch_size self._dynamic_batch_size = old_dynamic_batch_size
return np.array(res) return np.array(res)
def _compute_batch_scores(self, batch_pairs, max_length=None): def _compute_batch_scores(self, batch_pairs, max_length=None):
if max_length is None: if max_length is None:
max_length = self._model.max_length scores = self._model.compute_score(batch_pairs)
else:
scores = self._model.compute_score(batch_pairs, max_length=max_length) scores = self._model.compute_score(batch_pairs, max_length=max_length)
scores = sigmoid(np.array(scores)).tolist() scores = sigmoid(np.array(scores)).tolist()
return scores return scores