mirror of
https://github.com/infiniflow/ragflow.git
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Fix: tokenizer issue. (#11902)
#11786 ### Type of change - [x] Bug Fix (non-breaking change which fixes an issue)
This commit is contained in:
Kevin Hu
@ -313,7 +313,7 @@ async def retrieval_test():
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langs = req.get("cross_languages", [])
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user_id = current_user.id
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def _retrieval_sync():
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async def _retrieval():
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local_doc_ids = list(doc_ids) if doc_ids else []
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tenant_ids = []
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@ -323,7 +323,7 @@ async def retrieval_test():
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metas = DocumentService.get_meta_by_kbs(kb_ids)
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if meta_data_filter.get("method") == "auto":
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chat_mdl = LLMBundle(user_id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
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filters: dict = gen_meta_filter(chat_mdl, metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, metas, question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -333,7 +333,7 @@ async def retrieval_test():
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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chat_mdl = LLMBundle(user_id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -347,7 +347,7 @@ async def retrieval_test():
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metas = DocumentService.get_meta_by_kbs(kb_ids)
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if meta_data_filter.get("method") == "auto":
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chat_mdl = LLMBundle(user_id, LLMType.CHAT)
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filters: dict = gen_meta_filter(chat_mdl, metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, metas, question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -357,7 +357,7 @@ async def retrieval_test():
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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chat_mdl = LLMBundle(user_id, LLMType.CHAT)
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -384,7 +384,7 @@ async def retrieval_test():
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_question = question
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if langs:
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_question = cross_languages(kb.tenant_id, None, _question, langs)
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_question = await cross_languages(kb.tenant_id, None, _question, langs)
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embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
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@ -394,7 +394,7 @@ async def retrieval_test():
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if req.get("keyword", False):
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chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
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_question += keyword_extraction(chat_mdl, _question)
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_question += await keyword_extraction(chat_mdl, _question)
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labels = label_question(_question, [kb])
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ranks = settings.retriever.retrieval(_question, embd_mdl, tenant_ids, kb_ids, page, size,
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@ -421,7 +421,7 @@ async def retrieval_test():
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return get_json_result(data=ranks)
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try:
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return await asyncio.to_thread(_retrieval_sync)
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return await _retrieval()
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except Exception as e:
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if str(e).find("not_found") > 0:
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return get_json_result(data=False, message='No chunk found! Check the chunk status please!',
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@ -1549,11 +1549,11 @@ async def retrieval_test(tenant_id):
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rerank_mdl = LLMBundle(kb.tenant_id, LLMType.RERANK, llm_name=req["rerank_id"])
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if langs:
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question = cross_languages(kb.tenant_id, None, question, langs)
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question = await cross_languages(kb.tenant_id, None, question, langs)
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if req.get("keyword", False):
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chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
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question += keyword_extraction(chat_mdl, question)
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question += await keyword_extraction(chat_mdl, question)
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ranks = settings.retriever.retrieval(
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question,
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@ -33,6 +33,7 @@ from api.utils.web_utils import CONTENT_TYPE_MAP
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from common import settings
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from common.constants import RetCode
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@manager.route('/file/upload', methods=['POST']) # noqa: F821
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@token_required
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async def upload(tenant_id):
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@ -13,7 +13,6 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import asyncio
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import json
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import re
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import time
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@ -44,6 +43,7 @@ from rag.prompts.generator import cross_languages, gen_meta_filter, keyword_extr
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from common.constants import RetCode, LLMType, StatusEnum
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from common import settings
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@manager.route("/chats/<chat_id>/sessions", methods=["POST"]) # noqa: F821
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@token_required
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async def create(tenant_id, chat_id):
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@ -969,7 +969,7 @@ async def retrieval_test_embedded():
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if not tenant_id:
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return get_error_data_result(message="permission denined.")
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def _retrieval_sync():
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async def _retrieval():
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local_doc_ids = list(doc_ids) if doc_ids else []
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tenant_ids = []
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_question = question
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@ -980,7 +980,7 @@ async def retrieval_test_embedded():
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metas = DocumentService.get_meta_by_kbs(kb_ids)
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if meta_data_filter.get("method") == "auto":
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chat_mdl = LLMBundle(tenant_id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
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filters: dict = gen_meta_filter(chat_mdl, metas, _question)
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filters: dict = await gen_meta_filter(chat_mdl, metas, _question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -990,7 +990,7 @@ async def retrieval_test_embedded():
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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chat_mdl = LLMBundle(tenant_id, LLMType.CHAT, llm_name=search_config.get("chat_id", ""))
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, _question)
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, _question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -1004,7 +1004,7 @@ async def retrieval_test_embedded():
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metas = DocumentService.get_meta_by_kbs(kb_ids)
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if meta_data_filter.get("method") == "auto":
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chat_mdl = LLMBundle(tenant_id, LLMType.CHAT)
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filters: dict = gen_meta_filter(chat_mdl, metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, metas, question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -1014,7 +1014,7 @@ async def retrieval_test_embedded():
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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chat_mdl = LLMBundle(tenant_id, LLMType.CHAT)
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, question)
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local_doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not local_doc_ids:
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local_doc_ids = None
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@ -1038,7 +1038,7 @@ async def retrieval_test_embedded():
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return get_error_data_result(message="Knowledgebase not found!")
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if langs:
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_question = cross_languages(kb.tenant_id, None, _question, langs)
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_question = await cross_languages(kb.tenant_id, None, _question, langs)
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embd_mdl = LLMBundle(kb.tenant_id, LLMType.EMBEDDING.value, llm_name=kb.embd_id)
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@ -1048,7 +1048,7 @@ async def retrieval_test_embedded():
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if req.get("keyword", False):
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chat_mdl = LLMBundle(kb.tenant_id, LLMType.CHAT)
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_question += keyword_extraction(chat_mdl, _question)
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_question += await keyword_extraction(chat_mdl, _question)
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labels = label_question(_question, [kb])
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ranks = settings.retriever.retrieval(
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@ -1068,7 +1068,7 @@ async def retrieval_test_embedded():
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return get_json_result(data=ranks)
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try:
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return await asyncio.to_thread(_retrieval_sync)
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return await _retrieval()
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except Exception as e:
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if str(e).find("not_found") > 0:
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return get_json_result(data=False, message="No chunk found! Check the chunk status please!",
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@ -13,6 +13,7 @@
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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import asyncio
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import logging
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import json
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import os
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@ -76,8 +77,7 @@ def init_superuser(nickname=DEFAULT_SUPERUSER_NICKNAME, email=DEFAULT_SUPERUSER_
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f"Super user initialized. email: {email},A default password has been set; changing the password after login is strongly recommended.")
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chat_mdl = LLMBundle(tenant["id"], LLMType.CHAT, tenant["llm_id"])
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msg = chat_mdl.chat(system="", history=[
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{"role": "user", "content": "Hello!"}], gen_conf={})
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msg = asyncio.run(chat_mdl.async_chat(system="", history=[{"role": "user", "content": "Hello!"}], gen_conf={}))
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if msg.find("ERROR: ") == 0:
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logging.error(
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"'{}' doesn't work. {}".format(
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@ -397,7 +397,7 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
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# try to use sql if field mapping is good to go
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if field_map:
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logging.debug("Use SQL to retrieval:{}".format(questions[-1]))
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ans = use_sql(questions[-1], field_map, dialog.tenant_id, chat_mdl, prompt_config.get("quote", True), dialog.kb_ids)
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ans = await use_sql(questions[-1], field_map, dialog.tenant_id, chat_mdl, prompt_config.get("quote", True), dialog.kb_ids)
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if ans:
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yield ans
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return
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@ -411,17 +411,17 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
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prompt_config["system"] = prompt_config["system"].replace("{%s}" % p["key"], " ")
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if len(questions) > 1 and prompt_config.get("refine_multiturn"):
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questions = [full_question(dialog.tenant_id, dialog.llm_id, messages)]
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questions = [await full_question(dialog.tenant_id, dialog.llm_id, messages)]
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else:
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questions = questions[-1:]
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if prompt_config.get("cross_languages"):
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questions = [cross_languages(dialog.tenant_id, dialog.llm_id, questions[0], prompt_config["cross_languages"])]
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questions = [await cross_languages(dialog.tenant_id, dialog.llm_id, questions[0], prompt_config["cross_languages"])]
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if dialog.meta_data_filter:
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metas = DocumentService.get_meta_by_kbs(dialog.kb_ids)
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if dialog.meta_data_filter.get("method") == "auto":
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filters: dict = gen_meta_filter(chat_mdl, metas, questions[-1])
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filters: dict = await gen_meta_filter(chat_mdl, metas, questions[-1])
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attachments.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not attachments:
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attachments = None
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@ -430,7 +430,7 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
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if selected_keys:
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, questions[-1])
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, questions[-1])
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attachments.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not attachments:
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attachments = None
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@ -441,7 +441,7 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
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attachments = ["-999"]
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if prompt_config.get("keyword", False):
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questions[-1] += keyword_extraction(chat_mdl, questions[-1])
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questions[-1] += await keyword_extraction(chat_mdl, questions[-1])
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refine_question_ts = timer()
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@ -469,7 +469,7 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
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),
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)
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for think in reasoner.thinking(kbinfos, attachments_ + " ".join(questions)):
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async for think in reasoner.thinking(kbinfos, attachments_ + " ".join(questions)):
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if isinstance(think, str):
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thought = think
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knowledges = [t for t in think.split("\n") if t]
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@ -646,7 +646,7 @@ async def async_chat(dialog, messages, stream=True, **kwargs):
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return
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def use_sql(question, field_map, tenant_id, chat_mdl, quota=True, kb_ids=None):
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async def use_sql(question, field_map, tenant_id, chat_mdl, quota=True, kb_ids=None):
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sys_prompt = """
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You are a Database Administrator. You need to check the fields of the following tables based on the user's list of questions and write the SQL corresponding to the last question.
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Ensure that:
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@ -664,9 +664,9 @@ Please write the SQL, only SQL, without any other explanations or text.
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""".format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question)
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tried_times = 0
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def get_table():
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async def get_table():
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nonlocal sys_prompt, user_prompt, question, tried_times
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sql = chat_mdl.chat(sys_prompt, [{"role": "user", "content": user_prompt}], {"temperature": 0.06})
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sql = await chat_mdl.async_chat(sys_prompt, [{"role": "user", "content": user_prompt}], {"temperature": 0.06})
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sql = re.sub(r"^.*</think>", "", sql, flags=re.DOTALL)
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logging.debug(f"{question} ==> {user_prompt} get SQL: {sql}")
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sql = re.sub(r"[\r\n]+", " ", sql.lower())
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@ -705,7 +705,7 @@ Please write the SQL, only SQL, without any other explanations or text.
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return settings.retriever.sql_retrieval(sql, format="json"), sql
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try:
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tbl, sql = get_table()
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tbl, sql = await get_table()
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except Exception as e:
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user_prompt = """
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Table name: {};
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@ -723,7 +723,7 @@ Please write the SQL, only SQL, without any other explanations or text.
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Please correct the error and write SQL again, only SQL, without any other explanations or text.
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""".format(index_name(tenant_id), "\n".join([f"{k}: {v}" for k, v in field_map.items()]), question, e)
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try:
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tbl, sql = get_table()
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tbl, sql = await get_table()
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except Exception:
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return
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@ -839,7 +839,7 @@ async def async_ask(question, kb_ids, tenant_id, chat_llm_name=None, search_conf
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if meta_data_filter:
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metas = DocumentService.get_meta_by_kbs(kb_ids)
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if meta_data_filter.get("method") == "auto":
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filters: dict = gen_meta_filter(chat_mdl, metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, metas, question)
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doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not doc_ids:
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doc_ids = None
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@ -848,7 +848,7 @@ async def async_ask(question, kb_ids, tenant_id, chat_llm_name=None, search_conf
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if selected_keys:
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, question)
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doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not doc_ids:
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doc_ids = None
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@ -923,7 +923,7 @@ async def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
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if meta_data_filter:
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metas = DocumentService.get_meta_by_kbs(kb_ids)
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if meta_data_filter.get("method") == "auto":
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filters: dict = gen_meta_filter(chat_mdl, metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, metas, question)
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doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not doc_ids:
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doc_ids = None
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@ -932,7 +932,7 @@ async def gen_mindmap(question, kb_ids, tenant_id, search_config={}):
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if selected_keys:
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filtered_metas = {key: metas[key] for key in selected_keys if key in metas}
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if filtered_metas:
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filters: dict = gen_meta_filter(chat_mdl, filtered_metas, question)
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filters: dict = await gen_meta_filter(chat_mdl, filtered_metas, question)
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doc_ids.extend(meta_filter(metas, filters["conditions"], filters.get("logic", "and")))
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if not doc_ids:
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doc_ids = None
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@ -318,9 +318,6 @@ class LLMBundle(LLM4Tenant):
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return value
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raise value
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def chat(self, system: str, history: list, gen_conf: dict = {}, **kwargs) -> str:
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return self._run_coroutine_sync(self.async_chat(system, history, gen_conf, **kwargs))
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def _sync_from_async_stream(self, async_gen_fn, *args, **kwargs):
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result_queue: queue.Queue = queue.Queue()
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@ -350,23 +347,6 @@ class LLMBundle(LLM4Tenant):
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raise item
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yield item
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|
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def chat_streamly(self, system: str, history: list, gen_conf: dict = {}, **kwargs):
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ans = ""
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||||
for txt in self._sync_from_async_stream(self.async_chat_streamly, system, history, gen_conf, **kwargs):
|
||||
if isinstance(txt, int):
|
||||
break
|
||||
|
||||
if txt.endswith("</think>"):
|
||||
ans = txt[: -len("</think>")]
|
||||
continue
|
||||
|
||||
if not self.verbose_tool_use:
|
||||
txt = re.sub(r"<tool_call>.*?</tool_call>", "", txt, flags=re.DOTALL)
|
||||
|
||||
# cancatination has beend done in async_chat_streamly
|
||||
ans = txt
|
||||
yield ans
|
||||
|
||||
def _bridge_sync_stream(self, gen):
|
||||
loop = asyncio.get_running_loop()
|
||||
queue: asyncio.Queue = asyncio.Queue()
|
||||
|
||||
Reference in New Issue
Block a user