diff --git a/api/apps/conversation_app.py b/api/apps/conversation_app.py
index 648ecd3d91d3ee5849eb564093b11b97572e6baf..9ee201f9043b47fdfe6f3203132cceacffe3e01b 100644
--- a/api/apps/conversation_app.py
+++ b/api/apps/conversation_app.py
@@ -309,13 +309,13 @@ def use_sql(question, field_map, tenant_id, chat_mdl):
# compose markdown table
clmns = "|"+"|".join([re.sub(r"(/.*|ďĽ[^ďĽďĽ‰]+）)", "", field_map.get(tbl["columns"][i]["name"], tbl["columns"][i]["name"])) for i in clmn_idx]) + ("|原文|" if docid_idx and docid_idx else "|")
line = "|"+"|".join(["------" for _ in range(len(clmn_idx))]) + ("|------|" if docid_idx and docid_idx else "")
- line = re.sub(r"T[0-9]{2}:[0-9]{2}:[0-9]{2}\|", "|", line)
rows = ["|"+"|".join([rmSpace(str(r[i])) for i in clmn_idx]).replace("None", " ") + "|" for r in tbl["rows"]]
if not docid_idx or not docnm_idx:
chat_logger.warning("SQL missing field: " + sql)
return "\n".join([clmns, line, "\n".join(rows)]), []
rows = "\n".join([r + f" ##{ii}$$ |" for ii, r in enumerate(rows)])
+ rows = re.sub(r"T[0-9]{2}:[0-9]{2}:[0-9]{2}(\.[0-9]+Z)?\|", "|", rows)
docid_idx = list(docid_idx)[0]
docnm_idx = list(docnm_idx)[0]
return "\n".join([clmns, line, rows]), [{"doc_id": r[docid_idx], "docnm_kwd": r[docnm_idx]} for r in tbl["rows"]]
diff --git a/api/apps/llm_app.py b/api/apps/llm_app.py
index e89c85592104812d08c273d4d99d279b32c04930..d6a7b8176127e7002517de1ac1b8a1802877b417 100644
--- a/api/apps/llm_app.py
+++ b/api/apps/llm_app.py
@@ -39,36 +39,40 @@ def factories():
def set_api_key():
req = request.json
# test if api key works
+ chat_passed = False
+ factory = req["llm_factory"]
msg = ""
- for llm in LLMService.query(fid=req["llm_factory"]):
+ for llm in LLMService.query(fid=factory):
if llm.model_type == LLMType.EMBEDDING.value:
- mdl = EmbeddingModel[req["llm_factory"]](
+ mdl = EmbeddingModel[factory](
req["api_key"], llm.llm_name)
try:
arr, tc = mdl.encode(["Test if the api key is available"])
if len(arr[0]) == 0 or tc ==0: raise Exception("Fail")
except Exception as e:
msg += f"\nFail to access embedding model({llm.llm_name}) using this api key."
- elif llm.model_type == LLMType.CHAT.value:
- mdl = ChatModel[req["llm_factory"]](
+ elif not chat_passed and llm.model_type == LLMType.CHAT.value:
+ mdl = ChatModel[factory](
req["api_key"], llm.llm_name)
try:
m, tc = mdl.chat(None, [{"role": "user", "content": "Hello! How are you doing!"}], {"temperature": 0.9})
if not tc: raise Exception(m)
+ chat_passed = True
except Exception as e:
msg += f"\nFail to access model({llm.llm_name}) using this api key." + str(e)
if msg: return get_data_error_result(retmsg=msg)
llm = {
- "tenant_id": current_user.id,
- "llm_factory": req["llm_factory"],
"api_key": req["api_key"]
}
for n in ["model_type", "llm_name"]:
if n in req: llm[n] = req[n]
- TenantLLMService.filter_update([TenantLLM.tenant_id==llm["tenant_id"], TenantLLM.llm_factory==llm["llm_factory"]], llm)
+ if not TenantLLMService.filter_update([TenantLLM.tenant_id==current_user.id, TenantLLM.llm_factory==factory], llm):
+ for llm in LLMService.query(fid=factory):
+ TenantLLMService.save(tenant_id=current_user.id, llm_factory=factory, llm_name=llm.llm_name, model_type=llm.model_type, api_key=req["api_key"])
+
return get_json_result(data=True)
diff --git a/api/db/db_models.py b/api/db/db_models.py
index 020899198683efc8408a97b7a68c69dbe87d7298..c32b4d56b5df9a372edb12e73d064e6e218ef2a0 100644
--- a/api/db/db_models.py
+++ b/api/db/db_models.py
@@ -429,7 +429,7 @@ class LLMFactories(DataBaseModel):
class LLM(DataBaseModel):
# LLMs dictionary
- llm_name = CharField(max_length=128, null=False, help_text="LLM name", index=True)
+ llm_name = CharField(max_length=128, null=False, help_text="LLM name", index=True, primary_key=True)
model_type = CharField(max_length=128, null=False, help_text="LLM, Text Embedding, Image2Text, ASR")
fid = CharField(max_length=128, null=False, help_text="LLM factory id")
max_tokens = IntegerField(default=0)
diff --git a/api/db/init_data.py b/api/db/init_data.py
index 189e5437be463660e103e627cf80f145e0757aee..5696cd8d094f55615a2a3f3be16e1c4d08caedbd 100644
--- a/api/db/init_data.py
+++ b/api/db/init_data.py
@@ -73,41 +73,41 @@ def init_superuser():
print("\33[91mă€ERROR】\33[0m:", " '{}' dosen't work!".format(tenant["embd_id"]))
+factory_infos = [{
+ "name": "OpenAI",
+ "logo": "",
+ "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+ "status": "1",
+ },{
+ "name": "通义ĺŤé—®",
+ "logo": "",
+ "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+ "status": "1",
+ },{
+ "name": "智谱AI",
+ "logo": "",
+ "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+ "status": "1",
+ },
+ {
+ "name": "Local",
+ "logo": "",
+ "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+ "status": "1",
+ },{
+ "name": "Moonshot",
+ "logo": "",
+ "tags": "LLM,TEXT EMBEDDING",
+ "status": "1",
+ }
+ # {
+ # "name": "ć–‡ĺżä¸€č¨€",
+ # "logo": "",
+ # "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
+ # "status": "1",
+ # },
+]
def init_llm_factory():
- factory_infos = [{
- "name": "OpenAI",
- "logo": "",
- "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
- "status": "1",
- },{
- "name": "通义ĺŤé—®",
- "logo": "",
- "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
- "status": "1",
- },{
- "name": "智谱AI",
- "logo": "",
- "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
- "status": "1",
- },
- {
- "name": "Local",
- "logo": "",
- "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
- "status": "1",
- },{
- "name": "Moonshot",
- "logo": "",
- "tags": "LLM,TEXT EMBEDDING",
- "status": "1",
- }
- # {
- # "name": "ć–‡ĺżä¸€č¨€",
- # "logo": "",
- # "tags": "LLM,TEXT EMBEDDING,SPEECH2TEXT,MODERATION",
- # "status": "1",
- # },
- ]
llm_infos = [
# ---------------------- OpenAI ------------------------
{
@@ -260,21 +260,30 @@ def init_llm_factory():
},
]
for info in factory_infos:
- LLMFactoriesService.save(**info)
+ try:
+ LLMFactoriesService.save(**info)
+ except Exception as e:
+ pass
for info in llm_infos:
- LLMService.save(**info)
+ try:
+ LLMService.save(**info)
+ except Exception as e:
+ pass
def init_web_data():
start_time = time.time()
- if not LLMService.get_all().count():init_llm_factory()
+ if LLMFactoriesService.get_all().count() != len(factory_infos):
+ init_llm_factory()
if not UserService.get_all().count():
init_superuser()
print("init web data success:{}".format(time.time() - start_time))
+
if __name__ == '__main__':
init_web_db()
- init_web_data()
\ No newline at end of file
+ init_web_data()
+ add_tenant_llm()
\ No newline at end of file
diff --git a/api/db/services/llm_service.py b/api/db/services/llm_service.py
index 67dd70cae938c37fb68caf26e6aec94fb73aca44..5bb54b138e52aba0341ad758049be3fbc8671869 100644
--- a/api/db/services/llm_service.py
+++ b/api/db/services/llm_service.py
@@ -53,7 +53,7 @@ class TenantLLMService(CommonService):
cls.model.used_tokens
]
objs = cls.model.select(*fields).join(LLMFactories, on=(cls.model.llm_factory == LLMFactories.name)).where(
- cls.model.tenant_id == tenant_id).dicts()
+ cls.model.tenant_id == tenant_id, ~cls.model.api_key.is_null()).dicts()
return list(objs)
diff --git a/rag/llm/chat_model.py b/rag/llm/chat_model.py
index 57d6480c51cd2bb4ed157a8ca1358609be92acb8..2d9d9f5df4667fc92cb989b2d3fbc8da815920f0 100644
--- a/rag/llm/chat_model.py
+++ b/rag/llm/chat_model.py
@@ -54,6 +54,21 @@ class MoonshotChat(GptTurbo):
self.client = OpenAI(api_key=key, base_url="https://api.moonshot.cn/v1",)
self.model_name = model_name
+ def chat(self, system, history, gen_conf):
+ if system: history.insert(0, {"role": "system", "content": system})
+ try:
+ response = self.client.chat.completions.create(
+ model=self.model_name,
+ messages=history,
+ **gen_conf)
+ ans = response.choices[0].message.content.strip()
+ if response.choices[0].finish_reason == "length":
+ ans += "...\nFor the content length reason, it stopped, continue?" if is_english(
+ [ans]) else "······\nç”±äşŽé•żĺş¦çš„ĺŽźĺ› ďĽŚĺ›žç”被ćŞć–了，č¦ç»§ç»ĺ—？"
+ return ans, response.usage.completion_tokens
+ except openai.APIError as e:
+ return "**ERROR**: "+str(e), 0
+
from dashscope import Generation
class QWenChat(Base):