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Feat: conversation completion can specify different model (#9485)

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### What problem does this PR solve?

Conversation completion can specify different model

### Type of change

- [x] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Yongteng Lei
2025-08-15 17:44:58 +08:00
committed by GitHub
parent 799c57287c
commit ffc095bd50
3 changed files with 57 additions and 13 deletions
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43
api/apps/conversation_app.py
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@ -29,7 +29,8 @@ from api.db.services.conversation_service import ConversationService, structure_
from api.db.services.dialog_service import DialogService, ask, chat
from api.db.services.knowledgebase_service import KnowledgebaseService
from api.db.services.llm_service import LLMBundle
from api.db.services.user_service import UserTenantService, TenantService
from api.db.services.tenant_llm_service import TenantLLMService
from api.db.services.user_service import TenantService, UserTenantService
from api.utils.api_utils import get_data_error_result, get_json_result, server_error_response, validate_request
from graphrag.general.mind_map_extractor import MindMapExtractor
from rag.app.tag import label_question
@ -66,8 +67,14 @@ def set_conversation():
e, dia = DialogService.get_by_id(req["dialog_id"])
if not e:
return get_data_error_result(message="Dialog not found")
conv = {"id": conv_id, "dialog_id": req["dialog_id"], "name": name, "message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}],"user_id": current_user.id,
"reference":[],}
conv = {
"id": conv_id,
"dialog_id": req["dialog_id"],
"name": name,
"message": [{"role": "assistant", "content": dia.prompt_config["prologue"]}],
"user_id": current_user.id,
"reference": [],
}
ConversationService.save(**conv)
return get_json_result(data=conv)
except Exception as e:
@ -174,6 +181,21 @@ def completion():
continue
msg.append(m)
message_id = msg[-1].get("id")
chat_model_id = req.get("llm_id", "")
req.pop("llm_id", None)
chat_model_config = {}
for model_config in [
"temperature",
"top_p",
"frequency_penalty",
"presence_penalty",
"max_tokens",
]:
config = req.get(model_config)
if config:
chat_model_config[model_config] = config
try:
e, conv = ConversationService.get_by_id(req["conversation_id"])
if not e:
@ -190,13 +212,23 @@ def completion():
conv.reference = [r for r in conv.reference if r]
conv.reference.append({"chunks": [], "doc_aggs": []})
if chat_model_id:
if not TenantLLMService.get_api_key(tenant_id=dia.tenant_id, model_name=chat_model_id):
req.pop("chat_model_id", None)
req.pop("chat_model_config", None)
return get_data_error_result(message=f"Cannot use specified model {chat_model_id}.")
dia.llm_id = chat_model_id
dia.llm_setting = chat_model_config
is_embedded = bool(chat_model_id)
def stream():
nonlocal dia, msg, req, conv
try:
for ans in chat(dia, msg, True, **req):
ans = structure_answer(conv, ans, message_id, conv.id)
yield "data:" + json.dumps({"code": 0, "message": "", "data": ans}, ensure_ascii=False) + "\n\n"
ConversationService.update_by_id(conv.id, conv.to_dict())
if not is_embedded:
ConversationService.update_by_id(conv.id, conv.to_dict())
except Exception as e:
traceback.print_exc()
yield "data:" + json.dumps({"code": 500, "message": str(e), "data": {"answer": "**ERROR**: " + str(e), "reference": []}}, ensure_ascii=False) + "\n\n"
@ -214,7 +246,8 @@ def completion():
answer = None
for ans in chat(dia, msg, **req):
answer = structure_answer(conv, ans, message_id, conv.id)
ConversationService.update_by_id(conv.id, conv.to_dict())
if not is_embedded:
ConversationService.update_by_id(conv.id, conv.to_dict())
break
return get_json_result(data=answer)
except Exception as e: