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Fix: resolve hash collisions by switching to UUID &correct logic for always-true statements & Update GPT api integration & Support qianwen-deepresearch (#10208)

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### What problem does this PR solve?

Fix: resolve hash collisions by switching to UUID &correct logic for
always-true statements, solved: #10165
Feat: Update GPT api integration, solved: #10204 
Feat: Support qianwen-deepresearch, solved: #10163 
### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] New Feature (non-breaking change which adds functionality)
This commit is contained in:
Billy Bao
2025-09-23 09:34:30 +08:00
committed by GitHub
parent c8b79dfed4
commit da82566304
5 changed files with 28 additions and 16 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
agent/canvas.py
View File

@ -490,7 +490,8 @@ class Canvas(Graph):
r = self.retrieval[-1]
for ck in chunks_format({"chunks": chunks}):
cid = hash_str2int(ck["id"], 100)
cid = hash_str2int(ck["id"], 500)
# cid = uuid.uuid5(uuid.NAMESPACE_DNS, ck["id"])
if cid not in r:
r["chunks"][cid] = ck

2
api/apps/sdk/session.py
View File

@ -183,7 +183,7 @@ def chat_completion_openai_like(tenant_id, chat_id):
stream = True
reference = True
completion = client.chat.completions.create(
completion = client.responses.create(
model=model,
messages=[
{"role": "system", "content": "You are a helpful assistant."},

7
conf/llm_factories.json
View File

@ -622,6 +622,13 @@
"tags": "SPEECH2TEXT,8k",
"max_tokens": 8000,
"model_type": "speech2text"
},
{
"llm_name": "qianwen-deepresearch-30b-a3b-131k",
"tags": "LLM,CHAT,1M,AGENT,DEEPRESEARCH",
"max_tokens": 1000000,
"model_type": "chat",
"is_tools": true
}
]
},

23
rag/llm/chat_model.py
View File

@ -143,7 +143,8 @@ class Base(ABC):
logging.info("[HISTORY]" + json.dumps(history, ensure_ascii=False, indent=2))
if self.model_name.lower().find("qwen3") >= 0:
kwargs["extra_body"] = {"enable_thinking": False}
response = self.client.chat.completions.create(model=self.model_name, messages=history, **gen_conf, **kwargs)
response = self.client.responses.create(model=self.model_name, messages=history, **gen_conf, **kwargs)
if any([not response.choices, not response.choices[0].message, not response.choices[0].message.content]):
return "", 0
@ -155,10 +156,12 @@ class Base(ABC):
def _chat_streamly(self, history, gen_conf, **kwargs):
logging.info("[HISTORY STREAMLY]" + json.dumps(history, ensure_ascii=False, indent=4))
reasoning_start = False
if kwargs.get("stop") or "stop" in gen_conf:
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf, stop=kwargs.get("stop"))
response = self.client.responses.create(model=self.model_name, messages=history, stream=True, **gen_conf, stop=kwargs.get("stop"))
else:
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf)
response = self.client.responses.create(model=self.model_name, messages=history, stream=True, **gen_conf)
for resp in response:
if not resp.choices:
continue
@ -254,7 +257,7 @@ class Base(ABC):
try:
for _ in range(self.max_rounds + 1):
logging.info(f"{self.tools=}")
response = self.client.chat.completions.create(model=self.model_name, messages=history, tools=self.tools, tool_choice="auto", **gen_conf)
response = self.client.responses.create(model=self.model_name, messages=history, tools=self.tools, tool_choice="auto", **gen_conf)
tk_count += self.total_token_count(response)
if any([not response.choices, not response.choices[0].message]):
raise Exception(f"500 response structure error. Response: {response}")
@ -339,7 +342,7 @@ class Base(ABC):
for _ in range(self.max_rounds + 1):
reasoning_start = False
logging.info(f"{tools=}")
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, tools=tools, tool_choice="auto", **gen_conf)
response = self.client.responses.create(model=self.model_name, messages=history, stream=True, tools=tools, tool_choice="auto", **gen_conf)
final_tool_calls = {}
answer = ""
for resp in response:
@ -402,7 +405,7 @@ class Base(ABC):
logging.warning(f"Exceed max rounds: {self.max_rounds}")
history.append({"role": "user", "content": f"Exceed max rounds: {self.max_rounds}"})
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf)
response = self.client.responses.create(model=self.model_name, messages=history, stream=True, **gen_conf)
for resp in response:
if any([not resp.choices, not resp.choices[0].delta, not hasattr(resp.choices[0].delta, "content")]):
raise Exception("500 response structure error.")
@ -556,7 +559,7 @@ class BaiChuanChat(Base):
}
def _chat(self, history, gen_conf={}, **kwargs):
response = self.client.chat.completions.create(
response = self.client.responses.create(
model=self.model_name,
messages=history,
extra_body={"tools": [{"type": "web_search", "web_search": {"enable": True, "search_mode": "performance_first"}}]},
@ -578,7 +581,7 @@ class BaiChuanChat(Base):
ans = ""
total_tokens = 0
try:
response = self.client.chat.completions.create(
response = self.client.responses.create(
model=self.model_name,
messages=history,
extra_body={"tools": [{"type": "web_search", "web_search": {"enable": True, "search_mode": "performance_first"}}]},
@ -648,7 +651,7 @@ class ZhipuChat(Base):
tk_count = 0
try:
logging.info(json.dumps(history, ensure_ascii=False, indent=2))
response = self.client.chat.completions.create(model=self.model_name, messages=history, stream=True, **gen_conf)
response = self.client.responses.create(model=self.model_name, messages=history, stream=True, **gen_conf)
for resp in response:
if not resp.choices[0].delta.content:
continue
@ -1361,7 +1364,7 @@ class LiteLLMBase(ABC):
drop_params=True,
timeout=self.timeout,
)
# response = self.client.chat.completions.create(model=self.model_name, messages=history, **gen_conf, **kwargs)
# response = self.client.responses.create(model=self.model_name, messages=history, **gen_conf, **kwargs)
if any([not response.choices, not response.choices[0].message, not response.choices[0].message.content]):
return "", 0

9
rag/llm/cv_model.py
View File

@ -75,7 +75,7 @@ class Base(ABC):
def chat(self, system, history, gen_conf, images=[], **kwargs):
try:
response = self.client.chat.completions.create(
response = self.client.responses.create(
model=self.model_name,
messages=self._form_history(system, history, images)
)
@ -87,7 +87,7 @@ class Base(ABC):
ans = ""
tk_count = 0
try:
response = self.client.chat.completions.create(
response = self.client.responses.create(
model=self.model_name,
messages=self._form_history(system, history, images),
stream=True
@ -174,7 +174,8 @@ class GptV4(Base):
def describe(self, image):
b64 = self.image2base64(image)
res = self.client.chat.completions.create(
# Check if this is a GPT-5 model and use responses.create API
res = self.client.responses.create(
model=self.model_name,
messages=self.prompt(b64),
)
@ -182,7 +183,7 @@ class GptV4(Base):
def describe_with_prompt(self, image, prompt=None):
b64 = self.image2base64(image)
res = self.client.chat.completions.create(
res = self.client.responses.create(
model=self.model_name,
messages=self.vision_llm_prompt(b64, prompt),
)