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

### 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)

agent/canvas.py

@@ -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
 

api/apps/sdk/session.py

@@ -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."},

conf/llm_factories.json

@@ -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
                 }
             ]
         },

rag/llm/chat_model.py

@@ -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

rag/llm/cv_model.py

@@ -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),
         )