Enhance SQL generation and streaming capabilities in the API server. Introduce optional parameters for streaming throttle and SQL stream granularity in NLChatRequest. Implement new functions for iterating SQL generation content pieces and adjusting streaming behavior based on user-defined settings. Update prompts for few-shot SQL adaptation and improve logging for SQL generation processes. Refactor orchestrator methods to support streaming responses and integrate few-shot SQL conditions. Update impact analysis documentation to reflect these changes.

backend/llm/deepseek_client.py

@@ -6,7 +6,7 @@ DeepSeek API 客户端封装
 import os
 import json
 import logging
-from typing import Dict, List, Optional, Any, Union
+from typing import Any, Dict, Iterator, List, Optional, Union
 from dataclasses import dataclass, field
 from openai import OpenAI, AsyncOpenAI
 from openai.types.chat import ChatCompletion, ChatCompletionMessage
@@ -104,6 +104,43 @@ class DeepSeekClient:
             logger.error(f"DeepSeek API调用失败: {e}")
             raise
 
+    def chat_stream(
+        self,
+        messages: List[Dict[str, str]],
+        **kwargs: Any,
+    ) -> Iterator[str]:
+        """
+        流式聊天：按 completion 增量产出文本片段（与 chat 同参，固定 stream=True）。
+        """
+        params: Dict[str, Any] = {
+            "model": self.config.model_name,
+            "messages": messages,
+            "temperature": kwargs.get("temperature", self.config.temperature),
+            "max_tokens": kwargs.get("max_tokens", self.config.max_tokens),
+            "top_p": kwargs.get("top_p", self.config.top_p),
+            "frequency_penalty": kwargs.get(
+                "frequency_penalty", self.config.frequency_penalty
+            ),
+            "presence_penalty": kwargs.get(
+                "presence_penalty", self.config.presence_penalty
+            ),
+            "stream": True,
+            "timeout": kwargs.get("timeout", self.config.timeout),
+        }
+        if self.config.extra_headers:
+            params["extra_headers"] = self.config.extra_headers
+        try:
+            stream = self.client.chat.completions.create(**params)
+            for chunk in stream:
+                if not chunk.choices:
+                    continue
+                delta = chunk.choices[0].delta
+                if delta and getattr(delta, "content", None):
+                    yield delta.content
+        except Exception as e:
+            logger.error(f"DeepSeek API流式调用失败: {e}")
+            raise
+
     def chat_with_json(
         self,
         messages: List[Dict[str, str]],

backend/llm/openai_client.py

@@ -10,7 +10,7 @@ import json
 import logging
 import os
 from dataclasses import dataclass
-from typing import Any, Dict, List, Optional
+from typing import Any, Dict, Iterator, List, Optional
 
 from openai import AsyncOpenAI, OpenAI  # type: ignore[import-not-found]
 from openai.types.chat import (  # type: ignore[import-not-found]
@@ -119,6 +119,69 @@ class OpenAIClient:
             logger.error("OpenAI API调用失败: %s", e)
             raise
 
+    def chat_stream(
+        self,
+        messages: List[Dict[str, str]],
+        **kwargs: Any,
+    ) -> Iterator[str]:
+        """流式聊天：按 completion 增量产出文本片段（与 chat 同参，固定 stream=True）。"""
+        max_tokens = kwargs.get("max_tokens", self.config.max_tokens)
+        max_completion_tokens = kwargs.get("max_completion_tokens", None)
+
+        params: Dict[str, Any] = {
+            "model": self.config.model_name,
+            "messages": messages,
+            "temperature": kwargs.get("temperature", self.config.temperature),
+            "top_p": kwargs.get("top_p", self.config.top_p),
+            "frequency_penalty": kwargs.get(
+                "frequency_penalty", self.config.frequency_penalty
+            ),
+            "presence_penalty": kwargs.get(
+                "presence_penalty", self.config.presence_penalty
+            ),
+            "stream": True,
+            "timeout": kwargs.get("timeout", self.config.timeout),
+        }
+        if max_completion_tokens is not None:
+            params["max_completion_tokens"] = max_completion_tokens
+        else:
+            params["max_tokens"] = max_tokens
+
+        if self.config.extra_headers:
+            params["extra_headers"] = self.config.extra_headers
+
+        try:
+            stream = self.client.chat.completions.create(**params)
+            for chunk in stream:
+                if not chunk.choices:
+                    continue
+                delta = chunk.choices[0].delta
+                if delta and getattr(delta, "content", None):
+                    yield delta.content
+        except Exception as e:
+            msg = str(e)
+            if (
+                "Unsupported parameter" in msg
+                and "max_tokens" in msg
+                and "max_completion_tokens" in msg
+                and "max_completion_tokens" not in params
+            ):
+                params.pop("max_tokens", None)
+                params["max_completion_tokens"] = max_tokens
+                try:
+                    stream = self.client.chat.completions.create(**params)
+                    for chunk in stream:
+                        if not chunk.choices:
+                            continue
+                        delta = chunk.choices[0].delta
+                        if delta and getattr(delta, "content", None):
+                            yield delta.content
+                    return
+                except Exception:
+                    pass
+            logger.error("OpenAI API流式调用失败: %s", e)
+            raise
+
     def chat_with_json(
         self, messages: List[Dict[str, str]], **kwargs
     ) -> Dict[str, Any]: