chore: initial snapshot for gitea/github upload

llm-gateway-competitors/litellm-wheel-src/litellm/llms/gigachat/chat/streaming.py

@@ -0,0 +1,137 @@
+"""
+GigaChat Streaming Response Handler
+"""
+
+import json
+import uuid
+from typing import Any, Optional
+
+from litellm.types.llms.openai import (
+    ChatCompletionToolCallChunk,
+    ChatCompletionToolCallFunctionChunk,
+)
+from litellm.types.utils import GenericStreamingChunk
+
+
+class GigaChatModelResponseIterator:
+    """Iterator for GigaChat streaming responses."""
+
+    def __init__(
+        self,
+        streaming_response: Any,
+        sync_stream: bool,
+        json_mode: Optional[bool] = False,
+    ):
+        self.streaming_response = streaming_response
+        self.response_iterator = self.streaming_response
+        self.json_mode = json_mode
+
+    def chunk_parser(self, chunk: dict) -> GenericStreamingChunk:
+        """Parse a single streaming chunk from GigaChat."""
+        text = ""
+        tool_use: Optional[ChatCompletionToolCallChunk] = None
+        is_finished = False
+        finish_reason: Optional[str] = None
+
+        choices = chunk.get("choices", [])
+        if not choices:
+            return GenericStreamingChunk(
+                text="",
+                tool_use=None,
+                is_finished=False,
+                finish_reason="",
+                usage=None,
+                index=0,
+            )
+
+        choice = choices[0]
+        delta = choice.get("delta", {})
+        finish_reason = choice.get("finish_reason")
+
+        # Extract text content
+        text = delta.get("content", "") or ""
+
+        # Handle function_call in stream
+        if finish_reason == "function_call" and delta.get("function_call"):
+            func_call = delta["function_call"]
+            args = func_call.get("arguments", {})
+
+            if isinstance(args, dict):
+                args = json.dumps(args, ensure_ascii=False)
+
+            tool_use = ChatCompletionToolCallChunk(
+                id=f"call_{uuid.uuid4().hex[:24]}",
+                type="function",
+                function=ChatCompletionToolCallFunctionChunk(
+                    name=func_call.get("name", ""),
+                    arguments=args,
+                ),
+                index=0,
+            )
+            finish_reason = "tool_calls"
+
+        if finish_reason is not None:
+            is_finished = True
+
+        return GenericStreamingChunk(
+            text=text,
+            tool_use=tool_use,
+            is_finished=is_finished,
+            finish_reason=finish_reason or "",
+            usage=None,
+            index=choice.get("index", 0),
+        )
+
+    def __iter__(self):
+        return self
+
+    def __next__(self) -> GenericStreamingChunk:
+        try:
+            chunk = self.response_iterator.__next__()
+            if isinstance(chunk, str):
+                # Parse SSE format: data: {...}
+                if chunk.startswith("data: "):
+                    chunk = chunk[6:]
+                if chunk.strip() == "[DONE]":
+                    raise StopIteration
+                try:
+                    chunk = json.loads(chunk)
+                except json.JSONDecodeError:
+                    return GenericStreamingChunk(
+                        text="",
+                        tool_use=None,
+                        is_finished=False,
+                        finish_reason="",
+                        usage=None,
+                        index=0,
+                    )
+            return self.chunk_parser(chunk)
+        except StopIteration:
+            raise
+
+    def __aiter__(self):
+        return self
+
+    async def __anext__(self) -> GenericStreamingChunk:
+        try:
+            chunk = await self.response_iterator.__anext__()
+            if isinstance(chunk, str):
+                # Parse SSE format
+                if chunk.startswith("data: "):
+                    chunk = chunk[6:]
+                if chunk.strip() == "[DONE]":
+                    raise StopAsyncIteration
+                try:
+                    chunk = json.loads(chunk)
+                except json.JSONDecodeError:
+                    return GenericStreamingChunk(
+                        text="",
+                        tool_use=None,
+                        is_finished=False,
+                        finish_reason="",
+                        usage=None,
+                        index=0,
+                    )
+            return self.chunk_parser(chunk)
+        except StopAsyncIteration:
+            raise