tiennm99/litellm
1
0
Fork 0
mirror of https://github.com/tiennm99/litellm.git synced 2026-07-20 02:18:38 +00:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #19179 from BerriAI/litellm_fix_streaming_chunk

Browse Source 
Fix : test_stream_chunk_builder_litellm_mixed_calls
This commit is contained in:
Sameer Kankute
2026-01-16 10:52:25 +05:30
committed by GitHub
parent 18de9d71af aec1990dc2
commit 9ac490de62
2 changed files with 71 additions and 29 deletions
Download Patch File Download Diff File Expand all files Collapse all files
litellm/litellm_core_utils/streaming_chunk_builder_utils.py
+65 -23
View File
@@ -147,10 +147,26 @@ class ChunkProcessor:
tool_calls = delta.get("tool_calls", [])
for tool_call in tool_calls:
if not tool_call or not hasattr(tool_call, "function"):
# Handle both dict and object formats
if not tool_call:
continue
# Check if tool_call has function (either as attribute or dict key)
has_function = False
if isinstance(tool_call, dict):
has_function = "function" in tool_call and tool_call["function"] is not None
else:
has_function = hasattr(tool_call, "function") and tool_call.function is not None
if not has_function:
continue
index = getattr(tool_call, "index", 0)
# Get index (handle both dict and object)
if isinstance(tool_call, dict):
index = tool_call.get("index", 0)
else:
index = getattr(tool_call, "index", 0)
if index not in tool_call_map:
tool_call_map[index] = {
"id": None,
@@ -160,30 +176,56 @@ class ChunkProcessor:
"provider_specific_fields": None,
}
if hasattr(tool_call, "id") and tool_call.id:
tool_call_map[index]["id"] = tool_call.id
if hasattr(tool_call, "type") and tool_call.type:
tool_call_map[index]["type"] = tool_call.type
if hasattr(tool_call, "function"):
if (
hasattr(tool_call.function, "name")
and tool_call.function.name
):
tool_call_map[index]["name"] = tool_call.function.name
if (
hasattr(tool_call.function, "arguments")
and tool_call.function.arguments
):
tool_call_map[index]["arguments"].append(
tool_call.function.arguments
)
# Extract id, type, and function data (handle both dict and object)
if isinstance(tool_call, dict):
if tool_call.get("id"):
tool_call_map[index]["id"] = tool_call["id"]
if tool_call.get("type"):
tool_call_map[index]["type"] = tool_call["type"]
function = tool_call.get("function", {})
if isinstance(function, dict):
if function.get("name"):
tool_call_map[index]["name"] = function["name"]
if function.get("arguments"):
tool_call_map[index]["arguments"].append(function["arguments"])
else:
# function is an object
if hasattr(function, "name") and function.name:
tool_call_map[index]["name"] = function.name
if hasattr(function, "arguments") and function.arguments:
tool_call_map[index]["arguments"].append(function.arguments)
else:
# tool_call is an object
if hasattr(tool_call, "id") and tool_call.id:
tool_call_map[index]["id"] = tool_call.id
if hasattr(tool_call, "type") and tool_call.type:
tool_call_map[index]["type"] = tool_call.type
if hasattr(tool_call, "function"):
if (
hasattr(tool_call.function, "name")
and tool_call.function.name
):
tool_call_map[index]["name"] = tool_call.function.name
if (
hasattr(tool_call.function, "arguments")
and tool_call.function.arguments
):
tool_call_map[index]["arguments"].append(
tool_call.function.arguments
)
# Preserve provider_specific_fields from streaming chunks
provider_fields = None
if hasattr(tool_call, "provider_specific_fields") and tool_call.provider_specific_fields:
provider_fields = tool_call.provider_specific_fields
elif hasattr(tool_call, "function") and hasattr(tool_call.function, "provider_specific_fields") and tool_call.function.provider_specific_fields:
provider_fields = tool_call.function.provider_specific_fields
if isinstance(tool_call, dict):
provider_fields = tool_call.get("provider_specific_fields")
if not provider_fields and isinstance(tool_call.get("function"), dict):
provider_fields = tool_call["function"].get("provider_specific_fields")
else:
if hasattr(tool_call, "provider_specific_fields") and tool_call.provider_specific_fields:
provider_fields = tool_call.provider_specific_fields
elif hasattr(tool_call, "function") and hasattr(tool_call.function, "provider_specific_fields") and tool_call.function.provider_specific_fields:
provider_fields = tool_call.function.provider_specific_fields
if provider_fields:
# Merge provider_specific_fields if multiple chunks have them
tests/test_litellm/google_genai/test_google_genai_adapter.py
+6 -6
View File
@@ -422,7 +422,7 @@ def test_streaming_tool_calls_transformation():
ChatCompletionDeltaToolCall,
Delta,
Function,
ModelResponse,
ModelResponseStream,
StreamingChoices,
)
@@ -454,7 +454,7 @@ def test_streaming_tool_calls_transformation():
delta=mock_delta
)
mock_response = ModelResponse(
mock_response = ModelResponseStream(
id="test-streaming",
choices=[mock_choice],
created=1234567890,
@@ -493,7 +493,7 @@ def test_streaming_partial_tool_calls_accumulation():
ChatCompletionDeltaToolCall,
Delta,
Function,
ModelResponse,
ModelResponseStream,
StreamingChoices,
)
@@ -543,7 +543,7 @@ def test_streaming_partial_tool_calls_accumulation():
delta=mock_delta
)
mock_response = ModelResponse(
mock_response = ModelResponseStream(
id="test-streaming",
choices=[mock_choice],
created=1234567890,
@@ -595,7 +595,7 @@ def test_streaming_multiple_partial_tool_calls():
ChatCompletionDeltaToolCall,
Delta,
Function,
ModelResponse,
ModelResponseStream,
StreamingChoices,
)
@@ -642,7 +642,7 @@ def test_streaming_multiple_partial_tool_calls():
delta=mock_delta
)
mock_response = ModelResponse(
mock_response = ModelResponseStream(
id="test-streaming",
choices=[mock_choice],
created=1234567890,