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Litellm dev 03 08 2025 p3 (#9089)

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* feat(ollama_chat.py): pass down http client to ollama_chat

enables easier testing

* fix(factory.py): fix passing images to ollama's `/api/generate` endpoint

Fixes https://github.com/BerriAI/litellm/issues/6683

* fix(factory.py): fix ollama pt to handle templating correctly
This commit is contained in:
Krish Dholakia 2025-03-09 18:20:56 -07:00 • committed by GitHub
parent 93273723cd
commit e00d4fb18c
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5 changed files with 165 additions and 52 deletions
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148
litellm/litellm_core_utils/prompt_templates/factory.py
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@ -187,53 +187,125 @@ def ollama_pt(
final_prompt_value="### Response:",
messages=messages,
)
elif "llava" in model:
prompt = ""
images = []
for message in messages:
if isinstance(message["content"], str):
prompt += message["content"]
elif isinstance(message["content"], list):
# see https://docs.litellm.ai/docs/providers/openai#openai-vision-models
for element in message["content"]:
if isinstance(element, dict):
if element["type"] == "text":
prompt += element["text"]
elif element["type"] == "image_url":
base64_image = convert_to_ollama_image(
element["image_url"]["url"]
)
images.append(base64_image)
return {"prompt": prompt, "images": images}
else:
user_message_types = {"user", "tool", "function"}
msg_i = 0
images = []
prompt = ""
for message in messages:
role = message["role"]
content = message.get("content", "")
while msg_i < len(messages):
init_msg_i = msg_i
user_content_str = ""
## MERGE CONSECUTIVE USER CONTENT ##
while (
msg_i < len(messages) and messages[msg_i]["role"] in user_message_types
):
msg_content = messages[msg_i].get("content")
if msg_content:
if isinstance(msg_content, list):
for m in msg_content:
if m.get("type", "") == "image_url":
if isinstance(m["image_url"], str):
images.append(m["image_url"])
elif isinstance(m["image_url"], dict):
images.append(m["image_url"]["url"])
elif m.get("type", "") == "text":
user_content_str += m["text"]
else:
# Tool message content will always be a string
user_content_str += msg_content
if "tool_calls" in message:
tool_calls = []
msg_i += 1
for call in message["tool_calls"]:
call_id: str = call["id"]
function_name: str = call["function"]["name"]
arguments = json.loads(call["function"]["arguments"])
if user_content_str:
prompt += f"### User:\n{user_content_str}\n\n"
tool_calls.append(
{
"id": call_id,
"type": "function",
"function": {"name": function_name, "arguments": arguments},
}
assistant_content_str = ""
## MERGE CONSECUTIVE ASSISTANT CONTENT ##
while msg_i < len(messages) and messages[msg_i]["role"] == "assistant":
msg_content = messages[msg_i].get("content")
if msg_content:
if isinstance(msg_content, list):
for m in msg_content:
if m.get("type", "") == "text":
assistant_content_str += m["text"]
elif isinstance(msg_content, str):
# Tool message content will always be a string
assistant_content_str += msg_content
tool_calls = messages[msg_i].get("tool_calls")
ollama_tool_calls = []
if tool_calls:
for call in tool_calls:
call_id: str = call["id"]
function_name: str = call["function"]["name"]
arguments = json.loads(call["function"]["arguments"])
ollama_tool_calls.append(
{
"id": call_id,
"type": "function",
"function": {
"name": function_name,
"arguments": arguments,
},
}
)
if ollama_tool_calls:
assistant_content_str += (
f"Tool Calls: {json.dumps(ollama_tool_calls, indent=2)}"
)
prompt += f"### Assistant:\nTool Calls: {json.dumps(tool_calls, indent=2)}\n\n"
msg_i += 1
elif "tool_call_id" in message:
prompt += f"### User:\n{message['content']}\n\n"
if assistant_content_str:
prompt += f"### Assistant:\n{assistant_content_str}\n\n"
elif content:
prompt += f"### {role.capitalize()}:\n{content}\n\n"
if msg_i == init_msg_i: # prevent infinite loops
raise litellm.BadRequestError(
message=BAD_MESSAGE_ERROR_STR + f"passed in {messages[msg_i]}",
model=model,
llm_provider="ollama",
)
# prompt = ""
# images = []
# for message in messages:
# if isinstance(message["content"], str):
# prompt += message["content"]
# elif isinstance(message["content"], list):
# # see https://docs.litellm.ai/docs/providers/openai#openai-vision-models
# for element in message["content"]:
# if isinstance(element, dict):
# if element["type"] == "text":
# prompt += element["text"]
# elif element["type"] == "image_url":
# base64_image = convert_to_ollama_image(
# element["image_url"]["url"]
# )
# images.append(base64_image)
# if "tool_calls" in message:
# tool_calls = []
# for call in message["tool_calls"]:
# call_id: str = call["id"]
# function_name: str = call["function"]["name"]
# arguments = json.loads(call["function"]["arguments"])
# tool_calls.append(
# {
# "id": call_id,
# "type": "function",
# "function": {"name": function_name, "arguments": arguments},
# }
# )
# prompt += f"### Assistant:\nTool Calls: {json.dumps(tool_calls, indent=2)}\n\n"
# elif "tool_call_id" in message:
# prompt += f"### User:\n{message['content']}\n\n"
return {"prompt": prompt, "images": images}
return prompt