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bugfix-239
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devin/1746
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c63010daaa | ||
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d0191df996 | ||
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e27bcfb381 | ||
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082cbd2c1c | ||
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3361fab293 |
11
src/crewai/patches/__init__.py
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11
src/crewai/patches/__init__.py
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"""
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Patches module for CrewAI.
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This module contains patches for external dependencies to fix known issues.
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Version: 1.0.0
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"""
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from crewai.patches.litellm_patch import apply_patches, patch_litellm_ollama_pt
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__all__ = ["apply_patches", "patch_litellm_ollama_pt"]
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186
src/crewai/patches/litellm_patch.py
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186
src/crewai/patches/litellm_patch.py
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"""
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Patch for litellm to fix IndexError in ollama_pt function.
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This patch addresses issue #2744 in the crewAI repository, where an IndexError occurs
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in litellm's Ollama prompt template function when CrewAI Agent with Tools uses Ollama/Qwen models.
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Version: 1.0.0
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"""
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import json
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import logging
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from typing import Any, Dict, List, Optional, Tuple, Union
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# Set up logging
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logger = logging.getLogger(__name__)
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# Patch version
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PATCH_VERSION = "1.0.0"
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class PatchApplicationError(Exception):
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"""Exception raised when a patch fails to apply."""
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pass
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def apply_patches() -> bool:
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"""
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Apply all patches to fix known issues with dependencies.
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Returns:
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bool: True if all patches were applied successfully, False otherwise.
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"""
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success = patch_litellm_ollama_pt()
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logger.info(f"LiteLLM ollama_pt patch applied: {success}")
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return success
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def patch_litellm_ollama_pt() -> bool:
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"""
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Patch the ollama_pt function in litellm to fix IndexError.
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The issue occurs when accessing messages[msg_i].get("tool_calls") without checking
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if msg_i is within bounds of the messages list. This happens after tool execution
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during the next LLM call.
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Returns:
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bool: True if the patch was applied successfully, False otherwise.
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Raises:
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PatchApplicationError: If there's an error during patch application.
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"""
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try:
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# Import the module containing the function to patch
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import litellm.litellm_core_utils.prompt_templates.factory as factory
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# Define a patched version of the function
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def patched_ollama_pt(model: str, messages: List[Dict]) -> Dict[str, Any]:
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"""
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Patched version of ollama_pt that adds bounds checking.
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This fixes the IndexError that occurs when the assistant message is the last
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message in the list and msg_i goes out of bounds.
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Args:
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model: The model name.
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messages: The list of messages to process.
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Returns:
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Dict containing the prompt and images.
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"""
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user_message_types = {"user", "tool", "function"}
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msg_i = 0
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images: List[str] = []
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prompt = ""
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# Handle empty messages list
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if not messages:
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return {"prompt": prompt, "images": images}
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while msg_i < len(messages):
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init_msg_i = msg_i
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user_content_str = ""
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## MERGE CONSECUTIVE USER CONTENT ##
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while msg_i < len(messages) and messages[msg_i]["role"] in user_message_types:
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msg_content = messages[msg_i].get("content")
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if msg_content:
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if isinstance(msg_content, list):
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for m in msg_content:
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if m.get("type", "") == "image_url":
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if isinstance(m["image_url"], str):
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images.append(m["image_url"])
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elif isinstance(m["image_url"], dict):
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images.append(m["image_url"]["url"])
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elif m.get("type", "") == "text":
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user_content_str += m["text"]
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else:
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# Tool message content will always be a string
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user_content_str += msg_content
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msg_i += 1
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if user_content_str:
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prompt += f"### User:\n{user_content_str}\n\n"
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system_content_str, msg_i = factory._handle_ollama_system_message(
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messages, prompt, msg_i
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)
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if system_content_str:
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prompt += f"### System:\n{system_content_str}\n\n"
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assistant_content_str = ""
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## MERGE CONSECUTIVE ASSISTANT CONTENT ##
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while msg_i < len(messages) and messages[msg_i]["role"] == "assistant":
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assistant_content_str += factory.convert_content_list_to_str(messages[msg_i])
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msg_i += 1
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# Add bounds check before accessing messages[msg_i]
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# This is the key fix for the IndexError
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if msg_i < len(messages):
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tool_calls = messages[msg_i].get("tool_calls")
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ollama_tool_calls = []
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if tool_calls:
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for call in tool_calls:
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call_id = call["id"]
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function_name = call["function"]["name"]
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arguments = json.loads(call["function"]["arguments"])
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ollama_tool_calls.append(
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{
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"id": call_id,
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"type": "function",
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"function": {
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"name": function_name,
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"arguments": arguments,
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},
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}
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)
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if ollama_tool_calls:
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assistant_content_str += (
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f"Tool Calls: {json.dumps(ollama_tool_calls, indent=2)}"
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)
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msg_i += 1
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if assistant_content_str:
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prompt += f"### Assistant:\n{assistant_content_str}\n\n"
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if msg_i == init_msg_i: # prevent infinite loops
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raise factory.litellm.BadRequestError(
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message=factory.BAD_MESSAGE_ERROR_STR + f"passed in {messages[msg_i]}",
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model=model,
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llm_provider="ollama",
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)
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response_dict = {
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"prompt": prompt,
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"images": images,
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}
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return response_dict
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# Replace the original function with our patched version
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factory.ollama_pt = patched_ollama_pt
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logger.info(f"Successfully applied litellm ollama_pt patch version {PATCH_VERSION}")
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return True
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except Exception as e:
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error_msg = f"Failed to apply litellm ollama_pt patch: {e}"
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logger.error(error_msg)
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return False
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# For backwards compatibility
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def patch_litellm() -> bool:
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"""
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Legacy function for backwards compatibility.
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Returns:
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bool: True if the patch was applied successfully, False otherwise.
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"""
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try:
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return patch_litellm_ollama_pt()
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except Exception as e:
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logger.error(f"Failed to apply legacy litellm patch: {e}")
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return False
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71
tests/patches/test_litellm_patch.py
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71
tests/patches/test_litellm_patch.py
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@@ -0,0 +1,71 @@
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"""
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Test for the litellm patch that fixes the IndexError in ollama_pt function.
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"""
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import sys
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import unittest
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from unittest.mock import MagicMock, patch
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import litellm
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import pytest
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from litellm.litellm_core_utils.prompt_templates.factory import ollama_pt
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from crewai.patches.litellm_patch import patch_litellm_ollama_pt
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class TestLitellmPatch(unittest.TestCase):
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def test_ollama_pt_patch_fixes_index_error(self):
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"""Test that the patch fixes the IndexError in ollama_pt."""
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# Create a message list where the assistant message is the last one
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messages = [
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{"role": "user", "content": "Hello"},
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{"role": "assistant", "content": "Hi there"},
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]
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# Store the original function to restore it after the test
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original_ollama_pt = litellm.litellm_core_utils.prompt_templates.factory.ollama_pt
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try:
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# Apply the patch
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success = patch_litellm_ollama_pt()
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self.assertTrue(success, "Patch application failed")
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# Use the function from the module directly to ensure we're using the patched version
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result = litellm.litellm_core_utils.prompt_templates.factory.ollama_pt("qwen3:4b", messages)
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# Verify the result is as expected
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self.assertIn("prompt", result)
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self.assertIn("images", result)
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self.assertIn("### User:\nHello", result["prompt"])
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self.assertIn("### Assistant:\nHi there", result["prompt"])
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finally:
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# Restore the original function to avoid affecting other tests
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litellm.litellm_core_utils.prompt_templates.factory.ollama_pt = original_ollama_pt
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def test_ollama_pt_patch_with_empty_messages(self):
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"""Test that the patch handles empty message lists."""
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messages = []
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# Store the original function to restore it after the test
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original_ollama_pt = litellm.litellm_core_utils.prompt_templates.factory.ollama_pt
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try:
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# Apply the patch
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success = patch_litellm_ollama_pt()
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self.assertTrue(success, "Patch application failed")
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# Use the function from the module directly to ensure we're using the patched version
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result = litellm.litellm_core_utils.prompt_templates.factory.ollama_pt("qwen3:4b", messages)
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# Verify the result is as expected
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self.assertIn("prompt", result)
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self.assertIn("images", result)
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self.assertEqual("", result["prompt"])
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self.assertEqual([], result["images"])
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finally:
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# Restore the original function to avoid affecting other tests
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litellm.litellm_core_utils.prompt_templates.factory.ollama_pt = original_ollama_pt
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if __name__ == "__main__":
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unittest.main()
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