diff --git a/patchwork/app.py b/patchwork/app.py
index c759ec238..4e33609e7 100644
--- a/patchwork/app.py
+++ b/patchwork/app.py
@@ -8,12 +8,11 @@
 from collections import deque
 from contextlib import nullcontext
 from pathlib import Path
-from typing import Any
 
 import click
 import yaml
 from click import echo
-from typing_extensions import Iterable
+from typing_extensions import Any, Iterable
 
 from patchwork.common.client.patched import PatchedClient
 from patchwork.common.constants import PROMPT_TEMPLATE_FILE_KEY
diff --git a/patchwork/common/client/llm/aio.py b/patchwork/common/client/llm/aio.py
index 19b9e63df..ccc2263c2 100644
--- a/patchwork/common/client/llm/aio.py
+++ b/patchwork/common/client/llm/aio.py
@@ -10,7 +10,11 @@
     ChatCompletionToolParam,
     completion_create_params,
 )
-from typing_extensions import Dict, Iterable, List, Optional, Union
+from pydantic_ai.messages import ModelMessage, ModelResponse
+from pydantic_ai.models import ModelRequestParameters, StreamedResponse
+from pydantic_ai.settings import ModelSettings
+from pydantic_ai.usage import Usage
+from typing_extensions import AsyncIterator, Dict, Iterable, List, Optional, Union
 
 from patchwork.common.client.llm.anthropic import AnthropicLlmClient
 from patchwork.common.client.llm.google import GoogleLlmClient
@@ -32,6 +36,64 @@ def __init__(self, *clients: LlmClient):
             except Exception:
                 pass
 
+    def __get_model(self, model_settings: ModelSettings | None) -> Optional[str]:
+        if model_settings is None:
+            raise ValueError("Model settings cannot be None")
+        model_name = model_settings.get("model")
+        if model_name is None:
+            raise ValueError("Model must be set cannot be None")
+
+        return model_name
+
+    async def request(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> tuple[ModelResponse, Usage]:
+        model = self.__get_model(model_settings)
+        if model is None:
+            raise ValueError("Model cannot be unset")
+
+        for client in self.__clients:
+            if client.is_model_supported(model):
+                return await client.request(messages, model_settings, model_request_parameters)
+
+        client_names = [client.__class__.__name__ for client in self.__original_clients]
+        raise ValueError(
+            f"Model {model} is not supported by {client_names} clients. "
+            f"Please ensure that the respective API keys are correct."
+        )
+
+    async def request_stream(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> AsyncIterator[StreamedResponse]:
+        model = self.__get_model(model_settings)
+        if model is None:
+            raise ValueError("Model cannot be unset")
+
+        for client in self.__clients:
+            if client.is_model_supported(model):
+                yield client.request(messages, model_settings, model_request_parameters)
+                return
+
+        client_names = [client.__class__.__name__ for client in self.__original_clients]
+        raise ValueError(
+            f"Model {model} is not supported by {client_names} clients. "
+            f"Please ensure that the respective API keys are correct."
+        )
+
+    @property
+    def model_name(self) -> str:
+        return "Undetermined"
+
+    @property
+    def system(self) -> str:
+        return next(iter(self.__clients)).system
+
     def get_models(self) -> set[str]:
         return self.__supported_models
 
diff --git a/patchwork/common/client/llm/anthropic.py b/patchwork/common/client/llm/anthropic.py
index 19d14be61..7250502be 100644
--- a/patchwork/common/client/llm/anthropic.py
+++ b/patchwork/common/client/llm/anthropic.py
@@ -2,7 +2,7 @@
 
 import json
 import time
-from functools import lru_cache
+from functools import cached_property, lru_cache
 from pathlib import Path
 
 from anthropic import Anthropic
@@ -15,13 +15,18 @@
     ChatCompletionToolParam,
     completion_create_params,
 )
-from openai.types.chat.chat_completion import Choice, CompletionUsage
+from openai.types.chat.chat_completion import Choice
 from openai.types.chat.chat_completion_message_tool_call import (
     ChatCompletionMessageToolCall,
     Function,
 )
 from openai.types.completion_usage import CompletionUsage
-from typing_extensions import Dict, Iterable, List, Optional, Union
+from pydantic_ai.messages import ModelMessage, ModelResponse
+from pydantic_ai.models import Model, ModelRequestParameters, StreamedResponse
+from pydantic_ai.models.anthropic import AnthropicModel
+from pydantic_ai.settings import ModelSettings
+from pydantic_ai.usage import Usage
+from typing_extensions import AsyncIterator, Dict, Iterable, List, Optional, Union
 
 from patchwork.common.client.llm.protocol import NOT_GIVEN, LlmClient, NotGiven
 
@@ -74,7 +79,46 @@ class AnthropicLlmClient(LlmClient):
     __100k_models = {"claude-2.0", "claude-instant-1.2"}
 
     def __init__(self, api_key: str):
-        self.client = Anthropic(api_key=api_key)
+        self.__api_key = api_key
+
+    @cached_property
+    def __client(self):
+        return Anthropic(api_key=self.__api_key)
+
+    def __get_pydantic_model(self, model_settings: ModelSettings | None) -> Model:
+        if model_settings is None:
+            raise ValueError("Model settings cannot be None")
+        model_name = model_settings.get("model")
+        if model_name is None:
+            raise ValueError("Model must be set cannot be None")
+
+        return AnthropicModel(model_name, api_key=self.__api_key)
+
+    async def request(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> tuple[ModelResponse, Usage]:
+        model = self.__get_pydantic_model(model_settings)
+        return await model.request(messages, model_settings, model_request_parameters)
+
+    async def request_stream(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> AsyncIterator[StreamedResponse]:
+        model = self.__get_pydantic_model(model_settings)
+        yield model.request_stream(messages, model_settings, model_request_parameters)
+
+    @property
+    def model_name(self) -> str:
+        return "Undetermined"
+
+    @property
+    def system(self) -> str:
+        return "anthropic"
 
     def __get_model_limit(self, model: str) -> int:
         # it is observed that the count tokens is not accurate, so we are using a safety margin
@@ -250,7 +294,7 @@ def is_prompt_supported(
             for k, v in input_kwargs.items()
             if k in {"messages", "model", "system", "tool_choice", "tools", "beta"}
         }
-        message_token_count = self.client.beta.messages.count_tokens(**count_token_input_kwargs)
+        message_token_count = self.__client.beta.messages.count_tokens(**count_token_input_kwargs)
         return model_limit - message_token_count.input_tokens
 
     def truncate_messages(
@@ -295,5 +339,5 @@ def chat_completion(
             top_p=top_p,
         )
 
-        response = self.client.messages.create(**input_kwargs)
+        response = self.__client.messages.create(**input_kwargs)
         return _anthropic_to_openai_response(model, response)
diff --git a/patchwork/common/client/llm/google.py b/patchwork/common/client/llm/google.py
index cdc653ab0..286d13327 100644
--- a/patchwork/common/client/llm/google.py
+++ b/patchwork/common/client/llm/google.py
@@ -25,7 +25,21 @@
 )
 from openai.types.chat.chat_completion import ChatCompletion, Choice
 from pydantic import BaseModel
-from typing_extensions import Any, Dict, Iterable, List, Optional, Type, Union
+from pydantic_ai.messages import ModelMessage, ModelResponse
+from pydantic_ai.models import Model, ModelRequestParameters, StreamedResponse
+from pydantic_ai.models.gemini import GeminiModel
+from pydantic_ai.settings import ModelSettings
+from pydantic_ai.usage import Usage
+from typing_extensions import (
+    Any,
+    AsyncIterator,
+    Dict,
+    Iterable,
+    List,
+    Optional,
+    Type,
+    Union,
+)
 
 from patchwork.common.client.llm.protocol import NOT_GIVEN, LlmClient, NotGiven
 from patchwork.common.client.llm.utils import json_schema_to_model
@@ -48,6 +62,41 @@ def __init__(self, api_key: str):
     def __get_models_info(self) -> list[Model]:
         return list(self.client.models.list())
 
+    def __get_pydantic_model(self, model_settings: ModelSettings | None) -> Model:
+        if model_settings is None:
+            raise ValueError("Model settings cannot be None")
+        model_name = model_settings.get("model")
+        if model_name is None:
+            raise ValueError("Model must be set cannot be None")
+
+        return GeminiModel(model_name, api_key=self.__api_key)
+
+    async def request(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> tuple[ModelResponse, Usage]:
+        model = self.__get_pydantic_model(model_settings)
+        return await model.request(messages, model_settings, model_request_parameters)
+
+    async def request_stream(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> AsyncIterator[StreamedResponse]:
+        model = self.__get_pydantic_model(model_settings)
+        yield model.request_stream(messages, model_settings, model_request_parameters)
+
+    @property
+    def model_name(self) -> str:
+        return "Undetermined"
+
+    @property
+    def system(self) -> str:
+        return "google-gla"
+
     def __get_model_limits(self, model: str) -> int:
         for model_info in self.__get_models_info():
             if model_info.name == f"{self.__MODEL_PREFIX}{model}" and model_info.input_token_limit is not None:
diff --git a/patchwork/common/client/llm/openai_.py b/patchwork/common/client/llm/openai_.py
index 42f6513b7..adcb27a2f 100644
--- a/patchwork/common/client/llm/openai_.py
+++ b/patchwork/common/client/llm/openai_.py
@@ -1,6 +1,7 @@
 from __future__ import annotations
 
 import functools
+from functools import cached_property
 from pathlib import Path
 
 import tiktoken
@@ -12,7 +13,12 @@
     ChatCompletionToolParam,
     completion_create_params,
 )
-from typing_extensions import Dict, Iterable, List, Optional, Union
+from pydantic_ai.messages import ModelMessage, ModelResponse
+from pydantic_ai.models import Model, ModelRequestParameters, StreamedResponse
+from pydantic_ai.models.openai import OpenAIModel
+from pydantic_ai.settings import ModelSettings
+from pydantic_ai.usage import Usage
+from typing_extensions import AsyncIterator, Dict, Iterable, List, Optional, Union
 
 from patchwork.common.client.llm.protocol import NOT_GIVEN, LlmClient, NotGiven
 from patchwork.logger import logger
@@ -42,20 +48,59 @@ class OpenAiLlmClient(LlmClient):
     }
 
     def __init__(self, api_key: str, base_url=None, **kwargs):
-        self.api_key = api_key
-        self.base_url = base_url
-        self.client = OpenAI(api_key=api_key, base_url=base_url, **kwargs)
+        self.__api_key = api_key
+        self.__base_url = base_url
+        self.__kwargs = kwargs
+
+    @cached_property
+    def __client(self) -> OpenAI:
+        return OpenAI(api_key=self.__api_key, base_url=self.__base_url, **self.__kwargs)
+
+    def __get_pydantic_model(self, model_settings: ModelSettings | None) -> Model:
+        if model_settings is None:
+            raise ValueError("Model settings cannot be None")
+        model_name = model_settings.get("model")
+        if model_name is None:
+            raise ValueError("Model must be set cannot be None")
+
+        return OpenAIModel(model_name, base_url=self.__base_url, api_key=self.__api_key)
+
+    async def request(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> tuple[ModelResponse, Usage]:
+        model = self.__get_pydantic_model(model_settings)
+        return await model.request(messages, model_settings, model_request_parameters)
+
+    async def request_stream(
+        self,
+        messages: list[ModelMessage],
+        model_settings: ModelSettings | None,
+        model_request_parameters: ModelRequestParameters,
+    ) -> AsyncIterator[StreamedResponse]:
+        model = self.__get_pydantic_model(model_settings)
+        yield model.request_stream(messages, model_settings, model_request_parameters)
+
+    @property
+    def model_name(self) -> str:
+        return "Undetermined"
+
+    @property
+    def system(self) -> str | None:
+        return "openai"
 
     def __is_not_openai_url(self):
         # Some providers/apis only implement the chat completion endpoint.
         # We mainly use this to skip using the model endpoints.
-        return self.base_url is not None and self.base_url != "https://api.openai.com/v1"
+        return self.__base_url is not None and self.__base_url != "https://api.openai.com/v1"
 
     def get_models(self) -> set[str]:
         if self.__is_not_openai_url():
             return set()
 
-        return _cached_list_models_from_openai(self.api_key)
+        return _cached_list_models_from_openai(self.__api_key)
 
     def is_model_supported(self, model: str) -> bool:
         # might not implement model endpoint
@@ -147,4 +192,4 @@ def chat_completion(
             top_p=top_p,
         )
 
-        return self.client.chat.completions.create(**NotGiven.remove_not_given(input_kwargs))
+        return self.__client.chat.completions.create(**NotGiven.remove_not_given(input_kwargs))
diff --git a/patchwork/common/client/llm/protocol.py b/patchwork/common/client/llm/protocol.py
index 3577b2102..c4c77e293 100644
--- a/patchwork/common/client/llm/protocol.py
+++ b/patchwork/common/client/llm/protocol.py
@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+from abc import abstractmethod
 from pathlib import Path
 
 from openai.types.chat import (
@@ -9,14 +10,15 @@
     ChatCompletionToolParam,
     completion_create_params,
 )
-from typing_extensions import Any, Dict, Iterable, List, Optional, Protocol, Union
+from pydantic_ai.models import Model
+from typing_extensions import Any, Dict, Iterable, List, Optional, Union
 
 
 class NotGiven:
     ...
 
     @staticmethod
-    def remove_not_given(obj: Any) -> Any:
+    def remove_not_given(obj: Any) -> Union[None, dict[Any, Any], list[Any], Any]:
         if isinstance(obj, NotGiven):
             return None
         if isinstance(obj, dict):
@@ -29,13 +31,16 @@ def remove_not_given(obj: Any) -> Any:
 NOT_GIVEN = NotGiven()
 
 
-class LlmClient(Protocol):
+class LlmClient(Model):
+    @abstractmethod
     def get_models(self) -> set[str]:
         ...
 
+    @abstractmethod
     def is_model_supported(self, model: str) -> bool:
         ...
 
+    @abstractmethod
     def is_prompt_supported(
         self,
         messages: Iterable[ChatCompletionMessageParam],
@@ -57,6 +62,7 @@ def is_prompt_supported(
     ) -> int:
         ...
 
+    @abstractmethod
     def truncate_messages(
         self, messages: Iterable[ChatCompletionMessageParam], model: str
     ) -> Iterable[ChatCompletionMessageParam]:
@@ -121,6 +127,7 @@ def __truncate_message(message, direction_callback, min_guess, max_guess):
 
         return LlmClient.__truncate_message(message, direction_callback, min_guess, max_guess)
 
+    @abstractmethod
     def chat_completion(
         self,
         messages: Iterable[ChatCompletionMessageParam],
diff --git a/patchwork/common/client/llm/utils.py b/patchwork/common/client/llm/utils.py
index afb06dfff..41358d759 100644
--- a/patchwork/common/client/llm/utils.py
+++ b/patchwork/common/client/llm/utils.py
@@ -1,12 +1,11 @@
 from __future__ import annotations
 
 import json
-from typing import Any, Dict, List, Optional, Type
 
 from openai.lib._parsing._completions import type_to_response_format_param
 from openai.types.chat.completion_create_params import ResponseFormat
 from pydantic import BaseModel, Field, create_model
-from typing_extensions import List
+from typing_extensions import Any, Dict, List, Optional, Type
 
 from patchwork.logger import logger
 
@@ -60,12 +59,7 @@ def example_json_to_schema(json_example: str | dict | None) -> ResponseFormat |
     if json_example is None:
         return None
 
-    base_model = None
-    if isinstance(json_example, str):
-        base_model = __example_string_to_base_model(json_example)
-    elif isinstance(json_example, dict):
-        base_model = __example_dict_to_base_model(json_example)
-
+    base_model = example_json_to_base_model(json_example)
     if base_model is None:
         return None
 
@@ -76,25 +70,38 @@ def base_model_to_schema(base_model: Type[BaseModel]) -> ResponseFormat:
     return type_to_response_format_param(base_model)
 
 
-def __example_string_to_base_model(json_example: str) -> Type[BaseModel] | None:
+def example_json_to_base_model(json_example: str | dict | None) -> Type[BaseModel] | None:
+    if json_example is None:
+        return None
+
+    base_model = None
+    if isinstance(json_example, str):
+        base_model = example_string_to_base_model(json_example)
+    elif isinstance(json_example, dict):
+        base_model = example_dict_to_base_model(json_example)
+
+    return base_model
+
+
+def example_string_to_base_model(json_example: str) -> Type[BaseModel] | None:
     try:
         example_data = json.loads(json_example)
     except Exception as e:
         logger.error(f"Failed to parse example json", e)
         return None
 
-    return __example_dict_to_base_model(example_data)
+    return example_dict_to_base_model(example_data)
 
 
-def __example_dict_to_base_model(example_data: dict) -> Type[BaseModel]:
+def example_dict_to_base_model(example_data: dict) -> Type[BaseModel]:
     base_model_field_defs: dict[str, tuple[type | BaseModel, Field]] = dict()
     for example_data_key, example_data_value in example_data.items():
         if isinstance(example_data_value, dict):
-            value_typing = __example_dict_to_base_model(example_data_value)
+            value_typing = example_dict_to_base_model(example_data_value)
         elif isinstance(example_data_value, list):
             nested_value = example_data_value[0]
             if isinstance(nested_value, dict):
-                nested_typing = __example_dict_to_base_model(nested_value)
+                nested_typing = example_dict_to_base_model(nested_value)
             else:
                 nested_typing = type(nested_value)
             value_typing = List[nested_typing]
diff --git a/patchwork/common/client/patched.py b/patchwork/common/client/patched.py
index 743b39828..da3dd4718 100644
--- a/patchwork/common/client/patched.py
+++ b/patchwork/common/client/patched.py
@@ -9,13 +9,13 @@
 from importlib import metadata
 from pathlib import Path
 from threading import Thread
-from typing import Any
 
 import click
 import requests
 from git.repo.base import Repo
 from requests import Response, Session
 from requests.adapters import DEFAULT_POOLBLOCK, HTTPAdapter
+from typing_extensions import Any
 from urllib3 import HTTPConnectionPool, HTTPSConnectionPool, PoolManager
 
 from patchwork.common.utils.user_config import get_user_config
diff --git a/patchwork/common/client/sonar.py b/patchwork/common/client/sonar.py
index e57fcb745..8d0cdc1d0 100644
--- a/patchwork/common/client/sonar.py
+++ b/patchwork/common/client/sonar.py
@@ -1,8 +1,10 @@
+from __future__ import annotations
+
 from collections import defaultdict
 from dataclasses import dataclass
-from typing import Optional, Union
 
 import requests
+from typing_extensions import Optional, Union
 
 
 @dataclass
diff --git a/patchwork/common/multiturn_strategy/agentic_strategy.py b/patchwork/common/multiturn_strategy/agentic_strategy.py
index b86fe1fe3..10b5a0aaa 100644
--- a/patchwork/common/multiturn_strategy/agentic_strategy.py
+++ b/patchwork/common/multiturn_strategy/agentic_strategy.py
@@ -23,6 +23,8 @@ def __init__(self, llm_client: LlmClient, tool_set: dict[str, Tool]):
         self.llm_client = llm_client
         self.tool_set = tool_set
         self.history: list[ChatCompletionMessageParam] = []
+        self.request_tokens = 0
+        self.response_tokens = 0
 
     def generate_reply(self, message: str) -> str:
         self.history.append(dict(role="user", content=message))
@@ -36,6 +38,9 @@ def generate_reply(self, message: str) -> str:
         if is_prompt_safe < 0:
             raise ValueError("The subsequent prompt is not supported, due to large size.")
         response = self.llm_client.chat_completion(**input_kwargs)
+        self.response_tokens = response.usage.completion_tokens
+        self.request_tokens = response.usage.prompt_tokens
+
         choices = response.choices or []
 
         message_content = ""
@@ -145,6 +150,17 @@ def __is_session_completed(self) -> bool:
 
         return False
 
+    def usage(self):
+        request_tokens = 0
+        response_tokens = 0
+        for role in [self.__assistant_role, self.__user_role]:
+            request_tokens += role.request_tokens
+            response_tokens += role.response_tokens
+        return {
+            "request_tokens": request_tokens,
+            "response_tokens": response_tokens,
+        }
+
     def execute(self, limit: int | None = None) -> None:
         message = self.__render_prompt(self.__user_prompt_template)
         try:
diff --git a/patchwork/common/multiturn_strategy/agentic_strategy_v2.py b/patchwork/common/multiturn_strategy/agentic_strategy_v2.py
new file mode 100644
index 000000000..5b33a23d1
--- /dev/null
+++ b/patchwork/common/multiturn_strategy/agentic_strategy_v2.py
@@ -0,0 +1,144 @@
+from __future__ import annotations
+
+import asyncio
+import logging
+import sys
+
+from pydantic import BaseModel
+from pydantic_ai import Agent
+from pydantic_ai.models.anthropic import AnthropicModel
+from pydantic_ai.result import RunResult
+from typing_extensions import Any, Dict, Optional, Union
+
+from patchwork.common.client.llm.utils import example_json_to_base_model
+from patchwork.common.tools import Tool
+from patchwork.common.utils.utils import mustache_render
+
+_COMPLETION_FLAG_ATTRIBUTE = "is_task_completed"
+_MESSAGE_ATTRIBUTE = "message"
+
+
+class AgentConfig(BaseModel):
+    class Config:
+        arbitrary_types_allowed = True
+
+    name: str
+    tool_set: Dict[str, Tool]
+    system_prompt: str = ""
+    example_json: Union[
+        str, Dict[str, Any]
+    ] = f'{{"{_MESSAGE_ATTRIBUTE}":"message", "{_COMPLETION_FLAG_ATTRIBUTE}": false}}'
+
+
+class AgenticStrategyV2:
+    def __init__(
+        self,
+        api_key: str,
+        template_data: dict[str, str],
+        system_prompt_template: str,
+        user_prompt_template: str,
+        agent_configs: list[AgentConfig],
+        example_json: Union[str, dict[str, Any]] = '{"output":"output text"}',
+        limit: Optional[int] = None,
+    ):
+        self.__limit = limit
+        self.__template_data = template_data
+        self.__user_prompt_template = user_prompt_template
+        model = AnthropicModel("claude-3-5-sonnet-latest", api_key=api_key)
+        self.__summariser = Agent(
+            model,
+            system_prompt=mustache_render(system_prompt_template, self.__template_data),
+            result_type=example_json_to_base_model(example_json),
+            model_settings=dict(parallel_tool_calls=False),
+        )
+        self.__agents = []
+        for agent_config in agent_configs:
+            tools = []
+            for tool in agent_config.tool_set.values():
+                tools.append(tool.to_pydantic_ai_function_tool())
+            agent = Agent(
+                model,
+                name=agent_config.name,
+                system_prompt=mustache_render(agent_config.system_prompt, self.__template_data),
+                tools=tools,
+                result_type=example_json_to_base_model(agent_config.example_json),
+                model_settings=dict(parallel_tool_calls=False),
+            )
+
+            self.__agents.append(agent)
+
+        self.__request_tokens = 0
+        self.__response_tokens = 0
+
+    def reset(self):
+        self.__request_tokens = 0
+        self.__response_tokens = 0
+
+    def usage(self):
+        return {
+            "request_tokens": self.__request_tokens,
+            "response_tokens": self.__response_tokens,
+        }
+
+    def execute(self, limit: Optional[int] = None) -> dict:
+        agents_result = dict()
+        loop = asyncio.new_event_loop()
+        try:
+            for index, agent in enumerate(self.__agents):
+                user_message = mustache_render(self.__user_prompt_template, self.__template_data)
+                message_history = None
+                agent_output = None
+                for i in range(limit or self.__limit or sys.maxsize):
+                    agent_output: RunResult[Any] = loop.run_until_complete(
+                        agent.run(user_message, message_history=message_history)
+                    )
+                    message_history = agent_output.all_messages()
+                    self.__request_tokens += agent_output.usage().request_tokens or 0
+                    self.__response_tokens += agent_output.usage().response_tokens or 0
+
+                    if getattr(agent_output.data, _COMPLETION_FLAG_ATTRIBUTE, False):
+                        break
+                    user_message = "Please continue"
+                agents_result[index] = agent_output
+        except Exception as e:
+            logging.error(e)
+
+        if len(agents_result) == 0:
+            return dict()
+
+        if len(agents_result) == 1:
+            final_result = loop.run_until_complete(
+                self.__summariser.run(
+                    "From the actions taken by the assistant. Please give me the result.",
+                    message_history=next(v for _, v in agents_result.items()).all_messages(),
+                )
+            )
+        else:
+            agent_summaries = []
+            for agent_result in agents_result.values():
+                agent_summary_result = loop.run_until_complete(
+                    self.__summariser.run(
+                        "From the actions taken by the assistant. Please give me the result.",
+                        message_history=agent_result.all_messages(),
+                    )
+                )
+                self.__request_token += agent_summary_result.usage().request_tokens or 0
+                self.__response_token += agent_summary_result.usage().response_tokens or 0
+
+                agent_summary = getattr(agent_summary_result.data, _MESSAGE_ATTRIBUTE, None)
+                if agent_summary is None:
+                    continue
+
+                agent_summaries.append(agent_summary)
+            agent_summary_list = "\n* " + "\n* ".join(agent_summaries)
+            final_result = loop.run_until_complete(
+                self.__summariser.run(
+                    "Please give me the result from the following summary of what the assistants have done."
+                    + agent_summary_list,
+                )
+            )
+        self.__request_tokens += final_result.usage().request_tokens or 0
+        self.__response_tokens += final_result.usage().response_tokens or 0
+
+        loop.close()
+        return final_result.data.dict()
diff --git a/patchwork/common/multiturn_strategy/analyze_implement.py b/patchwork/common/multiturn_strategy/analyze_implement.py
index 3686eaec6..16fa7ab46 100644
--- a/patchwork/common/multiturn_strategy/analyze_implement.py
+++ b/patchwork/common/multiturn_strategy/analyze_implement.py
@@ -40,6 +40,14 @@ def _reset(self):
         self._stage = STAGE.ANALYSIS
         self.run_count = 0
         self.stage_run_counts = defaultdict(int)
+        self.__request_tokens = 0
+        self.__response_tokens = 0
+
+    def usage(self):
+        return dict(
+            request_tokens=self.__request_tokens,
+            response_tokens=self.__response_tokens,
+        )
 
     def __run_prompt(self, messages: list[ChatCompletionMessageParam]) -> list[ChatCompletionMessageParam]:
         input_kwargs = dict(
@@ -52,6 +60,8 @@ def __run_prompt(self, messages: list[ChatCompletionMessageParam]) -> list[ChatC
         if is_prompt_safe < 0:
             raise ValueError("The subsequent prompt is not supported, due to large size.")
         response = self.llm_client.chat_completion(**input_kwargs)
+        self.__request_tokens += response.usage.prompt_tokens
+        self.__response_tokens += response.usage.response_tokens
         new_messages = [choice.message.to_dict() for choice in response.choices]
         messages.extend(new_messages)
         return messages
diff --git a/patchwork/common/tools/__init__.py b/patchwork/common/tools/__init__.py
index e813cb9d9..1501b3687 100644
--- a/patchwork/common/tools/__init__.py
+++ b/patchwork/common/tools/__init__.py
@@ -1,9 +1,13 @@
 from patchwork.common.tools.bash_tool import BashTool
-from patchwork.common.tools.code_edit_tools import CodeEditTool
+from patchwork.common.tools.code_edit_tools import CodeEditTool, FileViewTool
+from patchwork.common.tools.grep_tool import FindTextTool, FindTool
 from patchwork.common.tools.tool import Tool
 
 __all__ = [
     "Tool",
     "CodeEditTool",
     "BashTool",
+    "FileViewTool",
+    "FindTool",
+    "FindTextTool",
 ]
diff --git a/patchwork/common/tools/bash_tool.py b/patchwork/common/tools/bash_tool.py
index 77e9052ae..8440f179a 100644
--- a/patchwork/common/tools/bash_tool.py
+++ b/patchwork/common/tools/bash_tool.py
@@ -3,6 +3,8 @@
 import subprocess
 from pathlib import Path
 
+from typing_extensions import Optional
+
 from patchwork.common.tools.tool import Tool
 
 
@@ -35,9 +37,7 @@ def json_schema(self) -> dict:
 
     def execute(
         self,
-        command: str | None = None,
-        *args,
-        **kwargs,
+        command: Optional[str] = None,
     ) -> str:
         """Execute editor commands on files in the repository."""
         if command is None:
diff --git a/patchwork/common/tools/code_edit_tools.py b/patchwork/common/tools/code_edit_tools.py
index 48c7701b0..bb576960a 100644
--- a/patchwork/common/tools/code_edit_tools.py
+++ b/patchwork/common/tools/code_edit_tools.py
@@ -1,14 +1,94 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import Literal
+
+from typing_extensions import Literal, Optional, Union
 
 from patchwork.common.tools.tool import Tool
 from patchwork.common.utils.utils import detect_newline
 
 
+class FileViewTool(Tool, tool_name="file_view"):
+    __TRUNCATION_TOKEN = "<TRUNCATED>"
+    __VIEW_LIMIT = 3000
+
+    def __init__(self, path: Union[Path, str]):
+        super().__init__()
+        self.repo_path = Path(path).resolve()
+
+    @property
+    def json_schema(self) -> dict:
+        return {
+            "name": "file_view",
+            "description": f"""\
+Custom tool for viewing files
+    
+* If `path` is a file, `view` displays the result of applying `cat -n` up to {self.__VIEW_LIMIT} characters. If `path` is a directory, `view` lists non-hidden files and directories.
+* The output is too lone, it will be truncated and marked with `{self.__TRUNCATION_TOKEN}`
+* The working directory is always {self.repo_path}
+""",
+            "input_schema": {
+                "type": "object",
+                "properties": {
+                    "path": {
+                        "description": "Absolute path to file or directory, e.g. `/repo/file.py` or `/repo`.",
+                        "type": "string",
+                    },
+                    "view_range": {
+                        "description": "Optional parameter when `path` points to a file. If none is given, the full file is shown. If provided, the file will be shown in the indicated line number range, e.g. [11, 12] will show lines 11 and 12. Indexing at 1 to start. Setting `[start_line, -1]` shows all lines from `start_line` to the end of the file.",
+                        "items": {"type": "integer"},
+                        "type": "array",
+                    },
+                },
+                "required": ["path"],
+            },
+        }
+
+    def __get_abs_path(self, path: str):
+        wanted_path = Path(path).resolve()
+        if wanted_path.is_relative_to(self.repo_path):
+            return wanted_path
+        else:
+            raise ValueError(f"Path {path} contains illegal path traversal")
+
+    def execute(self, path: str, view_range: Optional[list[int]] = None) -> str:
+        abs_path = self.__get_abs_path(path)
+        if not abs_path.exists():
+            return f"Error: Path {abs_path} does not exist"
+
+        if abs_path.is_file():
+            with open(abs_path, "r") as f:
+                content = f.read()
+
+            if view_range:
+                lines = content.splitlines()
+                start, end = view_range
+                content = "\n".join(lines[start - 1 : end])
+
+            if len(content) > self.__VIEW_LIMIT:
+                content = content[: self.__VIEW_LIMIT] + self.__TRUNCATION_TOKEN
+            return content
+        elif abs_path.is_dir():
+            directories = []
+            files = []
+            for file in abs_path.iterdir():
+                directories.append(file.name) if file.is_dir() else files.append(file.name)
+
+            rv = ""
+            if len(directories) > 0:
+                rv += "Directories: \n"
+                rv += "\n".join(directories)
+                rv += "\n"
+
+            if len(files) > 0:
+                rv += "Files: \n"
+                rv += "\n".join(files)
+
+            return rv
+
+
 class CodeEditTool(Tool, tool_name="code_edit_tool"):
-    def __init__(self, path: Path | str):
+    def __init__(self, path: Union[Path, str]):
         super().__init__()
         self.repo_path = Path(path).resolve()
         self.modified_files = set()
@@ -21,9 +101,7 @@ def json_schema(self) -> dict:
 Custom editing tool for viewing, creating and editing files
 
 * State is persistent across command calls and discussions with the user
-* If `path` is a file, `view` displays the result of applying `cat -n`. If `path` is a directory, `view` lists non-hidden files and directories up to 2 levels deep
 * The `create` command cannot be used if the specified `path` already exists as a file
-* If a `command` generates a long output, it will be truncated and marked with `<response clipped>`
 * The working directory is always {self.repo_path}
 
 Notes for using the `str_replace` command:
@@ -35,8 +113,8 @@ def json_schema(self) -> dict:
                 "properties": {
                     "command": {
                         "type": "string",
-                        "enum": ["view", "create", "str_replace", "insert"],
-                        "description": "The commands to run. Allowed options are: `view`, `create`, `str_replace`, `insert`.",
+                        "enum": ["create", "str_replace", "insert"],
+                        "description": "The commands to run. Allowed options are: `create`, `str_replace`, `insert`.",
                     },
                     "file_text": {
                         "description": "Required parameter of `create` command, with the content of the file to be created.",
@@ -58,11 +136,6 @@ def json_schema(self) -> dict:
                         "description": "Absolute path to file or directory, e.g. `/repo/file.py` or `/repo`.",
                         "type": "string",
                     },
-                    "view_range": {
-                        "description": "Optional parameter of `view` command when `path` points to a file. If none is given, the full file is shown. If provided, the file will be shown in the indicated line number range, e.g. [11, 12] will show lines 11 and 12. Indexing at 1 to start. Setting `[start_line, -1]` shows all lines from `start_line` to the end of the file.",
-                        "items": {"type": "integer"},
-                        "type": "array",
-                    },
                 },
                 "required": ["command", "path"],
             },
@@ -70,15 +143,12 @@ def json_schema(self) -> dict:
 
     def execute(
         self,
-        command: Literal["view", "create", "str_replace", "insert"] | None = None,
+        command: Optional[Literal["create", "str_replace", "insert"]] = None,
         file_text: str = "",
-        insert_line: int | None = None,
+        insert_line: Optional[int] = None,
         new_str: str = "",
-        old_str: str | None = None,
-        path: str | None = None,
-        view_range: list[int] | None = None,
-        *args,
-        **kwargs,
+        old_str: Optional[str] = None,
+        path: Optional[str] = None,
     ) -> str:
         """Execute editor commands on files in the repository."""
         required_dict = dict(command=command, path=path)
@@ -88,9 +158,7 @@ def execute(
 
         try:
             abs_path = self.__get_abs_path(path)
-            if command == "view":
-                result = self.__view(abs_path, view_range)
-            elif command == "create":
+            if command == "create":
                 result = self.__create(file_text, abs_path)
             elif command == "str_replace":
                 result = self.__str_replace(new_str, old_str, abs_path)
@@ -101,9 +169,7 @@ def execute(
         except Exception as e:
             return f"Error: {str(e)}"
 
-        if command in {"create", "str_replace", "insert"}:
-            self.modified_files.update({abs_path})
-
+        self.modified_files.update({abs_path})
         return result
 
     @property
@@ -117,37 +183,6 @@ def __get_abs_path(self, path: str):
         else:
             raise ValueError(f"Path {path} contains illegal path traversal")
 
-    def __view(self, abs_path: Path, view_range):
-        if not abs_path.exists():
-            return f"Error: Path {abs_path} does not exist"
-
-        if abs_path.is_file():
-            with open(abs_path, "r") as f:
-                content = f.read()
-
-            if view_range:
-                lines = content.splitlines()
-                start, end = view_range
-                content = "\n".join(lines[start - 1 : end])
-            return content
-        elif abs_path.is_dir():
-            directories = []
-            files = []
-            for file in abs_path.iterdir():
-                directories.append(file.name) if file.is_dir() else files.append(file.name)
-
-            rv = ""
-            if len(directories) > 0:
-                rv += "Directories: \n"
-                rv += "\n".join(directories)
-                rv += "\n"
-
-            if len(files) > 0:
-                rv += "Files: \n"
-                rv += "\n".join(files)
-
-            return rv
-
     def __create(self, file_text, abs_path):
         if abs_path.exists():
             return f"Error: File {abs_path} already exists"
diff --git a/patchwork/common/tools/grep_tool.py b/patchwork/common/tools/grep_tool.py
new file mode 100644
index 000000000..ac173875d
--- /dev/null
+++ b/patchwork/common/tools/grep_tool.py
@@ -0,0 +1,187 @@
+from __future__ import annotations
+
+import fnmatch
+import itertools
+import os
+from pathlib import Path
+
+from typing_extensions import Optional
+
+from patchwork.common.tools.tool import Tool
+
+
+class FindTool(Tool, tool_name="find_files"):
+    def __init__(self, path: Path | str, **kwargs):
+        self.__working_dir = Path(path).resolve()
+
+    @property
+    def json_schema(self) -> dict:
+        return {
+            "name": "find_files",
+            "description": f"""\
+Tool to find files in {self.__working_dir} using a pattern based on the Unix shell style.
+Unix shell style:
+    *       matches everything
+    ?       matches any single character
+    [seq]   matches any character in seq
+    [!seq]  matches any char not in seq
+
+""",
+            "input_schema": {
+                "type": "object",
+                "properties": {
+                    "pattern": {
+                        "description": """\
+The Unix shell style pattern to match files using.
+
+Unix shell style:
+    *       matches everything
+    ?       matches any single character
+    [seq]   matches any character in seq
+    [!seq]  matches any char not in seq
+
+Example:
+* '*macs' will match the file '.emacs'
+* '*.py' will match all files with the '.py' extension
+""",
+                        "type": "string",
+                    },
+                    "depth": {
+                        "description": "The maximum depth files in directories to look for. Default is 1.",
+                        "type": "integer",
+                    },
+                    "is_case_sensitive": {
+                        "description": "Whether the pattern should be case-sensitive.",
+                        "type": "boolean",
+                    },
+                },
+                "required": ["pattern"],
+            },
+        }
+
+    def __is_dot(self, path: Path | str) -> bool:
+        return any(part.startswith(".") for part in path.relative_to(self.__working_dir).parts)
+
+    def execute(self, pattern: Optional[str] = None, depth: int = 1, is_case_sensitive: bool = False) -> str:
+        if pattern is None:
+            raise ValueError("Pattern argument is required!")
+
+        matcher = fnmatch.fnmatch
+        if is_case_sensitive:
+            matcher = fnmatch.fnmatchcase
+
+        file_matches = []
+        dir_matches = []
+        for root, dirs, files in os.walk(self.__working_dir):
+            root_path = Path(root)
+            if len(root_path.resolve().relative_to(self.__working_dir).parts) > depth:
+                continue
+
+            for file in itertools.chain(dirs, files):
+                file_path = root_path / file
+                if self.__is_dot(file_path):
+                    continue
+
+                if file_path.is_file():
+                    list_to_append = file_matches
+                else:
+                    list_to_append = dir_matches
+
+                if matcher(str(file_path), pattern):
+                    relative_file_path = file_path.relative_to(self.__working_dir)
+                    list_to_append.append(str(relative_file_path))
+
+        delim = "\n  * "
+        files_part = (delim + delim.join(file_matches)) if len(file_matches) > 0 else "\n  No files found"
+        dirs_part = (delim + delim.join(dir_matches)) if len(dir_matches) > 0 else "\n  No directories found"
+        return f"""\
+Files:{files_part}
+
+Directories:{dirs_part}
+
+"""
+
+
+class FindTextTool(Tool, tool_name="find_text"):
+    __CHAR_LIMIT = 200
+    __CHAR_LIMIT_TEXT = "<Too many characters>"
+
+    def __init__(self, path: Path | str, **kwargs):
+        self.__working_dir = Path(path).resolve()
+
+    @property
+    def json_schema(self) -> dict:
+        return {
+            "name": "find_text",
+            "description": f"""\
+Tool to find text in a file using a pattern based on the Unix shell style.
+The current working directory is always {self.__working_dir}. 
+The path provided should either be absolute or relative to the current working directory.
+
+This tool will match each line of the file with the provided pattern and prints the line number and the line content.
+If the line contains more than {self.__CHAR_LIMIT} characters, the line content will be replaced with {self.__CHAR_LIMIT_TEXT}.
+""",
+            "input_schema": {
+                "type": "object",
+                "properties": {
+                    "path": {
+                        "description": "The path to the file to find text in.",
+                        "type": "string",
+                    },
+                    "pattern": {
+                        "description": """\
+The Unix shell style pattern to match files using.
+
+Unix shell style:
+    *       matches everything
+    ?       matches any single character
+    [seq]   matches any character in seq
+    [!seq]  matches any char not in seq
+
+Example:
+* '*macs' will match the file '.emacs'
+* '*.py' will match all files with the '.py' extension
+""",
+                        "type": "string",
+                    },
+                    "is_case_sensitive": {
+                        "description": "Whether the pattern should be case-sensitive.",
+                        "type": "boolean",
+                    },
+                },
+                "required": ["path", "pattern"],
+            },
+        }
+
+    def execute(
+        self,
+        path: Optional[Path] = None,
+        pattern: Optional[str] = None,
+        is_case_sensitive: bool = False,
+    ) -> str:
+        if path is None:
+            raise ValueError("Path argument is required!")
+
+        if pattern is None:
+            raise ValueError("pattern argument is required!")
+
+        matcher = fnmatch.fnmatch
+        if is_case_sensitive:
+            matcher = fnmatch.fnmatchcase
+
+        path = Path(path).resolve()
+        if not path.is_relative_to(self.__working_dir):
+            raise ValueError("Path must be relative to working dir")
+
+        matches = []
+        with path.open("r") as f:
+            for i, line in enumerate(f.readlines()):
+                if not matcher(line, pattern):
+                    continue
+
+                content = f"Line {i + 1}: {line}"
+                if len(line) > self.__CHAR_LIMIT:
+                    content = f"Line {i + 1}: {self.__CHAR_LIMIT_TEXT}"
+
+                matches.append(content)
+        return f"Pattern matches found in '{path}':\n" + "\n".join(matches)
diff --git a/patchwork/common/tools/tool.py b/patchwork/common/tools/tool.py
index f9011c14b..d13ac38fd 100644
--- a/patchwork/common/tools/tool.py
+++ b/patchwork/common/tools/tool.py
@@ -1,5 +1,9 @@
 from abc import ABC, abstractmethod
-from typing import Type
+
+from pydantic_ai.tools import RunContext
+from pydantic_ai.tools import Tool as PydanticTool
+from pydantic_ai.tools import ToolDefinition
+from typing_extensions import Type
 
 
 class Tool(ABC):
@@ -36,9 +40,18 @@ def get_tools(**kwargs) -> dict[str, "Tool"]:
         return rv
 
     @staticmethod
-    def get_description(tooling: "ToolProtocol") -> str:
+    def get_description(tooling: "Tool") -> str:
         return tooling.json_schema.get("description", "")
 
     @staticmethod
-    def get_parameters(tooling: "ToolProtocol") -> str:
+    def get_parameters(tooling: "Tool") -> str:
         return ", ".join(tooling.json_schema.get("required", []))
+
+    def to_pydantic_ai_function_tool(self) -> PydanticTool[None]:
+        async def _prep(ctx: RunContext[None], tool_def: ToolDefinition) -> ToolDefinition:
+            tool_def.parameters_json_schema = self.json_schema.get("input_schema", {})
+            return tool_def
+
+        return PydanticTool(
+            self.execute, prepare=_prep, name=self.name, description=self.json_schema.get("description", "")
+        )
diff --git a/patchwork/patchflow.py b/patchwork/patchflow.py
index 27c53ceb9..be4983382 100644
--- a/patchwork/patchflow.py
+++ b/patchwork/patchflow.py
@@ -1,7 +1,7 @@
 import abc
-from typing import Type
 
 import click
+from typing_extensions import Type
 
 _internal_map: dict[str, Type["Patchflow"]]
 
diff --git a/patchwork/patchflows/GenerateDocstring/GenerateDocstring.py b/patchwork/patchflows/GenerateDocstring/GenerateDocstring.py
index 9f81787b7..108d02d24 100644
--- a/patchwork/patchflows/GenerateDocstring/GenerateDocstring.py
+++ b/patchwork/patchflows/GenerateDocstring/GenerateDocstring.py
@@ -1,9 +1,9 @@
 from __future__ import annotations
 
 from pathlib import Path
-from typing import Any
 
 import yaml
+from typing_extensions import Any
 
 from patchwork.common.utils.progress_bar import PatchflowProgressBar
 from patchwork.common.utils.step_typing import validate_steps_with_inputs
diff --git a/patchwork/patchflows/LogAnalysis/LogAnalysis.py b/patchwork/patchflows/LogAnalysis/LogAnalysis.py
new file mode 100644
index 000000000..d2450df78
--- /dev/null
+++ b/patchwork/patchflows/LogAnalysis/LogAnalysis.py
@@ -0,0 +1,91 @@
+import json
+import os
+from pathlib import Path
+
+import yaml
+
+from patchwork.common.utils.progress_bar import PatchflowProgressBar
+from patchwork.common.utils.step_typing import validate_steps_with_inputs
+from patchwork.logger import logger
+from patchwork.step import Step
+from patchwork.steps import AgenticLLMV2
+
+_DEFAULT_INPUT_FILE = Path(__file__).parent / "defaults.yml"
+
+
+class LogAnalysis(Step):
+    def __init__(self, inputs: dict):
+        PatchflowProgressBar(self).register_steps(
+            AgenticLLMV2,
+        )
+        final_inputs = yaml.safe_load(_DEFAULT_INPUT_FILE.read_text()) or dict()
+        final_inputs.update(inputs)
+
+        validate_steps_with_inputs(
+            set(final_inputs.keys()).union({""}),
+            AgenticLLMV2,
+        )
+
+        self.inputs = final_inputs
+
+    def run(self) -> dict:
+        for i in range(self.inputs.get("analysis_limit") or 5):
+            # for i in range(self.inputs.get("log_finding_limit") or sys.maxsize):
+            logs_detection_output = AgenticLLMV2(
+                dict(
+                    max_agent_calls=5,
+                    agent_system_prompt="""\
+You are a Senior software engineer trying to debug a issue. 
+You are provided with the relevant logs in files in the current directory.
+Explore the logs and reply with the relevant logs position, the file path and line number.  
+""",
+                    user_prompt=f"""\
+Logs are uploaded to the current working directory at {os.getcwd()}.
+
+{self.inputs.get('query')}
+""",
+                    example_json="""
+{
+  "logs":[
+    {
+        "file_path": "path to log file", 
+        "line_number": 10
+    }
+  ]
+}
+""",
+                    **self.inputs,
+                )
+            ).run()
+
+            analysis_output = AgenticLLMV2(
+                dict(
+                    max_agent_calls=5,
+                    prompt_value=logs_detection_output,
+                    agent_system_prompt="""\
+You are a senior software engineer trying to debug a issue. 
+You are provided with file paths and their line number.
+Review the logs and analyze if the logs are relevant or enough to debug the issue.
+If the provided logs are enough set 'is_log_analysis_done' to true.
+""",
+                    user_prompt="""\
+Should we reevaluate the logs:
+{{logs}}
+""",
+                    example_json="""\
+{
+  "message": "Message about missing or irrelevant logs to analyze or a success message", 
+  "is_log_analysis_done": true
+}
+""",
+                    **self.inputs,
+                )
+            ).run()
+
+            if analysis_output.get("is_log_analysis_done", False):
+                break
+
+        logger.info("Log Analysis Complete")
+        logger.info("Message:")
+        logger.info(json.dumps(analysis_output.get("message")))
+        return dict()
diff --git a/patchwork/patchflows/LogAnalysis/defaults.yml b/patchwork/patchflows/LogAnalysis/defaults.yml
new file mode 100644
index 000000000..2f1f63404
--- /dev/null
+++ b/patchwork/patchflows/LogAnalysis/defaults.yml
@@ -0,0 +1 @@
+query: ""
\ No newline at end of file
diff --git a/patchwork/patchflows/__init__.py b/patchwork/patchflows/__init__.py
index 93af42023..a2b792781 100644
--- a/patchwork/patchflows/__init__.py
+++ b/patchwork/patchflows/__init__.py
@@ -5,6 +5,7 @@
 from .GenerateDocstring.GenerateDocstring import GenerateDocstring
 from .GenerateREADME.GenerateREADME import GenerateREADME
 from .GenerateUnitTests.GenerateUnitTests import GenerateUnitTests
+from .LogAnalysis.LogAnalysis import LogAnalysis
 from .PRReview.PRReview import PRReview
 from .ResolveIssue.ResolveIssue import ResolveIssue
 from .SonarFix.SonarFix import SonarFix
@@ -20,4 +21,5 @@
     "GenerateDiagram",
     "GenerateCodeUsageExample",
     "SonarFix",
+    "LogAnalysis",
 ]
diff --git a/patchwork/steps/AgenticLLM/AgenticLLM.py b/patchwork/steps/AgenticLLM/AgenticLLM.py
index 77bbc5a92..0eab3871e 100644
--- a/patchwork/steps/AgenticLLM/AgenticLLM.py
+++ b/patchwork/steps/AgenticLLM/AgenticLLM.py
@@ -27,4 +27,5 @@ def run(self) -> dict:
         return dict(
             conversation_history=self.agentic_strategy.history,
             tool_records=self.agentic_strategy.tool_records,
+            **self.agentic_strategy.usage(),
         )
diff --git a/patchwork/steps/AgenticLLM/README.md b/patchwork/steps/AgenticLLM/README.md
new file mode 100644
index 000000000..4db9d9b8d
--- /dev/null
+++ b/patchwork/steps/AgenticLLM/README.md
@@ -0,0 +1,48 @@
+# Documentation for Agentic LLM Code
+
+## Overview
+
+The Agentic LLM module appears to be part of the `patchwork` package designed to handle Large Language Model (LLM) interactions using a predefined agentic strategy. This implementation facilitates the elicitation of responses from a language model, manages API keys, and defines the input and output data structures for the interactions.
+
+### Structure
+
+The module is organized as follows:
+
+- **`__init__.py`**: An empty initialization file to make the directory a package.
+- **`typed.py`**: Defines the input and output data types for the agentic LLM process.
+- **`AgenticLLM.py`**: Implements the main logic for the agentic LLM step, utilizing an agentic strategy and multi-turn interactions with a language model.
+
+## Detailed Description
+
+### File: `typed.py`
+
+#### Inputs
+
+- **`base_path`**: (Optional) The base path for accessing necessary tools.
+- **`prompt_value`**: A dictionary that contains dynamic values for templated prompts.
+- **`system_prompt`**: A string used as a system prompt template.
+- **`user_prompt`**: A string used as a user prompt template.
+- **`max_llm_calls`**: An integer that indicates the maximum number of LLM API calls allowed. It is treated as a configuration parameter.
+- **API Keys**: Includes `openai_api_key`, `anthropic_api_key`, `patched_api_key`, and `google_api_key`. These configurations allow different API keys to be specified for integrations with various LLM services.
+
+#### Outputs
+
+- **`conversation_history`**: A list of dictionaries tracking the conversation steps with the model.
+- **`tool_records`**: A list of dictionaries containing records of tool usage during interactions.
+- **`request_tokens`**: An integer indicating the number of tokens sent in requests.
+- **`response_tokens`**: An integer showing the number of tokens received in responses.
+
+### File: `AgenticLLM.py`
+
+#### Functionality
+
+- **Initialization**: The class initializes by configuring the LLM client and toolset for interaction. It uses the provided input configuration to create an agentic strategy.
+- **Execution**: The `run` method executes the agentic strategy with a set conversation limit. It returns structured output data including conversation history and tool usage statistics.
+
+#### Usage
+
+The `AgenticLLM` class is likely used in scenarios where automated and dynamic interaction with a language model is needed. The inputs are configured to adjust queries dynamically, and the comprehensive configuration support ensures flexible integration across multiple API providers.
+
+---
+
+This documentation is intended to offer a comprehensive overview and guide for developers working with or extending the functionality of the AgenticLLM module within the `patchwork` framework.
diff --git a/patchwork/steps/AgenticLLM/typed.py b/patchwork/steps/AgenticLLM/typed.py
index 5e698215a..597fd2078 100644
--- a/patchwork/steps/AgenticLLM/typed.py
+++ b/patchwork/steps/AgenticLLM/typed.py
@@ -38,5 +38,5 @@ class AgenticLLMInputs(TypedDict, total=False):
 class AgenticLLMOutputs(TypedDict):
     conversation_history: List[Dict]
     tool_records: List[Dict]
-    # request_tokens: int
-    # response_tokens: int
+    request_tokens: int
+    response_tokens: int
diff --git a/patchwork/steps/AgenticLLMV2/AgenticLLMV2.py b/patchwork/steps/AgenticLLMV2/AgenticLLMV2.py
new file mode 100644
index 000000000..584124b7c
--- /dev/null
+++ b/patchwork/steps/AgenticLLMV2/AgenticLLMV2.py
@@ -0,0 +1,36 @@
+from pathlib import Path
+
+from patchwork.common.multiturn_strategy.agentic_strategy_v2 import (
+    AgentConfig,
+    AgenticStrategyV2,
+)
+from patchwork.common.tools import Tool
+from patchwork.step import Step
+from patchwork.steps.AgenticLLMV2.typed import AgenticLLMV2Inputs, AgenticLLMV2Outputs
+
+
+class AgenticLLMV2(Step, input_class=AgenticLLMV2Inputs, output_class=AgenticLLMV2Outputs):
+    def __init__(self, inputs):
+        super().__init__(inputs)
+        base_path = inputs.get("base_path")
+        if base_path is None:
+            base_path = str(Path.cwd())
+        self.conversation_limit = int(inputs.get("max_agent_calls", 1))
+        self.agentic_strategy = AgenticStrategyV2(
+            api_key=inputs.get("anthropic_api_key"),
+            template_data=inputs.get("prompt_value", {}),
+            system_prompt_template=inputs.get("system_prompt", "Summarise from our previous conversation"),
+            user_prompt_template=inputs.get("user_prompt"),
+            agent_configs=[
+                AgentConfig(
+                    name="Assistant",
+                    tool_set=Tool.get_tools(path=base_path),
+                    system_prompt=inputs.get("agent_system_prompt"),
+                )
+            ],
+            example_json=inputs.get("example_json"),
+        )
+
+    def run(self) -> dict:
+        result = self.agentic_strategy.execute(limit=self.conversation_limit)
+        return {**result, **self.agentic_strategy.usage()}
diff --git a/patchwork/steps/AgenticLLMV2/README.md b/patchwork/steps/AgenticLLMV2/README.md
new file mode 100644
index 000000000..884aadb4b
--- /dev/null
+++ b/patchwork/steps/AgenticLLMV2/README.md
@@ -0,0 +1,52 @@
+# AgenticLLMV2 Module Documentation
+
+## Overview
+The `AgenticLLMV2` module provides a step for executing a multi-turn conversation strategy using the `AgenticStrategyV2` framework. This is part of a system that involves complex conversational models and tool integrations. The module is composed of three scripts: an initializer, the main class implementation, and type definitions for controlled inputs and outputs.
+
+## Components
+
+### 1. AgenticLLMV2/__init__.py
+This script is an initializer for the `AgenticLLMV2` module. It currently contains no code but serves to correctly package the Python files in this directory.
+
+### 2. AgenticLLMV2/AgenticLLMV2.py
+
+#### Description
+This file implements the `AgenticLLMV2` class, which extends the `Step` class and is responsible for managing the setup and execution of an `AgenticStrategyV2` conversation process.
+
+#### Inputs
+
+- `base_path` (str): The base path for tool configurations. Defaults to the current working directory if not specified.
+- `prompt_value` (Dict[str, Any]): Template data used in the prompts.
+- `system_prompt` (str): The system prompt used if not overridden.
+- `user_prompt` (str): Prompt provided for user-specific queries.
+- `max_agent_calls` (int): Maximum number of turns for agent calls. Defaults to 1.
+- `anthropic_api_key` (str): API key for Anthropic.
+- `agent_system_prompt` (str): Custom system prompt for agents.
+- `example_json` (str): JSON format data for prompt examples.
+
+#### Outputs
+
+- `request_tokens` (int): The number of tokens in the request.
+- `response_tokens` (int): The number of tokens in the response.
+
+#### Usage
+To use the `AgenticLLMV2` class, instantiate it with `AgenticLLMV2Inputs`, then call the `run()` method to perform the conversation operations. It integrates tools found at the specified base path and supports a configurable number of conversation turns.
+
+### 3. AgenticLLMV2/typed.py
+
+#### Description
+This script defines the data types used for input and output of the `AgenticLLMV2` class using Python's `TypedDict` for structured data handling.
+
+#### Inputs
+- Inputs are defined in `AgenticLLMV2Inputs` which includes optional attributes such as `base_path`, `prompt_value`, and more, facilitating flexible configuration of the agent strategy.
+
+#### Outputs
+- Outputs are defined in `AgenticLLMV2Outputs`, ensuring that only request and response token counts are recorded as outputs.
+
+## How to Use
+1. Define input parameters using `AgenticLLMV2Inputs`.
+2. Initialize the `AgenticLLMV2` class with these inputs.
+3. Execute the `run()` method to process a conversation based on the configured strategy.
+4. Analyze the token usage from the outputs to understand usage and billing metrics if needed.
+
+This module is useful for developers working on advanced AI conversational systems, offering customization and detailed control over conversation flows and tools used within those flows.
diff --git a/patchwork/steps/AgenticLLMV2/__init__.py b/patchwork/steps/AgenticLLMV2/__init__.py
new file mode 100644
index 000000000..e69de29bb
diff --git a/patchwork/steps/AgenticLLMV2/typed.py b/patchwork/steps/AgenticLLMV2/typed.py
new file mode 100644
index 000000000..0cdd56c3c
--- /dev/null
+++ b/patchwork/steps/AgenticLLMV2/typed.py
@@ -0,0 +1,19 @@
+from typing_extensions import Annotated, Any, Dict, TypedDict
+
+from patchwork.common.utils.step_typing import StepTypeConfig
+
+
+class AgenticLLMV2Inputs(TypedDict, total=False):
+    base_path: str
+    prompt_value: Dict[str, Any]
+    system_prompt: str
+    user_prompt: str
+    max_agent_calls: Annotated[int, StepTypeConfig(is_config=True)]
+    anthropic_api_key: str
+    agent_system_prompt: str
+    example_json: str
+
+
+class AgenticLLMV2Outputs(TypedDict):
+    request_tokens: int
+    response_tokens: int
diff --git a/patchwork/steps/CallSQL/README.md b/patchwork/steps/CallSQL/README.md
new file mode 100644
index 000000000..4f171c968
--- /dev/null
+++ b/patchwork/steps/CallSQL/README.md
@@ -0,0 +1,80 @@
+# CallSQL Module Documentation
+
+The `CallSQL` module is designed to facilitate interaction with a SQL database by executing SQL queries and fetching results. This functionality is particularly useful for integrating database operations within a larger data processing or ETL pipeline.
+
+## Components
+
+The `CallSQL` module consists of three primary components:
+
+1. **CallSQL.py**: Contains the main logic for executing a SQL query and fetching results.
+2. **\_\_init\_\_.py**: Initializes the module (empty in this case, can be used for package-level imports or initial setup).
+3. **typed.py**: Defines input and output data structures using typed dictionaries.
+
+## File: CallSQL.py
+
+### Description
+
+The `CallSQL` class inherits from the `Step` base class and is responsible for running a SQL query against a specified database. It uses SQLAlchemy to manage database connections and execute queries.
+
+### Inputs
+
+- **db_query**: (str) The SQL query to be executed.
+- **db_dialect**: (str) The type of SQL dialect (e.g., 'postgresql', 'mysql').
+- **db_driver**: (Optional[str]) The specific driver for the database dialect.
+- **db_username**: (Optional[str]) Username for database authentication.
+- **db_password**: (Optional[str]) Password for database authentication.
+- **db_host**: (Optional[str]) Database host, default is 'localhost'.
+- **db_port**: (Optional[int]) Port number for database connection, default is 5432.
+- **db_database**: (Optional[str]) Name of the database to connect to.
+- **db_params**: (Optional[dict[str, Any]]) Additional parameters for the database connection.
+- **db_driver_args**: (Optional[dict[str, Any]]) Custom arguments for the database driver.
+- **db_query_template_values**: (Optional[dict[str, Any]]) Values to render into the SQL query using Mustache templating.
+
+### Outputs
+
+- **results**: (list[dict[str, Any]]) A list of rows returned by the executed query, each represented as a dictionary.
+
+## File: \_\_init\_\_.py
+
+### Description
+
+This file is included to initialize the package. It's empty, but serves as a placeholder for future expansions or to include package-level imports.
+
+## File: typed.py
+
+### Description
+
+Defines typed dictionaries to ensure structured input and output data handling:
+
+### Data Structures
+
+- **__RequiredCallSQLInputs**: Contains required fields for executing the SQL query (`db_dialect`, `db_query`).
+- **CallSQLInputs**: Extends `__RequiredCallSQLInputs` with optional fields like database connection details (`db_username`, `db_password`, etc.).
+- **CallSQLOutputs**: Defines the structure of the output data, containing the `results` list.
+
+## Usage
+
+To use the `CallSQL` module, you need to provide a dictionary of inputs detailing the database connection parameters and the SQL query. The `run` method will execute the query and return the result set as a list of dictionaries.
+
+### Example
+
+```python
+inputs = {
+    "db_query": "SELECT * FROM users WHERE age > :age",
+    "db_dialect": "postgresql",
+    "db_username": "user",
+    "db_password": "password",
+    "db_host": "localhost",
+    "db_port": 5432,
+    "db_database": "example_db",
+    "db_query_template_values": {
+        "age": 21
+    }
+}
+
+sql_step = CallSQL(inputs)
+results = sql_step.run()
+print(results)
+```
+
+This code sets up the required inputs, runs a SQL query to select users older than 21, and prints the results.
diff --git a/patchwork/steps/CallShell/README.md b/patchwork/steps/CallShell/README.md
new file mode 100644
index 000000000..1497b2a4a
--- /dev/null
+++ b/patchwork/steps/CallShell/README.md
@@ -0,0 +1,70 @@
+# CallShell Module Documentation
+
+## Overview
+
+The `CallShell` module is a Python implementation that provides functionality for executing shell scripts within an application workflow. Using a combination of template rendering and environment configuration, it seamlessly integrates shell execution into Python processes.
+
+This document details the components and functionalities of the `CallShell` module, which is a part of the larger `patchwork` framework.
+
+## Components
+
+The module consists of the following key files:
+
+1. `CallShell.py` - Implements the main functionality for shell script execution.
+2. `__init__.py` - This file is currently empty and serves as a package marker.
+3. `typed.py` - Contains type definitions for inputs and outputs used by the `CallShell` class.
+
+## File: CallShell.py
+
+### Functionality
+
+The `CallShell` class serves as the primary entry point for executing shell scripts. It allows users to specify a script, working directory, and environment variables. Here's a breakdown of how it works:
+
+- **Script Rendering**: Templates within scripts can be dynamically rendered using provided values.
+- **Environment Parsing**: Environment variables are parsed and set up appropriately for the script execution.
+- **Script Execution**: The shell script is executed within a specified working directory with the configured environment.
+- **Logging**: Outputs (stdout and stderr) from the script execution are logged for reference.
+
+### Inputs
+
+The `CallShell` class accepts the following inputs via a dictionary:
+
+- `script` (str): The shell script to execute. Required.
+- `script_template_values` (dict): Values to render within the script template.
+- `working_dir` (str, optional): Directory where the script is executed.
+- `env` (str, optional): String describing environment variables to set.
+
+### Outputs
+
+The `CallShell` class returns the following outputs in the form of a dictionary:
+
+- `stdout_output` (str): Standard output from the executed script.
+- `stderr_output` (str): Standard error output from the executed script.
+
+### Logging
+
+The execution results, including both stdout and stderr, are logged using the `patchwork` logger. This aids in debugging and tracking script execution.
+
+## File: __init__.py
+
+This file is a standard marker to indicate that the directory can be treated as a Python package. Currently, it does not contain any code or declarations.
+
+## File: typed.py
+
+### Definitions
+
+The `typed.py` file is utilized to define the types of inputs and outputs for the `CallShell` class, helping to ensure type safety and clarity. It uses `TypedDict` from Python's typing extensions module to define these structures.
+
+### Input Types
+
+- `CallShellInputs`: Extends to include optional fields like `working_dir`, `env`, and `script_template_values` in addition to the required `script`.
+
+### Output Types
+
+- `CallShellOutputs`: Defines the structure with a single field `stdout_output` for capturing the script's output.
+
+## Usage Scenario
+
+The `CallShell` module is ideal for scenarios where shell scripts need to be dynamically executed within a Python application, particularly when the script requires specific environment variables or must be run within a certain directory context.
+
+By accommodating template rendering and environment variable parsing, `CallShell` integrates well into pipelines and workflows where hybrid Python and shell script operations are necessary.
diff --git a/patchwork/steps/FixIssue/FixIssue.py b/patchwork/steps/FixIssue/FixIssue.py
index 0f7d419af..aebeca86c 100644
--- a/patchwork/steps/FixIssue/FixIssue.py
+++ b/patchwork/steps/FixIssue/FixIssue.py
@@ -1,9 +1,9 @@
 import re
 from pathlib import Path
-from typing import Any, Optional
 
 from git import InvalidGitRepositoryError, Repo
 from openai.types.chat import ChatCompletionMessageParam
+from typing_extensions import Any, Optional
 
 from patchwork.common.client.llm.aio import AioLlmClient
 from patchwork.common.client.llm.protocol import LlmClient
@@ -178,4 +178,4 @@ def run(self):
                     # Git-specific errors (untracked files, etc) - keep empty diff
                     logger.warning(f"Could not get git diff for {file}: {str(e)}")
 
-        return dict(modified_files=modified_files)
+        return dict(modified_files=modified_files, **self.multiturn_llm_call.usage())
diff --git a/patchwork/steps/FixIssue/typed.py b/patchwork/steps/FixIssue/typed.py
index cd0265f40..6716a2135 100644
--- a/patchwork/steps/FixIssue/typed.py
+++ b/patchwork/steps/FixIssue/typed.py
@@ -55,3 +55,5 @@ class ModifiedFile(TypedDict):
 
 class FixIssueOutputs(TypedDict):
     modified_files: List[ModifiedFile]
+    request_tokens: int
+    response_tokens: int
diff --git a/patchwork/steps/ReadEmail/README.md b/patchwork/steps/ReadEmail/README.md
new file mode 100644
index 000000000..73cfd2039
--- /dev/null
+++ b/patchwork/steps/ReadEmail/README.md
@@ -0,0 +1,82 @@
+# ReadEmail Module Documentation
+
+This documentation describes the ReadEmail module, which is structured to facilitate the reading and parsing of email files encoded in the `.eml` format. The module is divided across three main source files: `__init__.py`, `ReadEmail.py`, and `typed.py`. Below, we describe the functionalities of these components, including input and output specifications.
+
+---
+
+## 1. Overview
+
+The ReadEmail module is designed to read `.eml` files, parse the email headers, body, and attachments, and return this data in a structured form. It's intended for applications where email processing and analysis are required, such as in email clients, document processing systems, or automated data extraction tasks.
+
+---
+
+## 2. Files
+
+### 2.1. `__init__.py`
+
+This file is an empty file created to make the directory a Python package. It contains no code or logic.
+
+### 2.2. `ReadEmail.py`
+
+This file contains the main logic of the ReadEmail module. Below is a breakdown of its components.
+
+#### 2.2.1. Classes
+
+- **ParsedHeader**: Represents the parsed email header with fields such as `subject`, `from`, `to`, and `date`.
+- **ParsedBody**: Represents the content and content type of the email body.
+- **AttachmentHeader**: Contains fields related to the attachment's header such as content disposition and encoding.
+- **ParsedAttachment**: Represents an attachment with fields including `filename`, `raw` content, and `content_header`.
+- **ParsedEmail**: Combines all parsed data (header, body, attachment).
+- **ReadEmail**: Inherits from the `Step` class and contains the core functionality for running the email parsing task.
+
+#### 2.2.2. Key Methods
+
+- **`__decode`**: Decodes the email content based on its encoding, e.g., `base64` or `quoted-printable`.
+- **`run`**: Executes the parsing process using `EmlParser`, processes email data, attaches parsed data, and decodes attachments.
+
+### 2.3. `typed.py`
+
+This file defines the input and output types used by the `ReadEmail` class.
+
+#### 2.3.1. Inputs
+
+- `eml_file_path`: Path to the `.eml` email file to be processed.
+- `base_path`: (Optional) Base directory path where attachments should be saved.
+
+#### 2.3.2. Outputs
+
+- `subject`: Email subject.
+- `datetime`: Date and time the email was sent.
+- `from_`: Sender's email.
+- `body`: Full body text of the email.
+- `message_id`: Unique message identifier.
+- `attachments`: List of attachments with file paths.
+
+---
+
+## 3. Usage
+
+To utilize the ReadEmail module effectively, instantiate the `ReadEmail` class with the required inputs and execute the `run` method. The `run` method will parse the email and return a dictionary containing the parsed data.
+
+### Example
+
+```python
+inputs = {
+    "eml_file_path": "path/to/email.eml",
+    "base_path": "path/to/save/attachments"
+}
+
+read_email = ReadEmail(inputs)
+parsed_data = read_email.run()
+
+print(parsed_data["subject"])
+print(parsed_data["body"])
+for attachment in parsed_data["attachments"]:
+    print(attachment["path"])
+```
+
+This example will print out the email subject, body, and paths to any attachments extracted from the specified `.eml` file.
+
+---
+
+By following this guide, users can effectively integrate and utilize the ReadEmail module for processing and extracting information from `.eml` files in their applications.
diff --git a/patchwork/steps/ScanSonar/ScanSonar.py b/patchwork/steps/ScanSonar/ScanSonar.py
index 973af4f91..3ee5fcbb0 100644
--- a/patchwork/steps/ScanSonar/ScanSonar.py
+++ b/patchwork/steps/ScanSonar/ScanSonar.py
@@ -1,4 +1,4 @@
-from typing import List
+from typing_extensions import List
 
 from patchwork.common.client.sonar import SonarClient
 from patchwork.step import Step, StepStatus
diff --git a/patchwork/steps/SendEmail/README.md b/patchwork/steps/SendEmail/README.md
new file mode 100644
index 000000000..460ffce02
--- /dev/null
+++ b/patchwork/steps/SendEmail/README.md
@@ -0,0 +1,69 @@
+# SendEmail Module Documentation
+
+## Overview
+
+The SendEmail module is a Python implementation that facilitates sending emails using SMTP. It is structured mainly with three components: an empty `__init__.py`, a `SendEmail.py` file containing the logic for sending emails, and a `typed.py` file defining the input and output types.
+
+## Files
+
+- **`__init__.py`**: Placeholder for module initialization.
+- **`SendEmail.py`**: Implements the email sending functionality.
+- **`typed.py`**: Defines the types for inputs and outputs used by the `SendEmail` class.
+
+## Usage
+
+The module is used to send emails using configurable SMTP settings. It's incorporated into a larger application that presumably utilizes the `patchwork` framework, which structures steps and inputs/outputs neatly.
+
+### File: SendEmail.py
+
+The `SendEmail` class extends `Step` from the `patchwork` framework. This class manages the construction and sending of an email based on provided parameters and SMTP settings.
+
+#### Key Features
+
+- Allows templated email content using the `mustache_render` function.
+- Supports both SSL and non-SSL connections to the SMTP server.
+- Configurable with numerous email-related parameters: subject, body, sender and recipient addresses, SMTP server details, and more.
+
+### Inputs
+
+#### Required Inputs
+
+The `SendEmailInputs` class extends `TypedDict` to describe necessary inputs for sending an email:
+
+- **`sender_email`** (`str`): Email address of the sender.
+- **`recipient_email`** (`str`): Email address of the recipient.
+- **`smtp_username`** (`str`): Username for SMTP authentication.
+- **`smtp_password`** (`str`): Password for SMTP authentication.
+
+#### Optional Inputs
+
+- **`email_template_value`** (`dict[str, Any]`): Values to render templated parts of the email.
+- **`subject`** (`str`): Email subject. Defaults to "Patchwork Execution Email".
+- **`body`** (`str`): Email body. Defaults to "Patchwork Execution Email".
+- **`smtp_host`** (`str`): SMTP server address. Defaults to `smtp.gmail.com`.
+- **`smtp_port`** (`int`): Port for the SMTP server. Defaults to 25.
+- **`reply_message_id`** (`str`): Message ID this email replies to.
+- **`is_smtp_ssl`** (`str`): Boolean value to determine if SSL connections are used.
+
+### Outputs
+
+- **`SendEmailOutputs`**: An empty `TypedDict`. This suggests that no specific outputs are defined or expected from the email sending process.
+
+### Implementation
+
+This module can be utilized by instantiating the `SendEmail` class with proper inputs and calling the `run()` method to send the email. Ensure all required and optional parameters are properly set up for desired email configuration and delivery.
+
+```python
+inputs = {
+    'sender_email': 'example@example.com',
+    'recipient_email': 'recipient@example.com',
+    'smtp_username': 'user',
+    'smtp_password': 'pass',
+    # Other optional parameters can also be specified
+}
+
+email_step = SendEmail(inputs)
+result = email_step.run()
+```
+
+This code effectively sends an email according to the specified parameters and inputs.
diff --git a/patchwork/steps/__init__.py b/patchwork/steps/__init__.py
index 862dc94b1..30c1e6b0f 100644
--- a/patchwork/steps/__init__.py
+++ b/patchwork/steps/__init__.py
@@ -1,4 +1,5 @@
 from patchwork.steps.AgenticLLM.AgenticLLM import AgenticLLM
+from patchwork.steps.AgenticLLMV2.AgenticLLMV2 import AgenticLLMV2
 from patchwork.steps.AnalyzeImpact.AnalyzeImpact import AnalyzeImpact
 from patchwork.steps.CallAPI.CallAPI import CallAPI
 from patchwork.steps.CallCode2Prompt.CallCode2Prompt import CallCode2Prompt
@@ -62,6 +63,7 @@
 
 __all__ = [
     "AgenticLLM",
+    "AgenticLLMV2",
     "AnalyzeImpact",
     "CallAPI",
     "CallCode2Prompt",
diff --git a/poetry.lock b/poetry.lock
index ca356e4c0..a38f0aa5d 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -152,13 +152,13 @@ files = [
 
 [[package]]
 name = "anthropic"
-version = "0.40.0"
+version = "0.45.2"
 description = "The official Python library for the anthropic API"
 optional = false
 python-versions = ">=3.8"
 files = [
-    {file = "anthropic-0.40.0-py3-none-any.whl", hash = "sha256:442028ae8790ff9e3b6f8912043918755af1230d193904ae2ef78cc22995280c"},
-    {file = "anthropic-0.40.0.tar.gz", hash = "sha256:3efeca6d9e97813f93ed34322c6c7ea2279bf0824cd0aa71b59ce222665e2b87"},
+    {file = "anthropic-0.45.2-py3-none-any.whl", hash = "sha256:ecd746f7274451dfcb7e1180571ead624c7e1195d1d46cb7c70143d2aedb4d35"},
+    {file = "anthropic-0.45.2.tar.gz", hash = "sha256:32a18b9ecd12c91b2be4cae6ca2ab46a06937b5aa01b21308d97a6d29794fb5e"},
 ]
 
 [package.dependencies]
@@ -168,7 +168,7 @@ httpx = ">=0.23.0,<1"
 jiter = ">=0.4.0,<1"
 pydantic = ">=1.9.0,<3"
 sniffio = "*"
-typing-extensions = ">=4.7,<5"
+typing-extensions = ">=4.10,<5"
 
 [package.extras]
 bedrock = ["boto3 (>=1.28.57)", "botocore (>=1.31.57)"]
@@ -502,13 +502,13 @@ redis = ["redis (>=2.10.5)"]
 
 [[package]]
 name = "cachetools"
-version = "5.5.1"
+version = "5.5.2"
 description = "Extensible memoizing collections and decorators"
 optional = false
 python-versions = ">=3.7"
 files = [
-    {file = "cachetools-5.5.1-py3-none-any.whl", hash = "sha256:b76651fdc3b24ead3c648bbdeeb940c1b04d365b38b4af66788f9ec4a81d42bb"},
-    {file = "cachetools-5.5.1.tar.gz", hash = "sha256:70f238fbba50383ef62e55c6aff6d9673175fe59f7c6782c7a0b9e38f4a9df95"},
+    {file = "cachetools-5.5.2-py3-none-any.whl", hash = "sha256:d26a22bcc62eb95c3beabd9f1ee5e820d3d2704fe2967cbe350e20c8ffcd3f0a"},
+    {file = "cachetools-5.5.2.tar.gz", hash = "sha256:1a661caa9175d26759571b2e19580f9d6393969e5dfca11fdb1f947a23e640d4"},
 ]
 
 [[package]]
@@ -850,6 +850,28 @@ docs = ["Pallets-Sphinx-Themes", "m2r2", "sphinx"]
 tests = ["pytest"]
 tests-cov = ["coverage", "coveralls", "pytest", "pytest-cov"]
 
+[[package]]
+name = "cohere"
+version = "5.13.12"
+description = ""
+optional = false
+python-versions = "<4.0,>=3.9"
+files = [
+    {file = "cohere-5.13.12-py3-none-any.whl", hash = "sha256:2a043591a3e5280b47716a6b311e4c7f58e799364113a9cb81b50cd4f6c95f7e"},
+    {file = "cohere-5.13.12.tar.gz", hash = "sha256:97bb9ac107e580780b941acbabd3aa5e71960e6835398292c46aaa8a0a4cab88"},
+]
+
+[package.dependencies]
+fastavro = ">=1.9.4,<2.0.0"
+httpx = ">=0.21.2"
+httpx-sse = "0.4.0"
+pydantic = ">=1.9.2"
+pydantic-core = ">=2.18.2,<3.0.0"
+requests = ">=2.0.0,<3.0.0"
+tokenizers = ">=0.15,<1"
+types-requests = ">=2.0.0,<3.0.0"
+typing_extensions = ">=4.0.0"
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -1192,6 +1214,20 @@ filemagic = ["file-magic (>=0.4.0)"]
 regex = ["regex"]
 test = ["coverage", "pytest", "pytest-sugar"]
 
+[[package]]
+name = "eval-type-backport"
+version = "0.2.2"
+description = "Like `typing._eval_type`, but lets older Python versions use newer typing features."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "eval_type_backport-0.2.2-py3-none-any.whl", hash = "sha256:cb6ad7c393517f476f96d456d0412ea80f0a8cf96f6892834cd9340149111b0a"},
+    {file = "eval_type_backport-0.2.2.tar.gz", hash = "sha256:f0576b4cf01ebb5bd358d02314d31846af5e07678387486e2c798af0e7d849c1"},
+]
+
+[package.extras]
+tests = ["pytest"]
+
 [[package]]
 name = "exceptiongroup"
 version = "1.2.2"
@@ -1240,6 +1276,52 @@ typing-extensions = ">=4.8.0"
 all = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "itsdangerous (>=1.1.0)", "jinja2 (>=3.1.5)", "orjson (>=3.2.1)", "pydantic-extra-types (>=2.0.0)", "pydantic-settings (>=2.0.0)", "python-multipart (>=0.0.18)", "pyyaml (>=5.3.1)", "ujson (>=4.0.1,!=4.0.2,!=4.1.0,!=4.2.0,!=4.3.0,!=5.0.0,!=5.1.0)", "uvicorn[standard] (>=0.12.0)"]
 standard = ["email-validator (>=2.0.0)", "fastapi-cli[standard] (>=0.0.5)", "httpx (>=0.23.0)", "jinja2 (>=3.1.5)", "python-multipart (>=0.0.18)", "uvicorn[standard] (>=0.12.0)"]
 
+[[package]]
+name = "fastavro"
+version = "1.10.0"
+description = "Fast read/write of AVRO files"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "fastavro-1.10.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:1a9fe0672d2caf0fe54e3be659b13de3cad25a267f2073d6f4b9f8862acc31eb"},
+    {file = "fastavro-1.10.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:86dd0410770e0c99363788f0584523709d85e57bb457372ec5c285a482c17fe6"},
+    {file = "fastavro-1.10.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:190e80dc7d77d03a6a8597a026146b32a0bbe45e3487ab4904dc8c1bebecb26d"},
+    {file = "fastavro-1.10.0-cp310-cp310-musllinux_1_2_aarch64.whl", hash = "sha256:bf570d63be9155c3fdc415f60a49c171548334b70fff0679a184b69c29b6bc61"},
+    {file = "fastavro-1.10.0-cp310-cp310-musllinux_1_2_x86_64.whl", hash = "sha256:e07abb6798e95dccecaec316265e35a018b523d1f3944ad396d0a93cb95e0a08"},
+    {file = "fastavro-1.10.0-cp310-cp310-win_amd64.whl", hash = "sha256:37203097ed11d0b8fd3c004904748777d730cafd26e278167ea602eebdef8eb2"},
+    {file = "fastavro-1.10.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:d183c075f527ab695a27ae75f210d4a86bce660cda2f85ae84d5606efc15ef50"},
+    {file = "fastavro-1.10.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d7a95a2c0639bffd7c079b59e9a796bfc3a9acd78acff7088f7c54ade24e4a77"},
+    {file = "fastavro-1.10.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:0a678153b5da1b024a32ec3f611b2e7afd24deac588cb51dd1b0019935191a6d"},
+    {file = "fastavro-1.10.0-cp311-cp311-musllinux_1_2_aarch64.whl", hash = "sha256:67a597a5cfea4dddcf8b49eaf8c2b5ffee7fda15b578849185bc690ec0cd0d8f"},
+    {file = "fastavro-1.10.0-cp311-cp311-musllinux_1_2_x86_64.whl", hash = "sha256:1fd689724760b17f69565d8a4e7785ed79becd451d1c99263c40cb2d6491f1d4"},
+    {file = "fastavro-1.10.0-cp311-cp311-win_amd64.whl", hash = "sha256:4f949d463f9ac4221128a51e4e34e2562f401e5925adcadfd28637a73df6c2d8"},
+    {file = "fastavro-1.10.0-cp312-cp312-macosx_10_13_universal2.whl", hash = "sha256:cfe57cb0d72f304bd0dcc5a3208ca6a7363a9ae76f3073307d095c9d053b29d4"},
+    {file = "fastavro-1.10.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:74e517440c824cb65fb29d3e3903a9406f4d7c75490cef47e55c4c82cdc66270"},
+    {file = "fastavro-1.10.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:203c17d44cadde76e8eecb30f2d1b4f33eb478877552d71f049265dc6f2ecd10"},
+    {file = "fastavro-1.10.0-cp312-cp312-musllinux_1_2_aarch64.whl", hash = "sha256:6575be7f2b5f94023b5a4e766b0251924945ad55e9a96672dc523656d17fe251"},
+    {file = "fastavro-1.10.0-cp312-cp312-musllinux_1_2_x86_64.whl", hash = "sha256:fe471deb675ed2f01ee2aac958fbf8ebb13ea00fa4ce7f87e57710a0bc592208"},
+    {file = "fastavro-1.10.0-cp312-cp312-win_amd64.whl", hash = "sha256:567ff515f2a5d26d9674b31c95477f3e6022ec206124c62169bc2ffaf0889089"},
+    {file = "fastavro-1.10.0-cp313-cp313-macosx_10_13_universal2.whl", hash = "sha256:82263af0adfddb39c85f9517d736e1e940fe506dfcc35bc9ab9f85e0fa9236d8"},
+    {file = "fastavro-1.10.0-cp313-cp313-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:566c193109ff0ff84f1072a165b7106c4f96050078a4e6ac7391f81ca1ef3efa"},
+    {file = "fastavro-1.10.0-cp313-cp313-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:e400d2e55d068404d9fea7c5021f8b999c6f9d9afa1d1f3652ec92c105ffcbdd"},
+    {file = "fastavro-1.10.0-cp313-cp313-musllinux_1_2_aarch64.whl", hash = "sha256:9b8227497f71565270f9249fc9af32a93644ca683a0167cfe66d203845c3a038"},
+    {file = "fastavro-1.10.0-cp313-cp313-musllinux_1_2_x86_64.whl", hash = "sha256:8e62d04c65461b30ac6d314e4197ad666371e97ae8cb2c16f971d802f6c7f514"},
+    {file = "fastavro-1.10.0-cp313-cp313-win_amd64.whl", hash = "sha256:86baf8c9740ab570d0d4d18517da71626fe9be4d1142bea684db52bd5adb078f"},
+    {file = "fastavro-1.10.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:5bccbb6f8e9e5b834cca964f0e6ebc27ebe65319d3940b0b397751a470f45612"},
+    {file = "fastavro-1.10.0-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:b0132f6b0b53f61a0a508a577f64beb5de1a5e068a9b4c0e1df6e3b66568eec4"},
+    {file = "fastavro-1.10.0-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:ca37a363b711202c6071a6d4787e68e15fa3ab108261058c4aae853c582339af"},
+    {file = "fastavro-1.10.0-cp39-cp39-musllinux_1_2_aarch64.whl", hash = "sha256:cf38cecdd67ca9bd92e6e9ba34a30db6343e7a3bedf171753ee78f8bd9f8a670"},
+    {file = "fastavro-1.10.0-cp39-cp39-musllinux_1_2_x86_64.whl", hash = "sha256:f4dd10e0ed42982122d20cdf1a88aa50ee09e5a9cd9b39abdffb1aa4f5b76435"},
+    {file = "fastavro-1.10.0-cp39-cp39-win_amd64.whl", hash = "sha256:aaef147dc14dd2d7823246178fd06fc5e477460e070dc6d9e07dd8193a6bc93c"},
+    {file = "fastavro-1.10.0.tar.gz", hash = "sha256:47bf41ac6d52cdfe4a3da88c75a802321321b37b663a900d12765101a5d6886f"},
+]
+
+[package.extras]
+codecs = ["cramjam", "lz4", "zstandard"]
+lz4 = ["lz4"]
+snappy = ["cramjam"]
+zstandard = ["zstandard"]
+
 [[package]]
 name = "fastjsonschema"
 version = "2.21.1"
@@ -1552,13 +1634,13 @@ websockets = ">=13.0,<15.0dev"
 
 [[package]]
 name = "googleapis-common-protos"
-version = "1.67.0"
+version = "1.68.0"
 description = "Common protobufs used in Google APIs"
 optional = true
 python-versions = ">=3.7"
 files = [
-    {file = "googleapis_common_protos-1.67.0-py2.py3-none-any.whl", hash = "sha256:579de760800d13616f51cf8be00c876f00a9f146d3e6510e19d1f4111758b741"},
-    {file = "googleapis_common_protos-1.67.0.tar.gz", hash = "sha256:21398025365f138be356d5923e9168737d94d46a72aefee4a6110a1f23463c86"},
+    {file = "googleapis_common_protos-1.68.0-py2.py3-none-any.whl", hash = "sha256:aaf179b2f81df26dfadac95def3b16a95064c76a5f45f07e4c68a21bb371c4ac"},
+    {file = "googleapis_common_protos-1.68.0.tar.gz", hash = "sha256:95d38161f4f9af0d9423eed8fb7b64ffd2568c3464eb542ff02c5bfa1953ab3c"},
 ]
 
 [package.dependencies]
@@ -1653,6 +1735,39 @@ files = [
 docs = ["Sphinx", "furo"]
 test = ["objgraph", "psutil"]
 
+[[package]]
+name = "griffe"
+version = "1.5.7"
+description = "Signatures for entire Python programs. Extract the structure, the frame, the skeleton of your project, to generate API documentation or find breaking changes in your API."
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "griffe-1.5.7-py3-none-any.whl", hash = "sha256:4af8ec834b64de954d447c7b6672426bb145e71605c74a4e22d510cc79fe7d8b"},
+    {file = "griffe-1.5.7.tar.gz", hash = "sha256:465238c86deaf1137761f700fb343edd8ffc846d72f6de43c3c345ccdfbebe92"},
+]
+
+[package.dependencies]
+colorama = ">=0.4"
+
+[[package]]
+name = "groq"
+version = "0.18.0"
+description = "The official Python library for the groq API"
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "groq-0.18.0-py3-none-any.whl", hash = "sha256:81d5ac00057a45d8ce559d23ab5d3b3893011d1f12c35187ab35a9182d826ea6"},
+    {file = "groq-0.18.0.tar.gz", hash = "sha256:8e2ccfea406d68b3525af4b7c0e321fcb3d2a73fc60bb70b4156e6cd88c72f03"},
+]
+
+[package.dependencies]
+anyio = ">=3.5.0,<5"
+distro = ">=1.7.0,<2"
+httpx = ">=0.23.0,<1"
+pydantic = ">=1.9.0,<3"
+sniffio = "*"
+typing-extensions = ">=4.10,<5"
+
 [[package]]
 name = "grpcio"
 version = "1.70.0"
@@ -1858,15 +1973,26 @@ http2 = ["h2 (>=3,<5)"]
 socks = ["socksio (==1.*)"]
 zstd = ["zstandard (>=0.18.0)"]
 
+[[package]]
+name = "httpx-sse"
+version = "0.4.0"
+description = "Consume Server-Sent Event (SSE) messages with HTTPX."
+optional = false
+python-versions = ">=3.8"
+files = [
+    {file = "httpx-sse-0.4.0.tar.gz", hash = "sha256:1e81a3a3070ce322add1d3529ed42eb5f70817f45ed6ec915ab753f961139721"},
+    {file = "httpx_sse-0.4.0-py3-none-any.whl", hash = "sha256:f329af6eae57eaa2bdfd962b42524764af68075ea87370a2de920af5341e318f"},
+]
+
 [[package]]
 name = "huggingface-hub"
-version = "0.28.1"
+version = "0.29.1"
 description = "Client library to download and publish models, datasets and other repos on the huggingface.co hub"
 optional = false
 python-versions = ">=3.8.0"
 files = [
-    {file = "huggingface_hub-0.28.1-py3-none-any.whl", hash = "sha256:aa6b9a3ffdae939b72c464dbb0d7f99f56e649b55c3d52406f49e0a5a620c0a7"},
-    {file = "huggingface_hub-0.28.1.tar.gz", hash = "sha256:893471090c98e3b6efbdfdacafe4052b20b84d59866fb6f54c33d9af18c303ae"},
+    {file = "huggingface_hub-0.29.1-py3-none-any.whl", hash = "sha256:352f69caf16566c7b6de84b54a822f6238e17ddd8ae3da4f8f2272aea5b198d5"},
+    {file = "huggingface_hub-0.29.1.tar.gz", hash = "sha256:9524eae42077b8ff4fc459ceb7a514eca1c1232b775276b009709fe2a084f250"},
 ]
 
 [package.dependencies]
@@ -2214,6 +2340,17 @@ files = [
     {file = "json_repair-0.30.3.tar.gz", hash = "sha256:0ac56e7ae9253ee9c507a7e1a3a26799c9b0bbe5e2bec1b2cc5053e90d5b05e3"},
 ]
 
+[[package]]
+name = "jsonpath-python"
+version = "1.0.6"
+description = "A more powerful JSONPath implementation in modern python"
+optional = false
+python-versions = ">=3.6"
+files = [
+    {file = "jsonpath-python-1.0.6.tar.gz", hash = "sha256:dd5be4a72d8a2995c3f583cf82bf3cd1a9544cfdabf2d22595b67aff07349666"},
+    {file = "jsonpath_python-1.0.6-py3-none-any.whl", hash = "sha256:1e3b78df579f5efc23565293612decee04214609208a2335884b3ee3f786b575"},
+]
+
 [[package]]
 name = "jsonschema"
 version = "4.23.0"
@@ -2274,13 +2411,13 @@ testing = ["pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-ena
 
 [[package]]
 name = "kubernetes"
-version = "32.0.0"
+version = "32.0.1"
 description = "Kubernetes python client"
 optional = true
 python-versions = ">=3.6"
 files = [
-    {file = "kubernetes-32.0.0-py2.py3-none-any.whl", hash = "sha256:60fd8c29e8e43d9c553ca4811895a687426717deba9c0a66fb2dcc3f5ef96692"},
-    {file = "kubernetes-32.0.0.tar.gz", hash = "sha256:319fa840345a482001ac5d6062222daeb66ec4d1bcb3087402aed685adf0aecb"},
+    {file = "kubernetes-32.0.1-py2.py3-none-any.whl", hash = "sha256:35282ab8493b938b08ab5526c7ce66588232df00ef5e1dbe88a419107dc10998"},
+    {file = "kubernetes-32.0.1.tar.gz", hash = "sha256:42f43d49abd437ada79a79a16bd48a604d3471a117a8347e87db693f2ba0ba28"},
 ]
 
 [package.dependencies]
@@ -2347,6 +2484,17 @@ typing-inspect = ">=0.4.0"
 [package.extras]
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+[[package]]
+name = "logfire-api"
+version = "3.6.2"
+description = "Shim for the Logfire SDK which does nothing unless Logfire is installed"
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
 [[package]]
 name = "markdown-it-py"
 version = "3.0.0"
@@ -2452,6 +2600,28 @@ files = [
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 ]
 
+[[package]]
+name = "mistralai"
+version = "1.5.0"
+description = "Python Client SDK for the Mistral AI API."
+optional = false
+python-versions = ">=3.8"
+files = [
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+]
+
+[package.dependencies]
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+httpx = ">=0.27.0"
+jsonpath-python = ">=1.0.6"
+pydantic = ">=2.9.0"
+python-dateutil = ">=2.8.2"
+typing-inspect = ">=0.9.0"
+
+[package.extras]
+gcp = ["google-auth (>=2.27.0)", "requests (>=2.32.3)"]
+
 [[package]]
 name = "mmh3"
 version = "5.1.0"
@@ -3210,13 +3380,13 @@ sympy = "*"
 
 [[package]]
 name = "openai"
-version = "1.63.2"
+version = "1.64.0"
 description = "The official Python library for the openai API"
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.dependencies]
@@ -3839,13 +4009,13 @@ xmp = ["defusedxml"]
 
 [[package]]
 name = "pkginfo"
-version = "1.12.0"
+version = "1.12.1.2"
 description = "Query metadata from sdists / bdists / installed packages."
 optional = false
 python-versions = ">=3.8"
 files = [
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 ]
 
 [package.extras]
@@ -3966,13 +4136,13 @@ poetry-core = ">=1.7.0,<3.0.0"
 
 [[package]]
 name = "posthog"
-version = "3.14.1"
+version = "3.15.1"
 description = "Integrate PostHog into any python application."
 optional = true
 python-versions = "*"
 files = [
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+    {file = "posthog-3.15.1.tar.gz", hash = "sha256:ea42b83c985ce28f2ae46713469b4107762805250c21807bc456c3fdc5ae940c"},
 ]
 
 [package.dependencies]
@@ -4015,93 +4185,109 @@ wcwidth = "*"
 
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 name = "rpds-py"
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 [[package]]
@@ -5487,16 +5751,16 @@ jeepney = ">=0.6"
 
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 optional = true
 python-versions = ">=3.8"
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-    {file = "semgrep-1.86.0.tar.gz", hash = "sha256:4f0fec59cfbf40f1c1cb9fa71539725cebaad4a9097bd68bc6ae8835edcd3201"},
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+    {file = "semgrep-1.85.0-cp38.cp39.cp310.cp311.py37.py38.py39.py310.py311-none-macosx_10_14_x86_64.whl", hash = "sha256:a63055b392da70c46947780f43fecf54064fb60d8de11a16902e0cc149350a3e"},
+    {file = "semgrep-1.85.0-cp38.cp39.cp310.cp311.py37.py38.py39.py310.py311-none-macosx_11_0_arm64.whl", hash = "sha256:157b7724c35a8bda972921abfaaf252bdb754bbda004b2a82aaa38ac8099e176"},
+    {file = "semgrep-1.85.0-cp38.cp39.cp310.cp311.py37.py38.py39.py310.py311-none-musllinux_1_0_aarch64.manylinux2014_aarch64.whl", hash = "sha256:0a6b5d509576bbe0d68245d9ee2973ccecb485ca5907e85a7a8793552bf622cb"},
+    {file = "semgrep-1.85.0.tar.gz", hash = "sha256:1a321cca4c5da84eb466ca1a4ceda10223e806225e371c4fef710cfe4b4b1df7"},
 ]
 
 [package.dependencies]
@@ -5515,7 +5779,6 @@ opentelemetry-instrumentation-requests = ">=0.46b0,<1.0"
 opentelemetry-sdk = ">=1.25.0,<1.26.0"
 packaging = ">=21.0"
 peewee = ">=3.14,<4.0"
-pydantic = ">=2.8.2,<2.9.0"
 requests = ">=2.22,<3.0"
 rich = ">=12.6.0"
 "ruamel.yaml" = ">=0.16.0,<0.18"
@@ -5873,7 +6136,7 @@ blobfile = ["blobfile (>=2)"]
 name = "tokenizers"
 version = "0.21.0"
 description = ""
-optional = true
+optional = false
 python-versions = ">=3.7"
 files = [
     {file = "tokenizers-0.21.0-cp39-abi3-macosx_10_12_x86_64.whl", hash = "sha256:3c4c93eae637e7d2aaae3d376f06085164e1660f89304c0ab2b1d08a406636b2"},
@@ -6216,13 +6479,13 @@ tutorials = ["matplotlib", "pandas", "tabulate"]
 
 [[package]]
 name = "trove-classifiers"
-version = "2025.1.15.22"
+version = "2025.2.18.16"
 description = "Canonical source for classifiers on PyPI (pypi.org)."
 optional = false
 python-versions = "*"
 files = [
-    {file = "trove_classifiers-2025.1.15.22-py3-none-any.whl", hash = "sha256:5f19c789d4f17f501d36c94dbbf969fb3e8c2784d008e6f5164dd2c3d6a2b07c"},
-    {file = "trove_classifiers-2025.1.15.22.tar.gz", hash = "sha256:90af74358d3a01b3532bc7b3c88d8c6a094c2fd50a563d13d9576179326d7ed9"},
+    {file = "trove_classifiers-2025.2.18.16-py3-none-any.whl", hash = "sha256:7f6dfae899f23f04b73bc09e0754d9219a6fc4d6cca6acd62f1850a87ea92262"},
+    {file = "trove_classifiers-2025.2.18.16.tar.gz", hash = "sha256:b1ee2e1668589217d4edf506743e28b1834da128f8a122bad522c02d837006e1"},
 ]
 
 [[package]]
@@ -7069,4 +7332,4 @@ security = ["owasp-depscan", "semgrep"]
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.9"
-content-hash = "90e967442eec961b3c24810ec9da028d4c667624a2d3d16f6e496cfb85f15f02"
+content-hash = "2a8a11d54ca4549e1f1b9ed9d872f0c469e8ddf590122e5f10441e9a01cd60cc"
diff --git a/pyproject.toml b/pyproject.toml
index 02d0823ba..14c626a89 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "patchwork-cli"
-version = "0.0.99"
+version = "0.0.100"
 description = ""
 authors = ["patched.codes"]
 license = "AGPL"
@@ -32,7 +32,8 @@ python-gitlab = "^4.13.0"
 pygithub = "~2.1.1"
 azure-devops = "~7.1.0b4"
 gitpython = "~3.1.40"
-pydantic = "~2.8.2"
+pydantic = "~2.10.6"
+pydantic-ai = "^0.0.23"
 libcst = "~1.1.0"
 sqlalchemy = "~2.0.36"
 patched-code2prompt = "~0.9.0.dev1"
@@ -43,7 +44,7 @@ requests = "~2.32.3"
 chardet = "~5.2.0"
 attrs = "~23.2.0"
 google-genai = "^1.2.0"
-anthropic = "^0.40.0"
+anthropic = "^0.45.2"
 rich = "~13.7.1"
 chevron = "~0.14.0"
 giturlparse = "~0.12.0"
diff --git a/tests/common/test_app.py b/tests/common/test_app.py
index f36e75fd8..d8dffea50 100644
--- a/tests/common/test_app.py
+++ b/tests/common/test_app.py
@@ -53,6 +53,7 @@ def test_default_list_option_callback(runner):
 GenerateDocstring
 GenerateREADME
 GenerateUnitTests
+LogAnalysis
 PRReview
 ResolveIssue
 SonarFix"""
@@ -74,6 +75,7 @@ def test_config_list_option_callback(runner, config_dir, patchflow_file):
 GenerateDocstring
 GenerateREADME
 GenerateUnitTests
+LogAnalysis
 PRReview
 ResolveIssue
 SonarFix