wip

* Clean up to match enterprise

* add additional params to LLM calls

* make sure additional params are getting passed to llm

* update docs

* drop print

docs/concepts/llms.mdx

@@ -465,11 +465,22 @@ Learn how to get the most out of your LLM configuration:
     # https://cloud.google.com/vertex-ai/generative-ai/docs/overview
     ```
 
+    ## GET CREDENTIALS 
+    file_path = 'path/to/vertex_ai_service_account.json'
+
+    # Load the JSON file
+    with open(file_path, 'r') as file:
+        vertex_credentials = json.load(file)
+
+    # Convert to JSON string
+    vertex_credentials_json = json.dumps(vertex_credentials)
+
     Example usage:
     ```python Code
     llm = LLM(
         model="gemini/gemini-1.5-pro-latest",
-        temperature=0.7
+        temperature=0.7,
+        vertex_credentials=vertex_credentials_json
     )
     ```
   </Accordion>

pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "pydantic>=2.4.2",
     "openai>=1.13.3",
     "litellm==1.59.8",
-    "instructor>=1.3.3",
+    "instructor>=1.7.2",
     # Text Processing
     "pdfplumber>=0.11.4",
     "regex>=2024.9.11",

src/crewai/agents/crew_agent_executor.py

@@ -519,7 +519,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
             color="yellow",
         )
         self._handle_crew_training_output(initial_answer, feedback)
-        self.messages.append(self._format_msg(f"Feedback: {feedback}"))
+        self.messages.append(
+            self._format_msg(
+                self._i18n.slice("feedback_instructions").format(feedback=feedback)
+            )
+        )
         improved_answer = self._invoke_loop()
         self._handle_crew_training_output(improved_answer)
         self.ask_for_human_input = False
@@ -566,7 +570,11 @@ class CrewAgentExecutor(CrewAgentExecutorMixin):
 
     def _process_feedback_iteration(self, feedback: str) -> AgentFinish:
         """Process a single feedback iteration."""
-        self.messages.append(self._format_msg(f"Feedback: {feedback}"))
+        self.messages.append(
+            self._format_msg(
+                self._i18n.slice("feedback_instructions").format(feedback=feedback)
+            )
+        )
         return self._invoke_loop()
 
     def _log_feedback_error(self, retry_count: int, error: Exception) -> None:

src/crewai/llm.py

@@ -7,7 +7,10 @@ import warnings
 from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Union, cast
 
+import instructor
 from dotenv import load_dotenv
+from openai.types.chat import ChatCompletionMessageParam
+from pydantic import BaseModel
 
 with warnings.catch_warnings():
     warnings.simplefilter("ignore", UserWarning)
@@ -137,6 +140,7 @@ class LLM:
         api_version: Optional[str] = None,
         api_key: Optional[str] = None,
         callbacks: List[Any] = [],
+        **kwargs,
     ):
         self.model = model
         self.timeout = timeout
@@ -158,6 +162,7 @@ class LLM:
         self.api_key = api_key
         self.callbacks = callbacks
         self.context_window_size = 0
+        self.additional_params = kwargs
 
         litellm.drop_params = True
 
@@ -180,34 +185,63 @@ class LLM:
         available_functions: Optional[Dict[str, Any]] = None,
     ) -> str:
         """
-        High-level llm call method that:
-          1) Accepts either a string or a list of messages
-          2) Converts string input to the required message format
-          3) Calls litellm.completion
-          4) Handles function/tool calls if any
-          5) Returns the final text response or tool result
+        High-level LLM call method that handles:
+        1. Multiple input formats (string or message list)
+        2. Structured responses via Instructor integration
+        3. Tool/function calling with optional structured output
+        4. Callback integration
 
         Parameters:
-        - messages (Union[str, List[Dict[str, str]]]): The input messages for the LLM.
-          - If a string is provided, it will be converted into a message list with a single entry.
-          - If a list of dictionaries is provided, each dictionary should have 'role' and 'content' keys.
-        - tools (Optional[List[dict]]): A list of tool schemas for function calling.
-        - callbacks (Optional[List[Any]]): A list of callback functions to be executed.
-        - available_functions (Optional[Dict[str, Any]]): A dictionary mapping function names to actual Python functions.
+            messages: Input prompt(s) as either:
+                - String (converted to single user message)
+                - List of message dicts with 'role' and 'content'
+
+            tools: List of tool schemas for function calling
+            callbacks: List of callback handlers
+            available_functions: Mapping of function names to callables
+            response_format: Pydantic model for structured responses
 
         Returns:
-        - str: The final text response from the LLM or the result of a tool function call.
+            str: Can be:
+            - Plain text response
+            - Structured response (if response_format provided)
+            - Tool function result (raw or structured)
+
+        Behavior:
+        - With response_format and no tools: Direct structured response
+        - With tools: Initial LLM call → Tool execution → Optional secondary structured call
+        - Without tools/response_format: Standard text completion
 
         Examples:
-        ---------
-        # Example 1: Using a string input
-        response = llm.call("Return the name of a random city in the world.")
-        print(response)
+            # Basic text completion
+            llm.call("Hello world")
 
-        # Example 2: Using a list of messages
-        messages = [{"role": "user", "content": "What is the capital of France?"}]
-        response = llm.call(messages)
-        print(response)
+            # Structured response without tools
+            class City(BaseModel):
+                name: str
+                population: int
+
+            response = llm.call(
+                "Name a major US city",
+                response_format=City
+            )
+            print(response.name)  # Structured access
+
+            # Tool usage with raw output
+            llm.call(
+                "What's 5 squared?",
+                tools=[math_tools],
+                available_functions={"square": square_number}
+            )
+
+            # Tool usage with structured output
+            response = llm.call(
+                "Analyze this data",
+                tools=[data_tools],
+                available_functions={"analyze": analyze_data},
+                response_format=AnalysisResult
+            )
+            print(response.metrics)  # Structured access
         """
         if isinstance(messages, str):
             messages = [{"role": "user", "content": messages}]
@@ -216,36 +250,54 @@ class LLM:
             if callbacks and len(callbacks) > 0:
                 self.set_callbacks(callbacks)
 
+            # Prepare the parameters for the completion call.
+            params = {
+                "model": self.model,
+                "messages": messages,
+                "timeout": self.timeout,
+                "temperature": self.temperature,
+                "top_p": self.top_p,
+                "n": self.n,
+                "stop": self.stop,
+                "max_tokens": self.max_tokens or self.max_completion_tokens,
+                "presence_penalty": self.presence_penalty,
+                "frequency_penalty": self.frequency_penalty,
+                "logit_bias": self.logit_bias,
+                "seed": self.seed,
+                "logprobs": self.logprobs,
+                "top_logprobs": self.top_logprobs,
+                "api_base": self.api_base,
+                "base_url": self.base_url,
+                "api_version": self.api_version,
+                "api_key": self.api_key,
+                "stream": False,
+                "tools": tools,
+                **self.additional_params,
+            }
+
+            # Remove any keys with None values.
+            params = {k: v for k, v in params.items() if v is not None}
+
+            # --- Direct structured response if no tools are provided.
+            if self.response_format is not None and (tools is None or len(tools) == 0):
+                print("Direct structured response")
+                try:
+                    # Cast messages to required type and remove model param
+                    params["messages"] = cast(
+                        List[ChatCompletionMessageParam], messages
+                    )
+                    params.pop("model", None)
+
+                    client = instructor.from_litellm(litellm.completion)
+                    response = client.chat.completions.create(**params)
+                    return response
+                except Exception as e:
+                    logging.error(f"LiteLLM call failed: {str(e)}")
+                    raise
+
+            # --- Standard flow with potential tool calls.
             try:
-                # --- 1) Prepare the parameters for the completion call
-                params = {
-                    "model": self.model,
-                    "messages": messages,
-                    "timeout": self.timeout,
-                    "temperature": self.temperature,
-                    "top_p": self.top_p,
-                    "n": self.n,
-                    "stop": self.stop,
-                    "max_tokens": self.max_tokens or self.max_completion_tokens,
-                    "presence_penalty": self.presence_penalty,
-                    "frequency_penalty": self.frequency_penalty,
-                    "logit_bias": self.logit_bias,
-                    "response_format": self.response_format,
-                    "seed": self.seed,
-                    "logprobs": self.logprobs,
-                    "top_logprobs": self.top_logprobs,
-                    "api_base": self.api_base,
-                    "base_url": self.base_url,
-                    "api_version": self.api_version,
-                    "api_key": self.api_key,
-                    "stream": False,
-                    "tools": tools,
-                }
-
-                # Remove None values from params
-                params = {k: v for k, v in params.items() if v is not None}
-
-                # --- 2) Make the completion call
+                print("NOT DIRECT STRUCTURED RESPONSE")
                 response = litellm.completion(**params)
                 response_message = cast(Choices, cast(ModelResponse, response).choices)[
                     0
@@ -253,7 +305,6 @@ class LLM:
                 text_response = response_message.content or ""
                 tool_calls = getattr(response_message, "tool_calls", [])
 
-                # --- 3) Handle callbacks with usage info
                 if callbacks and len(callbacks) > 0:
                     for callback in callbacks:
                         if hasattr(callback, "log_success_event"):
@@ -266,11 +317,11 @@ class LLM:
                                     end_time=0,
                                 )
 
-                # --- 4) If no tool calls, return the text response
+                # If no tool call is requested or available_functions is not provided, return the text response.
                 if not tool_calls or not available_functions:
                     return text_response
 
-                # --- 5) Handle the tool call
+                # --- Handle tool calls.
                 tool_call = tool_calls[0]
                 function_name = tool_call.function.name
 
@@ -283,22 +334,40 @@ class LLM:
 
                     fn = available_functions[function_name]
                     try:
-                        # Call the actual tool function
                         result = fn(**function_args)
-                        return result
-
                     except Exception as e:
                         logging.error(
                             f"Error executing function '{function_name}': {e}"
                         )
                         return text_response
 
+                    # If a structured response is requested, perform a secondary call using the tool result.
+                    if self.response_format is not None:
+                        new_params = dict(params)
+                        # Cast tool result message to required type
+                        new_params["messages"] = cast(
+                            List[ChatCompletionMessageParam],
+                            [{"role": "user", "content": result}],
+                        )
+                        new_params.pop("model", None)
+                        if "tools" in new_params:
+                            del new_params["tools"]
+                        try:
+                            client = instructor.from_litellm(litellm.completion)
+                            final_response = client.chat.completions.create(
+                                **new_params, response_model=response_format
+                            )
+                            return final_response
+                        except Exception as e:
+                            logging.error(f"LiteLLM structured call failed: {e}")
+                            return result
+                    else:
+                        return result
                 else:
                     logging.warning(
                         f"Tool call requested unknown function '{function_name}'"
                     )
                     return text_response
-
             except Exception as e:
                 if not LLMContextLengthExceededException(
                     str(e)

src/crewai/translations/en.json

@@ -24,7 +24,8 @@
     "manager_request": "Your best answer to your coworker asking you this, accounting for the context shared.",
     "formatted_task_instructions": "Ensure your final answer contains only the content in the following format: {output_format}\n\nEnsure the final output does not include any code block markers like ```json or ```python.",
     "human_feedback_classification": "Determine if the following feedback indicates that the user is satisfied or if further changes are needed. Respond with 'True' if further changes are needed, or 'False' if the user is satisfied. **Important** Do not include any additional commentary outside of your 'True' or 'False' response.\n\nFeedback: \"{feedback}\"",
-    "conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals."
+    "conversation_history_instruction": "You are a member of a crew collaborating to achieve a common goal. Your task is a specific action that contributes to this larger objective. For additional context, please review the conversation history between you and the user that led to the initiation of this crew. Use any relevant information or feedback from the conversation to inform your task execution and ensure your response aligns with both the immediate task and the crew's overall goals.",
+    "feedback_instructions": "User feedback: {feedback}\nInstructions: Use this feedback to enhance the next output iteration.\nNote: Do not respond or add commentary."
   },
   "errors": {
     "force_final_answer_error": "You can't keep going, here is the best final answer you generated:\n\n {formatted_answer}",

src/crewai/utilities/training_handler.py

@@ -35,6 +35,4 @@ class CrewTrainingHandler(PickleHandler):
     def clear(self) -> None:
         """Clear the training data by removing the file or resetting its contents."""
         if os.path.exists(self.file_path):
-            with open(self.file_path, "wb") as file:
-                # Overwrite with an empty dictionary
-                self.save({})
+            self.save({})

tests/llm_test.py

@@ -1,4 +1,5 @@
 from time import sleep
+from unittest.mock import MagicMock, patch
 
 import pytest
 
@@ -154,3 +155,50 @@ def test_llm_call_with_tool_and_message_list():
 
     assert isinstance(result, int)
     assert result == 25
+
+
+@pytest.mark.vcr(filter_headers=["authorization"])
+def test_llm_passes_additional_params():
+    llm = LLM(
+        model="gpt-4o-mini",
+        vertex_credentials="test_credentials",
+        vertex_project="test_project",
+    )
+
+    messages = [{"role": "user", "content": "Hello, world!"}]
+
+    with patch("litellm.completion") as mocked_completion:
+        # Create mocks for response structure
+        mock_message = MagicMock()
+        mock_message.content = "Test response"
+        mock_choice = MagicMock()
+        mock_choice.message = mock_message
+        mock_response = MagicMock()
+        mock_response.choices = [mock_choice]
+        mock_response.usage = {
+            "prompt_tokens": 5,
+            "completion_tokens": 5,
+            "total_tokens": 10,
+        }
+
+        # Set up the mocked completion to return the mock response
+        mocked_completion.return_value = mock_response
+
+        result = llm.call(messages)
+
+        # Assert that litellm.completion was called once
+        mocked_completion.assert_called_once()
+
+        # Retrieve the actual arguments with which litellm.completion was called
+        _, kwargs = mocked_completion.call_args
+
+        # Check that the additional_params were passed to litellm.completion
+        assert kwargs["vertex_credentials"] == "test_credentials"
+        assert kwargs["vertex_project"] == "test_project"
+
+        # Also verify that other expected parameters are present
+        assert kwargs["model"] == "gpt-4o-mini"
+        assert kwargs["messages"] == messages
+
+        # Check the result from llm.call
+        assert result == "Test response"

uv.lock

@@ -736,7 +736,7 @@ requires-dist = [
     { name = "crewai-tools", marker = "extra == 'tools'", specifier = ">=0.32.1" },
     { name = "docling", marker = "extra == 'docling'", specifier = ">=2.12.0" },
     { name = "fastembed", marker = "extra == 'fastembed'", specifier = ">=0.4.1" },
-    { name = "instructor", specifier = ">=1.3.3" },
+    { name = "instructor", specifier = ">=1.7.2" },
     { name = "json-repair", specifier = ">=0.25.2" },
     { name = "json5", specifier = ">=0.10.0" },
     { name = "jsonref", specifier = ">=1.1.0" },
@@ -1961,7 +1961,7 @@ wheels = [
 
 [[package]]
 name = "instructor"
-version = "1.6.3"
+version = "1.7.2"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohttp" },
@@ -1971,13 +1971,14 @@ dependencies = [
     { name = "openai" },
     { name = "pydantic" },
     { name = "pydantic-core" },
+    { name = "requests" },
     { name = "rich" },
     { name = "tenacity" },
     { name = "typer" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/b8/e6/21969fe0de9d278979872240b6af17510af8bd5020f6845891719c1d3eef/instructor-1.6.3.tar.gz", hash = "sha256:399cd90e30b5bc7cbd47acd7399c9c4e84926a96c20c8b5d00c5a04b41ed41ab", size = 56708 }
+sdist = { url = "https://files.pythonhosted.org/packages/63/ba/692739c76959191aa7e5f0fccda871b36548355f4a09c8733687e64e62b0/instructor-1.7.2.tar.gz", hash = "sha256:6c01b2b159766df24865dc81f7bf8457cbda88a3c0bbc810da3467d19b185ed2", size = 66200177 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/10/98/c96bf0b1656173d06cd6c3a5adaf3ac429f86d5d696ae8e90e6eb15e89be/instructor-1.6.3-py3-none-any.whl", hash = "sha256:a8f973fea621c0188009b65a3429a526c24aeb249fc24100b605ea496e92d622", size = 69447 },
+    { url = "https://files.pythonhosted.org/packages/c5/82/fd319382c1a33d7021cf151007b4cbd5daddf09d9ca5fb670e476668f9fc/instructor-1.7.2-py3-none-any.whl", hash = "sha256:cb43d27f6d7631c31762b936b2fcb44d2a3f9d8a020430a0f4d3484604ffb95b", size = 71353 },
 ]
 
 [[package]]
@@ -2028,46 +2029,46 @@ wheels = [
 
 [[package]]
 name = "jiter"
-version = "0.5.0"
+version = "0.8.2"
 source = { registry = "https://pypi.org/simple" }
-sdist = { url = "https://files.pythonhosted.org/packages/d7/1a/aa64be757afc614484b370a4d9fc1747dc9237b37ce464f7f9d9ca2a3d38/jiter-0.5.0.tar.gz", hash = "sha256:1d916ba875bcab5c5f7d927df998c4cb694d27dceddf3392e58beaf10563368a", size = 158300 }
+sdist = { url = "https://files.pythonhosted.org/packages/f8/70/90bc7bd3932e651486861df5c8ffea4ca7c77d28e8532ddefe2abc561a53/jiter-0.8.2.tar.gz", hash = "sha256:cd73d3e740666d0e639f678adb176fad25c1bcbdae88d8d7b857e1783bb4212d", size = 163007 }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/af/09/f659fc67d6aaa82c56432c4a7cc8365fff763acbf1c8f24121076617f207/jiter-0.5.0-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b599f4e89b3def9a94091e6ee52e1d7ad7bc33e238ebb9c4c63f211d74822c3f", size = 284126 },
-    { url = "https://files.pythonhosted.org/packages/07/2d/5bdaddfefc44f91af0f3340e75ef327950d790c9f86490757ac8b395c074/jiter-0.5.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:2a063f71c4b06225543dddadbe09d203dc0c95ba352d8b85f1221173480a71d5", size = 299265 },
-    { url = "https://files.pythonhosted.org/packages/74/bd/964485231deaec8caa6599f3f27c8787a54e9f9373ae80dcfbda2ad79c02/jiter-0.5.0-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:acc0d5b8b3dd12e91dd184b87273f864b363dfabc90ef29a1092d269f18c7e28", size = 332178 },
-    { url = "https://files.pythonhosted.org/packages/cf/4f/6353179174db10254549bbf2eb2c7ea102e59e0460ee374adb12071c274d/jiter-0.5.0-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:c22541f0b672f4d741382a97c65609332a783501551445ab2df137ada01e019e", size = 342533 },
-    { url = "https://files.pythonhosted.org/packages/76/6f/21576071b8b056ef743129b9dacf9da65e328b58766f3d1ea265e966f000/jiter-0.5.0-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:63314832e302cc10d8dfbda0333a384bf4bcfce80d65fe99b0f3c0da8945a91a", size = 363469 },
-    { url = "https://files.pythonhosted.org/packages/73/a1/9ef99a279c72a031dbe8a4085db41e3521ae01ab0058651d6ccc809a5e93/jiter-0.5.0-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:a25fbd8a5a58061e433d6fae6d5298777c0814a8bcefa1e5ecfff20c594bd749", size = 379078 },
-    { url = "https://files.pythonhosted.org/packages/41/6a/c038077509d67fe876c724bfe9ad15334593851a7def0d84518172bdd44a/jiter-0.5.0-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:503b2c27d87dfff5ab717a8200fbbcf4714516c9d85558048b1fc14d2de7d8dc", size = 318943 },
-    { url = "https://files.pythonhosted.org/packages/67/0d/d82673814eb38c208b7881581df596e680f8c2c003e2b80c25ca58975ee4/jiter-0.5.0-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:6d1f3d27cce923713933a844872d213d244e09b53ec99b7a7fdf73d543529d6d", size = 357394 },
-    { url = "https://files.pythonhosted.org/packages/56/9e/cbd8f6612346c38cc42e41e35cda19ce78f5b12e4106d1186e8e95ee839b/jiter-0.5.0-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:c95980207b3998f2c3b3098f357994d3fd7661121f30669ca7cb945f09510a87", size = 511080 },
-    { url = "https://files.pythonhosted.org/packages/ff/33/135c0c33565b6d5c3010d047710837427dd24c9adbc9ca090f3f92df446e/jiter-0.5.0-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:afa66939d834b0ce063f57d9895e8036ffc41c4bd90e4a99631e5f261d9b518e", size = 492827 },
-    { url = "https://files.pythonhosted.org/packages/68/c1/491a8ef682508edbaf2a32e41c1b1e34064078b369b0c2d141170999d1c9/jiter-0.5.0-cp310-none-win32.whl", hash = "sha256:f16ca8f10e62f25fd81d5310e852df6649af17824146ca74647a018424ddeccf", size = 195081 },
-    { url = "https://files.pythonhosted.org/packages/31/20/8cda4faa9571affea6130b150289522a22329778bdfa45a7aab4e7edff95/jiter-0.5.0-cp310-none-win_amd64.whl", hash = "sha256:b2950e4798e82dd9176935ef6a55cf6a448b5c71515a556da3f6b811a7844f1e", size = 190977 },
-    { url = "https://files.pythonhosted.org/packages/94/5f/3ac960ed598726aae46edea916e6df4df7ff6fe084bc60774b95cf3154e6/jiter-0.5.0-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:d4c8e1ed0ef31ad29cae5ea16b9e41529eb50a7fba70600008e9f8de6376d553", size = 284131 },
-    { url = "https://files.pythonhosted.org/packages/03/eb/2308fa5f5c14c97c4c7720fef9465f1fa0771826cddb4eec9866bdd88846/jiter-0.5.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:c6f16e21276074a12d8421692515b3fd6d2ea9c94fd0734c39a12960a20e85f3", size = 299310 },
-    { url = "https://files.pythonhosted.org/packages/3c/f6/dba34ca10b44715fa5302b8e8d2113f72eb00a9297ddf3fa0ae4fd22d1d1/jiter-0.5.0-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:5280e68e7740c8c128d3ae5ab63335ce6d1fb6603d3b809637b11713487af9e6", size = 332282 },
-    { url = "https://files.pythonhosted.org/packages/69/f7/64e0a7439790ec47f7681adb3871c9d9c45fff771102490bbee5e92c00b7/jiter-0.5.0-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:583c57fc30cc1fec360e66323aadd7fc3edeec01289bfafc35d3b9dcb29495e4", size = 342370 },
-    { url = "https://files.pythonhosted.org/packages/55/31/1efbfff2ae8e4d919144c53db19b828049ad0622a670be3bbea94a86282c/jiter-0.5.0-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:26351cc14507bdf466b5f99aba3df3143a59da75799bf64a53a3ad3155ecded9", size = 363591 },
-    { url = "https://files.pythonhosted.org/packages/30/c3/7ab2ca2276426a7398c6dfb651e38dbc81954c79a3bfbc36c514d8599499/jiter-0.5.0-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:4829df14d656b3fb87e50ae8b48253a8851c707da9f30d45aacab2aa2ba2d614", size = 378551 },
-    { url = "https://files.pythonhosted.org/packages/47/e7/5d88031cd743c62199b125181a591b1671df3ff2f6e102df85c58d8f7d31/jiter-0.5.0-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:a42a4bdcf7307b86cb863b2fb9bb55029b422d8f86276a50487982d99eed7c6e", size = 319152 },
-    { url = "https://files.pythonhosted.org/packages/4c/2d/09ea58e1adca9f0359f3d41ef44a1a18e59518d7c43a21f4ece9e72e28c0/jiter-0.5.0-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:04d461ad0aebf696f8da13c99bc1b3e06f66ecf6cfd56254cc402f6385231c06", size = 357377 },
-    { url = "https://files.pythonhosted.org/packages/7d/2f/83ff1058cb56fc3ff73e0d3c6440703ddc9cdb7f759b00cfbde8228fc435/jiter-0.5.0-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:e6375923c5f19888c9226582a124b77b622f8fd0018b843c45eeb19d9701c403", size = 511091 },
-    { url = "https://files.pythonhosted.org/packages/ae/c9/4f85f97c9894382ab457382337aea0012711baaa17f2ed55c0ff25f3668a/jiter-0.5.0-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:2cec323a853c24fd0472517113768c92ae0be8f8c384ef4441d3632da8baa646", size = 492948 },
-    { url = "https://files.pythonhosted.org/packages/4d/f2/2e987e0eb465e064c5f52c2f29c8d955452e3b316746e326269263bfb1b7/jiter-0.5.0-cp311-none-win32.whl", hash = "sha256:aa1db0967130b5cab63dfe4d6ff547c88b2a394c3410db64744d491df7f069bb", size = 195183 },
-    { url = "https://files.pythonhosted.org/packages/ab/59/05d1c3203c349b37c4dd28b02b9b4e5915a7bcbd9319173b4548a67d2e93/jiter-0.5.0-cp311-none-win_amd64.whl", hash = "sha256:aa9d2b85b2ed7dc7697597dcfaac66e63c1b3028652f751c81c65a9f220899ae", size = 191032 },
-    { url = "https://files.pythonhosted.org/packages/aa/bd/c3950e2c478161e131bed8cb67c36aed418190e2a961a1c981e69954e54b/jiter-0.5.0-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:9f664e7351604f91dcdd557603c57fc0d551bc65cc0a732fdacbf73ad335049a", size = 283511 },
-    { url = "https://files.pythonhosted.org/packages/80/1c/8ce58d8c37a589eeaaa5d07d131fd31043886f5e77ab50c00a66d869a361/jiter-0.5.0-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:044f2f1148b5248ad2c8c3afb43430dccf676c5a5834d2f5089a4e6c5bbd64df", size = 296974 },
-    { url = "https://files.pythonhosted.org/packages/4d/b8/6faeff9eed8952bed93a77ea1cffae7b946795b88eafd1a60e87a67b09e0/jiter-0.5.0-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:702e3520384c88b6e270c55c772d4bd6d7b150608dcc94dea87ceba1b6391248", size = 331897 },
-    { url = "https://files.pythonhosted.org/packages/4f/54/1d9a2209b46d39ce6f0cef3ad87c462f9c50312ab84585e6bd5541292b35/jiter-0.5.0-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:528d742dcde73fad9d63e8242c036ab4a84389a56e04efd854062b660f559544", size = 342962 },
-    { url = "https://files.pythonhosted.org/packages/2a/de/90360be7fc54b2b4c2dfe79eb4ed1f659fce9c96682e6a0be4bbe71371f7/jiter-0.5.0-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:8cf80e5fe6ab582c82f0c3331df27a7e1565e2dcf06265afd5173d809cdbf9ba", size = 363844 },
-    { url = "https://files.pythonhosted.org/packages/ba/ad/ef32b173191b7a53ea8a6757b80723cba321f8469834825e8c71c96bde17/jiter-0.5.0-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:44dfc9ddfb9b51a5626568ef4e55ada462b7328996294fe4d36de02fce42721f", size = 378709 },
-    { url = "https://files.pythonhosted.org/packages/07/de/353ce53743c0defbbbd652e89c106a97dbbac4eb42c95920b74b5056b93a/jiter-0.5.0-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:c451f7922992751a936b96c5f5b9bb9312243d9b754c34b33d0cb72c84669f4e", size = 319038 },
-    { url = "https://files.pythonhosted.org/packages/3f/92/42d47310bf9530b9dece9e2d7c6d51cf419af5586ededaf5e66622d160e2/jiter-0.5.0-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:308fce789a2f093dca1ff91ac391f11a9f99c35369117ad5a5c6c4903e1b3e3a", size = 357763 },
-    { url = "https://files.pythonhosted.org/packages/bd/8c/2bb76a9a84474d48fdd133d3445db8a4413da4e87c23879d917e000a9d87/jiter-0.5.0-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:7f5ad4a7c6b0d90776fdefa294f662e8a86871e601309643de30bf94bb93a64e", size = 511031 },
-    { url = "https://files.pythonhosted.org/packages/33/4f/9f23d79c0795e0a8e56e7988e8785c2dcda27e0ed37977256d50c77c6a19/jiter-0.5.0-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:ea189db75f8eca08807d02ae27929e890c7d47599ce3d0a6a5d41f2419ecf338", size = 493042 },
-    { url = "https://files.pythonhosted.org/packages/df/67/8a4f975aa834b8aecdb6b131422390173928fd47f42f269dcc32034ab432/jiter-0.5.0-cp312-none-win32.whl", hash = "sha256:e3bbe3910c724b877846186c25fe3c802e105a2c1fc2b57d6688b9f8772026e4", size = 195405 },
-    { url = "https://files.pythonhosted.org/packages/15/81/296b1e25c43db67848728cdab34ac3eb5c5cbb4955ceb3f51ae60d4a5e3d/jiter-0.5.0-cp312-none-win_amd64.whl", hash = "sha256:a586832f70c3f1481732919215f36d41c59ca080fa27a65cf23d9490e75b2ef5", size = 189720 },
+    { url = "https://files.pythonhosted.org/packages/f2/f3/8c11e0e87bd5934c414f9b1cfae3cbfd4a938d4669d57cb427e1c4d11a7f/jiter-0.8.2-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:ca8577f6a413abe29b079bc30f907894d7eb07a865c4df69475e868d73e71c7b", size = 303381 },
+    { url = "https://files.pythonhosted.org/packages/ea/28/4cd3f0bcbf40e946bc6a62a82c951afc386a25673d3d8d5ee461f1559bbe/jiter-0.8.2-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:b25bd626bde7fb51534190c7e3cb97cee89ee76b76d7585580e22f34f5e3f393", size = 311718 },
+    { url = "https://files.pythonhosted.org/packages/0d/17/57acab00507e60bd954eaec0837d9d7b119b4117ff49b8a62f2b646f32ed/jiter-0.8.2-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:d5c826a221851a8dc028eb6d7d6429ba03184fa3c7e83ae01cd6d3bd1d4bd17d", size = 335465 },
+    { url = "https://files.pythonhosted.org/packages/74/b9/1a3ddd2bc95ae17c815b021521020f40c60b32137730126bada962ef32b4/jiter-0.8.2-cp310-cp310-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:d35c864c2dff13dfd79fb070fc4fc6235d7b9b359efe340e1261deb21b9fcb66", size = 355570 },
+    { url = "https://files.pythonhosted.org/packages/78/69/6d29e2296a934199a7d0dde673ecccf98c9c8db44caf0248b3f2b65483cb/jiter-0.8.2-cp310-cp310-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:f557c55bc2b7676e74d39d19bcb8775ca295c7a028246175d6a8b431e70835e5", size = 381383 },
+    { url = "https://files.pythonhosted.org/packages/22/d7/fbc4c3fb1bf65f9be22a32759b539f88e897aeb13fe84ab0266e4423487a/jiter-0.8.2-cp310-cp310-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:580ccf358539153db147e40751a0b41688a5ceb275e6f3e93d91c9467f42b2e3", size = 390454 },
+    { url = "https://files.pythonhosted.org/packages/4d/a0/3993cda2e267fe679b45d0bcc2cef0b4504b0aa810659cdae9737d6bace9/jiter-0.8.2-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:af102d3372e917cffce49b521e4c32c497515119dc7bd8a75665e90a718bbf08", size = 345039 },
+    { url = "https://files.pythonhosted.org/packages/b9/ef/69c18562b4c09ce88fab5df1dcaf643f6b1a8b970b65216e7221169b81c4/jiter-0.8.2-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:cadcc978f82397d515bb2683fc0d50103acff2a180552654bb92d6045dec2c49", size = 376200 },
+    { url = "https://files.pythonhosted.org/packages/4d/17/0b5a8de46a6ab4d836f70934036278b49b8530c292b29dde3483326d4555/jiter-0.8.2-cp310-cp310-musllinux_1_1_aarch64.whl", hash = "sha256:ba5bdf56969cad2019d4e8ffd3f879b5fdc792624129741d3d83fc832fef8c7d", size = 511158 },
+    { url = "https://files.pythonhosted.org/packages/6c/b2/c401a0a2554b36c9e6d6e4876b43790d75139cf3936f0222e675cbc23451/jiter-0.8.2-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:3b94a33a241bee9e34b8481cdcaa3d5c2116f575e0226e421bed3f7a6ea71cff", size = 503956 },
+    { url = "https://files.pythonhosted.org/packages/d4/02/a0291ed7d72c0ac130f172354ee3cf0b2556b69584de391463a8ee534f40/jiter-0.8.2-cp310-cp310-win32.whl", hash = "sha256:6e5337bf454abddd91bd048ce0dca5134056fc99ca0205258766db35d0a2ea43", size = 202846 },
+    { url = "https://files.pythonhosted.org/packages/ad/20/8c988831ae4bf437e29f1671e198fc99ba8fe49f2895f23789acad1d1811/jiter-0.8.2-cp310-cp310-win_amd64.whl", hash = "sha256:4a9220497ca0cb1fe94e3f334f65b9b5102a0b8147646118f020d8ce1de70105", size = 204414 },
+    { url = "https://files.pythonhosted.org/packages/cb/b0/c1a7caa7f9dc5f1f6cfa08722867790fe2d3645d6e7170ca280e6e52d163/jiter-0.8.2-cp311-cp311-macosx_10_12_x86_64.whl", hash = "sha256:2dd61c5afc88a4fda7d8b2cf03ae5947c6ac7516d32b7a15bf4b49569a5c076b", size = 303666 },
+    { url = "https://files.pythonhosted.org/packages/f5/97/0468bc9eeae43079aaa5feb9267964e496bf13133d469cfdc135498f8dd0/jiter-0.8.2-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:a6c710d657c8d1d2adbbb5c0b0c6bfcec28fd35bd6b5f016395f9ac43e878a15", size = 311934 },
+    { url = "https://files.pythonhosted.org/packages/e5/69/64058e18263d9a5f1e10f90c436853616d5f047d997c37c7b2df11b085ec/jiter-0.8.2-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:a9584de0cd306072635fe4b89742bf26feae858a0683b399ad0c2509011b9dc0", size = 335506 },
+    { url = "https://files.pythonhosted.org/packages/9d/14/b747f9a77b8c0542141d77ca1e2a7523e854754af2c339ac89a8b66527d6/jiter-0.8.2-cp311-cp311-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:5a90a923338531b7970abb063cfc087eebae6ef8ec8139762007188f6bc69a9f", size = 355849 },
+    { url = "https://files.pythonhosted.org/packages/53/e2/98a08161db7cc9d0e39bc385415890928ff09709034982f48eccfca40733/jiter-0.8.2-cp311-cp311-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:d21974d246ed0181558087cd9f76e84e8321091ebfb3a93d4c341479a736f099", size = 381700 },
+    { url = "https://files.pythonhosted.org/packages/7a/38/1674672954d35bce3b1c9af99d5849f9256ac8f5b672e020ac7821581206/jiter-0.8.2-cp311-cp311-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:32475a42b2ea7b344069dc1e81445cfc00b9d0e3ca837f0523072432332e9f74", size = 389710 },
+    { url = "https://files.pythonhosted.org/packages/f8/9b/92f9da9a9e107d019bcf883cd9125fa1690079f323f5a9d5c6986eeec3c0/jiter-0.8.2-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:8b9931fd36ee513c26b5bf08c940b0ac875de175341cbdd4fa3be109f0492586", size = 345553 },
+    { url = "https://files.pythonhosted.org/packages/44/a6/6d030003394e9659cd0d7136bbeabd82e869849ceccddc34d40abbbbb269/jiter-0.8.2-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:ce0820f4a3a59ddced7fce696d86a096d5cc48d32a4183483a17671a61edfddc", size = 376388 },
+    { url = "https://files.pythonhosted.org/packages/ad/8d/87b09e648e4aca5f9af89e3ab3cfb93db2d1e633b2f2931ede8dabd9b19a/jiter-0.8.2-cp311-cp311-musllinux_1_1_aarch64.whl", hash = "sha256:8ffc86ae5e3e6a93765d49d1ab47b6075a9c978a2b3b80f0f32628f39caa0c88", size = 511226 },
+    { url = "https://files.pythonhosted.org/packages/77/95/8008ebe4cdc82eac1c97864a8042ca7e383ed67e0ec17bfd03797045c727/jiter-0.8.2-cp311-cp311-musllinux_1_1_x86_64.whl", hash = "sha256:5127dc1abd809431172bc3fbe8168d6b90556a30bb10acd5ded41c3cfd6f43b6", size = 504134 },
+    { url = "https://files.pythonhosted.org/packages/26/0d/3056a74de13e8b2562e4d526de6dac2f65d91ace63a8234deb9284a1d24d/jiter-0.8.2-cp311-cp311-win32.whl", hash = "sha256:66227a2c7b575720c1871c8800d3a0122bb8ee94edb43a5685aa9aceb2782d44", size = 203103 },
+    { url = "https://files.pythonhosted.org/packages/4e/1e/7f96b798f356e531ffc0f53dd2f37185fac60fae4d6c612bbbd4639b90aa/jiter-0.8.2-cp311-cp311-win_amd64.whl", hash = "sha256:cde031d8413842a1e7501e9129b8e676e62a657f8ec8166e18a70d94d4682855", size = 206717 },
+    { url = "https://files.pythonhosted.org/packages/a1/17/c8747af8ea4e045f57d6cfd6fc180752cab9bc3de0e8a0c9ca4e8af333b1/jiter-0.8.2-cp312-cp312-macosx_10_12_x86_64.whl", hash = "sha256:e6ec2be506e7d6f9527dae9ff4b7f54e68ea44a0ef6b098256ddf895218a2f8f", size = 302027 },
+    { url = "https://files.pythonhosted.org/packages/3c/c1/6da849640cd35a41e91085723b76acc818d4b7d92b0b6e5111736ce1dd10/jiter-0.8.2-cp312-cp312-macosx_11_0_arm64.whl", hash = "sha256:76e324da7b5da060287c54f2fabd3db5f76468006c811831f051942bf68c9d44", size = 310326 },
+    { url = "https://files.pythonhosted.org/packages/06/99/a2bf660d8ccffee9ad7ed46b4f860d2108a148d0ea36043fd16f4dc37e94/jiter-0.8.2-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:180a8aea058f7535d1c84183c0362c710f4750bef66630c05f40c93c2b152a0f", size = 334242 },
+    { url = "https://files.pythonhosted.org/packages/a7/5f/cea1c17864828731f11427b9d1ab7f24764dbd9aaf4648a7f851164d2718/jiter-0.8.2-cp312-cp312-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:025337859077b41548bdcbabe38698bcd93cfe10b06ff66617a48ff92c9aec60", size = 356654 },
+    { url = "https://files.pythonhosted.org/packages/e9/13/62774b7e5e7f5d5043efe1d0f94ead66e6d0f894ae010adb56b3f788de71/jiter-0.8.2-cp312-cp312-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ecff0dc14f409599bbcafa7e470c00b80f17abc14d1405d38ab02e4b42e55b57", size = 379967 },
+    { url = "https://files.pythonhosted.org/packages/ec/fb/096b34c553bb0bd3f2289d5013dcad6074948b8d55212aa13a10d44c5326/jiter-0.8.2-cp312-cp312-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:ffd9fee7d0775ebaba131f7ca2e2d83839a62ad65e8e02fe2bd8fc975cedeb9e", size = 389252 },
+    { url = "https://files.pythonhosted.org/packages/17/61/beea645c0bf398ced8b199e377b61eb999d8e46e053bb285c91c3d3eaab0/jiter-0.8.2-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:14601dcac4889e0a1c75ccf6a0e4baf70dbc75041e51bcf8d0e9274519df6887", size = 345490 },
+    { url = "https://files.pythonhosted.org/packages/d5/df/834aa17ad5dcc3cf0118821da0a0cf1589ea7db9832589278553640366bc/jiter-0.8.2-cp312-cp312-manylinux_2_5_i686.manylinux1_i686.whl", hash = "sha256:92249669925bc1c54fcd2ec73f70f2c1d6a817928480ee1c65af5f6b81cdf12d", size = 376991 },
+    { url = "https://files.pythonhosted.org/packages/67/80/87d140399d382fb4ea5b3d56e7ecaa4efdca17cd7411ff904c1517855314/jiter-0.8.2-cp312-cp312-musllinux_1_1_aarch64.whl", hash = "sha256:e725edd0929fa79f8349ab4ec7f81c714df51dc4e991539a578e5018fa4a7152", size = 510822 },
+    { url = "https://files.pythonhosted.org/packages/5c/37/3394bb47bac1ad2cb0465601f86828a0518d07828a650722e55268cdb7e6/jiter-0.8.2-cp312-cp312-musllinux_1_1_x86_64.whl", hash = "sha256:bf55846c7b7a680eebaf9c3c48d630e1bf51bdf76c68a5f654b8524335b0ad29", size = 503730 },
+    { url = "https://files.pythonhosted.org/packages/f9/e2/253fc1fa59103bb4e3aa0665d6ceb1818df1cd7bf3eb492c4dad229b1cd4/jiter-0.8.2-cp312-cp312-win32.whl", hash = "sha256:7efe4853ecd3d6110301665a5178b9856be7e2a9485f49d91aa4d737ad2ae49e", size = 203375 },
+    { url = "https://files.pythonhosted.org/packages/41/69/6d4bbe66b3b3b4507e47aa1dd5d075919ad242b4b1115b3f80eecd443687/jiter-0.8.2-cp312-cp312-win_amd64.whl", hash = "sha256:83c0efd80b29695058d0fd2fa8a556490dbce9804eac3e281f373bbc99045f6c", size = 204740 },
 ]
 
 [[package]]