11 Commits (e08879147b17e45fc3ecaf1387a3c43b2534b173)

Author	SHA1	Message	Date
ccurme	0ea1e89b2c	groq: read tool calls from .tool_calls attribute (#22096)	4 months ago
back2nix	a1614b88ac	groq[patch]: groq proxy support (#20758) ... # Proxy Fix for Groq Class 🐛 🚀 ## Description This PR fixes a bug related to proxy settings in the `Groq` class, allowing users to connect to LangChain services via a proxy. ## Changes Made - ✅ FIX support for specifying proxy settings in the `Groq` class. - ✅ Resolved the bug causing issues with proxy settings. - ❌ Did not include unit tests and documentation updates. - ❌ Did not run make format, make lint, and make test to ensure code quality and functionality because I couldn't get it to run, so I don't program in Python and couldn't run `ruff`. - ❔ Ensured that the changes are backwards compatible. - ✅ No additional dependencies were added to `pyproject.toml`. ### Error Before Fix ```python Traceback (most recent call last): File "/home/bg/Documents/code/github.com/back2nix/test/groq/main.py", line 9, in <module> chat = ChatGroq( ^^^^^^^^^ File "/home/bg/Documents/code/github.com/back2nix/test/groq/venv310/lib/python3.11/site-packages/langchain_core/load/serializable.py", line 120, in __init__ super().__init__(**kwargs) File "/home/bg/Documents/code/github.com/back2nix/test/groq/venv310/lib/python3.11/site-packages/pydantic/v1/main.py", line 341, in __init__ raise validation_error pydantic.v1.error_wrappers.ValidationError: 1 validation error for ChatGroq __root__ Invalid `http_client` argument; Expected an instance of `httpx.AsyncClient` but got <class 'httpx.Client'> (type=type_error) ``` ### Example usage after fix ```python3 import os import httpx from langchain_core.prompts import ChatPromptTemplate from langchain_groq import ChatGroq chat = ChatGroq( temperature=0, groq_api_key=os.environ.get("GROQ_API_KEY"), model_name="mixtral-8x7b-32768", http_client=httpx.Client( proxies="socks5://127.0.0.1:1080", transport=httpx.HTTPTransport(local_address="0.0.0.0"), ), http_async_client=httpx.AsyncClient( proxies="socks5://127.0.0.1:1080", transport=httpx.HTTPTransport(local_address="0.0.0.0"), ), ) system = "You are a helpful assistant." human = "{text}" prompt = ChatPromptTemplate.from_messages([("system", system), ("human", human)]) chain = prompt | chat out = chain.invoke({"text": "Explain the importance of low latency LLMs"}) print(out) ``` --------- Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Bagatur <baskaryan@gmail.com>	5 months ago
Erick Friis	8c95ac3145	docs, multiple: de-beta with_structured_output (#20850)	5 months ago
ccurme	3bcfbcc871	groq: handle null queue_time (#20839)	5 months ago
ccurme	4b6b0a87b6	groq[patch]: Make stream robust to ToolMessage (#20417) ... ```python from langchain.agents import AgentExecutor, create_tool_calling_agent, tool from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder from langchain_groq import ChatGroq prompt = ChatPromptTemplate.from_messages( [ ("system", "You are a helpful assistant"), ("human", "{input}"), MessagesPlaceholder("agent_scratchpad"), ] ) model = ChatGroq(model_name="mixtral-8x7b-32768", temperature=0) @tool def magic_function(input: int) -> int: """Applies a magic function to an input.""" return input + 2 tools = [magic_function] agent = create_tool_calling_agent(model, tools, prompt) agent_executor = AgentExecutor(agent=agent, tools=tools, verbose=True) agent_executor.invoke({"input": "what is the value of magic_function(3)?"}) ``` ``` > Entering new AgentExecutor chain... Invoking: `magic_function` with `{'input': 3}` 5The value of magic\_function(3) is 5. > Finished chain. {'input': 'what is the value of magic_function(3)?', 'output': 'The value of magic\\_function(3) is 5.'} ```	5 months ago
Bagatur	9514bc4d67	core[minor], ...: add tool calls message (#18947) ... core[minor], langchain[patch], openai[minor], anthropic[minor], fireworks[minor], groq[minor], mistralai[minor] ```python class ToolCall(TypedDict): name: str args: Dict[str, Any] id: Optional[str] class InvalidToolCall(TypedDict): name: Optional[str] args: Optional[str] id: Optional[str] error: Optional[str] class ToolCallChunk(TypedDict): name: Optional[str] args: Optional[str] id: Optional[str] index: Optional[int] class AIMessage(BaseMessage): ... tool_calls: List[ToolCall] = [] invalid_tool_calls: List[InvalidToolCall] = [] ... class AIMessageChunk(AIMessage, BaseMessageChunk): ... tool_call_chunks: Optional[List[ToolCallChunk]] = None ... ``` Important considerations: - Parsing logic occurs within different providers; - ~Changing output type is a breaking change for anyone doing explicit type checking;~ - ~Langsmith rendering will need to be updated: https://github.com/langchain-ai/langchainplus/pull/3561~ - ~Langserve will need to be updated~ - Adding chunks: - ~AIMessage + ToolCallsMessage = ToolCallsMessage if either has non-null .tool_calls.~ - Tool call chunks are appended, merging when having equal values of `index`. - additional_kwargs accumulate the normal way. - During streaming: - ~Messages can change types (e.g., from AIMessageChunk to AIToolCallsMessageChunk)~ - Output parsers parse additional_kwargs (during .invoke they read off tool calls). Packages outside of `partners/`: - https://github.com/langchain-ai/langchain-cohere/pull/7 - https://github.com/langchain-ai/langchain-google/pull/123/files --------- Co-authored-by: Chester Curme <chester.curme@gmail.com>	6 months ago
Erick Friis	51bdfe04e9	groq: handle streaming tool call case (#19978)	6 months ago
Graden Rea	88cf8a2905	groq: Add tool calling support (#19971) ... **Description:** Add with_structured_output to groq chat models **Issue:** **Dependencies:** N/A **Twitter handle:** N/A	6 months ago
aditya thomas	4cd38fe89f	docs: update docstring of the ChatGroq class (#18645) ... **Description:** Update docstring of the ChatGroq class **Issue:** Not applicable **Dependencies:** None	6 months ago
William De Vena	5ee76fccd5	langchain_groq[patch]: Invoke callback prior to yielding token (#18272) ... ## PR title langchain_groq[patch]: Invoke callback prior to yielding ## PR message **Description:**Invoke callback prior to yielding token in _stream and _astream methods for groq. Issue: https://github.com/langchain-ai/langchain/issues/16913 Dependencies: None Twitter handle: None	7 months ago
Graden Rea	e5e38e89ce	partner: Add groq partner integration and chat model (#17856) ... Description: Add a Groq chat model issue: TODO Dependencies: groq Twitter handle: N/A	7 months ago