langchain_ibm[patch] update docstring, dependencies, tests (langchain…

…-ai#18386)

- **Description:** Update docstring, dependencies, tests, README
- **Dependencies:**
[ibm-watsonx-ai](https://pypi.org/project/ibm-watsonx-ai/),
  - **Tag maintainer:** : 

Please make sure your PR is passing linting and testing before
submitting. Run `make format`, `make lint` and `make test` to check this
locally -> ✅
Please make sure integration_tests passing locally -> ✅

---------

Co-authored-by: Erick Friis <erick@langchain.dev>

libs/partners/ibm/README.md

@@ -1,6 +1,6 @@
 # langchain-ibm
 
-This package provides the integration between LangChain and IBM Watson AI through the `ibm-watsonx-ai` SDK.
+This package provides the integration between LangChain and IBM watsonx.ai through the `ibm-watsonx-ai` SDK.
 
 ## Installation
 
@@ -10,10 +10,6 @@ To use the `langchain-ibm` package, follow these installation steps:
 pip install langchain-ibm
 ```
 
-
-
-
-
 ## Usage
 
 ### Setting up
@@ -44,15 +40,10 @@ In alternative, you can set the environment variable in your terminal.
     set WATSONX_APIKEY=your_ibm_api_key
     ```
 
-
-
-
-
 ### Loading the model
 
 You might need to adjust model parameters for different models or tasks. For more details on the parameters, refer to IBM's [documentation](https://ibm.github.io/watsonx-ai-python-sdk/fm_model.html#metanames.GenTextParamsMetaNames).
 
-
 ```python
 parameters = {
     "decoding_method": "sample",
@@ -83,7 +74,6 @@ watsonx_llm = WatsonxLLM(
 - You need to specify the model you want to use for inferencing through `model_id`. You can find the list of available models [here](https://ibm.github.io/watsonx-ai-python-sdk/fm_model.html#ibm_watsonx_ai.foundation_models.utils.enums.ModelTypes).
 
 
-
 Alternatively you can use Cloud Pak for Data credentials. For more details, refer to IBM's [documentation](https://ibm.github.io/watsonx-ai-python-sdk/setup_cpd.html).
 
 ```python
@@ -99,9 +89,6 @@ watsonx_llm = WatsonxLLM(
 )
 ```
 
-
-
-
 ### Create a Chain
 
 Create `PromptTemplate` objects which will be responsible for creating a random question.
@@ -123,10 +110,6 @@ response = llm_chain.invoke("dog")
 print(response)
 ```
 
-
-
-
-
 ### Calling the Model Directly
 To obtain completions, you can call the model directly using a string prompt.
 
@@ -149,9 +132,6 @@ response = watsonx_llm.generate(
 print(response)
 ```
 
-
-
-
 ### Streaming the Model output
 
 You can stream the model output.

libs/partners/ibm/langchain_ibm/llms.py

@@ -16,7 +16,7 @@ class WatsonxLLM(BaseLLM):
     """
     IBM watsonx.ai large language models.
 
-    To use, you should have ``ibm_watsonx_ai`` python package installed,
+    To use, you should have ``langchain_ibm`` python package installed,
     and the environment variable ``WATSONX_APIKEY`` set with your API key, or pass
     it as a named parameter to the constructor.
 
@@ -103,6 +103,18 @@ def is_lc_serializable(cls) -> bool:
 
     @property
     def lc_secrets(self) -> Dict[str, str]:
+        """A map of constructor argument names to secret ids.
+
+        For example:
+            {
+                "url": "WATSONX_URL",
+                "apikey": "WATSONX_APIKEY",
+                "token": "WATSONX_TOKEN",
+                "password": "WATSONX_PASSWORD",
+                "username": "WATSONX_USERNAME",
+                "instance_id": "WATSONX_INSTANCE_ID",
+            }
+        """
         return {
             "url": "WATSONX_URL",
             "apikey": "WATSONX_APIKEY",

libs/partners/ibm/pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langchain-ibm"
-version = "0.1.0"
+version = "0.1.1"
 description = "An integration package connecting IBM watsonx.ai and LangChain"
 authors = ["IBM"]
 readme = "README.md"
@@ -12,21 +12,20 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.10,<4.0"
-langchain-core = "^0.1.26"
-ibm-watsonx-ai = "^0.1.8"
+langchain-core = "^0.1.27"
+ibm-watsonx-ai = "^0.2.0"
 
 [tool.poetry.group.test]
 optional = true
 
 [tool.poetry.group.test.dependencies]
 pytest = "^7.3.0"
 freezegun = "^1.2.2"
-pytest-mock  = "^3.10.0"
-ibm-watsonx-ai = "^0.1.8"
+pytest-mock = "^3.10.0"
 syrupy = "^4.0.2"
 pytest-watcher = "^0.3.4"
 pytest-asyncio = "^0.21.1"
-langchain-core = {path = "../../core", develop = true}
+langchain-core = { path = "../../core", develop = true }
 
 [tool.poetry.group.codespell]
 optional = true
@@ -38,7 +37,6 @@ codespell = "^2.2.0"
 optional = true
 
 [tool.poetry.group.test_integration.dependencies]
-ibm-watsonx-ai = "^0.1.8"
 
 [tool.poetry.group.lint]
 optional = true
@@ -48,29 +46,27 @@ ruff = "^0.1.5"
 
 [tool.poetry.group.typing.dependencies]
 mypy = "^0.991"
-langchain-core = {path = "../../core", develop = true}
+langchain-core = { path = "../../core", develop = true }
 types-requests = "^2"
 
 [tool.poetry.group.dev]
 optional = true
 
 [tool.poetry.group.dev.dependencies]
-langchain-core = {path = "../../core", develop = true}
+langchain-core = { path = "../../core", develop = true }
 
 [tool.ruff]
 select = [
-  "E",  # pycodestyle
-  "F",  # pyflakes
-  "I",  # isort
+  "E", # pycodestyle
+  "F", # pyflakes
+  "I", # isort
 ]
 
 [tool.mypy]
 disallow_untyped_defs = "True"
 
 [tool.coverage.run]
-omit = [
-    "tests/*",
-]
+omit = ["tests/*"]
 
 [build-system]
 requires = ["poetry-core>=1.0.0"]