Mask API keys for various LLM/ChatModel Modules (langchain-ai#13885)

**Description:** 
- Added masking of the API Keys for the modules:
  - `langchain/chat_models/openai.py`
  - `langchain/llms/openai.py`
  - `langchain/llms/google_palm.py`
  - `langchain/chat_models/google_palm.py`
  - `langchain/llms/edenai.py`

- Updated the modules to utilize `SecretStr` from pydantic to securely
manage API key.
- Added unit/integration tests
- `langchain/chat_models/asure_openai.py` used the `open_api_key` that
is derived from the `ChatOpenAI` Class and it was assuming
`openai_api_key` is a str so we changed it to expect `SecretStr`
instead.

**Issue:** langchain-ai#12165 ,
**Dependencies:** none,
**Tag maintainer:** @eyurtsev

---------

Co-authored-by: HassanA01 <[email protected]>
Co-authored-by: Aneeq Hassan <[email protected]>
Co-authored-by: kristinspenc <[email protected]>
Co-authored-by: faisalt14 <[email protected]>
Co-authored-by: Harshil-Patel28 <[email protected]>
Co-authored-by: kristinspenc <[email protected]>
Co-authored-by: faisalt14 <[email protected]>
Co-authored-by: Chester Curme <[email protected]>

libs/community/tests/integration_tests/llms/test_edenai.py

@@ -9,6 +9,8 @@
 You'll then need to set EDENAI_API_KEY environment variable to your api key.
 """
 
+from langchain_core.pydantic_v1 import SecretStr
+
 from langchain_community.llms import EdenAI
 
 
@@ -45,3 +47,13 @@ def test_edenai_call_with_old_params() -> None:
     assert llm.feature == "text"
     assert llm.subfeature == "generation"
     assert isinstance(output, str)
+
+
+def test_api_key_is_secret_string() -> None:
+    llm = EdenAI(provider="openai", edenai_api_key="secret-api-key")
+    assert isinstance(llm.edenai_api_key, SecretStr)
+
+
+def test_uses_actual_secret_value() -> None:
+    llm = EdenAI(provider="openai", edenai_api_key="secret-api-key")
+    assert llm.edenai_api_key.get_secret_value() == "secret-api-key"