Brody/doc 60 port integrations docs (#153)

Current preview:
https://langchain-5e9cc07a-preview-brodyd-1755879478-9f01bc4.mintlify.app/oss/python/integrations/providers/anthropic

Related task:
https://linear.app/langchain/issue/DOC-60/port-integrations-docs

## What this PR does

- Using our docs CLI, migrates everything in this folder
https://github.com/langchain-ai/langchain/tree/master/docs/docs/integrations
to this new repo
- Updates a bunch of titles
- Fixes a bunch of rendering/syntax issues
- Replaces some notebook references since those files were turned into
.md files
- Ports tables and auto-gen docs lists/cards to Card components

## What this PR does not do

- Adds the Integration section of the docs to the nav
- Fix all the broken links
- Fix every rendering issue
- Fix every title
- Finalize the sidebar
- Finalize table appearance and other theme settings
- Set up the contributing page

---------

Co-authored-by: Lauren Hirata Singh <[email protected]>

Author: beklapko

src/oss/images/base-chat-ui.mp4

@@ -0,0 +1,138 @@
+---
+title: OpenAI Adapter(Old)
+---
+
+**Please ensure OpenAI library is less than 1.0.0; otherwise, refer to the newer doc [OpenAI Adapter](/oss/integrations/adapters/openai/).**
+
+A lot of people get started with OpenAI but want to explore other models. LangChain's integrations with many model providers make this easy to do so. While LangChain has it's own message and model APIs, we've also made it as easy as possible to explore other models by exposing an adapter to adapt LangChain models to the OpenAI api.
+
+At the moment this only deals with output and does not return other information (token counts, stop reasons, etc).
+
+
+```python
+import openai
+from langchain_community.adapters import openai as lc_openai
+```
+
+## ChatCompletion.create
+
+
+```python
+messages = [{"role": "user", "content": "hi"}]
+```
+
+Original OpenAI call
+
+
+```python
+result = openai.ChatCompletion.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0
+)
+result["choices"][0]["message"].to_dict_recursive()
+```
+
+
+
+```output
+{'role': 'assistant', 'content': 'Hello! How can I assist you today?'}
+```
+
+
+LangChain OpenAI wrapper call
+
+
+```python
+lc_result = lc_openai.ChatCompletion.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0
+)
+lc_result["choices"][0]["message"]
+```
+
+
+
+```output
+{'role': 'assistant', 'content': 'Hello! How can I assist you today?'}
+```
+
+
+Swapping out model providers
+
+
+```python
+lc_result = lc_openai.ChatCompletion.create(
+    messages=messages, model="claude-2", temperature=0, provider="ChatAnthropic"
+)
+lc_result["choices"][0]["message"]
+```
+
+
+
+```output
+{'role': 'assistant', 'content': ' Hello!'}
+```
+
+
+## ChatCompletion.stream
+
+Original OpenAI call
+
+
+```python
+for c in openai.ChatCompletion.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0, stream=True
+):
+    print(c["choices"][0]["delta"].to_dict_recursive())
+```
+```output
+{'role': 'assistant', 'content': ''}
+{'content': 'Hello'}
+{'content': '!'}
+{'content': ' How'}
+{'content': ' can'}
+{'content': ' I'}
+{'content': ' assist'}
+{'content': ' you'}
+{'content': ' today'}
+{'content': '?'}
+{}
+```
+LangChain OpenAI wrapper call
+
+
+```python
+for c in lc_openai.ChatCompletion.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0, stream=True
+):
+    print(c["choices"][0]["delta"])
+```
+```output
+{'role': 'assistant', 'content': ''}
+{'content': 'Hello'}
+{'content': '!'}
+{'content': ' How'}
+{'content': ' can'}
+{'content': ' I'}
+{'content': ' assist'}
+{'content': ' you'}
+{'content': ' today'}
+{'content': '?'}
+{}
+```
+Swapping out model providers
+
+
+```python
+for c in lc_openai.ChatCompletion.create(
+    messages=messages,
+    model="claude-2",
+    temperature=0,
+    stream=True,
+    provider="ChatAnthropic",
+):
+    print(c["choices"][0]["delta"])
+```
+```output
+{'role': 'assistant', 'content': ' Hello'}
+{'content': '!'}
+{}
+```

src/oss/images/interrupt-chat-ui.mp4

@@ -0,0 +1,162 @@
+---
+title: OpenAI Adapter
+---
+
+**Please ensure OpenAI library is version 1.0.0 or higher; otherwise, refer to the older doc [OpenAI Adapter(Old)](/oss/integrations/adapters/openai-old/).**
+
+A lot of people get started with OpenAI but want to explore other models. LangChain's integrations with many model providers make this easy to do so. While LangChain has it's own message and model APIs, we've also made it as easy as possible to explore other models by exposing an adapter to adapt LangChain models to the OpenAI api.
+
+At the moment this only deals with output and does not return other information (token counts, stop reasons, etc).
+
+
+```python
+import openai
+from langchain_community.adapters import openai as lc_openai
+```
+
+## chat.completions.create
+
+
+```python
+messages = [{"role": "user", "content": "hi"}]
+```
+
+Original OpenAI call
+
+
+```python
+result = openai.chat.completions.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0
+)
+result.choices[0].message.model_dump()
+```
+
+
+
+```output
+{'content': 'Hello! How can I assist you today?',
+ 'role': 'assistant',
+ 'function_call': None,
+ 'tool_calls': None}
+```
+
+
+LangChain OpenAI wrapper call
+
+
+```python
+lc_result = lc_openai.chat.completions.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0
+)
+
+lc_result.choices[0].message  # Attribute access
+```
+
+
+
+```output
+{'role': 'assistant', 'content': 'Hello! How can I help you today?'}
+```
+
+
+
+```python
+lc_result["choices"][0]["message"]  # Also compatible with index access
+```
+
+
+
+```output
+{'role': 'assistant', 'content': 'Hello! How can I help you today?'}
+```
+
+
+Swapping out model providers
+
+
+```python
+lc_result = lc_openai.chat.completions.create(
+    messages=messages, model="claude-2", temperature=0, provider="ChatAnthropic"
+)
+lc_result.choices[0].message
+```
+
+
+
+```output
+{'role': 'assistant', 'content': 'Hello! How can I assist you today?'}
+```
+
+
+## chat.completions.stream
+
+Original OpenAI call
+
+
+```python
+for c in openai.chat.completions.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0, stream=True
+):
+    print(c.choices[0].delta.model_dump())
+```
+```output
+{'content': '', 'function_call': None, 'role': 'assistant', 'tool_calls': None}
+{'content': 'Hello', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': '!', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': ' How', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': ' can', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': ' I', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': ' assist', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': ' you', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': ' today', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': '?', 'function_call': None, 'role': None, 'tool_calls': None}
+{'content': None, 'function_call': None, 'role': None, 'tool_calls': None}
+```
+LangChain OpenAI wrapper call
+
+
+```python
+for c in lc_openai.chat.completions.create(
+    messages=messages, model="gpt-3.5-turbo", temperature=0, stream=True
+):
+    print(c.choices[0].delta)
+```
+```output
+{'role': 'assistant', 'content': ''}
+{'content': 'Hello'}
+{'content': '!'}
+{'content': ' How'}
+{'content': ' can'}
+{'content': ' I'}
+{'content': ' assist'}
+{'content': ' you'}
+{'content': ' today'}
+{'content': '?'}
+{}
+```
+Swapping out model providers
+
+
+```python
+for c in lc_openai.chat.completions.create(
+    messages=messages,
+    model="claude-2",
+    temperature=0,
+    stream=True,
+    provider="ChatAnthropic",
+):
+    print(c["choices"][0]["delta"])
+```
+```output
+{'role': 'assistant', 'content': ''}
+{'content': 'Hello'}
+{'content': '!'}
+{'content': ' How'}
+{'content': ' can'}
+{'content': ' I'}
+{'content': ' assist'}
+{'content': ' you'}
+{'content': ' today'}
+{'content': '?'}
+{}
+```