community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463)

Moved the following modules to new package langchain-community in a backwards compatible fashion:

```
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
mv langchain/langchain/adapters community/langchain_community
mv langchain/langchain/callbacks community/langchain_community/callbacks
mv langchain/langchain/chat_loaders community/langchain_community
mv langchain/langchain/chat_models community/langchain_community
mv langchain/langchain/document_loaders community/langchain_community
mv langchain/langchain/docstore community/langchain_community
mv langchain/langchain/document_transformers community/langchain_community
mv langchain/langchain/embeddings community/langchain_community
mv langchain/langchain/graphs community/langchain_community
mv langchain/langchain/llms community/langchain_community
mv langchain/langchain/memory/chat_message_histories community/langchain_community
mv langchain/langchain/retrievers community/langchain_community
mv langchain/langchain/storage community/langchain_community
mv langchain/langchain/tools community/langchain_community
mv langchain/langchain/utilities community/langchain_community
mv langchain/langchain/vectorstores community/langchain_community
mv langchain/langchain/agents/agent_toolkits community/langchain_community
mv langchain/langchain/cache.py community/langchain_community
```

Moved the following to core
```
mv langchain/langchain/utils/json_schema.py core/langchain_core/utils
mv langchain/langchain/utils/html.py core/langchain_core/utils
mv langchain/langchain/utils/strings.py core/langchain_core/utils
cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py
rm langchain/langchain/utils/env.py
```

See .scripts/community_split/script_integrations.sh for all changes

libs/community/langchain_community/utilities/reddit_search.py

@@ -0,0 +1,121 @@
+"""Wrapper for the Reddit API"""
+
+from typing import Any, Dict, List, Optional
+
+from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.utils import get_from_dict_or_env
+
+
+class RedditSearchAPIWrapper(BaseModel):
+    """Wrapper for Reddit API
+
+    To use, set the environment variables ``REDDIT_CLIENT_ID``,
+    ``REDDIT_CLIENT_SECRET``, ``REDDIT_USER_AGENT`` to set the client ID,
+    client secret, and user agent, respectively, as given by Reddit's API.
+    Alternatively, all three can be supplied as named parameters in the
+    constructor: ``reddit_client_id``, ``reddit_client_secret``, and
+    ``reddit_user_agent``, respectively.
+
+    Example:
+        .. code-block:: python
+
+            from langchain_community.utilities import RedditSearchAPIWrapper
+            reddit_search = RedditSearchAPIWrapper()
+    """
+
+    reddit_client: Any
+
+    # Values required to access Reddit API via praw
+    reddit_client_id: Optional[str]
+    reddit_client_secret: Optional[str]
+    reddit_user_agent: Optional[str]
+
+    @root_validator()
+    def validate_environment(cls, values: Dict) -> Dict:
+        """Validate that the API ID, secret and user agent exists in environment
+        and check that praw module is present.
+        """
+        reddit_client_id = get_from_dict_or_env(
+            values, "reddit_client_id", "REDDIT_CLIENT_ID"
+        )
+        values["reddit_client_id"] = reddit_client_id
+
+        reddit_client_secret = get_from_dict_or_env(
+            values, "reddit_client_secret", "REDDIT_CLIENT_SECRET"
+        )
+        values["reddit_client_secret"] = reddit_client_secret
+
+        reddit_user_agent = get_from_dict_or_env(
+            values, "reddit_user_agent", "REDDIT_USER_AGENT"
+        )
+        values["reddit_user_agent"] = reddit_user_agent
+
+        try:
+            import praw
+        except ImportError:
+            raise ImportError(
+                "praw package not found, please install it with pip install praw"
+            )
+
+        reddit_client = praw.Reddit(
+            client_id=reddit_client_id,
+            client_secret=reddit_client_secret,
+            user_agent=reddit_user_agent,
+        )
+        values["reddit_client"] = reddit_client
+
+        return values
+
+    def run(
+        self, query: str, sort: str, time_filter: str, subreddit: str, limit: int
+    ) -> str:
+        """Search Reddit and return posts as a single string."""
+        results: List[Dict] = self.results(
+            query=query,
+            sort=sort,
+            time_filter=time_filter,
+            subreddit=subreddit,
+            limit=limit,
+        )
+        if len(results) > 0:
+            output: List[str] = [f"Searching r/{subreddit} found {len(results)} posts:"]
+            for r in results:
+                category = "N/A" if r["post_category"] is None else r["post_category"]
+                p = f"Post Title: '{r['post_title']}'\n\
+                    User: {r['post_author']}\n\
+                    Subreddit: {r['post_subreddit']}:\n\
+                    Text body: {r['post_text']}\n\
+                    Post URL: {r['post_url']}\n\
+                    Post Category: {category}.\n\
+                    Score: {r['post_score']}\n"
+                output.append(p)
+            return "\n".join(output)
+        else:
+            return f"Searching r/{subreddit} did not find any posts:"
+
+    def results(
+        self, query: str, sort: str, time_filter: str, subreddit: str, limit: int
+    ) -> List[Dict]:
+        """Use praw to search Reddit and return a list of dictionaries,
+        one for each post.
+        """
+        subredditObject = self.reddit_client.subreddit(subreddit)
+        search_results = subredditObject.search(
+            query=query, sort=sort, time_filter=time_filter, limit=limit
+        )
+        search_results = [r for r in search_results]
+        results_object = []
+        for submission in search_results:
+            results_object.append(
+                {
+                    "post_subreddit": submission.subreddit_name_prefixed,
+                    "post_category": submission.category,
+                    "post_title": submission.title,
+                    "post_text": submission.selftext,
+                    "post_score": submission.score,
+                    "post_id": submission.id,
+                    "post_url": submission.url,
+                    "post_author": submission.author,
+                }
+            )
+        return results_object