templates: Add neo4j semantic layer with ollama template (#17192)

A template with JSON-based agent using Mixtral via Ollama.

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

templates/neo4j-semantic-ollama/README.md

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+# neo4j-semantic-ollama
+
+This template is designed to implement an agent capable of interacting with a graph database like Neo4j through a semantic layer using Mixtral as a JSON-based agent.
+The semantic layer equips the agent with a suite of robust tools, allowing it to interact with the graph database based on the user's intent.
+Learn more about the semantic layer template in the [corresponding blog post](https://medium.com/towards-data-science/enhancing-interaction-between-language-models-and-graph-databases-via-a-semantic-layer-0a78ad3eba49).
+
+![Diagram illustrating the workflow of the Neo4j semantic layer with an agent interacting with tools like Information, Recommendation, and Memory, connected to a knowledge graph.](https://raw.githubusercontent.com/langchain-ai/langchain/master/templates/neo4j-semantic-ollama/static/workflow.png "Neo4j Semantic Layer Workflow Diagram")
+
+## Tools
+
+The agent utilizes several tools to interact with the Neo4j graph database effectively:
+
+1. **Information tool**:
+   - Retrieves data about movies or individuals, ensuring the agent has access to the latest and most relevant information.
+2. **Recommendation Tool**:
+   - Provides movie recommendations based upon user preferences and input.
+3. **Memory Tool**:
+   - Stores information about user preferences in the knowledge graph, allowing for a personalized experience over multiple interactions.
+4. **Smalltalk Tool**:
+   - Allows an agent to deal with smalltalk.
+
+## Environment Setup
+
+Before using this template, you need to set up Ollama and Neo4j database.
+
+1. Follow instructions [here](https://python.langchain.com/docs/integrations/chat/ollama) to download Ollama.
+
+2. Download your LLM of interest:
+
+    * This package uses `mixtral`: `ollama pull mixtral`
+    * You can choose from many LLMs [here](https://ollama.ai/library)
+
+You need to define the following environment variables
+
+```
+OLLAMA_BASE_URL=<YOUR_OLLAMA_URL>
+NEO4J_URI=<YOUR_NEO4J_URI>
+NEO4J_USERNAME=<YOUR_NEO4J_USERNAME>
+NEO4J_PASSWORD=<YOUR_NEO4J_PASSWORD>
+```
+
+## Populating with data
+
+If you want to populate the DB with an example movie dataset, you can run `python ingest.py`.
+The script import information about movies and their rating by users.
+Additionally, the script creates two [fulltext indices](https://neo4j.com/docs/cypher-manual/current/indexes-for-full-text-search/), which are used to map information from user input to the database.
+
+## Usage
+
+To use this package, you should first have the LangChain CLI installed:
+
+```shell
+pip install -U "langchain-cli[serve]"
+```
+
+To create a new LangChain project and install this as the only package, you can do:
+
+```shell
+langchain app new my-app --package neo4j-semantic-ollama
+```
+
+If you want to add this to an existing project, you can just run:
+
+```shell
+langchain app add neo4j-semantic-ollama
+```
+
+And add the following code to your `server.py` file:
+```python
+from neo4j_semantic_layer import agent_executor as neo4j_semantic_agent
+
+add_routes(app, neo4j_semantic_agent, path="/neo4j-semantic-ollama")
+```
+
+(Optional) Let's now configure LangSmith. 
+LangSmith will help us trace, monitor and debug LangChain applications. 
+LangSmith is currently in private beta, you can sign up [here](https://smith.langchain.com/). 
+If you don't have access, you can skip this section
+
+```shell
+export LANGCHAIN_TRACING_V2=true
+export LANGCHAIN_API_KEY=<your-api-key>
+export LANGCHAIN_PROJECT=<your-project>  # if not specified, defaults to "default"
+```
+
+If you are inside this directory, then you can spin up a LangServe instance directly by:
+
+```shell
+langchain serve
+```
+
+This will start the FastAPI app with a server is running locally at 
+[http://localhost:8000](http://localhost:8000)
+
+We can see all templates at [http://127.0.0.1:8000/docs](http://127.0.0.1:8000/docs)
+We can access the playground at [http://127.0.0.1:8000/neo4j-semantic-ollama/playground](http://127.0.0.1:8000/neo4j-semantic-ollama/playground)  
+
+We can access the template from code with:
+
+```python
+from langserve.client import RemoteRunnable
+
+runnable = RemoteRunnable("http://localhost:8000/neo4j-semantic-ollama")
+```