Examples Update + Code Refactor (#25)

* Removed StorageManager

* Added examples for OpenAI, Bedrock, Anthropic, and VertexAI

* Updating old examples (1/2)

* Updating old examples (2/2)

examples/ack_test.yaml

@@ -1,6 +1,13 @@
 ---
 # Simple loopback flow
 # Solace -> Pass Through -> Solace
+# 
+# required ENV variables:
+# - SOLACE_BROKER_URL
+# - SOLACE_BROKER_USERNAME
+# - SOLACE_BROKER_PASSWORD
+# - SOLACE_BROKER_VPN
+
 log:
   stdout_log_level: DEBUG
   log_file_level: DEBUG

examples/anthropic_bedrock.yaml

@@ -4,6 +4,22 @@
 # sends the response back to the Solace broker
 # It will ask the model to write a dry joke about the input
 # message. It takes the entire payload of the input message
+# 
+# Dependencies:
+# pip install langchain_aws langchain_community
+# 
+# Dependencies:
+# - langchain_aws
+# pip install langchain_aws
+# 
+# required ENV variables:
+# - SOLACE_BROKER_URL
+# - SOLACE_BROKER_USERNAME
+# - SOLACE_BROKER_PASSWORD
+# - SOLACE_BROKER_VPN
+# - AWS_BEDROCK_ANTHROPIC_CLAUDE_MODEL_ID
+
+
 instance_name: LLM
 log:
   stdout_log_level: DEBUG
@@ -19,21 +35,6 @@ shared_config:
       broker_password: ${SOLACE_BROKER_PASSWORD}
       broker_vpn: ${SOLACE_BROKER_VPN}
 
-# Storage
-storage:
-  - storage_name: default
-    storage_type: file
-    storage_config: 
-      path: app/data.json
-  - storage_name: backup
-    storage_type: aws_s3
-    storage_config:
-      aws_access_key_id: ${AWS_ACCESS_KEY_ID}
-      aws_secret_access_key: ${AWS_SECRET_ACCESS_KEY}
-      aws_region_name: ${AWS_REGION_NAME}
-      bucket_name: ${AWS_BUCKET_NAME}
-      path: app/data.json
-
 # List of flows
 flows:
   - name: test_flow
@@ -90,7 +91,7 @@ flows:
           payload_format: text
         input_transforms:
           - type: copy
-            source_expression: user_data.temp
+            source_expression: previous
             dest_expression: user_data.output:payload
           - type: copy
             source_expression: template:response/{{text://input.topic}}

examples/chat_model_with_history.yaml

@@ -1,5 +1,12 @@
 ---
-# Example uses goes from STDIN to STDOUT with a chat model with history
+# Example uses goes from STDIN to STDOUT with a chat model with history hosted on AWS Bedrock
+
+# Dependencies:
+# pip install langchain_aws
+
+# required ENV variables:
+# - AWS_DEFAULT_REGION
+
 log:
   stdout_log_level: INFO
   log_file_level: DEBUG

examples/error_handler.yaml

@@ -1,8 +1,21 @@
 ---
 # This is an example configuration file that contains an 
 # error handler flow and a test flow. The error handler flow
-# will log any error messages locally and will also
-# send them to a Solace broker. 
+# will log any error messages locally to a file and will also
+# send them to a Solace broker.
+#
+# It will subscribe to `my/topic1` and expect an event with the payload:
+# {
+#   "value": <number>
+# }
+# If value is not a number, the error will be caught, logged to file and send back to the Solace broker.
+# 
+# required ENV variables:
+# - SOLACE_BROKER_URL
+# - SOLACE_BROKER_USERNAME
+# - SOLACE_BROKER_PASSWORD
+# - SOLACE_BROKER_VPN
+
 instance:
   name: solace_ai_connector1
 log:
@@ -27,12 +40,19 @@ flows:
         component_module: error_input
         component_config:
       - component_name: error_logger
-        component_module: logger
-        component_config:
-          log_level: ERROR
-          max_log_line_size: 1000
+        component_module: file_output
+        input_transforms:
+          - type: copy
+            source_expression: input.payload
+            dest_expression: user_data.log:content
+          - type: copy
+            source_value: a
+            dest_expression: user_data.log:mode
+          - type: copy
+            source_value: error_log.log
+            dest_expression: user_data.log:file_path
         component_input:
-          source_expression: input.payload
+          source_expression: user_data.log
       - component_name: solace_sw_broker
         component_module: broker_output
         component_config: 
@@ -66,7 +86,7 @@ flows:
             - topic: my/topic1
               qos: 1
           payload_encoding: utf-8
-          payload_format: text
+          payload_format: json
 
       - component_name: pass_through
         component_module: pass_through
@@ -89,6 +109,16 @@ flows:
           - type: copy
             source_expression: input.payload
             dest_expression: user_data.output:payload.original_payload
+          - type: copy
+            source_expression: 
+              invoke:
+                module: invoke_functions
+                function: power
+                params:
+                  positional:
+                    - source_expression(input.payload:value) # This will throw an error if value is not a number
+                    - 2
+            dest_expression: user_data.output:payload.valueSquared
           - type: copy
             source_expression: input.user_properties
             dest_expression: user_data.output:payload.user_properties

examples/llm/anthropic_chat.yaml

@@ -0,0 +1,99 @@
+# This will create a flow like this:
+#    Solace -> Anthropic -> Solace
+#
+# It will subscribe to `demo/question` and expect an event with the payload:
+#
+# The input message has the following schema:
+# {
+#   "text": "<question or request as text>"
+# }
+#
+# It will then send an event back to Solace with the topic: `demo/question/response`
+#
+# Dependencies:
+# pip install -U langchain-anthropic
+#
+# required ENV variables:
+# - ANTHROPIC_API_KEY
+# - ANTHROPIC_API_ENDPOINT
+# - MODEL_NAME
+# - SOLACE_BROKER_URL
+# - SOLACE_BROKER_USERNAME
+# - SOLACE_BROKER_PASSWORD
+# - SOLACE_BROKER_VPN
+
+---
+log:
+  stdout_log_level: INFO
+  log_file_level: DEBUG
+  log_file: solace_ai_connector.log
+
+shared_config:
+  - broker_config: &broker_connection
+      broker_type: solace
+      broker_url: ${SOLACE_BROKER_URL}
+      broker_username: ${SOLACE_BROKER_USERNAME}
+      broker_password: ${SOLACE_BROKER_PASSWORD}
+      broker_vpn: ${SOLACE_BROKER_VPN}
+
+# Take from Slack and publish to Solace
+flows:
+  # Slack chat input processing
+  - name: Simple template to LLM
+    components:
+      # Input from a Solace broker
+      - component_name: solace_sw_broker
+        component_module: broker_input
+        component_config:
+          <<: *broker_connection
+          broker_queue_name: demo_question
+          broker_subscriptions:
+            - topic: demo/question
+              qos: 1
+          payload_encoding: utf-8
+          payload_format: json
+
+      #
+      # Do an LLM request
+      #
+      - component_name: llm_request
+        component_module: langchain_chat_model
+        component_config:
+          langchain_module: langchain_anthropic
+          langchain_class: ChatAnthropic
+          langchain_component_config:
+            api_key: ${ANTHROPIC_API_KEY}
+            base_url: ${ANTHROPIC_API_ENDPOINT}
+            model: ${MODEL_NAME}
+            temperature: 0.01
+        input_transforms:
+          - type: copy
+            source_expression: |
+              template:You are a helpful AI assistant. Please help with the user's request below:
+              <user-question>
+              {{text://input.payload:text}}
+              </user-question>
+            dest_expression: user_data.llm_input:messages.0.content
+          - type: copy
+            source_expression: static:user
+            dest_expression: user_data.llm_input:messages.0.role
+        component_input:
+          source_expression: user_data.llm_input
+
+      # Send response back to broker
+      - component_name: send_response
+        component_module: broker_output
+        component_config:
+          <<: *broker_connection
+          payload_encoding: utf-8
+          payload_format: json
+          copy_user_properties: true
+        input_transforms:
+          - type: copy
+            source_expression: previous
+            dest_expression: user_data.output:payload
+          - type: copy
+            source_expression: template:{{text://input.topic}}/response
+            dest_expression: user_data.output:topic
+        component_input:
+          source_expression: user_data.output

examples/llm/bedrock_anthropic_chat.yaml

@@ -7,8 +7,16 @@
 #
 # The input message has the following schema:
 # {
-#   "text": "<question or request as text>",
+#   "text": "<question or request as text>"
 # }
+# 
+# Dependencies:
+# pip install langchain_aws
+# 
+# required ENV variables:
+# - AWS_BEDROCK_ANTHROPIC_CLAUDE_MODEL_ID
+# - AWS_BEDROCK_ANTHROPIC_CLAUDE_REGION
+
 ---
 log:
   stdout_log_level: DEBUG
@@ -35,8 +43,8 @@ flows:
       - component_name: llm_request
         component_module: langchain_chat_model
         component_config:
-          langchain_module: langchain_community.chat_models
-          langchain_class: BedrockChat
+          langchain_module: langchain_aws
+          langchain_class: ChatBedrock
           langchain_component_config:
             model_id: ${AWS_BEDROCK_ANTHROPIC_CLAUDE_MODEL_ID}
             region_name: ${AWS_BEDROCK_ANTHROPIC_CLAUDE_REGION}

examples/llm/langchain_openai_with_history_chat.yaml

@@ -0,0 +1,98 @@
+# This will create a flow like this:
+#    Solace -> OpenAI -> Solace
+#
+# It will subscribe to `demo/joke/subject` and expect an event with the payload:
+#
+# {
+#   "joke": {
+#     "subject": "<subject for the joke>"
+#   }
+# }
+#
+# It will then send an event back to Solace with the topic: `demo/joke/subject/response`
+#
+# Dependencies:
+# pip install -U langchain_openai openai
+#
+# required ENV variables:
+# - OPENAI_API_KEY
+# - OPENAI_API_ENDPOINT - optional
+# - MODEL_NAME
+# - SOLACE_BROKER_URL
+# - SOLACE_BROKER_USERNAME
+# - SOLACE_BROKER_PASSWORD
+# - SOLACE_BROKER_VPN
+
+---
+log:
+  stdout_log_level: INFO
+  log_file_level: DEBUG
+  log_file: solace_ai_connector.log
+
+shared_config:
+  - broker_config: &broker_connection
+      broker_type: solace
+      broker_url: ${SOLACE_BROKER_URL}
+      broker_username: ${SOLACE_BROKER_USERNAME}
+      broker_password: ${SOLACE_BROKER_PASSWORD}
+      broker_vpn: ${SOLACE_BROKER_VPN}
+
+# Take from Slack and publish to Solace
+flows:
+  # Slack chat input processing
+  - name: Simple template to LLM
+    components:
+      # Input from a Solace broker
+      - component_name: solace_sw_broker
+        component_module: broker_input
+        component_config:
+          <<: *broker_connection
+          broker_queue_name: ed_demo_joke
+          broker_subscriptions:
+            - topic: demo/joke/subject
+              qos: 1
+          payload_encoding: utf-8
+          payload_format: json
+
+      # Go to the LLM and keep history
+      - component_name: chat_request_llm
+        component_module: langchain_chat_model_with_history
+        component_config:
+          langchain_module: langchain_openai
+          langchain_class: ChatOpenAI
+          langchain_component_config:
+            api_key: ${OPENAI_API_KEY}
+            base_url: ${OPENAI_API_ENDPOINT}
+            model: ${MODEL_NAME}
+            temperature: 0.01
+          history_module: langchain_core.chat_history
+          history_class: InMemoryChatMessageHistory
+          history_max_turns: 20
+          history_max_length: 6000
+        input_transforms:
+          - type: copy
+            source_expression: template:Write a joke about {{text://input.payload:joke.subject}}
+            dest_expression: user_data.input:messages.0.content
+          - type: copy
+            source_value: user
+            dest_expression: user_data.input:messages.0.role
+        component_input:
+          source_expression: user_data.input
+
+      # Send response back to broker
+      - component_name: send_response
+        component_module: broker_output
+        component_config:
+          <<: *broker_connection
+          payload_encoding: utf-8
+          payload_format: json
+          copy_user_properties: true
+        input_transforms:
+          - type: copy
+            source_expression: previous
+            dest_expression: user_data.output:payload
+          - type: copy
+            source_expression: template:{{text://input.topic}}/response
+            dest_expression: user_data.output:topic
+        component_input:
+          source_expression: user_data.output