feat: add integration with OpenAI, Groq, and LangChain agents and added format converters

Author: tedi-software

docs/_includes/head_custom.html

@@ -103,14 +103,35 @@
 
 
 {% elsif page.title == "Processors" %}
-<title>TEDI | HTTP, SFTP, Oracle, SQLServer, PGP, XSLT, NATS</title>
+<title>TEDI | HTTP, SFTP, Oracle, SQLServer, PGP, XSLT, NATS, AI</title>
+
+    {% elsif page.title == "ai_transform_groq" %}
+    <title>TEDI | AI-powered data transformation using GROQ models</title>
+
+    {% elsif page.title == "ai_transform_openai" %}
+    <title>TEDI | AI-powered data transformation using OpenAI models</title>
+
+    {% elsif page.title == "ai_transform_langchain" %}
+    <title>TEDI | AI-powered data transformation using LangChain</title>
 
     {% elsif page.title == "cmdin" %}
     <title>TEDI | Run an external command to provide custom logic</title>
 
     {% elsif page.title == "cmdout" %}
     <title>TEDI | Run an external command in your workflow integration</title>
 
+    {% elsif page.title == "converter_xml_to_json" %}
+    <title>TEDI | Convert XML data to JSON format</title>
+
+    {% elsif page.title == "converter_json_to_csv" %}
+    <title>TEDI | Convert JSON data to CSV format</title>
+
+    {% elsif page.title == "converter_csv_to_json" %}
+    <title>TEDI | Convert CSV data to JSON format</title>
+
+    {% elsif page.title == "converter_json_to_xml" %}
+    <title>TEDI | Convert JSON data to XML format</title>
+
     {% elsif page.title == "httpin" %}
     <title>TEDI | Adapter to integrate with RESTful HTTP APIs</title>
 

docs/pages/architecture.md

@@ -35,6 +35,8 @@ Composable Architecture
 {: .label .label-blue } 
 Microservices
 {: .label .label-green }
+AI Agent Integration
+{: .label .label-blue }
 
 ---
 
@@ -51,6 +53,8 @@ Middleware
 {: .label .label-yellow }
 System Integration
 {: .label .label-red }
+AI Agent Integration
+{: .label .label-blue }
 
 ---
 

docs/pages/feedback.md docs/pages/contact-us.mddocs/pages/feedback.md renamed to docs/pages/contact-us.md

@@ -1,7 +1,7 @@
 ---
 layout: page
-title: Feedback
-permalink: /feedback/
+title: Contact Us
+permalink: /contact/
 nav_order: 7
 has_children: false
 description: "TEDI can support all of your integration needs. Contact us to request features, provide feedback, and to stay in touch for future features and functions"
@@ -14,7 +14,7 @@ description: "TEDI can support all of your integration needs. Contact us to requ
 
 We are always striving to improve and provide the best possible integration software to our clients. To help us achieve this, your feedback is incredibly valuable.
 
-We would love to hear your thoughts on your experience with us, as well as any suggestions you might have for improvement. Please feel free to share your feedback by emailing us at [tedi-support](mailto:tedi-help@outlook.com) or come find us over on [GitHub](https://github.com/tedi-software/tedi).
+We would love to hear your thoughts on your experience with TEDI, as well as any suggestions you might have for improvement. Please feel free to share your feedback by emailing us at [tedi-support](mailto:tedi-help@outlook.com) or come find us over on [GitHub](https://github.com/tedi-software/tedi).
 
 Thank you for taking the time to share your insights. We look forward to hearing from you and using your input to serve you even better in the future.
 

docs/pages/index.md

@@ -14,6 +14,8 @@ In today’s fast-paced business world, companies rely on multiple software appl
 
 **TEDI** is the key to unlocking the full potential of your business software. By connecting systems and automating workflows, TEDI helps companies operate more efficiently, reduce costs, and make smarter, data-driven decisions. If you're looking to future-proof your organization and break down operational silos, TEDI is the solution you need.
 
+**TEDI** is now **AI-capable** — enabling integration with Groq, OpenAI, and LangChain to introduce intelligent reasoning, transformation, and decision-making steps directly into your workflows. Whether you're enriching data, generating structured outputs, or applying context-aware logic, TEDI can now incorporate AI models into pipelines with ease.
+
 
 {: .important-title }
 > QUICK START
@@ -70,6 +72,12 @@ Implementing TEDI can have transformative benefits for your business:
 ## TEDI Use Cases
 {: .fs-6 }
 
+**Why pay for for expensive COTS software and iPaaS solutions ?**
+
+{: .highlight }
+> TEDI gives you a self-hosted, no-bloat integration engine to move data between systems, files, and APIs — using config files, not consultants.
+
+
 1. **Automated Order Processing**: Connect your e-commerce, inventory, and shipping systems so that orders are processed and fulfilled without manual intervention.
 
 2. **Data Consolidation**: Aggregate customer data from multiple channels (e.g., CRM, support, marketing) into a single, unified view.
@@ -78,9 +86,10 @@ Implementing TEDI can have transformative benefits for your business:
 
 4. **Business-to-Business (B2B)**: Integrate and exchange documents with 3rd party logistics, supply chains, anti-fraud, invoicing and orders, all-things business intelligence and data analytics, and much much more.
 
+
 ---
 
-## Getting Started
+## Getting Started with TEDI
 {: .fs-6 }
 
 Getting started with TEDI is easy. To begin your journey:
@@ -91,3 +100,12 @@ Getting started with TEDI is easy. To begin your journey:
 1. Learn about the TEDI [tools]({{site.baseurl}}/tools).
 1. Finally, learn how to build an integration in [Building Integrations]({{site.baseurl}}/integrations).
 
+---
+
+## Need Help or Want a Demo ?
+{: .fs-6 }
+
+- Email for support [TEDI Support](mailto:tedi-help@outlook.com)
+- Book a free 30-minute demo [TEDI Demo](mailto:tedi-help@outlook.com)
+- Have questions ? [Ask a Question](https://github.com/tedi-software/tedi/discussions).
+- [contact us]({{site.baseurl}}/contact)

docs/pages/proc-ai-transform-groq.md

@@ -0,0 +1,39 @@
+---
+layout: page
+title: ai_transform_groq
+parent: Processors
+permalink: /processors/ai-transform-groq
+description: "Integrate Groq for AI-driven reasoning, dynamic data transformation, and intelligent logic steps in system workflows."
+---
+
+# ai_transform_groq Processor
+{: .fs-7 }
+
+The **`ai_transform_groq`** processor enables seamless integration with Groq's high-performance LLMs as a reasoning or transformation step within your data pipeline. 
+
+Use it to inject AI-powered decision-making, contextual analysis, or format conversion directly into your workflows. Whether you're enriching records, restructuring output, or applying custom logic through prompts — this processor gives you a flexible, extensible interface to Groq's models. 
+
+The use cases are virtually unlimited.
+
+---
+
+**Settings**
+{: .fs-4 }
+
+
+| **Setting**                   | **Description**           |
+|:------------------------------|:--------------------------|
+| `sub.service.type.config`     | http configuration (httpout service settings) to make the API requests (inc_http.properties) |
+| `groq.model`                  | specify the LLM name (e.g. mixtral-8x7b, gpt-4,llama3-70b-8192) |
+| `groq.temperature`            | controls randomness (0 = deterministic, 1 = creative) |
+| `groq.top.p`                  | nucleus sampling (0–1); often left at 1.0 |
+| `groq.max.tokens`             | limit token output (helps cost, latency) |
+| `groq.stop`                   | custom stop sequences (e.g. ["\n\n"]) |
+|                               | note: not curerntly used | 
+| `groq.response.format`        | controls how the AI service formats its response [ text \| json_object ]| 
+| `groq.response.output.format` |  format to extract from the response [json, xml, csv, raw, regex] | 
+| `groq.response.output.format.regex`        | use a regular expression to extract the desired content | 
+| `groq.response.output.format.regex.group`  | if using regex, specify the group (optional) | 
+| `groq.prompt.templated `            | allow the use of templated prompts in the AI service | 
+| `groq.log.prompt`            | log the prompt (only if templated prompt is used) | 
+| `groq.prompt`               | the prompt to use for the AI service.  | 

docs/pages/proc-ai-transform-langchain.md

@@ -0,0 +1,39 @@
+---
+layout: page
+title: ai_transform_langchain
+parent: Processors
+permalink: /processors/ai-transform-langchain
+description: "Integrate LangChain for AI-powered reasoning, transformation, and dynamic logic in your system workflows."
+
+---
+
+# ai_transform_langchain Processor
+{: .fs-7 }
+
+The **`ai_transform_langchain`** processor integrates with LangChain to perform AI-driven reasoning, transformation, and logic within your data pipeline.  
+
+Use it to execute chains that perform contextual analysis, enrich or restructure data, or apply prompt-driven logic to dynamic inputs.  
+Whether you're leveraging LLMs to interpret, reformat, or route content — this processor gives you a flexible interface to LangChain’s powerful capabilities.
+
+The use cases are virtually unlimited.
+
+---
+
+**Settings**
+{: .fs-4 }
+
+
+| **Setting**                   | **Description**           |
+|:------------------------------|:--------------------------|
+| `sub.service.type.config`     | http configuration (httpout service settings) to make the API requests (inc_http.properties) |
+| `langchain.chain.name`        | chain name to invoke on the LangChain server |
+| `langchain.temperature`       | controls randomness (0 = deterministic, 1 = creative) |
+| `langchain.top.p`             | nucleus sampling (0–1); often left at 1.0 |
+| `langchain.max.tokens`        | limit token output (helps cost, latency) |
+| `langchain.response.format`        | controls how the AI service formats its response [ text \| json_object ]| 
+| `langchain.response.output.format` |  format to extract from the response [json, xml, csv, raw, regex] | 
+| `langchain.response.output.format.regex`        | use a regular expression to extract the desired content | 
+| `langchain.response.output.format.regex.group`  | if using regex, specify the group (optional) | 
+| `langchain.prompt.templated `            | allow the use of templated prompts in the AI service | 
+| `langchain.log.prompt`            | log the prompt (only if templated prompt is used) | 
+| `langchain.prompt`               | the prompt to use for the AI service.  | 

docs/pages/proc-ai-transform-openai.md

@@ -0,0 +1,39 @@
+---
+layout: page
+title: ai_transform_openai
+parent: Processors
+permalink: /processors/ai-transform-openai
+description: "Integrate OpenAI for AI-driven reasoning, dynamic data transformation, and intelligent logic steps in system workflows."
+---
+
+# ai_transform_openai Processor
+{: .fs-7 }
+
+The **`ai_transform_openai`** processor enables seamless integration with OpenAI's high-performance LLMs as a reasoning or transformation step within your data pipeline. 
+
+Use it to inject AI-powered decision-making, contextual analysis, or format conversion directly into your workflows. Whether you're enriching records, restructuring output, or applying custom logic through prompts — this processor gives you a flexible, extensible interface to openai's models. 
+
+The use cases are virtually unlimited.
+
+---
+
+**Settings**
+{: .fs-4 }
+
+
+| **Setting**                   | **Description**           |
+|:------------------------------|:--------------------------|
+| `sub.service.type.config`     | http configuration (httpout service settings) to make the API requests (inc_http.properties) |
+| `openai.model`                  | specify the LLM name (e.g. mixtral-8x7b, gpt-4,llama3-70b-8192) |
+| `openai.temperature`            | controls randomness (0 = deterministic, 1 = creative) |
+| `openai.top.p`                  | nucleus sampling (0–1); often left at 1.0 |
+| `openai.max.tokens`             | limit token output (helps cost, latency) |
+| `openai.stop`                   | custom stop sequences (e.g. ["\n\n"]) |
+|                               | note: not curerntly used | 
+| `openai.response.format`        | controls how the AI service formats its response [ text \| json_object ]| 
+| `openai.response.output.format` |  format to extract from the response [json, xml, csv, raw, regex] | 
+| `openai.response.output.format.regex`        | use a regular expression to extract the desired content | 
+| `openai.response.output.format.regex.group`  | if using regex, specify the group (optional) | 
+| `openai.prompt.templated `            | allow the use of templated prompts in the AI service | 
+| `openai.log.prompt`            | log the prompt (only if templated prompt is used) | 
+| `openai.prompt`               | the prompt to use for the AI service.  | 

docs/pages/proc-cmdin.md

@@ -3,7 +3,6 @@ layout: page
 title: cmdin
 parent: Processors
 permalink: /processors/cmdin
-nav_order: 5
 description: "Add custom logic to your integration workflows by using the output of external commands or programs as input, enhancing automation and flexibility"
 ---
 

docs/pages/proc-cmdout.md

@@ -3,7 +3,6 @@ layout: page
 title: cmdout
 parent: Processors
 permalink: /processors/cmdout
-nav_order: 6
 description: "Leverage external commands or programs to introduce specialized logic into your integrations, giving you enhanced control over data processing"
 ---
 

docs/pages/proc-convert-csv-to-json.md

@@ -0,0 +1,29 @@
+---
+layout: page
+title: converter_csv_to_json
+parent: Processors
+permalink: /processors/converter-csv-to-json
+description: "Convert CSV to JSON or JSONL automatically to streamline data processing and system integration."
+---
+
+# converter_csv_to_json Processor
+{: .fs-7 }
+
+The **`converter_csv_to_json`** processor transforms a CSV document into either a structured JSON array or line-delimited JSON (JSONL).  
+
+Use this processor to convert tabular data into a format suitable for APIs, data pipelines, or storage systems that require JSON.
+
+---
+
+**Settings**
+{: .fs-4 }
+
+
+| **Setting**                   | **Description**           |
+|:------------------------------|:--------------------------|
+| `timeout`                     | maximum time allowed to complete the conversion |
+| `field.delimiter`             | indicate the field delimiter, e.g. comma, semicolon, tab (\t), ^, \|, etc.  comma is the default delimiter for CSV files |
+| `file.includes.headers`       | indicate the first line of the CSV file contains headers |
+| `file.headers`                | specify the headers directly (if the file itself does not contain them) - comma delimited |
+|                               | note: if file.includes.headers=false and file.headers is not set the converter will use default headers: col1, col2, col3, etc. |
+| `output.format`               | output the result as json array (default) or jsonl |