[Enhancement] Python version support 3.11-3.13

.github/workflows/ci.yml

@@ -40,7 +40,7 @@ jobs:
       - uses: actions/setup-python@v6
         id: setup-python
         with:
-          python-version: "3.9.25"
+          python-version: "3.11.14"
 
       # ---- Install uv ----
       - name: Install uv

.github/workflows/publish.yml

@@ -16,7 +16,7 @@ jobs:
       - name: Set up Python
         uses: actions/setup-python@v6
         with:
-          python-version: "3.9"
+          python-version: "3.11"
 
       - name: Install uv
         run: |

docs/installation.md

@@ -1,12 +1,12 @@
 
 # Installation Guide
 
-1. Create an environment with Python `3.9` or higher, using `pyenv` or `conda`.
+1. Create an environment with Python `3.11` or higher, using `pyenv` or `conda`.
     * For `pyenv`, use the following commands:
         ```bash
         brew install pyenv
-        pyenv install 3.9
-        pyenv local 3.9
+        pyenv install 3.11
+        pyenv local 3.11
         ```
     * To set up your PATH automatically every time you open a shell session, add this to your .zshrc file:
         ```bash

docs/library/sygra_library.md

@@ -17,7 +17,7 @@ The **SyGra Library** provides a high-level Python interface for building and ex
 
 ## Installation
 
-Requirements: Python 3.9-3.11 recommended. We also recommend upgrading `pip` first.
+Requirements: Python 3.11-3.13 recommended. We also recommend upgrading `pip` first.
 
 **Install from PyPI**
 ```bash
@@ -117,7 +117,7 @@ workflow.llm("gpt-4o", "Summarize: {text}")
 ```python
 workflow.llm(
     model={
-        "name": "gpt-4o", 
+        "name": "gpt-4o",
         "parameters": {"temperature": 0.7, "max_tokens": 2000}
     },
     prompt=[
@@ -180,8 +180,8 @@ class TextProcessor(LambdaFunction):
     def apply(lambda_node_dict: dict, state: SygraState):
         text = state.get("text", "").strip().lower()
         return {
-            **state, 
-            "processed_text": text, 
+            **state,
+            "processed_text": text,
             "word_count": len(text.split())
         }
 
@@ -205,11 +205,11 @@ workflow.lambda_func(extract_keywords, output="keywords")
 class DataValidator:
     def __init__(self, config):
         self.config = config
-    
+
     def __call__(self, data):
         score = len(data["text"]) / 100
         return {
-            "quality_score": min(1.0, score), 
+            "quality_score": min(1.0, score),
             "is_valid": score > self.config["threshold"]
         }
 
@@ -239,9 +239,9 @@ workflow = sygra.Workflow("existing_task") \
 
 ```python
 workflow.override_model(
-    node_name="analyzer", 
-    model_name="gpt-4o", 
-    temperature=0.8, 
+    node_name="analyzer",
+    model_name="gpt-4o",
+    temperature=0.8,
     max_tokens=1500
 )
 ```
@@ -250,9 +250,9 @@ workflow.override_model(
 
 ```python
 workflow.override_prompt(
-    node_name="generator", 
-    role="system", 
-    content="You are a helpful assistant", 
+    node_name="generator",
+    role="system",
+    content="You are a helpful assistant",
     index=0
 )
 ```
@@ -263,15 +263,15 @@ workflow.override_prompt(
 # Override glaive_code_assistant task configuration
 workflow = sygra.Workflow("examples/glaive_code_assistant") \
     .override_prompt(
-        "generate_answer", 
-        "user", 
-        "Solve step by step: {question}", 
+        "generate_answer",
+        "user",
+        "Solve step by step: {question}",
         index=1
     ) \
     .override_prompt(
-        "critique_answer", 
-        "system", 
-        "Be thorough in your code review", 
+        "critique_answer",
+        "system",
+        "Be thorough in your code review",
         index=0
     ) \
     .override_model("generate_answer", "gpt-4o", temperature=0.2) \
@@ -342,17 +342,17 @@ class InputValidator(NodePreProcessor):
         # Validate required fields
         if "text" not in state or not state["text"]:
             state["text"] = "[MISSING_TEXT]"
-        
+
         # Add metadata
         state["validated"] = True
         state["timestamp"] = datetime.now().isoformat()
-        
+
         return state
 
 # Use in workflow
 workflow.llm(
-    "gpt-4o", 
-    "Process: {text}", 
+    "gpt-4o",
+    "Process: {text}",
     pre_process=InputValidator
 )
 ```
@@ -367,7 +367,7 @@ from sygra.core.graph.functions.node_processor import NodePostProcessor
 class ResponseFormatter(NodePostProcessor):
     def apply(self, response: SygraMessage) -> SygraState:
         content = response.message.content
-        
+
         return {
             "formatted_response": content.strip(),
             "response_length": len(content),
@@ -377,8 +377,8 @@ class ResponseFormatter(NodePostProcessor):
 
 # Use in workflow
 workflow.llm(
-    "gpt-4o", 
-    "Analyze: {text}", 
+    "gpt-4o",
+    "Analyze: {text}",
     post_process=ResponseFormatter
 )
 ```
@@ -394,17 +394,17 @@ class QualityAnalyzer(NodePostProcessorWithState):
     def apply(self, response: SygraMessage, state: SygraState) -> SygraState:
         content = response.message.content
         original_text = state.get("text", "")
-        
+
         # Calculate quality metrics
         quality_score = self._calculate_quality(original_text, content)
-        
+
         return {
             **state,  # Preserve original state
             "processed_response": content,
             "quality_score": quality_score,
             "is_high_quality": quality_score > 0.7
         }
-    
+
     def _calculate_quality(self, original, response):
         # Your quality calculation logic
         return 0.85
@@ -531,7 +531,7 @@ workflow = sygra.Workflow("research_assistant") \
     ) \
     .multi_llm(
         models={
-            "summarizer": "gpt-4o", 
+            "summarizer": "gpt-4o",
             "reviewer": "claude-3-sonnet"
         },
         prompt="Synthesize research findings: {messages}"
@@ -551,4 +551,3 @@ workflow = sygra.Workflow("research_assistant") \
 | `workflow.run()` | `List[Dict]` or `Any` | Processed results |
 | `graph.build()` | `ExecutableGraph` | Built graph object |
 | `graph.run()` | `List[Dict]` or `Any` | Execution results |
-

pyproject.toml

@@ -7,7 +7,7 @@ name = "sygra"
 version = "1.0.0"
 description = "Graph-oriented Synthetic data generation Pipeline library"
 readme = "README.md"
-requires-python = ">=3.9,<3.12,!=3.9.7"
+requires-python = ">=3.11,<3.14"
 authors = [{ name = "Bidyapati Pradhan, Surajit Dasgupta, Amit Kumar Saha, Sriram Puttagunta, Omkar Anustoop, Vipul Mittal, Gopal Sarda", email = "[email protected]" }]
 maintainers = [
   { name = "SyGra Team", email = "[email protected]" }
@@ -20,9 +20,9 @@ classifiers = [
   "Topic :: Software Development :: Libraries",
   "License :: OSI Approved :: Apache Software License",
   "Programming Language :: Python :: 3",
-  "Programming Language :: Python :: 3.9",
-  "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
+  "Programming Language :: Python :: 3.12",
+  "Programming Language :: Python :: 3.13",
   "Operating System :: OS Independent",
 ]
 keywords = ["llm", "fine-tuning", "data generation", "synthetic data", "nlp", "sft", "dpo", "data quality", "metadata tagging", "graph",]
@@ -51,22 +51,22 @@ dependencies = [
   "langchain-openai>=0.3,<1.0",
   "ollama>=0.5,<1.0",
   "torch>=2.8,<3.0",
-  "mlxtend>=0.23,<1.0",
+  "mlxtend>=0.24,<1.0",
   "pandarallel>=1.6,<2.0",
   "sentence-transformers>=5.1,<6.0",
   "soundfile>=0.13,<1.0",
   "types-pyyaml>=6.0,<7.0",
   "fasttext-wheel>=0.9.2,<0.10.0",
-  "litellm>=1.79.3,<2.0.0",
-  "pysnc>=1.1.0,<1.2.0",
-  "boto3>=1.40.71,<2.0.0",
+  "litellm>=1.80.11,<2.0.0",
+  "pysnc>=1.2.0,<2.0.0",
+  "boto3>=1.34,<2.0.0",
   "google-auth>=2.43.0,<3.0.0",
   "google-cloud-aiplatform>=1.128.0,<2.0.0",
 ]
 
 [project.optional-dependencies]
 ui = [
-  "streamlit>=1.49,<2.0; python_version != '3.9.7'",
+  "streamlit>=1.49,<2.0",
   "streamlit-agraph>=0.0,<1.0",
   "streamlit-autorefresh>=1.0,<2.0",
   "streamlit-flow-component>=1.6,<2.0",