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Update documentation: reduce code examples, add cookbook links, improve structure

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- Reduced code examples in all guide pages (getting-started, quickstart, concepts, modules, examples, use-cases, learning-more)
- Added comprehensive cookbook links with descriptions (topics, difficulty, time, use cases)
- Improved structure and organization across all guide pages
- Updated use-cases.md to only include use cases with corresponding cookbooks
- Removed 'Last Updated: 2024' from all documentation files
- Enhanced navigation with better 'Next Steps' sections
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KaifAhmad1
2025-12-31 15:19:08 +05:30
parent 35391382d3
commit 04eea7e7eb
34 changed files with 2243 additions and 1496 deletions
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docs/reference/context.md
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@@ -57,12 +57,13 @@ The **Context Module** provides agents with a persistent, searchable, and struct
The high-level facade that unifies all context operations. It routes data to the appropriate subsystems (Memory, Graph, Vector Store) and manages the lifecycle of context.
#### **Constructor Parameters**
* `vector_store` (Required): The backing vector database instance (e.g., FAISS, Weaviate).
* `knowledge_graph` (Optional): The graph store instance for structured knowledge.
* `token_limit` (Default: `2000`): The maximum number of tokens allowed in short-term memory before pruning occurs.
* `short_term_limit` (Default: `10`): The maximum number of distinct memory items in short-term memory.
* `hybrid_alpha` (Default: `0.5`): The weighting factor for retrieval (0.0 = Pure Vector, 1.0 = Pure Graph).
* `use_graph_expansion` (Default: `True`): Whether to fetch neighbors of retrieved nodes from the graph.
- `` `vector_store` `` (Required): The backing vector database instance (e.g., FAISS, Weaviate)
- `` `knowledge_graph` `` (Optional): The graph store instance for structured knowledge
- `` `token_limit` `` (Default: `` `2000` ``): The maximum number of tokens allowed in short-term memory before pruning occurs
- `` `short_term_limit` `` (Default: `` `10` ``): The maximum number of distinct memory items in short-term memory
- `` `hybrid_alpha` `` (Default: `` `0.5` ``): The weighting factor for retrieval (`` `0.0` `` = Pure Vector, `` `1.0` `` = Pure Graph)
- `` `use_graph_expansion` `` (Default: `` `True` ``): Whether to fetch neighbors of retrieved nodes from the graph
#### **Core Methods**
@@ -507,5 +508,15 @@ context_config.set("retention_days", 60)
- [Reasoning](reasoning.md) - Uses context for logic
## Cookbook
- [Context Module](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/introduction/19_Context_Module.ipynb)
- [Advanced Context Engineering](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/advanced/11_Advanced_Context_Engineering.ipynb)
Interactive tutorials to learn context management and GraphRAG:
- **[Context Module](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/introduction/19_Context_Module.ipynb)**: Practical guide to the context module for AI agents
- **Topics**: Agent memory, context graph, hybrid retrieval, entity linking
- **Difficulty**: Intermediate
- **Use Cases**: Building stateful AI agents, persistent memory systems
- **[Advanced Context Engineering](https://github.com/Hawksight-AI/semantica/blob/main/cookbook/advanced/11_Advanced_Context_Engineering.ipynb)**: Build a production-grade memory system for AI agents
- **Topics**: Agent memory, GraphRAG, entity injection, lifecycle management, persistent stores
- **Difficulty**: Advanced
- **Use Cases**: Production agent systems, advanced memory management