Documentation updates for pg_semantic_cache

docs/LICENSE.md

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+PostgreSQL License
+
+Copyright (c) 2024, Aqeel
+
+Permission to use, copy, modify, and distribute this software and its
+documentation for any purpose, without fee, and without a written agreement
+is hereby granted, provided that the above copyright notice and this
+paragraph and the following two paragraphs appear in all copies.
+
+IN NO EVENT SHALL THE AUTHOR BE LIABLE TO ANY PARTY FOR DIRECT, INDIRECT,
+SPECIAL, INCIDENTAL, OR CONSEQUENTIAL DAMAGES, INCLUDING LOST PROFITS,
+ARISING OUT OF THE USE OF THIS SOFTWARE AND ITS DOCUMENTATION, EVEN IF THE
+AUTHOR HAS BEEN ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+
+THE AUTHOR SPECIFICALLY DISCLAIMS ANY WARRANTIES, INCLUDING, BUT NOT LIMITED
+TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
+PURPOSE. THE SOFTWARE PROVIDED HEREUNDER IS ON AN "AS IS" BASIS, AND THE
+AUTHOR HAS NO OBLIGATIONS TO PROVIDE MAINTENANCE, SUPPORT, UPDATES,
+ENHANCEMENTS, OR MODIFICATIONS.

docs/architecture.md

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+# Architecture
+
+The pg_semantic_cache extension is implemented in pure C using the PostgreSQL
+extension API (PGXS). This implementation approach provides several benefits
+for performance and compatibility.
+
+The extension provides the following benefits:
+
+- The small binary size is approximately 100KB versus 2-5MB for Rust versions.
+- Fast build times range from 10-30 seconds versus 2-5 minutes for Rust.
+- Immediate compatibility works with new PostgreSQL versions immediately.
+- Standard packaging is compatible with all PostgreSQL packaging tools.
+
+## How It Works
+
+The following diagram illustrates the semantic cache workflow:
+
+```mermaid
+graph LR
+    A[Query] --> B[Generate Embedding]
+    B --> C{Cache Lookup}
+    C -->|Hit| D[Return Cached Result]
+    C -->|Miss| E[Execute Query]
+    E --> F[Store Result + Embedding]
+    F --> G[Return Result]
+```
+
+The semantic cache operates through the following workflow:
+
+1. The application generates an embedding by converting query text into a
+   vector embedding using a preferred model (OpenAI, Cohere, etc.).
+2. The extension checks the cache by searching for semantically similar
+   cached queries using cosine similarity.
+3. On a cache hit, if a similar query exists above the similarity threshold,
+   the extension returns the cached result.
+4. On a cache miss, the extension executes the actual query and caches the
+   result with the embedding for future use.
+5. Automatic maintenance evicts expired entries based on TTL and configured
+   policies.
+
+## Getting Help
+
+The following resources are available for assistance:
+
+- Browse the [documentation](https://docs.pgedge.com/) for detailed information.
+- Report issues at [GitHub Issues](https://github.com/pgedge/pg_semantic_cache/issues).
+- See [Use Cases](use_cases.md) for practical implementation examples.
+- Check the [FAQ](FAQ.md) for answers to common questions.
+