working

Author: truemagic-coder

README.md

@@ -418,7 +418,6 @@ config = {
         "pinecone": {
             "api_key": "your-pinecone-api-key",
             "index_name": "your-pinecone-index-name",
-            "use_reranking": True # optional - but increases better matching - requires Pinecone Standard
         }
     },
     "mongo": {

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "solana-agent"
-version = "30.0.0"
+version = "30.0.0-dev11"
 description = "AI Agents for Solana"
 authors = ["Bevan Hunt <bevan@bevanhunt.com>"]
 license = "MIT"

solana_agent/adapters/pinecone_adapter.py

@@ -41,7 +41,7 @@ def __init__(
         create_index_if_not_exists: bool = True,
         # Reranking Config
         use_reranking: bool = False,
-        rerank_model: Optional[PineconeRerankModel] = None,
+        rerank_model: Optional[PineconeRerankModel] = "cohere-rerank-3.5",
         rerank_top_k: int = 3,  # Final number of results after reranking
         # Multiplier for initial fetch before rerank
         initial_query_top_k_multiplier: int = 5,
@@ -371,7 +371,7 @@ async def query_and_rerank(
                     "parameters": rerank_params,
                 }
 
-                rerank_response = await self.pinecone.rerank(**rerank_request)
+                rerank_response = await self.pinecone.inference.rerank(**rerank_request)
 
                 # 4. Process Reranked Results
                 reranked_results = []

solana_agent/factories/agent_factory.py

@@ -270,7 +270,9 @@ def create_from_config(config: Dict[str, Any]) -> QueryService:
                     ),
                     # Reranking config
                     use_reranking=pinecone_config.get("use_reranking", False),
-                    rerank_model=pinecone_config.get("rerank_model"),
+                    rerank_model=pinecone_config.get(
+                        "rerank_model", "cohere-rerank-3.5"
+                    ),
                     rerank_top_k=pinecone_config.get("rerank_top_k", 3),
                     initial_query_top_k_multiplier=pinecone_config.get(
                         "initial_query_top_k_multiplier", 5

solana_agent/services/graph_memory.py

@@ -58,7 +58,13 @@ async def add_episode(
                 entity["text"], model=self.embedding_model
             )
             await self.pinecone.upsert(
-                [{"id": node_id, "values": embedding}],
+                [
+                    {
+                        "id": node_id,
+                        "values": embedding,
+                        "metadata": {"text": self._truncate_text(entity["text"])},
+                    }
+                ],
                 namespace=namespace,
             )
         return episode_id
@@ -85,3 +91,12 @@ async def search(
 
     async def traverse(self, node_id: str, depth: int = 1) -> List[Dict[str, Any]]:
         return await self.graph.find_neighbors(node_id, depth=depth)
+
+    # pinecone has a 40kb character limit for text
+    def _truncate_text(self, text: str, max_length: int = 40960) -> str:
+        """
+        Truncate text to a maximum length.
+        """
+        if len(text) > max_length - 3:
+            return text[:max_length] + "..."
+        return text