Add /recall endpoint, add Redis support

main.py

@@ -3,6 +3,29 @@ from pydantic import BaseModel
 from typing import Any
 import uvicorn
 import json
+import redis
+import os
+
+# Initialize Redis connection
+def get_redis_client():
+    redis_host = os.getenv('REDIS_HOST', 'localhost')
+    redis_port = int(os.getenv('REDIS_PORT', 6379))
+    redis_db = int(os.getenv('REDIS_DB', 0))
+
+    try:
+        client = redis.StrictRedis(
+            host=redis_host,
+            port=redis_port,
+            db=redis_db,
+            decode_responses=True
+        )
+        # Test connection
+        client.ping()
+        return client
+    except redis.ConnectionError as e:
+        raise HTTPException(status_code=503, detail=f"Could not connect to Redis: {str(e)}")
+
+redis_client = get_redis_client()
 
 app = FastAPI(
     title="Remember Service",
@@ -17,20 +40,63 @@ class RememberRequest(BaseModel):
     content: Any
     metadata: dict = {}
 
-@app.post("/remember", 
+@app.post("/remember",
           summary="Store information to remember",
-          description="Saves the provided content and optional metadata. This endpoint is designed to be called by an LLM as a tool.")
+          description="Saves the provided content and optional metadata in Redis.")
 def remember_endpoint(request: RememberRequest):
     """
     Endpoint to remember information.
-    Prints the received payload to stdout in JSON format.
+    Stores the received payload in Redis and prints it to stdout in JSON format.
     """
     payload = {
         "content": request.content,
         "metadata": request.metadata
     }
+    payload_json = json.dumps(payload, ensure_ascii=False)
+
+    # Generate a unique key based on timestamp
+    import time
+    key = f"remember:{int(time.time())}"
+
+    # Store in Redis
+    redis_client.set(key, payload_json)
+
     print(json.dumps(payload, indent=2, ensure_ascii=False))
-    return {"status": "remembered"}
+    return {"status": "remembered", "key": key}
+
+@app.get("/recall",
+         summary="Recall information previously remembered",
+         description="Searches for content in Redis based on query string. Returns matching entries.")
+def recall_endpoint(query: str):
+    """
+    Endpoint to recall information from Redis.
+    Searches for entries containing the query string in their content or metadata.
+    """
+    try:
+        # Get all keys matching the remember pattern
+        keys = redis_client.keys("remember:*")
+
+        results = []
+        for key in keys:
+            data = redis_client.get(key)
+            if data:
+                payload = json.loads(data)
+                # Check if query is in content or metadata
+                if (isinstance(payload.get("content"), str) and query.lower() in payload["content"].lower()) or \
+                   (isinstance(payload.get("metadata"), dict) and any(
+                       isinstance(v, str) and query.lower() in v.lower()
+                       for v in payload["metadata"].values()
+                   )):
+                    results.append({
+                        "key": key,
+                        "content": payload["content"],
+                        "metadata": payload["metadata"]
+                    })
+
+        return {"results": results, "count": len(results)}
+
+    except redis.RedisError as e:
+        raise HTTPException(status_code=500, detail=f"Error searching Redis: {str(e)}")
 
 if __name__ == "__main__":
     uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

@@ -1,3 +1,4 @@
 fastapi>=0.68.0
 uvicorn>=0.15.0
 pydantic>=1.8.0
+redis>=4.0.0