revision

Signed-off-by: xtzhang1122 <[email protected]>

src/core/routes/test.py

@@ -1,9 +1,9 @@
-from typing import List
+from typing import List, AsyncGenerator
 from fastapi import APIRouter
 from pydantic import BaseModel
 import uuid, asyncio
 from fastapi.responses import StreamingResponse
-from typing import AsyncGenerator
+import re
 
 router = APIRouter(prefix="/api/test")
 
@@ -26,51 +26,64 @@ class RequestConversation(BaseModel):
 
 
 responses = {
-    "What is Hyperledger Fabric?": "Hyperledger Fabric is an open-source blockchain framework designed for enterprise solutions. It allows for a modular architecture where different components like consensus mechanisms, membership services, and ledger storage can be tailored to specific needs.",
-    "How to install Hyperledger Fabric?": "To install Hyperledger Fabric, follow these steps:\n1. Install Docker and Docker Compose.\n2. Download the Hyperledger Fabric binaries and docker images using the Fabric CA and Fabric binaries script.\n3. Set up the environment variables for Fabric binaries.\n4. Verify the installation by running Fabric sample network scripts.",
-    "How to deploy a Hyperledger Fabric network?": "To deploy a Hyperledger Fabric network:\n1. Define the network topology and configuration files (e.g., 'configtx.yaml').\n2. Use the 'fabric-cli' or scripts to create channel artifacts.\n3. Launch the network by starting the necessary Docker containers and services using 'docker-compose' or Kubernetes.\n4. Instantiate and upgrade chaincode as needed.",
-    "How to run a Hyperledger Fabric network?": "To run a Hyperledger Fabric network:\n1. Start the network by running 'docker-compose up' or the appropriate command for your setup.\n2. Use the Fabric CLI tools or SDKs to interact with the network, including creating and joining channels, and submitting transactions.\n3. Monitor the network's health and performance using Fabric's built-in tools or external monitoring solutions.",
-    "How to ensure data privacy in Hyperledger Fabric?": "To ensure data privacy in Hyperledger Fabric:\n1. Use private data collections to restrict access to sensitive data.\n2. Implement access control policies and endorsement policies.\n3. Utilize encryption for data at rest and in transit.\n4. Regularly review and update security configurations and practices.",
+    "what is hyperledger fabric": "Hyperledger Fabric is an open-source blockchain framework designed for enterprise solutions. It allows for a modular architecture where different components like consensus mechanisms, membership services, and ledger storage can be tailored to specific needs.",
+    "how to install hyperledger fabric": "To install Hyperledger Fabric, follow these steps:\n1. Install Docker and Docker Compose.\n2. Download the Hyperledger Fabric binaries and docker images using the Fabric CA and Fabric binaries script.\n3. Set up the environment variables for Fabric binaries.\n4. Verify the installation by running Fabric sample network scripts.",
+    "how to deploy a hyperledger fabric network": "To deploy a Hyperledger Fabric network:\n1. Define the network topology and configuration files (e.g., 'configtx.yaml').\n2. Use the 'fabric-cli' or scripts to create channel artifacts.\n3. Launch the network by starting the necessary Docker containers and services using 'docker-compose' or Kubernetes.\n4. Instantiate and upgrade chaincode as needed.",
+    "how to run a hyperledger fabric network": "To run a Hyperledger Fabric network:\n1. Start the network by running 'docker-compose up' or the appropriate command for your setup.\n2. Use the Fabric CLI tools or SDKs to interact with the network, including creating and joining channels, and submitting transactions.\n3. Monitor the network's health and performance using Fabric's built-in tools or external monitoring solutions.",
+    "how to ensure data privacy in hyperledger fabric": "To ensure data privacy in Hyperledger Fabric:\n1. Use private data collections to restrict access to sensitive data.\n2. Implement access control policies and endorsement policies.\n3. Utilize encryption for data at rest and in transit.\n4. Regularly review and update security configurations and practices.",
 }
 
 
 def get_hyperledger_fabric_answer(question):
     return responses.get(question, "Question not found in the database.")
 
 
-# TODO: Get all chats for a user in a paginated format
+def normalize_question(question: str) -> str:
+    # Convert to lowercase and strip punctuation
+    question = question.rstrip()
+    return re.sub(r'[^\w\s]', '', question.lower())
+
+
 async def conversation_stream(offset: int = 0, limit: int = 30, order: str = "updated") -> AsyncGenerator[ResponseConversation, None]:
-    items = list(responses.items())[offset:offset + limit]
-    for idx, (question, answer) in enumerate(items):
-        yield ResponseConversation(
+    # Normalize the keys in the responses dictionary
+    normalized_responses = {normalize_question(k): v for k, v in responses.items()}
+
+    # Retrieve items based on offset and limit
+    items = list(normalized_responses.items())[offset:offset + limit]
+
+    for idx, (_, answer) in enumerate(items):
+        conversation = ResponseConversation(
             id=str(uuid.uuid4()),
             message=ResponseMessage(
                 content=answer,
                 type=1,
                 id=str(uuid.uuid4()),
             )
         )
+        yield f"data: {conversation.json()}\n\n"
         await asyncio.sleep(0.1)  # Simulate processing time
 
+
 @router.post("/conversations")
 def get_conversations(
     offset: int = 0, limit: int = 30, order: str = "updated"
 ) -> ResponseConversation:
     return StreamingResponse(conversation_stream(offset, limit), media_type="application/json")
 
 
-# TODO: Get a single chat for a user
 async def single_conversation_stream(question: str) -> AsyncGenerator[ResponseConversation, None]:
+    question = normalize_question(question)
     answer = responses.get(question, "Question not found")
 
-    yield ResponseConversation(
+    conversation = ResponseConversation(
         id=str(uuid.uuid4()),
         message=ResponseMessage(
             content=answer,
             type=1,
             id=str(uuid.uuid4()),
         )
     )
+    yield f"data: {conversation.json()}\n\n"
     await asyncio.sleep(0.1)  # Simulate processing time