We are currently solving the following issue within our repository. Here is the issue text:
--- BEGIN ISSUE ---
Miner error on netuid 1 - string indicies must be integers
When running a miner on netuid 1, we get this output with current text_prompting branch:

![image](https://user-images.githubusercontent.com/35969959/233508574-7502a388-a7cb-4748-b0f1-88bbcfbd3dfe.png)

It should cause an error for any miner, since what happens is that before the bittensor.BasePromptingMiner (in this case in neurons/text/prompting/miners/pythia/neuron.py) previously recieved the "messages" argument in the form of a list of dictionaries, but now gets it in the form of a list with strings.

To clarify,efore, we got something like this:

[{'role': 'system', 'content': '\nYou are designed to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics.\n'}, {'role': 'user', 'content': '\nAsk me a random question about anything. Make the question very domain specific. Do not include the answer in the question.\n'}]

Now we get something like this:

['{"role": "system", "content": "\\nYou are designed to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics.\\n"}', '{"role": "user", "content": "What is the function of the Golgi apparatus in a eukaryotic cell?"}']


While making a more permanent fix to this issue, I can confirm that this quickfix works:

Adding this to the start of the  forward() function in the miner, in this case in this case in neurons/text/prompting/miners/pythia/neuron.py:

```
            import json
            messages = [json.loads(item) for item in messages]
```

It takes all the strings in the messages variable and turns them into dictionaries.


--- END ISSUE ---

Below are some code segments, each from a relevant file. One or more of these files may contain bugs.
--- BEGIN FILES ---
Path: `bittensor/_synapse/text_prompting/synapse.py`
Content:
```
1 # The MIT License (MIT)
2 # Copyright © 2021 Yuma Rao
3 
4 # Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated
5 # documentation files (the “Software”), to deal in the Software without restriction, including without limitation
6 # the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,
7 # and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
8 
9 # The above copyright notice and this permission notice shall be included in all copies or substantial portions of
10 # the Software.
11 
12 # THE SOFTWARE IS PROVIDED “AS IS”, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO
13 # THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
14 # THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION
15 # OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
16 # DEALINGS IN THE SOFTWARE.
17 
18 import grpc
19 import torch
20 import bittensor
21 
22 from typing import List, Dict, Union, Callable
23 from abc import ABC, abstractmethod
24 
25 class SynapseForward( bittensor.SynapseCall ):
26     name: str = "text_prompting_forward"
27     is_forward: bool = True
28     completion: str = ""
29 
30     def __init__( 
31             self, 
32             synapse: "TextPromptingSynapse", 
33             request_proto: bittensor.proto.BackwardTextPromptingRequest,
34             forward_callback: Callable,
35         ):
36         super().__init__( synapse = synapse, request_proto = request_proto )
37         self.messages = request_proto.messages
38         self.formatted_messages = [ message for message in self.messages ]
39         self.forward_callback = forward_callback
40 
41     def apply( self ):
42         bittensor.logging.trace( "SynapseForward.apply()" )
43         self.completion = self.forward_callback( messages = self.formatted_messages )
44         bittensor.logging.trace( "SynapseForward.apply() = ", self.completion )
45 
46     def get_response_proto( self ) -> bittensor.proto.ForwardTextPromptingResponse: 
47         bittensor.logging.trace( "SynapseForward.get_response_proto()" )
48         return bittensor.ForwardTextPromptingResponse( response = self.completion )
49     
50     def get_inputs_shape(self) -> Union[torch.Size, None]: 
51         bittensor.logging.trace( "SynapseForward.get_inputs_shape()" )
52         return torch.Size( [ len(message) for message in self.messages ] )
53     
54     def get_outputs_shape(self) -> Union[torch.Size, None]: 
55         bittensor.logging.trace( "SynapseForward.get_outputs_shape()" )
56         return torch.Size( [ len(self.completion) ]  )
57     
58 class SynapseBackward( bittensor.SynapseCall ):
59     name: str = "text_prompting_backward"
60     is_forward: bool = False
61 
62     def __init__( 
63             self, 
64             synapse: "TextPromptingSynapse", 
65             request_proto: bittensor.proto.BackwardTextPromptingRequest,
66             backward_callback: Callable,
67         ):
68         super().__init__( synapse = synapse, request_proto = request_proto )
69         self.formatted_messages = [ message for message in request_proto.messages ]
70         self.formatted_rewards = torch.tensor( [ request_proto.rewards ], dtype = torch.float32 )
71         self.completion = request_proto.response
72         self.backward_callback = backward_callback
73 
74     def apply( self ):
75         self.backward_callback(
76             rewards = self.formatted_rewards,
77             messages = self.formatted_messages,
78             response = self.completion,
79         )    
80     
81     def get_response_proto( self ) -> bittensor.proto.BackwardTextPromptingResponse: 
82         return bittensor.BackwardTextPromptingResponse( )
83 
84     def get_inputs_shape(self) -> torch.Size: 
85         return torch.Size( [ len(message) for message in self.formatted_messages ] )
86     
87     def get_outputs_shape(self) -> torch.Size: 
88         return torch.Size( [ 0 ] )
89 
90 
91 class TextPromptingSynapse( bittensor.Synapse, bittensor.grpc.TextPromptingServicer ):
92     name: str = "text_prompting_synapse"
93 
94     def __init__(self, axon: "bittensor.axon" ):
95         super().__init__( axon = axon )
96         self.axon = axon
97         bittensor.grpc.add_TextPromptingServicer_to_server( self, self.axon.server )
98 
99     @abstractmethod
100     def forward( self, messages: List[Dict[str, str]] ) -> str: ...
101 
102     @abstractmethod
103     def backward( self, messages: List[Dict[str, str]], response: str, rewards: torch.FloatTensor ) -> str: ...
104 
105     def Forward( self, request: bittensor.proto.ForwardTextPromptingRequest, context: grpc.ServicerContext ) -> bittensor.proto.ForwardTextPromptingResponse:
106         call = SynapseForward( self, request, self.forward )
107         bittensor.logging.trace( 'Forward: {} '.format( call ) )
108         return self.apply( call = call ) 
109                          
110     def Backward( self, request: bittensor.proto.BackwardTextPromptingRequest, context: grpc.ServicerContext ) -> bittensor.proto.BackwardTextPromptingResponse:
111         call = SynapseBackward( self, request, self.backward )
112         bittensor.logging.trace( 'Backward: {}'.format( call ) )
113         return self.apply( call = call ) 
114 
115
```
--- END FILES ---

Please first localize the bug based on the issue statement, and then generate a patch according to the `git diff` format fenced by three backticks.

Here is an example:

```diff
diff --git a/examples/server_async.py b/examples/server_async.py
--- a/examples/server_async.py
+++ b/examples/server_async.py
@@ -313,4 +313,4 @@
 
 
 if __name__ == "__main__":
-    asyncio.run(run_async_server("."), debug=True)
+    asyncio.run(run_async_server(), debug=True)
diff --git a/examples/server_sync.py b/examples/server_sync.py
--- a/examples/server_sync.py
+++ b/examples/server_sync.py
@@ -313,5 +313,5 @@
 
 
 if __name__ == "__main__":
-    server = run_sync_server(".")
+    server = run_sync_server()
     server.shutdown()

```

diff --git a/bittensor/_synapse/text_prompting/synapse.py b/bittensor/_synapse/text_prompting/synapse.py
--- a/bittensor/_synapse/text_prompting/synapse.py
+++ b/bittensor/_synapse/text_prompting/synapse.py
@@ -21,6 +21,7 @@
 
 from typing import List, Dict, Union, Callable
 from abc import ABC, abstractmethod
+import json
 
 class SynapseForward( bittensor.SynapseCall ):
     name: str = "text_prompting_forward"
@@ -35,7 +36,7 @@
         ):
         super().__init__( synapse = synapse, request_proto = request_proto )
         self.messages = request_proto.messages
-        self.formatted_messages = [ message for message in self.messages ]
+        self.formatted_messages = [ json.loads(message) for message in self.messages ]
         self.forward_callback = forward_callback
 
     def apply( self ):

{"golden_diff": "diff --git a/bittensor/_synapse/text_prompting/synapse.py b/bittensor/_synapse/text_prompting/synapse.py\n--- a/bittensor/_synapse/text_prompting/synapse.py\n+++ b/bittensor/_synapse/text_prompting/synapse.py\n@@ -21,6 +21,7 @@\n \n from typing import List, Dict, Union, Callable\n from abc import ABC, abstractmethod\n+import json\n \n class SynapseForward( bittensor.SynapseCall ):\n     name: str = \"text_prompting_forward\"\n@@ -35,7 +36,7 @@\n         ):\n         super().__init__( synapse = synapse, request_proto = request_proto )\n         self.messages = request_proto.messages\n-        self.formatted_messages = [ message for message in self.messages ]\n+        self.formatted_messages = [ json.loads(message) for message in self.messages ]\n         self.forward_callback = forward_callback\n \n     def apply( self ):\n", "issue": "Miner error on netuid 1 - string indicies must be integers\nWhen running a miner on netuid 1, we get this output with current text_prompting branch:\r\n\r\n![image](https://user-images.githubusercontent.com/35969959/233508574-7502a388-a7cb-4748-b0f1-88bbcfbd3dfe.png)\r\n\r\nIt should cause an error for any miner, since what happens is that before the bittensor.BasePromptingMiner (in this case in neurons/text/prompting/miners/pythia/neuron.py) previously recieved the \"messages\" argument in the form of a list of dictionaries, but now gets it in the form of a list with strings.\r\n\r\nTo clarify,efore, we got something like this:\r\n\r\n[{'role': 'system', 'content': '\\nYou are designed to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics.\\n'}, {'role': 'user', 'content': '\\nAsk me a random question about anything. Make the question very domain specific. Do not include the answer in the question.\\n'}]\r\n\r\nNow we get something like this:\r\n\r\n['{\"role\": \"system\", \"content\": \"\\\\nYou are designed to assist with a wide range of tasks, from answering simple questions to providing in-depth explanations and discussions on a wide range of topics.\\\\n\"}', '{\"role\": \"user\", \"content\": \"What is the function of the Golgi apparatus in a eukaryotic cell?\"}']\r\n\r\n\r\nWhile making a more permanent fix to this issue, I can confirm that this quickfix works:\r\n\r\nAdding this to the start of the  forward() function in the miner, in this case in this case in neurons/text/prompting/miners/pythia/neuron.py:\r\n\r\n```\r\n            import json\r\n            messages = [json.loads(item) for item in messages]\r\n```\r\n\r\nIt takes all the strings in the messages variable and turns them into dictionaries.\r\n\n", "before_files": [{"content": "# The MIT License (MIT)\n# Copyright \u00a9 2021 Yuma Rao\n\n# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated\n# documentation files (the \u201cSoftware\u201d), to deal in the Software without restriction, including without limitation\n# the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,\n# and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n\n# The above copyright notice and this permission notice shall be included in all copies or substantial portions of\n# the Software.\n\n# THE SOFTWARE IS PROVIDED \u201cAS IS\u201d, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO\n# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL\n# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION\n# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER\n# DEALINGS IN THE SOFTWARE.\n\nimport grpc\nimport torch\nimport bittensor\n\nfrom typing import List, Dict, Union, Callable\nfrom abc import ABC, abstractmethod\n\nclass SynapseForward( bittensor.SynapseCall ):\n    name: str = \"text_prompting_forward\"\n    is_forward: bool = True\n    completion: str = \"\"\n\n    def __init__( \n            self, \n            synapse: \"TextPromptingSynapse\", \n            request_proto: bittensor.proto.BackwardTextPromptingRequest,\n            forward_callback: Callable,\n        ):\n        super().__init__( synapse = synapse, request_proto = request_proto )\n        self.messages = request_proto.messages\n        self.formatted_messages = [ message for message in self.messages ]\n        self.forward_callback = forward_callback\n\n    def apply( self ):\n        bittensor.logging.trace( \"SynapseForward.apply()\" )\n        self.completion = self.forward_callback( messages = self.formatted_messages )\n        bittensor.logging.trace( \"SynapseForward.apply() = \", self.completion )\n\n    def get_response_proto( self ) -> bittensor.proto.ForwardTextPromptingResponse: \n        bittensor.logging.trace( \"SynapseForward.get_response_proto()\" )\n        return bittensor.ForwardTextPromptingResponse( response = self.completion )\n    \n    def get_inputs_shape(self) -> Union[torch.Size, None]: \n        bittensor.logging.trace( \"SynapseForward.get_inputs_shape()\" )\n        return torch.Size( [ len(message) for message in self.messages ] )\n    \n    def get_outputs_shape(self) -> Union[torch.Size, None]: \n        bittensor.logging.trace( \"SynapseForward.get_outputs_shape()\" )\n        return torch.Size( [ len(self.completion) ]  )\n    \nclass SynapseBackward( bittensor.SynapseCall ):\n    name: str = \"text_prompting_backward\"\n    is_forward: bool = False\n\n    def __init__( \n            self, \n            synapse: \"TextPromptingSynapse\", \n            request_proto: bittensor.proto.BackwardTextPromptingRequest,\n            backward_callback: Callable,\n        ):\n        super().__init__( synapse = synapse, request_proto = request_proto )\n        self.formatted_messages = [ message for message in request_proto.messages ]\n        self.formatted_rewards = torch.tensor( [ request_proto.rewards ], dtype = torch.float32 )\n        self.completion = request_proto.response\n        self.backward_callback = backward_callback\n\n    def apply( self ):\n        self.backward_callback(\n            rewards = self.formatted_rewards,\n            messages = self.formatted_messages,\n            response = self.completion,\n        )    \n    \n    def get_response_proto( self ) -> bittensor.proto.BackwardTextPromptingResponse: \n        return bittensor.BackwardTextPromptingResponse( )\n\n    def get_inputs_shape(self) -> torch.Size: \n        return torch.Size( [ len(message) for message in self.formatted_messages ] )\n    \n    def get_outputs_shape(self) -> torch.Size: \n        return torch.Size( [ 0 ] )\n\n\nclass TextPromptingSynapse( bittensor.Synapse, bittensor.grpc.TextPromptingServicer ):\n    name: str = \"text_prompting_synapse\"\n\n    def __init__(self, axon: \"bittensor.axon\" ):\n        super().__init__( axon = axon )\n        self.axon = axon\n        bittensor.grpc.add_TextPromptingServicer_to_server( self, self.axon.server )\n\n    @abstractmethod\n    def forward( self, messages: List[Dict[str, str]] ) -> str: ...\n\n    @abstractmethod\n    def backward( self, messages: List[Dict[str, str]], response: str, rewards: torch.FloatTensor ) -> str: ...\n\n    def Forward( self, request: bittensor.proto.ForwardTextPromptingRequest, context: grpc.ServicerContext ) -> bittensor.proto.ForwardTextPromptingResponse:\n        call = SynapseForward( self, request, self.forward )\n        bittensor.logging.trace( 'Forward: {} '.format( call ) )\n        return self.apply( call = call ) \n                         \n    def Backward( self, request: bittensor.proto.BackwardTextPromptingRequest, context: grpc.ServicerContext ) -> bittensor.proto.BackwardTextPromptingResponse:\n        call = SynapseBackward( self, request, self.backward )\n        bittensor.logging.trace( 'Backward: {}'.format( call ) )\n        return self.apply( call = call ) \n\n", "path": "bittensor/_synapse/text_prompting/synapse.py"}], "after_files": [{"content": "# The MIT License (MIT)\n# Copyright \u00a9 2021 Yuma Rao\n\n# Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated\n# documentation files (the \u201cSoftware\u201d), to deal in the Software without restriction, including without limitation\n# the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software,\n# and to permit persons to whom the Software is furnished to do so, subject to the following conditions:\n\n# The above copyright notice and this permission notice shall be included in all copies or substantial portions of\n# the Software.\n\n# THE SOFTWARE IS PROVIDED \u201cAS IS\u201d, WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO\n# THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL\n# THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION\n# OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER\n# DEALINGS IN THE SOFTWARE.\n\nimport grpc\nimport torch\nimport bittensor\n\nfrom typing import List, Dict, Union, Callable\nfrom abc import ABC, abstractmethod\nimport json\n\nclass SynapseForward( bittensor.SynapseCall ):\n    name: str = \"text_prompting_forward\"\n    is_forward: bool = True\n    completion: str = \"\"\n\n    def __init__( \n            self, \n            synapse: \"TextPromptingSynapse\", \n            request_proto: bittensor.proto.BackwardTextPromptingRequest,\n            forward_callback: Callable,\n        ):\n        super().__init__( synapse = synapse, request_proto = request_proto )\n        self.messages = request_proto.messages\n        self.formatted_messages = [ json.loads(message) for message in self.messages ]\n        self.forward_callback = forward_callback\n\n    def apply( self ):\n        bittensor.logging.trace( \"SynapseForward.apply()\" )\n        self.completion = self.forward_callback( messages = self.formatted_messages )\n        bittensor.logging.trace( \"SynapseForward.apply() = \", self.completion )\n\n    def get_response_proto( self ) -> bittensor.proto.ForwardTextPromptingResponse: \n        bittensor.logging.trace( \"SynapseForward.get_response_proto()\" )\n        return bittensor.ForwardTextPromptingResponse( response = self.completion )\n    \n    def get_inputs_shape(self) -> Union[torch.Size, None]: \n        bittensor.logging.trace( \"SynapseForward.get_inputs_shape()\" )\n        return torch.Size( [ len(message) for message in self.messages ] )\n    \n    def get_outputs_shape(self) -> Union[torch.Size, None]: \n        bittensor.logging.trace( \"SynapseForward.get_outputs_shape()\" )\n        return torch.Size( [ len(self.completion) ]  )\n    \nclass SynapseBackward( bittensor.SynapseCall ):\n    name: str = \"text_prompting_backward\"\n    is_forward: bool = False\n\n    def __init__( \n            self, \n            synapse: \"TextPromptingSynapse\", \n            request_proto: bittensor.proto.BackwardTextPromptingRequest,\n            backward_callback: Callable,\n        ):\n        super().__init__( synapse = synapse, request_proto = request_proto )\n        self.formatted_messages = [ message for message in request_proto.messages ]\n        self.formatted_rewards = torch.tensor( [ request_proto.rewards ], dtype = torch.float32 )\n        self.completion = request_proto.response\n        self.backward_callback = backward_callback\n\n    def apply( self ):\n        self.backward_callback(\n            rewards = self.formatted_rewards,\n            messages = self.formatted_messages,\n            response = self.completion,\n        )    \n    \n    def get_response_proto( self ) -> bittensor.proto.BackwardTextPromptingResponse: \n        return bittensor.BackwardTextPromptingResponse( )\n\n    def get_inputs_shape(self) -> torch.Size: \n        return torch.Size( [ len(message) for message in self.formatted_messages ] )\n    \n    def get_outputs_shape(self) -> torch.Size: \n        return torch.Size( [ 0 ] )\n\n\nclass TextPromptingSynapse( bittensor.Synapse, bittensor.grpc.TextPromptingServicer ):\n    name: str = \"text_prompting_synapse\"\n\n    def __init__(self, axon: \"bittensor.axon\" ):\n        super().__init__( axon = axon )\n        self.axon = axon\n        bittensor.grpc.add_TextPromptingServicer_to_server( self, self.axon.server )\n\n    @abstractmethod\n    def forward( self, messages: List[Dict[str, str]] ) -> str: ...\n\n    @abstractmethod\n    def backward( self, messages: List[Dict[str, str]], response: str, rewards: torch.FloatTensor ) -> str: ...\n\n    def Forward( self, request: bittensor.proto.ForwardTextPromptingRequest, context: grpc.ServicerContext ) -> bittensor.proto.ForwardTextPromptingResponse:\n        call = SynapseForward( self, request, self.forward )\n        bittensor.logging.trace( 'Forward: {} '.format( call ) )\n        return self.apply( call = call ) \n                         \n    def Backward( self, request: bittensor.proto.BackwardTextPromptingRequest, context: grpc.ServicerContext ) -> bittensor.proto.BackwardTextPromptingResponse:\n        call = SynapseBackward( self, request, self.backward )\n        bittensor.logging.trace( 'Backward: {}'.format( call ) )\n        return self.apply( call = call ) \n\n", "path": "bittensor/_synapse/text_prompting/synapse.py"}]}