Upload README.md

README.md

@@ -297,9 +297,11 @@ print(json.dumps(response.model_dump(), indent=2, ensure_ascii=False))
 Time series inference is currently only supported in LMDeploy. To get started, download and deploy Intern-S2-Preview with LMDeploy by following the [Model Deployment Guide](./deployment_guide.md).
 Below is an example of detecting earthquake events from a time series signal file. Additional data types and functionalities are also supported.
 
+**Please note**: this demo is slightly different from the one in [Intern-S1-Pro](https://huggingface.co/internlm/Intern-S1-Pro#time-series-demo). The main difference is that in the messages content, you need to provide time_series_url first, followed by the text prompt. Please adapt your implementation based on this demo.
+
 ```
 from openai import OpenAI
-from lmdeploy.vl.time_series_utils import encode_time_series_base64
+from lmdeploy.vl.utils import encode_time_series_base64
 
 openai_api_key = "EMPTY"
 openai_api_base = "http://0.0.0.0:8000/v1"
@@ -321,10 +323,6 @@ def send_base64(file_path: str, sampling_rate: int = 100):
         {
             "role": "user",
             "content": [
-                {
-                    "type": "text",
-                    "text": "Please determine whether an Earthquake event has occurred in the provided time-series data. If so, please specify the starting time point indices of the P-wave and S-wave in the event."
-                },
                 {
                     "type": "time_series_url",
                     "time_series_url": {
@@ -332,6 +330,10 @@ def send_base64(file_path: str, sampling_rate: int = 100):
                         "sampling_rate": sampling_rate
                     },
                 },
+                {
+                    "type": "text",
+                    "text": "Please determine whether an Earthquake event has occurred in the provided time-series data. If so, please specify the starting time point indices of the P-wave and S-wave in the event."
+                },
             ],
         }
     ]
@@ -341,6 +343,9 @@ def send_base64(file_path: str, sampling_rate: int = 100):
         messages=messages,
         temperature=0,
         max_tokens=200,
+        extra_body={
+            "chat_template_kwargs": {"enable_thinking": False}
+        }
     )
 
 
@@ -350,10 +355,6 @@ def send_http_url(url: str, sampling_rate: int = 100):
         {
             "role": "user",
             "content": [
-                {
-                    "type": "text",
-                    "text": "Please determine whether an Earthquake event has occurred in the provided time-series data. If so, please specify the starting time point indices of the P-wave and S-wave in the event."
-                },
                 {
                     "type": "time_series_url",
                     "time_series_url": {
@@ -361,6 +362,10 @@ def send_http_url(url: str, sampling_rate: int = 100):
                         "sampling_rate": sampling_rate
                     },
                 },
+                {
+                    "type": "text",
+                    "text": "Please determine whether an Earthquake event has occurred in the provided time-series data. If so, please specify the starting time point indices of the P-wave and S-wave in the event."
+                },
             ],
         }
     ]
@@ -370,6 +375,9 @@ def send_http_url(url: str, sampling_rate: int = 100):
         messages=messages,
         temperature=0,
         max_tokens=200,
+        extra_body={
+            "chat_template_kwargs": {"enable_thinking": False}
+        }
     )
 
 
@@ -379,10 +387,6 @@ def send_file_url(file_path: str, sampling_rate: int = 100):
         {
             "role": "user",
             "content": [
-                {
-                    "type": "text",
-                    "text": "Please determine whether an Earthquake event has occurred in the provided time-series data. If so, please specify the starting time point indices of the P-wave and S-wave in the event."
-                },
                 {
                     "type": "time_series_url",
                     "time_series_url": {
@@ -390,6 +394,10 @@ def send_file_url(file_path: str, sampling_rate: int = 100):
                         "sampling_rate": sampling_rate
                     },
                 },
+                {
+                    "type": "text",
+                    "text": "Please determine whether an Earthquake event has occurred in the provided time-series data. If so, please specify the starting time point indices of the P-wave and S-wave in the event."
+                },
             ],
         }
     ]
@@ -399,6 +407,9 @@ def send_file_url(file_path: str, sampling_rate: int = 100):
         messages=messages,
         temperature=0,
         max_tokens=200,
+        extra_body={
+            "chat_template_kwargs": {"enable_thinking": False}
+        }
     )
 
 response = send_base64("./0092638_seism.npy")
@@ -406,6 +417,7 @@ response = send_base64("./0092638_seism.npy")
 # response = send_file_url("./0092638_seism.npy")
 
 print(response.choices[0].message)
+
 ```
 
 ## Agent Integration