Update hugchat.py

src/hugchat/hugchat.py

@@ -395,6 +395,7 @@ def get_llm_from_name(self, name: str) -> Union[Model, None]:
 
     # Gives information such as name, websiteUrl, description, displayName, parameters, etc.
     # We can use it in the future if we need to get information about models
+
     def get_remote_llms(self) -> list:
         """
         Fetches all possible LLMs that could be used. Returns the LLMs in a list
@@ -411,66 +412,70 @@ def get_remote_llms(self) -> list:
                 f"Failed to get remote LLMs with status code: {r.status_code}"
             )
 
-        data = r.json()["nodes"][0]["data"]
-        modelsIndices = data[data[0]["models"]]
+        import json
         model_list = []
-
-        def return_data_from_index(
-            index): return None if index == -1 else data[index]
-
-        for modelIndex in modelsIndices:
-            model_data = data[modelIndex]
-
-            # Model is unlisted, skip it
-            if data[model_data["unlisted"]]:
-                continue
-
-            m = Model(
-                id=return_data_from_index(model_data["id"]),
-                name=return_data_from_index(model_data["name"]),
-                displayName=return_data_from_index(model_data["displayName"]),
-                preprompt=return_data_from_index(model_data["preprompt"]),
-                # promptExamples = return_data_from_index(model_data["promptExamples"]),
-                websiteUrl=return_data_from_index(model_data["websiteUrl"]),
-                description=return_data_from_index(model_data["description"]),
-                datasetName=return_data_from_index(model_data["datasetName"]),
-                datasetUrl=return_data_from_index(model_data["datasetUrl"]),
-                modelUrl=return_data_from_index(model_data["modelUrl"]),
-                # parameters = return_data_from_index(model_data["parameters"]),
-            )
-
-            prompt_list = return_data_from_index(model_data["promptExamples"])
-            if prompt_list is not None:
-                _promptExamples = [
-                    return_data_from_index(index) for index in prompt_list
-                ]
-                m.promptExamples = [
-                    {"title": data[prompt["title"]],
-                        "prompt": data[prompt["prompt"]]}
-                    for prompt in _promptExamples
-                ]
-
-            indices_parameters_dict = return_data_from_index(
-                model_data["parameters"])
-            out_parameters_dict = {}
-            for key, value in indices_parameters_dict.items():
-                if value == -1:
-                    out_parameters_dict[key] = None
-                    continue
-
-                if isinstance(type(data[value]), list):
-                    out_parameters_dict[key] = [data[index]
-                                                for index in data[value]]
-                    continue
-
-                out_parameters_dict[key] = data[value]
-
-            m.parameters = out_parameters_dict
-
-            model_list.append(m)
+        try:
+            # Splitting the response text by lines or another delimiter if appropriate
+            lines = r.text.splitlines()
+
+            for line in lines:
+                try:
+                    # Attempt to load each line as JSON individually
+                    data = json.loads(line)["nodes"][0]["data"]
+
+                    # Rest of your processing with `data` as per your original logic
+                    modelsIndices = data[data[0]["models"]]
+                    def return_data_from_index(index): return None if index == -1 else data[index]
+
+                    for modelIndex in modelsIndices:
+                        model_data = data[modelIndex]
+                        if data[model_data["unlisted"]]:
+                            continue
+
+                        m = Model(
+                            id=return_data_from_index(model_data["id"]),
+                            name=return_data_from_index(model_data["name"]),
+                            displayName=return_data_from_index(model_data["displayName"]),
+                            preprompt=return_data_from_index(model_data["preprompt"]),
+                            websiteUrl=return_data_from_index(model_data["websiteUrl"]),
+                            description=return_data_from_index(model_data["description"]),
+                            datasetName=return_data_from_index(model_data["datasetName"]),
+                            datasetUrl=return_data_from_index(model_data["datasetUrl"]),
+                            modelUrl=return_data_from_index(model_data["modelUrl"]),
+                        )
+
+                        prompt_list = return_data_from_index(model_data["promptExamples"])
+                        if prompt_list is not None:
+                            _promptExamples = [return_data_from_index(index) for index in prompt_list]
+                            m.promptExamples = [
+                                {"title": data[prompt["title"]], "prompt": data[prompt["prompt"]]}
+                                for prompt in _promptExamples
+                            ]
+
+                        indices_parameters_dict = return_data_from_index(model_data["parameters"])
+                        out_parameters_dict = {}
+                        for key, value in indices_parameters_dict.items():
+                            if value == -1:
+                                out_parameters_dict[key] = None
+                                continue
+                            if isinstance(data[value], list):
+                                out_parameters_dict[key] = [data[index] for index in data[value]]
+                                continue
+                            out_parameters_dict[key] = data[value]
+
+                        m.parameters = out_parameters_dict
+                        model_list.append(m)
+
+                except json.JSONDecodeError:
+                    # Skip or log the error for this specific line
+                    print(f"Skipping non-JSON or malformed line: {line}")
+
+        except Exception as e:
+            print("An error occurred while parsing:", e)
 
         return model_list
 
+
     def get_remote_conversations(self, replace_conversation_list=True):
         """
         Returns all the remote conversations for the active account. Returns the conversations in a list.