unify venv calling, add basic huggingchat module

nostr_dvm/tasks/textgeneration_huggingchat.py

@@ -0,0 +1,108 @@
+import json
+import os
+
+from nostr_dvm.interfaces.dvmtaskinterface import DVMTaskInterface, process_venv
+from nostr_dvm.utils.admin_utils import AdminConfig
+from nostr_dvm.utils.definitions import EventDefinitions
+from nostr_dvm.utils.dvmconfig import DVMConfig, build_default_config
+from nostr_dvm.utils.nip89_utils import NIP89Config, check_and_set_d_tag
+
+"""
+This File contains a Module to generate Text, based on a prompt using a LLM (local or API) (Ollama, custom model, chatgpt)
+
+Accepted Inputs: Prompt (text)
+Outputs: Generated text
+"""
+
+
+class TextGenerationHuggingChat(DVMTaskInterface):
+    KIND: int = EventDefinitions.KIND_NIP90_GENERATE_TEXT
+    TASK: str = "text-to-text"
+    FIX_COST: float = 0
+    dependencies = [("nostr-dvm", "nostr-dvm"),
+                    ("hugchat", "hugchat")]
+
+    def __init__(self, name, dvm_config: DVMConfig, nip89config: NIP89Config,
+                 admin_config: AdminConfig = None, options=None):
+        dvm_config.SCRIPT = os.path.abspath(__file__)
+        super().__init__(name, dvm_config, nip89config, admin_config, options)
+
+    def is_input_supported(self, tags, client=None, dvm_config=None):
+        for tag in tags:
+            if tag.as_vec()[0] == 'i':
+                input_value = tag.as_vec()[1]
+                input_type = tag.as_vec()[2]
+                if input_type != "text":
+                    return False
+
+        return True
+
+    def create_request_from_nostr_event(self, event, client=None, dvm_config=None):
+        request_form = {"jobID": event.id().to_hex() + "_" + self.NAME.replace(" ", "")}
+        prompt = ""
+
+        for tag in event.tags():
+            if tag.as_vec()[0] == 'i':
+                input_type = tag.as_vec()[2]
+                if input_type == "text":
+                    prompt = tag.as_vec()[1]
+
+        options = {
+            "prompt": prompt,
+        }
+        request_form['options'] = json.dumps(options)
+
+        return request_form
+
+    def process(self, request_form):
+        from hugchat import hugchat
+        from hugchat.login import Login
+        sign = Login(os.getenv("HUGGINGFACE_EMAIL"), os.getenv("HUGGINGFACE_PASSWORD"))
+        cookie_path_dir = "./cookies_snapshot"
+        try:
+            cookies = sign.loadCookiesFromDir(
+                cookie_path_dir)  # This will detect if the JSON file exists, return cookies if it does and raise an Exception if it's not.
+        except:
+            cookies = sign.login()
+            sign.saveCookiesToDir(cookie_path_dir)
+
+
+        options = DVMTaskInterface.set_options(request_form)
+
+        try:
+            chatbot = hugchat.ChatBot(cookies=cookies.get_dict())  # or cookie_path="usercookies/<email>.json"
+            query_result = chatbot.query(options["prompt"])
+            print(query_result["text"])  # or query_result.text or query_result["text"]
+            return str(query_result["text"]).lstrip()
+
+        except Exception as e:
+            print("Error in Module: " + str(e))
+            raise Exception(e)
+
+
+# We build an example here that we can call by either calling this file directly from the main directory,
+# or by adding it to our playground. You can call the example and adjust it to your needs or redefine it in the
+# playground or elsewhere
+def build_example(name, identifier, admin_config):
+    dvm_config = build_default_config(identifier)
+    admin_config.LUD16 = dvm_config.LN_ADDRESS
+
+    nip89info = {
+        "name": name,
+        "image": "https://image.nostr.build/c33ca6fc4cc038ca4adb46fdfdfda34951656f87ee364ef59095bae1495ce669.jpg",
+        "about": "I use a LLM connected via Huggingchat",
+        "encryptionSupported": True,
+        "cashuAccepted": True,
+        "nip90Params": {}
+    }
+
+    nip89config = NIP89Config()
+    nip89config.DTAG = check_and_set_d_tag(identifier, name, dvm_config.PRIVATE_KEY, nip89info["image"])
+    nip89config.CONTENT = json.dumps(nip89info)
+
+    return TextGenerationHuggingChat(name=name, dvm_config=dvm_config, nip89config=nip89config,
+                                     admin_config=admin_config)
+
+
+if __name__ == '__main__':
+    process_venv(TextGenerationHuggingChat)