Update text_generator.py

text_generator.py

@@ -1,7 +1,8 @@
+import os
 import requests
 
 from transformers import Tool
-from transformers import pipeline
+# Import other necessary libraries if needed
 
 class TextGenerationTool(Tool):
     name = "text_generator"
@@ -11,40 +12,25 @@ class TextGenerationTool(Tool):
 
     inputs = ["text"]
     outputs = ["text"]
-        
 
-def __call__(self, prompt: str):
+    def __call__(self, prompt: str):
+        API_URL = "https://api-inference.huggingface.co/models/lukasdrg/clinical_longformer_same_tokens_220k"
+        headers = {"Authorization": "Bearer " + os.environ['HF']}
 
+        # Define the payload for the request
+        payload = {
+            "inputs": prompt  # Adjust this based on your model's input format
+        }
 
-    API_URL = "https://api-inference.huggingface.co/models/lukasdrg/clinical_longformer_same_tokens_220k"
-    headers = {"Authorization": "Bearer "+os.environ['HF']}
-    
-    #def query(payload):
-    generated_text = requests.post(API_URL, headers=headers, json=payload)
-    #	return response.json()
-        
-    #output = query({
-    #	"inputs": "The answer to the universe is <mask>.",
-    #})
+        # Make the request to the API
+        generated_text = requests.post(API_URL, headers=headers, json=payload).json()
 
+        # Extract and return the generated text
+        return generated_text["generated_text"]
 
-    
-    # Replace the following line with your text generation logic
-    #generated_text = f"Generated text based on the prompt: '{prompt}'"
-
-    # Initialize the text generation pipeline
-    #text_generator = pipeline("text-generation") llama mistralai/Mistral-7B-Instruct-v0.1
-    #text_generator = pipeline(model="gpt2")
-    #text_generator = pipeline(model="meta-llama/Llama-2-7b-chat-hf")
-
-    # Generate text based on a prompt
-    #generated_text = text_generator(prompt, max_length=500, num_return_sequences=1, temperature=0.7)
-
-    # Print the generated text
-    #print(generated_text)
-
-
-
-    return generated_text
-
+# Uncomment and customize the following lines based on your text generation needs
+# text_generator = pipeline(model="gpt2")
+# generated_text = text_generator(prompt, max_length=500, num_return_sequences=1, temperature=0.7)
 
+# Print the generated text if needed
+# print(generated_text)