Update actions/actions_llm.py

actions/actions_llm.py

@@ -1,47 +1,47 @@
-# run_search.py
-import os
-import sys
-import openai
+# # run_search.py
+# import os
+# import sys
+# import openai
 
-# Add "/actions" to the sys.path
-actions_path = os.path.abspath("/actions")
-sys.path.insert(0, actions_path)
+# # Add "/actions" to the sys.path
+# actions_path = os.path.abspath("/actions")
+# sys.path.insert(0, actions_path)
 
-# Import search_content.py from /actions folder
-from search_content import main_search
+# # Import search_content.py from /actions folder
+# from search_content import main_search
 
 
-# Import api key from secrets
-secret_value_0 = os.environ.get("openai")
+# # Import api key from secrets
+# secret_value_0 = os.environ.get("openai")
 
-openai.api_key = secret_value_0
-# Provide your OpenAI API key
+# openai.api_key = secret_value_0
+# # Provide your OpenAI API key
 
-def generate_openai_response(query, model_engine="text-davinci-002", max_tokens=124, temperature=0.8):
-    """Generate a response using the OpenAI API."""
-    # Run the main function from search_content.py and store the results in a variable
-    results = main_search(query)
+# def generate_openai_response(query, model_engine="text-davinci-002", max_tokens=124, temperature=0.8):
+#     """Generate a response using the OpenAI API."""
+#     # Run the main function from search_content.py and store the results in a variable
+#     results = main_search(query)
 
-    # Create context from the results
-    context = "".join([f"#{str(i)}" for i in results])[:2014] # Trim the context to 2014 characters - Modify as necessory
-    prompt_template = f"Relevant context: {context}\n\n Answer the question in detail: {query}"
+#     # Create context from the results
+#     context = "".join([f"#{str(i)}" for i in results])[:2014] # Trim the context to 2014 characters - Modify as necessory
+#     prompt_template = f"Relevant context: {context}\n\n Answer the question in detail: {query}"
 
-    # Generate a response using the OpenAI API
-    response = openai.Completion.create(
-        engine=model_engine,
-        prompt=prompt_template,
-        max_tokens=max_tokens,
-        temperature=temperature,
-        n=1,
-        stop=None,
-    )
+#     # Generate a response using the OpenAI API
+#     response = openai.Completion.create(
+#         engine=model_engine,
+#         prompt=prompt_template,
+#         max_tokens=max_tokens,
+#         temperature=temperature,
+#         n=1,
+#         stop=None,
+#     )
 
-    return response.choices[0].text.strip()
+#     return response.choices[0].text.strip()
 
-def main():
-    query = "What is omdena local chapters, how a developer can benifit from it"
-    response = generate_openai_response(query)
-    print(response)
+# def main():
+#     query = "What is omdena local chapters, how a developer can benifit from it"
+#     response = generate_openai_response(query)
+#     print(response)
 
-if __name__ == "__main__":
-    main()
+# if __name__ == "__main__":
+#     main()