added spanish folder

Author: madebygps

spanish/chained_calls.py

@@ -0,0 +1,80 @@
+import os
+
+import azure.identity
+import openai
+from dotenv import load_dotenv
+
+# Setup the OpenAI client to use either Azure, OpenAI.com, or Ollama API
+load_dotenv(override=True)
+API_HOST = os.getenv("API_HOST")
+
+if API_HOST == "azure":
+
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+    )
+    client = openai.AzureOpenAI(
+        api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_ad_token_provider=token_provider,
+    )
+    MODEL_NAME = os.environ["AZURE_OPENAI_DEPLOYMENT"]
+
+elif API_HOST == "ollama":
+
+    client = openai.OpenAI(base_url=os.environ["OLLAMA_ENDPOINT"], api_key="nokeyneeded")
+    MODEL_NAME = os.environ["OLLAMA_MODEL"]
+
+elif API_HOST == "github":
+
+    client = openai.OpenAI(base_url="https://models.inference.ai.azure.com", api_key=os.environ["GITHUB_TOKEN"])
+    MODEL_NAME = os.environ["GITHUB_MODEL"]
+
+else:
+
+    client = openai.OpenAI(api_key=os.environ["OPENAI_KEY"])
+    MODEL_NAME = os.environ["OPENAI_MODEL"]
+
+
+response = client.chat.completions.create(
+    model=MODEL_NAME,
+    temperature=0.7,
+    messages=[{"role": "user", "content": "Explica cómo funcionan los LLM en un solo párrafo."}],
+)
+
+explanation = response.choices[0].message.content
+print("Explicación: ", explanation)
+response = client.chat.completions.create(
+    model=MODEL_NAME,
+    temperature=0.7,
+    messages=[
+        {
+            "role": "user",
+            "content": (
+                "Eres un editor. Revisa la explicación y proporciona comentarios detallados sobre claridad, coherencia "
+                "y cautivación (pero no la edites tú mismo):\n\n"
+            )
+            + explanation,
+        }
+    ],
+)
+
+feedback = response.choices[0].message.content
+print("\n\nRetroalimentación: ", feedback)
+
+response = client.chat.completions.create(
+    model=MODEL_NAME,
+    temperature=0.7,
+    messages=[
+        {
+            "role": "user",
+            "content": (
+                "Revisa el artículo utilizando los siguientes comentarios, pero mantenlo a un solo párrafo."
+                f"\nExplicación:\n{explanation}\n\nComentarios:\n{feedback}"
+            ),
+        }
+    ],
+)
+
+final_article = response.choices[0].message.content
+print("\n\nFinal Article: ", final_article)

spanish/chat.py

@@ -0,0 +1,50 @@
+import os
+
+import azure.identity
+import openai
+from dotenv import load_dotenv
+
+# Setup the OpenAI client to use either Azure, OpenAI.com, or Ollama API
+load_dotenv(override=True)
+API_HOST = os.getenv("API_HOST")
+
+if API_HOST == "azure":
+
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+    )
+    client = openai.AzureOpenAI(
+        api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_ad_token_provider=token_provider,
+    )
+    MODEL_NAME = os.environ["AZURE_OPENAI_DEPLOYMENT"]
+
+elif API_HOST == "ollama":
+
+    client = openai.OpenAI(base_url=os.environ["OLLAMA_ENDPOINT"], api_key="nokeyneeded")
+    MODEL_NAME = os.environ["OLLAMA_MODEL"]
+
+elif API_HOST == "github":
+
+    client = openai.OpenAI(base_url="https://models.inference.ai.azure.com", api_key=os.environ["GITHUB_TOKEN"])
+    MODEL_NAME = os.environ["GITHUB_MODEL"]
+
+else:
+
+    client = openai.OpenAI(api_key=os.environ["OPENAI_KEY"])
+    MODEL_NAME = os.environ["OPENAI_MODEL"]
+
+
+response = client.chat.completions.create(
+    model=MODEL_NAME,
+    temperature=0.7,
+    n=1,
+    messages=[
+        {"role": "system", "content": "Eres un asistente útil que hace muchas referencias a gatos y usa emojis."},
+        {"role": "user", "content": "Escribe un haiku sobre un gato hambriento que quiere atún"},
+    ],
+)
+
+print(f"Response from {API_HOST}: \n")
+print(response.choices[0].message.content)

spanish/chat_async.py

@@ -0,0 +1,69 @@
+import asyncio
+import os
+
+import azure.identity
+import openai
+from dotenv import load_dotenv
+
+# Setup the OpenAI client to use either Azure, OpenAI.com, or Ollama API
+load_dotenv(override=True)
+API_HOST = os.getenv("API_HOST")
+
+if API_HOST == "azure":
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+    )
+    client = openai.AsyncAzureOpenAI(
+        api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_ad_token_provider=token_provider,
+    )
+    MODEL_NAME = os.environ["AZURE_OPENAI_DEPLOYMENT"]
+elif API_HOST == "ollama":
+    client = openai.AsyncOpenAI(base_url=os.environ["OLLAMA_ENDPOINT"], api_key="nokeyneeded")
+    MODEL_NAME = os.environ["OLLAMA_MODEL"]
+elif API_HOST == "github":
+    client = openai.AsyncOpenAI(base_url="https://models.inference.ai.azure.com", api_key=os.environ["GITHUB_TOKEN"])
+    MODEL_NAME = os.environ["GITHUB_MODEL"]
+else:
+    client = openai.AsyncOpenAI(api_key=os.environ["OPENAI_KEY"])
+    MODEL_NAME = os.environ["OPENAI_MODEL"]
+
+
+async def generate_response(location):
+    print("Generating response for", location)
+    response = await client.chat.completions.create(
+        model=MODEL_NAME,
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant."},
+            {
+                "role": "user",
+                "content": f"Name a single place I should visit on my trip to {location} and describe in one sentence",
+            },
+        ],
+        temperature=1,
+        max_tokens=400,
+        top_p=0.95,
+        frequency_penalty=0,
+        presence_penalty=0,
+        stop=None,
+    )
+    print("Got response for ", location)
+    return response.choices[0].message.content
+
+
+async def single():
+    print(await generate_response("Tokyo"))
+
+
+async def multiple():
+    answers = await asyncio.gather(
+        generate_response("Tokyo"),
+        generate_response("Berkeley"),
+        generate_response("Singapore"),
+    )
+    for answer in answers:
+        print(answer, "\n")
+
+
+asyncio.run(single())

spanish/chat_history.py

@@ -0,0 +1,55 @@
+import os
+
+import azure.identity
+import openai
+from dotenv import load_dotenv
+
+# Setup the OpenAI client to use either Azure, OpenAI.com, or Ollama API
+load_dotenv(override=True)
+API_HOST = os.getenv("API_HOST")
+
+if API_HOST == "azure":
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+    )
+    client = openai.AzureOpenAI(
+        api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_ad_token_provider=token_provider,
+    )
+    MODEL_NAME = os.environ["AZURE_OPENAI_DEPLOYMENT"]
+elif API_HOST == "ollama":
+    client = openai.OpenAI(base_url=os.environ["OLLAMA_ENDPOINT"], api_key="nokeyneeded")
+    MODEL_NAME = os.environ["OLLAMA_MODEL"]
+elif API_HOST == "github":
+    client = openai.OpenAI(base_url="https://models.inference.ai.azure.com", api_key=os.environ["GITHUB_TOKEN"])
+    MODEL_NAME = os.environ["GITHUB_MODEL"]
+else:
+    client = openai.OpenAI(api_key=os.environ["OPENAI_KEY"])
+    MODEL_NAME = os.environ["OPENAI_MODEL"]
+
+
+messages = [
+    {"role": "system", "content": "I am a teaching assistant helping with Python questions for Berkeley CS 61A."},
+]
+
+while True:
+    question = input("\nYour question: ")
+    print("Sending question...")
+
+    messages.append({"role": "user", "content": question})
+    response = client.chat.completions.create(
+        model=MODEL_NAME,
+        messages=messages,
+        temperature=1,
+        max_tokens=400,
+        top_p=0.95,
+        frequency_penalty=0,
+        presence_penalty=0,
+        stop=None,
+    )
+    bot_response = response.choices[0].message.content
+    messages.append({"role": "assistant", "content": bot_response})
+
+    print("Answer: ")
+    print(bot_response)

spanish/chat_history_stream.py

@@ -0,0 +1,61 @@
+import os
+
+import azure.identity
+import openai
+from dotenv import load_dotenv
+
+# Setup the OpenAI client to use either Azure, OpenAI.com, or Ollama API
+load_dotenv(override=True)
+API_HOST = os.getenv("API_HOST")
+
+if API_HOST == "azure":
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+    )
+    client = openai.AzureOpenAI(
+        api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_ad_token_provider=token_provider,
+    )
+    MODEL_NAME = os.environ["AZURE_OPENAI_DEPLOYMENT"]
+elif API_HOST == "ollama":
+    client = openai.OpenAI(base_url=os.environ["OLLAMA_ENDPOINT"], api_key="nokeyneeded")
+    MODEL_NAME = os.environ["OLLAMA_MODEL"]
+elif API_HOST == "github":
+    client = openai.OpenAI(base_url="https://models.inference.ai.azure.com", api_key=os.environ["GITHUB_TOKEN"])
+    MODEL_NAME = os.environ["GITHUB_MODEL"]
+else:
+    client = openai.OpenAI(api_key=os.environ["OPENAI_KEY"])
+    MODEL_NAME = os.environ["OPENAI_MODEL"]
+
+
+messages = [
+    {"role": "system", "content": "I am a large language model."},
+]
+
+while True:
+    question = input("\nYour question: ")
+    print("Sending question...")
+
+    messages.append({"role": "user", "content": question})
+    response = client.chat.completions.create(
+        model=MODEL_NAME,
+        messages=messages,
+        temperature=1,
+        max_tokens=400,
+        top_p=0.95,
+        frequency_penalty=0,
+        presence_penalty=0,
+        stop=None,
+        stream=True,
+    )
+
+    print("\nAnswer: ")
+    bot_response = ""
+    for event in response:
+        if event.choices and event.choices[0].delta.content:
+            content = event.choices[0].delta.content
+            print(content, end="", flush=True)
+            bot_response += content
+    print("\n")
+    messages.append({"role": "assistant", "content": bot_response})

spanish/chat_langchain.py

@@ -0,0 +1,45 @@
+import os
+
+import azure.identity
+from dotenv import load_dotenv
+from langchain_core.prompts import ChatPromptTemplate
+from langchain_openai import AzureChatOpenAI, ChatOpenAI
+
+# Setup the OpenAI client to use either Azure, OpenAI.com, or Ollama API
+load_dotenv(override=True)
+API_HOST = os.getenv("API_HOST")
+
+if API_HOST == "azure":
+    token_provider = azure.identity.get_bearer_token_provider(
+        azure.identity.DefaultAzureCredential(), "https://cognitiveservices.azure.com/.default"
+    )
+    llm = AzureChatOpenAI(
+        azure_endpoint=os.environ["AZURE_OPENAI_ENDPOINT"],
+        azure_deployment=os.environ["AZURE_OPENAI_DEPLOYMENT"],
+        openai_api_version=os.environ["AZURE_OPENAI_VERSION"],
+        azure_ad_token_provider=token_provider,
+    )
+elif API_HOST == "ollama":
+    llm = ChatOpenAI(
+        model_name=os.environ["OLLAMA_MODEL"],
+        openai_api_base=os.environ["OLLAMA_ENDPOINT"],
+        openai_api_key=os.environ["OPENAI_KEY"],
+    )
+elif API_HOST == "github":
+    llm = ChatOpenAI(
+        model_name=os.environ["GITHUB_MODEL"],
+        openai_api_base="https://models.inference.ai.azure.com",
+        openai_api_key=os.environ["GITHUB_TOKEN"],
+    )
+else:
+    llm = ChatOpenAI(model_name=os.environ["OPENAI_MODEL"], openai_api_key=os.environ["OPENAI_KEY"])
+
+
+prompt = ChatPromptTemplate.from_messages(
+    [("system", "Eres un asistente útil que hace muchas referencias a gatos y usa emojis."), ("user", "{input}")]
+)
+chain = prompt | llm
+response = chain.invoke({"input": "escribe un haiku sobre un gato hambriento que quiere atún"})
+
+print(f"Respuesta de {API_HOST}: \n")
+print(response.content)