| import gradio as gr | |
| import requests | |
| from g4f import Provider, models | |
| from langchain.llms.base import LLM | |
| from langchain_g4f import G4FLLM | |
| url = "https://app.embedchain.ai/api/v1/pipelines/f14b3df8-db63-456c-8a7f-4323b4467271/context/" | |
| def greet(name): | |
| payload = { | |
| "query": f"{name}", | |
| "count": 10 | |
| } | |
| headers = { | |
| 'Authorization': 'Token ec-pbVFWamfNAciPwb18ZwaQkKKUCCBnafko9ydl3Y5', | |
| } | |
| response = requests.request("POST", url, headers=headers, json=payload) | |
| print(name) | |
| c = response.text | |
| llm = LLM = G4FLLM( | |
| model=models.gpt_35_turbo, | |
| provider=Provider.GeekGpt, | |
| ) | |
| res = llm(f""" | |
| Use the following pieces of context to answer the query at the end. | |
| If you don't know the answer, just say that you don't know, don't try to make up an answer. | |
| ${c} | |
| Query: ${name} | |
| Helpful Answer: | |
| system_prompt: | | |
| Act as William Shakespeare. Answer the following questions in the style of William Shakespeare. | |
| """) | |
| print(res) | |
| return res | |
| iface = gr.Interface(fn=greet, inputs="text", outputs="text") | |
| iface.launch() |