use ChatGPT API in flask app

apps/file-q-and-a/nextjs-with-flask-server/server/answer_question.py

@@ -41,33 +41,35 @@ def get_answer_from_files(question, session_id, pinecone_index):
  f"[get_answer_from_files] score {score} is below threshold {COSINE_SIM_THRESHOLD} and i is {i}, breaking")
  break
  files_string += file_string
+
+ messages = [
+ {
+ "role": "system",
+ "content": f"Given a question, try to answer it using the content of the file extracts below, and if you cannot answer, or find " \
+ f"a relevant file, just output \"I couldn't find the answer to that question in your files.\".\n\n" \
+ f"If the answer is not contained in the files or if there are no file extracts, respond with \"I couldn't find the answer " \
+ f"to that question in your files.\" If the question is not actually a question, respond with \"That's not a valid question.\"\n\n" \
+ f"In the cases where you can find the answer, first give the answer. Then explain how you found the answer from the source or sources, " \
+ f"and use the exact filenames of the source files you mention. Do not make up the names of any other files other than those mentioned "\
+ f"in the files context. Give the answer in markdown format." \
+ f"Use the following format:\n\nQuestion: <question>\n\nFiles:\n<###\n\"filename 1\"\nfile text>\n<###\n\"filename 2\"\nfile text>...\n\n"\
+ f"Answer: <answer or \"I couldn't find the answer to that question in your files\" or \"That's not a valid question.\">\n\n" \
+ f"Question: {question}\n\n" \
+ f"Files:\n{files_string}\n" \
+ f"Answer:"
+ },
+ ]
 
- prompt = f"Given a question, try to answer it using the content of the file extracts below, and if you cannot answer, or find " \
- f"a relevant file, just output \"I couldn't find the answer to that question in your files.\".\n\n" \
- f"If the answer is not contained in the files or if there are no file extracts, respond with \"I couldn't find the answer " \
- f"to that question in your files.\" If the question is not actually a question, respond with \"That's not a valid question.\"\n\n" \
- f"In the cases where you can find the answer, first give the answer. Then explain how you found the answer from the source or sources, " \
- f"and use the exact filenames of the source files you mention. Do not make up the names of any other files other than those mentioned "\
- f"in the files context. Give the answer in markdown format." \
- f"Use the following format:\n\nQuestion: <question>\n\nFiles:\n<###\n\"filename 1\"\nfile text>\n<###\n\"filename 2\"\nfile text>...\n\n"\
- f"Answer: <answer or \"I couldn't find the answer to that question in your files\" or \"That's not a valid question.\">\n\n" \
- f"Question: {question}\n\n" \
- f"Files:\n{files_string}\n" \
- f"Answer:"
-
- logging.info(f"[get_answer_from_files] prompt: {prompt}")
-
- response = openai.Completion.create(
- prompt=prompt,
- temperature=0,
+ response = openai.ChatCompletion.create(
+ messages=messages,
+ model=GENERATIVE_MODEL,
  max_tokens=1000,
- top_p=1,
- frequency_penalty=0,
- presence_penalty=0,
- engine=GENERATIVE_MODEL,
+ temperature=0,
  )
 
- answer = response.choices[0].text.strip()
+ choices = response["choices"] # type: ignore
+ answer = choices[0].message.content.strip()
+
  logging.info(f"[get_answer_from_files] answer: {answer}")
 
  return jsonify({"answer": answer})

apps/file-q-and-a/nextjs-with-flask-server/server/config.yaml

@@ -8,7 +8,7 @@ SERVER_PORT: "8080"
 
 # ---- OPENAI CONFIG -----
 EMBEDDINGS_MODEL: "text-embedding-ada-002"
-GENERATIVE_MODEL: "text-davinci-003"
+GENERATIVE_MODEL: "gpt-3.5-turbo" # use gpt-4 for better results
 EMBEDDING_DIMENSIONS: 1536
 TEXT_EMBEDDING_CHUNK_SIZE: 200
 # This is the minimum cosine similarity score that a file must have with the search query to be considered relevant

apps/file-q-and-a/nextjs-with-flask-server/server/requirements.txt

@@ -1,11 +1,11 @@
-Flask-Cors==3.0.10
-openai==0.13.0
-pinecone-client==2.0.13
-PyPDF2==2.10.4
-numpy==1.23.2
-scikit-learn==1.1.2
-docx2txt==0.8
+Flask-Cors>=3.0.10
+openai>=0.27.2
+pinecone-client>=2.0.13
+PyPDF2>=2.10.4
+numpy>=1.23.2
+scikit-learn>=1.1.2
+docx2txt>=0.8
 flask>=1.1.4
-jinja2==3.0.1
-PyYAML==6.0
-tiktoken==0.1.2
+jinja2>=3.0.1
+PyYAML>=6.0
+tiktoken>=0.1.2