Ollama response troubleshooting

this just returns a series of numbers: import os import logging import argparse from dotenv import load_dotenv import chromadb import fitz import praw from sentence_transformers import SentenceTransformer from ollama import generate # Setup logging logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") logger = logging.getLogger(__name__) # Load environment variables load_dotenv() # Initialize tools chroma_client = chromadb.PersistentClient(path=os.getenv("STYLE_DB_PATH", "./style_db")) style_collection = chroma_client.get_or_create_collection("writing_style") model = SentenceTransformer(os.getenv("SENTENCE_MODEL", "all-MiniLM-L6-v2")) reddit = praw.Reddit(client_id=os.getenv("REDDIT_CLIENT_ID"), client_secret=os.getenv("REDDIT_CLIENT_SECRET"), user_agent=os.getenv("REDDIT_USER_AGENT")) # --- Functions --- def process_text_file(filepath): try: with open(filepath, "r", encoding="utf-8") as f: return f.read() except (FileNotFoundError, UnicodeDecodeError) as e: logger.error("Error processing text file %s: %s", filepath, e) return "" def process_pdf_file(filepath): try: doc = fitz.open(filepath) return "\n".join(page.get_text() for page in doc) except Exception as e: logger.error("Error processing PDF %s: %s", filepath, e) return "" def store_writing_style(folder): """Store writing styles from files in a folder into ChromaDB.""" if not os.path.isdir(folder): logger.error("Directory %s does not exist.", folder) return texts, ids = [], [] for file in os.listdir(folder): path = os.path.join(folder, file) text = (process_text_file(path) if file.endswith(".txt") else process_pdf_file(path) if file.endswith(".pdf") else "") if text: texts.append(text) ids.append(file) if texts: embeddings = model.encode(texts).tolist() style_collection.add(documents=texts, embeddings=embeddings, ids=ids) logger.info("Writing style stored successfully.") else: logger.warning("No valid files found in %s.", folder) def fetch_reddit_thread(url): """Fetch title, selftext, and comments from a Reddit thread.""" try: post_id = url.split("/")[-3] submission = reddit.submission(id=post_id) comments = [c.body for c in submission.comments if hasattr(c, "body")] return submission.title + "\n" + submission.selftext, comments except Exception as e: logger.error("Error fetching Reddit thread %s: %s", url, e) return "", [] def expand_ideas(text): """Expand and fact-check a given text.""" try: response = generate(model=os.getenv("OLLAMA_MODEL", "mistral-small:24b-instruct-2501-q8_0"), prompt=f"Expand and fact-check this idea logically: {text}") logger.debug("Raw expand_ideas response: %s", response) # Debug raw output if isinstance(response, dict): return response.get("response", text) # Extract text if it’s a dict return response except Exception as e: logger.error("Error expanding ideas: %s", e) return text def generate_response(prompt, context_text): """Generate a response in a style similar to the context.""" context_embedding = model.encode(context_text).tolist() retrieved = style_collection.query(query_embeddings=[context_embedding], n_results=1) style_doc = retrieved["documents"][0][0] if retrieved.get("documents") else "Default writing style" full_prompt = f"Write a response in this style: {style_doc}\n\n{prompt}" try: response = generate(model=os.getenv("OLLAMA_MODEL", "mistral-small:24b-instruct-2501-q8_0"), prompt=full_prompt) logger.debug("Raw generate_response prompt: %s", full_prompt) # Debug prompt logger.debug("Raw generate_response output: %s", response) # Debug raw output if isinstance(response, dict): return response.get("response", "Failed to generate response.") # Handle dict response return response except Exception as e: logger.error("Error generating response: %s", e) return "Failed to generate response." def main(samples_folder, reddit_url): store_writing_style(samples_folder) thread_title, thread_comments = fetch_reddit_thread(reddit_url) if thread_comments: expanded_comment = expand_ideas(thread_comments[0]) final_response = generate_response(expanded_comment, thread_title) logger.info("Generated Response:\n%s", final_response) else: logger.warning("No comments found in the thread.") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Generate a styled response to a Reddit thread.") parser.add_argument("--samples", default="./writing_samples", help="Folder with writing samples") parser.add_argument("--url", required=True, help="Reddit thread URL") args = parser.parse_args() main(args.samples, args.url)

It looks like the issue could be in the `generate` function from `ollama`. If the output is just a series of numbers, it might be returning raw token IDs instead of the expected text. A few things to check: 1. **Check Ollama's Response Format** Add a debug log inside `expand_ideas` and `generate_response`: ```python logger.debug("Raw Ollama response: %s", response) ``` If the response is a list of numbers, the model might not be returning text properly. 2. **Ensure `generate` Returns Text** The way you handle the response suggests it could be a dictionary. Try forcing it to extract text: ```python if isinstance(response, dict): response_text = response.get("response") if isinstance(response_text, list): # If numbers, force conversion response_text = "".join(chr(int(n)) for n in response_text if isinstance(n, (int, float))) return response_text or "Failed to generate response." ``` If `response` is just a list of numbers, it could mean Ollama is returning token IDs, and the model might need a different decoding step. 3. **Try a Simple Ollama Call** Run this separately to check if Ollama is working correctly: ```python from ollama import generate print(generate(model="mistral-small:24b-instruct-2501-q8_0", prompt="Hello!")) ``` If this also returns numbers, there’s an issue with the model configuration. 4. **Check Ollama Model and Configuration** - Verify that `"mistral-small:24b-instruct-2501-q8_0"` exists in your local Ollama instance. - Try using a different model like `"mistral"` or `"llama2"` to see if the issue persists. - If using a custom quantized model, ensure it supports text output. Try these debugging steps and let me know what you find!

(venv) (3.10.0) danielkliewer@Daniels-MacBook-Pro RedComm01 % python3 main.py --url https://www.reddit.com/r/ArtificialInteligence/comments/1itxoav/ai_in_the_home/ 2025-02-20 11:21:12,201 - INFO - Anonymized telemetry enabled. See https://docs.trychroma.com/telemetry for more information. 2025-02-20 11:21:12,262 - INFO - Use pytorch device_name: mps 2025-02-20 11:21:12,262 - INFO - Load pretrained SentenceTransformer: all-MiniLM-L6-v2 Batches: 100%|███████████████████████████████████████████████████████| 1/1 [00:00<00:00, 1.12it/s] 2025-02-20 11:21:14,654 - WARNING - Insert of existing embedding ID: BrothersKaramazov.txt 2025-02-20 11:21:14,654 - WARNING - Add of existing embedding ID: BrothersKaramazov.txt 2025-02-20 11:21:14,656 - INFO - Writing style stored successfully. 2025-02-20 11:22:39,232 - INFO - HTTP Request: POST http://127.0.0.1:11434/api/generate "HTTP/1.1 200 OK" Batches: 100%|███████████████████████████████████████████████████████| 1/1 [00:00<00:00, 13.73it/s] 2025-02-20 11:23:12,985 - INFO - HTTP Request: POST http://127.0.0.1:11434/api/generate "HTTP/1.1 200 OK" 2025-02-20 11:23:13,030 - ERROR - Error generating response: local variable 'response_text' referenced before assignment 2025-02-20 11:23:13,035 - INFO - Generated Response: Failed to generate response.

The error **"local variable 'response_text' referenced before assignment"** suggests that the `generate` function returned something unexpected (likely `None` or an empty response), causing `response_text` to never be assigned before being used. ### Steps to Debug: 1. **Print or Log Raw Ollama Response** Modify `generate_response` to log the raw output: ```python try: response = generate(model=os.getenv("OLLAMA_MODEL", "mistral-small:24b-instruct-2501-q8_0"), prompt=full_prompt) logger.debug("Raw Ollama response: %s", response) # Log raw response if isinstance(response, dict): response_text = response.get("response") if response_text is None: logger.error("Ollama returned None for response.") return "Failed to generate response." return response_text # Ensure response_text is assigned return response if response else "Failed to generate response." ``` 2. **Check Ollama API Response Manually** Run this directly in your terminal to see if Ollama is responding correctly: ```bash curl -X POST http://127.0.0.1:11434/api/generate -d '{"model": "mistral-small:24b-instruct-2501-q8_0", "prompt": "Hello!"}' ``` If this returns numbers or unexpected output, the model might not be responding in the expected format. 3. **Try a Simpler Ollama Call in Python** Run this separately in Python: ```python from ollama import generate response = generate(model="mistral-small:24b-instruct-2501-q8_0", prompt="Say hello.") print(response) ``` If it returns a list of numbers, Ollama may be giving tokenized output instead of text. 4. **Ensure Your Model is Correctly Installed** Run: ```bash ollama list ``` Ensure `mistral-small:24b-instruct-2501-q8_0` is in the list. If not, install or switch models: ```bash ollama pull mistral ``` ### Likely Causes: - Ollama is returning raw tokenized output instead of plain text. - Your specific model might not be compatible with `generate()`. - A misconfiguration in `OLLAMA_MODEL` in your `.env` file. Try these fixes and let me know what the raw response looks like! 🚀

this just returns a string of numbers: import os import logging import argparse from dotenv import load_dotenv import chromadb import fitz import praw from sentence_transformers import SentenceTransformer from ollama import generate # Setup logging logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(levelname)s - %(message)s") logger = logging.getLogger(__name__) # Load environment variables load_dotenv() # Initialize tools chroma_client = chromadb.PersistentClient(path=os.getenv("STYLE_DB_PATH", "./style_db")) style_collection = chroma_client.get_or_create_collection("writing_style") model = SentenceTransformer(os.getenv("SENTENCE_MODEL", "all-MiniLM-L6-v2")) reddit = praw.Reddit(client_id=os.getenv("REDDIT_CLIENT_ID"), client_secret=os.getenv("REDDIT_CLIENT_SECRET"), user_agent=os.getenv("REDDIT_USER_AGENT")) # --- Functions --- def process_text_file(filepath): try: with open(filepath, "r", encoding="utf-8") as f: return f.read() except (FileNotFoundError, UnicodeDecodeError) as e: logger.error("Error processing text file %s: %s", filepath, e) return "" def process_pdf_file(filepath): try: doc = fitz.open(filepath) return "\n".join(page.get_text() for page in doc) except Exception as e: logger.error("Error processing PDF %s: %s", filepath, e) return "" def store_writing_style(folder): """Store writing styles from files in a folder into ChromaDB.""" if not os.path.isdir(folder): logger.error("Directory %s does not exist.", folder) return texts, ids = [], [] for file in os.listdir(folder): path = os.path.join(folder, file) text = (process_text_file(path) if file.endswith(".txt") else process_pdf_file(path) if file.endswith(".pdf") else "") if text: texts.append(text) ids.append(file) if texts: embeddings = model.encode(texts).tolist() style_collection.add(documents=texts, embeddings=embeddings, ids=ids) logger.info("Writing style stored successfully.") else: logger.warning("No valid files found in %s.", folder) def fetch_reddit_thread(url): """Fetch title, selftext, and comments from a Reddit thread.""" try: post_id = url.split("/")[-3] submission = reddit.submission(id=post_id) comments = [c.body for c in submission.comments if hasattr(c, "body")] return submission.title + "\n" + submission.selftext, comments except Exception as e: logger.error("Error fetching Reddit thread %s: %s", url, e) return "", [] def expand_ideas(text): """Expand and fact-check a given text.""" try: response = generate(model=os.getenv("OLLAMA_MODEL", "mistral-small:24b-instruct-2501-q8_0"), prompt=f"Expand and fact-check this idea logically: {text}") logger.debug("Raw expand_ideas response: %s", response) # Debug raw output if isinstance(response, dict): return response.get("response", text) # Extract text if it’s a dict return response except Exception as e: logger.error("Error expanding ideas: %s", e) return text def generate_response(prompt, context_text): """Generate a response in a style similar to the context.""" context_embedding = model.encode(context_text).tolist() retrieved = style_collection.query(query_embeddings=[context_embedding], n_results=1) style_doc = retrieved["documents"][0][0] if retrieved.get("documents") else "Default writing style" full_prompt = f"Write a response in this style: {style_doc}\n\n{prompt}" try: response = generate(model=os.getenv("OLLAMA_MODEL", "mistral-small:24b-instruct-2501-q8_0"), prompt=full_prompt) logger.debug("Raw generate_response prompt: %s", full_prompt) # Debug prompt logger.debug("Raw generate_response output: %s", response) # Debug raw output if isinstance(response, dict): return response.get("response", "Failed to generate response.") # Handle dict response return response except Exception as e: logger.error("Error generating response: %s", e) return "Failed to generate response." def main(samples_folder, reddit_url): store_writing_style(samples_folder) thread_title, thread_comments = fetch_reddit_thread(reddit_url) if thread_comments: expanded_comment = expand_ideas(thread_comments[0]) final_response = generate_response(expanded_comment, thread_title) logger.info("Generated Response:\n%s", final_response) else: logger.warning("No comments found in the thread.") if __name__ == "__main__": parser = argparse.ArgumentParser(description="Generate a styled response to a Reddit thread.") parser.add_argument("--samples", default="./writing_samples", help="Folder with writing samples") parser.add_argument("--url", required=True, help="Reddit thread URL") args = parser.parse_args() main(args.samples, args.url)

If `generate()` from Ollama is returning a string of numbers, it's likely returning token IDs instead of actual text. This suggests that the model output is either incorrectly formatted or misinterpreted. ### Debugging Steps: #### 1. **Log the Raw Ollama Response** Modify the `generate_response` function to log the entire raw response: ```python def generate_response(prompt, context_text): """Generate a response in a style similar to the context.""" context_embedding = model.encode(context_text).tolist() retrieved = style_collection.query(query_embeddings=[context_embedding], n_results=1) style_doc = retrieved["documents"][0][0] if retrieved.get("documents") else "Default writing style" full_prompt = f"Write a response in this style: {style_doc}\n\n{prompt}" try: response = generate(model=os.getenv("OLLAMA_MODEL", "mistral-small:24b-instruct-2501-q8_0"), prompt=full_prompt) logger.debug("Raw Ollama response: %s", response) # Log raw output if isinstance(response, dict): return response.get("response", "Failed to generate response.") # Handle dict response elif isinstance(response, list): # If it's a list of numbers, try decoding it decoded_text = "".join(chr(int(n)) for n in response if isinstance(n, (int, float))) return decoded_text or "Failed to generate response." return response except Exception as e: logger.error("Error generating response: %s", e) return "Failed to generate response." ``` #### 2. **Run Ollama Manually** Try generating text using Ollama directly in your terminal: ```bash curl -X POST http://127.0.0.1:11434/api/generate -d '{"model": "mistral-small:24b-instruct-2501-q8_0", "prompt": "Hello!"}' ``` If it returns numbers, the model might not be configured properly. #### 3. **Check Your Model** Run: ```bash ollama list ``` If `mistral-small:24b-instruct-2501-q8_0` isn't listed, you may need to download it: ```bash ollama pull mistral ``` Try switching to a different model (`mistral` or `llama2`) and see if the problem persists. #### 4. **Force String Conversion** If the model output is tokenized, try enforcing a text response: ```python if isinstance(response, list): try: return "".join(chr(int(n)) for n in response if isinstance(n, (int, float))) except ValueError: logger.error("Failed to decode response from token IDs.") return "Failed to decode response." ``` #### 5. **Test a Simple Python Script** ```python from ollama import generate response = generate(model="mistral", prompt="Say hello.") print(response) ``` If this also returns numbers, the issue is likely with the model itself. Let me know what the raw response looks like after logging it! 🚀